by khristin highet, b.psych (hons); m.psych...

Thinking Matters: The Profile of Executive Functioning Associated with Cannabis

Use in Schizophrenia and its Functional Outcome Correlates

by

Khristin Highet, B.Psych (Hons); M.Psych (Clin)

This thesis is submitted in partial fulfilment of the requirements for the degree of

Doctor of Psychology (Clinical)

at Murdoch University

2014

I declare that this thesis is my own account of my research and contains as its main

content work which has not previously been submitted for a degree at any tertiary

institution

.........................................................

Khristin Highet

Abstract

Not only is there a high prevalence of cannabis use in schizophrenia, but long-term or

heavy cannabis users are also considered to demonstrate deficits similar to the cognitive

endophenotypes of the illness itself. The specific neurocognitive domain of executive

function has particular clinical relevance as executive dysfunction has been found to be

significantly associated with the functional outcomes of schizophrenia patients. The

current study sought to examine the pattern of executive functioning in schizophrenia

patients with cannabis use and its functional outcome correlates. Eleven measures

guided by a hierarchical model of executive function were administered to 28

schizophrenic outpatients with cannabis use and 28 matched-controls with a similar

cannabis use history. Premorbid IQ and ‘real-world’ functional outcome were also

assessed. A series of ANCOVA’s revealed that patients with cannabis use demonstrated

poorer performances on a number of executive function measures relative to controls.

However, further analysis indicated that a significantly larger proportion of this sample

showed performances that did not fall in the range of clinical impairment. Using

multiple regression analyses, a retrospective memory and an interference control task

were found to significantly contribute to ‘real-world’ functional outcome. A lack of

clinical impairment in the executive functioning of a representative sample of

schizophrenia patients with cannabis use may be suggestive of differential and subtle

deficits in this subgroup. Retrospective memory and interference control abilities may

also present as potential targets helping to better inform rehabilitation planning efforts

for such patients. Evaluating different subgroups of schizophrenia from a

neurocognitive viewpoint should be an important consideration for treating clinicians

particularly when attempting to achieve more successful functional outcomes.

ii

Acknowledgements

There are a number of individuals and organisations that have contributed to the

development and completion of this project. Firstly, I would like to express my sincere

and utmost gratitude to my chief research supervisor at Murdoch University, Dr

Bethanie Gouldthorp, for her continual mentorship, dedication and confidence in my

study. I also wish to thank my co-supervisors, Dr Allen Gregg Harbaugh and Dr

Corinne Reid, for their collaboration on the project and offering their invaluable

guidance. In addition, I would like to thank Dr Marjorie Collins, a previous faculty

member and supervisor at Murdoch University, and Dr Janet Bryan at the University of

South Australia, for their assistance and support with the original design, methodology

and initial supervision of the project. Without all of their support, direction and

expertise, this study would not have been possible.

I would also like to show my appreciation to the many public health and mental

health organizations, as well as their staff, that have helped contribute to and support the

various activities that were crucial elements in this research project. I am extremely

grateful to the Queen Elizabeth Hospital and Lyell McEwin Hospital Service

(specifically Port Adelaide Mental Health Service and Beaufort Clinic), Flinders

Medical Centre (specifically Southern Mental Health Service and Adaire Clinic), The

Royal Adelaide Hospital, as well as the Mental Illness Fellowship of South Australia

(MIFSA), for their participation in the study through providing not only access to

prospective clinical participant populations, but for also allowing me access to their

facilities and liaison with their mental health treatment teams. In addition, I wish to

thank all of the local mental health community centres and mental health supported

accommodation/hostels which also took part by posting advertisements for the study

within their facilities. An enormous thank you also goes out to the individuals who took

iii

part in study itself by taking the time to undertake comprehensive interviews and

assessments. Without the extensive multi-site involvement and support of these

organisations and individuals, the present research would not have been achievable.

Another important acknowledgement goes to the Department of Psychiatry at

Monash University for providing distance training and support in the administration,

scoring, and interpretation of the Positive and Negative Symptom Scale (PANSS) and to

the Brain Injury Rehabilitation Community Hospital (BIRCH) team in South Australia

for affording me the opportunity to utilise difficult to access neuropsychological test

resources. I would also like to thank Andrew Rothwell, for his time, professional

networks, neuropsychological knowledge and invaluable feedback.

A special expression of gratitude is dedicated to my dear friend, Rachel, for her

tireless and enduring unconditional support and enthusiasm throughout this journey. A

huge thank you also goes out to another dear friend and fellow student, Carlo. Your out-

of-this-world statistical mind astounds me and I cannot thank you enough for not only

the guidance you have provided me in this area, but also the continual motivation, moral

support and understanding since we have met. We finally made it! To my partner Mike,

for all of the amazing home-cooked meals, cups of tea, massages and even practical

assistance in the final editing and cross-checking of my extensive reference list, I

sincerely thank you. Without your patience and encouragement during moments of

doubt, I could not have brought this project to finality.

To my family and friends, I wish to thank you all for your unwavering

accommodation, flexibility, love and support. Your belief in me has truly played a vital

role in the completion of this thesis.

iv

TABLE OF CONTENTS

ABSTRACT.......................................................................................................................

i

ACKNOWLEDGEMENTS...............................................................................................

ii

LIST OF ABBREVIATIONS............................................................................................

vii

LIST OF TABLES.............................................................................................................

x

LIST OF FIGURES...........................................................................................................

xi

CHAPTER

INTRODUCTION............................................................................................................

Part A

The Issue of Comorbid Substance Use and Schizophrenia

The Relationship Between Cannabis use, Schizophrenia and Cognition

1

Cognitive impairments associated with cannabis use

The role of executive function

Executive function deficits associated with cannabis use

Attention

Working memory

Inhibition and impulsivity

Verbal fluency

Decision-making

Cognitive impairments associated with schizophrenia

The importance of executive function to individuals with schizophrenia

Cognitive impairments associated with cannabis use and schizophrenia

Limitations to Previous Research

Part B

The Assessment of Executive Function

Models of executive function

West’s model of executive function

Damasio’s somatic marker hypothesis

The Validity of Tests of Executive Function

‘Traditional’ tests of executive function

Assessing Functional Outcome

The Current Study

Hypotheses

METHOD......................................................................................................................... 70

Participants

Recruitment

Measures

Demographics

Clinical symptoms

Neuropsychometric battery

v

Premorbid intelligence

Executive Function

The temporal organisation of behaviour

Retrospective memory

Prospective memory

Interference control

Inhibition of prepotent responses

Verbal fluency

Emotion-based decision-making

Functional outcome

Procedure

RESULTS......................................................................................................................... 89

Data Screening

Part A

Group Differences in Executive Function

Level of executive function impairment between groups

The Effect of Cannabis-Use Status on the Recovery of Executive Function

The Effect of Length of Abstinence on the Recovery of Executive Function

The Validity of West’s Theoretical Model of Executive Function

Principal Components Analysis

Part B

The Relationship Between Executive Function and Functional Outcome

The predictive ability of executive function measures in predicting functional

outcome ratings

Personal Management (Independent Living Skills Inventory)

Hygiene and Grooming (Independent Living Skills Inventory)

Clothing (Independent Living Skills Inventory)

Basic Skills (Independent Living Skills Inventory)

Interpersonal skills (Independent Living Skills Inventory)

Home Maintenance (Independent Living Skills Inventory)

Money Management (Independent Living Skills Inventory)

Cooking (Independent Living Skills Inventory)

Resource Utilization (Independent Living Skills Inventory)

General Occupational Skills (Independent Living Skills Inventory)

Medication Management (Independent Living Skills Inventory)

Total ILSI Score (Independent Living Skills Inventory)

Moderation effects on executive function measures for functional outcome

Hygiene and Grooming (Independent Living Skills Inventory)

Clothing (Independent Living Skills Inventory)

Interpersonal Skills (Independent Living Skills Inventory)

Home Maintenance (Independent Living Skills Inventory)

Money Management (Independent Living Skills Inventory)

Cooking (Independent Living Skills Inventory)

Resource Utilization (Independent Living Skills Inventory)

Medication Management (Independent Living Skills Inventory)

Total ILSI Score (Independent Living Skills Inventory)

vi

GENERAL DISCUSSION.............................................................................................. 125

Part A


Level of executive function impairment between groups




Part B


Practical Applications of the Findings

Limitations and Future Directions

Conclusions

REFERENCES................................................................................................................. 166

APPENDICES.................................................................................................................. 217

Appendix A: Structured Interview

Appendix B(i): Advertisement for Clinical Participants – Cannabis Users

Appendix B(ii): Advertisement for Clinical Participants – Non-drug Users

Appendix C: Clinical Participant Information Form

Appendix D: Advertisement for Control Participants

Appendix E: Control Participant Information Form

Appendix F: Consent Form for Clinical Participants

Appendix G: Consent Form for Control Participants

Appendix H: Debrief Information

vii

LIST OF ABBREVIATIONS

Analysis of Covariance (ANCOVA)

Behavioral Assessment of the Dysexecutive Syndrome (BADS)

Brief Assessment of Cognition in Schizophrenia (BACS)

Brief Visual Memory Test – Revised (BVMT-R)

Cambridge Neuropsychological Test Automated Battery (CANTAB)

Cannabis Use Disorder (CUD)

Continuous Performance Test (CPT)

Continuous Performance Test – Second Edition (CPT-II)

Controlled Oral Word Association Test (COWAT)

Delis-Kaplan Executive Function System (D-KEFS)

Delta-9-tetrahydrocannabinol (∆9-THC)

Depression Anxiety Stress Scale (DASS)

Diagnostic and Statistical Manual of Mental Disorders – Fourth Edition (DSM-IV)

Digit Symbol Substitution Test (DSST)

Dorsolateral Prefrontal Cortex (DLPFC)

Dysexecutive Questionnaire (DEX)

Event-Related Potentials (ERP’s)

Full Scale Intelligence Quotient (FSIQ)

Functional Magnetic Resonance Imaging (fMRI)

Global Assessment of Functioning (GAF)

Goal Management Training (GMT)

Independent Living Skills Inventory (ILSI)

Instrumental Activities of Daily Living (IADLs)

Intelligence Quotient (IQ)

viii

Iowa Gambling Task (IGT)

Letter-Number Sequencing (LNS)

Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT)

Modified Six Elements (MSE)

National Adult Reading Test – Second Edition (NART-II)

Neurocognitive Enhancement Therapy (NET)

Orbitofrontal Cortex (OFC)

Positive and Negative Syndrome Scale (PANSS)

Positron Emission Tomography (PET)

Prefrontal Cortex (PFC)

Premorbid Adjustment Scale (PAS)

Principal Components Analysis (PCA)

Standard Deviation (SD)

Statistical Package for the Social Sciences (SPSS)

Structured Clinical Interview for the Positive and Negative Syndrome Scale (SCI-

PANSS)

Test de Aprendizaje Verbal Espan ˜a-Complutense (TAVEC)

Test of Grocery Shopping Skills (TGSS)

Trail Making Test (TMT)

UCSD Performance-based Skills Assessment (UPSA)

Ventromedial Prefrontal Cortex (VPFC)

Verbal Intelligence Quotient (VIQ)

Wechsler Adult Intelligence Scale – Fourth Edition (WAIS-IV)

Wechsler Adult Intelligence Scale – Revised (WAIS-R)

Wechsler Adult Intelligence Scale – Third Edition (WAIS-III)

ix

Wechsler Memory Scale – Revised (WMS-R)

Wechsler Memory Scale – Third Edition (WMS-III)

Wisconsin Card Sorting Test (WCST)

x

LIST OF TABLES

Table 1 Sociodemographic characteristics of the sample………………………..

74

Table 2 Results of ANCOVAs of executive function performance for Group

with covariate of premorbid IQ................................................................

92

Table 3 The proportion (n) of each sample group and effect size of proportional

differences in executive function performance across each of the

impairment level categories......................................................................

94


and cannabis-use status with covariate of duration of use.......................

97


and time since cessation categories with covariate of duration of use.....

101

Table 6 Factor loadings based on a Principal Components Analysis utilising

orthogonal (varimax) rotation of 10 executive function measures...........

104

Table 7 Correlations between executive function measures and ILSI sub-scales

and total ILSI score for the schizophrenia group.....................................

108


and total ILSI score for the matched-control group.................................

109


and total ILSI score for the overall sample..............................................

110

Table 10 Regression models for predicting ILSI ratings.........................................

116

xi

LIST OF FIGURES

Figure 1 Moderation effect between groups on Digit Span for Hygiene and

Grooming ratings........................................................................................

117

Figure 2 Moderation effect between groups on Symbol Search for Interpersonal

Skills ratings...............................................................................................

119

Figure 3 Moderation effect between groups on Symbol Search for Cooking

ratings..........................................................................................................

121

Figure 4 Moderation effect between groups on Symbol Search for Resource

Utilization ratings.......................................................................................

122

Figure 5 Moderation effect between groups on Symbol Search for Medication

Management ratings....................................................................................

123

Figure 6 Moderation effect between groups on Symbol Search for Total ILSI

Score...........................................................................................................

125

CANNABIS USE, SCHIZOPHRENIA & EXECUTIVE FUNCTION 1

Thinking Matters: The Profile of Executive Functioning Associated with Cannabis

Use in Schizophrenia and its Functional Outcome Correlates

Substance use and its misuse have been associated with detrimental effects on

cognition (Beatty, Katzung, Moreland, & Nixon, 1995; O’Malley, Adamse, Heaton, &

Gawin, 1993). Cognitive impairment is also considered to be a core feature of the illness

of schizophrenia (Bleuler, 1911, 1950; Green, 1996; Herman, 2004; Hoff, Riordan,

O'Donnell, Morris, & DeLisi, 1992; Kraeplin, 1919, 1971; Saykin, Gur, Gur, Mozley,

Mozley, Resnick, & Stafniak, 1991; Sharma & Antonova, 2003), and executive

dysfunction is found to be particularly implicated (Pantelis, Barnes, Nelson, Tanner,

Weatherley, Owen, & Robbins, 1997; Reichenberg & Harvey, 2007; Shallice, Burgess,

& Frith, 1999). Executive function is considered an important cognitive domain as it has

been strongly linked to the functional outcomes of patients (Greenwood, Landau, &

Wykes, 2005; McClure, Bowie, Patterson, Heaton, Weaver, Anderson, & Harvey, 2007;

Penadés, Boget, Catalán, Bernardo, Gastó, & Salamero 2003; Simon, Giacomini,

Ferrero, & Mohr, 2012; Williams, Whitford, Flynn, Wong, Liddell, Silverstein et al.,

2008). Not only are there high rates of substance abuse in patients with schizophrenia

(Drake, Osher, & Wallach, 1991; Mueser, Yarnold, Levinson, Singh, Bellack, Kee et

al., 1990; Regier, Farmer, Rae, Locke, Keith, Judd, & Goldwin, 1990), but cannabis is

the most commonly used illicit drug among patients with the illness (Barnes, Mutsatsa,

Hutton, Watt, & Joyce, 2006). Impaired cognitive function has also been found in

cannabis abusers alone (Pope, Gruber, & Yurgelun-Todd, 1995). In addition, the

widespread use of cannabis amongst individuals with schizophrenia has been found to

be strongly related to the severity of symptoms, the course of their illness, and poor

outcome (Caspari, 1999; Grech, Van Os, Jones, Lewis, & Murray, 2005; Linszen,

Dingemans, & Lenior, 1994). Therefore, examining the relative differences in the


executive functioning of schizophrenia patients with cannabis use has important clinical

significance when considering treatment targets for comorbid patients and ultimately

more successful functional outcomes. Considering the high rates of cannabis use in this

particular clinical population, both the neuropsychological and functional outcome

correlates of cannabis use and schizophrenia will be specifically examined.

Part A

The Issue of Comorbid Substance Use and Schizophrenia

There is a high prevalence of substance use and misuse in individuals with first-

episode psychosis (Cantwell, Brewin, Glazebrook, Dalkin, Fox, Medley, & Harrison,

1999). In addition, amongst those with psychotic disorders approximately 52% of

patients are not only found to have comorbid diagnoses, but the most common of these

diagnoses is substance use disorder (Stratowski, Maurico, Stoll, Faedda, Mayer,

Kolbrener et al., 1993). Substance abuse is also the most prevalent comorbid condition

associated with the illness of schizophrenia (Cuffel, Heithoff, & Lawson, 1993).

Evidence from community studies suggests that schizophrenia patients in particular, are

more prone to comorbid substance use disorders than the general population and that the

rate of substance abuse has been found to be 4.6 times higher than those without the

illness (Regier et al., 1990). The estimated lifetime prevalence rates of substance abuse

in this clinical population are reported to approximate 50% and the prevalence rates

relating to recent or current substance use range from 20% to 40% (Drake et al., 1991;

Mueser et al., 1990). Not only are substance abuse prevalence rates high in this

population, but substance use in schizophrenia is associated with the greater utilisation

of services as well as higher service costs (Bartels, Teague, Drake, Clark, Bush, &

Noordsy, 1993).


In comparison to other types of psychiatric patients or healthy individuals, it has

been found that schizophrenia patients in particular are more likely to use cannabis than

other drugs of abuse (Degenhardt, Hall, & Lynskey, 2003; Warner, Taylor, Wright,

Sloat, Springett, Arnold, & Weinberg, 1994). With lifetime use reported to be as high as

64.4%, cannabis is the most commonly used illicit drug reported among patients with

schizophrenia (Barnes et al., 2006). More specific to the Australian population,

approximately 25% of a nationally represented sample of individuals with psychotic

disorders in contact with services, were found to have reported a lifetime history of

cannabis abuse (Hall, Teesson, Lynskey, & Degenhardt, 1999). Twenty-four percent of

these patients were reported to be daily or near-daily users. Data from an Australian

survey also showed that cannabis dependence was associated with an 11-fold higher

odds of screening positively for schizophrenia or schizoaffective disorders (Degenhardt

et al., 2003). Green and colleagues (2005) have considered that the variation in

prevalence findings across studies is contributed to by a number of factors. These

include age, the percentage of male representation in studies, the methods used as well

as the clinical experience of researchers in applying diagnostic criteria to individuals

with psychoses, the variation in specificity of diagnostic inclusion criteria, and the

variance in the nature of the interviews used to collect information and the method of

data collection (e.g., self-report versus sample analysis). Such variability in factors

across studies makes prevalence rates more difficult to precisely define. However, the

general consensus suggests that cannabis use and its misuse is a commonality amongst

this particular clinical population.

In a meta-analysis of studies examining cannabis use in schizophrenia occurring

between 1996 and 2008, a median current prevalence rate of 16.0% was reported and a

median lifetime prevalence rate was estimated to be 27.1% (Koskinen, Löhönen,


Koponen, Isohanni, & Miettunen, 2010). It was found that the median rate of cannabis

use disorders (CUD’s) was higher in first-episode patients compared to long-term

patients, with rates for current CUD’s being 28.6% and 22.0% respectively, and lifetime

prevalence rates being 44.4% and 12.2% respectively. The overall findings of the meta-

analysis indicated that approximately 1 in 4 schizophrenia patients in the included

studies had a diagnosis of CUD. The reviewed studies also suggest that countries such

as Australia are an example of a country that evidences a high consumption of cannabis

not only in schizophrenia patients, but also in the general population. Data from the

Low Prevalence arm of the Australian National Survey of Mental Health and Wellbeing

which targeted a sample of 970 individuals diagnosed with psychosis, showed that

26.5% of schizoprenia patients had a comorbid lifetime diagnosis of cannabis abuse or

dependence (Kavanagh, Waghorn, Jenner, Chant, Carr, Evans, et al., 2004). Cannabis

was also found to be the most frequently used drug with 40.9% of the overall sample

using this particular illicit substance. In a review of population-based studies, it has

been reported that cannabis use appears to overall be associated with a two-fold increase

in the relative risk for later schizophrenia or schizophreniform disorders when compared

to the general population (Arseneault, Cannon, Witton, & Murray, 2004).

It is considered that many young people in Australia use cannabis and that this

use usually occurs during late adolescence and early adulthood, which is a period of

development considered to be where the risk of psychoses is at its peak (Hall,

Degenhardt, & Teesson, 2004). Australian survey data suggests that the age of cannabis

use initiation now occurs at an earlier age in young people, compared to the age of

cannabis use onset reported in the 1980’s (Degenhardt, Lynskey, & Hall, 2000). It is

reasonable to consider that if the onset of psychosis symptoms occurs around this time

in development; consequently, so does a diagnosis of the illness. However, research


findings have suggested a more direct link between earlier age of cannabis use onset and

increased risk of the development of psychosis. Arsenault and colleagues (2002)

examined the relationship between cannabis use in adolescence and psychosis in young

adulthood. Results of their study not only demonstrated a significant relationship

between cannabis use by the age of 15 and an increased risk of reported psychotic

symptoms by the age of 26, but also the specificity of effects of this particular substance

on such symptoms. In other words, no significant relationship was found between

psychotic disorders and other drugs of abuse. In addition to this, no relationship was

demonstrated between depression and cannabis use. An interaction between age of

cannabis use onset and psychosis risk was also found, showing earlier cannabis use

onset being significantly related to psychosis. In line with these findings, results from a

meta-analysis indicated that the age of psychoses onset in cannabis users is 2.7 years

earlier in comparison to non-cannabis using individuals (Large, Sharma, Compton,

Slade, & Nielssen, 2011). It has also been shown that earlier initiation of cannabis abuse

is associated with the onset of high-risk symptoms for psychosis at a younger age

(Dragt, Nieman, Becker, van de Fliert, Dingemans, de Haan et al., 2010). In light of the

research evidence, it appears that earlier age of cannabis use onset has a significant

association with earlier age of illness onset. In addition, not only is cannabis use in

schizophrenia highly prevalent around the world, as well as within Australia, but that

the age of cannabis use onset has become younger over the years which places such

individuals at greater risk considering the abovementioned relationships.

Studies investigating the subjective effects of substances based on the self-report

of users, suggest that patients with schizophrenia use drugs such as cannabis to help

self-medicate. Cannabis has been reported to be used in order to relieve negative affect,

‘to increase pleasure’ , ‘to get high’, ‘to relax,’, ‘to satisfy curiosity’, ‘to give more


interests’, as well as to ‘get along with the group’ (Addington & Duchak, 1997;

Goswami, Mattoo, Basu, & Singh, 2004). However, despite the many reported reasons

for using cannabis by individuals with schizophrenia, extensive research has

demonstrated that there are also many detrimental consequences that are associated with

cannabis use in this particular patient population. While it has been proposed that

cannabis may help to relieve negative symptoms (Dixon, Haas, Weiden, Sweeney, &

Frances, 1991; Peralta & Cuesta, 1992), it has been also reported to have a negative

impact on the symptom dimensions of the illness and its course (Linszen et al., 1994).

More specifically, the research examining substance abuse and outcome in

schizophrenia has suggested that cannabis use is associated with an increase in positive

symptoms and significantly more and earlier psychotic relapses (Linszen et al., 1994).

This association is also found to be stronger among heavy cannabis users. Those with a

history of cannabis use have significantly more rehospitalisations, poorer psychosocial

functioning, as well as increased ratings of thought disorder and hostility (Caspari,

1999). Moreover, not only is there is a significant association between increased

cannabis use and increased severity of positive symptoms, but also a more continuous

course of the illness itself (Grech et al., 2005). While substance use in schizophrenia has

been found to be associated with generally fewer negative symptoms, more social

contacts and better functioning in social-leisure areas, issues in relation to interpersonal

relationships and family dynamics are still reported to be associated with cannabis use

in schizophrenia (Salyers & Mueser, 2001). Therefore, given the high rates of

comorbidity between schizophrenia and substance abuse, as well as considering the vast

detrimental clinical effects that can be associated with the misuse of substances in

psychotic disorders, further insight into the implications of substance abuse in

schizophrenia are of particular relevance when considering the management of such


individuals. The following section provides an overview of the literature examining the

individual relationships between cannabis use and cognition, and schizophrenia and

cognition. More specifically, the relationships between cannabis use, schizophrenia and

the neurocognitive domain of executive function. The role of this neurocognitive

domain and its clinical relevance to patients with schizophrenia will then be outlined,

particularly in relation to the functional outcome of such individuals. Lastly, the

challenges associated with the assessment of executive function and the ecological

validity of traditional psychometric measures will be discussed.

The Relationship Between Cannabis Use, Schizophrenia and Cognition

In addition to the many clinical implications associated with cannabis use in

schizophrenia, cognitive functioning has also been found to be significantly affected.

Cognition involves mental processes that enable day-to-day functioning in humans

spanning over a range of personal, social and/or occupational domains (Sharma &

Antonova, 2003). Research has found deleterious cognitive impairments associated with

cannabis abuse (for review, see Pope, Gruber, & Yurgelun-Todd, 1995), as well as

substantial cognitive impairments have also been demonstrated in schizophrenia

patients without a substance abuse history (Hoff et al., 1992; Saykin, Shtasel, Gur,

Kester, Mozley, Stafiniak, & Gur, 1994). Therefore, given the high rates of cannabis use

in schizophrenia and its association with poor outcome, a better understanding of the

relationship between cannabis use, schizophrenia and cognition is warranted. In order to

be able to fully evaluate the clinical significance of the relationship between dual-

diagnosis and cognition, it is important to firstly review the individual relationships

between cannabis use, schizophrenia and cognition separately.

Cognitive impairments associated with cannabis use. Cannabis consumption

in otherwise healthy subjects has been demonstrated to be accompanied by cognitive


deficits similar to the cognitive endophenotypes found in schizophrenia patients (for

review, see Solowij & Michie, 2007). It has been found that early onset, higher dose,

higher frequency of use and duration of use are considered as risk factors when

examining the relationship between patterns of cannabis use and the extent of cognitive

impairment (Bolla, Brown, Eldreth, Tate, & Cadet, 2002; Harvey, Sellman, Porter, &

Frampton, 2007; Pope, Gruber, Hudson, Cohane, Huestis, & Yurgelun-Todd, 2003).

Evidence has also suggested that the cognitive impairments associated with cannabis

use not only persist beyond the acute intoxication state, but that worse cognitive

performance has been found to be specifically associated with cumulative years of use

(Solowij, Stephens, Roffman, Babor, Kadden, Miller et al., 2002). While there has been

an increase in the empirical evidence suggesting that the deficits demonstrated in

cannabis users have been shown to persist beyond the acute effects of intoxication, the

findings related to the recovery of such functions following cannabis use abstinence is

inconsistent (Solowij & Battisti, 2008; Solowij & Michie, 2007).

Frontal lobe function, particularly prefrontal, superiorfrontal and central areas,

have been found to be negatively affected by long-term cannabis use (Lundqvist,

Jönsson, & Warkentin, 2001). The frontal lobe of the brain is a structure thought to be

associated with attentional abilities, the facilitation of memory functions and retrieval

strategies, and the support of higher-level cognitive functions (Lezak, Howieson, &

Loring, 2004). Such higher-level cognitive abilities, otherwise known as the executive

functions, are considered to be crucial in decision-making processes where one is faced

with novel or unfamiliar situations (Crean, Crane, & Mason, 2011). Patients with

prefrontal cortex (PFC) lesions in the ventromedial sector and individuals with

substance dependence have been found to show similar behaviours where they not only

have reduced awareness of their difficulties, but also demonstrate a tendency to choose


a course of action that presents themselves with rewards of an immediate nature and

ignore the risk of future negative consequences (Bechara, 2001; Bechara, Dolan,

Denburg, Hindes, Anderson, & Nathan, 2001; DiClemente, 1993). In a study conducted

by Bechara and Martin (2004), it was found that individuals with substance dependence

who demonstrated decision-making impairments also showed severe deficits in working

memory performance. However, the pattern of results found were suggestive of deficits

in the ‘executive’ process of working memory (i.e., switching and response inhibition

components) in comparison to the memory storage aspect of the task. While it was

found that overall as a group, individuals with substance dependence showed poor

performance on measures of decision-making and working memory, not every subject

demonstrated impaired performances. The authors concluded that the different pattern

of deficits across individuals with substance dependence may be a result of such

individuals demonstrating any one, or a combination, of a number of different

mechanisms which are thought to be involved in decision-making processes and

inhibitory control supported by the PFC region. As executive dysfunction can result in

self-monitoring difficulties, reduced ability to modify or control inappropriate

behaviours, as well as impact rational decision-making processes, it is also considered

that executive dysfunction may result in the perpetuation of addictive behaviour (Bolla,

Cadet, & London, 1998). It is postulated that such decision-making deficits could be

potentially attributable to the cumulative effects of heavy substance use, but may also

result in the continuation of substance use and unsuccessful abstinence attempts (Bolla,

Eldreth, London, Kiehl, Mouratidis, Contoreggi et al., 2003; Paulus, Tapert, &

Schuckit, 2005). In addition, reduced decision-making abilities may make an individual

more susceptible to the commencement of substance use and further, becoming a

substance abuser. Therefore, it appears that executive functions may play an important


role in the engagement as well as maintenance of substance abuse; consequently, the

following discussion will specifically focus on the effects of cannabis use in relation to

this particular neurocognitive domain.

The role of executive function. Due to previous neuroanatomical research

findings suggesting associations between impairments in executive function and frontal

lobe pathology, the use of the term ‘executive function’ was traditionally equated with

the term ‘frontal lobe function’ (Benton & Hamsher, 1976; Fuster, 1989; Katz, Tadmor,

Felzen, & Hartman-Maeir, 2007; Luria, 1973; Milner, 1963; Roberts, Robbins, &

Weiskrantz, 1998; Stuss & Benson,1986). However, the use of the functional definition

of ‘executive function(s)’ over the more anatomical-based definition of ‘frontal

functions’ became increasingly more emphasised over the years. This was largely due to

the number of regions in the brain that were postulated to be implicated in such

cognitive processes which included those falling outside of the frontal lobes alone

(Baddeley, 1996). Executive functions are conceptualised as higher-order cognitive

processes which are considered pertinent to forming intentions, planning and

organisation, the translation of a plan into purposive action, and self-monitoring and

self-regulation (Lezak et al., 2004). The term ‘executive function’ is an umbrella term

that has been used to describe, ‘capacities that enable a person to engage successfully in

independent, purposive and self-serving behaviour’ (Lezak et al., 2004, p. 35).

While it is agreed that executive functions are considered to be complex, as well

as highly important to adaptive human behaviour, there are an array of definitions for

this particular neurocognitive construct (Jurado & Rosselli, 2007; Lyon & Krasnegor,

2001). Executive function is considered to be a multidimensional construct referring to

a number of ‘higher-order cognitive processes including initiation, planning, hypothesis

generation, cognitive flexibility, decision making, regulation, judgement, feedback


utilization, and self-perception that are necessary for effective and contextually

appropriate behavior’ (Spreen & Strauss, 1998, p. 171). Such functions have been

considered to be supported by the dorsolateral prefrontal cortex (DLPFC) and referred

to as the ‘cold’ components of executive functioning due to their corresponding

processes involving relatively ‘mechanistic’ or logically-driven abilities (Grafman &

Litvan, 1999). Those executive functions thought to be supported by the ventromedial

prefrontal cortex (VPFC) are considered to reflect those cognitive processes that are

more emotionally-driven. These include the experience of reward and punishment,

decision-making processes related to interpersonal and social behaviour, and the

interpretation of complex emotions, and are often referred to as ‘hot’ components of

executive functioning (Bechara, Damasio, Damasio, & Lee, 1999; Bechara, Tranel,

Damasio, & Damasio, 1996; Damasio, 1995; Grafman & Litvan, 1999).

Executive functions are also thought to act as those cognitive processes which

are considered vital for success in the ‘Instrumental Activities of Daily Living’ (IADLs)

(Chevignard, Taillefer, Picq, Poncet, Noulhiane, & Pradat-Diel, 2008; Shallice &

Burgess, 1991). Such activities may involve a range of domestic and community

activities, occupational activities, interpersonal and social behaviours, and the temporal

organisation of daily activities as a whole (Chevignard et al., 2008). Research

investigating the effects of executive function impairments have found that such deficits

may have a negative impact on an individual’s activities of everyday life such as ‘real-

world’ planning abilities (e.g., financial management), the ability to attend to

educational and work pursuits, independent living, or even the development and/or

maintenance of social relationships and understanding of social rules (Goel, Grafman,

Tajik, Gana, & Danto, 1997; Grafman, Schwab, Warden, Pridgen, Brown, & Salazar,

1996; Green, 1996; Green, Kern, Braff, & Mintz, 2000).


Executive function deficits associated with cannabis use. When considering the

more long-term effects of cannabis use in the literature, tasks that employ executive

control abilities have at least in some way been shown to be affected (Grant, Gonzalez,

Carey, Natarajan, & Wolfson, 2003; Pope, Gruber, Hudson, Huestis, & Yurgelun-Todd,

2001). The impact of cannabis use on executive functioning can be evaluated by its

acute, residual and long-term effects. However, it is acknowledged that any

neurocognitive deficits observed following a relatively minimal period of abstinence

may be associated with drug residues in the brain or even the effects of drug

withdrawal, therefore it is considered that the interpretation of such results would be

difficult. With this in mind, the residual (7 hours to 20 days after last use) and longer-

term (over 21 days after last use) effects are of greater interest and will be the focus of

the following section. In addition, studies examining adolescent subjects were not

included in the following review due to the consideration that the effects of cumulative

cannabis use/longer lifetime-use potentially not being fully achieved in such samples. In

relation to the specific effects of cannabis use on executive processes, the areas of

attentional processing, working memory, inhibition and impulsivity, verbal fluency and

decision-making will be discussed.

Attention. In relation to attentional abilities, no significant differences were

found between current heavy cannabis users (i.e., those that used at least 5000 times in

their lifetime and were daily users), individuals with a history of past heavy use (i.e.,

those that used at least 5000 times in their lifetime, but less than 12 times in the last 3

months), and control subjects with limited cannabis use experience (Pope et al., 2001,

2002). Subjects were assessed following 0, 1, 7 and 28 days of abstinence. Jager and

colleagues (2006) not only assessed the cognitive performance of moderate cannabis

users (i.e., median lifetime use of 1300 joints and median last year use of 350 joints) in


the area of attention, but also measured alterations of brain activity with functional

Magnetic Resonance Imaging (fMRI) after one week of abstinence. Findings of the

study were similar to Pope and colleagues’ results showing no significant differences in

task performance compared to controls and, in addition to this, no significant

differences in associated brain activity. Grant and colleagues (2012) examined the

cognitive performances between cannabis users (with a 3.1 ± 2.2 times per week mean

frequency of use within the past 12 months; n= 16) and controls (n=214). However, the

authors did not impose a specific abstinence period as they wished to evaluate cognition

under normal circumstances in day-to-day life. Findings from their study also indicated

that there were no significant differences between groups in performance on sustained

attention (as measured by the Rapid Visual Information Processing task from the

Cambridge Neuropsychological Test Automated Battery (CANTAB; Sahakian & Owen,

1992). Conversely, Solowij and colleagues (1991) found that long-term cannabis users

(with a mean of 11.2 years of use, mean level of use of 4.77 days a week, and a mean

consumption of 766 mg per week) demonstrated significantly poorer performance than

controls on a selective attention task as well as a reduced ability to filter out irrelevant

information, following a minimum 12-hour period of abstinence. In a later study, it was

found that heavy cannabis users (i.e., those that used more than or equal to 3 days per

week) had slower reaction times during cognitive tasks compared to not only controls,

but to light cannabis users (i.e., those that used less than or equal to 2 days per week)

following a minimum of 24 hours abstinence (Solowij, Michie, & Fox, 1995). Findings

from the study also indicated that the ability for cannabis users to filter out irrelevant

information was progressively impaired as a function of duration of use. In addition,

both long-term (with a mean of 23.9 years of regular use) and short-term cannabis (with

a mean of 10.2 years of regular use) users were found to make more errors on a speed of


comprehension task following a minimum 12-hour period of abstinence in comparison

to controls (Solowij et al., 2002). Slower processing rates were also demonstrated in

long-term cannabis users compared to short-term cannabis users (Solowij et al., 2002).

Verdejo-García et al. (2013) examined whether genetic polymorphisms moderated the

effects of cannabis use on executive function. The study included 86 cannabis users

(with daily use of cannabis of >7 joints per week and for a minimum duration of 3

years) and 58 non-drug using controls. Both groups were genotyped and matched for

genetic makeup, sex, age, education and Intelligence Quotient (IQ). The authors found

no significant differences between users and controls in sustained attention performance

(as measured by the Rapid Visual Information Processing test; CANTAB) following a

72-hour abstinence period. Further findings from the study suggested that certain

genotypes of the COMT and SLC6A4 genes moderated the impact of cannabis use on

executive functions. More specifically, results showed that cannabis users carrying the

COMT val/val genotype exhibited lower accuracy of sustained attention than non-users

of the same genotype. Research into the long-term effects of cannabis use on

attentional abilities has also produced mixed findings. It was found that heavy cannabis

users (with a mean consumption of 93.9 joints per week, a mean level of use of 7 days a

week, and a mean of 5.3 years duration of use) who were abstinent for a period of

approximately 28 days were found to demonstrate deficits in reaction time (Bolla et al.,

2002). In addition, results from Solowij’s (1995) study found significant deficits in the

ability to process irrelevant information in ex-cannabis users who were abstinent from a

minimum of 6 weeks to an average of 2 years. However, in a study examining

monozygotic twins, no impairments in attention or concentration were reported in

cannabis-using twins who were abstinent for a minimum period of 1 year, in


comparison to non-using co-twins (Lyons, Bar, Panizzon, Toomey, Eisen, Xian, &

Tsuang, 2004).

Working memory. Findings from Scholes & Martin-Iverson’s (2010) study

showed that cannabis users (n=36; with a median total duration of cannabis use of 10

years and a median of 2 usage times per day) showed no significant differences from

controls (n=35) on Letter-Number Sequencing (LNS; Wechsler Memory Scales – Third

Edition (WMS-III); Wechsler, 1997), Spatial Span (WMS-III; Wechsler, 1997), and

overall working memory (i.e., the summed score of LNS and Spatial Span). Cannabis

users were instructed to not alter their pattern of cannabis use on the day of testing and

therefore a set abstinence period was not imposed. This was considered by the authors

to reduce the likelihood of abstinence syndrome. Of the cannabis users, 21 were

daily/nearly daily users; 12 were weekly users; one was a monthly user and two used

cannabis less than monthly. Sixteen of these users reported using other drugs in the last

month. A similar pattern of results were also found regarding spatial working memory

performance (measured by the Spatial Working Memory task from the CANTAB) in

Grant and colleagues’ (2012) study. However, results also showed that cannabis users

demonstrated significant impairments on the One Touch Stockings of Cambridge Task

(from the CANTAB) relative to controls. While the test developers indicate that

working memory is assessed by this task, spatial planning abilities are also tapped into

by this measure. In addition, Gruber et al. (2012) found no significant differences

between controls and marijuana users on tasks of visuospatial construction and working

memory (measured by the Rey-Osterrieth Complex Figure test: for test description, see

Lezak et al., 2004), as well as attention and working memory (measured by Digit Span).

No significant differences in working memory (measured by Digit Span) were found

between cannabis users (categorised as heavy and light) and a control group following a

http://www.archimedes-lab.org/Rey_test.html


minimum period of 19 hours abstinence (Pope & Yurgelun-Todd, 1996). Additional

studies have replicated similar findings when assessing working memory with

auditory/verbal tasks including computation span, omitted numbers, and a spatial task

(e.g., a modified Sternberg item recognition task) (Fisk & Montgomery, 2008; Jager et

al., 2006; Solowij et al., 2002). In a fMRI study, it was found that cannabis users

demonstrated greater and more distributed brain activation during the performance of a

spatial working memory task (measured by a perception task and a short-delay response

task) in comparison to control subjects following 6-36 hours after last cannabis use

(Kanayama, Rogowska, Pope, Gruber, & Yurgelun-Todd, 2004). Thames and

colleagues (2014) examined neurocognitive performances across recent users (n=68;

those who reported use in the last 4 weeks), past users (n=41; those who used more than

28 days prior to testing) and non-users (n=49). Results indicated that recent users

performed more poorly than past users and non-users in attention/working memory (a

composite score of performance on the Trail Making Test – Part A, Reitan, 1958;

Stroop Test [colour and word conditions], Golden, 1978; and the Letter-Number

Sequencing test from the Wechsler Adult Intelligence Scale – Fourth Edition (WAIS-

IV); Wechsler, 2008). However, it is noted that the criteria of what constituted a user

regarding frequency, amount and duration of use was not reported by the authors.

Inhibition and impulsivity. Results from Pope and Yurgelun-Todd’s (1996)

study indicated that heavy cannabis users (with a median use of 29 days in the past 30

days) demonstrated significantly greater perseverations on a card sorting measure (i.e.,

Wisconsin Card Sorting Task (WCST); Heaton, 1981), in comparison to light users

(with a median use of 2 days in the past 30 days) following a minimum period of 19

hours of abstinence. Solowij and colleagues (2002) found that performance differences

between task trials on the Stroop test suggested that cannabis users had greater


vulnerability to task complexity and increased demands following a minimum of 12

hours abstinence relative to controls. In addition, there was also an inverse relationship

between the number of task items completed and duration of cannabis use. In the same

study, there were no significant differences between groups on WCST performance.

Gruber et al. (2012) examined the relationship between age of onset of marijuana use

and executive function performance in 34 chronic, heavy marijuana smokers (with a

mean frequency of 19.24 ±19.58 smokes per week; mean amount of 10.86 ± 14.95

grams per week; and mean duration of 7.24 ± 7.30 years) and 28 non-using controls

following a minimum 12-hour abstinence period. From the results of the study,

significantly poorer performances were found on the WCST, as well as in both the

Word Reading and Interference condition of the Stroop test. Findings also suggested

that early onset marijuana users were significantly more impaired than late onset users

on both measures. However, Battisti et al. (2010) conducted a neurophysiological

measure study using event-related potentials (ERP’s) to examine discrete cognitive

events. Event-related brain potentials to neutral, congruent, and incongruent trials were

compared between 21 cannabis users (with a mean of 16.4 years of nearly daily use) and

19 non-using controls following at least a 12 hour abstinence period. Results of the

study indicated that chronic cannabis use produced changes in accuracy and brain

activity associated with performance on the Stroop task during the unintoxicated state. It

was shown that users displayed increased errors on colour-incongruent trials (e.g.,

“RED” printed in blue ink) suggesting more susceptibility to the colour-naming

interference effect. However, no significant differences were found between users and

controls on colour-congruent (“RED” printed in red ink) or neutral trials (e.g., “*****”

printed in green ink). Further, earlier age of cannabis use onset was found to

significantly predict accuracy on incongruent trials. Results imply that users may have


difficulty suppressing more automatic responses. Attentional inhibition dysfunction

(assessed by a visuospatial negative priming task) was demonstrated in current cannabis

users in comparison to past cannabis users and controls following a minimum 48-hour

abstinence period in a study conducted by Skosnik, Spatz-Glenn, and Park (2001). The

authors proposed that as current cannabis users had significantly faster reactions times

when performing a simple detection task, the demonstrated deficit was not the result of

visual inattention, but instead reflective of increased disinhibition. Poorer performances

demonstrated by cannabis users have also been reported in other studies using the

WCST (Bolla et al., 2002; Pope, Yurgelun, & Todd, 1996; Pope et al., 2001, 2002;

2003). Conversely, findings from Lyons and colleagues’ (2004) study did not indicate

reduced performance on the WCST by users. Other studies have also reported no effects

on inhibition or impulsivity to be associated with cannabis use (Gruber & Yurgelun-

Todd, 2005; Hermann, Sartorius, Welzel, Walter, Skopp, Ende, & Mann, 2007;

Whitlow, Liguori, Brooke Livengood, Hart, Mussat-Whitlow, Lamborn et al., 2004).

Additionally, when inhibition was measured using the Stroop test, no significant

differences were reported between cannabis users and controls (Lyons et al., 2004; Pope

& Yurgelun-Todd, 1996; Pope et al., 2001, 2002, 2003). It is possible that differences in

results could possibly be due to the WCST and Stroop test measuring different

underlying executive function subdomains. While both have been used as measure of

inhibition and impulsivity, the WCST is also thought to be a measure of cognitive

flexibility and abstraction ability (Milner, 1963), whereas the Stroop test also measures

sustained attention with or without interference (MaCleod, 1991). In Verdejo-García et

al.’s (2013) study no differences were found between users and controls in

monitoring/shifting (as measured by the CANTAB Intradimensional/Extradimensional


set-shifting task). However, it was found that users carrying the COMT val allele

committed more monitoring/shifting errors than users carrying the met/met genotype.

Verbal fluency. While verbal fluency tasks do not traditionally fall into the

category of being solely a frontal lobe executive function task due to also tapping into

functions of the temporal lobe (Raskin & Rearick, 1996), verbal fluency tasks are

thought to load heavily on executive function (Rabbitt, 1997). It is also considered a

well established measure of executive functioning and has been commonly used to

assess the integrity of the pre-frontal region (Kolb & Whishaw, 1985; Parkin & Java,

1999; Warkentin & Passant, 1997). In addition, due to the tendency of verbal fluency

measures heavily relying on processes involving strategic searching, such tests are

deemed to be some of the most sensitive and best validated measures of dysfunction in

the frontal lobe (Benton, 1968; Bryan & Luszcz, 2000; Lezak, 1995; Parker &

Crawford, 1992; Stuss & Benson, 1986). Following a minimum 12-hour abstinence

period, Gruber et al. (2012) found no significant differences between marijuana users

and controls in verbal fluency performance (as measured by the Controlled Oral Word

Association Test (COWAT; Benton, Hamsher, & Sivan, 1983). In Pope and Yurgelun-

Todd’s (1996) study, no significant differences were found between light and heavy

cannabis users on verbal fluency following a minimum 19-hour abstinence period.

However, a significant interaction was found between Verbal Intelligence Quotient

(VIQ) and cannabis-use status indicating that out of those subjects with the lowest

VIQ’s, the heavy users demonstrated reduced verbal fluency in comparison to light

users. In addition, those subjects with average to high VIQ scores demonstrated no

verbal fluency deficits. Findings from Fisk and Montgomery’s (2008) study showed no

significant differences in verbal fluency (both letter and semantic) between cannabis

users and controls following a minimum of 24 hours abstinence. Both recent (i.e., had


used in the last 7 days) and abstinent cannabis users (i.e., had not used in the last 7 days)

were found to demonstrate deficits in verbal fluency (phonemic verbal fluency)

following a minimum 24-hour abstinence period compared to controls (McHale & Hunt,

2008). Pope and colleagues (2003) reported a significant difference between groups in

verbal fluency (COWAT - FAS) following a minimum of 28 days abstinence. In this

study, the cannabis users were grouped according to age of onset (early and late).

Cannabis users with early age of onset (i.e., those who commenced use before 17 years

of age) were found to demonstrate significant verbal fluency deficits compared to the

control group. However, the researchers’ earlier studies (2001, 2002) found no

significant differences on this domain. Results from the more recent study suggest that

age of onset may be an influencing factor (Pope et al., 2003).

Decision-making. In a study conducted by Whitlow and colleagues (2004) long-

term, heavy cannabis users (i.e., those that were daily users for at least 25 out of 30 days

and for at least 5 years duration) were found to demonstrate impaired performance on

the Iowa Gambling Task (IGT; Bechara, Damasio, Damasio, & Anderson, 1994), in

comparison to controls (i.e., those who had a minimal use of 1-50 lifetime uses and did

not use in the last year). Subjects in the user group were required to abstain for a

minimum of 12 hours prior to testing. Findings from the study suggest that long-term,

heavy cannabis users made decisions which led to larger immediate gains, but more

losses overall in comparison to individuals with minimum cannabis use in their history.

The authors concluded that long-term, heavy cannabis users may have a reduced ability

to effectively weigh up costs and rewards and that this deficit may contribute to the

continuation of their drug-use. However, it is also acknowledged by the researchers that

such deficits may be the consequence of cannabis use, or may alternatively reflect the

presence of pre-existing differences regarding genetics or behaviour. Additional


findings from Grant et al.’s (2012) study also indicated significant impairments in

decision-making performance (as measured by the Cambridge Gamble Task from the

CANTAB) in cannabis users. Bolla et al. (2005) examined brain activity using Positron

Emission Tomography (PET) during the administration of the IGT. Not only did the

authors find similar results where decision-making deficits were demonstrated in

cannabis users (i.e., those who currently smoked at least 4 days a week, for at least 2

years duration) following a 25-day abstinent period, but cannabis users also showed

different patterns of brain activation than non-users. More specifically, cannabis users

showed less activation in the right dorsolateral prefrontal cortex (DLPFC) and right

lateral orbitofrontal cortex (OFC), in addition to greater brain activation in the left

cerebellum. One study, examined the relationship between cocaine and cannabis users

(i.e., those that used at least 4 times a week, for at least 2 years duration) and IGT

learning (Verdejo-García, Benbrook, Funderburk, David, Cadet, & Bolla, 2007). Results

suggested that while both cocaine and cannabis users demonstrated worse performance

on the total IGT net score than controls, the pattern of learning indicated that the

cannabis-using group showed less learning than the cocaine-using group. Dose-related

measures of cannabis use (i.e., joints per week), were also found to predict IGT

performance where the heavier the use, the lower the performance demonstrated.

Contrastingly, Quednow and colleagues (2007) did not find IGT decision-making

deficits in chronic cannabis users who had been abstinent for a mean of 7 days. The

chronic cannabis users in this study (with a mean consumption of 3.89 times a week and

6.55 years duration of use) did report using other drugs of abuse in their history, but

were included in the study as long as they were deemed to not have substantially used

amphetamine derivatives like MDMA or have substantial previous use of cocaine. In

Verdejo-García et al.’s (2013) study, a significant difference was found between groups


on the IGT (block 3), which is considered to index the learning phase of the task. In

addition, users carrying the 5-HTTLPR s/s genotype had worse decision-making skills

than s/s non-users.

The abovementioned studies indicate that the cognitive impairments associated

with cannabis use are demonstrated across a range of important executive function

processes. However, differences in findings across studies could be attributed to

variability in sample characteristics, abstinence periods and differences in frequency,

severity/quantity, or duration of use/cumulative amount. In addition, results indicating

no significant differences suggest that while some of the measures mentioned above

may be sensitive enough to tap into the neurocognitive domain of interest, they may not

support the specificity of the measures to solely detect deficits in that specific domain.

In other words, such measures may not serve as specific markers for deficits in the

associated domain in question. In addition, differences in the actual tests used to assess

specific domains may have impacted the consistency of the findings. It would also not

be surprising that multiple brain regions and connections would be involved in a

neurocognitive process as complex as executive function and thus, isolating the domain

by a single psychometric task presents another concern. While the findings suggest that

some executive function impairments related to cannabis use have been found to

improve following the discontinuation of cannabis use (Pope et al., 2001, 2002, 2003),

deficits have been also shown to persist following cannabis use cessation (Bolla et al.,

2005). It is also proposed that the specific factors of age of cannabis use onset, duration

and amount of cannabis use may play a part in the manifestation of differing executive

functioning impairments (Grant et al., 2003; Pope et al., 2003; Solowij, 1995; Solowij et

al., 2002). Considering the differences in findings across studies, it is thought that the

more precise and adequate assessment of executive function abilities, as well as of such


cannabis use parameters, is crucial in order to ensure that the measures used are

sensitive enough to detect impairment if it indeed exists.

Cognitive impairments associated with schizophrenia. In 1896, the first

clinical account of schizophrenia was made by Kraepelin and was termed ‘dementia

praecox’ (Kraepelin, 1919, 1971, cited in Sharma & Antonova, 2003). Cognitive

impairment was emphasized to be a core part of the illness and that such impairments

comprised of deficits in attention, problem-solving, motivation, learning and memory

(Sharma & Antonova, 2003). In 1911, Bleuler used the term ‘schizophrenia’ and also

conceived cognitive impairment as being a fundamental aspect of the illness (Bleuler,

1911, 1950, cited in Sharma & Antonova, 2003). Through extensive research over the

years, it is now universally recognised that cognitive impairment is a central and

enduring feature of the illness and that such deficits have greater predictive ability of

functional outcome than clinical symptoms (Green, 1996). More contemporary

understandings of the illness indicate that cognitive impairments are more specifically

demonstrated in the domains of sustained attention, language skills, executive functions,

verbal learning and memory (Bilder, Lipschutz-Broch, Reiter, Geisler, Mayerhoff, &

Lieberman, 1992; Riley, McGovern, Mockler, Doku, O’Ceallaigh, Fannon, & Sharma,

2000).

The cognitive impairment associated with schizophrenia is not thought to be the

result of symptomatology, nor the effects of antipsychotic medication (Green, 2006).

Research has suggested that the cognitive impairments associated with schizophrenia

are present prior to the onset of clinical symptomatology and show relative stability

across the course of the illness (Finkelstein, Cannon, Gur, Gur, & Moberg, 1997; Gold,

2004). Cognitive dysfunction in schizophrenia has also been found to be related to, but

distinct from, negative symptoms (Harvey, Lombardi, Leibman, White, Parrella,

http://0-www.sciencedirect.com.prospero.murdoch.edu.au/science/article/pii/S0920996499001772


Powchik, & Davidson, 1996; Hughes, Kumari, Soni, Das, Binneman, Drozd, & Sharma,

2003). Impairments have also been observed to already be present in first-episode

patients with schizophrenia (Hutton, Puri, Duncan, Robbins, Barnes, & Joyce, 1998). In

addition, cognitive deficits have not only been found in patients with schizophrenia

prior to illness onset, but there is evidence of similar deficits in their first degree

relatives (Cornblatt, Obuchowski, Schnur, & O’Brien, 1998). The cognitive

impairments found in first-episode patients with schizophrenia are also considered to be

important predictors of long-term outcome (Green, Kern, & Heaton, 2004).

A wide range of cognitive impairments have been associated with the illness of

schizophrenia. While deficits in global performance have been described (Braff, Heaton,

Kuck, Cullum, Moranville, Grant, & Zisook, 1991), as well as broad deficits spanning

across a number of cognitive domains (Heinrichs & Zakzanis, 1998), other findings

have shown selective cognitive deficits which are deemed over-and-above general

cognitive impairment (Saykin et al., 1991, 1994). Meta-analytic, epidemiological and

twin-study findings suggest that the most severe impairments are consistently observed

in the domains of episodic memory and executive function (Reichenberg & Harvey,

2007). Therefore, considering the postulated relationship between executive function

and substance abuse maintenance, this neurocognitive domain in particular will once

again be focussed on in the following section.

Many pathophysiological accounts of schizophrenia suggest that the illness

results from neural network dysfunction where the PFC is considered an intrinsic part of

these networks (Reichenberg & Harvey, 2007). The most prevalent findings from brain-

imaging studies are impairments in frontal lobe functions and ‘hypofrontality’

associated with the illness of schizophrenia (Davidson & Heinrichs, 2003). It is also

found that medication variables are not significant contributors to these

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pathophysiological differences (Davidson & Heinrichs, 2003). It has been reported that

the similar pattern of deficits demonstrated between individuals with schizophrenia and

frontal lesion patients not only suggest frontostriatal circuitry disturbance, but that there

are even greater impairments in executive functioning among schizophrenia patients

than those individuals with frontal lobe lesions (Pantelis et al., 1997).

It has been argued that executive function deficits are a commonality across the

cognitive deficits seen in the illness of schizophrenia (Shallice et al., 1999). The study

of executive functions in schizophrenia is of great importance considering deficits in

this domain have been associated with psychosis proneness (Franke, Maier, Hain, &

Klinger, 1992). Schizophrenia patients also demonstrate profound impairments in

executive function at the beginning of their illness and that such deficits are thought to

mainly involve planning and strategy use, but not attentional set-shifting (Hutton et al.,

1998). Such impairments are found to progress over the course of the illness. Findings

have also suggested that schizophrenia patients demonstrate a distinctive pattern of

decision-making impairment on specific cognitive tasks with which performance is also

dependent on executive function (Shurman, Horan, & Neuchterlein, 2005). Once again,

such evidence is suggestive of specific frontal lobe function abnormalities, supporting

the notion that the cognitive impairments associated with the illness are related to

frontostriatal dysfunction (Robbins, 1990).

Results from Katz et al.’s (2007) study suggested that while schizophrenia

patients demonstrated executive deficits, those patients in the more chronic stages of the

illness demonstrated worse executive function performance in comparison to those in a

more acute phase. Such deficits have been shown to be associated with treatment-

refractory symptoms, such as negative symptoms (Kerns & Berenbaum, 2002;

Voruganti, Heslegrave, & Awad, 1997), as well as with poor functional outcome


(Greenwood et al., 2005; McClure et al., 2007). Impairments in this particular cognitive

domain have also been suggested to be associated with performance in daily

independent living skills, occupational and community functioning (Green, 1996;

Sharma & Antonova, 2003).

Impaired performances have been specifically demonstrated on ‘traditional’

executive functions measures such as the Wisconsin Card Sorting Test (WCST), tests of

verbal fluency, and the Trail Making Test (TMT) (Chen, Chen, Chan, Lam, & Lieh-

Mak, 2000; Chen, Lam, Chen, Nguyen, & Chan, 1996; Franke, Maier, Hardt, Frieboes,

Lichterman, & Hain, 1993; Goldberg, Torrey, Berman, & Weinberger, 1994; Hutton et

al., 1998; Zalla, Joyce, Szöke, Schürhoff, Pillon, Komano et al., 2004). However, the

extent of impairment on such measures has been found to vary among individuals with

schizophrenia depending on illness presentation. For example, findings have suggested

that there is a poor correlation between positive symptoms and reduced performance on

executive function measures (Morris, Rushe, Woodruffe, & Murray, 1995). Some

authors report that negative symptoms have been found to be significantly correlated

with the severity of executive dysfunction (Voruganti et al., 1997). However, in a study

by Rodriguez-Jimenez and colleagues (2008), it was found that while those

schizophrenia patients who performed poorly on the WCST also exhibited more

negative symptoms, there was no association found between WCST performance and

negative symptoms in dually-diagnosed schizophrenia patients with substance use

disorders. No significant association between neuroleptic medication and executive

functioning impairment in schizophrenia has also been found (Verdoux, Magnin, &

Bourgeois, 1995). Therefore, it is possible that there may be certain subgroups among

the schizophrenia population that may comprise of individuals with differing illness

pathology and possibly different executive abilities. Due to the high prevalence of


substance use, more specifically cannabis use, in schizophrenia, investigation into the

neurocognitive abilities of such a subgroup is of particular interest.

The importance of executive function to individuals with schizophrenia. The

illness of schizophrenia has significant economic implications and it is considered as the

most costly of the psychiatric disorders (Capri, 1994; Knapp, 1997; Torrey, 2002).

Functional impairment in particular has been identified as one the primary factors

contributing to the illness’ high cost (Kenny & Meltzer, 1991). In an extensive review

of the measurement of outcome in schizophrenia, Green (1996) defined functional

outcome as ‘the result of competence in a large number of constituent social and

instrumental role tasks’ (p. 323). Research findings have shown that cognitive

impairments account for significant variance in functional status measures (Green,

1996). Both cross-sectionally (Green, 1996) and longitudinally (Green, Kern, & Heaton,

2004), the cognitive impairments found in schizophrenia have been shown to be

associated with impairments in everyday functioning. Past research has found that

cognition is a stronger predictor of functional outcome than symptomatology (Harvey,

Howanitz, Parrella, White, Davidson, Mohs, & Davis, 1998; Harvey, Napolitano, Mao,

& Gharabawi, 2003; Kurtz, Moberg, Ragland, Gur, & Gur, 2005; Perlick, Rosenheck,

Kaczynski, Bingham, & Collins, 2008; Velligan, Mahurin, Diamond, Hazleton, Eckert,

& Miller, 1997). Therefore, in order for rehabilitation efforts to be more precise and

thus ultimately have a higher success rate, identifying the specific cognitive domains

found to be particularly associated with successful independent living is crucial.

Current treatments targeting functional impairments typically involve

behavioural techniques aimed at social, occupational, self-care and independent living

skills training (Sharma & Antonova, 2003). However, despite the levels of residential

independence demonstrated in schizophrenia outpatients (i.e., those that reside in the


community), widespread functional impairments are still evidenced (Auslander,

Lindamer, Delapena, Harless, Polichar, Patterson et al., 2001). It has been postulated

that one of the main reasons for the lack of improvement in the functional outcome of

patients with schizophrenia is the lack of success in sufficiently treating those features

of schizophrenia which are considered strong predictors of functional outcome, such as

negative symptoms and cognitive impairment (Harvey, Green, Keefe, & Velligan,

2004). Therefore, there appears to possibly be a mediating factor in influencing the

effectiveness of such approaches and it is cognitive impairment that is considered to be

this link (Green, 1996; Green et al., 2000).

Specific cognitive domains have been found to be closely related to functional

outcome (Green & Neuchterlein 1999; Green et al., 2000). It has been found that the

utilisation of complex and higher-order cognitive abilities (i.e., executive functions)

which include flexibility with set-shifting, reasoning, decision-making, planning and

working memory are related to successful treatment outcomes (Gordon, Kennedy, &

McPeake, 1988; O’Leary, Donovan, Chaney, & Walker, 1979; Weinstein & Shaffer,

1993). Among the range of cognitive deficits which have been most commonly found in

individuals with schizophrenia, it is acknowledged that executive functions play a

crucial role when considering outcome (Simon et al., 2003). Through extensive reviews

in the area of cognition in schizophrenia, performance on measures assessing executive

functioning was consistently found to be associated with poor community outcomes in

particular (i.e., independent living) (Green, 1999; Green et al., 2000). In addition,

Penadés and colleagues (2003) examined the effects of cognitive rehabilitation

strategies (i.e., the cognitive differentiation and social perception cognitive modules

from the Integrated Psychological Therapy program, implemented in 24 group sessions

over a 12-week period), on cognition and functional outcome in patients with


schizophrenia. The authors found that changes in encoding and executive function were

specifically associated with changes in functional outcome.

Several research studies have suggested that tests measuring executive functions

are the best predictors of performance in activities of daily living, particularly when

considering patients with schizophrenia (Dickenson & Coursey, 2002; Ihara, Berrios, &

McKenna, 2003; Semkovska, Stip, Godbout, Pacquet, & Bedard, 2002). Results from a

study conducted by McClure and colleagues (2007) indicated that two domains of

functional capacity (i.e., social and living skills) had different neuropsychological

correlates in schizophrenia. More specifically, it was found that both working and

episodic memory, as well as verbal fluency abilities, were related to social competence.

It was also found that processing speed, episodic memory and executive function were

associated with everyday living skills. Katz et al.’s (2007) findings suggested that

performance on executive function measures were more strongly related to performance

in complex areas of daily living (which included social communication, IADLs, and

occupational skills), in comparison to performance on a basic cognitive skill measure. It

is also considered that executive function measures in general have better predictive

ability regarding lack of insight in comparison to premorbid intellectual ability, IQ,

memory, or language measures (Burgess, Alderman, Evans, Emslie, & Wilson, 1998).

It has been well established that cognitive impairment is a core feature of

schizophrenia. In addition, executive dysfunction is not only particularly implicated in

the illness of schizophrenia, but is also identified as an important predictor of functional

outcome status. This neurocognitive domain has been considered as an area of

importance especially when evaluating the independent living capacity of patients in the

community. Therefore, if this particular domain is considered as a potential target for

treatment, then the comprehensive assessment of this neurocognitive system has


significant clinical importance. Without obtaining knowledge with regard to which

specific deficits are linked to ‘real-world’ functioning, efforts towards cognitive

rehabilitation will continue to remain not only less clearly focused, but ultimately less

successful in their utility. In the current study, executive functions are targeted due to

their close connections to community functioning, as well as their association with

negative symptoms which are also linked to functional outcome. Considering the

relationship between executive function and illness presentation, as well as outcome,

this particular neurocognitive domain has specific relevance in the examination of

cognitive functioning in schizophrenia.

Cognitive impairments associated with cannabis use and schizophrenia.

Since previous research findings have suggested an association between cannabis use in

schizophrenia and worsened illness prognosis, in addition to the reported adverse effects

of cannabis use alone on cognitive function without the presence of psychotic illness, it

would be reasonable to suggest that poorer cognitive function would be expected in

schizophrenia patients with cannabis use. However, relatively few studies have

specifically examined the relationship between cannabis use and cognitive functioning

in the schizophrenia spectrum disorders, with mixed results being reported. The current

literature review will further outline these studies. Once again, only neurocognitive

effects associated with chronic or long-term use cannabis use will be focussed on in the

following review.

Some studies have reported poorer performance amongst schizophrenia patients

with cannabis use. Mata and colleagues (2008) examined the relationship between pre-

illness cannabis abuse and cognitive performance in 61 cannabis-abusing and 71 non-

abusing patients experiencing their first episode of schizophrenia-spectrum psychosis.

The patients were grouped according to their cannabis abuse prior to illness onset and


cannabis abuse status was based on the criteria of at least weekly use during the

previous year. In their study, a cognitive battery was administered which included tasks

thought to utilise the DLPFC, such as a measure of working memory (assessed by Digit

Span - backwards condition), a measure of verbal fluency (measured by phonemic

fluency task – FAS), and a set-shifting task (measured by the TMT), as well as an OFC

related task designed to measure decision-making capacity (e.g., IGT). Findings from

their research showed no significant differences between patients who had abused

cannabis before their psychosis onset and patients who had not abused cannabis before

their psychosis onset on any of the DLPFC related tasks. However, results also showed

that those patients who had abused cannabis before their psychosis onset demonstrated

poorer total performance and lower improvement in performance on the IGT. The

authors suggested a possible explanation for the findings is that decision-making

differences between cannabis abusers and non-abusers may reflect a pre-existing

condition that led abusers to make costly decisions in the gambling task.

In a recent study conducted by Sánchez-Torres and colleagues (2013), the

relationship between lifetime cannabis use (over 10 years of follow-up) and current

cognitive performance was examined in a sample of 42 patients with schizophrenia, 35

of their unaffected siblings, and 42 healthy control subjects. Drug abuse was assessed in

patients and siblings longitudinally using the Composite International Diagnostic

Interview (World Health Organisation, 1993). The controls were only assessed at

follow-up and reported current consumption. A lifetime estimate of consumption was

determined for all participants (using information from subject reports, family and

charts) and subjects were given a rating from 0 (no consumption) to 5 (every-day

consumption). In the patient group, longitudinal cannabis consumption was found to

have a negative relationship with performance in a social cognition task (assessed by the


Managing Emotions section of the Mayer-Salovey-Caruso Emotional Intelligence Test

(MSCEIT; Mayer, Salovey, Caruso, 2009). The investigators did not find a significant

relationship between cannabis use in the patient group for the three time points and the

composite scores for processing speed, attention, declarative memory, working memory

and executive function. In the unaffected sibling group, a significant negative

correlation between cannabis use at baseline 10 years prior to assessment, current use

and the declarative memory composite score (assessed by the Spanish version of the

California Verbal Learning Test, the Test de Aprendizaje Verbal Espan ˜a-Complutense

(TAVEC; Benedet & Alejandre, 1998) and the Brief Visual Memory Test-Revised

(BVMT-R; Benedict, 1997)) was found. However, while cannabis use was not found to

predict cognitive performance in the healthy control group, a negative association

between lifetime cannabis and tobacco use together and processing speed and social

cognition performance was found. Results indicated that longitudinal cannabis use was

associated with poorer social cognition in patients and that current cannabis use was

associated with poorer performance in working memory, particularly when low

premorbid IQ and earlier age of illness onset was accounted for in the explanatory

model.

Other research findings have suggested no differences in cognitive performance

between cannabis-using and non-cannabis using patients with schizophrenia. Sevy and

colleagues (2007) compared the performance of 14 schizophrenia patients with

concurrent cannabis use disorders and 13 patients without concurrent substance use

disorders on a number of measures of cognition as well as on a decision-making task

(i.e., IGT), with that of 20 healthy normal subjects. Results of the study showed that

both schizophrenia groups demonstrated more cognitive impairments and worse

performance on the IGT, compared to healthy controls. However, no significant


differences on most of the cognitive tests (including the IGT) were found between

schizophrenia patients with cannabis use disorders and schizophrenia patients without.

While it is noted that the study conducted by Sevy and colleagues (2007) included

subjects who also used substances other than cannabis, due to the inclusion of the IGT

measure in their assessment of cognition (and its particular relevance to the

neurocognitive construct of interest), the results of the study were deemed worthy of

review.

Scholes and Martin-Iverson (2010) investigated the cognitive performances of

22 cannabis-using schizophrenia patients, 49 non-using schizophrenia patients, 36

otherwise healthy cannabis-using controls and 35 non-using healthy controls.

Performances on tasks measuring attentional control (Stroop test), auditory working

memory (LNS), spatial working memory (Spatial Span) and card-sorting/set-shifting

and peserveration (WCST), were assessed. Results from the study showed that while

both schizophrenia groups demonstrated significantly poorer performance across all

tasks relative to controls, no significant differences in cognitive performance between

cannabis-abusing schizophrenia and non-using schizophrenia patients were found. In

other words, cannabis use in schizophrenia was not associated with further

neurocognitive decrements. Scholes and Martin-Iverson’s findings also suggested that

cannabis use in healthy individuals was not associated with deficits in the measures

administered that resemble those deficits associated with schizophrenia. However, one

exception to this finding was noted and this was increased perseveration demonstrated

on the WCST. From these results, the authors concluded that cannabis use has subtle

effects on the cognitive performance of both healthy individuals and patients with

schizophrenia across a range of tasks.


Surprisingly and contrary to expectations, there has also been a number of

studies showing superior cognitive performance amongst schizophrenia patients with

cannabis use. Stirling and colleagues (2003, 2005) administered a neuropsychological

battery to 69 patients at a 10-12 year follow-up. The patients in this study were recruited

out of 112 individuals in 1987 who had experienced their first episode of psychosis

within 2 years prior to this time. Those who had a history of cannabis use (categorised

as ‘no use’ and ‘some use’) at the time of the onset of their illness were noted. Thirty-

seven patients were assessed with a neurocognitive battery at onset, 24 were re-assessed

at follow-up and an additional 25 from the parent sample were also assessed at follow-

up. Findings from the study showed that patients with cannabis use demonstrated better

performance on a verbal fluency task (COWAT – FAS), as well as on other

neurocognitive measures such as design memory (Memory for Design; Graham &

Kendall, 1960), visuospatial organisation (object assembly, block design, picture

completion, picture arrangement), and recognition memory (face recognition) at follow-

up. More specifically, after controlling for the effects of age of cannabis use onset

significantly better performance on measures of memory, verbal fluency, sequencing,

visuospatial organisation and recognition memory was found to be associated with a

history of cannabis use. In addition to these findings, the 26 patients who reported a

level of continued cannabis use at follow-up demonstrated significantly better

performance in several of these domains in comparison to those who had not sustained

their cannabis use at this time. It was suggested by the authors that while impairment in

executive function may be present in first episode patients, they do not appear to

deteriorate over 10-12 years. As both the patients with cannabis use and non-using

patients were not able to be distinguished based on their performance on any of the

premorbid adjustment measures or in relation to social/behavioural functions (as


assessed by the Premorbid Adjustment Scale (PAS); Cannon-Spoor, Potkin, & Wyatt,

1982), the authors concluded that their findings were not indicative of the presence of

differences between groups related to premorbid social functioning. Results suggested

that the cannabis-using group may represent a subgroup with a subtly different profile,

characterised by relatively preserved neurocognition and fewer negative symptoms.

While better performances demonstrated by schizophrenia patients with

cannabis use could be considered counterintuitive, other studies have also reported a

similar pattern of results. Jockers-Scherübl and colleagues (2007) compared the

cognitive functioning of 39 schizophrenia patients (19 cannabis abusers and 20 non-

abusers) with 39 healthy control subjects (18 cannabis abusers and 21 non-abusers)

following a minimum abstinence period of 28 days. The researchers excluded those

patients with any drug abuse or dependence history other than that involving cannabis.

The cannabis-abusing group in the study included only those individuals whom had

consumed an average of at least 0.5g of cannabis per day for a minimum of 2 years prior

to illness onset. Main effects of diagnostic group (i.e., schizophrenia vs. controls)

indicated cannabis-using patients with schizophrenia demonstrated worse performance

in most neurocognitive tests in comparison to cannabis-using controls. However, when

only the main effect of age of cannabis use onset was considered, irrespective of

diagnostic group, there was no significant difference found. A significant interaction

between diagnostic group and age of onset was found for performance on a processing

speed and working memory task (measured by the Digit Symbol Substitution Test

(DSST): Wechsler, 1981) and performance on another measure of working memory

(assessed by ‘other errors’ on the WCST). More specifically, control subjects with

cannabis abuse who had commenced regular use at 16 years or younger demonstrated

worse cognitive performance than those individuals whose age of cannabis use onset


was 17 years or older. Contrastingly, schizophrenia patients with cannabis abuse who

commenced their abuse at the age of 16 years or younger performed better on the DSST,

but demonstrated worse performance relative to controls when their cannabis abuse had

started at 17 years or older. No significant difference in performance between control

subjects and schizophrenia patients with early onset of regular cannabis abuse were also

observed on this test. A similar pattern of results was observed on ‘other errors’ of the

WCST. These results suggested that regular cannabis abuse commencing before the age

of 17 (and prior to illness onset) was associated with better neurocognitive performance

in patients with schizophrenia. However in the control group, early age of onset of

regular cannabis abuse was found to be associated with worse performance. It was noted

that once the authors made corrections to the alpha level in order to account for multiple

statistical tests, the difference in performance remained significant for ‘other errors’ on

the WCST (when age of onset was applied), but only approached significance for

performance on the DSST. The authors considered that a possible explanation for the

findings showing better performance by patients with cannabis abuse on such measures

who commenced their cannabis use prior to the age of 17 (and also illness onset) may be

potentially due to the latter measure not only assessing processing speed abilities. It is

thought that the DSST in particular may also tap into a number of neurocognitive

abilities including attention, sustained attention, psychomotor speed, working memory

and other executive functions (Lezak et al., 2004). Therefore, it was considered by the

authors that such a measure may be possibly more sensitive in detecting subtle

differences that exist between groups. It is postulated that when there are slight deficits

on a collection of neurocognitive abilities, the need to simultaneously integrate these

abilities may consequently lead to overall impairments in performance becoming more

evident. Therefore, the authors proposed that a possible explanation for the findings of


better performance on this test may suggest that those patients with cannabis abuse with

an age of cannabis abuse onset prior to illness onset could possibly possess a better

capacity to integrate several cognitive functions despite demonstrating poor

performance in individual tests.

Coulston, Perdices and Tennant (2007) examined the relationship between

neuropsychological performance and three different indices of cannabis use in 60 males

with schizophrenia/schizoaffective disorder and 17 male healthy control subjects. Forty-

four schizophrenia patients met the Diagnostic and Statistical Manual of Mental

Disorders - Fourth Edition (DSM-IV; American Psychiatric Association, 2004) criteria

for lifetime cannabis abuse/dependence. The indices used by the researchers included

lifetime abuse/dependence (assessed according to the DSM-IV criteria of substance

abuse/dependence), frequency of use, and recency of use. In line with the pattern of

results of previous studies, findings indicated that cannabis use was associated with

enhanced neurocognitive functioning in schizophrenia. More specifically, results

showed that a larger proportion of those schizophrenia patients with lifetime cannabis

abuse/dependence demonstrated performance classified in the normal range on one of

the executive function measures administered (i.e., the TMT), in comparison to those

without lifetime abuse/dependence. However, the actual component of the measure

which was found to be significantly associated with better performance was that aspect

of the test which assessed psychomotor speed. In this study, cognitive performance was

classified as ‘impaired’, ‘normal’, and ‘above average’ based on scores derived from the

control group. Subjects were deemed to demonstrate cognitive ‘impairment’ if

performance fell 1.5 – 2.0 standard deviations or more below the mean of the control

group (Spreen & Strauss, 1998; Ruff & Allen, 1996, both cited in Coulston et al., 2007).

In addition, above average performance was determined if scores were 0.5 standard


deviations or more above the mean of the control group. Intriguingly, high frequency

cannabis use was found to be associated with better performance on Principal

Component Analysis derived cognitive components of speed of information processing,

divided attention, visual conceptual switching, and planning efficiency. However in

contrast, a larger proportion of subjects categorised as medium frequency cannabis users

fell in the ‘impaired’ range on the cognitive components of planning efficiency and

complex information processing. It was noted that while premorbid IQ was not found to

be significantly different between frequency groups, the medium frequency group had a

mean premorbid IQ at almost half a standard deviation lower than the high and low

frequency cannabis user groups. The cannabis use indices measuring recency (i.e.,

cannabis abuse/dependence in the past week; cannabis use at a non-dependent level in

the past month, but prior to the past week; cannabis use at a non-dependent level prior

to the past month), were also found to be associated with better performance on the

cognitive components reflective of speed of information processing, complex

information processing, psychomotor speed, inhibition accuracy, planning efficiency,

planning and organisation, and complex perceptual organisation. Worse performance on

a non-executive cognitive component of immediate memory was however, associated

with the recency category of non-dependent cannabis use in the past week. In addition,

cannabis use at a non-dependent level in the past week was associated with worse

performance on the cognitive components of planning and organisation and complex

information processing. As the cognitive components which were found to be associated

with better performance, as well as with the cannabis use parameters of frequency and

recency of use, were attention/processing speed and executive function domains, the

authors postulated that cannabis use may possibly stimulate prefrontal

neurotransmission.


Further evidencing the surprising observation of better neurocognitive

performance, Schnell and colleagues (2009) investigated the residual impact of cannabis

use and specific parameters of cannabis consumption on cognition in a sample of

schizophrenia patients with a lifetime diagnosis of comorbid cannabis use disorder. The

indices of cannabis use assessed included age of onset of use, the duration of regular

use, time since last dose, average frequency of use (joints per month), and maximum

frequency of use (joints per month). A cognitive test battery was administered to 34

schizophrenia patients and 35 currently abstinent schizophrenia patients with cannabis

use disorder. The minimum period of abstinence from cannabis was 3 weeks. The

schizophrenia patients with cannabis use disorder had poorer academic achievement and

lower vocabulary scores. However, after potential confounds were accounted for

schizophrenia patients with cannabis use disorder were found to demonstrate better

performance in tests of verbal memory (measured by the Auditory Verbal Learning and

Memory Test; Heubrock, 1992), working memory (LNS; Gold, Carpenter, Randolph,

Goldberg, & Weinberger, 1997), and visuomotor speed and executive function (DSST;

Tewes, 1991; TMT, Part B; Reitan 1958; Reitan & Wolfson, 1993), in comparison to

schizophrenia patients without comorbid cannabis use disorder. Results of the study

were in support of previous findings (Coulston et al., 2007; Jockers-Scherübl et al.,

2007; Stirling et al., 2005). More frequent cannabis use was also associated with better

performance in tasks of attention (Continuous Performance Test (CPT); Cornblatt,

Risch, Faris, Friedman, & Erlenmeyer-Kimling, 1988) and working memory (LNS). In

addition, DeRosse and colleagues (2010) compared lifetime measures of psychotic

symptoms, as well as cognitive performance in 280 schizophrenia patients without a

history of cannabis use disorder and 175 schizophrenia patients with a history of

cannabis use (51 patients with comorbid cannabis abuse; 124 patients with cannabis


dependence). Similar results were found where schizophrenia patients with a history of

cannabis use disorder demonstrated significantly better performances on measures of

processing speed (TMT, Part A & B), verbal fluency (animal naming) and verbal

learning and memory (California Verbal Learning Test). This group also had better

Global Assessment of Functioning (GAF) scores than schizophrenia patients without a

history of cannabis use disorder.

Rodríguez-Sánchez et al (2010) conducted a study amongst 107 first-episode

patients with schizophrenia (47 cannabis users and 57 non-users) and 37 healthy

controls. Patients were considered to be cannabis users if there had been at least weekly

use during the year prior to program entry. The aim was to compare subjects on clinical

features, cognitive performance and premorbid adjustment, both cross-sectionally and

longitudinally. Results showed that cannabis users demonstrated better performance in

attention (as measured by the CPT) and executive function (as measured by the TMT-B)

at baseline and following 1 year of treatment. In addition, cannabis users were found to

have better social premorbid adjustment, particularly during childhood and adolescence.

They were also found to have earlier age of illness onset. Findings also indicated that

the amount of cannabis consumed and duration of use was not associated with cognitive

performance. While it was noted by the investigators that some patients regularly used

other drugs of abuse in addition to their cannabis use, it was found that results relating

to executive function performance remained significant after the omission of these

subjects from analyses. The authors argued that the findings of the higher presence of

positive symptoms at baseline, better premorbid adjustment and higher performance on

frontal related cognitive functions suggest that cannabis users may represent a specific

subgroup of patients with better overall premorbid abilities.


Leeson and colleagues (2011) aimed to explore the role of age of onset and

cognition on outcomes in cannabis users with first-episode schizophrenia. In addition,

the investigators aimed to evaluate the effect of cannabis use parameters such as dose

and cessation. Ninety-nine patients were divided into 65 lifetime cannabis users (as

defined by those who reported having used the drug at all during their lifetime) and 34

never-users. The cannabis-using group were further parsed into a high frequency group

(i.e., those who reported either daily or almost daily use; n = 30) and a low frequency

group (i.e., those who reported use of either twice a week or less; n = 35). Results of the

study showed that cannabis users had better premorbid IQ and social function at

psychosis onset. Cannabis users also demonstrated better performance in verbal learning

(assessed by the Rey Auditory Verbal Learning Task), working memory span (Spatial

Span) and planning (assessed by a task analogous to the Tower of London), but not on a

working memory manipulation task (self-ordered search task from the CANTAB), in

comparison to non-users. However, when premorbid IQ was entered into analyses as a

covariate, these between group differences were no longer significant except for

planning. It was found that premorbid IQ did not explain the between group difference

in social functioning. Low frequency users were found to have significantly higher

current IQ than high frequency users and cannabis users had an earlier age of illness

onset than non-users. There was also a strong relationship found between age at first

cannabis use and age of onset of both prodromal and psychotic symptoms. The authors

concluded from their overall findings that cannabis use may trigger the onset of

psychosis in individuals who otherwise have good prognostic features (i.e., higher

intellectual and social functioning prior to psychosis onset). It was also considered that

the cannabis-using patients in the study had higher ‘cognitive reserve’ not only as

evidence by better premorbid abilities, but by also better social function demonstrated


over the first 15 months of illness. It was considered that the earlier age of illness onset

in cannabis users may therefore be due to the toxic action of cannabis instead of it

reflecting of a form of illness that is more severe in nature.

Yücel and colleagues (2010) conducted a meta-analysis of the research in the

area examining the cognitive functioning of patients with established schizophrenia with

and without comorbid cannabis use. Findings suggested that patients with history of

cannabis use were found to have superior cognitive functioning. These particular results

were predominantly influenced by those studies which included schizophrenia patients

who had a lifetime history of cannabis use (defined elsewhere e.g., Schnell et al., 2009

as those that were assessed to have a lifetime diagnosis of comorbid CUD according to

DSM-IV-TR), rather than current or recent use factors. In a second study conducted by

the authors, the cognitive performance of 59 first-episode patients with psychosis with a

cannabis use history was examined in comparison to 26 patients with first-episode

psychosis patients without a history of cannabis use and 43 healthy non-using control

patients. Findings showed that first-episode patients with a cannabis use history

demonstrated better performance in the neurocognitive domains of visual memory (as

measured by Visual Reproduction (Part I) from the Wechsler Memory Scale - Revised

(WMS-R); Wechsler, 1987), working memory (as measured by ‘SWM-errors’ on

Spatial Working Memory from the CANTAB), and planning and reasoning (as

measured by the Tower of London; Shallice, 1982). In addition to these results, it was

also found that earlier onset of cannabis use was associated with less cognitive

impairment in comparison to a later age of cannabis use onset which is in support of

previous findings (Jockers-Scherübl et al., 2007).

Rabin and colleagues (2011) also conducted their own meta-analysis, but instead

only included studies that examined the direct effects of cannabis on cognition in


schizophrenia, with no other substance use included. Similar findings were reported,

denoting overall superior cognitive performance in schizophrenia patients associated

with lifetime cannabis use in comparison to non-using patients. However, the authors

noted that the magnitude of the effect sizes found were considered to be in the small to

medium range (mean d = .06 - .48) which were also similar to the effect sizes reported

in Yücel and colleagues’ (2010) meta-analysis. As it is considered that effect sizes of

0.50 or greater are deemed to be clinically significant (Lezak et al., 2004), it is possible

that results of the meta-analysis may be reflective of variability in methodological

design instead of between-group differences. Therefore, effect sizes of these magnitudes

may serve to question the clinical significance of the found relationship between

cannabis use and neurocognition in schizophrenia amongst these studies. In a recent

study by the same authors (2013), the cognitive performance in schizophrenia as a

function of cannabis use indices was examined. The study included 18 schizophrenia

outpatients with current cannabis dependence and 29 patients with no current cannabis

dependence. The latter group was then parsed into subgroups which included 21

patients with lifetime cannabis dependence and 8 patients with no lifetime dependence.

Results indicated no significant differences in cognitive performance between patients

with current cannabis dependence and no current cannabis dependence. However,

never-dependent patients were found to demonstrate poorer reaction time on a measure

of sustained attention, concentration, psychomotor speed, response inhibition and

impulsivity (Continuous Performance Test II (CPT-II); Conners, 2000), than current and

former dependent patients. These results remained significant after controlling for age.

In current dependent patients, negative correlations were found between years of

cannabis exposure and performance on the CPT-II, a measure used to assess working

memory (Digit Span; Wechsler, 1997), another measure of executive function (WCST),


a measure of verbal memory (California Verbal Learning Test—Second Edition; Delis,

Kramer, Kaplan, & Ober, 2000), and long delayed cued recall. It is important to note

that the reported associations with years of cannabis use exposure were found on the

Digit Span forwards condition only. There was no association between performance on

tests of impulsivity and risky decision making (assessed by the Kirby Delayed

Discounting Task; Kirby, Petry, & Bickel, 1999 and the IGT - Computerized version;

Bechara et al., 1994) and cumulative cannabis use. Results of the study suggest that the

cessation of cannabis use was not associated with worse or better performance. Also,

while poorer reaction times were demonstrated by never-dependent patients, reduced

performance on a range of cognitive tasks was found to be associated with cumulative

use in current dependent patients suggesting that years of cannabis use exposure may be

a more important contributing factor than cannabis use status.

The increasing picture of better cognitive performance associated with cannabis

use in schizophrenia patients is not only counterintuitive, but rather unexpected

considering the impact of cannabis use on cognition in otherwise healthy users. One

possible explanation for these findings is that better cognitive functioning may serve to

be a risk factor in patients with schizophrenia for the development of cannabis use

disorders. In other words, this cohort of individuals may have higher social competence

(i.e., as demonstrated by the ability to seek, obtain and maintain drug use) and therefore

be reflective of more intact cognitive functions (DeRosse et al., 2010; Jockers-Scherübl

et al. 2007; Leeson et al., 2011; Rodríguez-Sánchez et al., 2010). Arndt and colleagues

(1992) found better premorbid adjustment in those individuals with schizophrenia who

abused alcohol or cannabis. A two-stage model was proposed by the authors to attempt

to explain substance abuse in these individuals. The authors postulated that those with

better premorbid adjustment were more sociable in nature and thus would possibly be


exposed to more opportunities for substance use experimentation. Other authors have

also suggested better premorbid abilities in substance-using schizophrenia patients,

where such cohorts have been considered to reflect a relatively distinct group who differ

from non-using patients in terms of premorbid social adjustment which is thought to be

required in order to initiate and maintain drug-seeking behaviour (Wobrock, Sittinger,

Behrendt, D’Amelio, Falkai, & Caspari, 2007). Similarly, in a study conducted by

Kumra and colleagues (2005) which examined performances on measures of intellectual

functioning in adolescent inpatients with schizophrenia and schizoaffective disorder,

findings suggested that a better Full Scale Intelligence Quotient (FSIQ) and Verbal

Intelligence Quotient (VIQ) was associated with a history of cannabis

abuse/dependence. However, this perspective is contrary to previous findings which

failed to identify significant differences in premorbid adjustment and social/behavioural

functioning between groups (Coulston et al., 2007; Stirling et al., 2005). It is also noted

that the sample in Kumra et al.’s (2005) study were adolescents.

Limitations to Previous Research

The results of the abovementioned sudies cannot be adequately evaluated

without reviewing the limitations in methodology across each study. In some studies, it

was more difficult to establish the direct impact of cannabis on cognition because

additional substances had also been used by patients and these had not been controlled

for in analyses (Sevy et al., 2007; Yücel et al., 2010). Yücel and colleagues (2010)

included studies in their meta-analysis as long as cannabis was the most preferred

substance of the sample. Therefore, some cannabis-using groups also included patients

who did not only use cannabis. However, it is noted that in studies which included other

substance use one would assume that this would only serve to increase the likelihood of

detecting poorer performance in the drug-using patient group, but surprisingly most


found better performances. It is considered that the inclusion of other substances may

potentially make it more difficult to establish the precise contributing factors to this

level of performance (i.e., whether superior performances are associated with cannabis

use related brain functioning per se, or are just simply associated with the

neurocorrelates of substance use in schizophrenia in general). It is acknowledged that

this issue is considered to be practically unavoidable, or at least in part a contributing

factor, making the recruitment of larger, more specific patient sample groups more

difficult to achieve. Some studies also only examined the effects of cannabis use prior to

the first psychotic episode and failed to investigate the effects of continuing cannabis

use after illness onset (Jockers-Scherübl et al., 2007; Mata et al., 2008).

Such inconsistent findings in the existing literature may also be explained by the

level of variability in population characteristics between the studies. One source of this

variability in sampling includes the types of patients used. Reported better performances

amongst cannabis-using patients have involved a relatively young sample (Coulston et

al., 2007). It was considered that the effects of cumulative substance use may not be

fully developed in the tested sample and therefore, the effects associated with longer

lifetime cannabis use could not be established. Another possibility is that the deficits

found may be a reflection of age-related cognitive decline, as there is increasing

evidence in the literature suggesting age-related deficits in executive functioning (Fisk

& Sharp, 2004; Fisk & Warr, 1996; Fristoe, Salthouse, & Woodard, 1997; Salthouse &

Babcock, 1991; Van der Linden, Beerten, & Pesenti, 1998). In other words, the

neurocognitive performances observed in these previous studies may not be directly

related to the effects of cannabis use, but instead a function of age differences. In Rabin

and colleagues’ (2013) study, never-dependent patients were found to be significantly

older than current-dependent and former-dependent patients. In addition, never-


dependent patients were found to have a significantly older age of diagnosis than

former-dependent patients. Similar differences in age of diagnosis between never-

dependent and current-dependent patients approached significance.

Further, the way in which cannabis users were classified or identified also varied

between studies. For example, some studies have utilised a binary system grouping

participants as being either users or non-users (Mata et al., 2008; Scholes & Martin-

Iverson, 2010; Sevy et al., 2007; Stirling et al., 2005) and cannabis use parameters such

as severity/quantity, frequency, and duration were not accounted for in the researchers’

classification of what characterised a user. In most of these studies, either no significant

differences were reported or worse cognitive performance was associated with cannabis.

However, Stirling and colleagues (2005) reported better performance. Contrastingly,

those studies which classified participants as having a cannabis use disorder diagnosis

or being defined by a minimum amount or duration of use showed only better cognitive

performance associated with cannabis (Coulston et al., 2007; DeRosse et al., 2010;

Jockers-Scherübl et al., 2007; Leeson et al., 2011; Rabin et al., 2013; Rodríguez-

Sánchez et al., 2010; Schnell et al., 2009). In addition, two studies reported a

relationship between higher frequency of cannabis use and superior cognitive

functioning (Coulston et al., 2007; Schnell et al., 2009). Therefore, considering the

differences in findings it seems that assessing the different parameters of cannabis use is

of particular importance when examining the effect of cannabis on cognition in

schizophrenia.

Studies also differed in the range of tests used to assess cognitive functioning or

the types of measures used to tap into specific cognitive functions. Further, it is

acknowledged that the selection of measures used in previous studies appears to be

relatively atheoretically driven and instead based upon face validity (i.e., they appear to


assess these functions) in measuring their proposed cognitive constructs. In addition, the

cognitive assessment conducted in some studies were restricted to only a few cognitive

domains (DeRosse et al., 2010; Schnell et al., 2009; Scholes & Martin-Iverson, 2009).

The means in which these domains were assessed were also limited by the diminutive

number of measures used to do so. Performance on the measures utilised in previous

research may not precisely enough reflect the range of deficits implicated in

schizophrenia, as well as in cannabis users, particularly when considering the multi-

faceted neurocognitive processes involved in the executive function system. Therefore,

it is possible that these studies could fall short of being able to adequately assess the full

range of abilities or components that are theoretically conceptualised to be involved in

the executive functioning system. Considering the relationship between executive

function and functional outcome in schizophrenia, consequently it may be more difficult

to fully evaluate the clinical relevance of previous findings regarding overall cognitive

performances. A methodological problem commonly involved in neuropsychological

research, involves the issue of how the multi-faceted and complex construct that is

termed ‘executive function’ has been mainly assessed by relatively few psychometric

measures (e.g., the WCST, the Stroop test, verbal fluency or TMT). This potential

inadequacy in assessment approach has been considered an important issue (Green,

1996; Green et al., 2000; Thoma, Wiebel, & Daum, 2007). Therefore, previous

neuropsychological evidence may not be reflective of the true nature of, or sufficiently

narrow down, the various subcomponents which could be specific to the executive

deficits deemed to be crucial to the illness of schizophrenia. It is possible that the

inconsistencies in previous findings may be related to the methodological difficulties

that are involved in precisely defining and measuring the construct of executive

function, as well as assessing the range of sub-processes which fall under the executive


function domain. Neurocognitive test batteries should aim to target and delineate the

construct(s) of interest (e.g., executive function) more precisely. In addition, a lack of

examination of whether performance on such measures is related to day-to-day

functioning abilities (i.e., functional outcome) questions the ecological validity of the

employed measures used in previous studies (i.e., are they are adequately reflective, and

predictive, of the abilities required to function in the ‘real-world’?). It is possible that

outside of the testing context, there are more complex demands and distractions that an

individual may encounter in more naturalistic settings. Therefore, any absence of

deficits demonstrated in a psychometric assessment situation may not necessarily reflect

intact neurocognitive function. It is possible that utilising more ecologically valid

measures could potentially allow for the detection of more subtle deficits by creating

conditions that could serve to place greater ‘real-world’ demands on an individual.

The inconsistency in past findings suggests that the evaluation of neurocognitive

function in schizophrenia patients with cannabis use requires further examination.

Considering the results in previous studies indicating superior cognitive performances in

cannabis-using schizophrenia patients, in comparison to patients without a cannabis-use

history, it is possible that the use of a matched-pairs control group with cannabis use

could potentially help to further tease apart or further explain these observations. An

otherwise healthy control group with a similar cannabis use history could possibly allow

for more information in addition to the previous findings, by assisting to determine

whether cannabis acts correspondingly in otherwise healthy users in comparison to

patient users, or whether there is something truly unique to the schizophrenia patient

with cannabis use population. Considering the prevalence rates of cannabis use in this

particular clinical population, cannabis use in schizophrenia is an often unavoidable

confounding variable that needs to be carefully accounted for. Indices of cannabis use


are also often highly variable across individuals and consequently cannabis use per se

can be difficult to define. Therefore, in order to address this issue it is imperative that a

detailed assessment of the different parameters of cannabis use is conducted (e.g.,

severity/quantity, frequency, duration, time since last use). The use of a control group

with a similar cannabis use history would also help to control for any confounding

influence contributed to by such variations in crucial cannabis-use indices which have

been considered to have an impact on cognitive performance. In addition, as executive

impairments have been found to be associated with age-related cognitive decline, age is

also deemed an important variable to control for.

The previously mentioned methodological issues also provide scope for the

further development of neuropsychological battery measures in not only being able to

more effectively examine complex cognitive constructs such as executive function, but

in addition sufficiently validate individual neurocognitive sub-components against

various aspects of functional outcome. In order to critically examine the validity of

various tests of executive function, further exploration into the concept of executive

function and its specific components, will be discussed in the following section.

Part B

The Assessment of Executive Function

Over the years, establishing a precise definition, as well as developing the

effective measurement, of executive function has had its challenges. This can be

explained in part by there being much debate about the validity of specific measures in

being able to capture the full range of abilities which fall under this domain (i.e., being

able to successfully ‘fractionate’ the executive system). While various studies have

aimed to assess executive functioning in patients with schizophrenia, many of these

studies have appeared to examine only a unitary concept of the construct using a limited


number of assessment measures (for review, see Green, 1996; Green et al., 2000).

Therefore, many studies have failed to directly address the fractionation of the executive

function system in schizophrenia and hence, it is possible that performance on selected

measures may not adequately reflect the range of processes that fall within the construct

that is termed ‘executive function’. It is thought that the more successful fractionation of

the executive functions is largely dependent on the ability to develop specific theoretical

models of this neurocognitive system (Baddeley, 1998; Burgess et al., 1998; Shallice &

Burgess, 1991). While there is a long history of various models conceptualising the

construct of executive function in the neurocognitive literature, for the purposes of this

study one specific model (chosen on the basis of its comprehensive features), will be

discussed in detail.

Models of executive function. Developing a good understanding of the specific

mechanisms and components of executive functioning has unfolded over various

approaches. The conceptualisations, definitions and models of executive functioning

subscribe to various research findings arising from neuroanatomical, neurophysiological

and neural circuitry evidence from animal brain-behavioural relationship observations

(for overview, see Goldman-Rakic, 1987), the examination of the relationship between

cognitive and behavioural deficits and frontal lobe damage (e.g., Fuster, 1989;

Goldman-Rakic, 1996; Luria, 1973; Royall, Lauterbach, Cummings, Reeve, Rummans,

Kaufer et al., 2002), as well as theoretical model fit from statistical approaches such as

confirmatory factor analysis methods (e.g., Daigneault, Braun, & Whitaker, 1992).

More recently, there has been various theoretical and psychometric approaches

that have been developed in an attempt to determine whether executive functioning

should be conceptualised as a unitary system or whether is it is more adequately

described by a model involving multi-processes (Baddeley, 1998; Miyeake, Friedman,


Emerson, Witzky, & Howerter, 2000; Parkin, 1998; Stuss & Alexander, 2000).

Increasingly it has become more apparent that executive functioning cannot be

considered as a unitary construct as various executive function components have been

able to be individualised and while found to be related, are shown to be independent to

each other (Chevignard et al., 2008; Duncan, Johnson, Swales, & Freer, 1997; Miyake

et al., 2000; Robbins, James, Owen, Sahakian, Lawrence, McInnes, & Rabbit, 1998).

Models of executive function which have emerged over the years view the overall

system as comprising of individual and distinct subcomponents (Andres, 2003;

Baddeley, Della Sala, Robbins, & Baddeley, 1996; Goethals, Audenaert, Van de Wiele,

& Dierckx, 2004) which are then conceptualised as being structured either in a

hierarchical manner (e.g., Fuster, 1989; West, 1996) or as a distinction between

'hot/cold’ processes (e.g., Damasio, 1995).

West’s model of executive function. West’s (1996) model of executive function

builds upon a previous hierarchical model originally proposed by Fuster (1989), which

incorporates the conceptualisation of superordinate and subordinate functions.

According to Fuster’s model, it is postulated that executive functioning involves an

overarching or ‘superordinate’ function called the ‘temporal organisation of behaviour’

which is considered to be responsible for the initiation and maintenance of behaviours

that have a common goal. This function is conceptualised to be subserved by three

subordinate functions. These include provisional memory which involves the

recollection of previous experience; prospective memory which is thought to be

responsible for the storage and cueing of information that is required to perform a future

goal; and interference control which serves to suppress interferance or conflicts

irrelevant to the task at hand. This model emphasizes the concept of ‘temporal gestalt’,

meaning that such functions support the organisation of behaviour over time in


sequence, connecting past actions and future events or goals in conjunction with the

integration of information that is task-relevant and the disregard of task-irrelevant

information (Fuster, 1989). It is acknowledged that Fuster’s model affords, at least in

part, a way of theoretically explaining the executive function system as a hierarchy of

cognitive processes. However, considering that many previous studies investigating

executive function have also examined the cognitive process of inhibition, Fuster’s

model appears to be somewhat lacking. Therefore, additional models of executive

function will also be discussed in order to incorporate other executive function domains

which appear to not be accounted for in this model alone.

In addition to Fuster’s (1989) conceptualised executive processes, West included

a fourth subordinate function to his own model which is termed the inhibition of

prepotent responses. West also used the term ‘retrospective memory’ instead of

provisional memory. According to West, retrospective memory involves the retrieval

and maintenance of information that is task-relevant from its storage in memory. This

function has also been conceptualised to be similar to the construct of working memory

(Baddeley, Della Sala, Papagno, & Spinnler, 1997). In West’s model, prospective

memory is thought to aid in the preparation of an individual for an upcoming action or

behavioural response. Interference control serves to manage the intrusion of task-

irrelevant information incoming from external sources. Such task-irrelevant information

can be incorporated into retrospective memory and, therefore, subsequently interfere

with correct task execution if it is not adequately controlled. Finally, the inhibition of

prepotent responses is thought to inhibit more dominant, habitual behavioural responses

particularly when such responses are not considered to be optimal or appropriate for the

present task. It is acknowledged that West’s (1996) model encompasses a much broader

range of cognitive functions than other models of ‘executive functions’. However, as


previously mentioned Lezak et al. (2004) describes the structure of the frontal lobe as

being associated with not only higher-order cognitive functions, but also the facilitation

of memory functions and retrieval strategies. In addition, Fuster (2000) considers that it

would be erroneous to localise various executive functions to the prefrontal cortex alone

and that only part of the networks involved in memory abilities can be localised to this

region. Both retrospective memory and prospective memory abilities are described to

complement each other at the service of frontal executive function playing the critical

role in the mediation of contingencies of action across time.

There have been a number of different measures designed and utilized to capture

the different components highlighted in this model. The following section discusses an

approach in the measurement of each of these domains guided by West’s (1996)

theoretical model of executive function, as well as a comprehensive investigation in

evaluating the validity of the theoretical constructs involved.

Num (2006) evaluated the construct validity of a hierarchical model of the

executive functions proposed by West (1996). In the study, participants were

administered a battery of neurocognitive tests individually selected based on the

theoretical concepts of the individual processes outlined in West’s model. The study

utilised the Zoo Map task from the Behavioural Assessment of the Dysexecutive

Syndrome test battery (BADS; Wilson, Alderman, Burgess, Emslie, & Evans, 1996), a

modified version of the Self-Ordered Pointing Task (Bryan & Luszcz, 2001), and the

Modified Six Elements task also from the BADS, in order to assess the construct of the

temporal organisation of behaviour. Retrospective memory was assessed using memory

for items from the Zoo Map task, recall of items from the Self-Ordered Pointing Task,

and a measure of working memory called the Reading Span test (Daneman & Carpenter,

1980). Prospective memory was assessed using both event-based and time-based tasks


which have been used in previous research aimed to measure this particular cognitive

construct (Einstein, McDaniel, Richardson, Guynn, & Cunfer, 1995; Park, Hertzog,

Kidder, Morrell, & Mayhorn, 1997; Smith & Bayen, 2005). Interference control was

assessed using the Symbol Search subtest of the Wechsler Adult Intelligence Scale –

Third Edition (WAIS-III; Wechsler, 1997), and the Letter Cancellation test (Diller, Ben-

Yishay, Gerstman, Goodkin, Gordon, & Weinberg, 1974). The inhibition of prepotent

responses was measured using the Stroop test (Dodrill, 1978), a modified version of the

Rule Shift card test from the BADS, and the Trail Making Test from the Delis-Kaplan

Executive Function System test battery (D-KEFS; Delis, Kaplan, & Kramer, 2001).

Results of the study demonstrated that measures of the temporal organisation of

behaviour, retrospective memory, prospective memory, interference control and the

inhibition of prepotent responses significantly correlated within each of the constructs

tested. However, it was also found that only retrospective memory performance

predicted temporal organisation of behaviour performance after controlling for the

effects of fluid intelligence. Through factor analysis these measures were compared in

order to determine whether the pattern of results served to support West’s hierarchical

model of executive function. Overall, results of the study suggested that ‘executive

functions’ operate as a group of individual, though related, functions. It was also found

that performance on these functions were found to be independent of performance on a

measure of fluid intelligence, suggesting that such functions were distinct from general

intellectual ability. Findings of the study were in support of West’s (1996) theoretical

hierarchical model of executive function. These findings are particularly relevant to the

current study as previous reseach investigating the executive functioning of

schizophrenia patients with cannabis use appear to fall short of examining the range of

abilities that have been considered to be reflective of the executive function construct as


a whole. It should be noted that this particular testing protocol has also yet to be utilised

among clinical samples.

Damasio’s somatic marker hypothesis. Taking a different perspective,

Damasio’s ‘somatic marker hypothesis’ model (Damasio, 1995; Damasio, Everitt, &

Bishop, 1996; Damasio, Grabowski, Frank, Galaburda, & Damasio, 1994)

conceptualises the role of frontal lobe functions in emotion and interpersonal behaviour,

specifically in relation to reasoning and decision-making. It was considered by Damasio

that emotion is mediated by the prefrontal regions, via the complex links found between

the cortical (which involve the ventromedial cortex) and subcortical (which involve the

mediodorsal nucleus of the thalamus, the amygdala, and the hypothalamus) linkages.

This model considers and emphasizes the ‘hot’ or emotional-related component of

executive function and its associated relationship with ‘cold’ or more mechanistic

cognitive components of executive function with regard to decision-making processes

and the development and/or maintenance of social relationships. Damasio (1995)

developed the model to help explain impairments such as dramatic personality change,

emotional and interpersonal problems which are commonly seen after VPFC damage in

patients. It is thought that individuals with damage to the VPFC experience difficulties

in behaviour regulation due a reduced ability to utlise emotion-related somatic signals

which are used to ‘mark’ inappropriate behaviours. Therefore, considering the

conceptualised relationship between the prefrontal cortex and executive function,

Damasio’s model provides further insight into the construct of executive function and

its potential subcomponents.

The Iowa Gambling Task (IGT) was developed by Damasio and his colleagues

in order to test the somatic marker hypothesis (Bechara et al., 1994; Bechara, Damasio,

Tranel, & Damasio, 1997; Bechara, Tranel, & Damasio, 2000; Bechara, Tranel,


Damasio, & Damasio, 1996). Studies have shown the IGT to demonstrate sound

sensitivity in individuals with VPFC lesions. Previous research has also utilised the IGT

in the examination of cognitive function related to the frontal regions in cannabis users,

schizophrenia patients, as well as schizophrenia patients who also abuse cannabis (Mata

et al., 2008; Sevy et al., 2007; Shurman et al., 2005; Whitlow et al., 2004). However,

studies have reported that performance on ‘traditional’ measures of executive function,

such as the WCST, is poorly correlated with performance on the IGT (Ritter, Meador-

Woodruff, & Dalack, 2004; Wilder, Weinberger, & Goldberg, 1998). These findings

therefore suggest that the IGT is more sensitive in tapping into other components of

executive function which have yet to be adequately measured by more traditional tests

of executive function, and fails to be addressed through West’s (1996) model alone.

The Validity of Tests of Executive Function

One of the difficulties in the neuropsychological examination of executive

functioning (and its potential in determining corresponding rehabilitation regimes) lies

in the ability of traditional psychometric tests in providing a true and accurate

assessment of the executive functions per se (i.e., whether such tests are really

measuring what they claim to measure), as well as whether performance on such

measures relates to performance in the real world. In other words, the question is

whether commonly used psychometric measures of executive function are ‘ecologically

valid’. Although meta-analytic results have shown that performance on neurocognitive

tests have the ability to predict everyday functioning on a relatively global scale, more

often than not, the typical standardised neuropsychological tests used to conduct such

assessments are selected on the basis of their ability to detect pathology (Green et al.,

2000). Therefore, it is plausible that such measures may not truly capture the essence of

the demands and routines involved in everyday life. Wilson and colleagues (1997)


emphasised that some clinical patients who exhibit deficits in day-to-day functioning

can also demonstrate normal performance on executive functioning tests. Accordingly,

it seems reasonable that the evaluation of the ecological validity of executive

functioning tests as an empirical research target has specific clinical relevance to the

schizophrenia population.

Many common neuropsychological test approaches involve presenting the

subject with a single explicit task at any one time, relatively short task trials, prompts or

instructions by the examiner regarding when to initiate behaviour, and some type of

indication of the intended/expected successful outcome (Shallice & Burgess, 1991).

However, through the process of administering a set of standard instructions and scoring

systems in such approaches, it is reasonable to consider that these approaches may not

adequately correspond to the naturalistic demands involved in everyday life. The use of

quantitative approaches in research is mainly thought to capture an individual’s

performance at either the pathological or impairment level, but fails to tap into more

clinical concerns such as functional everyday life deficits (Whyte, Polanski, Cavallucci,

Fleming, Lhulier, & Coslet, 1996). It is considered that much of the discrepancy

between cognitive performances demonstrated in formal testing and real-world

situations could possibly be explained by the notion that such testing contexts provide a

structured and often well-controlled environmental setting for the examinee (Chaytor &

Schmitter-Edgecombe, 2003; Lezak et al., 2004; Manchester, Priestley, & Jackson,

2004, Shallice & Burgess, 1991; Whyte et al., 1996). Due to these characteristics, many

traditional tests of executive function are said to lack ecological validity (Acker, 1990;

Cripe, 1996), and consequently may fail to sufficiently assess the complex interplay of

behaviours that are involved in ‘real-world’ living.


A general limitation involved in standardised test procedures is that such

experimental contexts strongly prompt the participant toward exhibiting certain

behaviours. It is therefore plausible that situations that require behaviours such initiative

or volition may not be able to adequately be assessed and represented by such measures.

This notion is particularly relevant to the assessment of executive functioning, which

can be conceptualised as reflecting not solely what an individual does, but how they do

it as well as whether or not the individual exhibits the behaviour in the first place (Lezak

et al., 2004). It is thought that measures sensitive to executive dysfunction should

involve those contexts which are ill-structured and capture strategic planning, and

retrospective memory and prospective memory abilities, particularly when considering

the relationship between performance on such measures and performance in daily living

(Burgess, Veitch, de Lacy Costello, & Shallice, 2000; Fortin, Godbout, & Braun, 2003;

Godbout, Grenier, Braun, & Gagnon, 2005; Goel et al., 1997). Due to the structured and

standardised nature of many traditional executive function tests, it is argued that such

measures may not be adequate in their sensitivity to detect true executive deficits, such

as the ability to deal with multi-task demands that are required for day-to-day

functioning (Burgess, 2000; Shallice & Burgess, 1991).

‘Traditional’ tests of executive function. Typical measures which have been

deemed to assess executive abilities are usually those which have been found to be

related and sensitive to dysfunction of the frontal lobe. Examples of such measures

include the WCST (Milner, 1963). Deficits have also been shown on other widely used

measures of executive functioning such as the TMT (Reitan, 1958), verbal fluency

(Allen, Liddle & Frith, 1993; Benton, 1968), and the Stroop test (MacLeod, 1991;

Stroop, 1935). However, it is considered that the construct validity of many traditional

tests of executive function, such as the WCST, verbal fluency, the Tower of Hanoi, and


the TMT, is not well established despite their extensive use in neuropsychological

assessment (Kafer & Hunter, 1997; Phillips, 1997; Rabbit, 1997). In the schizophrenia

literature, the WCST is the single most commonly applied measure in the investigation

of executive functioning (Reicheberg & Harvey, 2007). However, despite its

widespread use not all schizophrenia patients have been found to demonstrate deficits in

WCST performance (Braff et al., 1991; Goldstein, 1990; Goldstein, Beers &

Shemansky, 1996). Reports of normal performances in schizophrenia patients on the

WCST further suggests that the construct of executive function is not only complex, but

comprises a range of different components. Therefore, the ability of psychometric

measures to fractionate the executive functions seems crucial in order to be more

sensitive to individual variation in executive functioning performance. Considering the

importance of executive functions in schizophrenia, previous research has failed to

employ a range of neurocognitive measures aimed at tapping into the various

subcomponents theorized to be involved in the construct of executive function. It also

appears that the construction of many commonly used measures of executive function

has been fundamentally atheoretical in nature. The selection of such tests which are

hypothesised to assess this neurocognitive domain more often than not, rely on their

apparent face validity which is largely subjectively based (Salthouse, Atkinson, &

Berish, 2003). New research in this area should endeavour to take into account this issue

as an important methodological consideration when assessing a neurocognitive domain

that is as complex and multi-faceted as executive function.

However, there are some more theoretically-driven psychometric measures that

exist which have been specifically developed in order to attempt to tap into the

processes conceptualised be involved in executive function and validated to assess their

reliability in the detection of executive dysfunction. Such tests include the Tower of


London test (Shallice, 1982), the Cognitive Estimates Test (Shallice & Evans, 1978),

and the Self-Ordered Pointing Task (Petrides & Milner, 1982; Bryan & Luszcz, 2001).

However, establishing the construct validity of such tests has not been without

difficulty. For example, Kafer and Hunter (1997) utilised a structural equation

modelling approach in order to evaluate the relationship among four tests

conceptualised to measure planning/problem-solving abilities (i.e., the Tower of London

test, the Six Element Test, the Twenty Questions Test, and the Rey Complex Figure

Test) and the latent construct of planning/problem-solving. Findings indicated that an

adequate statistical model was not able to be estimated in their analyses. Such results

therefore served to question the construct of planning/problem-solving, as well as

problems were specifically identified with the psychometric structure of the Tower of

London test. O’Carroll, Egan and MacKenzie (1994) conducted a study in order to

provide normative data for the Cognitive Estimates Test from a representative sample of

the general population. A Principal Component Analysis resulted in a five-factor

solution, suggesting that the test does not measure a single factor. In addition, while the

test demonstrated adequate inter-rater reliability, it was also found to have poor internal

reliability. From the results obtained, the investigators concluded that the Cognitive

Estimates Test is psychometrically unsatisfactory. Issues in establishing the validity of

measures has also been the case where various classic tests of executive function (e.g.,

WCST, COWAT/phonemic verbal fluency, and the Stroop test), have shown sensitivity

to frontal lobe lesions, but fail to demonstrate specificity to frontal lobe pathology alone

(Alvarez & Emory, 2006).

Despite the importance of the various theoretical models of executive function, it

was not until approximately the last two decades that specific constructs were

incorporated into the development of clinical and experimental assessments of executive


functions. For example, the Behavioural Assessment of the Dysexecutive Syndrome

(BADS) is an executive function test battery that is specifically designed to assess the

everyday deficits in executive functioning among clinical groups (Wilson, Alderman,

Burgess, Emslie, & Evans, 1996) and was developed as a modification of the Six

Elements Test and Multiple Errands Test (Shallice & Burgess, 1991). It consists of six

subtests aimed at measuring different facets of executive functioning such initiation and

task implementation, as well as planning and cognitive flexibility. However, this test

battery as a whole has been limited in its use when assessing schizophrenia patients

(Evans, Chua, McKenna, & Wilson, 1997; Katz et al., 2007; Krabbendam, de Vugt,

Derix, & Jolles, 1999). Findings from Katz and colleagues’ (2007) study confirmed the

ecological validity of the BADS test battery in its sensitivity and predictive validity in

determining ‘real-world’ functioning in individuals with schizophrenia.

Another major difficulty related to the assessment of the executive functions lies

in the ability for performance on one particular test of executive function in not only

having predictive value in performance on another test of executive function, but also in

coping and performance in the functional domains of ‘real world’ contexts (Burgess,

1997; Burgess et al., 1998). Due to this issue, reduced performance on executive

function tests may be due to many different reasons and could be independent of actual

executive dysfunction. It is also possible that individuals may demonstrate adequate

performance on such measures and still experience significant difficulties in their ability

to navigate the complex demands of day-to-day life activities (Shallice & Burgess,

1991). Therefore, incorporating more ‘real-world’ characteristics into specific

assessment measures has been considered imperative when attempting to make progress

in this area (Schwartz, Reed, Montgomery, Palmer, & Mayer, 1991; Shallice & Burgess,

1991). Particular assessment methods have been developed to attempt to achieve this


such as in the Modified Six Elements test from the BADS test battery (MSE; Evans et

al., 1997; Wilson, Alderman, Burgess, Emslie, & Evans, 1996). The MSE aims to assess

planning abilities by allowing subjects to complete several tasks and navigate their work

according to their own self-driven plan, as well as a set of prescribed rules. This test has

been shown to demonstrate superior ecological validity, as well as sensitivity, in

comparison to other subtests in schizophrenia patients (Evans et al., 1997). There

appears to be many factors to take into account when considering the more precise and

effective measurement of specific cognitive domains, particularly in the case of those

conceptualised to be multi-faceted and fractionable in nature, such as executive

function.

Assessing Functional Outcome

A number of methods have also been employed to assess functional outcome

status. In order to achieve a more ecological approximation in the measurement of

executive functions, several approaches have been taken such as the use of

questionnaires (Bennett, Ong, & Ponsford, 2005; Broadbent, Cooper, Fitzgerald, &

Parkes, 1982; Burgess, Alderman, Wilson, Evans, & Emslie, 1996), or through

laboratory tasks approximating real-life situations, such as those tasks used in the

BADS (Evans et al., 1997; Katz et al., 2007; Krabbendam et al., 1999; Wilson et al.,

1996; 1998). Other means involve observing and assessing the behaviours demonstrated

by patients in daily activity simulations (Knight, Titov, & Crawford, 2006; Zalla,

Plassiart, Pillon, Grafman, & Sirigu, 2001; Zhang, Abreu, Seale, Masel, Christiansen, &

Ottenbacher, 2003). In a study by Rempfer, Hamera, Brown and Cromwell (2003), the

relationship between performance on various cognitive tests and performance on a

functional outcome measure, namely the Test of Grocery Shopping Skills (TGSS), was

examined. The TGSS evaluates the performance of shopping skills within the natural


context of a grocery store, with the measure yielding three outcome scores (1) accuracy;

(2) redundancy (a measure of shopping efficiency); and (3) time. Associations were

found between shopping accuracy and measures from the first two trials of the Stroop

test, namely word reading and colour naming. There were also correlations between

accuracy and verbal recall on the Rey Auditory Verbal Learning Test (Rey, 1964) and

perseverative errors on the WCST. In addition, ‘redundancy’ while shopping was found

to be significantly related with poorer performance on three measures of executive

functioning (WCST total correct and perseverative errors, verbal fluency/FAS, and

performance on the colour-naming and colour-word trials of the Stroop test). Total time

on the Letter Cancellation test was also correlated with redundancy. Verbal memory

was shown to be associated with both shopping accuracy and redundancy. However,

while this investigative approach provides a good demonstration of the ecological

validity of certain standardised psychometric tasks, the results of this study were limited

specifically to the particular skill of independent living that was simulated (e.g., grocery

shopping). Therefore, addressing real-world functioning in a more precise manner by

making distinctions amongst the various aspects of social and community living

activities are warranted.

Keefe and colleagues (2006) examined the relationship between cognitive

performance in schizophrenia with functional capacity and functional outcome. In their

study, functional capacity was assessed using the UCSD Performance-based Skills

Assessment (UPSA; Patterson, Goldman, McKibbin, Hughs, & Jeste, 2001) and ‘real-

world’ functional outcome was measured using the Independent Living Skills Inventory

(ILSI; Menditto, Wallace, Liberman, Wal, Jones, & Stuve, 1999). The UPSA requires

patients to perform a number of tasks reflective of a range of skills considered important

for functioning in the community. Patients are then rated on their performance on these


tasks. The ILSI is a functional assessment tool which also aims to measure an

individual’s competence in a broad range of skills considered pertinent for successful

autonomous community living. Ratings are made on the basis of an interview with the

patient or the reports/observations of care givers. Findings from the study indicated that

cognitive performance (as assessed by the Brief Assessment of Cognition in

Schizophrenia (BACS); Keefe, Goldberg, Harvey, Gold, Poe, & Coughenour, 2004),

was found to be significantly correlated with both functional capacity and real-world

functional outcome. Results also suggested that measures of cognition and functional

capacity significantly predicted variance in real-world functional outcome. However,

only the measures of cognition independently accounted for significant variance in real-

world functional outcome, when compared to the contribution of performance-based

functional skills. The authors concluded that the latter measure appeared to fail to

uniquely contribute to real-world outcomes above and beyond that which was accounted

for by the cognitive performance measures. Results of the study are suggestive that

performance-based skills assessment may not necessarily have better predictive capacity

when considering ‘real-world’ functional outcome in schizophrenia in comparison to the

cognitive measures used.

While there are a range of methods in assessing functional outcome, it is

acknowledged that such an assessment can be difficult to achieve through observation

of real-world performance on activities in a research setting. In addition, the observation

of performance on specific daily activities is not only time consuming, but is limited to

the assessment of only the activity or task in question. While skill demonstrations and

task simulations have their important merits, the number and wide range of daily skills

thought to be required in successful community functioning would render such an

approach difficult when attempting to make a thorough assessment. Thus, a critical


advantage of the questionnaire method (e.g., the ILSI) is that it permits a more

comprehensive assessment of functional outcome across a variety of independent living

skill domains while at the same time allowing for a more resource efficient approach as

opposed to task simulation methods.

The Current Study

It has been widely established that cognitive impairment is a fundamental

characteristic of the illness of schizophrenia. In addition, the cognitive domain of

executive function is not only considered to be particularly implicated, but is also shown

to be significantly related to functional outcome. As cannabis is a commonly used

substance of abuse in schizophrenia, but in addition has also been found to contribute to

detrimental effects on the illness’ presentation, the examination of the relationship

between cannabis use, schizophrenia and neurocognitive performance has clinical

significance. There is already substantial evidence comparing schizophrenia patients

with non-schizophrenia controls, demonstrating deficits across different executive tasks.

Similarly, there is also extensive research demonstrating executive function impairment

associated with cannabis use. However, there have been some mixed and surprising

findings in relation to the associations between schizophrenia, cannabis use and

neurocognition. Contrary to expectation (which has been largely based on the premise

of well established cognitive deficits associated with the illness of schizophrenia, as

well as cannabis use alone, thus leading to a hypothesis of additive effects), some of the

findings that have emerged over the years have suggested that cannabis use in

schizophrenia is associated with better neurocognitive performances. Factors related to

variability in sample characteristics, neurocognitive assessment protocols, research

design, and failure to adequately control for potential confounds have been considered

as possible contributors to the inconsistent results.


Many previous studies have employed measures of executive function which are

adopted from frontal lobe neuropsychological paradigms based on lesion studies. On the

whole, it appears that the majority of schizophrenia research regarding cognition has

failed to adopt comprehensive enough theoretical approaches and assessment

methodologies in order to adequately tap into the range of executive abilities, and

therefore fall short of achieving the successful fractionation of the executive function

system. The current study employed the use several theory-driven selected tests of

executive function guided by West’s (1996) hierarchical model of executive function.

The current study proposes to apply a theoretical model of executive function, in

particular West’s model, to examine the executive functioning of schizophrenia patients

with a cannabis use history. A verbal fluency and an emotion-based decision-making

measure were also included in the present study. Verbal fluency (particulary letter

verbal fluency) has been shown to be sensitive to frontal dysfunction (for review, see

Parker & Crawford, 1992) and deficits on this measure is found to be consistently

observed in patients with schizophrenia (Chen et al., 2000, Crawford, Obonsawin,

Bremner, 1993, Gruzelier, Seymour, Wilson, Jolley, & Hirsch, 1988). In addition,

emotions are known to play a key role in decision-making processes (Bechara et al.,

1997). These additional components do not appear to be accounted for in West's model.

Therefore, this assessment approach will permit us to examine executive functioning

with a range of measures sampling both the conceptualised mechanistic and emotion-

related components of executive function.

Considering the inconsistency in the literature regarding the assessment of

executive function, it is important to evaluate and further develop the theoretical

conceptualisation of this neurocognitive domain that will in turn lead to the better

refinement, clarification and successful measurement of the construct. As it has been


shown in previous research that there are executive functioning deficits in individuals

with schizophrenia, as well as in individuals who use cannabis, it is important to

ascertain whether cannabis use in schizophrenia is associated with poorer executive

functioning and hence greater impairment and poorer adjustment in everyday life. While

previous studies have examined the relationship between executive function and various

aspects of functional outcome in schizophrenia, there appears to be a paucity of a

comprehensive examination of the the link between performance on tests of executive

function and functional outcome measures amongst the schizophrenia with cannabis use

population.

In the first part of the present study, the aim was to identify the relative

differences in executive functioning associated with cannabis use in schizophrenia

compared to those which are associated with cannabis use alone. Exploring the pattern

of executive functioning in schizophrenia patients with cannabis use and non-

schizophrenia controls with a similar cannabis use history will help to tease out such

differences. Since performance on executive function tests is rarely evaluated for its

'real-world' significance, in the second part of the study another aim was to examine the

relationship between performance on the tests selected in the current research and

ratings on a measure of ‘real-world’ functional outcome. This will enable not only the

comprehensive evaluation of executive functioning in schizophrenia patients with a

cannabis-use history, but also allow for the examination of whether performance on a

range of tests of executive function serve as effective predictors of performance in

specific ‘real-world’ functional outcome domains. This in turn, will permit an

evaluation of whether such executive function measures are 'ecologically valid' (i.e.,

reflective of 'real world' abilities and adjustment). The assessment of this clinical

population with ecologically valid measures may therefore help to better inform and


guide future treatment planning. This may be achieved by being able to more precisely

identify the various executive functioning components thought to more closely relate to

the specific functional skills that are required for successful independent living. From

the results of the study, it is hoped that through the neurocognitive sub-typing of

individuals with schizophrenia who use cannabis, specific cognitive rehabilitation

and/or behavioural strategies can be better directed and consequently help to assist in

the prediction of those who are more likely to successfully respond to such intervention.

Hypotheses. The aims of the current study will thus be achieved by dividing the

study into two parts. Part A of the study specifically aimed to examine the relative

differences in executive functioning associated with cannabis use in schizophrenia

patients, in comparison to individuals with no psychiatric or mental illness diagnoses

with a similar pattern of cannabis use. It was predicted that schizophrenia patients with

cannabis use will demonstrate poorer performance in constructs of executive

functioning, compared to healthy controls with a similar cannabis use history. Further,

performances falling greater than 1.0 standard deviation below normative mean criteria

will be described in schizophrenia patients with cannabis use, compared to controls. In

addition, it was hypothesised that the discontinuation or abstinence from cannabis use

will be associated with the recovery of executive function (i.e., ‘non-current users’ will

demonstrate significantly better performance on executive function measures than

‘current’ users). It was also predicted that former users who have ceased their cannabis

use for a longer period of time will have significantly better executive function

performance, in comparison to those individuals who have ceased cannabis use for a

shorter period of time.

Part B of the study aimed to further our understanding of the functional

outcome correlates associated with the executive functioning of schizophrenia patients


with cannabis use, relative to matched-control subjects with a similar cannabis use

history. The investigation into the relationship between the executive function

components belonging to West’s (1996) model and functional outcome is exploratory in

nature. However, due to reports of a significant association between executive function

and functional outcome in the literature, it is predicted that executive function scores

will have a significant relationship with functional outcome ratings. More specifically, it

was hypothesised that executive function scores will have significant predictive ability

in relation to functional outcome ratings.

Method

Participants

Participants included in the current study were aged between 18 and 55 years.

Schizophrenia patients were recruited as outpatients from public mental health services

in South Australia. Clinical participants were eligible for the study if they had a current

diagnosis of schizophrenia according to the DSM-IV (American Psychiatric

Association, 2004), which was verified by the patient’s clinical file information upon

their consent. Control subjects were eligible for the study if they did not have any

current psychotic, anxiety, or mood disorder diagnoses. While this was based on the

self-report of the healthy control group, subjects were also screened for elevated and

clinically significant levels of depression, anxiety and stress symptoms (see below for

further detail regarding the determination of the presence of group differences in

depression, anxiety and stress symptoms). An overall sample of 76 was recruited for the

study. However, data from 4 participants in the schizophrenia group were excluded

from the study due to these individuals not having a reported cannabis use history. Due

to the total sample size of this subgroup being too low, the maintenance of these cases


in the final data set was considered insufficient for meaningful between-subject

statistical analyses to be conducted. Data from an additional participant from the

schizophrenia patient group who did however have a reported history of cannabis use,

was also excluded due to the participant not being able to complete the full

neurocognitive battery. It was observed by the researcher that the participant

demonstrated significant difficulty in being able to understand the instructions of the

psychometric measures and was therefore assessed to be ineligible for the continuation

of testing. Data from two schizophrenia patients with cannabis use were also excluded

from the study, due to these participants not being able to be adequately matched to a

corresponding control subject on the matched variables. In addition, data from 13

otherwise healthy control subjects with cannabis use were also excluded from the study,

due to these participants not being able to be adequately matched to a corresponding

schizophrenia patient on the matched variables. The final sample included 28

individuals with schizophrenia (both former and current users) who had a regular

cannabis use history and 28 matched-controls (both former and current users) with a

similar cannabis use history. The process of recruiting matched controls involved

finding a suitable matched pair for an already recruited patient subject. Premorbid IQ

was matched with a suitable pair within +/- .05 standard deviation (SD) of the

schizophrenia patient’s score. The age, years of education, severity/quantity, duration,

and time since cessation variables were matched with a suitable pair in the control

groups within +/- 1.0 SD of the schizophrenia patient’s score. The frequency variable

was matched with a suitable pair according to frequency group category (i.e., light users

≤ 2 times per week; heavy users ≥ 3 times per week). Gender was equally matched

between groups. While the +/- 1.0 SD matching criteria was acknowledged to be much

less conservative than a +/- 0.5 SD matching criteria, it was considering necessary due


to the large variability found in such variables and consequently attempting to match

within +/- 0.5 SD would have made the process increasingly more difficult considering

the timeframes and resources available. However, independent sample t-tests indicated

that no significant differences were found between groups on the cannabis use

parameters (all p’s > .05), suggesting that the two groups were well matched on all of

these indicators of cannabis use. Participants were considered to be regular cannabis

users if they used cannabis for more than 2 years duration, with a frequency of use of

one or more days per week. Further, 34 participants (17 schizophrenia patients and 17

matched-controls) who reported regular cannabis use in their history, were currently

abstinent at the time of testing. In addition, 22 participants (11 schizophrenia patients

and 11 matched-controls) who reported to be regular users of cannabis were current

users at the time of testing. All participants were required to provide written informed

consent, as well as have the physical capacity to participate in cognitive assessment.

Participants with ages falling outside the range of 18 to 55 years, who had any

other mental illness diagnoses (other than schizophrenia for the patient group only), a

medical history of head or brain injury, a history of neurological disorder, or an

intellectual or developmental disability, were excluded from the study. Subjects who

regularly used other drugs of dependence or had a history of alcohol abuse/dependence

were also excluded from the study. This criteria was assessed in a structured interview

(see Appendix A) via self-report. Participants were required to abstain from cannabis

use for at least 24 hours prior to testing (if still a current user), as well as abstain from

the consumption of caffeine and nicotine use within 1 hour of testing. Adherence to the

24-hour and 1-hour abstinence period was assessed using self-report. Participants were

also required to be proficient in understanding and speaking the English language. All


participants were given a $25 Coles-Myer voucher as a token of appreciation for their

participation in the study.

The sociodemographic characteristics of the two groups are detailed in Table 1.

Independent sample t-tests indicated that no significant differences were found between

groups on the sociodemographic variables (all p’s > .05), suggesting that the groups

were well matched on all of these characteristics. No significant difference was found

between groups in nicotine use (p > .05). The groups also did not significantly differ on

self-reported depression, anxiety or stress symptoms (as measured by the Depression

Anxiety Stress Scales (DASS); S. H. Lovibond & P. H. Lovibond, 1995) (all p’s >.05).

It was noted that the between group differences in reported anxiety symptoms

approached significance (p = .052). However, the mean ratings for the schizophrenia

group fell in the moderate range for depressive and anxious symptomatology and in the

mild range for stress symptomatology. Mean ratings for the matched-controls group fell

in the mild range for depressive, anxious and stress symptomatology. A chi-square test

for goodness of fit examining symptom categories (as assessed by the the Structured

Clinical Interview for the Positive and Negative Syndrome Scale (SCI-PANSS); Kay,

Fiszbein & Opler, 1987) indicated that there was no significant difference in the

proportion of schizophrenia patients with cannabis use, falling in either the positive

symptom subtype or negative symptom subtype category, χ2(1, N = 27) = .333, p= .564,

w = .111. All but one schizophrenia patient were taking antipsychotic medications. Four

patients were taking typical antipsychotics, 16 were taking atypical antipsychotics, 7

were on combined therapy (i.e., taking both typical and atypical antipsychotic

medications), and 1 patient was currently not taking any medication.


Table 1. Sociodemographic characteristics of the sample

Total

(N=56)

Schizophrenia Patients

(n=28)

Matched Controls

(n=28)

Mean (SD) Mean (SD) Range Mean (SD) Range

Age 34.50 (7.20) 34.57 (7.71) 23-51 34.43 (6.78) 25-49

Male:Female 38:18 19:9 19:9

Years of

Education

11.83 (1.77) 11.77 (2.05) 8.0-16.0 11.89 (1.47) 9.0-14.0

Estimated

Premorbid IQ

99.09 (6.17) 98.75 (7.02) 82-108 99.43 (5.31) 88-107

Nicotine Use 11.21 (10.76) 13.50 (13.16) 0-40 8.93 (7.19) 0-25

Frequency

(days per week)

5.43 (2.08) 5.61 (2.15) 1.0-7.0 5.25 (2.03) 1.0-7.0

Severity

(grams)

1.42 (1.03) 1.44 (1.21) .25-5.0 1.39 (.82) .25-4.0

Duration

(years)

13.14 (8.85) 13.57 (10.04) 2.0-38.0 12.71 (7.64) 3.0-33.0

Time Since

Cessation

(years)

3.63 (5.40) 3.71 (5.74) .00-28.0 3.55 (5.14) .00-25.0

DASS

Depression 13.18 (11.23) 16.00 (13.84) 0-42 10.36 (6.99) 0-20

Anxiety 9.98 (7.80) 12.00 (9.36) 1-30 7.96 (5.27) 0-14

Stress 12.88 (8.57) 14.21 (10.02) 0-34 11.54 (6.74) 0-24

PANSS

Positive 18.25 (6.97) 7-36

Negative 18.79 (5.71) 10-33

General 39.18 (12.07) 16-69

Composite -.54 (4.84) -9-12

Recruitment

Advertisements (see Appendix B: (i) and (ii)) were distributed to the Royal

Adelaide Hospital, the Queen Elizabeth Hospital, Lyell McEwin Hospital Service,

Flinders Medical Centre, various local public mental health service locations (Port

Adelaide Mental Health Service, Beaufort Clinic, Southern Mental Health Service,

Adaire Clinic), a community-based mental health organisation (The Mental Illness

Fellowship of South Australia), mental health community centres and supported

residential facilities, requesting for patient volunteers willing to participate in the

current research study. The contact details of the researcher were provided for any

prospective patient participants to contact in order to express their interest. The

advertisement also informed potential participants that a form could alternatively be

completed and posted at the reception desk (found in each location) in order for the


participant to leave their contact details should they wish to be contacted by the

researcher instead. An information sheet about the study (see Appendix C) was then

provided through reception, upon request. In addition, the researcher attended the local

clinics on a arranged basis in order to be available to talk to individuals who were

interested in participating in the study.

Advertisements (see Appendix D) were also posted in various locations in the

local community (e.g., shopping/public community centre notice boards) requesting for

otherwise healthy control volunteers willing to participate in the research study.

Potential control subjects were initially screened using a telephone interview gathering

demographic details and information pertaining to patterns of cannabis use. Once

individuals were deemed eligible for inclusion in the study, an appointment time was

scheduled to attend a testing location in order to be assessed and an information sheet

(see Appendix E) was then sent out to the participant via post.

The current study employed a matched-control design to ensure that any

individual differences occurring between groups (outside of the variables of interest),

were controlled for. Due to the variation in indices of cannabis use (i.e., frequency,

severity/quantity, duration and time since last use), the interpretation of results based on

comparisons between groups is made more difficult. Therefore, the current study aimed

to take these indices into account when matching control subjects. Control subjects were

matched with schizophrenia subjects based on age, gender, years of education,

estimated premorbid IQ, frequency of cannabis use, severity of cannabis use, duration

of cannabis use and time since cannabis use cessation.

Measures

Demographics. The demographic information gathered included age, gender,

years of education, medical history (e.g., head/brain injury, neurological conditions,


stroke, cardiac problems etc.), medication, frequency, severity/quantity, duration of

cannabis use, time since cessation (if relevant), as well as other types of drugs used and

their patterns of use. Average days of use per week, average grams consumed per using-

day (where 1 joint was estimated to be .5 grams (Zeisser et al., 2011); and 1 cone was

estimated to be .25 grams), years of use, and years since last use were determined as

measures of frequency, severity/quantity, duration and time since cessation,

respectively. This was assessed through the structured interview conducted prior to

neurocognitive testing. This information was also gathered to assess the exclusion

criteria.

Clinical symptoms. To assess the positive and negative symptom profile of the

schizophrenia group, the Structured Clinical Interview for the Positive and Negative

Syndrome Scale (SCI-PANSS) was administered. The SCI-PANSS was used to

evaluate the presence and severity of positive, negative and general symptoms of

schizophrenia. Thirty items were rated on a 7-point scale from 1 = absent to 7 = extreme

and total scores were then calculated for the positive, negative and general symptom

areas. High internal reliability (r = .73 - .83) (Kay et al., 1987; Kay, Opler, &

Lindenmayer, 1988) is reported across each scale of the instrument.

To assess whether there were any significant differences between groups in

affective state the Depression Anxiety Stress Scales (DASS; S. H. Lovibond & P. F.

Lovibond, 1995) was administered. The DASS is divided into 3 scales (constituting 14-

items each) which correspond to the syndromes of depression, anxiety and stress. Each

syndrome has been found to be correlated, but distinct from each other (P. F. Lovibond

& S. H. Lovibond, 1995; S. H. Lovibond & P. F. Lovibond, 1995). Subjects were asked

to indicate the presence of symptoms occurring over the past week only, with responses

to the items based on a 4-point severity/frequency scale, ranging from ‘did not apply to


me at all’ (0) to ‘applied to me very much, or most of the time’ (3). The DASS has been

reported to have internal reliability coefficients of r = .87 - .95.

Neuropsychometric battery. Standardised measures of estimated premorbid

intelligence and executive function were chosen from the Behavioural Assessment of

the Dysexecutive Syndrome (BADS; Wilson et al., 1996), the Delis-Kaplan Executive

Function System (D-KEFS; Delis, Kaplan, & Kramer, 2001), the Wechsler Adult

Intelligence Scale – Third Edition (WAIS-III; Wechsler, 1997), and also included tests

modified or developed by previous researchers (e.g., Num, 2006). Considering a

number of tests used in the current study originate from well validated test batteries, the

validity of the batteries themselves will be discussed first. Individual test information

will then be further discussed in the sections following.

The main purpose of the BADS battery was to predict the presence and severity

of everyday executive problems amongst brain injured groups. The technical manual

reports correlations (using Pearson’s method), between the BADS profile score, each of

the six individual subtests, age, the National Adult Reading Test - Second Edition

(NART-II; Nelson & Willison, 1991), and WAIS FSIQ, with others’ and self-ratings on

the Dysexecutive Questionnaire (DEX) for a brain injured patient group. The degree of

insight, which is measured by the discrepancy between others’ and self-ratings is also

reported. Significant moderate negative correlations between each of the six individual

subtests and others’ ratings of executive problems were found. The negative correlations

indicate that satisfactory performance on any subtest in the BADS is indicative of low

ratings by significant others who know the patient well regarding the presence or

severity of executive problems, demonstrating the construct and predictive validity of

the BADS tests in detecting every day executive problems. Katz and colleagues (2007)

examined the construct validity and sensitivity of the BADS in differentiating between


different types of schizophrenia patients. The predictive validity of the BADS with

regard to functional outcomes within the outpatient group was also examined.

Performances were compared between adult schizophrenic inpatients who were in an

acute episode of the illness, adult schizophrenic outpatients who were in the more

chronic stages of the illness, and healthy control subjects. Results of the study showed

not only significant differences between schizophrenia patients and control subjects, but

also between both of the schizophrenic patient groups such that patients in the

outpatient (chronic) group demonstrated greater executive function deficits. It was also

found that within the outpatient group that performance on the BADS significantly

predicted Independent Activities of Daily Living (IADLs) and communication outcome

areas. These results were demonstrated to be beyond that which was accounted for by a

measure of basic cognitive skills. Not only do the results of the study show the BADS to

be a valid measure in the assessment of executive function of individuals with

schizophrenia by distinguishing between patients and healthy subjects, but in addition

distinguishing between patients with differing illness phases.

The technical manual for the D-KEFS (Delis et al., 2001) reports evidence for

the validity of the D-KEFS measures. The range of tests included in the current study

(see below for further discussion of specific tests used) are those which were either

developed by the test authors or modified versions of well-established, standardised

executive function measures. The modified D-KEFS instruments (i.e., versions of the

Stroop test, Trail Making Test, verbal and design fluency tests, Tower Task, the

Twenty-Questions test, and proverb interpretation) have demonstrated validity

evidenced across a number of neuropsychological studies spanning over 50 years.

Reviews of these studies are reported in Lezak (1995, cited in Delis et al., 2001, p. 47)

and Spreen and Strauss (1998, cited in Delis et al., 2001, p. 47). Validity studies have


also indicated that various D-KEFS measures have reasonable sensitivity in the

assessment of executive functioning of different clinical populations which include

patients with focal frontal-lobe lesions (Baldo, Shimamura, Delis, Kramer, & Kaplan,

2001; Delis, Squire, Bihrle, & Massman, 1992; Dimitrov, Phipps, Zahn, & Grafman,

1999), as well as schizophrenia (Beatty, Jocic, Monson, & Katzung, 1994; Savla,

Twamley, Thompson, Delis, Jeste, & Palmer, 2011). The current study only selected

those tests from the D-KEFS that were modifications of pre-existing, long-standing

clinical tests with proven validity.

The WAIS-III is a popular and widely used scale of intellectual ability. In a

study conducted by Dickinson, Iannone and Gold (2002), exploratory and confirmatory

analyses revealed that a four-factor model of WAIS-III performance (which was similar

to that reported by the developers of the scale), adequately fit data from a sample of

schizophrenia patients. In fact, the factor structure suggested by the developers (i.e.,

with correlated factors for verbal comprehension, perceptual organisation, working

memory, and processing speed) fit the clinical sample just as well as it did for the

comparison sample of non-clinical subjects. These results suggest the construct validity

of the scale and its subtests in the assessment of individuals with schizophrenia.

The test selections in the current study were guided by West’s (1996) model of

executive functioning and were also similar measures to those used in Num’s (2006)

study. A total of 12 tests were administered, including a measure of estimated

premorbid intelligence and 11 measures of executive functioning. All of the tests were

in paper-and-pencil format, with some verbal responses recorded on a tape recorder, and

time recorded using a stopwatch. All scores from the standardised tests used were

converted to standard scores based on norms which were reported in each test manual.


Premorbid intelligence. The National Adult Reading Test - Second Edition,

(NART-II; Nelson & Willison, 1991), was administered to assess estimated premorbid

intelligence and to determine if any differences in premorbid general cognitive ability

existed between groups. The NART-II consists of a list of 50 irregularly spelt words in

the English language. In this test, the reader is required to ‘know’ the word, rather than

rely on phonology in order to be able to read it correctly (e.g., ‘topiary’). Scores

represent the number of correct responses, with higher scores representing higher

estimated premorbid intelligence. The NART test manual reports a test-retest reliability

of r = .98.

Crawford and colleagues (1992) aimed to determine whether the National Adult

Reading Test would provide a valid estimate of premorbid intelligence in a sample of

schizophrenia patients. The overall sample comprised of a group of patients who resided

in long-stay wards and a group of patients residing in the community. Schizophrenia

subjects were individually matched with healthy control subjects on the variables of

age, sex, and education. Findings from the study indicated that a significant discrepancy

was found between the two IQ measures administered, where current WAIS IQ scores

were significantly lower than NART-derived estimated premorbid IQ scores. Such

results indicated a decline in cognitive functioning was present in the sample. These

results are indicative of the NART measure providing a valid measure of estimated

premorbid IQ in a schizophrenia sample. O’Carrol et al. (1992) also found NART

scores estimated significantly higher IQ scores than a current measure of IQ (i.e., the

Wechsler Adult Intelligence Scale - Revised (WAIS-R); Wechsler, 1981) in a

schizophrenia patient sample. Results of the study were consistent with Crawford et

al.’s (1992) findings.


Executive Function

The temporal organisation of behaviour. Two measures of the temporal

organisation of behaviour were used: the Zoo Map task from the BADS (Wilson et al.,

1996), and the Modified Six Elements test also from the BADS. In the Zoo Map task,

participants were required to plan and execute a trip on a map of a zoo visiting various

locations which were specified prior to commencing the test. They were also required to

follow rules involving using designated paths with which some can be travelled along

multiple times and others only once. Other rules in the task required the participant to

begin the trip at the entrance and finish at the picnic area. Two trials of the task were

administered. The first trial is of high demand (i.e., participants are required to negotiate

the trip independently) and the second trial is of low demand (i.e., participants are given

directions as to the route required). Scores on this measure reflected overall planning

time (i.e., the time that has elapsed between the participant finishing reading the

instructions and when they began the trial), the total time to complete the trial itself, the

number of places correctly visited and number of rules correctly adhered to. A profile

score was then calculated reflecting the extent to which participants followed the correct

path sequence minus error deductions, with a low profile score reflecting poor planning

and temporal organisation of behaviour. The BADS manual reports the Zoo Map test to

have inter-rater reliabilities of r = .88 – 1.0 and a test-retest reliability correlation of r =

.39.

The Modified Six Elements test comprised of six sub-tasks which require the

solving of two sets of arithmetic problems, the identification of pictures in two sets of

picture booklets, and two verbal tasks involving dictation (e.g., one task describing the

best holiday the participant has ever experienced and the second task describing any

memorable event in their life). Participants were required to attempt each task within an


allocated 10-minute period and attempt to spend equal amounts of time on each task.

However, participants were not allowed to attempt two tasks from the same superset

consecutively (e.g., not attempting two arithmetic tasks in a row). If the participant

failed to attempt every task within the allocated 10 minutes, if they spent more than 271

seconds on a single task, or if the participant attempted two tasks from the same

superset consecutively, then errors were incurred. A profile score was calculated based

on the number of tasks completed minus error deductions. A high profile score on this

measure reflected higher planning and temporal organisation of behaviour ability. For

this test, inter-rater reliabilities of r = .90 – .97 and a test-retest reliability of r = .33 is

reported.

Retrospective memory. Retrospective memory was assessed using two

measures: memory for items from the Zoo Map task from the BADS (which assessed

task-specific retrospective memory), and the Digit Span subtest from the WAIS-III.

Measures of task-specific retrospective memory were derived from Num’s (2006) study.

For memory for items from the Zoo Map task, participants were required to remember

the places they were asked to visit in the original Zoo Map task. Scores ranged from 0 to

7, with higher scores representing higher retrospective memory performance.

In the Digit Span subtest of the WAIS-III, participants were read a series of

numbers and were required to repeat them back to the examiner in sequence. The length

of the series of numbers was increased until the participant was no longer able to repeat

them back to the examiner in correct sequence across two trials. Two forms of digit-

spans were presented, one in which the participant was required to repeat the series of

numbers forwards and the other in which the participant was required to repeat the

series of numbers in reverse order to how they were verbally presented. Each length of

number series has two trials, with participants obtaining 1 point if they passed only one


trial and 2 points if they passed both trials. The maximum score on digits forwards is 16

points and maximum score on digits backwards is 14 points. The sum of digits forwards

and backwards gave a total Digit Span score. Higher scores on this measure represented

higher retrospective memory performance. The Digit Span subtest has a test-retest

reliability correlation of r = .90.

Prospective memory. For the current study, an event-based prospective

memory task was used. This measure was also derived from Num’s (2006) study. In the

event-based prospective memory task, participants were informed at the beginning of

neurocognitive testing to place a paperclip into a plastic cup at the completion of every

second task administered throughout the testing session. Paperclips and the plastic cup

were positioned in front of the participant on the table used for test administration.

Scores ranged from 0 to 6, with higher scores reflecting higher performance on

prospective memory.

Interference control. Interference control was assessed using two measures:

the Symbol Search subtest from the WAIS-III, and the Trail Making Test from the D-

KEFS. In the Symbol Search test, participants were required to indicate whether either

of two symbols which were printed on the left of the page, were present in a row of a

five symbols printed on the right of the page. They were given a time limit of 120

seconds to complete as many rows (trials) as possible. Scores represented the number of

trials completed correctly minus the number of incorrect trials, with higher scores

indicating an increased ability to control for interference. The Symbol Search test has a

test-retest reliability correlation of r = .77.

Trial 4 of the Trail Making Test from the D-KEFS was also used to assess

interference control. In this trial of the Trail Making Test, the participant was presented

with an array of 16 circles with consecutive numbers in them and 16 circles with


consecutive letters in them. Participants were required to join the numbers and letters

with a continuous line, by alternating between them (e.g., 1-A-2-B-3-C and so forth) in

the quickest time possible, without sacrificing accuracy. Scores represented the number

of errors and the time taken to complete the task. If the participant took longer than 240

seconds then they were required to stop completion of the task. Higher scores reflected

a lower ability to control interference. A Trial 4 Contrast score was also calculated to

provide a measure of the time taken to complete Trial 4 divided by the time taken to

complete both Trial 2 and Trial 3 (which provide an index of visuo-motor speed). Trial

2 of the TMT involved joining an array of circles with consecutive numbers in them

with a continuous line, in sequence and in the quickest time possible. Trial 3 of the

TMT involved joining an array of circles with consecutive letters in them with a

continuous line, in sequence and in the quickest time possible. Both Trial 2 and Trial 3

were administered prior to the participant commencing Trial 4 as part of an overall

TMT subtest administration procedure. The D-KEFS manual reports a test-retest

reliability correlation of r = .36 for this trial.

Inhibition of prepotent responses. The inhibition of prepotent responses was

assessed using two measures: the Color-Word Interference subtest (D-KEFS) and a

modified version of the Rule Shift card test from the BADS. Trial 3 of the Color-Word

Interference subtest was used in the current study, which is a variant of the Stroop test.

In this trial, participants were presented with a page of names of colours which were

printed in incongruent coloured ink. The participant is asked to name the colour of the

ink that each word is printed in, as quickly as possible but not naming the actual word

printed. The time taken to complete the trial, as well as the number of errors, was

recorded. A higher score reflected a lower ability to inhibit a prepotent response. In

addition, a Color-Word Trial 3 Contrast score was calculated to provide a measure of


the time taken to complete Trial 3 divided by the time taken to complete Trial 1 (which

is an index of processing speed). Trial 1 of the Color-Word subtest required the

participant to name colours (presented as colour patches on the page) in the quickest

time possible. Trial 1 was administered prior to the participant commencing Trial 3 as

part of the overall Color-Word Interference subtest administration procedure. Test-retest

reliabilities are reported to be in the moderate to high range (r = .60 - .90).

A modified version of the Rule Shift card test from the BADS was derived from

Num’s (2006) study. In this task, participants were provided with a booklet of 20

playing cards which were presented in random order throughout the booklet. In the first

trial, the participant was required to say ‘yes’ if the colour of the card suit was red and

‘no’ if the colour of the card suit was black, until the participant went through all of the

cards in the booklet. Using the same 20-card booklet, on the second trial participants

were required to say ‘yes’ if the colour of the card suit was black and ‘no’ if the colour

of the card suit was red. In the third trial (which was a modified addition to the original

test), participants were required to once again go through the booklet and say ‘yes’ if the

card colour was the same colour as the previous card and ‘no’ if the card colour was

different to the colour of the card previously presented. In the fourth trial (also a

modified addition to the original test), participants were required to say ‘no’ if the card

colour was the same colour to the previous card and ‘yes’ if the card colour was

different to the colour of the card previously presented. The participant was required to

go through each trial as quickly as they could, without sacrificing accuracy. The overall

time taken to complete each trial, as well as the number of errors, was recorded. Profile

scores were calculated for performance on trial 2 and trial 4 of the test by the summing

the number of errors incurred minus an error deduction if the completion time on either

of these two trials was over 67 seconds. A Rule Shift Trial 2 and 4 combined score was


calculated to represent the average score across both trials. A lower profile score

reflected a lower ability to inhibit a response. A test-retest reliability coefficient of r =

.76 is reported for the original version of this test.

Verbal fluency. The Letter Fluency subtest of the D-KEFS was used to assess

verbal fluency. Participants were asked to generate as many words as they could,

beginning with a specified letter (e.g., F, A, S), within a timeframe of 60 seconds for

each letter. Participants were asked to exclude proper nouns, numbers, and multiple

forms of the same word. The total score was the number of correct responses summed

across the three letters. Sound internal consistency is reported for this subtest ranging

from .60 to .90, as well as adequate test-retest reliability (r = .60 - .90).

Emotion-based decision-making. The Iowa Gambling Task (IGT; Bechara et al.,

1994) was used to measure emotion-related decision-making. A computerized version

of the IGT was administered where participants were required to choose between decks

of cards which yielded high immediate gains but large future loss, and decks which

yielded lower immediate gains but a smaller future loss. The goal of the task was to

optimise profit on a loan of play money. Participants were presented with four decks of

cards (1, 2, 3 & 4), and were given a $2000 loan of play money. Participants were

informed that the game requires a series of card selections, one card at a time, from any

of the four decks, until they were told to stop (which was after 100 trials). Decks 1 and 2

were ‘disadvantageous’ because they resulted in larger overall loss, whereas decks 3

and 4 were ‘advantageous’ because they resulted in larger overall gain. A total score

was calculated by subtracting the total number of cards selected from the two

disadvantageous decks from the total number of cards selected from the two

advantageous decks. Lower total scores reflected poorer decision-making abilities.


The ability of the IGT to detect decision-making impairments has been demonstrated

across a variety of clinical samples which have included populations with VPFC lesions

(Bechara et al., 1994; Bechara et al., 1997; Bechara et al., 2001; Ernst, Grant, London,

Contoreggi, Kimes, & Spurgeon, 2003). These findings are suggestive of the construct

validity of this test. More specifically to the current study, individuals with

schizophrenia have been found to demonstrate a distinct pattern of impaired decision-

making (as assessed by the Iowa Gambling Task), that is somewhat different to that

found in patients with OFC lesions, as well as healthy participants (Ritter et al., 2004;

Shurman et al., 2005). Published reliability information on the computerised version of

the test is not available and internal consistency on this measure is difficult to calculate

due to the IGT not consisting of test items that usually make up conventional

neuropsychological tests (Dunn, Dalgleish, & Lawrence, 2006). There are also

difficulties examining the reliability of the measure as the ability to assess the temporal

stability of the test could be potentially impacted by practice effects on retesting

(Beulow & Shur, 2009).

Functional outcome. The Independent Living Skills Inventory (ILSI; Menditto

et. al., 1999), was used to measure functional outcome. This inventory measures the

extent to which individuals are able to perform competently on a broad range of skills

which have been found to be important for successful community living. The inventory

was completed on the basis of obtaining ratings from the patient’s key worker or

community support worker. The original version of the ILSI included 89 items divided

into 11 subscales. Items assessed a range of skills including personal management,

hygiene and grooming, clothing, basic skills, interpersonal skills, home maintenance,

money management, cooking, resource utilisation, general occupation skills and

medication management. Each item was rated in relation to the extent in which the


individual was considered to be able to perform particular skills in conjunction to the

extent in which assistance or support is required. Ratings ranged from ‘No Competence’

(0) to ‘Independent Competence’ (3). A total ILSI score was calculated as the average

score across all of the ILSI subscales. The present study used the current version of the

inventory which contained 55 items. The shorter version was based on the psychometric

properties of items from the original scale, as well as on the feedback from raters about

their usefulness. The internal consistency among the items of the orginal version of this

scale is 0.82 (Cronbach’s coefficient alpha). This measure has been used in previous

research investigating the relationship between cognitive impairments in individuals

with schizophrenia and 'real-world' functional outcome (Keefe et al., 2006). As the

matched-control participants were not clinical patients, the measure was completed as a

self-report questionnaire by these subjects.

Procedure

After patient participant recruitment, an information sheet about the study was

provided and a mutually convenient time for testing was scheduled. Testing took place

at various local public mental health service suburban clinics. At the beginning of each

testing session, participants were informed that participation was voluntary and they had

the right to withdraw at any given time. Informed consent was then obtained (see

Appendix F). The structured interview gathering demographic information was

conducted after informed consent was obtained and this took approximately 10 minutes

to complete. The DASS and the SCI-PANSS were administered afterwards, taking

approximately 30 minutes to complete. Neurocognitive testing followed taking

approximately 60 to 90 minutes to complete. Tests were administered in a standardised

order so as to minimize measurement error due to test order interaction. A break was

also provided to participants depending on the level of participant motivation and


fatigue demonstrated/reported. All testing was completed by the researcher who is a

registered psychologist and has professional training in the administration and scoring

of neuropsychometric assessments, as well as additional professional training in the

administration and scoring of the SCI-PANSS. The Independent Living Skills Inventory

was given to the rater which was nominated by the patient participant as being able to

give the most accurate evaluation of their independent living skills. This questionnaire

was then returned to the researcher via post by a self-addressed stamped envelope which

was either provided to the participant at the time of testing or posted directly to the

nominated rater.

The matched-control subjects underwent a similar procedure. Testing took place

at one of the available testing locations selected by the participant. Informed consent

was obtained prior to the testing session (see Appendix G) and overall testing time for

this group of participants was approximately 60 to 90 minutes. The SCI-PANSS was

not administered to this group. For matched-control subjects, the Independent Living

Skills Inventory was self-completed in their own time and then sent back to the

researcher via post.

Debriefing information (see Appendix H) was given at the conclusion of testing

detailing the use of the obtained data from the research.

Results

Data Screening

Prior to testing hypotheses, data was entered into a statistical analysis program,

SPSS Version 22.0 (2013), and checked for missing values, outliers and departures from

normality. There were no missing values in the final data set. Outliers were detected on

two variables, Color-Word Trial 3 and the Iowa Gambling Task. The distributions of


these variables were Winsorised whereby the ranks of extreme scores (i.e., values

falling outside of 3.29 standard deviations from the mean) were maintained by assigning

them a value of the closest score that was not greater than 3.29 standard deviations from

the mean (for discussion, see Erceg-Hurn & Mirosevich, 2008; Field, 2009). Two scores

on the Color-Word Trial 3 variable and one score on the Iowa Gambling Task variable

were dealt with using this protocol in order to maintain the integrity of the data and

protect against any departures from normality. Following winsorisation of these

variables, normality was achieved. Further data screening demonstrated that there were

no departures from normality on any of the other variables.

Part A


As the first aim of the current study was to determine if schizophrenia patients with

cannabis use demonstrate poorer performance in constructs of executive functioning

compared to a matched-control group with a similar cannabis use history, the focus of

the initial statistical analyses was to compare the executive function performance of

these two groups. For further exploration, the proportion of schizophrenia patients with

cannabis use which demonstrated executive function performance falling in the

‘impaired’ range (compared to normative criteria), was described. Prior to analyses,

standardised scores (z) were calculated using normative means and standard deviations.

However, as Zoo Map recall, Rule Shift Trial 4, the Rule Shift Trial 2 and 4 combined

score, and the event-based prospective memory task did not have normative mean

criteria available, scores relating to these measures were left in their original form. In

order to examine the executive function performances of schizophrenia patients with

cannabis use, relative to matched-controls with a similar cannabis use history, a series

of Analysis of Covariance (ANCOVA) analyses were conducted to determine the effect


of Group on executive function performance when accounting for the effects of

premorbid IQ. Examination of Shapiro-Wilk statistics and histograms for each group

indicated that the ANCOVA assumption of normality was supported. Scatterplots

indicated that the relationship between the covariate (premorbid IQ) and the dependent

variables (performance on the individual executive function measures) was linear.

Finally the assumptions of homogeneity of regression slopes and homogeneity of

variances were supported by the absence of a significant interaction between the

independent variable and the covariate. The ANCOVA results will be categorised

according to the executive function components defined by West’s (1996) hierarchical

model of executive function specifically: (i) the Temporal Organisation of Behaviour,

(ii) Retrospective Memory, (iii) Interference Control, (iv) the Inhibition of Prepotent

Responses and (v) Prospective Memory. Performance in the additional executive

function domains included in the current study that were not outlined in West’s model,

specifically verbal fluency and emotion-based decision making, will also be discussed.

Table 2 displays the results of the covariate analyses of executive function performance

for the schizophrenia group with cannabis use and matched-control group with a similar

cannabis use history, with premorbid IQ as a covariate. Premorbid IQ was found to have

an impact on Modified Six Elements, Digit Span and Letter Fluency task performance.

However, the main effects of Group remained significant for Digit Span after

accounting for the effects of premorbid IQ. An examination of the adjusted means

indicated that schizophrenia patients with cannabis use demonstrated significantly lower

scores on the Temporal Organisation of Behaviour (except for on the Modified Six

Elements measure), Retrospective Memory, Interference Control (except for the Trail

Making Test Trial 4 Contrast score), and the Inhibition of Prepotent Responses (except

for the Color-Word Trial 3 Contrast score), relative to controls. Adjusted means


Table 2. Results of ANCOVAs of executive function performance for Group with covariate of premorbid

IQ Executive Function

Performance

Adjusted Mean

Effects

Group Premorbid IQ

SCH /C

n=28

MC

n=28

F p ηp2 F p ηp

2

TOB

Zoo Map .055 .936 11.46 .001** .178 .095 .759 .002

Modified Six Elements -.008 .315 3.03 .088 .054 10.97 .002** .172

RM

Zoo Map Recall 4.79 6.39 21.42 <.001** .288 .008 .930 .000

Digit Span -.511 .392 26.93 <.001** .337 7.47 .009** .123

IC

Symbol Search -.662 .377 20.05 <.001** .275 .456 .502 .009

TMT Trial 4 -.729 .420 34.05 <.001** .391 2.48 .121 .045

TMT Trial 4 Contrast .043 -.019 .081 .777 .002 1.32 .255 .024

IPR

Rule Shift Trial 2 -.260 .518 7.60 .008**† .125 .206 .652 .004

Rule Shift Trial 4 2.01 3.31 25.32 <.001** .323 3.32 .074 .059

RS Trial 2 and 4 5.37 7.27 27.84 <.001** .344 2.50 .120 .045

Color-Word Trial 3 -.817 .531 26.23 <.001** .331 .985 .325 .018

Color-Word Trial 3

Contrast

.484 .778 1.85 .179 .034 .555 .460 .010

PM

Event-based task 3.05 3.52 1.52 .224 .028 1.94 .170 .035

Verbal Fluency

Letter Fluency -.552 -.210 2.28 .137 .041 9.84 .003** .157

Emotion-based

decision making

Iowa Gambling Task 15.23 13.57 .062 .804 .001 .319 .574 .006

df = 2

SCH/C schizophrenia patients with cannabis use, MC matched-controls with a similar cannabis-use

history, TOB Temporal Organisation of Behaviour, RM Retrospective Memory, IC Interference Control,

IPP Inhibition of Prepotent Responses, RS Rule Shift, PM Prospective Memory, TMT Trail Making Test

Note.*p< .05, **p< .01, †non sig. following post hoc analyses

comparisons also revealed no significant differences between schizophrenia patients

with cannabis use and matched-control subjects with a similar cannabis use history on

the event-based prospective memory, verbal fluency and emotion-based decision

making tasks. Post hoc analyses using a Holm-Bonferroni correction method revealed

that no significant differences were detected between groups on Rule Shift Trial 2

performance while controlling for family-wise Type I error rate at level α = .05.


Level of executive function impairment between groups. To gain further

insight into the extent and level of executive function impairment in the sample groups,

a number of calculations using normative data and impairment criteria or impairment

cut-off scores were conducted prior to analysis. The z-scores calculated prior to

analyses were used for this examination. Used as a guide in Coulston et al.’s (2007)

study, ‘impairment’ status was defined if neurocognitive performance fell 1.5 – 2.0

SD’s or more below the mean of the control group. Lezak et al. (2004) also suggests

that a neurocognitive test performance change of 1.0, 1.5 and 2.0 SD’s may be used for

determining impairment. Lezak considers that while a test performance reflective of a

1.0 SD change may not be sufficient enough to indicate a difference of statistical

significance, some examiners may still classify this performance as ‘probably impaired’.

However, as approximately 15% of individuals who are considered ‘intact’ are expected

to obtain scores greater than 1.0 SD below normative means and therefore, potentially

resulting in too many false positives, a change in performance of 2.0 SD’s is considered

to be a clear indication of impairment (Lezak, 2004). Therefore, the current study aimed

to examine performances between groups across the different impairment criteria of 1.0,

1.5 and 2.0 SD’s below the normative mean in order to better our understanding of the

nature of any impairment that may be shown. Table 3 displays the chi-square results for

proportional differences in each group that demonstrated neurocognitive performance

across the different impairment ranges (i.e., greater than 1.0, 1.5 and 2.0 standard

deviations below normative mean criteria) for each of the six executive function

measures where significant differences were demonstrated in the previous analyses. It

should be noted that as Zoo Map recall, Rule Shift Trial 4, the Rule Shift Trial 2 and 4

combined score, and the event-based prospective memory task, did not have normative

mean criteria available they were therefore not included in the table. The Iowa


Table 3. The proportion (n) of each sample group and effect size of proportional differences in executive function performance across each of the impairment level categories Executive

Function

Performance

Mean

(SD) Proportion of sample >

-1.0 SD’s below

normative mean

n

Proportion of sample

between

-1.0 to -1.49 SD’s below

normative mean

n

Proportion of sample

between

-1.5 to -1.99 SD’s below

normative mean

n

Proportion of sample <

-2.0 SD’s below

normative mean

n

Effect Size of difference

between frequencies

within each group

w

SCH/C

(n= 28)

MC

(n= 28)

SCH/C

(n= 28)

MC

(n= 28)

SCH/C

(n= 28)

MC

(n= 28)

SCH/C

(n= 28)

MC

(n= 28)

SCH/C

(n= 28)

MC

(n= 28)

SCH/C

(n= 28)

MC

(n= 28)

TOB

Zoo Map .05 (1.14) .94 (.74) 23 27 2 1 0 0 3 0 1.04** .929**

RM

Digit Span -.52 (.64) .40 (.73) 19 27 7 1 1 0 1 0 1.05** .929**

IC

Symbol

Search

-.67 (-.87) .38 (.85) 16 26 8 2 3 0 1 0 .827** .857**

TMT Trial 4 -.74 (.91) .43 (.53) 14 27 8 1 3 0 3 0 .647** .929**

IPP

Rule Shift

Trial 2

-.26 (.56) .52 (.24) 21 28 0 0 0 0 7 0 .500**

CW Trial 3 -.81 (1.29) .52 (.52) 16 28 6 0 0 0 6 0 .505**

Note.**p< .01


Gambling Task will then be discussed due to impairment criteria for this measure

involving a cut-off score instead of normative means and standard deviations.

Symbol Search and Trail Making Test Trial 4 had the highest proportion of

participants that performed at greater than 1.0 below the normative mean. A chi-square

test for goodness of fit (with α = .01) was used to assess whether certain levels of

performance (according to the impairment level criteria of 1.0, 1.5 and 2.0 SD’s below

the normative mean) were more common than others in each sample group. The chi-

square test was statistically significant on all measures for the schizophrenia group with

cannabis use (p < .001), indicating that some impairment criteria levels were achieved

with significantly greater frequencies than others. Results indicate that a significantly

larger proportion of schizophrenia patients with cannabis use demonstrated performance

on all of the 6 measures above the impairment level criteria of greater than 1.0, 1.5 and

2.0 standard deviations below normative mean than patients with cannabis use falling

below these criteria. In other words, a larger proportion of schizophrenia patients with

cannabise use demonstrated performances which were classified in the normal range on

these executive function measures than those which were deemed to be at the probably

impaired or clinically impaired range. These findings suggest that a statistically

significant larger proportion of patients with schizophrenia with cannabis use did not

perform at a level that was considered to be even ‘probably impaired’, let alone fall into

the clinically impaired category and this was significantly different than chance (p <

.001). Similar results were found for matched-controls (p < .001) indicating a

significantly larger proportion of the group demonstrating performances in the normal

range. An examination of the index of effect size Cohen’s w ranged from 0.50 to 1.05,

which can be considered large. These results suggest that the previously reported

significant results showing significant differences between groups is more reflective of


‘poorer’ performance by the schizophrenia group, but does not reflect ‘impaired’

performance relative to normative criteria.

Adjusted mean comparisons also reveal that neither group performed below the

cut-off score for impaired performance on the Iowa Gambling Task (i.e., net score <10)

(Bechara et al., 2001). This result also suggests that neither the schizophrenia group

with cannabis use (M = 15.23), nor the matched-controls group (M = 13.57), in the

current study demonstrated impairment on this measure according to this criterion.


As another aim was to investigate whether continued/current cannabis use is

associated with the non-recovery of executive function, the groups were partitioned into

current cannabis users and abstinent cannabis users based on self-reported current use at

the time of testing. In order to examine this relationship, a series of two-way

ANCOVA’s were conducted to determine the effect of Group and cannabis-use status

on executive function, when controlling for the effects of duration of use. Once again,

the results will be grouped according to the executive function domains outlined in

West’s (1996) model and the additionally included measures of executive function will

then be reported.

The ANCOVA assumption of normality was supported via the examination of

Shapiro-Wilk statistics and histograms for each group and cannabis-use status

categories. Scatterplots indicated that the relationship between the covariate (duration of

use) and the dependent variables (executive function performance) was linear. Finally

the assumptions of homogeneity of regression slopes and homogeneity of variances

were supported by the independence of the covariate and both of the independent

variables. Table 4 outlines the ANCOVA results of executive function performance for

each group, with duration of use as a covariate. No statistically significant interactions


Table 4. Results of ANCOVAs of executive function performance for Group and cannabis-use status with covariate of duration of use

Cognitive

performance

Adjusted Mean

Effects

Group Cannabis-Use Status Group Cannabis-Use Status Duration of Use

SCH/C

n=28

MC

n=28

Current

Users

n=22

Non-Current

Users

n=34

F p ηp2 F p ηp

2 F p ηp

2

TOB

Zoo Map .021 .958 .461 .518 112.23 .001** .193 .043 .836 .001 .826 .368 .016

Modified Six Elements -.038 .339 .135 .165 3.15 .082 .058 .019 .892 .000 .108 .743 .002

RM

Zoo Map Recall 4.72 6.40 5.44 5.68 21.98 <.001** .301 .421 .519 .008 .039 .845 .001

Digit Span -.508 .429 .053 -.133 24.33 <.001** .323 .909 .345 .018 .687 .411 .013

IC

Symbol Search -.674 .378 -.172 -.124 18.75 <.001** .269 .038 .846 .001 .028 .869 .001

TMT Trial 4 -.747 .449 -.122 -.176 32.71 .001** .391 .065 .800 .001 .000 .989 .000

TMT Trial 4 Contrast .024 -.024 -.055 .055 .047 .829 .001 .227 .636 .004 1.30 .260 .025

IPP

RS Trial 2 -.298 .527 .044 .184 8.09 .006** .137 .220 .641 .004 .013 .909 .000

RS Trial 4 2.06 3.36 2.96 2.47 23.80 <.001** .318 3.18 .080 .059 1.60 .212 .030

RS Trial 2 and 4 5.39 7.33 6.55 6.17 26.50 <.001** .342 .96 .332 .018 .92 .341 .018

CW Trial 3 Contrast .430 .778 .478 .730 2.65 .110 .049 1.32 .256 .025 1.56 .218 .030

PM

Event-based task 3.03 3.57 3.37 3.24 1.77 .189 .034 .100 .754 .002 .594 .445 .012

Verbal Fluency

Letter Fluency -.495 -.146 -.039 -.602 2.05 .159 .039 5.05 .029* .090 .036 .850 .001

Emotion-based decision

making

Iowa Gambling Task 15.54 13.46 14.96 14.03 .091 .756 .002 .017 .896 .000 .292 .591 .006

Note.*p< .05, **p< .01


between the independent variables and executive function performance were found after

adjustment for duration of use. Duration of use was not found to have an impact on

performance for the majority of the executive function measures. However, a significant

interaction between the covariate of duration of use and the independent variables of

Group and cannabis-use status on Color-Word Trial 3 was found, F(6, 49) = 3.01, p

=.039, ηp2 = .156. Therefore, the assumption of the homogeneity of regression slopes

was violated in this instance and an ANCOVA was not conducted. Inspection of the

regression slopes revealed a poor association between duration of use and Color-Word

Trial 3 scores across the test groups (i.e., schizophrenia patients with cannabis use and

matched-control subjects with a similar cannabis use history). However, for the

cannabis-use status groups, an association between duration of use and Color-Word

Trial 3 scores was found. As a general pattern, the regression slopes indicated that in the

current-user group, a longer duration of use was associated with higher Color-Word

Trial 3 scores indicating better performance on this measure due to the conversion to z-

scores using normative criteria. Contrastingly, in the non-current user group, longer

duration of use was found to be associated with lower Color-Word Trial 3 scores

indicating poorer performance.

A two-way ANOVA revealed a significant main effect of Group on Color-Word

Trial 3, F(3, 52) = 26.86, p <.001, ηp2 = .341. Main effects of cannabis-use status, F(3,

52) = 3.41, p = .071, ηp2= .062 and the interaction, F(3, 52) = .446, p = .512, ηp

2= .008

were not significant. Comparison of means indicated that the schizophrenia group with

cannabis use (M = -.81) had significantly lower scores on Color-Word Trial 3, than

matched-controls (M = .53). Although, current users (M = -.44) and non-current users

(M = .05) showed similar performance on this measure.


An examination of the adjusted means for the other executive function domains

indicated that schizophrenia patients with cannabis use had significantly lower scores on

the Temporal Organisation of Behaviour (except on the Modified Six Elements

measure), Retrospective Memory, Interference Control (except for the Trail Making

Test Trial 4 Contrast score), and the Inhibition of Prepotent Responses (except for the

Color-Word Trial 3 Contrast score), relative to controls. Adjusted means comparisons

also revealed no significant differences between schizophrenia patients with cannabis

use and matched-control subjects with a similar cannabis use history on the event-based

Prospective Memory, Verbal Fluency and Emotion-based Decision-making tasks.

Further, results showed no significant differences in performance on all of the executive

function domains between current users and non-current users, except for in the domain

of verbal fluency. Findings revealed that current users (M = -.04) had higher scores on

Letter Fluency than former users (M = -.60), suggesting that continued cannabis use is

associated with better performance on Letter Fluency. The effect size of this result is

considered moderate. Holm-Bonferroni correction was applied to adjust for multiple

comparisons, with all results remaining statistically significant following correction.


An additional aim of the study was to investigate if a longer period of abstinence

is associated with the recovery of executive function. In order to examine this

relationship, a series of two-way ANCOVA’s were conducted to determine the effect of

Group and time since cessation (i.e., abstinence for less than 5 years and abstinence for

equal to, or greater than, 5 years) on executive function, when controlling for duration

of use. For this analysis, non-current users were divided into two groups using a median

split. Following this, 16 subjects were in the less than 5 years abstinence group and 18


subjects were in the equal to, or greater than, 5 years abstinence group. The following

analyses were only conducted on the sample of non-current cannabis users (n = 34).

Examination of Shapiro-Wilk statistics and histograms for each group and time since

cessation categories indicated the ANCOVA assumption of normality was supported.

Scatterplots indicated that the relationship between the covariate (duration of use) and

the dependent variables (performance on the individual executive function measures)

was linear. Finally the assumptions of homogeneity of regression slopes and

homogeneity of variances were supported by the absence of a significant IV-by-

covariate interaction. Table 5 outlines the ANCOVA results of executive function

performance for Group and time since cessation categories amongst the non-current

user sample, with duration of use as a covariate. There were no statistically significant

interactions found between either group, or time since cessation categories, and

executive function performance after adjustment for duration of use. Duration of use

was not found to have an impact on performance for the majority of the executive

function measures, except for Color-Word Trial 3. However, the main effect of group

on Color-Word Trial 3 remained significant after accounting for the effects of duration

of use. Comparison of adjusted means show that schizophrenia patients with cannabis

use had significantly lower scores on Retrospective Memory, Interference Control

(except for the Trail Making Test Trial 4 Contrast score), and the Inhibition of Prepotent

Responses domains, relative to controls (except for Rule Shift Trial 2 and the Color-

Word Trial 3 Contrast score). Adjusted means comparisons also revealed no significant

differences between schizophrenia patients with cannabis use and matched-control

subjects with a similar cannabis use history on the Temporal Organisation of Behaviour

(on the Modified Six Elements measure only), Prospective Memory, Verbal Fluency

and Emotion-based Decision-making domains. Post hoc analyses using the Holm-


Table 5. Results of ANCOVAs of executive function performance for Group and time since cessation categories with covariate of duration of use

Cognitive

performance

Adjusted Mean

Effects

Group Time Since Cessation Group Time Since Cessation Duration of Use

SCH+C

n=28

C CTRL

n=28

< 5 years

n=16

≥5 years

n=18

F p ηp2 F p ηp

2 F p ηp

2

TOB

Zoo Map .210 .830 .920 .110 3.17 .086 .098 4.57 .041* .136 .116 .736 .004

Modified Six Elements .014 .311 .290 .034 1.25 .273 .041 .767 .388 .026 .619 .438 .021

RM

Zoo Map Recall 5.08 6.30 5.98 5.40 6.86 .014*† .191 1.29 .266 .043 1.10 .302 .037

Digit Span -.664 .345 -.244 -.075 14.35 .001* .331 .337 .566 .011 2.72 .110 .086

IC

Symbol Search -.584 .373 -.126 .085 9.11 .005** .239 .014 .906 .000 2.14 .154 .069

TMT Trial 4 -.677 .338 -.143 -.196 11.43 .002** .283 .027 .872 .001 .644 .429 .022

TMT Trial 4 Contrast .111 .024 .056 .079 .078 .782 .003 .004 .947 .000 .266 .610 .009

IPP

RS Trial 2 -.085 .480 .308 .086 3.44 .074 .106 .441 .512 .015 .043 .837 .001

RS Trial 4 1.76 3.17 2.24 2.70 12.95 .001** .309 1.16 .290 .039 .098 .756 .003

RS Trial 2 and 4 5.26 7.11 6.04 6.33 14.37 .001** .331 .295 .591 .010 .124 .727 .004

CW Trial 3 -.484 .606 .050 .067 17.16 <.001** .372 .003 .956 .000 6.55 .016* .184

CW Trial 3 Contrast .722 .728 .671 .779 .001 .976 .000 .185 .670 .006 2.79 .105 .088

PM

Event-based task 3.12 3.43 3.34 3.20 .377 .544 .013 .065 .801 .002 .132 .719 .005

Verbal Fluency

Letter Fluency -.821 -.367 -.427 -.762 1.72 .200 .056 .776 .386 .026 .002 .964 .000

Emotion-based decision

making

Iowa Gambling Task 14.00 14.96 11.07 17.90 .009 .923 .000 .403 .531 .014 .006 .938 .000

Note.*p< .05, **p< .01, †non sig. following post hoc analyses


Bonferroni correction method revealed that significant differences no longer remained

between groups on Zoo Map recall performance after adjusting the alpha level for

multiple comparisons. Further, results showed no significant differences in performance

on all of the executive function domains between non-current users who were abstinent

for less than 5 years and non-current users who were abstinent for equal to, or greater

than, 5 years, except for in the Temporal Organization of Behaviour domain (on the Zoo

Map measure only). Findings revealed that non-current users who were abstinent for

less than 5 years (M = .92) had higher scores on Zoo Map than non-current users who

were abstinent for equal to, or greater than, 5 years (M = .11), suggesting that shorter

abstinence periods (i.e., less than 5 years) was associated with better performance on

this measure. The effect size of this result is considered moderate.


Principal Components Analysis. Principal Components Analysis (PCA) was

conducted to determine what, if any, factor structures underlie the following executive

function measures: Zoo Map, Zoo Map recall, Digit Span, Symbol Search, Trail Making

Test Trial 4, Rule Shift Trial 2, Color-Word Trial 3, the event-based prospective

memory task, Letter Fluency, and the Iowa Gambling Task. Rule Shift Trial 4 and the

Rule Shift Trial 2 and 4 combined score were not included in the analyses as they

involved modified versions of the original measures. The Trail Making Test Trial 4

Contrast score and Color-Word Trial 3 Contrast score were also not included in PCA as

the Trail Making Test Trial 4 and Color-Word Trial 3 appeared to be more successful in

detecting differences between groups. This was considered an important concern when

attempting to determine any underlying factors amongst the executive function

measures administered which may serve to be more sensitive and thus, reflective of the

fundamental construct in question. The purpose of the PCA was exploratory in nature.


This type of analysis was conducted in order to determine which executive function

measures were related to each other in a theoretically consistent way.

Criteria to determine the best factor model included: (a) exclusion of measures

or items exhibiting Kaiser’s measurement of sampling adequacy (MSA), Kaiser-Meyer-

Olkin (KMO) or communality values < .5; (b) Bartlett’s test of sphericity exhibiting

significance (p < .0001); (c) retention of factors with eigenvalues > 1 that were

supported by scree plot analysis and clinical/theoretical plausibility of factors; (d) factor

loadings ≥ .4 for interpretation of factors (explaining ≥ 16% of total variance); and (e)

stability of factor solutions across analyses employing oblique and orthogonal rotations

(Field, 2009; Tabachnick & Fidell, 2007).

PCA was conducted utilising both orthogonal (varimax) and oblique (oblimin)

rotations. During initial analysis, one item (the Iowa Gambling Task) failed to meet the

minimum criterion of .5 for Kaiser’s MSA and was excluded in further analyses.

Subsequently, PCA of the remaining 10 executive function measures yielded near-

identical factor solutions across orthogonal (varimax) and oblique (oblimin) rotations.

However, results of the former are reported only as varimax rotation provided the best

defined factor structure (see Table 6). A three-factor solution explaining 61.57% of the

total variance in executive function was extracted. Of this variance, 40.26% was

accounted for by factor 1 (‘Mental Control and Self-Regulation’; 8 variables), 11.22%

by factor 2 (‘Voluntary Response Generation and Disinhibition’; 2 variables), and

10.09% by factor 3 (‘Maintenance of Intention for Future Action’; 2 variables).

The outcomes of the PCA indicate that the executive function measures which

loaded onto factor 1 include mostly those tests which were guided by West’s (1996)

theoretical model of executive function. However, verbal fluency (which was included

as an additional executive function component for exploration and did not appear to be

104

Table 6. Factor loadings based on a Principal Components Analysis utilising orthogonal (varimax)

rotation of 10 executive function measures (N=56)

Loading

Theoretical

Construct

Item Measure Factor 1 Factor 2 Factor 3

Temporal

Organisation of

Behaviour

Zoo Map .576

Modified Six

Elements .513

Retrospective

Memory

Zoo Map Recall .646

Digit Span .692

Interference

Control

Symbol Search .703

Trail Making Test

Trial 4 .798

Inhibition of

Prepotent

Responses

Rule Shift Trial 2 .707 -.473

Color-Word Trial

3 .637 .405

Prospective

Memory

Event-based task .903

Verbal Fluency Letter Fluency .847

Note. Factor loadings less than the absolute value of ± .4 are omitted

included in West’s model), appeared to load onto a separate factor relative to the

remaining measures (i.e., factor 2). Taken together with the negative loading of Rule

Shift Trial 2 onto factor 2, this may indicate that the underlying structure of this

component involves response generation/fluency abilities or cognitive responses that

require disinhibition. Moreover, the positive loadings of both Color-Word Trial 3 and

the event-based prospective memory onto factor 3 potentially reflect an underlying

structure involving cognitive responses that require the ability to remember an intention

for future action. Finally, the Iowa Gambling Task (which did not meet criterion for

PCA and was excluded in the subsequent analysis) may not have been sensitive enough

to sufficiently tap into the executive function constructs of interest, albeit in this

particular sample.


While the sample size in the current study is notably low, it has been suggested

by Stevens (1986; 2002) that as low as 5 subjects per variable is the minimum needed in

Principle Components Analysis based on Gorsuch’s (1983) guidelines. The current

study’s sample size is just over 50 with the combined sample and is therefore just above

the minimum requirements in the recommended guidelines. In addition,

recommendations arising from a study by Guadagnoli and Velicer (1988) outline that

‘components with four or more loadings above .60 in absolute value are reliable,

regardless of sample size’ (cited in Stevens, 2002, p. 395). As the results indicate 6

loadings above .60, it can be considered that at least factor 1 is a reliable component.

Another recommendation arising from Guadagnoli and Velicer’s (1988) study is that

‘components with only a few low loadings should not be interpreted unless sample size

is at a least 300’ (Stevens, 2002, p. 395). It is outlined that a low loading would include

those .40 and below. However, Stevens (2002) suggested that a factor which was

defined by only a few loadings was not considered as much of a factor and instead, the

factor could be considered as variable specific. Therefore, as factor 2 included loadings

of only two variables (Rule Shift Trial 2 at -.473 and Letter Fluency at .847), and factor

3 including loadings of only two variables (Color-Word Trial 3 at .405 and Prospective

Memory at .903) this could indeed represent some of those cases.

Overall, these results are in partial support of the construct validity of the

selected executive function measures (which were those guided by West’s model). That

is, the measures which loaded on factor 1 seemed to adequately tap into a single

theoretical neurocognitive construct, namely executive function. However, the results

also suggest that the while the measure of Letter Fluency may assess executive function

abilities, it may also rely upon other cognitive abilities that are separate, or independent,

to executive function alone. In addition, the event-based prospective memory measure


utilised may not have been sensitive enough to detect the true construct of prospective

memory abilities. In alternative, the prospective memory measure used may have tapped

into other cognitive processes that fall outside of the executive function domain.

Part B


The predictive ability of executive function measures in predicting

functional outcome ratings. The investigation into the relationship between the

executive function domains belonging to West’s (1996) model and functional outcome

is exploratory in nature. However, due to reports of an association between executive

function and functional outcome in the literature, it was hypothesized that executive

function performance would be significantly related to functional outcome. More

specifically, scores on executive function measures would have significant predictive

ability in relation to functional outcome ratings (as measured by the Independent Living

Skills Inventory (ILSI)). The purpose of the following analyses is to assist in identifying

a measure (or measures) of executive functioning that significantly predicts a specific

domain of functional outcome in schizophrenia patients (e.g., if measures of prospective

memory are shown to predict a given functional outcome domain then cognitive

remediation specific to enhancing prospective memory abilities could be utilised to

ultimately target improvements in that functional outcome domain). From this

perspective, the goal of the analyses (and in turn the consequent results) is to assist in

identifying whether there is potential for improvements to specific cognitive abilities

which may in turn affect associated functional outcomes.

In order to identify the predictors that would be considered important to enter

into regression analyses, Pearson correlation analyses between each of the individual

executive function measures and each of the ILSI sub-scale ratings, as well as the Total


ILSI score, were first computed. Correlations were calculated for the schizophrenia

group with cannabis use, the matched-control group with a similar cannabis use history,

and the overall combined sample. Table 7, 8 and 9 display the correlation matrices.

A series of multiple regression and hierarchical multiple regression analyses

(divided into three stages) were conducted for each functional outcome sub-domain, as

well as for overall functional outcome. Only the schizophrenia group with cannabis use

were used the analyses (n = 28). In the first stage of regression analysis, the measure(s)

showing significant correlations in the schizophrenia group with cannabis use were

entered as predictors into a multiple regression analysis. For stage 2, at step 1 these

same predictors are entered simultaneously. At step 2, only the predictor from Stage 1

showing a significant slope was then entered. At step 3, this same predictor as well as

those executive function measures showing significant correlations in the matched

control group (not including those already entered), were then entered as predictors. At

stage 3, all of the previous steps were used again. However, in step 4 only the

predictor(s) from previous steps showing a significant slope were entered. In the final

step, these same significant predictors in addition to those measures showing significant

correlations in the combined sample (not including those already entered previously),

were entered as predictors. Before interpreting the results of the regression analyses, a

number of assumptions were tested and checks were performed. Firstly, an inspection of

the normal probability plot of standardised residuals and the scatterplot of standardised

residuals against standardised predicted values indicated that the assumptions of

normality, linearity and homoscedasticity of residuals were met. In addition,

Mahalanobis distance did not exceed the critical χ2

for degrees of freedom for any cases

in the data, indicating that multivariate outliers were not of concern. Finally, relatively


Table 7. Correlations between executive function measures and ILSI sub-scales and total ILSI score for

the schizophrenia group

Executive Function Measures

Independent

Living Skills

Zoo

Map

Zoo

Map

Recall

Digit

Span

Symbol

Search

Trail

Making

Test

Trial 4

Rule

Shift

Trial 2

Rule

Shift

Trial 4

Rule Shift

Trial 2 and

4

Combined

Color-

Word

Trial 3

Personal

Management

.223 .220 -.097 .316 .038 -.067 -.209 -.063 .310

Hygiene &

Grooming

.185

.123

.429*

.335

.089

.146

.015

-.084

.353

Clothing

-.051

.108

.278

.118

-.108

-.207

-.120

-.215

.260

Basic Skills

-.083

-.057

.216

.170

.043

-.266

.154

-.276

.145

Interpersonal

skills

.178

.257

.181

.457*

.241

-.135

.138

.007

.361

Home

Maintenance

.160

.274

.083

.251

-.038

-.171

-.137

-.203

.300

Money

Management

-.087

.307

.194

.209

-.107

-.202

-.063

-.173

.162

Cooking

.145

.331

.169

.456*

.119

-.178

.138

-.021

.371

Resource

Utilization

.097

.304

.113

.390*

.199

-.009

-.042

-.035

.288

General

.225

.053

.012

.289

.136

-.172

.105

-.040

.352

Occupational

Skills

Medication

Management

.197

.368

.074

.431*

.252

-.016

.074

.040

.309

Total

.

141

.271

.183

.389*

.096

-.152

.036

-.074

.328

Note. *p<.05, **p<.01

high tolerances indicated that multicollinearity would not interfere with the ability to

interpret the outcome of the regression analyses.

Personal Management (Independent Living Skills Inventory). There were no

significant correlations found in each of the separate groups (i.e., schizophrenia group

with cannabis use and matched-controls group with a similar cannabis use history),

therefore stage 1 and 2 of the regression analyses were not conducted. For stage 3,

results indicate that the overall model which included Zoo Map, Zoo Map recall, Digit

Span, Symbol Search, Trail Making Test Trial 4, Rule Shift Trial 4, the Rule Shift Trial

2 and 4 combined score, and Color-Word Trial 3 as predictors, did not significantly

predict ratings in Personal Management on the Independent Living Skills Inventory in



the matched-control group


Independent

Living Skills

Zoo

Map

Zoo

Map

Recall

Digit

Span

Symbol

Search

Trail

Making

Test

Trial 4

Rule

Shift

Trial 2

Rule

Shift

Trial 4

Rule Shift

Trial 2 and

4

Combined

Color-

Word

Trial 3

Personal

Management

-.055 -.115 .287 -.195 -.280 .173 -.027 .016 -.367

Hygiene &

Grooming

.070

.226

.088

-.211

-.233

.556**

.157

.270

-.098

Clothing

.337

.098

.416*

-.095

.140

.694**

.321

.448*

-.260

Basic Skills

-

-

-

-

-

-

-

-

-

Interpersonal

skills

.290

.199

.158

-.176

-.287

.125

.011

.039

-.558**

Home

Maintenance

.213

.110

.049

.168

.226

.662**

.222

.353

-.092

Money

Management

.051

-.148

.387*

-.224

-.238

.306

-.130

-.045

-.322

Cooking

.284

.150

-.062

-.307

-.150

.540**

.188

.294

-.263

Resource

Utilization

.314

.041

.419*

.032

.074

.970**

.306

.499**

-.128

General

Occupational

Skills

-.117

-.105

.199

-.220

-.336

-.037

-.184

-.173

-.307

Medication

Management

.282

-.087

.245

-.231

-.317

.243

-.104

-.036

-.430*

Total

.240

.032

.331

-.233

-.218

.647**

.106

.246

-.414*

Note. *p<.05, **p<.01

schizophrenia patients with cannabis use, R2 = .247, R

2adj = -.070, F(8, 19) = .780, p =

.625.

Hygiene and Grooming (Independent Living Skills Inventory). At stage 1,

Digit Span significantly accounted for 15.3% of the variance in Hygiene and Grooming

ratings on the Independent Living Skills Inventory in schizophrenia patients with

cannabis use, R2 = .184, R

2adj = 153, F(1, 26) = 5.87, p = .023. By Cohen’s (1988)

conventions, an effect of this magnitude can be considered ‘medium’ (f 2

= .23). At

stage 2, Rule Shift Trial 2 was added as a predictor to the regression equation and

accounted for an additional 4.2% of the variance in Hygiene and Grooming ratings.

However, this change was not statistically significant, ∆R2 = .042, ∆F(1, 25) = 1.345, p



the overall sample


Independent

Living Skills

Zoo

Map

Zoo

Map

Recall

Digit

Span

Symbol

Search

Trail

Making

Test

Trial 4

Rule

Shift

Trial

2

Rule

Shift

Trial 4

Rule Shift

Trial 2 and

4

Combined

Color-

Word

Trial 3

Personal

Management

.392** .441** .358** .459** .399** .188 .345** .342** .520**

Hygiene &

Grooming

.334*

.350**

.488**

.418**

.347**

.071

.297*

.247

.508**

Clothing

.205

.342**

.451**

.324*

.264*

.034

.235

.184

.451**

Basic Skills

.108

.176

.331*

.301*

.271*

-.086

.122

.042

.325*

Interpersonal

skills

.393**

.489**

.455**

.544**

.519**

.142

.444**

.388**

.562**

Home

Maintenance

.355**

.464**

.370**

.439**

.350**

.090

.260

.231

.514**

Money

Management

.193

.446**

.453**

.369**

.271*

.061

.269*

.222

.396**

Cooking.

.354**

.490**

.380**

.476**

.398**

.084

.409**

.344*

.526**

Resource

Utilization

.355**

.497**

.458**

.517**

.504**

.250

.364**

.388**

.519**

General

Occupational

Skills

.405**

.379**

.391**

.471**

.473**

.119

.425**

.363**

.571**

Medication

Management

.385**

.506**

.384**

.505**

.490**

.203

.370**

.367**

.509**

Total

.369**

.487**

.

.467**

.508**

.448**

.138

.394**

.350**

.547**

Note. *p<.05, **p<.01

= .257. At stage 3, results indicate that the overall model which included Zoo Map, Zoo

Map recall, Symbol Search, Trail Making Test Trial 4, Rule Shift Trial 4, and Color-

Word Trial 3 as additional predictors, accounted for an additional 15.1% of the variance

in Hygiene and Grooming ratings. However, again this change was not statistically

significant, ∆R2 = .151, ∆F(6, 19) = .766, p = .605.

Clothing (Independent Living Skills Inventory). There were no significant

correlations found in the schizophrenia group with cannabis use for Clothing ratings.

Therefore, stage 1 of the regression analyses was not conducted. At stage 2, Digit Span,

Rule Shift Trial 2 and the Rule Shift Trial 2 and 4 combined score were entered as


predictors to the regression equation. This model was not found to be statistically

significant, R2 = .198, R

2adj = .098, F(3, 24) = 1.975, p = .145. Due to the non-significant

results in the previous stage, at stage 3 only Zoo Map recall, Symbol Search, Trail

Making Test Trial 4, and Color-Word Trial 3 were entered as predictors in the model.

Results indicate that the overall model did not significantly predict the variance in

Clothing ratings, R2 = .125, R

2adj = -.027, F(4, 23) = .819, p = .526.

Basic Skills (Independent Living Skills Inventory). As there were no significant

correlations found in each of the separate groups for Basic Skills ratings, stage 1 and 2

of the regression analyses were not conducted. At stage 3, Digit Span, Symbol Search,

Trail Making Test Trial 4, and Color-Word Trial 3 were entered as predictors. Results

indicate that the overall model did not significantly predict ratings in Basic Skills, R2 =

.068, R2

adj = -.094, F(4, 23) = .418, p = .794.

Interpersonal skills (Independent Living Skills Inventory). At stage 1, Symbol

Search significantly accounted for 17.9% of the variance in Interpersonal Skills ratings

in schizophrenia patients with cannabis use, R2 = .209, R

2adj = .179, F(1, 26) = 6.881, p

= .014. The effect size is considered to be ‘medium’ (f 2

= .26) (Cohen, 1988). At stage

2, Color-Word Trial 3 was added as a predictor to the regression equation and

accounted for an additional 0.9% of the variance in Interpersonal Skills ratings, with

this change being non-significant, ∆R2 = .009, ∆F(1, 25) = 2.83, p = .599. At stage 3,

the overall model which included Zoo Map, Zoo Map recall, Digit Span, Trail Making

Test Trial 4, Rule Shift Trial 4, and the Rule Shift Trial 2 and 4 combined score as

additional predictors, accounted for an additional 0.7% of the variance in Interpersonal

Skills ratings. Once again, this change was not statistically significant, ∆R2 = .074,

∆F(6, 19) = .328, p = .914.


Home Maintenance (Independent Living Skills Inventory). There were no

significant correlations found in the schizophrenia group with cannabis use, hence stage

1 of the regression analyses was not conducted. At stage 2, Rule Shift Trial 2 was

entered as a predictor into the regression equation. This model was not found to be

statistically significant, R2 = .029, R

2adj = -.008, F(1, 26) = .783, p = .384. Due to this

non-significant result, at stage 3 only Zoo Map, Zoo Map recall, Digit Span, Symbol

Search, Trail Making Test Trial 4, and Color-Word Trial 3 were entered as predictors,

with again no significant results, R2 = .193, R

2adj = -.038, F(6, 21) = .835, p = .557.

Money Management (Independent Living Skills Inventory). No significant

correlations were found in the schizophrenia group with cannabis use. Therefore, stage

1 of the regression analyses was not conducted. At stage 2, Digit Span was entered as a

predictor into the regression equation with the model not being statistically significant,

R2 = .037, R

2adj = .000, F(1, 26) = 1.013, p = .324. Due to this result, at stage 3 only Zoo

Map recall, Symbol Search, Trail Making Test Trial 4, Rule Shift Trial 4, and Color-

Word Trial 3 were entered as predictors. No significant results were found, R2 = .211,

R2

adj = .032, F(5, 22) = 1.179, p = .351.

Cooking (Independent Living Skills Inventory). At stage 1, Symbol Search

significantly accounted for 17.7% of the variance in Cooking ratings in schizophrenia

patients with cannabis use, R2 = .207, R

2adj = .177, F(1, 26) = 6.807, p = .015. The effect

size is ‘medium’ (f 2

= .26) (Cohen, 1988). At stage 2, Rule Shift Trial 2 was added as a

predictor to the regression equation and accounted for an additional 7.3% of the

variance in Cooking ratings with this change not being statistically significant, ∆R2 =

.073, ∆F(1, 25) = 2.502, p = .126. For stage 3, the overall model which included Zoo

Map, Zoo Map recall, Digit Span, Trail Making Test Trial 4, Rule Shift Trial 4, Rule

Shift Trial 2 and 4 combined score, and Color-Word Trial 3 as additional predictors,


accounted for an additional 13.5% of the variance in Cooking ratings, with no further

significant results found, ∆R2 = .135, ∆F(7, 19) = .557, p = .781.

Resource Utilization (Independent Living Skills Inventory). At stage 1, Symbol

Search significantly accounted for 11.9% of the variance in Resource Utilization ratings

in schizophrenia patients with cannabis use, R2 = .152, R

2adj = .119, F(1, 26) = 4.663, p

= .040, with a ‘medium’ effect size (f 2

= .18) (Cohen, 1988). At stage 2, Digit Span,

Rule Shift Trial 2 and the Rule Shift Trial 2 and 4 combined score were added as

additional predictors to the model and accounted for an additional 10.9% of the variance

in Resource Utilization ratings. However, this change was not significant, ∆R2 = .109,

∆F(3, 23) = 1.133, p = .357. At stage 3, the overall model which included Zoo Map,

Zoo Map recall, Trail Making Test Trial 4, Rule Shift Trial 4, and Color-Word Trial 3

as additional predictors, accounted for an additional 13.2% of the variance in Resource

Utilization ratings with this change being non-significant, ∆R2 = .132, ∆F(5, 21) = .775,

p = .579.

General Occupational Skills (Independent Living Skills Inventory). No

significant correlations were found in each of the separate groups, therefore stage 1 and

2 of the regression analyses were not conducted. At stage 3, Zoo Map, Zoo Map recall,

Digit Span, Symbol Search, Trail Making Test Trial 4, Rule Shift Trial 4, the Rule Shift

Trial 2 and 4 combined score, and Color-Word Trial 3 were entered as predictors.

Results indicate that the overall model did not significantly predict ratings in General

Occupational Skills in schizophrenia patients with cannabis use, R2 = .200, R

2adj = -.136,

F(8, 19) = .595, p = .771.

Medication Management (Independent Living Skills Inventory). At stage 1,

Symbol Search significantly accounted for 15.5% of the variance in Medication

Management ratings in schizophrenia patients with cannabis use, R2 = .186, R

2adj = .155,


F(1, 26) = 5.945, p = .022, with a ‘medium’ effect size (f 2

= .23) (Cohen, 1988). At

stage 2, Color-Word Trial 3 was added to the equation and accounted for an additional

0.2% of the variance in Medication Management ratings with results not being

statistically significant, ∆R2 = .002, ∆F(1, 25) = .069, p = .795. At stage 3, the overall

model included Zoo Map, Zoo Map recall, Digit Span, Trail Making Test Trial 4, Rule

Shift Trial 4, the Rule Shift Trial 2 and 4 combined score, and Color-Word Trial 3 as

additional predictors and accounted for an additional 9.6% of the variance in

Medication Management ratings. Again, no further significant results were found, ∆R2 =

.096, ∆F(6, 20) = .448, p = .838.

Total ILSI Score (Independent Living Skills Inventory). At stage 1, Symbol

Search significantly accounted for 11.9% of the variance in the Total ILSI Score in

schizophrenia patients with cannabis use, R2 = .151, R

2adj = .119, F(1, 26) = 4.630, p =

.041. The effect size is considered ‘medium’ (f 2

= .18) (Cohen, 1988). At stage 2, Rule

Shift Trial 2 and Color-Word Trial 3 were included as additional predictors to the

regression equation and accounted for an additional 6.2% of the variance in the Total

ILSI Score with the results however, being non-significant, ∆R2 = .062, ∆F(2, 24) =

.938, p = .405. At stage 3, the overall model included Zoo Map, Zoo Map recall, Digit

Span, Trail Making Test Trial 4, Rule Shift Trial 4, and the Rule Shift Trial 2 and 4

combined score as additional predictors and accounted for an additional 12.3% of the

variance in the Total ILSI Score. However, again this change was not statistically

significant, ∆R2 = .123, ∆F(6, 20) = .566, p = .753.

Following post hoc Holm-Bonferroni correction, the abovementioned significant

results were found to no longer remain. However, considering the small sample size and

extent to the nature of the analyses performed, it is acknowledged that the current study

was likely underpowered in order to detect more significant results. Therefore, the


significant results prior to correction will still be reported and further considered in the

following chapter.

Table 10 displays a summary of significant regression statistics for the

individual ILSI sub-scale models and total ILSI score model.

Moderation effects on executive function measures for functional outcome.

The results outlined in Table 7 & Table 8 indicate that the relationships between

executive function test performance and functional outcome differ across groups and

hence suggestive of possible moderation effects on 8 of the functional outcome sub-

domains, namely: Hygiene & Grooming, Clothing, Interpersonal Skills, Home

Maintenance, Money Management, Cooking, Resource Utilization, Medication

Management, as well as on the Total ILSI Score. Therefore, additional regression

analyses were conducted in order to further explore these potential moderation

relationships. In this phase of regression analyses, 3 variables were entered into the

regression equation in order to examine possible moderation effects. Firstly, a new

variable was computed which calculated the interaction between Group (schizophrenia

patients with cannabis use and matched-controls with a similar cannabis use history)

and the executive function measure of interest. This variable was then entered, in

addition to the executive function measure of interest, as well as the Group variable.

Once again, only those executive function measures which showed a significant

correlation with the functional outcome sub-scale ratings (from the Pearson correlation

analyses), or the Total ILSI score, in each of the separate groups (i.e., schizophrenia

group with cannabis use and matched-controls group with a similar cannabis use

history) were entered into the regression analyses. Regression analyses in this phase

were conducted using the overall combined sample (N = 56). Once again, before

interpreting the results of the regression analyses, assumption tests and checks were


Table 10. Regression models for predicting ILSI ratings

Outcome

Variable

Predictor

Variable

B Standard

error

Beta

(β)

Effect size

(f 2) p-value

Hygiene &

Grooming

Digit Span .150 .062 .429 .23 .023*

Interpersonal

Skills

Symbol Search .123 .047 .457 .26 .014*

Cooking Symbol Search .141 .054 .456 .26 .015*

Resource

Utilization

Symbol Search .110 .051 .390 .18 .040*

Medication

Management

Symbol Search .156 .064 .431 .23 .022*

Total ILSI

Score

Symbol Search .098 .045 .389 .18 .041*

Note. *p<.05, **p<.01

performed with results indicating assumptions of normality, linearity and

homoscedasticity of residuals were met. Further, multivariate outliers and

multicollinearity were not found to be an issue.

Hygiene and Grooming (Independent Living Skills Inventory). Results indicate

that the overall model which included Digit Span significantly accounted for 34.3% of

the variance in Hygiene and Grooming ratings on the Independent Living Skills

Inventory in the combined sample, R2 = .379, R

2adj = .343, F(3, 52) = 10.591, p < .001.

Digit Span (B = .297, β = 1.33, p =.004) and Group (B = 1.76, β = 1.61, p = .004) were

found to have a significant impact on Hygiene and Grooming ratings at an individual

level. The Group*Digit Span variable was also found to have a significant impact on the

outcome variable (B = -.146, β = -2.07, p = .017), suggesting that a moderation effect

between groups on Digit Span was present for Hygiene and Grooming ratings. Figure 1

displays the moderation effect between groups on Digit Span for Hygiene and

Grooming ratings. The difference in slopes between groups shown in Figure 1 indicate

that Digit Span has more predictive power for the schizophrenia group, than it does for

the matched-control group in relation to predicting Hygiene and Grooming ratings.


Figure 1. Moderation effect between groups on Digit Span for Hygiene and Grooming ratings

The overall model which included Rule Shift Trial 2 as the executive function

measure of interest, significantly accounted for 22.2% of the variance in Hygiene and

Grooming ratings in the combined sample, R2 = .264, R

2adj = .222, F(3, 52) = 6.218, p =

.001. However at an individual level, Rule Shift Trial 2 (B = -.481, β = -.748, p = .362),

Group (B = -.967, β = -.884, p = .629), and the Group*Rule Shift Trial 2 variable (B =

.393, β = 1.748, p = .438) were not found to have a significant impact on Hygiene and

Grooming ratings.

Clothing (Independent Living Skills Inventory). The overall model which

included Digit Span significantly accounted for 28.2% of the variance in Clothing

ratings in the combined sample, R2 = .321, R

2adj = .282, F(3, 52) = 8.201, p < .001.

However, results additionally indicate that Digit Span (B = .155, β = .781, p = .094),

Group (B = 1.04, β = .553, p = .066), and the Group*Digit Span variable (B = -.069, β =

-1.101, p = .217) were not found to have any individual significant impact on Clothing

ratings.

Results also indicate that the model which included Rule Shift Trial 2,

significantly accounted for 26.1% of the variance in Clothing ratings in the combined


sample, R2 = .301, R

2adj = .261, F(3, 52) = 7.467, p < .001. No further significant results

were found at an individual level for Rule Shift Trial 2 (B = -.537, β = .455, p = .244),

Group (B = -1.127, β = -1.153, p = .518), and the Group*Rule Shift Trial 2 variable (B =

.427, β = 2.126, p = .333).

The model including the Rule Shift Trial 2 and 4 combined score significantly

accounted for 25.9% of the variance in Clothing ratings in the combined sample, R2 =

.299, R2

adj = .259, F(3, 52) = 7.403, p < .001. At the individual level, no additional

significant results were found for Rule Shift Trial 2 and 4 combined score (B = -.195, β

= -.658, p = .162), Group (B = -.242, β = -.248, p = .759), and the Group*Rule Shift

Trial 2 and 4 combined score variable (B = .121, β = 1.271, p = .280).

Interpersonal Skills (Independent Living Skills Inventory). By including

Symbol Search as a predictor, the model significantly accounted for 52.1% of the

variance in Interpersonal Skills ratings in the combined sample, R2 = .547, R

2adj = .521,

F(3, 52) = 20.939, p < .001. In addition, Symbol Search (B = .252, β = 1.152, p = .002),

Group (B = 1.913, β = 1.461, p < .001) and the Group*Symbol Search variable (B = -

.129, β = -1.617, p = .010) were found to each have a significant impact on the outcome

variable. The significant results of the interaction term suggest a moderation effect

between groups on Symbol Search for Interpersonal Skills ratings (see Figure 2). Figure

2 displays the difference in the regression slopes between groups which suggest that

Symbol Search had better predictive ability for Interpersonal Skills ratings for the

schizophrenia group, than for matched-controls.

The model which included Color-Word Trial 3, significantly accounted for

47.7% of the variance in Interpersonal Skills ratings in the combined sample, R2 = .506,

R2

adj = .477, F(3, 52) = 17.731, p < .001. Significant individual results for Color-Word

Trial 3 (B = .165, β = .887, p = .034) and Group (B = 1.741, β = 1.330, p = .019), were


Figure 2. Moderation effect between groups on Symbol Search for Interpersonal Skills ratings

also found. However, there were no further significant results for the Group*Color-

Word Trial 3 variable (B = -.099, β = -1.289, p = .127).

Home Maintenance (Independent Living Skills Inventory). Including Rule

Shift Trial 2 as a predictor resulted in a model which significantly accounted for 32.5%

of the variance in Home Maintenance ratings in the combined sample, R2 = .362, R

2adj =

.325, F(3, 52) = 9.843, p < .001. At the individual level, no further significant results

were found for Rule Shift Trial 2 (B = -.639, β = -.693, p = .364), Group (B = -.988, β =

-.630, p = .711), and the Group*Rule Shift Trial 2 variable (B = .501, β = -1.552, p =

.459).

Money Management (Independent Living Skills Inventory). Results indicate

that the model including Digit Span, significantly accounted for 30.7% of the variance

in Money Management ratings in the combined sample, R2 = .344, R

2adj = .307, F(3, 52)

= 9.103, p < .001. However, no significant individual results were found for Digit Span

(B = .126, β = .435, p = .338), Group (B = 1.060, β = .744, p = .187), and the

Group*Digit Span variable (B = -.044, β = -.476, p = .585).


Cooking (Independent Living Skills Inventory). The model including Symbol

Search as a predictor, significantly accounted for 41.4% of the variance in Cooking


2adj = .414, F(3, 52) = 13.972, p < .001.

Results additionally indicated that Symbol Search (B = .308, β = 1.311, p = .001),

Group (B = 2.198, β = 1.567, p < .001), and the Group*Symbol Search variable (B = -

.167, β = -1.948, p = .005) were found to have a statistically significant impact on the

outcome variable at an individual level. The significant result of the interaction term

suggests that a moderation effect between groups on Symbol Search is present for

Cooking ratings (see Figure 3). Figure 3 highlights the differences in regression slope

between groups showing that Symbol Search had better predictive ability for Cooking

ratings in the schizophrenia group, than for the matched-control group.

The model including Rule Shift Trial 2, significantly accounted for 30.4% of the

variance in Cooking ratings in the combined sample, R2 = .342, R

2adj = .304, F(3, 52) =

9.013, p < .001. However, no further significant results were found for Rule Shift Trial

2 (B = -.879, β = -1.066, p = .172), Group (B = -2.119, β = -1.510, p = .384), and the

Group*Rule Shift Trial 2 variable (B = .750, β = 2.600, p = .224), at an individual level.

Resource Utilization (Independent Living Skills Inventory). The overall model

including Symbol Search as a predictor, significantly accounted for 46.3% of the

variance in Resource Utilization ratings in the combined sample, R2 = .492, R

2adj = .463,

F(3, 52) = 16.818, p < .001. In addition, Symbol Search (B = .218, β = .941, p = .013)

and Group (B = 1.738, β = 1.256, p = .002) were each found to have a statistically

significant impact on Interpersonal Skills ratings. However, following Holm-Bonferroni

adjustment the result related to the individual impact of Symbol Search no longer

remained significant. The impact of the Group*Symbol Search variable on the outcome


Figure 3. Moderation effect between groups on Symbol Search for Cooking Ratings

variable was found to approach significance (B = -.108, β = -1.274, p = .051),

suggesting a trend towards a moderation effect between groups on Symbol Search for

Resource Utilization ratings (see Figure 4). The regression line differences seen in

Figure 4 illustrate the higher predictive ability of Symbol Search for Resource

Utilization ratings in the schizophrenia group, than in the matched-control group.

By including Digit Span into the regression equation, the model significantly

accounted for 38.8% of the variance in Resource Utilization ratings in the combined

sample, R2 = .422, R

2adj = .388, F(3, 52) = 12.647, p < .001. No individual significant

results were found for Digit Span (B = .050, β = .178, p = .675), Group (B = .836, β =

.604, p = .253), and the Group*Digit Span variable (B = -.007, β = -.073, p = .929).

The model including Rule Shift Trial 2, significantly accounted for 41.1% of the

variance in Resource Utilization ratings in the combined sample, R2 = .443, R

2adj = .411,

F(3, 52) = 13.813, p < .001. However, additional results were not significant for Rule

Shift Trial 2 (B = -1.003, β = -1.234, p = .087), Group (B = -3.065, β = -2.215, p =

.167), and the Group*Rule Shift Trial 2 variable (B = .997, β = 3.503, p = .077), at the

individual level.


Figure 4. Moderation effect between groups on Symbol Search for Resource Utilization ratings

Including the Rule Shift Trial 2 and 4 combined score in the regression equation,

the model significantly accounted for 38.5% of the variance in Resource Utilization


2adj = .385, F(3, 52) = 12.456, p < .001. No

additional significant results were found for the Rule Shift Trial 2 and 4 combined score

(B = -.148, β = -.354, p = .407), Group (B = -.062, β = -.045, p = .952), and the

Group*Rule Shift Trial 2 and 4 combined score variable (B = .134, β = .946, p = .356),

when examining individual effects.

Medication Management (Independent Living Skills Inventory). With Symbol

Search included as a predictor, the overall model was found to significantly account for

43.7% of the variance in Medication Management ratings in the combined sample, R2 =

.468, R2

adj = .437, F(3, 52) = 15.241, p < .001. Additional results found Symbol Search

(B = .324, β = 1.175, p= .003), Group (B = 2.359, β = 1.431, p = .001), and the

Group*Symbol Search variable (B = -.168, β = -1.670, p = .013) to each have a

significant impact on the outcome variable. Results suggest a moderation effect between

groups on Symbol Search for Medication Management ratings (see Figure 5). Once

again, differences in regression slopes are displayed in Figure 5 indicating that Symbol


Figure 5. Moderation effect between groups on Symbol Search for Medication Management ratings

Search has better predictive ability for Medication Management ratings in the

schizophrenia group, than for matched-controls.

By adding Color-Word Trial 3 into the regression equation, the model

significantly accounted for 37.8% of the variance in Medication Management ratings in

the combined sample, R2 = .412, R

2adj = .378, F(3, 52) = 12.127, p < .001. No further

individual significant results were found for Color-Word Trial 3 (B = .189, β = .808, p =

.076), and the Group*Color-Word Trial 3 variable (B = -.114, β = -1.173, p = .201). The

individual impact of Group on the outcome variable was found to approach significance

(B = 1.985, β = 1.204, p = .050).

Total ILSI Score (Independent Living Skills Inventory). The overall model

which included Symbol Search, significantly accounted for 48.6% of the variance in

Total ILSI scores in the combined sample, R2 = .514, R

2adj = .486, F(3, 52) = 18.320, p <

.001. Examining individual effects, it was found that Symbol Search (B = .203, β =

.995, p = .007), Group (B = 1.671, β = 1.368, p = .001), and the Group*Symbol Search

variable (B = -.106, β = -1.416, p = .027) each had a statistically significant impact on


the outcome variable. The significant result of the interaction term suggests a

moderation effect between groups on Symbol Search for the Total ILSI score (see

Figure 6). The regression line differences shown in Figure 6 demonstrate that Symbol

Search has better predictive power for the schizophrenia group regarding the Total ILSI

score, than for the matched-control group.

By including Rule Shift Trial 2 as a predictor into the regression equation, the

model significantly accounted for 41.4% of the variance in Total ILSI scores in the

combined sample, R2 = .446, R

2adj = .414, F(3, 52) = 13.941, p < .001. No additional

individual significant results were found for Rule Shift Trial 2 (B = -.483, β = -.673, p =

.345), Group (B = -.707, β = -.579, p = .715), and the Group*Rule Shift Trial 2 variable

(B = .394, β = 1.567, p = .423).

The model including Color-Word Trial 3, significantly accounted for 46.1% of

the variance in Total ILSI scores in the combined sample, R2 = .490, R

2adj = .461, F(3,

52) = 16.685, p < .001. Color- Word Trial 3 (B = .135, β = .780, p = .066), and the

Group*Color-Word Trial 3 variable (B = -.080, β = -1.109, p = .194) were not found to

have any individual significant impact on Total ILSI scores. However, Group was found

to have a significant impact on the outcome variable (B = 1.497, β = 1.226, p = .033).

Once again, it is important to note that considering the small sample size and the

extent to the nature of the abovementioned analyses performed, it is acknowledged that

the current study was likely underpowered in order to detect more significant results

following post hoc Holm-Bonferroni correction. Therefore the results that no longer

remained significant following adjustment will still be reported and considered.


Figure 6. Moderation effect between groups on Symbol Search for Total ILSI Score

The overall reported regression analyses results indicate, as well as confirm, that

Digit Span is a significant predictor of Hygiene and Grooming ratings, and Symbol

Search significantly predicts Interpersonal Skills, Cooking, Resource Utilization,

Medication Management ratings, as well as the Total ILSI score, for schizophrenia

patients with cannabis use. However, results also suggest that these measures have

greater predictive power for the schizophrenia group, than they have for the matched-

control group, in predicting ratings in the abovementioned ILSI areas, and Total ILSI

score.

General Discussion

The current study sought to further our understanding of the neurocognitive

profiles associated with schizophrenia patients with cannabis use and more specifically,

their distinct profiles in relation to executive function. Previous research has explored

this by examining group differences in neurocognitive performance between cannabis-

using schizophrenia patients and non-cannabis using schizophrenia patients. However,

the literature evaluating these differences has produced contradictory findings. Such


mixed results are likely due to variations in methodology, the failure to account for

various indicators of cannabis use (e.g., a range of cannabis use parameters such as

frequency, severity/quantity, duration and length of abstinence), a lacking in the

examination of clinical ‘impairment’ levels, and varying approaches in classifying

cannabis users. The present research aimed to address these issues not by directly

investigating the possible additive relationship between cannabis use and schizophrenia

on neurocognitive performance, but instead by examining the differential effects of

cannabis use on cognitive performance in individuals with schizophrenia in comparison

to otherwise healthy subjects with a similar cannabis use history, in relation to one

specific neurocognitive system namely, executive function.

While the neurocognitive profiles of individuals with schizophrenia have been

already well established in the literature, little is known about specific patterns that may

exist in the schizophrenia patient with cannabis use population particularly in relation to

the different aspects of executive function. The neurocognitive system of executive

function is considered to have particular clinical relevance as executive function deficits

have been found to be specifically associated with the illness of schizophrenia (Pantelis

et al., 1997; Reichenberg & Harvey, 2007, Shallice et al., 1999), and have also been

associated with functional outcome (Greenwood et al., 2005; McClure et al., 2007;

Williams et al., 2008).

The current study was divided into two parts. Part A of the research aimed to

determine whether differences exist in executive function performance between

schizophrenia patients with cannabis use and otherwise healthy controls with a similar

cannabis use history. This was achieved by assessing the neurocognitive performance of

both groups on several measures of executive functioning which were guided by West’s

(1996) theoretical model of executive function. Additional executive function constructs


which appeared to not be described in West’s model, were also included in the study for

exploration purposes. In line with this further exploration, the construct validity of

West’s theoretical model of executive function in the current sample was also

examined. The present research also permits some comment on whether cannabis use

status and length of abstinence have an impact on differences in executive function

performance. Part B to the study aimed to explore the relationship between executive

function performance and functional outcome. Of particular interest was determining

whether performance on specific executive function measures predicted performance in

different functional outcome sub-domains, as well as overall functional outcome.

Overall, there are four principal findings from Part A of the present study: a)

schizophrenia patients with cannabis use demonstrated poorer performances on a range

of executive function domains when compared to participants from the matched-control

group with a similar cannabis use history; however, a significantly larger proportion of

the schizophrenia group with cannabis use demonstrated performances that were not at

an impaired level compared to those falling in the impaired range; b) an underlying

structure was found to exist on a number of selected tests of executive function,

providing partial support for the construct validity of West’s (1996) theoretical model of

executive function in the current sample; c) the discontinuation of, or abstinence from,

cannabis use was mainly not found to be associated with the recovery of executive

functioning; d) longer abstinence periods were mainly not found to be associated with

the recovery of executive function.

The main findings from Part B of the study were that: a) performance on two

executive function measures were shown to significantly predict specific functional

outcome domains, namely Digit Span and Symbol Search, and that: b) moderation

effects on the executive function measures were found for 8 of the individual functional


outcome sub-domains, as well as for overall functional outcome. Each of the main

findings will now be discussed.

Part A


With the interpretation of results being conceptually guided by West’s (1996)

model, schizophrenia patients with cannabis use were found to have poorer performance

in the Temporal Organisation of Behaviour (on the Zoo Map measure only),

Retrospective Memory (on both Zoo Map recall and Digit Span measures), Interference

Control (on both Symbol Search and Trail Making Test Trial 4 measures), and the

Inhibition of Prepotent Responses (on both the Rule Shift Trial’s 2 and 4 and Color-

Word Trial 3 measures), when compared to matched-controls with a similar cannabis

use history. These differences were found after accounting for the possible effects of

estimated premorbid IQ. However, while the Modified Six Elements test was also used

to assess the Temporal Organisation of Behaviour domain, no significant differences

between the two groups was demonstrated on this particular measure. In addition, no

significant differences were found between the two groups in the executive function

domains of Prospective Memory (assessed by an event-based prospective memory task),

Verbal Fluency (assessed by Letter Fluency), and Emotion-based Decision-making

abilities (assessed by the Iowa Gambling Task). Overall these findings could be

interpreted as cannabis possibly playing a different role for patients with schizophrenia,

in comparison to healthy individuals. The pattern of results found in the current study is

somewhat similar to the findings of Jockers-Schrübel and colleagues (2007) showing

that overall, cannabis-using schizophrenic patients performed worse than cannabis-

using healthy controls in most of the neurocognitive tests administered in their study.

Scholes and Martin-Iverson (2010) also found poorer performances across cognitive


tasks in cannabis-using patients relative to healthy cannabis-using controls. In addition

to these findings, contrastingly Jockers-Schrübel and colleagues found that cannabis use

was however associated with better test performance in schizophrenia patients, and

conversely worse performance in healthy control subjects when the regular consumption

of cannabis commenced prior to the age of 17.

It is difficult to compare the current study’s findings when evaluating group

differences in neurocognitive performance as we did not aim to specifically examine

additive effects. However, despite schizophrenia patients with cannabis use

demonstrating poorer performance on a number of executive function measures relative

to controls, a significantly larger proportion of the schizophrenia group with cannabis

use demonstrated performances in the normal range and were not reflective of even

probable neurocognitive impairment. This was determined following examining their

performances against normative mean criteria. As the current study compared the

neurocognitive performances of individuals with schizophrenia to individuals without a

mental illness (with cannabis use being controlled for), it would be reasonable to

interpret the current results as potentially reflecting the effects of schizophrenia alone.

However, as schizophrenia patients have been found to demonstrate neurocognitive

performance on a variety of tests at 1.0 - 2.0 standard deviations below the norm of

healthy populations (Heinrichs & Zakzanis, 1998; Wilk, Gold, Humber, Dickerkson,

Fenton, & Buchanan, 2004), the significantly larger proportion of the schizophrenia

group with cannabis use in the current study demonstrating performances falling in the

normal range is contrary to such observations. Therefore, the current findings are

unlikely to be reflective of just the simple effects of the illness of schizophrenia on

neurocognitive performance alone. If the current findings specifically related to the

schizophrenia group with cannabis use are considered to be a mere reflection of the


effects of the illness of schizophrenia alone, then one would expect performances falling

even in the probable impairment range. However, this was not the case in the present

study.

Despite there being mainly poorer neurocognitive performances demonstrated

by schizophrenia patients with cannabis use on a number of executive function domains

in comparison to those in the matched-control group, there were no significant

differences shown in performance in the domains of Prospective Memory, Verbal

Fluency and Emotion-based Decision-making. These results potentially suggest that

schizophrenia patients with cannabis use show nominal disruptions in performance in

these particular executive function domains. In the current literature review, no research

to date has been located where measures assessing the domain of Prospective Memory

have been used to directly examine the neurocognitive performance of schizophrenia

patients with cannabis use in particular. Therefore, a comparison of the results on this

executive function domain to past findings is difficult. However, in a meta-analytic

review of 11 studies examining prospective memory performance in schizophrenia

patients, impairments were found on time-, event-, and activity-based prospective

memory tasks compared to controls (Wang, Cui, Chan, Deng, Shi, Hong et al., 2009). In

addition, performances on time-based prospective memory tasks were demonstrated to

be more impaired than performances on event-based tasks. It was considered by the

authors that time-based prospective memory measures may require a greater level of

self-initiation than tests of event-based prospective memory. Therefore, while the

present findings may suggest that schizophrenia patients with cannabis use show

nominal disruptions in this domain, in alternative it could also indicate that the event-

based prospective memory measure used may not have sufficiently loaded onto

prospective memory abilities. Previous research has also found no difference in


performance amongst cannabis-abusing patients in verbal fluency in comparison to non-

abusers (Mata et al., 2008; Schnell et al., 2009). The current results involving emotion-

based decision making abilities were somewhat inconsistent with Sevy and colleagues’

study (2007), where it was reported that both schizophrenia groups (i.e., both cannabis

users and non-users) were found to be more cognitively impaired, and demonstrated

worse performance on the Iowa Gambling Task, when compared to healthy controls.

However, the healthy participants in this study were not matched for cannabis use and

included six individuals who reported smoking marijuana less than 10 times in their

lifetime, as well as individuals who did not report any cannabis use history. Therefore, it

is possible that the measures selected in order to assess these domains may actually be

sensitive enough measures in detecting deficits in executive function, but do not

demonstrate specificity in identifying differences in this particular schizophrenia sub-

population.

While the Temporal Organisation of Behaviour was also measured by the

Modified Six Elements test in the current study, a lack of significant difference in

performance between groups on this measure may suggest that this particular test was

also perhaps not sensitive enough, nor did not sufficiently load onto this particular

executive function domain, in order to detect differences in these samples. It is also

possible that the samples recruited in the current study may have high heterogeneity,

thus creating more variability within groups and making differences between groups

harder to locate. However, as group differences were demonstrated on another measure

of the Temporal Organisation of Behaviour (namely the Zoo Map task), as well as many

other measures tapping into additional executive function domains, it is unlikely that

this was the case. In addition, estimated premorbid IQ was found to have an impact on

Modified Six Elements task performance and this could suggest that while this test may


assess an aspect of executive function, it may also rely upon other cognitive abilities

specifically related to premorbid IQ. There has also not been any research located to

date directly examining the performance of cannabis-using schizophrenia patients in

particular on the Modified Six Elements test which limits the ability to compare and

contrast the current results with previous findings.

Level of executive function impairment between groups. The different

performances of the two groups, requires further comment. Due to the lack of clinically

impaired performances observed in a significant proportion of the schizophrenia group

with cannabis use and the expected performance of 1.0 - 2.0 standard deviations below

the norm for cannabis-naive schizophrenia patients, it appears that cannabis use in

schizophrenia may have relatively nominal clinical effects on executive function

performance when compared to normative criteria. A possible explanation for this result

may be due to cannabis use in schizophrenia being potentially associated with outcomes

of a more preserving nature. Cannabinoids have been shown to possess characteristics

serving to protect individuals from brain insult and are associated with improvements in

a range of illnesses which are considered neurodegenerative in nature (Sarne &

Mechoulam, 2005). Thus, the findings of the present study may be reflective of

differential effects of cannabis on the brain of individuals with schizophrenia, as

opposed to a healthy brain, potentially as a consequence of neuroprotective effects.

As the examination of impairment level was based on normative criteria, it is

also reasonable to consider that schizophrenia patients with cannabis use may represent

a distinct schizophrenia sub-population that has specific executive function abilities

remaining at a non-impaired level when compared to individuals with schizophrenia

who are cannabis naive. It has been postulated that the onset of psychosis in this

subgroup may be aetiologically different to non-using schizophrenic patients, such that


cannabis use may serve as a catalyst to the onset of the illness in these individuals who

may already possess better premorbid adjustment, social skills and hence a better

prognosis, than their non-using counterparts (Dixon et al., 1991, Leeson et al., 2011;

Rodríguez-Sánchez et al., 2010). It has also been suggested that this sub-group may

have a lower vulnerability to the illness compared to those patients whose illness onset

occur independent of the context of cannabis use (Schnell et al., 2009). Therefore, it is

possible that such individuals already have better cognitive abilities due to not

possessing as many neurodevelopmental risk factors, as well as having more enhanced

prognostic characteristics (Leeson et al., 2011). Findings from Kumra and colleagues’

study (2005) showed that a history of cannabis use/dependence was associated with

better FSIQ, as well as better VIQ, scores which also suggests the presence of better

cognitive adjustment in cannabis-using schizophrenics. The lack of clinical impairment

demonstrated by schizophrenia patients with cannabis use in the current research is

consistent with the theme that has emerged from previous studies suggesting better

neurocognitive performances in this group when compared to non-using schizophrenia

patients.


Cannabis-use status (i.e., current users and non-current users) was mainly not

found to have an impact on executive function performance, when controlling for the

effects of duration of use (although there were a few notable exceptions to this, as

discussed below). In other words, in general, cannabis use cessation or abstinence was

not associated with the recovery of executive function. These results are also somewhat

consistent with previous findings indicating no significant differences between patients

with current cannabis dependence and patients without a current cannabis dependence

diagnosis (which included both former users and those with minimal or no use) (Rabin


et al., 2013). However, in the present study this was not the case for performance on

Letter Fluency, such that current cannabis users demonstrated better performance on

this task compared to non-current users. A possible explanation for this contrasting

result may be related to premorbid IQ being shown to significantly influence

performance on the Letter Fluency measure, in the earlier analyses of the current study.

Therefore, this finding could provide possible further evidence for current cannabis

users representing a group of individuals with better premorbid IQ, independent of

whether or not they have the illness of schizophrenia. Further, it is plausible that

individuals with better premorbid IQ may be more likely to continue cannabis use due

to possessing the abilities required to continually seek avenues in order to maintain their

drug use. In a recent study which specifically compared the relationship of cannabis use

to premorbid IQ in a group of first episode psychosis patients, results showed that those

patients who had ever smoked cannabis in their lifetime had higher premorbid IQ than

those who had never used cannabis in their lifetime (Ferraro, Russo, O'Connor, Wiffen,

Falcone, Sideli et al., 2013). However, as the current study controlled for premorbid IQ

through the matching process, the findings may not solely be related to premorbid IQ

(as measured by an estimated verbal premorbid IQ measure). Another possible

explanation for these results are in line with previous suggestions that this subgroup of

schizophrenia appears to demonstrate characteristics of having a less severe form of the

illness in relation to neurocognitive abilities and therefore remain relatively cognitively

preserved once psychosis develops potentially in the presence of early cannabis use.

Findings from Barnett, Salmond, Jones, and Sahakian’s (2006) study indicated that

superior cognitive function (i.e., cognitive reserve) may act as a protective function

from cognitive decline. Cognitive reserve is defined as the ‘individual differences in

how people process tasks which allow some to cope better than others with brain


pathology’ (Stern, 2009, p. 2016). In other words, individuals with higher cognitive

reserve are less affected by the same extent of neurological damage caused by either the

effects of the normal aging process, or from the effects of unhealthy aging (i.e., the

result of illnesses which may serve to compromise cognitive function). Barnett and

colleagues (2006) concluded from their results that this higher level of cognitive

function may impact on neuropsychiatric disorders by either influencing the risk for

developing the disorder, the expression of illness symptomatology, or the functional

outcome of the individual. Therefore, the current results suggest that it may not be that

cannabis is neuroprotective in nature, but instead findings implicate the possibility of a

higher overall cognitive reserve in individuals who may belong to this specific

schizophrenia subgroup.


The findings of the current study also showed that the length of abstinence was

mainly not associated with the recovery of executive function, independent of duration

of use. More specifically, shorter abstinence periods were not related to poorer

performance even after duration of use was taken into account. Surprisingly, it was

additionally found that former cannabis users with an abstinence period of less than 5

years demonstrated better skills in the Temporal Organisation of Behaviour compared to

former cannabis users with an abstinence period of equal to, or greater than, 5 years,

although this result was shown for performance on the Zoo Map measure only. This is

somewhat consistent with previous findings which showed that in addition to frequency,

recency of cannabis use was also associated with better neurocognitive performance

related to attention/processing speed and executive function in schizophrenia patients

(Coulston et al., 2007). Stirling and colleagues (2005) also found that schizophrenia

patients who had sustained their cannabis use at follow-up demonstrated better


neurocognitive performance on a variety of measures (i.e., design memory, verbal

fluency, object assembly, block design, picture completion, picture arrangement, face

recognition memory), than those individuals who did not continue their use until this

time. An explanation for this finding may involve the possibility that those individuals

with more recent use may still possess intact temporal organisational skills even after

cannabis use cessation. It could also be considered that perhaps these abilities begin to

reduce over time from the lack of exposure to drug-obtaining and drug use maintenance

activities, as well as the lack of rehearsal of the behaviours necessary to achieve these

objectives. This is a plausible explanation considering the temporal organisation of

behaviour involves temporally organizing steps of a process which serve as a guide in

selecting appropriate behaviors required to complete tasks (Fuster, 1989). It could be

also speculated that such processes are considered to be involved in the perpetuation of

drug use. Results of the current study suggest that these abilities also appear to be intact,

irrespective of the presence or absence of the illness of schizophrenia.


While there was no specific hypothesis outlined regarding the construct validity

of West’s (1996) theoretical model of executive functioning, findings indicated the

presence of an underlying structure on a number of selected tests of executive function

in the current study. The executive function measures which significantly loaded onto

factor 1 (namely Mental Control and Self-Regulation) were those which were guided by

West’s theoretical model. In addition, the executive function measures which were

added for exploration due to not appearing to be accounted for in West’s model (i.e.,

Verbal Fluency and an Emotion-based Decision-making task) seemed to either load

onto a separate component or failed to meet criterion for PCA. The overall results

appear to not only in part, confirm the construct validity of West’s theoretical model of


executive function, but also provide support for the convergent validity, as well as

divergent validity, of the model. Such results are also in part, supported by Num’s

(2006) findings. It is possible that the additional executive function domains that

weren’t accounted for in West’s model are not in fact, reflective of ‘pure’ executive

function domains due to having loaded onto a different component or not being able to

be included in PCA. This may be due to such measures tapping into other

neurocognitive domains in addition to those falling under the executive function

umbrella. While tests of verbal fluency (namely phonemic fluency) are one of the most

frequently utilised measures in the assessment of executive function (Baddley, 1996;

Baldo et al., 2001; Stuss & Levina, 2002), they also are known to activate non-frontal

brain areas (Frith, Friston, Herold, Silbersweig, Fletcher, Cahill et al., 1995; Paulesu,

Goldacre, Scifo, Cappa, Gilardi, Castiglioni et al., 1997). Interestingly, an additional

factor was produced as an outcome of the analysis, namely ‘Maintenance of Intention

for Future Action’. A possible explanation for why the event-based prospective memory

task loaded onto a different factor to factor 1 in the PCA, may have been due to the

specific measure that was selected in the current study not being sensitive enough to tap

into the true prospective memory construct. Similar to Wang et al.’s (2009) conclusions,

time-based prospective memory tasks have been thought to place a greater demand on

self-initiation for successful performance due to the lack of external cues provided in

such a measure and consequently more heavily relies on executive functioning

processes (McDaniel & Einstein, 1993). In addition, the result of Kinch and

McDonald’s (2001) study, suggest that successful performance in an event-based

prospective memory task was primarily attributed to retrospective memory abilities.

Therefore, it is possible that the abilities assessed by this particular type of prospective

memory task may not just reflect a more crucial underlying executive function process


such as retrospective memory, but in addition may tap into abilities falling outside of

the executive function domain alone. It is also reasonable to consider that Trial 3 of the

Color-Word Interference subtest of the D-KEFS may not just reflect the inhibition of

more dominant, habitual responses, but also measure the maintenance of information

required to perform a future action.

It has been argued that while various neuropsychological measures may have

good face validity, demonstrated high construct validity is imperative in order for such

measures to represent a construct accurately (Salthouse et al., 2003). Therefore, results

suggest that the majority of the executive function measures which loaded onto factor 1

demonstrate an ability to be sensitive to the executive processes conceptualised by

West’s model, but in addition they also demonstrate specificity in being able to tap into

these specific neurocognitive processes as opposed to others.

In order to conduct the PCA, the sub-samples were combined due to their small

sizes. As it was considered in previous literature (e.g., Solowij & Michie, 2007) that

cannabis users demonstrate deficits on cognitive measures similar to those shown in

schizophrenia patients, there is a chance that the sub-samples in the current study are

not all that dissimilar in cognition factor structure. Therefore, combining the samples

would be appropriate. However, it is considered that if the sub-samples are indeed

dissimilar to each other then this may help to explain why some executive function

measures did not load onto factor 1. Considering the PCA was intended to be

exploratory in nature, the results of this analysis were also not used in further analyses

and therefore, the interpretation of results should only be considered on a theoretical

basis. Prospective studies with larger samples should seek to further examine the factor

structure of cognition in schizophrenia patients with cannabis use, and cannabis users

with a similar cannabis use history, in order to clarify any similarities or dissimilarities.


It is also acknowledged that the current study did not aim to examine the actual

hierarchy of functions from West’s (1996) hierarchical model of executive function.

However, was considered that an analysis of this type would require much larger

samples. Future studies should look to examine the hierarchy of functions in West’s

model in patient populations in order to assist in further evaluating the validity of the

hierarchical nature of the model.

As the current study is the only study to date to have utilised this theoretical

model of executive function to guide test selections in order to assess the executive

functioning of individuals with schizophrenia, further studies are warranted to replicate

the present findings. Taking into account the abovementioned results, future

investigations should also consider the use of a time-based prospective memory

measure in order to better clarify the role, as well as confirm or disconfirm the

inclusion, of this particular cognitive domain in the executive function model. However,

the assessment methodology of the current study may provide a more effective approach

to future research, particularly when attempting to comprehensively assess and

fractionate the executive function system.

Part B


Findings from the present study not only showed that different aspects of

executive functioning were predictive of ‘real world’ functional outcome in

schizophrenia patients with cannabis use, but that these aspects also moderated the level

of functional outcome in different groups. From the variety of executive function

measures administered in the current research, it was found that performance on the

specific measures of Digit Span and Symbol Search significantly predicted performance


in particular areas of functional outcome for schizophrenia patients with cannabis use,

in comparison to that for the matched-control group.

Findings suggest that performance on Digit Span (a measure used to assess

Retrospective Memory), was significantly related to those functional outcome skills

associated with hygiene and grooming. It can be speculated why this aspect of executive

functioning would be related to this particular functional outcome sub-domain. It is

reasonable to consider that Retrospective Memory, which involves the maintenance of

task-relevant information online and provides a reference by which a task sequence is

formed (Fuster, 1989), has particular importance in maintaining adequate independent

skills in hygiene and grooming. Schroots, Dijkum, and Assink (2004) define

retrospective autobiographical memory as the ability to retrieve certain memories,

experiences, or past events in the present time. Dritschel et al. (1998) argued that

participants with traumatic brain injury would be able to plan further activities more

easily if they first tried to retrieve specific autobiographical memories of where they

have executed similar activities in the past and described step-by-step what they did. In

addition, Burgess and Shallice (1997) argued that the application of retrospective

memory processes, in particular those that are implicated in the recollection of previous

experiences play a critical part in prospective memory (i.e., the set of abilities that

enable an individual to carry out a future intention or plan-following behaviour). In

support of this, Kinch and McDonald (2001) also considered that a crucial component

of remembering the intention to commit a future action or task (i.e., prospective

memory) is considered to be largely retrospective in nature. Therefore, it appears that

retrospective memory processes in some form have the capacity to assist individuals to

carry out planned future intentions and one could expect such processes to be in

involved in the daily requirements of hygiene and grooming activities.


While in the current study retrospective memory has been considered a

component of executive function in West’s (1996) theoretical model of executive

function, it is acknowledged that the retrospective memory does include some more

general cognitive abilities that are not necessarily specific to the frontal lobe system.

However, Fuster (2000) refers to retrospective memory as short-term memory or

sensory working memory and uses the term ‘active short-term memory’ to encompass

the construct (p. 67). It has also been well documented that short-term active memory

involves prefrontal neurons (e.g., Funahashi, 1989; Fuster, 1973; Niki, 1974). In

addition, West (1996) conceptualises retrospective memory in his model as involving

the retrieval and maintenance of information that is task-relevant from its storage in

memory and is conceptualised to be similar to working memory. Much consistency

between the types of memory deficits experienced by patients with lesions of the frontal

lobe and by healthy older adults has been observed due to both types of subjects

demonstrating deficits on measures of memory which are thought to heavily require

processes that are strategic in nature and hence, executive functioning (Moscovitch &

Winocur, 1992). Further, it is important to note there have been a number of measures

utilised when assessing retrospective memory abilities in the literature. Some of these

include span, working memory, recall and recognition type measures. In the current

study, two measures were used in an attempt to assess retrospective memory abilities,

namely Digit Span (forwards assessing span, and backwards assessing working

memory) and Zoo Map recall (assessing free recall). While it is acknowledged that total

Digit Span provides a combination of span, as well as working memory abilities,

previous research has also utilised forward Digit Span as one approach to assessing

retrospective memory abilities (Maylor, Smith, Della Salla, & Logie, 2002). The authors

described retrospective memory being usually assessed by tasks that involve the


presentation of information that is subsequently required to be recalled or recognized

following a cue. In addition, the results of Maylor and colleagues’ (2002) factor analytic

study showed that more traditional Retrospective abilities (as measured by free recall

and recognition) and working memory abilities (as measured by Digit Span and

Sentence Span) loaded highly on one factor in a sample patients with Alzheimer’s

Disease and healthy older adults.

It is noted that the findings of Dickinson et al.’s (2008) study indicate that the

neuropsychological impairments associated with the illness of schizophrenia relative to

healthy control subjects is largely mediated through a common ability factor and that

further analyses revealed direct diagnosis effects on verbal memory and processing

speed. Therefore, it is reasonable to consider that processing speed and simple

maintenance working memory may have a more direct impact on the everyday

outcomes of schizophrenia patients based on such results. However, it may be erroneous

to apply the same conclusions about the cognition of schizophrenia patients with

cannabis use, particularly because the current study’s results related to impairment

levels (in conjunction with previous findings) suggest that this subgroup of the

schizophrenia patients may be dissimilar with regard to cognitive abilities.

Findings also showed that performance on Symbol Search (used to assess

Interference Control) is predictive of performance in the functional outcome areas of

interpersonal skills, cooking, resource utilization, medication management, as well as

overall functional outcome. These results are suggestive that the ability to deal with

interference or conflict from recently presented information that was once relevant, but

is now irrelevant, could be necessary to maintain independence in the abovementioned

areas and that these specific areas may also be important to the overall functional

outcome of this particular subgroup of individuals with schizophrenia. This could be


due to the possibility that poorer interference control abilities may limit the capacity of

individuals with schizophrenia to filter out previously attained information (that is no

longer relevant to the situation at hand) and adapt to new situations. It has been

considered that interference control abilities help to clear inappropriate information to

the task at hand from retrospective memory storage (West, 1996). It is possible that the

abovementioned sub-domains of functional outcome (as opposed to the sub-domains of

personal management, clothing, basic skills, home maintenance, money management,

and general occupational skills) may be more related to interference control deficits in

this particular schizophrenia sample. One could assume that such independent living

skills are not entirely guided by routine, but instead may involve modified action

sequences depending on the individual’s day-to-day circumstances (i.e., presenting the

individual with new information or demands). For example, this could occur when an

individual receives a phone call in the middle of following a recipe. Whereas the other

sub-domains not predicted by interference control abilities could either possibly

subscribe to more basic cognitive skill functions or even those cognitive abilities that

were not assessed for in the current study. It is also considered that proactive

interference is a major contributing factor to memory failure and in an attempt to

resolve the effects of interference from prior learning or encoding, individuals will

typically slow down and employ some type of cognitive control strategy (Persson &

Reuter-Lorenz, 2008). For example, this may involve either efforts to make a mental

note of where the individual left off before the interference/distraction, or even using a

compensatory approach such as marking the recipe at the interrupted step. Gaining a

better understanding of the nature of the neurocognitive domains which may serve to

significantly contribute to performance in specific functional outcome areas has the


potential to more effectively guide cognitive rehabilitation efforts and ultimately

increase their effectiveness and success.

Interestingly, the predictors identified as being significantly related to outcome

in the current study are in fact the variables that are not specific to executive functions

alone. While Symbol Search involves a measurement of interference control, it is also a

measure of processing speed. In this test, the participant is required to match a symbol

to an identical target that is displayed among several distractor stimuli that share similar

physical features. Interference control is assessed through the selection of correct

matches identified from the variety of distractors and speed is assessed by the number of

correct items the participant completes within the time limit. Definitions of interference

control commonly involve reference to the selection of relevant information and the

ignoring of irrelevant information (Dempster, 1993; Harnishfeger, 1995; Nigg, 2000). In

a study examining the relationship between inhibition and interference control, the

authors assessed ‘resistance to distractor interference’ with tasks in which participants

were required to select targets that were presented with irrelevant distracters (Friedman

& Miyake, 2004). For example, the authors utilised the Eriksen flanker task (Eriksen &

Eriksen, 1974) to measure this construct in which participants were required to identify

a target letter that was presented either alone or with response-incompatible letters

beside it, as quickly as possible without sacrificing accuracy. It is considered that

‘resistance to distractor interference’ is being assessed when distracting information is

presented simultaneously with the target information and is irrelevant to the response

required (Friedman et al., 2004). It would be reasonable to assume that the approach in

which to quantify interference control abilities would inevitably involve not only

determining one’s ability to control interference/distraction (i.e., by calculation of

accuracy via a number of errors score), but also the efficiency of one’s ability to control


interference/distraction (i.e., by calculation of the speed in which one can complete the

task). Therefore, the examination of one’s performance on such measures in the context

of both accuracy and speed seems fitting to determine an individual’s success on these

tasks. As the current findings also indicate that Trail Making Test performance (which

was also used as measure of Interference Control) did not significantly predict

functional outcome, this may suggest that interference from distraction could be more

directly related to the functional outcome domains of interpersonal skills, cooking,

resource utilization, medication management, as well as overall functional outcome,

compared to abilities that involve more of an active suppression process.

In addition, it is acknowledged that while there are some functional outcome

domains assessed by the Independent Living Skills Inventory that apply more to a

patient population, the current study required an inventory that was considered a valid

instrument to utilise in the assessment of this specific clinical population. As mentioned

previously the purpose of the regression analyses was to identify whether there is

potential for improvements to specific cognitive abilities which in turn may affect

associated functional outcome. Without a comprehensive assessment of a number of

functional outcome domains, the clinical relevance of potentially targeting the specific

functional outcome domains deemed to be involved in patient independent living skills

would be lost.

These results are not only in line with previous research suggesting a significant

relationship between executive functioning and functional outcome, but also extend

previous findings by being able to identify which specific aspects of executive function

(according to a theoretical model of executive function) significantly predict particular

sub-domains of functional outcome. By using a range of measures to assess the different

theoretical components of executive function and identifying which of these have better


predictive ability in relation to ‘real world’ functional outcome, we were able to more

comprehensively evaluate this relationship as well as potentially increase the ability to

detect differences between groups on this multi-faceted and complex neurocognitive

domain.

The results demonstrating moderation effects indicate that the abovementioned

measures in particular also have greater predictive power for schizophrenia patients

with cannabis use than they have for healthy matched-controls with a similar cannabis

use history. One explanation for this finding could be related to previous research

suggesting that cannabis may have differential effects on individuals with

schizophrenia, in comparison to healthy individuals (Jockers-Schrübl et al., 2007). Due

to a potential higher cognitive reserve (as suggested by their cannabis use history), it

would be expected that any preservation in cognitive performance would translate to

relative preservations in functional outcome areas. Therefore, it is possible that those

with more preserved outcome (across similar functional outcome sub-domains) in this

subpopulation may possess more preserved retrospective memory and interference

control abilities. Such findings suggest that the measures assessing these specific

executive function domains could be considered as useful tools in predicting the

functional outcome of this subgroup of individuals with schizophrenia, particularly in

relation to identifying areas for improvement regarding the associated day-to-day

independent living skills.

Practical Applications of the Findings

Given the significant association between cognition and functional outcome in

schizophrenia, over-and-above the effects of positive, negative and disorganisation

symptoms (Green, 1996; Green et al., 2000), it is considered imperative that both

researchers and clinicians look to develop specific and effective strategies in order to


improve cognitive function in this clinical population. The current study demonstrates

that through comprehensive and more construct-targeted assessment approaches, it is

possible to identify appropriate strategies that are both practical and customised to the

individual’s specific deficits. The treatment of cognition in schizophrenia has been

largely influenced and inspired by the field of neurological impairment rehabilitation

(Medalia & Choi, 2009). The cognitive problems associated with the ‘dysexecutive

syndrome’ are considered to represent a major challenge to the functional adaptation

and recovery of individuals affected by such deficits and consequently, serve as crucial

rehabilitation targets (Hewitt, Evans, & Dritschel, 2006). Therefore, clinical

neurocognitively-based rehabilitation techniques, particularly those focused on the

training of executive skills, are ideally suited to address the relationship between

cognitive dysfunction and functional outcome.

The present findings have value in that the current neurocognitive assessment

methods utilised can help to possibly attribute performance in a number of functional

outcome areas, specifically to difficulties in retrospective memory and interference

control abilities in schizophrenia patients with cannabis use. The results also indicate

that this relationship mainly exists between retrospective memory and interference

control, and various functional outcome areas, in comparison to the other executive

function domains assessed. Such findings suggest that targeting these specific executive

function domains in rehabilitation efforts may not only facilitate improvements in

performance on measures assessing these particular executive function domains, but

may also translate to performance improvements in day-to-day real-world functional

outcome areas in this subgroup. This notion is supported in the literature which

proposes that cognitive enhancement in individuals with schizophrenia may not just

generalise to neurocognitive task performance, but may also be observed in an


individual’s performance across everyday activities particularly if the skills required in

such activities tap into similar neurocognitive domains (for discussion, see Medalia &

Choi, 2009).

There are a number of rehabilitation programs which have been developed in

order to remediate cognitive impairments more specific to executive function, in

schizophrenia patients. The intention of cognitive remediation approaches is to assist

individuals to develop cognitive skills which are deemed fundamental in helping to

improve their function in day-to-day activities (Medalia & Choi, 2009). Some cognitive

rehabilitation interventions have been designed to target a number of neurocognitive

domains which include those that involve executive function abilities (Bell, Bryson,

Greig, Corcoran, & Wexler, 2001; Bellack, Dickinson, Morris, & Tenhula, 2005). Other

intervention approaches are tailored in order to target more specific executive processes,

such as working memory, cognitive flexibility, and planning abilities (Wykes, Reeder,

Landau, Everitt, Knapp, Patel, & Romeo 2007), and problem-solving abilities (Medalia,

Revheim, & Casey, 2002). A well-validated intervention aimed at the rehabilitation of

those executive function abilities involved in the self-regulation of behaviour is Goal

Management Training (GMT) (Levine, Robertson, Clare, Carter, Hong, Wilson et al.,

2000; Levine, Stuss, Winocur, Binns, Fahy, Mandic et al., 2007; Robertson, 1996;

Robertson, Levine, & Manly, 2005). GMT is a theoretically derived cognitive training

protocol based on Duncan’s theory of ‘goal neglect’ (Duncan, 1986; Duncan, Emslie,

Williams, Johnson, & Freer 1996), which describes deficits in strategic self-regulation

associated with the dysexecutive syndrome. The approach is a standardised, interactive

manual-based cognitive rehabilitation program that aims at improving an individual’s

attentional and organisation skills in order to improve the ability to achieve goal-

directed plans. The program provides a specific focus on goal-directed behaviours found


in everyday contexts. GMT procedures encompass training 5 steps, with each

emphasizing and corresponding to an important aspect of goal-directed behaviour. The

strategy involves training individuals as a first step to ‘stop and think’ by taking pauses

during the task at hand and direct their awareness to pertinent goals. Once relevant goals

are selected at step two, the individual is then required to subdivide the goal into smaller

and more manageable subgoals at step three. The fourth step trains the individual to

encode and maintain the goal, and more simple subgoals, in memory. At step five, the

outcome is then compared with and checked against the intended goal. This approach is

repeated in the event that the action outcome is mismatched with the original goal.

GMT is considered to be a top-down approach that aims to train processes across

several neurocognitive domains and incorporate different aspects involved in the stages

of goal management such as attention and task orientation, goal definition, problem-

solving, encoding, retention and retrieval strategies, and monitoring (Levine et al., 2000,

2007; Levaux, Larøi, Malmedier, Offerlin-Meyer, Danion, & Van der Linden, 2012).

Such an approach aims to promote generalisation where different behaviours or

activities that may not specifically be targeted in the actual GMT intervention may be

also subject to improvements, or the skills trained can be applied to various other

contexts that require the formulation of goal-directed plans (Levaux et al., 2012).

Levaux and colleagues (2012), sought to apply this method to a patient with

schizophrenia suffering from executive deficits in a case study. In their research they

applied the GMT strategies across three steps: (1) psychoeducation and learning GM

steps; (2) training GM principles on pencil-and-paper tasks; and (3) training in practical,

real-life situations. Results of the study showed improvements in planning and

dominant verbal response inhibition, as well as increased care and attention to tasks

(with the patient taking more contextual information into account). Progress was found


to be maintained 2 years later and continued to evolve, and generalisation of the effect

of GMT was observed on both non-trained laboratory and non-trained everyday tasks. A

significant increase in the patient’s self-esteem score was also found. Overall, the results

of the case study suggest that GMT is a promising technique for the rehabilitation of

everyday executive difficulties in people with schizophrenia. However, it was important

to note that there was no change in impaired flexibility, response inhibition and

attentional functions following the GMT intervention. In addition, working memory and

language flexibility remain preserved, and non-verbal process speed remained slowed.

Beneficial effects on a number of executive function deficits have been

demonstrated in patients with traumatic brain injury and older adults (Levine et al.,

2000, 2007; van Hooren, Valentijn, Bosma, Ponds, Van Boxtel, Levine et al., 2007), as

well as potentially for schizophrenia patients (Levaux et al., 2012), as a result of GMT

interventions. However, the approach has rarely been utilised in the context of substance

abuse. Alfonso and colleagues (2011), developed a program which not only included

methods derived from the GMT protocol, but in addition also incorporated aspects of

mindfulness-based meditation. Mindfulness-based meditation was considered to serve

as an effective compliment to traditional GMT training methods in order to improve

attention scanning and ‘reading’ of emotional signals involved in adaptive decision-

making. Mindfulness-based mediation practices promote paying attention to the present

moment, in a purposeful, non-judgemental, and emotionally aware manner (Kabat-Zinn,

Massion, Kristeller, Peterson, Fletcher, Pbert, Lenderking, & Santorelli, 1992; Segal,

Williams, & Teasdale, 2002). The use of mindfulness techniques has been considered a

promising approach for the treatment of problematic substance-use related behaviours

and supporting relapse prevention efforts (Bowen, Chawla, Collins, Witkiewitz, Hsu,

Grow et al., 2009; Bowen & Marlatt, 2009; Witkiewitz, Bowen, Douglas, & Hsu, 2013).


Results of the study showed that the GMT and mindfulness meditation program

significantly improved performance on working memory, selective attention/response

inhibition and decision-making. The authors concluded from the findings of the study

that improving competence in executive abilities may have the capacity to improve the

clinical prognosis of substance abusers. However, it is important to note that there were

no significant improvements in the neurocognitive domains of planning and flexibility

following the GMT and mindfulness meditation program. It was considered by the

authors that a possible explanation for this may perhaps involve the presence of

impairments in other more basic, underlying skills. Shallice, Burgess and Robertson

(1996) consider that an important process that serves to assist in appropriate strategy

generation and planning is episodic memory retrieval. In other words, retrospective

episodic memory processes. It is plausible that the recollection of previous similar

experiences would be beneficial when attempting to formulate solutions to unfamiliar

situations. It has been reported that retrieving more specific memories when devising

strategies to low frequency activities (i.e., unfamiliar situations), is associated with more

effective solutions as well as solutions containing more relevant steps (Dritschel et al.,

1998). This suggests that the recollection of previous similar experiences can be

beneficial for planning and problem-solving contexts. Einstein and McDonald (1990)

propose that the aspect of an activity that involves retrospective memory relates to one’s

ability to maintain information regarding action and context. Burgess and Shallice

(1997) also consider the view that the earlier stages of intention creation are not only

facilitated by executive control systems, but that such systems mediate the development

of intentions which involve complex retrieval. These findings are once again, consistent

with the view that retrospective memory processes play an important role in strategy

generation and planning future intentions.


The current study is believed to be an important first step in evaluating the

applications of more comprehensive neuropsychological assessment which has been

guided by a theoretical model of executive function (West, 1996). Considering the

potential practical applications of the current findings, further research is required in

order to demonstrate whether rehabilitation methods aimed at training specific executive

function deficits can improve performance in more practical, everyday situations. It has

been consistently found that cognitive remediation efforts aimed at specific cognitive

abilities is an effective approach for cognitive enhancement (Green & Harvey, 2014).

However, it is considered that such improvements may not necessarily translate to

functional change. With the view to improve the functional outcomes of individuals

with the illness, it is considered that the treatment of cognitive dysfunction as a sole

approach may fall short in its effectiveness (Harvey, 2007). To enable a more effective

translation of cognitive improvements into successful functional change, it is proposed

that other forms of intensive support or assistance may be required which target those

factors outside the illness that appear to also influence outcomes (e.g., demographics

and psychosocial variables) (Harvey, 2007). Bell and colleagues (2008) conducted a

study evaluating the effects of Neurocognitive Enhancement Therapy (NET) in

conjunction with a supported employment program (VOC) on the enhancement of

functional outcomes in patients with schizophrenia and schizoaffective disorder. The

NET+VOC program consisted of computer-based cognitive training, work feedback and

a social information information-processing group. Findings from the study suggested

that the combination of cognitive retraining methods with additional skills training in

other areas has the capacity to promote more beneficial functional gains. In a recent

study conducted by Bowie, McGurk, Mausbach, Patterson, and Harvey (2012),

individuals with schizophrenia living in community settings were randomly assigned to


either a cognitive remediation, functional skills training, or combined treatment group.

It was reported that those patients who either received cognitive remediation, or the

combined treatment, showed improved neurocognitive test performance from baseline

to end of treatment. At a 12-week durability assessment, these effects were observed to

be maintained. However, improvements in neurocognitive performance were not

observed following the functional skills training alone intervention. Those individuals

who either received functional skills training, or the combined treatment, demonstrated

improved social competence (as measured by the Social Skills Performance

Assessment) from baseline to end of treatment. In addition, patients who either received

functional skills training, or the combined treatment, showed improvements in

functional competence (as measured by a computed composite score from three

measures of everyday functional skills) from baseline to end of treatment. However, the

functional competence improvements demonstrated following functional skills training

were no longer significant at the 12-week durability assessment when compared to

baseline. It was noted that greater and more durable functional competence

improvements were demonstrated in those patients who were assigned to the combined

treatment group. Improvements in real-world community activities (as measured by the

Specific Levels of Functioning Scale; Schneider & Struening, 1983) were found to be

greater in patients who received the combined treatment, compared to the functional

skills training group. Patients who were assigned to the either the functional skills

training group, or the combined treatment group, showed improvements in real-world

occupational skills (also measured by the Specific Levels of Functioning Scale) at

baseline to end of treatment and these effects were maintained at the durability

assessment. However, the treatment effects in the combined treatment group were found

to be significantly larger than the functional skills group and the cognitive remediation


group. Overall findings from the study suggest that cognitive enhancement strategies in

isolation do not result in functional improvements in real-world behaviour. The authors

concluded that the transfer of cognitive improvements to everyday functioning is more

likely to occur in the context of receiving supplementary functional skills training in

addition to cognitive remediation intervention. While previous findings have indicated

that the use of cognitive remediation strategies as a standalone treatment may be

insufficient in translating to improvements in functional behaviour, it is considered that

an ideal approach may involve treating professionals placing additional focus on the

most appropriate avenues in supporting the efforts of schizophrenia patients and for

empirical studies to aim to identify which of these support methods are most effective

(Harvey, 2007).

In order for cognitive rehabilitation efforts to be optimal in their effectiveness,

there is also a need to better profile the patient samples of interest and the precise nature

of the deficits needing to be addressed. Identifying different intervention factors that

might serve to maximise the effectiveness of cognitive remediation efforts is also an

area that has the potential to optimise the efficacy of future intervention efforts (e.g.,

different instructional techniques, learning and presentation formats, and materials

used). There is also a need for the continued development of appropriate outcome

measures to ensure that interventions translate into meaningful changes in real-world

functioning. Further, future research should also not only aim to determine whether

training in executive processes can be effectively translated into benefits in daily life,

but to assess whether these benefits are maintained over time.

Finally, as only a little more than half of the variance of a number of functional

outcome areas were explained by performance on Digits Span or Symbol Search in the

current research, this suggests that other variables which were not examined in this


study could also have a significant impact on functional outcome. Therefore, our results

should be regarded as preliminary in nature. In addition, such results suggest that if only

certain aspects of executive function are significantly related to various areas in the

functional outcomes of schizophrenia patients with cannabis use, then other

neurocognitive domains may serve to also be targeted or emphasized in a strength-based

approach to cognitive training efforts. In other words, effective cognitive rehabilitation

protocols involving this particular clinical population should not only involve cognitive

training in identified deficits areas, but should also focus on making use of their intact

neurocognitive abilities. The current findings have clinical importance in that they

support the concept of developing interventions to treat neuropsychological deficits that

may contribute to the more successful functional outcomes of such patients.

Limitations and Future Directions

The results reported in the present research need to be assessed and interpreted

within the context of its limitations. Firstly, findings of the study should be considered

to be exploratory in nature considering the small sample sizes. However, unlike some of

the previous studies, the current research sought to collect more detailed information

about potential confounding variables which have been found to have a relationship

with cognitive impairment. These factors include cannabis use parameters such as

frequency, severity/quantity, duration and time since cannabis use cessation (i.e.,

recency). Also, individuals with other neuropsychiatric or neuromedical illnesses were

excluded from the study. Since the recruitment of participants also involved recruiting

suitable matched-pairs (based on a strict matching criteria on a range of variables in

order to restrict the possible impact of these potential confounds), the end result of

smaller sample sizes was difficult to avoid but arguably, offset by the reduction in


extraneous variation in the sample. Prospective studies with larger sample sizes that

maintain this strict matching process will help to extend the current findings.

Another potential limitation in the current study involves combining both former

users and current users in the primary ANCOVA analyses (due to small sub-sample

sizes). However, as previously mentioned a carefully matched-controls design was used

in an attempt to control for any confounding influence contributed to by variations in

crucial cannabis-use indices (which have been considered to have an impact on

cognitive performance) across individuals. Future studies could look to further examine

the separate cannabis status groups across the executive function measures of interest.

However, it is acknowledged that there would be difficulty in doing so reliably given

that the time since cessation variable is largely self-report in nature. In addition, it is

important to note the impact of small sample sizes on the validity of specific statistical

approaches such as PCA and multiple regression analyses. However, the sample size was

deemed sufficient for exploratory PCA. While findings from some of the multiple

regression analyses failed to reach statistical significance, it is still considered important

to particularly consider the effect sizes of all correlational analyses as indicated by the

shared variance statistic. It is acknowledged that as p values are heavily influenced by

small sample sizes and also do not provide an indication of the size or importance of the

observed effect, future studies with larger samples may inevitably produce additional

statistically significant results. As the shared variances found in the current study are

notably similar to Green et al.’s (2000) meta-analytic findings regarding the range of

detected effect sizes for the relationship between cognition and everyday outcomes in

schizophrenia patients, the results of the present research are in support of previous findings.

Therefore, future research with larger samples is also warranted for further evaluation of

similar effect sizes. The small samples size of the current study also inevitably reduces


the statistical power of being able to detect what could possibly have been significant

relationships. However, as mentioned the results of the present research are not all that

dissimilar from previous findings.

While the Holm-Bonferroni correction method is not considered as conservative

in controlling for family-wise Type I error as the Bonferroni approach, as with all

corrections the likelihood of Type II error is also increased. Therefore, truly important

clinical differences may be deemed non-significant following correction. It is

considered that the non-significant results emerging from the current study following

Holm-Bonferroni adjustment are plausibly a consequence of the small sample size and

reduced power, instead of reflective of the fact that none of these relationships

exist. Given the similar effect sizes reported in previous research related to the amount

of variance contributed to functional outcome by cognitive variables in the

schizophrenia population (and thus, raising question against the likelihood that the null

hypothesis is actually true), it is thought that it is entirely plausible for such

relationships to not only exist, but also have statistical significance. Therefore, those

results which had reached significance prior to Holm-Bonferroni correction have still

been interpreted in the current study, with the precaution that at least some of these

results may be truly reflective of Type I error. It is also considered that due to the small

sample size, once again it is recommended that effect sizes be taken into account not

just the overall significance level. Prospective studies should look to conduct similar

comparisons with larger samples sizes in order to detect results of larger statistical

significance and robustness.

It is also acknowledged that as the current study included matched-control subjects

with cannabis use as a comparison sample, it is difficult to differentiate between exceptional

performance and cannabis use associated impairment. In other words, the minimal impairment


shown in the present study could indeed be a reflection of schizophrenia patients with cannabis

use being more likely to be cognitively intact. However, it may also be that the matched-

control sample could be in some way cognitively impaired due to their cannabis use and that

the patient sample was exceptional in their performance. In addition, it is possible that the

cognitive signal for long-term cannabis use is relatively small in comparison to the signal for

schizophrenia such that additional increments are difficult to detect. The latter would not be

implausible as the cognitive deficits associated with chronic or heavy cannabis use are similar

to those seem in schizophrenia, which could serve to narrow the gap between controls and

patients. Although the similarities referred to here are related to deficits, the current

study’s results indicate a significantly larger proportion of schizophrenia patients with

cannabis use demonstrating performances in the clinically non-impaired range. While the

current study did not aim to examine the cumulative effects of schizophrenia and cannabis use,

future studies adopting a similar matched-control design, as well as including the addition of a

cannabis-naive schizophrenia patient sample would help to further elucidate these

relationships.

While it is acknowledged above that the current study did not have a cannabis

naive schizophrenia group or a cannabis-naive healthy control group for comparison,

this is the first study to directly compare between schizophrenic and non-schizophrenic

samples with carefully matched cannabis use histories. We also categorised our subjects

according to their current cannabis use status (i.e., currently using schizophrenia

patients with cannabis use, non-currently using schizophrenia patients with cannabis

use, currently using healthy controls with a similar cannabis use history and non-

currently using healthy controls with a similar cannabis use history) in subsequent

analyses. Rabin and colleagues (2013), also parsed their participants in terms of current

cannabis use status, but in addition included a group of patients containing 8 subjects


with minimal/no lifetime use. The current study also recruited a similar group, but

instead found individuals with no reported historical use at all (i.e., not even to a

minimal extent). The general pattern of recruited schizophrenia subjects in the present

research included either those patients who reported regular current or former use, or no

lifetime use at all. However, only 4 cannabis-naive individuals with schizophrenia were

recruited over a period of well over a 24-month timeframe. The small sample size of

this similar type of subgroup in Rabin and colleagues’ study may be reflective of related

difficulties faced when recruiting from this population. It is not entirely clear why such

limited numbers in this particular subgroup sample were achieved. One possible

explanation is that similarly to Rabin and colleagues’ (2013) study, recruitment was

community-based with only outpatients being included in these studies. It is reasonable

to consider that the cohort of individuals who are cannabis-naive may have much

smaller numbers in the community due to differing illness presentation, than there are in

the inpatient settings. The current study did not attempt to recruit individuals with

schizophrenia from an inpatient setting in order to reduce the likelihood of the acute

effects of the illness influencing results. The premise suggesting that schizophrenia

patients with cannabis use have better premorbid adjustment, social skills and

prognosis, supports this possibility. Future studies including all possible comparison

groups (i.e., patients with cannabis use (both current and former users), cannabis-naive

patients, healthy matched-controls with a similar cannabis use history (both current and

former users), and cannabis-naive healthy normals), will not only allow for more

informative between-subject comparisons, but will overall increase the generalisability

of findings. In addition, prospective investigations ascertaining the population

dispersion in both inpatient and outpatient settings in relation to patients with cannabis

use versus patients with no reported historical use, may help to provide a better


understanding of the overall schizophrenia population characteristics, but may also

serve to either additionally confirm or disconfirm the hypothesis related to better

premorbid adjustment in the cohort with cannabis use. Due to the cognitive

heterogeneity associated with this particular disorder (Joyce & Roiser, 2007), future

research should also look to adopt longitudinal designs that use within-subjects

approaches to statistical analyses so that not just cannabis use status, but the cumulative

effects of cannabis use over time, can be further examined within each of these groups.

A common limitation across many of the studies, including this one, when

investigating the relationship between cannabis use and neurocognitive performance

involves the ability to adequately measure the variability regarding different

concentrations of Delta-9-tetrahydrocannabinol (∆9-THC). Over the years the ∆

9-THC

content in cannabis has been seen to progressively increase with the average level of ∆9-

THC content from the 1960’s to 1980’s reported to approximate 1.5-3.5%, with

modern efforts to enhance its potency resulting in concentrations reaching up to 20%

(for discussion, see Adams & Martin, 1996). In addition to this, through more frequent

and deeper inhalation techniques experienced cannabis users are able to modify the dose

if desired, thus further altering concentration levels (Iversen, 2000). This issue poses

challenges regarding the range of variability in ∆9-THC concentration across users and

the difficulty in controlling for this factor in empirical research. However, by

controlling for differences in frequency, severity/quantity, duration of use and length of

abstinence through the matching process in the current study, the present research aimed

to address at least those measurable cannabis-use parameters which are associated with

variability in cannabis use. The objective measurement of ∆9-THC concentration in

future studies would help to address this issue and allow for more control when

considering the variations in cannabis use as a potential confound.


In the current study, we also did not directly examine the effects of frequency of

use and severity/quantity on neurocognitive performance. However, as mentioned

above, the present research did allow for the assessment of these parameters and

attempted to control for any possible differences via the matched-pairs design. While

the importance of taking into account the possible effects of these particular parameters

in cannabis use research is acknowledged, previous research has suggested that duration

of use may place more of a significant contribution to the development of

neurocognitive impairment when compared to the cannabis use parameters of frequency

of use or quantity (Solowij et al., 2002). Future investigations should look to closely

examine the possible effects of frequency, severity/quantity, duration of use, and time

since last use across all of the abovementioned relevant comparison groups in order to

determine whether these parameters have differential effects depending on group

membership.

As the current study only required the minimum of a 24-hour period of cannabis

use abstinence, it is possible that for the individuals that were current users their results

only represent the early stages of neurocognitive recovery, or quite possibly the

remaining effects from intoxication. However, following ∆9-THC inhalation peak

plasma concentrations and the associated psychotropic effects are thought to reach their

maximum level within 15-30 minutes and that the intoxication effects of the drug begin

to diminish within 2-3 hours (Grotenhermen, 2003). Previous studies have also adopted

a 24-hour abstinence period in an attempt capture the narrow window which occurs

between intoxication and drug withdrawal (Coulston et al., 2007; DeRosse et al., 2010).

In a study conducted by Budney and colleagues (2003) the withdrawal symptoms and

patterns following cannabis use abstinence were examined. Findings showed that the

onset of withdrawal symptoms usually occurred during the first day following cannabis


use cessation and that the peak of withdrawal symptom effects occurred between 2 and

6 days. It was also found that most effects lasted between 4 and 14 days. However, the

current study did aim to investigate effects associated with different lifetime use

categories (i.e., across current users and abstinent users) and therefore a much longer

period of abstinence prior to testing would have inevitably ruled out the ability to

compare performance with ‘current’ users.

Another limitation of the current study is that the history of drug consumption

was assessed using the self-report of subjects. Given the variability in cannabis use

across individuals, it would be difficult to precisely calculate an individual’s history and

pattern of substance use across their lifetime. Adherence to the 24-hour abstinence

period was also assessed using self-report. However, it has been reported that

information given by subjects about their drug use tends to be relatively reliable

(Brown, Kranzler, & Del Boca, 1992; Harrison, Haaga, & Richards, 1993; Pope et al.,

2001). Self-reports of substance use have also been found to correspond with urine

screen results (Fowler, Carr, Carter, & Lewin, 1998; Pope et al., 2001). In addition, the

quantification of various cannabis use parameters was also based on self-report. While it

has been identified that self-reporting bias is a potential limitation of the current study,

reporting the different aspects of their use is the best proxy that was available (for

example, reporting time since cessation in comparison to actual measurement of this

variable via longitudinal design). It is also acknowledged that the determination of the

validity and reliability of self-report measures of drug use in people with schizophrenia

is currently lacking. This may be particularly problematic given their difficulties with

memory and other cognitive abilities. Future studies aiming to replicate the current

study’s findings should consider the utilisation of drug-usage screening processes in


order to supplement the information provided in user self-reports and help to provide an

overall more accurate picture of actual use.

Conclusions

The main aims of the present study were to examine the patterns of executive

functioning of schizophrenia patients with cannabis use in comparison to otherwise

healthy matched-controls with a similar cannabis use history. An examination of these

complex neurocognitive profiles has clinical significance due to the reported

relationship between executive function and the functional outcome of individuals with

the illness. An additional aim was to also investigate the relationship between level of

executive functioning and ‘real world’ functional outcome. The identification of

specific functional outcome predictors is also considered a research area with important

clinical applications due to its potential in not only being able to more effectively guide

rehabilitation plans, but ultimately increasing their efficacy by offering specific

information regarding possible practical rehabilitation modifications. For example, in

order to better assist and support individuals with retrospective memory deficits,

strategies aimed at improving hygiene and grooming skills may not only involve more

structured approaches, but that these approaches could be chunked into smaller parts in

order to reduce the number of cognitive and behavioural units held online and

ultimately facilitate the more effective recall and implementation of these learned

strategies. In addition, for those with difficulties in interference control, strategies aimed

at improving interpersonal, cooking, resource utilisation and medication management

skills could involve once again more structured approaches, but also include the

repeated practice and rehearsal of scenarios where there are changing or interfering

circumstances, or even with distractors present. Such rehearsal could help to enhance

more fluency in behavioural adaptation to differing/interfering environmental demands


and possibly reduce the tendency for responses to be based on task-inappropriate

habitual behavioural patterns.

The strengths of the current study lie in the comprehensive assessment of a

multi-faceted neurocognitive construct thought to be related to functional outcome.

While the results are encouraging, this study also highlights the difficulties and

complexities associated in adequately assessing executive function. This is the first

study to use this type of assessment methodology in a clinical population such as

schizophrenia. The present findings also reinforce the importance of considering

executive function as a complex cognitive construct that is not always adequately

tapped into via the use of traditional executive functioning measures and this may help

to explain the previous mixed findings. Despite the noted limitations in the present

study, the comprehensive assessment of executive function has afforded an extension to

the existing knowledge about the neurocognitive profiles of schizophrenia patients with

cannabis use. This study also builds upon previous research by examining the relative

contribution of different components of executive function in explaining performance in

functional outcome. Specifically, the findings of this study suggest that schizophrenia

patients with cannabis use reported to demonstrate inadequate functional outcome in the

particular areas of hygiene and grooming, interpersonal skills, cooking, resource

utilization, and medication management, as well as overall functional outcome related

to independent living skills, may be partially due to less intact or poorer retrospective

memory and interference control abilities.

The neurocognitive measures used in the current study represented a theoretical

hierarchical model of the construct of executive function, allowing us to tap into a wide

range of executive processes. However, what remains unclear is which particular facets

of executive function contribute to the most crucial areas of functional outcome. Given


this identified gap, future research is needed in order to determine which aspects of

functional outcome are the most important to successful independent living.

While further research is required to replicate the study’s findings, the current

work suggests that neuropsychological evidence can be instrumental in identifying

specific neurocognitive domains and their likely functional outcome correlates. The

results of the present study and the applications of its findings, also suggest that

tailoring rehabilitation plans utilising neurocognitive information specific to particular

clinical subgroups has the potential to improve the functional outcomes of patients.

Prospective studies should endeavour to build upon such approaches and while the

future of research in the area may present its associated challenges, it also has the

potential to offer considerable promise. ‘Schizophrenia in the past was a grim diagnosis

with a poor prognosis. At the present time, it can probably be better described as a

serious condition, with plenty of reasons to be hopeful’ (Green & Harvey, 2014, p. 7).

The methodological approach of the current study is considered a first step in the

development of neurocognitive process-specific training protocols for this particular

subgroup of the schizophrenia population.


References

Acker, M. B. (1990). A review of the ecological validity of neuropsychological tests. In

D. E. Tupper & K. D. Cicerone (Eds.), The Neuropsychology of Everyday Life:

Assessment and Basic Competencies (Vol. 2, pp. 19–55). Boston, MA: Kluwer

Academic Publishers.

Adams, I. B., & Martin, B. R. (1996). Cannabis: pharmacology and toxicology in

animals and humans. Addiction, 91(11), 1585–1614. doi: 10.1046/j.1360-

0443.1996.911115852.x

Addington, J., & Duchak, V. (1997). Reasons for substance use in schizophrenia. Acta

Psychiatrica Scandinavica, 96(5), 329–333. doi:10.1111/j.1600-

0447.1997.tb09925.x

Allen, H. A., Liddle, P. F., & Frith, C. D. (1993). Negative features, retrieval processes

and verbal fluency in schizophrenia. The British Journal of Psychiatry, 163(6),

769–775. doi:10.1192/bjp.163.6.769

Alfonso, J. P., Caracuel, A., Delgado-Pastor, L. C., & Verdejo-García, A. (2011).

Combined goal management training and mindfulness meditation improve

executive functions and decision-making performance in abstinent

polysubstance abusers. Drug and Alcohol Dependence, 117(1), 78–81.

doi:10.1016/j.drugalcdep.2010.12.025

Alvarez, J. A., & Emory, E. (2006). Executive function and the frontal lobes: A meta-

analytic review. Neuropsychology Review, 16(1), 17–42. doi:10.1007/s11065-

006-9002-x

Andres, E. (2003). Drug-induced hepatotoxicity. New England Journal of Medicine,

349(20), 1974–1976. doi:10.1056/NEJM200311133492021


American Psychiatric Association (1994). Diagnostic and Statistical Manual of Mental

Disorders (Fourth Edition). Washington, D.C.: American Psychiatric

Association.

Arndt, S., Tyrrell, G., Flaum, M., & Andreasen, N. C. (1992). Comorbidity of substance

abuse and schizophrenia: the role of pre-morbid adjustment. Psychological

Medicine, 22(2), 379–388. doi:10.1017/S0033291700030324

Arseneault, L., Cannon, M., Poulton, R., Murray, R., Caspi, A., & Moffitt, T. E. (2002).

Cannabis use in adolescence and risk for adult psychosis: longitudinal

prospective study. British Medical Journal, 325(7374), 1212–1213.

doi:10.1136/bmj.325.7374.1212

Arseneault, L., Cannon, M., Witton, J., & Murray, R. M. (2004). Causal association

between cannabis and psychosis: Examination of the evidence. The British

Journal of Psychiatry, 184(2), 110–117. doi:10.1192/bjp.184.2.110

Auslander, L. A., Lindamer, L. L., Delapena, J., Harless, K., Polichar, D., Patterson, T.

L., ... Jeste, D. V. (2001). A comparison of community‐dwelling older

schizophrenia patients by residential status. Acta Psychiatrica Scandinavica,

103(5), 380–386. doi:10.1034/j.1600-0447.2001.00262.x

Baddeley, A. (1996). Exploring the central executive. The Quarterly Journal of

Experimental Psychology: Section A, 49(1), 5–28. doi:10.1080/713755608

Baddeley, A. (1998). The central executive: A concept and some misconceptions.

Journal of the International Neuropsychological Society, 4(5), 523–526.

doi:10.1017/s135561779800513x

Baddeley, A. D., Della Sala, S., Papagno, C., & Spinnler, H. (1997). Dual-task

performance in dysexecutive and non-dysexecutive patients with a frontal lesion.

Neuropsychology, 11(2), 187–194. doi:10.1037/0894-4105.11.2.187

http://dx.doi.org/10.1017/S0033291700030324

http://psycnet.apa.org/doi/10.1037/0894-4105.11.2.187


Baddeley, A., Della Sala, S., Robbins, T. W., & Baddeley, A. (1996). Working memory

and executive control [and discussion]. Philosophical Transactions of the Royal

Society of London, Series B: Biological Sciences, 351(1346), 1397–1404.

doi:10.1098/rstb.1996.0123

Baldo, J. V., Shimamura, A. P., Delis, D. C., Kramer, J., & Kaplan, E. (2001). Verbal

and design fluency in patients with frontal lobe lesions. Journal of the

International Neuropsychological Society, 7(5), 586–596. Retrieved from

http://www.ebire.org/aphasia/baldo/verbal_design.PDF

Barnes, T. R. E., Mutsatsa, S. H., Hutton, S. B., Watt, H. C., & Joyce, E. M. (2006).

Comorbid substance use and age at onset of schizophrenia. The British Journal

of Psychiatry, 188(3), 237–242. doi:10.1192/bjp.bp.104.007237

Barnett, J. H., Salmond, C. H., Jones, P. B., & Sahakian, B. J. (2006). Cognitive reserve

in neuropsychiatry. Psychological Medicine, 36(8), 1053–1064.

doi:10.1017/S0033291706007501

Bartels, S. J., Teague, G. B., Drake, R. E., Clark, R. E., Bush, P. W., & Noordsy, D. L.

(1993). Substance abuse in schizophrenia: Service utilization and costs. Journal

of Nervous Mental Disease, 181(4), 227–232. doi:10.1097/00005053-

199304000-00003

Battisti, R. A., Roodenrys, S., Johnstone, S. J., Respondek, C., Hermens, D. F., &

Solowij, N. (2010). Chronic use of cannabis and poor neural efficiency in verbal

memory ability. Psychopharmacology, 209(4), 319–330. doi: 10.1007/s00213-

010-1800-4

Beatty, W. W., Jocic, Z., Monson, N., & Katzung, V. M. (1994). Problem solving by

schizophrenic and schizoaffective patients on the Wisconsin and California Card

Sorting Tests. Neuropsychology, 8(1), 49–54. doi:10.1037/0894-4105.8.1.49

http://dx.doi.org/10.1017/S0033291706007501

http://dx.doi.org/10.1007/s00213-010-1800-4

http://dx.doi.org/10.1007/s00213-010-1800-4



Beatty, W. W., Katzung, V. M., Moreland, V. J., & Nixon, S. J. (1995).

Neuropsychological performance of recently abstinent alcoholics and cocaine

abusers. Drug and Alcohol Dependence, 37(3), 247–253. doi:10.1016/0376-

8716(94)01072-S

Bechara, A. (2001). Neurobiology of decision-making: risk and reward. Seminars in

Clinical Neuropsychiatry, 6(3), 205–216. doi:10.1053/scnp.2001.22927

Bechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. (1994). Insensitivity to

future consequences following damage to human prefrontal cortex. Cognition,

50(1-3), 7–15. doi:10.1016/0010-0277(94)90018-3

Bechara, D., Damasio, H., Damasio, A. R., & Lee, G. P. (1999). Different contributions

of the human amygdala and ventromedial prefrontal cortex to decision-making.

Journal of Neuroscience, 19(13), 5473–5481. Retrieved from

http://www.jneurosci.org/content/19/13/5473.full.pdf+html

Bechara, A., Damasio, H., Tranel, D., & Damasio, A. R. (1997). Deciding

advantageously before knowing the advantageous strategy. Science, 275(5304),

1293–1295. doi:10.1126/science.275.5304.1293

Bechara, A., Dolan, S., Denburg, N., Hindes, A., Anderson, S. W., & Nathan, P. E.

(2001). Decision-making deficits, linked to a dysfunctional ventromedial

prefrontal cortex, revealed in alcohol and stimulant abusers. Neuropsychologia,

39(4), 376–389. doi:10.1016/S0028-3932(00)00136-6

Bechara, A., & Martin, E. M. (2004). Impaired decision making related to working

memory deficits in individuals with substance addictions. Neuropsychology,

18(1), 152–162. doi:10.1037/0894-4105.18.1.152

http://dx.doi.org/10.1016/0376-8716(94)01072-S

http://dx.doi.org/10.1016/0376-8716(94)01072-S

http://dx.doi.org/10.1016/S0028-3932(00)00136-6



Bechara, A., Tranel, D., & Damasio, H. (2000). Characterization of the decision-making

deficit of patients with ventromedial prefrontal cortex lesions. Brain, 123(Pt 11),

2189–2202. doi:10.1093/brain/123.11.2189

Bechara, A., Tranel, D., Damasio, H., & Damasio, A. R. (1996). Failure to respond

autonomically to anticipated future outcomes following damage to prefrontal

cortex. Cerebral Cortex, 6(2), 215–225. doi:10.1093/cercor/6.2.215

Bell, M., Bryson, G., Greig, T., Corcoran, C., & Wexler, B. E. (2001). Neurocognitive

enhancement therapy with work therapy: effects on neuropsychological test

performance. Archives of General Psychiatry, 58(8), 763–768.

doi:10.1001/archpsyc.58.8.763.

Bell, M. D., Zito, W., Greig, T., & Wexler, B. E. (2008). Neurocognitive enhancement

therapy with vocational services: work outcomes at two-year follow-up.

Schizophrenia Research, 105(1), 18–29. doi:10.1016/j.schres.2008.06.026

Bellack, A. S., Dickinson, D., Morris, S. E., & Tenhula, W. N. (2005). The development

of a computer-assisted cognitive remediation program for patients with

schizophrenia. Israel Journal of Psychiatry and Related Sciences, 42(1), 5–14.

Retrieved from

http://gender.mednet.co.il/upload/infocenter/info_images/1405200621046PM@

Pages%20from%20IJP-42-1-5.pdf

Benedet, M. J., & Alejandre, M. A. (1998). Test de Aprendizaje Verbal Espan˜a-

Complutense. Madrid: TEA ediciones.

Benedict, R. H. B. (1997). Brief Visuospatial Memory Test - Revised. Odessa, Florida:

Psychological Assessment Resources.

http://dx.doi.org/10.1016/j.schres.2008.06.026

http://gender.mednet.co.il/upload/infocenter/info_images/1405200621046PM@Pages%20from%20IJP-42-1-5.pdf

http://gender.mednet.co.il/upload/infocenter/info_images/1405200621046PM@Pages%20from%20IJP-42-1-5.pdf


Bennett, P. C., Ong, B., & Ponsford, J. (2005). Assessment of executive dysfunction

following traumatic brain injury: Comparison of the BADS with other clinical

neuropsychological measures. Journal of the International Neuropsychological

Society, 11(5), 606–613. doi:10.1017/s1355617705050721

Benton, A. L. (1968). Differential behavioral effects in frontal lobe disease.

Neuropsychologia, 6(1), 53–60. doi:10.1016/0028-3932(68)90038-9

Benton, A. L., & Hamsher, K. (1976). The Multilingual Aphasia Examination. Iowa

City, IA: University of Iowa Press.

Benton, A. L., Hamsher, K., & Sivan, A. B. (1983). Multilingual Aphasia Examination

(Third Edition). Iowa City, IA: AJA Associates.

Bilder, R. M., Lipschutz-Broch, L., Reiter, G., Geisler, S. H., Mayerhoff, D. I., &

Lieberman, J. A. (1992). Intellectual deficits in first-episode schizophrenia:

evidence for progressive deterioration. Schizophrenia Bulletin, 18(3), 437–448.

doi:10.1093/schbul/18.3.437

Bleuler, E. (1911). (Translated by J. Zinkin, published in 1950). Dementia Praecox of

the Group of Schizophrenias. New York: International Universities Press.

Bolla, K. I., Brown, K., Eldreth, D., Tate, K., & Cadet, J. L. (2002). Dose-related

neurocognitive effects of marijuana use. Neurology, 59(9), 1337–1343.

doi:10.1212/01.wnl.0000031422.66442.49

Bolla, K. I., Cadet, J., &London, E. D. (1998). The neuropsychiatry of chronic cocaine

use. Journal of Neuropsychiatry and Clinical Neurosciences, 10(3), 280–289.

Bolla, K. I., Eldreth, D. A., London, E. D., Kiehl, K. A., Mouratidis, M., Contoreggi, C.,

... Ernst, M. (2003). Orbitofrontal cortex dysfunction in abstinent cocaine

abusers performing a decision-making task. Neuroimage, 19(3), 1085–1094.

doi:10.1016/S1053-8119(03)00113-7

http://dx.doi.org/10.1016/S1053-8119(03)00113-7


Bolla, K., Eldreth, D., Matochik, J., & Cadet, J. (2005). Neural substrates of faulty

decision-making in abstinent marijuana users. Neuroimage, 26(2), 480–492.

doi:10.1016/j.neuroimage.2005.02.012

Bowen, S., Chawla, N., Collins, S. E., Witkiewitz, K., Hsu, S., Grow, J., ... Marlatt,

A. (2009). Mindfulness-based relapse prevention for substance use disorders: A

pilot efficacy trial. Substance Abuse, 30(4), 295–305. doi:

10.1080/08897070903250084

Bowen, S., & Marlatt, A. (2009). Surfing the urge: brief mindfulness-based intervention

for college student smokers. Psychology of Addictive Behaviors, 23(4), 666–671.

doi:10.1037/a0017127

Bowie, C. R., McGurk, S. R., Mausbach, B., Patterson, T. L., & Harvey, P. D. (2012).

Combined cognitive remediation and functional skills training for schizophrenia:

effects on cognition, functional competence, and real-world behavior. American

Journal of Psychiatry, 169(7), 710–718. doi:10.1176/appi.ajp.2012.11091337

Braff, D. L. (1993). Information processing and attention dysfunctions in schizophrenia.

Schizophrenia Bulletin, 19(2), 233–259. doi.org/10.1093/schbul/19.2.233

Braff, D. L., Heaton, R., Kuck, J., Cullum, M., Moranville, J., Grant, I., & Zisook, S.

(1991). The generalized pattern of neuropsychological deficits in outpatients

with chronic schizophrenia with heterogeneous Wisconsin Card Sorting Test

results. Archives of General Psychiatry, 48(10), 891–898.

doi:10.1001/archpsyc.1991.01810340023003

Broadbent, D. E., Cooper, P. F., FitzGerald, P., & Parkes, K. R. (1982). The cognitive

failures questionnaire (CFQ) and its correlates. British Journal of Clinical

Psychology, 21(Pt 1), 1–16. doi:10.1111/j.2044-8260.1982.tb01421.x

http://psycnet.apa.org/doi/10.1037/a0017127


Brown, J., Kranzler, H. R., & Del Boca, F. K. (1992). Self‐reports by alcohol and drug

abuse inpatients: factors affecting reliability and validity. British Journal of

Addiction, 87(7), 1013–1024. doi:10.1111/j.1360-0443.1992.tb03118.x

Bryan, J., & Luszcz, M. A. (2000). Measurement of executive function: considerations

for detecting adult age differences. Journal of Clinical and Experimental

Neuropsychology, 22(1), 40–55. doi.org/10.1076/1380-3395(200002)22:1;1-

8;FT040

Bryan, J., & Luszcz, M. A. (2001). Adult age differences in self-ordered pointing task

performance: Contributions from working memory, executive function and

speed of information processing. Journal of Clinical and Experimental

Neuropsychology, 23(5), 608–619. doi:10.1076/jcen.23.5.608.1250

Budney, A. J., Moore, B. A., Vandrey, R. G., & Hughes, J. R. (2003). The time course

and significance of cannabis withdrawal. Journal of Abnormal Psychology,

112(3), 393–402. doi:10.1037/0021-843X.112.3.393

Buelow, M. T., & Suhr, J. A. (2009). Construct validity of the Iowa Gambling Task.

Neuropsychology Review, 19(1), 102–114. doi: 10.1007/s11065-009-9083-4

Burgess, P. W. (1997). Theory and methodology in executive function research. In P.

Rabbit (Ed.), Methodology of Frontal and Executive Function (pp. 81–116). East

Sussex, UK: Psychology Press Ltd.

Burgess, P. W. (2000). Strategy application disorder: The role of the frontal lobes in

human multitasking. Psychological Research, 63(3-4), 279–288.

doi:10.1007/s004269900006

Burgess, P. W., Alderman, N., Evans, J., Emslie, H., & Wilson, B. A. (1998). The

ecological validity of tests of executive function. Journal of the International

Neuropsychological Society, 4(6), 547–558. doi:10.1017/S1355617798466037

http://dx.doi.org/10.1076/1380-3395(200002)22:1;1-8;FT040

http://dx.doi.org/10.1076/1380-3395(200002)22:1;1-8;FT040

http://psycnet.apa.org/doi/10.1037/0021-843X.112.3.393


Burgess, P. W., Alderman, N., Wilson, B. A., Evans, J. J., & Emslie, H. (1996). The

dysexecutive questionnaire. Behavioural Assessment of the Dysexecutive

Syndrome. Bury St. Edmunds, U.K.: Thames Valley Test Company.

Burgess, P. W., Veitch, E., de Lacy Costello, A., & Shallice, T. (2000). The cognitive

and neuroanatomical correlates of multitasking. Neuropsychologia, 38(6), 848–

863. doi:10.1016/s0028-3932(99)00134-7

Cannon-Spoor, H. E., Potkin, S. G., & Wyatt, R. J. (1982). Measurement of premorbid

adjustment in chronic schizophrenia. Schizophrenia Bulletin, 8(3), 470–484.

doi:dx.doi.org/10.1093/schbul/8.3.470

Cantwell, R., Brewin, J., Glazebrook, C., Dalkin, T., Fox, R., Medley, I., & Harrison, G.

(1999). Prevalence of substance misuse in first-episode psychosis. The British

Journal of Psychiatry, 174(2), 150–153. doi:10.1192/bjp.174.2.150

Capri, S. (1994). Methods for evaluation of the direct and indirect costs of long-term

schizophrenia. Acta Psychiatrica Scandinavica, 89(S382), 80–83.

doi:10.1111/j.1600-0447.1994.tb05871.x

Caspari, D. (1999). Cannabis and schizophrenia: Results of a follow-up study.

European Archives of Psychiatry and Clinical Neuroscience, 249(1), 45–49.

doi:10.1007/s004060050064

Chaytor, N., & Schmitter-Edgecombe, M. (2003). The ecological validity of

neuropsychological tests: A review of the literature on everyday cognitive skills.

Neuropsychology Review, 13(4), 181–197.

doi:10.1023/B:NERV.0000009483.91468.fb


Chen, E. Y. H., Lam, L. C. W., Chen, R. Y. L., Nguyen, D. G. H., & Chan, C. K. Y.

(1996). Prefrontal neuropsychological impairment and illness duration in

schizophrenia: A study of 204 patients in Hong Kong. Acta Psychiatrica

Scandinavica, 93(2), 144–150. doi:10.1111/j.1600-0447.1996.tb09816.x

Chen, R. Y. L., Chen, E. Y. H., Chan, C. K. Y., Lam, L. C. W., & Lieh-Mak, F. (2000).

Verbal fluency in schizophrenia: Reduction in semantic store. Australian and

New Zealand Journal of Psychiatry, 34(1), 43–48. doi:10.1046/j.1440-

1614.2000.00647.x

Chevignard, M. P., Taillefer, C., Picq, C., Poncet, F., Noulhiane, M., & Pradat-Diehl, P.

(2008). Ecological assessment of the dysexecutive syndrome using execution of

a cooking task. Neuropsychological Rehabilitation, 18(4), 461–485.

doi:10.1080/09602010701643472

Conners, C. K. (2000). Conners’ Continuous Performance Test II: Computer Program

for Windows Technical Guide and Software Manual. North Tonawanda, NY:

Multi-Health Systems.

Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (Second

Edition). Hillsdale, NJ: Erlbaum.

Cornblatt, B. A., Risch, N. J., Faris, G., Friedman, D., & Erlenmeyer-Kimling, L.

(1988). The Continuous Performance Test, identical pairs version (CPT-IP): I.

New findings about sustained attention in normal families. Psychiatry Research,

26(2), 223–238. doi:10.1016/0165-1781(88)90076-5

Cornblatt, B., Obuchowski, M., Schnur, D., & O'Brien, J. D. (1998). Hillside study of

risk and early detection in schizophrenia. The British Journal of Psychiatry,

172(33), 26–32. Retrieved from http://0-bjp.rcpsych.org.

http://dx.doi.org/10.1016/0165-1781(88)90076-5


Coulston, C., Perdices, M., & Tennant, C. (2007). The neuropsychological correlates of

cannabis use in schizophrenia: Lifetime abuse/dependence, frequency of use,

and recency of use. Schizophrenia Research, 96(1-3), 169–184.

doi:10.1016/j.schres.2007.08.006

Crawford, J. R., Besson, J. A., Bremner, M., Ebmeier, K. P., Cochrane, R. H., &

Kirkwood, K. (1992). Estimation of premorbid intelligence in schizophrenia.

The British Journal of Psychiatry, 161(1), 69–74. doi: 10.1192/bjp.161.1.69

Crawford, J. R., Obonsawin, M. C., & Bremner, M. (1993). Frontal lobe impairment in

schizophrenia: relationship to intellectual functioning. Psychological Medicine,

23(3), 787–787. doi:10.1017/S0033291700025563

Crean, R. D., Crane, N. A., & Mason, B. J. (2011). An evidence-based review of acute

and long-term effects of cannabis use on executive cognitive functions. Journal

of Addiction Medicine, 5(1), 1–8. doi:10.1097/ADM.0b013e31820c23fa

Cripe, L. I. (1996). The ecological validity of executive function testing. In R. J.

Sbordone & C. J. Long (Eds.), Ecological Validity of Neuropsychological

Testing (pp. 171–202). Delray beach, FL: GR Press/St. Lucie Press.

Cuffel, B. J., Heithoff, K. A., & Lawson, W. (1993). Correlates of patterns of substance

abuse among patients with schizophrenia. Hospital and Community Psychiatry,

44(3), 247–251.

Daigneault, S., Braün, C. M. J., & Whitaker, H. A. (1992). An empirical test of two

opposing theoretical models of prefrontal function. Brain and Cognition, 19(1),

48–71. doi:10.1016/0278-2626(92)90037-m

Damasio, A. R. (1995). Review: Toward a neurobiology of emotion and feeling:

Operational concepts and hypotheses. The Neuroscientist, 1(1), 19–25.

doi:10.1177/107385849500100104

http://dx.doi.org/10.1017/S0033291700025563


Damasio, A. R., Everitt, B. J., & Bishop, D. (1996). The somatic marker hypothesis and

the possible functions of the prefrontal cortex [and discussion]. Philosophical

Transactions of the Royal Society of London, Series B: Biological Sciences,

351(1346), 1413–1420. Retrieved from http://www.jstor.org/stable/3069187

Damasio, H., Grabowski, T., Frank, R., Galaburda, A., & Damasio, A. (1994). The

return of phineas gage: Clues about the brain from the skull of a famous patient.

Science, 264(5162), 1102–1105. doi:10.1126/science.8178168

Daneman, M., & Carpenter, P. A. (1980). Individual differences in working memory

and reading. Journal of Verbal Learning and Verbal Behaviour, 19(4), 450–466.

doi:10.1016/s0022-5371(80)90312-6

Davidson, L. L., & Heinrichs, R. W. (2003). Quantification of frontal and temporal lobe

brain-imaging findings in schizophrenia: A meta-analysis. Psychiatry Research:

Neuroimaging, 122(2), 69–87. doi:10.1016/s0925-4927(02)00118-x

Degenhardt, L., Hall, W., & Lynskey, M. (2003). Exploring the association between

cannabis use and depression. Addiction, 98(11), 1493–1504. doi:10.1046/j.1360-

0443.2003.00437.x

Degenhardt, L., Lynskey, M., & Hall, W. (2000). Cohort trends in the age of initiation

of drug use in Australia. Australian and New Zealand Journal Public Health,

24(4), 421–426. doi:10.1111/j.1467-842X.2000.tb01605.x

Delis, D. C., Kaplan, E., & Kramer, J. H. (2001). The Delis-Kaplan Executive Function

System. San Antonio, TX: The Psychological Corporation, p. 47.

Delis, D. C., Kramer, J. H., Kaplan, E., & Ober, B., (2000). California Verbal Learning

Test (Second Edition) (CVLT-II). San Antonia, TX: The Psychological

Corporation.


Delis, D. C., Squire, L. R., Bihrle, A., & Massman, P. (1992). Componential analysis of

problem-solving ability: Performance of patients with frontal lobe damage and

amnesic patients on a new sorting test. Neuropsychologia, 30(8), 683–697.

doi:10.1016/0028-3932(92)90039-O

Dempster, F. N. (1993). Resistance to interference: Developmental changes in a basic

processing mechanism. In M. L. Howe & R. Pasnak (Eds), Emerging Themes in

Cognitive Development (pp. 3-27). New York: Springer New York. doi:

10.1007/978-1-4613-9220-0_1

DeRosse, P., Kaplan, A., Burdick, K. E., Lencz, T., & Malhotra, A. K. (2010). Cannabis

use disorders in schizophrenia: Effects on cognition and symptoms.

Schizophrenia Research, 120(1-3), 95–100. doi:10.1016/j.schres.2010.04.007

Dickinson, D., & Coursey, R. D. (2002). Independence and overlap among

neurocognitive correlates of community functioning in schizophrenia.

Schizophrenia Research, 56(1-2), 161–170.

doi:10.1016/s0920-9964(01)00229-8

Dickinson, D., Iannone, V. N., & Gold, J. M. (2002). Factor structure of the Wechsler

Adult Intelligence Scale–III in schizophrenia. Assessment, 9(2), 171–180. doi:

10.1177/10791102009002008

Dickinson, D., Ragland, J. D., Gold, J. M., & Gur, R. C. (2008). General and specific

cognitive deficits in schizophrenia: Goliath defeats David?. Biological

Psychiatry, 64(9), 823–827. doi: 10.1016/j.biopsych.2003.12.010

DiClemente, C. C. (1993). Changing addictive behaviors: A process perspective.

Current Directions in Psychological Science, 2(4), 101–106. Retrived from

http://www.jstor.org/stable/20182215

http://dx.doi.org/10.1016/0028-3932(92)90039-O

http://dx.doi.org/10.1007/978-1-4613-9220-0_1

http://dx.doi.org/10.1007/978-1-4613-9220-0_1

http://dx.doi.org/10.1016/j.biopsych.2003.12.010

http://www.jstor.org/stable/20182215


Diller, L., Ben-Yishay, T., Gerstman, L. J., Goodkin, R., Gordon, W., & Weinberg, J.

(1974). Studies in cognition and rehabilitation in hemiplegia. New York, NY:

University Medical Centre.

Dimitrov, M., Phipps, M., Zahn, T. P., & Grafman, J. (1999). A thoroughly modern

Gage. Neurocase, 5(4), 345–354. doi: 10.1080/13554799908411987

Dixon, L., Haas, G., Weiden, P. J., Sweeney, J., & Frances, A. J. (1991). Drug abuse in

schizophrenic patients: Clinical correlates and reasons for use. American Journal

of Psychiatry, 148(2), 224–230.

Dodrill, C. B. (1978). A neuropsychological battery for epilepsy. Epilepsia, 19(6), 611–

623. doi:10.1111/j.1528-1157.1978.tb05041.x

Dragt, S., Nieman, D. H., Becker, H. E, van de Fliert, R., Dingemans, P. M., de Haan,

L., van Amelsvoort, T. A., & Linszen, D. H. (2010). Age of onset of cannabis

use is associated with age of onset of high-risk symptoms for psychosis.

Canadian Journal of Psychiatry, 55(3), 165–71.

Drake, R. E., Osher, F. C., & Wallach, M. A. (1991). Homelessness and dual diagnosis.

American Psychologist, 46(11), 1149–1158. doi:10.1037/0003-066x.46.11.1149

Dritschel, B., Kogan, L., Burton, A., Burton, E., & Goddard, L. (1998). Everyday

planning difficulties following traumatic brain injury: A role for

autobiographical memory. Brain Injury, 12(10), 875–886.

doi:10.1080/026990598122098

Duncan, J. (1986). Disorganisation of behaviour after frontal lobe damage. Cognitive

Neuropsychology, 3(3), 271–290. doi: 10.1080/02643298608253360

Duncan, J., Emslie, H., Williams, P., Johnson, R., & Freer, C. (1996). Intelligence and

the frontal lobe: The organization of goal-directed behavior. Cognitive

Psychology, 30(3), 257–303. doi:10.1006/cogp.1996.0008

http://dx.doi.org/10.1006/cogp.1996.0008


Duncan, J., Johnson, R., Swale, M., & Freer, C. (1997). Frontal lobe deficits after head

injury: Unity and diversity of function. Cognitive Neuropsychology, 14(5), 713–

741. doi:10.1080/026432997381420

Dunn, B. D., Dalgleish, T., & Lawrence, A. D. (2006). The somatic marker hypothesis:

A critical evaluation. Neuroscience & Biobehavioral Reviews, 30(2), 239–271.

doi:10.1016/j.neubiorev.2005.07.001

Einstein, G. O., McDaniel, M. A., Richardson, S. L., Guynn, M. J., & Cunfer, A. R.

(1995). Aging and prospective memory: examining the influences of self-

initiated retrieval processes. Journal of Experimental Psychology: Learning,

Memory, and Cognition, 21(4), 996–1007. doi:10.1037/0278-7393.21.4.996

Elliott, R., McKenna, P. J., Robbins, T. W., & Sahakian, B. J. (1995).

Neuropsychological evidence for frontostriatal dysfunction in schizophrenia.

Psychological medicine, 25(3), 619–630. doi:10.1017/S0033291700033523

Erceg-Hurn, D. M., & Mirosevich, V. M. (2008). Modern robust statistical methods: an

easy way to maximize the accuracy and power of your research. American

Psychologist, 63(7), 591–601. doi:10.1037/0003-066X.63.7.591

Eriksen, B. A., & Eriksen, C. W. (1974). Effects of noise letters upon the identification

of a target letter in a nonsearch task. Perception & Psychophysics, 16(1), 143–

149. doi: 10.3758/BF03203267

Ernst, M., Grant, S. J., London, E. D., Contoreggi, C. S., Kimes, A. S., & Spurgeon, L.

(2003). Decision making in adolescents with behavior disorders and adults with

substance abuse. American Journal of Psychiatry, 160(1), 33–40.

doi:10.1176/appi.ajp.160.1.33

http://dx.doi.org/10.1016/j.neubiorev.2005.07.001


http://dx.doi.org/10.1017/S0033291700033523

http://psycnet.apa.org/doi/10.1037/0003-066X.63.7.591

http://dx.doi.org/10.3758/BF03203267


Evans, J. J., Chua, S. E., McKenna, P. J., & Wilson, B. A. (1997). Assessment of the

dysexecutive syndrome in schizophrenia. Psychological Medicine, 27(3), 635–

646. doi:10.1017/s0033291797004790

Ferraro, L., Russo, M., O'Connor, J., Wiffen, B. D., Falcone, M. A., Sideli, L., ... Di

Forti, M. (2013). Cannabis users have higher premorbid IQ than other patients

with first onset psychosis. Schizophrenia Research, 150(1), 129–135.

doi:10.1016/j.schres.2013.07.046

Field, A. (2009). Discovering statistics using SPSS (and sex and drugs and rock ‘n’roll)

(Third Edition). London: Sage publications.

Finkelstein, J. R. J., Cannon, T. D., Gur, R. E., Gur, R. C., & Moberg, P. (1997).

Attentional dysfunctions in neuroleptic-naive and neuroleptic-withdrawn

schizophrenic patients and their siblings. Journal of Abnormal Psychology,

106(2), 203–212. doi:10.1037//0021-843x.106.2.203

Fisk, J., & Montgomery, C. (2008). Real-world memory and executive processes in

cannabis users and non-users. Journal of Psychopharmacology, 22(7), 727–736.

doi:10.1177/0269881107084000

Fisk, J. E., & Sharp, C. A. (2004). Age-related impairment in executive functioning:

Updating, inhibition, shifting, and access. Journal of Clinical and Experimental

Neuropsychology, 26(7), 874–890. doi: 10.1080/13803390490510680

Fisk, J. E., & Warr, P. (1996). Age and working memory: the role of perceptual speed,

the central executive, and the phonological loop. Psychology and Aging, 11(2),

316–323. doi:10.1037/0882-7974.11.2.316

Fortin, S., Godbout, L., & Braun, C. (2003). Cognitive structure of executive deficits in

frontally lesioned head trauma patients performing activities of daily living.

Cortex, 39(2), 273–291. doi:10.1016/s0010-9452(08)70109-6




Fowler, I. L., Carr, V. J., Carter, N. T., & Lewin, T. J. (1998). Patterns of current and

lifetime substance use in schizophrenia. Schizophrenia bulletin, 24(3), 443–455.

Retrieved from http://schizophreniabulletin.oxfordjournals.org/content/24/3/443

Franke, P., Maier, W., Hain, C., & Klingler, T. (1992). Wisconsin Card Sorting Test:

An indicator of vulnerability to schizophrenia? Schizophrenia Research, 6(3),

243–249. doi:10.1016/0920-9964(92)90007-r

Franke, P., Maier, W., Hardt, J., Frieboes, R., Lichtermann, D., & Hain, C. (1993).

Assessment of frontal lobe functioning in schizophrenia and unipolar major

depression. Psychopathology, 26(2), 76–84. doi:10.1159/000284803

Friedman, N. P., & Miyake, A. (2004). The relations among inhibition and interference

control functions: a latent-variable analysis. Journal of Experimental

Psychology: General, 133(1), 101–135. doi: 10.1037/0096-3445.133.1.101

Fristoe, N. M., Salthouse, T. A., & Woodard, J. L. (1997). Examination of age-related

deficits on the Wisconsin Card Sorting Test. Neuropsychology, 11(3), 428–436.

doi:10.1037/0894-4105.11.3.428

Frith, C. D., Friston, K. J., Herold, S., Silbersweig, D., Fletcher, P., Cahill, C., ... Liddle,

P. F. (1995). Regional brain activity in chronic schizophrenic patients during the

performance of a verbal fluency task. The British Journal of Psychiatry, 167(3),

343–349. doi:10.1192/bjp.167.3.343

Funahashi, K. I. (1989). On the approximate realization of continuous mappings by

neural networks. Neural Networks, 2(3), 183–192. doi: 10.1016/0893-

6080(89)90003-8

Fuster, J. M. (1973). Unit activity in prefrontal cortex during delayed-response

performance: neuronal correlates of transient memory. Journal of

Neurophysiology, 36, 61–78.

http://dx.doi.org/10.1037/0096-3445.133.1.101


http://dx.doi.org/10.1016/0893-6080(89)90003-8

http://dx.doi.org/10.1016/0893-6080(89)90003-8


Fuster, J. M. (1989). The Prefrontal Cortex (Second Edition). New York, NY: Raven

Press.

Fuster, J. M. (2000). Executive frontal functions. Experimental Brain Research, 133(1),

66–70. doi: 10.1007/s002210000401

Godbout, L., Grenier, M. C., Braun, C. M. J., & Gagnon, S. (2005). Cognitive structure

of executive deficits in patients with frontal lesions performing activities of daily

living. Brain Injury, 19(5), 337–348. doi:10.1080/02699050400005093

Goel, V., Grafman, J., Tajik, J., Gana, S., & Danto, D. (1997). A study of the

performance of patients with frontal lobe lesions in a financial planning task.

Brain, 120(10), 1805–1822. doi:10.1093/brain/120.10.1805

Goethals, I., Audenaert, K., Van de Wiele, C., & Dierckx, R. (2004). The prefrontal

cortex: Insights from functional neuroimaging using cognitive activation tasks.

European Journal of Nuclear Medicine and Molecular Imaging, 31(3), 408–

416. doi:10.1007/s00259-003-1382-z

Gold, J. M. (2004). Cognitive deficits as treatment targets in schizophrenia.


Gold, J. M., Carpenter, C., Randolph, C., Goldberg, T. E., & Weinberger, D. R. (1997).

Auditory working memory and Wisconsin Card Sorting Test performance in

schizophrenia. Archives of General Psychiatry, 54(2), 159–165.

doi:10.1001/archpsyc.1997.01830140071013

Goldberg, T. E., Gold, J. M., Greenberg, R., Griffin, S., Schulz, S. C., Pickar, D.

... Weiberger, D. R. (1993). Contrasts between patients with affective disorders

and patients with schizophrenia on a neuropsychological test battery. American

Journal of Psychiatry, 150(9), 1355–1362. Retrieved from http:// proquest.com.

http://dx.doi.org/10.1007/s002210000401


Goldberg, T. E., Torrey, E. F., Berman, K. F., & Weinberger, D. R. (1994). Relations

between neuropsychological performance and brain morphological and

physiological measures in monozygotic twins discordant for schizophrenia.

Psychiatry Research: Neuroimaging, 55(1), 5–61. doi:10.1016/0925-

4927(94)90011-6

Golden, C. J. (1978). Stroop Color and Word Test: A Manual for Clinical and

Experimental Uses (pp. 1–46). Chicago: Stoelting.

Goldman-Rakic, P. S. (1987). Circuitry of the frontal association cortex and its

relevance to dementia. Archives of Gerontology and Geriatrics, 6(3), 299–309.

doi:10.1016/0167-4943(87)90029-x

Goldman-Rakic, P. S. (1996). Regional and cellular fractionation of working memory.

Proceedings of the National Academy of Sciences, 93(24), 13473-13480.

Retrieved from

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC33633/?tool=pmcentrez

Goldstein, G. (1990). Neuropsychological heterogeneity in schizophrenia: a

consideration of abstraction and problem-solving abilities. Archives of Clinical

Neuropsychology, 5(3), 251–264. doi:10.1016/0887-6177(90)90024-J

Goldstein, G., Beers, S. R., & Shemansky, W. J. (1996). Neuropsychological

differences between schizophrenic patients with heterogeneous Wisconsin Card

Sorting Test performance. Schizophrenia Research, 21(1), 13–18.

doi:10.1016/0920-9964(96)00019-9

Gordon, S. M., Kennedy, B. P., & McPeake, J. D. (1988). Neuropsychologically

impaired alcoholics: Assessment, treatment considerations, and rehabilitation.

Journal of Substance Abuse Treatment, 5(2), 99–104. doi:10.1016/0740-

5472(88)90019-0


http://dx.doi.org/10.1016/0887-6177(90)90024-J


Gorsuch, R. L. (1983). Three methods for analyzing limited time-series (N of 1) data.

Behavioral Assessment, 5, 141–154.

Goswami, S., Mattoo, S. K., Basu, D., & Singh, G. (2004). Substance-abusing

schizophrenics: Do they self-medicate? American Journal on Addictions, 13(2),

139–150. doi:10.1080/10550490490435795

Grafman, J., & Litvan, I. (1999). Importance of deficits in executive functions. The

Lancet, 354(9194),1921–1923. doi:10.1016/S0140-6736(99)90438-5

Grafman, J., Schwab, K., Warden, D., Pridgen, A., Brown, H. R., & Salazar, A. M.

(1996). Frontal lobe injuries, violence, and aggression: A report of the Vietnam

head injury study. Neurology, 46(5), 1231–1231. doi:10.1212/wnl.46.5.1231

Graham, F. K., & Kendall, B. S. (1960). Memory-for-designs test: Revised general

manual. Perceptual and Motor Skills, 11(2), 147–188. Retrieved from

http://www.amsciepub.com/doi/pdf/10.2466/pms.1960.11.2.147

Grant, I., Gonzalez, R., Carey, C. L., Natarajan, L., & Wolfson, T. (2003). Non-acute

(residual) neurocognitive effects of cannabis use: A meta-analytic study. Journal

of the International Neuropsychological Society, 9(5), 679–689.

doi:10.1017/s1355617703950016

Grant, J. E., Chamberlain, S. R., Schreiber, L., & Odlaug, B. L. (2012).

Neuropsychological deficits associated with cannabis use in young adults. Drug

and Alcohol Dependence, 121(1), 159–162.

doi: 10.1016/j.drugalcdep.2011.08.015

Grech, A., Van Os, J., Jones, P. B., Lewis, S. W., & Murray, R. M. (2005). Cannabis

use and outcome of recent onset psychosis. European Psychiatry, 20(4), 349–

353. doi:10.1016/j.eurpsy.2004.09.013

http://www.amsciepub.com/doi/pdf/10.2466/pms.1960.11.2.147

http://dx.doi.org/10.1016/j.drugalcdep.2011.08.015


Green, M. F. (1996). What are the functional consequences of neurocognitive

deficits in schizophrenia? American Journal of Psychiatry, 153(3), 321–330.

Retrieved from http://psycnet.apa.org/psycinfo/1996-00417-002

Green, M. F. (1999). Interventions for neurocognitive deficits: Editor's introduction.

Schizophrenia Bulletin, 25(2), 197–200.

doi:10.1093/oxfordjournals.schbul.a033373

Green, M. F. (2006). Cognitive impairment and functional outcome in schizophrenia

and bipolar disorder. The Journal of Clinical Psychiatry, 67(10), e12–e12.

Retrieved from http://europepmc.org/abstract/MED/16965182

Green, M. F., & Harvey, P. D. (2014). Cognition in schizophrenia: Past, present, and

future. Schizophrenia Research: Cognition, 1, e1–e9.

doi:10.1016/j.scog.2014.02.001

Green, B., Young, R., & Kavanagh, D. (2005). Cannabis use and misuse prevalence

among people with psychosis. The British Journal of Psychiatry, 187(4), 306–

313. doi:10.1192/bjp.187.4.306

Green, M. F., Kern, R. S., Braff, D. L., & Mintz, J. (2000). Neurocognitive deficits and

functional outcome in schizophrenia: Are we measuring the "right stuff"?

Schizophrenia Bulletin, 26(1), 119–136.


Green, M. F., Kern, R. S., & Heaton, R. K. (2004). Longitudinal studies of cognition

and functional outcome in schizophrenia: implications for MATRICS.


Green, M. F., & Nuechterlein, K. H. (1999). Should schizophrenia be treated as a

neurocognitive disorder? Schizophrenia Bulletin, 25(2), 309–319.


http://europepmc.org/abstract/MED/16965182



Greenwood, K. E., Landau,S., & Wykes, T. (2005). Negative symptoms and specific

cognitive impairments as combined targets for improved functional outcome

within cognitive remediation therapy. Schizophrenia Bulletin, 31(4), 910–921.

doi: 10.1093/schbul/sbi035

Grotenhermen, F. (2003). Pharmacokinetics and pharmacodynamics of cannabinoids.

Clinical Pharmacokinetics, 42(4), 327–360. doi:10.2165/00003088-200342040-

00003

Gruber, S. A., Sagar, K. A., Dahlgren, M. K., Racine, M., & Lukas, S. E. (2012). Age of

onset of marijuana use and executive function. Psychology of Addictive

Behaviors, 26(3), 496–506. doi: 10.1037/a0026269

Gruber, S. A., & Yurgelun-Todd, D. A. (2005). Neuroimaging of marijuana smokers

during inhibitory processing: A pilot investigation. Cognitive Brain Research,

23(1), 107–118. doi:10.1016/j.cogbrainres.2005.02.016

Gruzelier, J., Seymour, K., Wilson, L., Jolley, A., & Hirsch, S. (1988). Impairments on

neuropsychologic tests of temporohippocampal and frontohippocampal

functions and word fluency in remitting schizophrenia and affective disorders.

Archives of General Psychiatry, 45(7), 623–629.

doi:10.1001/archpsyc.1988.01800310027003.

Guadagnoli, E., & Velicer, W. F. (1988). Relation of sample size to the stability of

component patterns. Psychological Bulletin, 103(2), 265–275. doi:

10.1037/0033-2909.103.2.265

Hall, W., Degenhardt, L., & Teesson, M. (2004). Cannabis use and psychotic disorders:

an update. Drug and Alcohol Review, 23(4), 433–443.

doi: 10.1080/09595230412331324554

http://dx.doi.org/10.1037/a0026269

http://dx.doi.org/10.1037/0033-2909.103.2.265

http://dx.doi.org/10.1037/0033-2909.103.2.265


Hall, W., Teesson, M., Lynskey, M., & Degenhardt, L. (1999). The 12‐month

prevalence of substance use and ICD‐10 substance use disorders in Australian

adults: findings from the National Survey of Mental Health and Well‐Being.

Addiction, 94(10), 1541–1550. doi: 10.1046/j.1360-0443.1999.9410154110.x

Harnishfeger, K. K. (1995). The development of cognitive inhibition: Theories,

definitions, and research evidence. In F. N. Dempster & C. J. Brainerd (Eds.),

Interference and Inhibition in Cognition (pp. 175–204). San Diego, CA:

Academic Press. doi: 10.1016/B978-012208930-5/50007-6

Harrison, E. R., Haaga, J., & Richards, T. (1993). Self-reported drug use data: what do

they reveal?. The American Journal of Drug and Alcohol Abuse, 19(4), 423–

441. doi:10.3109/00952999309001632

Harvey, P. D. (2007). Will improving cognition change functional outcomes in

schizophrenia?. Psychiatry, 4(4), 58–602. Retrieved from

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2921243/

Harvey, P. D. (2013). Cognitive aspects of schizophrenia. Wiley Interdisciplinary

Reviews: Cognitive Science, 4(6), 599–608. doi: 10.1002/wcs.1253

Harvey, M., Sellman, J., Porter, R., & Frampton, C. (2007). The relationship between

non-acute adolescent cannabis use and cognition. Drug and Alcohol Review,

26(3), 309–319. doi:10.1080/09595230701247772

Harvey, P. D., Green, M. F., Keefe, R. S. E., & Velligan, D. I. (2004). Cognitive

functioning in schizophrenia. Journal of Clinical Psychiatry, 65(3), 361–372.

doi:10.4088/JCP.v65n0312

http://dx.doi.org/10.1016/B978-012208930-5/50007-6

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2921243/


Harvey, P. D., Howanitz, E., Parrella, M., White, L., Davidson, M., Mohs, R. C., &

Davis, K. L. (1998). Symptoms, cognitive functioning, and adaptive skills in

geriatric patients with lifelong schizophrenia: A comparison across treatment

sites. American Journal of Psychiatry, 155(8), 1080–1086.

doi.org/10.1176/ajp.155.8.1080

Harvey, P. D., Lombardi, J., Leibman, M., White, L., Parrella, M., Powchik, P., &

Davidson, M. (1996). Cognitive impairment and negative symptoms in geriatric

chronic schizophrenic patients: A follow-up study. Schizophrenia Research,

22(3), 223–231. doi:10.1016/s0920-9964(96)00075-8

Harvey, P. D., Napolitano, J. A., Mao, L., & Gharabawi, G. (2003). Comparative effects

of risperidone and olanzapine on cognition in elderly patients with schizophrenia

or schizoaffective disorder. International Journal of Geriatric Psychiatry, 18(9),

820–829. doi:10.1002/gps.929

Heaton, R. K., (1981). Wisconsin Card Sorting Test Manual. Odessa, FL: Psychological

Assessment Resources.

Heinrichs, R. W., & Zakzanis, K. K. (1998). Neurocognitive deficit in schizophrenia: A

quantitative review of the evidence. Neuropsychology, 12(3), 426–445.

doi:10.1037//0894-4105.12.3.426

Herman, M. (2004). Neurocognitive functioning and quality of life among dually

diagnosed and non‐substance abusing schizophrenia inpatients. International

Journal of Mental Health Nursing, 13(4), 282–291. doi: 10.1111/j.1440-

0979.2004.00346.x

http://dx.doi.org/10.1176/ajp.155.8.1080


Hermann, D., Sartorius, A., Welzel, H., Walter, S., Skopp, G., Ende, G., & Mann, K.

(2007). Dorsolateral prefrontal cortex n-acetylaspartate/total creatine (naa/tcr)

loss in male recreational cannabis users. Biological Psychiatry, 61(11), 1281–

1289. doi:10.1016/j.biopsych.2006.08.027

Hewitt, J., Evans, J. J., & Dritschel, B. (2006). Theory driven rehabilitation of executive

functioning: Improving planning skills in people with traumatic brain injury

through the use of an autobiographical episodic memory cueing procedure.

Neuropsychologia, 44(8), 1468–1474.

doi:10.1016/j.neuropsychologia.2005.11.016

Hoff, A. L., Riordan, H., O'Donnell, D. W., Morris, L., & DeLisi, L. E. (1992).

Neuropsychological functioning of first-episode schizophreniform patients.

American Journal of Psychiatry, 149(7), 898–903.

Hughes, C., Kumari, V., Soni, W., Das, M., Binneman, B., Drozd, S., & Sharma, T.

(2003). Longitudinal study of symptoms and cognitive function in chronic

schizophrenia. Schizophrenia Research, 59(2-3), 137–146. doi:10.1016/s0920-

9964(01)00393-0

Hutton, S. B., Puri, B. K., Duncan, L. J., Robbins, T. W., Barnes, T. R. E., & Joyce, E.

M. (1998). Executive function in first-episode schizophrenia. Psychological

Medicine, 28(2), 463–473. doi:10.1017/s0033291797006041

Ihara, H., Berrios, G. E., & McKenna, P. J. (2003). The association between negative

and dysexecutive syndromes in schizophrenia: A cross-cultural study.

Behavioral Neurology, 14(3-4), 63–74. doi:10.1155/2003/304095

Iversen, L. L. (2000). The Science of Marijuana [Review]. Oxford: Oxford

University Press.

http://dx.doi.org/10.1016/j.neuropsychologia.2005.11.016


Jager, G., Kahn, R. S., Van Den Brink, W., Van Ree, J. M., & Ramsey, N. F. (2006).

Long-term effects of frequent cannabis use on working memory and attention:

An fMRI study. Psychopharmacology, 185(3), 358–368. doi:10.1007/s00213-

005-0298-7

Jockers-Scherübl, M. C., Wolf, T., Radzei, N., Schlattmann, P., Rentzsch, J., Gómez-

Carrillo de Castro, A., & Kühl, K. P. (2007). Cannabis induces different

cognitive changes in schizophrenic patients and in healthy controls. Progress in

Neuro-Psychopharmacology and Biological Psychiatry, 31(5), 1054–1063.

doi:10.1016/j.pnpbp.2007.03.006

Joyce, E. M., Collinson, S. L., & Crichton, P. (1996). Verbal fluency in schizophrenia:

relationship with executive function, semantic memory and clinical alogia.

Psychological Medicine, 26(1), 39–49. doi:10.1017/S0033291700033705

Joyce, E. M., & Roiser, J. P. (2007). Cognitive heterogeneity in schizophrenia. Current

Opinion in Psychiatry, 20(3), 268–272. doi:10.1097/YCO.0b013e3280ba4975

Jurado, M. B., & Rosselli, M. (2007). The elusive nature of executive functions: a

review of our current understanding. Neuropsychology Review, 17(3), 213–233.

doi:10.1007/s11065-007-9040-z

Kabat-Zinn, J., Massion, A. O., Kristeller, J., Peterson, L. G., Fletcher, K. E., Pbert, L.,

Lenderking, W. R., & Santorelli, S. F. (1992). Effectiveness of a meditation-

based stress reduction program in the treatment of anxiety disorders. American

Journal of Psychiatry, 149(7), 936–943.

Kafer, K. L., & Hunter, M. (1997). On testing the face validity of planning/problem-

solving tasks in a normal population. Journal of the International

Neuropsychological Society, 3(2), 108–119.

http://dx.doi.org/10.1017/S0033291700033705

http://dx.doi.org/10.1097%2FYCO.0b013e3280ba4975

http://psycnet.apa.org/doi/10.1007/s11065-007-9040-z


Kanayama, G., Rogowska, J., Pope, H. G., Gruber, S. A., & Yurgelun-Todd, D. A.

(2004). Spatial working memory in heavy cannabis users: A functional magnetic

resonance imaging study. Psychopharmacology, 176(3-4), 239–247.

doi:10.1007/s00213-004-1885-8

Katz, N., Tadmor, I., Felzen, B., & Hartman-Maeir, A. (2007). The behavioural

assessment of the dysexecutive syndrome (BADS) in schizophrenia and its

relation to functional outcomes. Neuropsychological Rehabilitation, 17(2), 192–

205. doi:10.1080/09602010600685053

Kavanagh, D. J., Waghorn, G., Jenner, L., Chant, D. C., Carr, V., Evans, M., ...

McGrath, J. J. (2004). Demographic and clinical correlates of comorbid

substance use disorders in psychosis: Multivariate analyses from an

epidemiological sample. Schizophrenia Research, 66(2-3), 115–124.

doi:10.1016/s0920-9964(03)00130-0

Kay, S. R., Fiszbein, A., & Opler, L. A. (1987). The Positive and Negative Syndrome

Scale (PANSS) for schizophrenia. Schizophrenia Bulletin, 13(2), 261–276.

Retrieved from http://www.psycontent.com/content/p81u7t14n7303377/

Kay, S. R., Opler, L. A., & Lindenmayer, J. P. (1988). Reliability and validity of the

Positive and Negative Syndrome Scale for schizophrenics. Psychiatry Research,

23(1), 99–110. doi:10.1016/0165-1781(88)90038-8

Keefe, R. S. E., Goldberg, T. E., Harvey, P. D., Gold, J. M., Poe, M., & Coughenour, L.

(2004). The Brief Assessment of Cognition in Schizophrenia: Reliability,

sensitivity, and comparison with a standard neurocognitive battery.

Schizophrenia Research, 68(2-3), 283–297.

doi.org/10.1016/j.schres.2003.09.011

http://dx.doi.org/10.1016/0165-1781(88)90038-8



Keefe, R. S., Poe, M., Walker, T. M., Kang, J. W., & Harvey, P. D. (2006). The

Schizophrenia Cognition Rating Scale: an interview-based assessment and its

relationship to cognition, real-world functioning, and functional capacity.

American Journal of Psychiatry, 163(3), 426–432. doi:

10.1176/appi.ajp.163.3.426

Kenny, J. T., & Meltzer, H. Y. (1991). Attention and higher cortical functions in

schizophrenia. Journal of Neuropsychiatry, 3(3), 269–275.

Kerns, J. G., & Berenbaum, H. (2002). Cognitive impairments associated with formal

thought disorder in people with schizophrenia. Journal of Abnormal Psychology,

111(2), 211–224. doi:10.1037/0021-843x.111.2.211

Kinch, J., & McDonald, S. (2001). Traumatic brain injury and prospective memory: An

examination of the influences of executive functioning and retrospective

memory. Brain Impairment, 2(2), 119–130. doi:

http://dx.doi.org/10.1375/brim.2.2.119

Kirby, K. N., Petry, N. M., & Bickel, W. K. (1999). Heroin addicts have higher discount

rates for delayed rewards than non-drug-using controls. Journal of Experimental

Psychology: General, 128(1), 78–87. doi: http://dx.doi.org/10.1037/0096-

3445.128.1.78

Knapp, M. (1997). Costs of schizophrenia. The British Journal of Psychiatry, 171(6),

509–518. doi:10.1192/bjp.171.6.509

Knight, R. G., Titov, N., & Crawford, M. (2006). The effects of distraction on

prospective remembering following traumatic brain injury assessed in a

simulated naturalistic environment. Journal of the International

Neuropsychological Society, 12(1), 8–16. doi:10.1017/s1355617706060048

http://dx.doi.org/10.1375/brim.2.2.119




Kolb, B., & Whishaw, I. Q. (1985). Fundamentals of Human Neuropsychology (Second

Edition). New York: Freeman.

Koskinen, J., Löhönen, J., Koponen, H., Isohanni, M., & Miettunen, J. (2010). Rate of

cannabis use disorders in clinical samples of patients with schizophrenia: A

meta-analysis. Schizophrenia Bulletin, 36(6), 1115–1130.

doi:10.1093/schbul/sbp031

Krabbendam, L., de Vugt, M. E., Derix, M. M. A., & Jolles, J. (1999). The behavioural

assessment of the dysexecutive syndrome as a tool to assess executive functions

in schizophrenia. The Clinical Neuropsychologist (Neuropsychology,

Development and Cognition: Section D), 13(3), 370–375.

doi:10.1076/clin.13.3.370.1739

Kraepelin, E. (1919). (Translated by R. M. Barclay, published in 1971). Dementia

Praecox and Paraphrenia. New York: Krieger Publishing Company.

Kumra, S., Thaden, E., DeThomas, C., & Kranzler, H. (2005). Correlates of substance

abuse in adolescents with treatment-refractory schizophrenia and schizoaffective

disorder. Schizophrenia Research, 73(2-3), 369–371.

doi:10.1016/j.schres.2004.08.006

Kurtz, M. M., Moberg, P. J., Ragland, J. D., Gur, R. C., & Gur, R. E. (2005). Symptoms

versus neurocognitive test performance as predictors of psychosocial status in

schizophrenia: A 1- and 4-year prospective study. Schizophrenia Bulletin, 31(1),

167–174. doi:10.1093/schbul/sbi004

Large, M., Sharma, S., Compton, M. T., Slade, T., & Nielssen, O. (2011). Cannabis use

and earlier onset of psychosis: a systematic meta-analysis. Archives of General

Psychiatry, 68(6), 555–61. doi:10.1001/archgenpsychiatry.2011.5.


Leeson, V. C., Harrison, I., Ron, M. A., Barnes, T. R., & Joyce, E. M. (2011). The

effect of cannabis use and cognitive reserve on age at onset and psychosis

outcomes in first-episode schizophrenia. Schizophrenia Bulletin, 38(4), 873–

880. doi:10.1093/schbul/sbq153

Levaux, M. N., Larøi, F., Malmedier, M., Offerlin-Meyer, I., Danion, J. M., & Van der

Linden, M. (2012). Rehabilitation of executive functions in a real-life setting:

Goal Management Training applied to a person with schizophrenia. Case

Reports in Psychiatry, 2012(Article ID 503023), 1–15.

doi:10.1155/2012/503023

Levine, B., Robertson, I. H., Clare, L., Carter, G., Hong, J., Wilson, B. A., ... Stuss,

D. T. (2000). Rehabilitation of executive functioning: An experimental–clinical

validation of goal management training. Journal of the International

Neuropsychological Society, 6(3), 299–312. Retrieved from

http://www.tara.tcd.ie/bitstream/handle/2262/477/JINS2000.pdf;jsessionid=2C6

C4DB8366C1382F3B31D127FB7A9CC?sequence=1

Levine, B., Stuss, D. T., Winocur, G., Binns, M. A., Fahy, L., Mandic, M., ...

Robertson, I. H. (2007). Cognitive rehabilitation in the elderly: effects on

strategic behavior in relation to goal management. Journal of the International


Lezak, M. D., Howieson, D. B., Loring, D. W., Hannay, J. H., & Fischer, J. S. (1995).

Neuropsychological Assessment (Third Edition). New York, NY: Oxford

University Press.

Lezak, M. D., Howieson, D. B., & Loring, D. W. (2004). Neuropsychological

Assessment (Fourth Edition). New York, NY: Oxford University Press, p. 35.

http://dx.doi.org/10.1017/S1355617707070178


Liddle, P. F., & Morris, D. L. (1991). Schizophrenic syndromes and frontal lobe

performance. The British Journal of Psychiatry, 158(3), 340–345.

doi:10.1192/bjp.158.3.340

Linszen, D. H., Dingemans, P. M., & Lenior, M. E. (1994). Cannabis abuse and the

course of recent-onset schizophrenic disorders. Archives of General Psychiatry,

51(4), 273–279. doi:10.1001/archpsyc.1994.03950040017002

Lovibond, P. F., & Lovibond, S. H. (1995). The structure of negative emotional states:

Comparison of the Depression Anxiety Stress Scales (DASS) with the Beck

Depression and Anxiety Inventories. Behaviour Research and Therapy, 33(3),

335–343. doi:10.1016/0005-7967(94)00075-U

Lovibond, S. H., & Lovibond, P. F. (1995). Manual for the Depression Anxiety Stress

Scales. Sydney: Psychology Foundation.

Lundqvist, T., Jönsson, S., & Warkentin, S. (2001). Frontal lobe dysfunction in long-

term cannabis users. Neurotoxicology and Teratology, 23(5), 437–443.

doi:10.1016/S0892-0362(01)00165-9

Luria, A. R. (1973). The Working Brain. London, UK: Penguin.

Lyons, M. J., Bar, J. L., Panizzon, M. S., Toomey, R., Eisen, S., Xian, H., & Tsuang, M.

T. (2004). Neuropsychological consequences of regular marijuana use: A twin

study. Psychological Medicine, 34(7), 1239–1250.

doi:10.1017/s0033291704002260

Lyon, G. R., & Krasnegor, N. A. (1996). Attention, Memory, and Executive

Function. Baltimore, MD: Paul H. Brookes Publishing Co.

MacLeod, C. M. (1991). Half a century of research on the Stroop effect: An integrative

review. Psychological Bulletin, 109(2), 163–203. doi:10.1037//0033-

2909.109.2.163

http://dx.doi.org/10.1016/0005-7967(94)00075-U

http://dx.doi.org/10.1016/S0892-0362(01)00165-9


Manchester, D., Priestley, N., & Jackson, H. (2004). The assessment of executive

functions: Coming out of the office. Brain Injury, 18(11), 1067–1081.

doi:10.1080/02699050410001672387

Mata, I., Rodríguez-Sánchez, J. M., Pelayo-Terán, J. M., Pérez-Iglesias, R., González-

Blanch, C., Ramírez-Bonilla, M., ... Crespo-Facorro, B. (2008). Cannabis abuse

is associated with decision-making impairment among first-episode patients with

schizophrenia-spectrum psychosis. Psychological Medicine, 38(9), 1257–1266.

doi:10.1017/S0033291707002218

Mayer, J. D., Salovey, P., & Caruso, D. R. (2009). Mayer-Salovey-Caruso Emotional

Intelligence Test (Spanish version). Madrid: TEA ediciones.

Maylor, E. A., Smith, G., Della Sala, S., & Logie, R. H. (2002). Prospective and

retrospective memory in normal aging and dementia: An experimental study.

Memory & Cognition, 30(6), 871-884. doi: 10.3758/BF03195773

McClure, M. M., Bowie, C. R., Patterson, T. L., Heaton, R. K., Weaver, C., Anderson,

H., & Harvey, P. D. (2007). Correlations of functional capacity and

neuropsychological performance in older patients with schizophrenia: evidence

for specificity of relationships?. Schizophrenia Research, 89(1), 330–338.

doi:10.1016/j.schres.2006.07.024

McDaniel, M. A., & Einstein, G. O. (1993). The importance of cue familiarity and cue

distinctiveness in prospective memory. Memory, 1(1), 23–41.

doi:10.1080/09658219308258223

McHale, S., & Hunt, N. (2008). Executive function deficits in short‐term abstinent

cannabis users. Human Psychopharmacology: Clinical and Experimental, 23(5),

409–415. doi:10.1002/hup.941

http://dx.doi.org/10.1017/S0033291707002218

http://dx.doi.org/10.3758/BF03195773



Medalia, A., & Choi, J. (2009). Cognitive remediation in schizophrenia.

Neuropsychology Review, 19(3), 353–364. doi: 10.1007/s11065-009-9097-y

Medalia, A., Revheim, N., & Casey, M. (2002). Remediation of problem-solving skills

in schizophrenia: evidence of a persistent effect. Schizophrenia Research, 57(2),

165–171. doi:10.1016/S0920-9964(01)00293-6

Menditto, A. A., Wallace, C. J., Liberman, R. P., Wal, J. V., Jones, N. T., & Stuve, P.

(1999). Functional assessment of independent living skills. Psychiatric

Rehabilitation Skills, 3(2), 200–219. doi:10.1080/10973439908408384

Milner, B. (1963). Effects of different brain lesions on card sorting: The role of the

frontal lobes. Archives of Neurology, 9(1), 90–100.

doi:10.1001/archneur.1963.00460070100010.

Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T.

D. (2000). The unity and diversity of executive functions and their contributions

to complex “frontal lobe” tasks: A latent variable analysis. Cognitive

Psychology, 41(1), 49–100. doi:10.1006/cogp.1999.0734

Moscovitch, M., &Winocur, G. (1992). The neuropsychology of memory and aging. In

F. I. M. Craik & T. A. Salthouse (Eds.), The Handbook of Aging and Cognition

(pp. 315-372). Hillsdale, NJ: Erlbaum.

Morris, R., Rushe, T., Woodruffe, P. W., & Murray, R. M. (1995). Problem solving in

schizophrenia: A specific deficit in planning ability. Schizophrenia Research,

14(3), 235–246. doi:10.1016/0920-9964(94)00044-9

Mueser, K. T., Yarnold, P. R., Levinson, D. F., Singh, H., Bellack, A. S., Kee, K., ...

Yadalam, K. G. (1990). Prevalence of substance abuse in schizophrenia:

Demographic and clinical correlates. Schizophrenia Bulletin, 16(1), 31–56.

doi:10.1093/schbul/16.1.31

http://dx.doi.org/10.1016/S0920-9964(01)00293-6


Nelson, H. E., & Willison, J. R. (1991). National Adult Reading Test (NART) – Second

Edition. Windsor, UK: NFER-Nelson.

Nigg, J. T. (2000). On inhibition/disinhibition in developmental psychopathology:

views from cognitive and personality psychology and a working inhibition

taxonomy. Psychological Bulletin, 126(2), 220–246. doi: 10.1037/0033-

2909.126.2.220

Niki, H. (1974). Differential activity of prefrontal units during right and left delayed

response trials. Brain Research, 70(2), 346–349. doi: 10.1016/0006-

8993(74)90324-2

Num, S. (2006). The application of a hierarchical model in investigating the construct

validity of the executive functions in young adults (Unpublished honours thesis).

University of South Australia, South Australia, Australia.

O'Carroll, R., Egan, V., & MacKenzie, D. M. (1994). Assessing cognitive estimation.

British Journal of Clinical Psychology, 33(2), 193–197. doi: 10.1111/j.2044-

8260.1994.tb01110.x

O'Leary, M. R., Donovan, D. M., Chaney, E. F., & Walker, R. D. (1979). Cognitive

impairment and treatment outcome with alcoholics: Preliminary findings.

Journal of Clinical Psychiatry, 40(9), 397–398.

O’Malley, S., Adamse, M., Heaton, R. K., & Gawin, F. H. (1992). Neuropsychological

impairment in chronic cocaine abusers. American Journal of Drug and Alcohol

Abuse, 18(2), 131–144. doi: 10.3109/00952999208992826

Pantelis, C., Barnes, T. R., Nelson, H. E., Tanner, S., Weatherley, L., Owen, A. M., &

Robbins, T. W. (1997). Frontal-striatal cognitive deficits in patients with chronic

schizophrenia. Brain, 120(10), 1823–1843. doi:10.1093/brain/120.10.1823

http://dx.doi.org/10.1037/0033-2909.126.2.220

http://dx.doi.org/10.1037/0033-2909.126.2.220

http://dx.doi.org/10.1016/0006-8993(74)90324-2

http://dx.doi.org/10.1016/0006-8993(74)90324-2


Park, D. C., Hertzog, C., Kidder, D. P., Morrell, R. W., & Mayhorn, C. B. (1997).

Effect of age on event-based and time-based prospective memory. Psychology

and Aging, 12(2), 314–327. doi:10.1037//0882-7974.12.2.314

Parker, D. M., & Crawford, J. R. (1992). Assessment of frontal lobe function. In J. R.

Crawford, D. M. Parker, & W. W. McKinlay (Eds.), A Handbook of

Neuropsychological Assessment (pp. 267–291). London: Erlbaum.

Parkin, A. J. (1998). The central executive does not exist. Journal of the International


Parkin, A. J., & Java, R. I. (1999). Deterioration of frontal lobe function in normal

aging: Influences of fluid intelligence versus perceptual speed.

Neuropsychology, 13(4), 539–545. doi:10.1037/0894-4105.13.4.539

Patterson, T. L., Goldman, S., McKibbin, C. L., Hughs, T., & Jeste, D. V. (2001).

UCSD performance-based skills assessment: Development of a new measure of

everyday functioning for severely mentally ill adults. Schizophrenia Bulletin,

27(2), 235–245. doi:10.1093/oxfordjournals.schbul.a006870

Paulesu, E., Goldacre, B., Scifo, P., Cappa, S. F., Gilardi, M. C., Castiglioni, I., ...

Fazio, F. (1997). Functional heterogeneity of left inferior frontal cortex as

revealed by fMRI. Neuroreport, 8(8), 2011–2016.

Paulus, M. P., Tapert, S. F., & Schuckit, M. A. (2005). Neural activation patterns of

methamphetamine-dependent subjects during decision making predict relapse.

Archives of General Psychiatry, 62(7), 761–768. doi:10.1001/archpsyc.62.7.761

Penadés, R., Boget, T., Catalán, R., Bernardo, M., Gastó, C., & Salamero, M. (2003).

Cognitive mechanisms, psychosocial functioning, and neurocognitive

rehabilitation in schizophrenia. Schizophrenia Research, 63(3), 219–227.

doi:10.1016/s0920-9964(02)00359-6



Peralta, V., & Cuesta, M. J. (1992). Influence of cannabis abuse on schizophrenic

psychopathology. Acta Psychiatrica Scandinavica, 85(2), 127–130.

doi:10.1111/j.1600-0447.1992.tb01456.x

Perlick, D. A., Rosenheck, R. A., Kaczynski, R., Bingham, S., & Collins, J. (2008).

Association of symptomatology and cognitive deficits to functional capacity in

schizophrenia. Schizophrenia Research, 99(1-3), 192–199.

doi:10.1016/j.schres.2007.08.009

Persson, J., & Reuter-Lorenz, P. A. (2008). Gaining Control: Training Executive

Function and Far Transfer of the Ability to Resolve Interference [retracted].

Psychological Science, 19(9), 881–888. doi:10.1111/j.1467-9280.2008.02172.x

Petrides, M., & Milner, B. (1982). Deficits on subject-ordered tasks after frontal- and

temporal-lobe lesions in man. Neuropsychologia, 20(3), 249–262.

doi:10.1016/0028-3932(82)90100-2

Phillips, L. H. (1997). Do “frontal tests” measure executive function? Issues of

assessment and evidence from fluency tests. In P. Rabbit (Ed.), Methodology of

Frontal and Executive Function (pp. 191–213.). East Sussex, UK: Psychology

Press.

Pope, H., Gruber, A. J., & Yurgelun-Todd, D. (1995). The residual neuropsychological

effects of cannabis: The current status of research. Drug and Alcohol

Dependence, 38(1), 25–34. doi:10.1016/0376-8716(95)01097-i

Pope, H. G., Gruber, A. J., Hudson, J. I., Cohane, G., Huestis, M. A., & Yurgelun-Todd,

D. (2003). Early-onset cannabis use and cognitive deficits: What is the nature of

the association? Drug and Alcohol Dependence, 69(3), 303–310.

doi:10.1016/s0376-8716(02)00334-4


Pope, H. G., Gruber, A. J., Hudson, J. I., Huestis, M. A., & Yurgelun-Todd, D. (2001).

Neuropsychological performance in long-term cannabis users. Archives of

General Psychiatry, 58(10), 909–915. doi:10.1001/archpsyc.58.10.909.

Pope, H. G., Gruber, A. J., Hudson, J. I., Huestis, M. A., & Yurgelun-Todd, D. (2002).

Cognitive measures in long-term cannabis users. The Journal of Clinical

Pharmacology, 42(S1), 41S–47S. doi:10.1002/j.1552-4604.2002.tb06002.x

Pope, H. G., & Yurgelun-Todd, D. (1996). The residual cognitive effects of heavy

marijuana use in college students. The Journal of the American Medical

Association, 275(7), 521–527. doi:10.1001/jama.1996.03530310027028.

Potvin, S., Joyal, C. C., Pelletier, J., & Stip, E. (2008). Contradictory cognitive

capacities among substance-abusing patients with schizophrenia: a meta-

analysis. Schizophrenia Research, 100(1), 242–251.

doi:10.1016/j.schres.2007.04.022

Quednow, B. B., Kühn, K. U., Hoppe, C., Westheide, J., Maier, W., Daum, I., &

Wagner, M. (2007). Elevated impulsivity and impaired decision-making cognition in

heavy users of MDMA (“Ecstasy”). Psychopharmacology, 189(4), 517–530.

doi: 10.1007/s00213-005-0256-4

Rabbit, P. (1997). Introduction: Methodologies and models in the study of executive

function. In P. Rabbit (Ed.), Methodology of Frontal and Executive Function

(pp. 1–38). East Sussex, UK: Psychology Press.

Rabin, R. A., Zakzanis, K. K., Daskalakis, Z. J., & George, T. P. (2013). Effects of

cannabis use status on cognitive function, in males with schizophrenia.

Psychiatry Research, 206(2-3), 158–165. doi:10.1016/j.psychres.2012.11.019



Rabin, R. A., Zakzanis, K. K., & George, T. P. (2011). The effects of cannabis use on

neurocognition in schizophrenia: A meta-analysis. Schizophrenia Research,

128(1-3), 111–116. doi:10.1016/j.schres.2011.02.017

Raskin, S. A., & Rearick, E. (1996). Verbal fluency in individuals with mild traumatic

brain injury. Neuropsychology, 10(3), 416–422. doi:10.1037/0894-

4105.10.3.416

Regier, D. A., Farmer, M. E., Rae, D. S., Locke, B. Z., Keith, S. J., Judd, L. L., &

Goodwin, F. K. (1990). Comorbidity of mental disorders with alcohol and other

drug abuse. Journal of the American Medical Association, 264(19), 2511–2518.

doi:10.1001/jama.1990.03450190043026

Reichenberg, A., & Harvey, P. D. (2007). Neuropsychological impairments in

schizophrenia: Integration of performance-based and brain imaging findings.

Psychological Bulletin, 133(5), 833–858. doi:10.1037/0033-2909.133.5.833

Reitan, R. M. (1958). Validity of the Trail Making Test as an indicator of organic brain

damage. Perceptual and Motor Skills, 8(3), 271–276.

doi:10.2466/pms.1958.8.3.271

Reitan R. M., & Wolfson, D. (1993). The Halstead-Reitan Neuropsychological Test

Battery: Theory and Clinical Interpretation (Second Edition). South Tuscon:

Neuropsychology Press.

Rempfer, M. V., Hamera, E. K., Brown, C. E., & Cromwell, R. L. (2003). The relations

between cognition and the independent living skill of shopping in people with

schizophrenia. Psychiatry Research, 117(2), 103–112. doi:10.1016/s0165-

1781(02)00318-9

Rey, A. (1964). L’Examen Clinique en Psychologie. Paris: Universitaires de France.

http://dx.doi.org/10.1037/0894-4105.10.3.416

http://dx.doi.org/10.1037/0894-4105.10.3.416


Riley, E. M., McGovern, D., Mockler, D., Doku, V. C. K., ÓCeallaigh, S., Fannon, D.

G., & Sharma, T. (2000). Neuropsychological functioning in first-episode

psychosis — evidence of specific deficits. Schizophrenia Research, 43(1), 47–

55. doi:10.1016/s0920-9964(99)00177-2

Ritter, L., Meador-Woodruff, J. H., & Dalack, G. W. (2004). Neurocognitive measures

of prefrontal cortical dysfunction in schizophrenia. Schizophrenia Research,

68(1), 65–73. doi:10.1016/s0920-9964(03)00086-0

Robbins, T. W. (1990). The case for frontostriatal dysfunction in schizophrenia.

Schizophrenia Bulletin, 16(3), 391–402. doi:10.1093/schbul/16.3.391

Robbins, T. W., James, M., Owen, A. M., Sahakian, B. J., Lawrence, A. D., McInnes,

L., & Rabbitt, P. M. A. (1998). A study of performance on tests from the

CANTAB battery sensitive to frontal lobe dysfunction in a large sample of

normal volunteers: Implications for theories of executive functioning and

cognitive aging. Journal of the International Neuropsychological Society, 4(5),

474–490. doi:10.1017/s1355617798455073

Roberts, A. C., Robbins, T. W., & Weiskrantz, L. (1998). The Prefrontal Cortex:

Executive and Cognitive Functions. London, UK: Oxford University Press.

Robertson, I. H. (1996). Goal Management Training: A Clinical Manual. Cambridge,

UK: PsycConsult.

Robertson, I.H., Levine, B., & Manly, T., (2005). Goal Management Training.

Baycrest: Rotman Research Institute.

Rodríguez-Sánchez, J. M., Ayesa-Arriola, R., Mata, I., Moreno-Calle, T., Pérez-

Iglesias, R., González-Blanch, C., ... Crespo-Facorro, B. (2010). Cannabis use

and cognitive functioning in first-episode schizophrenia patients. Schizophrenia

Research, 124(1), 142–151. doi:10.1016/j.schres.2010.08.017



Rodriguez-Jimenez, R., Aragües, M., Jimenez-Arriero, M. A., Ponce, G.,

Martinez, I., Hoenicka, J., Rubio, G., & Palomo, T. (2008). Psychopathology

and Wisconsin Card Sorting Test performance in male schizophrenic patients:

Influence of dual diagnosis. Psychopathology, 41(1), 58–64.

doi.10.1159/000110627

Royall, D. R., Lauterbach, E. C., Cummings, J. L., Reeve, A., Rummans, T. A., Kaufer,

D. I., ... Coffey, C. E. (2002). Executive control function: A review of its

promise and challenges for clinical research. A report from the Committee on

Research of the American Neuropsychiatric Association. The Journal of

Neuropsychiatry and Clinical Neurosciences, 14(4), 377–405.

doi:10.1176/appi.neuropsych.14.4.377

Ruff, R. M., & Allen, C. C., (1996). Ruff 2 & 7 Selective Attention Test: Professional

Manual. Odessa, Florida: Psychological Assessment Resources.

Sahakian, B. J., & Owen, A. M. (1992). Computerized assessment in neuropsychiatry

using CANTAB: discussion paper. Journal of the Royal Society of Medicine,

85(7), 399–402. doi:10.1177/014107689208500711

Salthouse, T. A., Atkinson, T. M., & Berish, D. E. (2003). Executive functioning as a

potential mediator of age-related cognitive decline in normal adults. Journal of

Experimental Psychology: General, 132(4), 566–594. doi:10.1037/0096-

3445.132.4.566

Salthouse, T. A., & Babcock, R. L. (1991). Decomposing adult age differences in

working memory. Developmental psychology, 27(5), 763–776.

doi:10.1037/0012-1649.27.5.763

http://dx.doi.org/10.1176/appi.neuropsych.14.4.377

http://dx.doi.org/10.1037/0012-1649.27.5.763


Salyers, M. P., & Mueser, K. T. (2001). Social functioning, psychopathology, and

medication side effects in relation to substance use and abuse in schizophrenia.

Schizophrenia Research, 48(1), 109–123. doi:10.1016/s0920-9964(00)00063-3

Sánchez-Torres, A. M., Basterra, V., Rosa, A., Fañanás, L., Zarzuela, A., Ibáñez, B., ...

Cuesta, M. J. (2013). Lifetime cannabis use and cognition in patients with

schizophrenia spectrum disorders and their unaffected siblings. European

Archives of Psychiatry and Clinical Neuroscience, 263(8), 643–653.

doi:10.1007/s00406-013-0404-5

Savla, G. N., Twamley, E. W., Thompson, W. K., Delis, D. C., Jeste, D. V., & Palmer,

B. W. (2011). Evaluation of specific executive functioning skills and the

processes underlying executive control in schizophrenia. Journal of the

International Neuropsychological Society, 17(1), 14–23.

doi:10.1017/S1355617710001177

Sarne, Y., & Mechoulam, R. (2005). Cannabinoids: between neuroprotection and

neurotoxicity. Current Drug Targets-CNS & Neurological Disorders, 4(6), 677–

684. 10.2174/156800705774933005

Saykin, A. J., Gur, R. C., Gur, R. E., Mozley, P. D., Mozley, L. H., Resnick, S. M., &

Stafiniak, P. (1991). Neuropsychological function in schizophrenia. Archives of

General Psychiatry, 48(7), 618–624.

doi:10.1001/archpsyc.1991.01810310036007

Saykin, A. J., Shtasel, D. L., Gur, R. E., Kester, D. B., Mozley, L. H., Stafiniak, P., &

Gur, R. C. (1994). Neuropsychological deficits in neuroleptic naive patients with

first-episode schizophrenia. Archives of General Psychiatry, 51(2), 124–131.

doi:10.1001/archpsyc.1994.03950020048005


Segal, Z. V., Williams, J. M. G., & Teasdale, J. D. (2002) Mindfulness-based Cognitive

Therapy for Depression - A New Approach to Preventing Relapse. New York,

NY: Guilford Press.

Schneider, L. C., & Struening, E. L. (1983). SLOF: a behavioral rating scale for

assessing the mentally ill. Social Work Research & Abstracts, 19(3), 9–21.

Schnell, T., Koethe, D., Daumann, J., & Gouzoulis-Mayfrank, E. (2009). The role of

cannabis in cognitive functioning of patients with schizophrenia.

Psychopharmacology, 205(1), 45–52. doi: 10.1007/s00213-009-1512-9

Scholes, K. E., & Martin-Iverson, M. T. (2010). Cannabis use and neuropsychological

performance in healthy individuals and patients with schizophrenia.

Psychological Medicine, 40(10), 1635–1646. doi:10.1017/S0033291709992078

Schroots, J. J., Dijkum, C. V., & Assink, M. H. (2004). Autobiographical memory from

a life span perspective. The International Journal of Aging and Human

Development, 58(1), 69–85. doi: 10.2190/7A1A-8HCE-0FD9-7CTX

Schwartz, M. F., Reed, E. S., Montgomery, M., Palmer, C., & Mayer, N. H. (1991). The

quantitative description of action disorganisation after brain damage: A case

study. Cognitive Neuropsychology, 8(5), 381–414.

doi:10.1080/02643299108253379

Seifert, C. (1994). The role of goals in retrieving analogical cases. In K. Holyoak & J.

Barnden (Eds.), Analogy, Metaphor and Reminding (pp. 95–125). Westport, CT:

Ablex Publishing.

Semkovska, M., Stip, E., Godbout, L., Paquet, F., & Bedard, M. A. (2002). Behavioral

disorganization in schizophrenia during a daily activity: The kitchen behavioral

scoring scale. Brain Cognition, 48(2-3), 546–553. Retrieved from http://0-

www.sciencedirect.com.

http://dx.doi.org/10.1017/S0033291709992078


Sevy, S., Burdick, K. E., Visweswaraiah, H., Abdelmessih, S., Lukin, M., Yechiam, E.,

& Bechara, A. (2007). Iowa gambling task in schizophrenia: A review and new

data in patients with schizophrenia and co-occurring cannabis use disorders.


Shallice, T. (1982). Specific impairments of planning. Philosophical Transactions of the

Royal Society B: Biological Sciences, 298(1089), 199–209.

doi:10.1098/rstb.1982.0082

Shallice, T., & Burgess, P. W. (1991). Deficits in strategy application following frontal

lobe damage in man. Brain, 114(2), 727–741. doi:10.1093/brain/114.2.727

Shallice, T., Burgess, P. W., & Frith, C. D. (1991). Can the neuropsychological case-

study approach be applied to schizophrenia? Psychological Medicine, 21(3),

661–673. doi:10.1017/S0033291700022303

Shallice, T., Burgess, P., & Robertson, I. (1996). The domain of supervisory processes

and temporal organization of behaviour [and discussion]. Philosophical

Transactions of the Royal Society of London, Series B: Biological Sciences,

351(1346), 1405–1412. doi: 10.1098/rstb.1996.0124

Shallice, T., & Evans, M. E. (1978). The involvement of the frontal lobes in cognitive

estimation. Cortex, 14(2), 294–303. doi:10.1016/s0010-9452(78)80055-0

Sharma, T., & Antonova, L. (2003). Cognitive function in schizophrenia: deficits,

functional consequences, and future treatment. Psychiatric Clinics of North

America, 26(1), 25–40. doi:10.1016/S0193-953X(02)00084-9

Shurman, B., Horan, W. P., & Nuechterlein, K. H. (2005). Schizophrenia patients

demonstrate a distinctive pattern of decision-making impairment on the Iowa

gambling task. Schizophrenia Research, 72(2-3), 215–224.

doi:10.1016/j.schres.2004.03.020

http://psycnet.apa.org/doi/10.1016/S0193-953X(02)00084-9


Simon, A. E., Giacomini, V., Ferrero, F., & Mohr, S. (2003). Dysexecutive syndrome

and social adjustment in schizophrenia. Australian and New Zealand Journal of

Psychiatry, 37(3), 340–346. doi: 10.1046/j.1440-1614.2003.01186.x

Skosnik, P. D., Spatz-Glenn, L., & Park, S. (2001). Cannabis use is associated with

schizotypy and attentional disinhibition. Schizophrenia Research, 48(1), 83–92.

doi:10.1016/s0920-9964(00)00132-8

Smith, R. E., & Bayen, U. J. (2005). The effects of working memory resource

availability on prospective memory: A formal modeling approach. Experimental

Psychology, 52(4), 243–256. doi:10.1027/1618-3169.52.4.243

Solowij, N. (1995). Do cognitive impairments recover following cessation of cannabis

use? Life Science, 56(23–24), 2119–2126. doi:10.1016/0024-3205(95)00197-E

Solowij, N., & Battisti, R. (2008). The chronic effects of cannabis on memory in

humans: A review. Current Drug Abuse Reviews, 1(1), 81–98.

doi:10.2174/1874473710801010081

Solowij, N., & Michie, P. T. (2007). Cannabis and cognitive dysfunction: parallels with

endophenotypes of schizophrenia? Journal of Psychiatry and Neuroscience,

32(1), 30–52. Retrieved from


Solowij, N., Michie, P. T., & Fox, A. M. (1991). Effects of long-term cannabis use on

selective attention: an event-related potential study. Pharmacology,

Biochemistry and Behavior, 40(3), 683–688.

doi:10.1016/0091-3057(91)90382-C

Solowij, N., Michie, P. T., & Fox, A. M. (1995). Differential impairments of selective

attention due to frequency and duration of cannabis use. Biological Psychiatry,

37(10), 731–739. doi:10.1016/0006-3223(94)00178-6


http://dx.doi.org/10.1016/0091-3057(91)90382-C


Solowij, N., Stephens, R. S., Roffman, R. A., Babor, T., Kadden, R., Miller, M., ...

Vendetti, J. (2002). Cognitive functioning of long-term heavy cannabis users

seeking treatment. Journal of the American Medical Association, 287(9), 1123–

1131. doi:10.1001/jama.287.9.1123

Spreen, O., & Strauss, E., 1998. A Compendium of Neuropsychological Tests:

Administration, Norms, and Commentary (Second Edition). Oxford: Oxford

University Press, p. 171.

Stern, Y. (2009). Cognitive reserve. Neuropsychologia, 47(10), 2015–2028.

doi:10.1016/j.neuropsychologia.2009.03.004

Stevens, J. P. (1986). Applied Multivariate Statistics for the Social Sciences. New

Jersey: Lawrence Erlbaum Associates, p. 345.

Stevens, J. P. (2002). Applied Multivariate Statistics for the Social Sciences (Fourth

Edition). New Jersey: Lawrence Erlbaum Associates, p. 395.

Stirling, J., Lewis, S., Hopkins, R., & White, C. (2005). Cannabis use prior to first onset

psychosis predicts spared neurocognition at 10-year follow-up. Schizophrenia

Research, 75(1), 135–137. doi:10.1016/j.schres.2004.10.006

Stirling, J., White, C., Lewis, S., Hopkins, R., Tantam, D., Huddy, A., & Montague, L.

(2003). Neurocognitive function and outcome in first-episode schizophrenia: A

10-year follow-up of an epidemiological cohort. Schizophrenia Research, 65(2-

3), 75–86. doi:10.1016/s0920-9964(03)00014-8

Stratowski, S. M., Maurico, I., Stoll, A. L., Faedda, G., Mayer, P. V., Kolbrener, M. I.,

& Goodwin, D. C. (1993). Comorbidity in psychosis at first hospitalization.

American Journal of Psychiatry, 150(5), 752–757.

Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of

Experimental Psychology, 18(6), 643–662. doi:10.1037/h0054651

http://dx.doi.org/10.1016/j.neuropsychologia.2009.03.004



Stuss, D. T., & Alexander, M. P. (2000). Executive functions and the frontal lobes: a

conceptual view. Psychological Research, 63(3-4), 289–298.

doi:10.1007/s004269900007

Stuss, D. T., & Benson, D. F. (1986). The Frontal Lobes. New York: Raven Press.

Stuss, D. T., & Levine, B. (2002). Adult clinical neuropsychology: lessons from studies

of the frontal lobes. Annual Review of Psychology, 53(1), 401–433.

doi:10.1146/annurev.psych.53.100901.135220

Tabachnick, B. G., & Fidell, L. S. (2007). Using Multivariate Statistics (Fifth Edition).

New York: Allyn and Bacon.

Thames, A. D., Arbid, N., & Sayegh, P. (2014). Cannabis use and neurocognitive

functioning in a non-clinical sample of users. Addictive Behaviors, 39(5), 994–

999. doi: 10.1016/j.addbeh.2014.01.019

Thoma, P., Wiebel, B., & Daum, I. (2007). Response inhibition and cognitive flexibility

in schizophrenia with and without comorbid substance use disorder.


Torrey, E. F. (2002). Surviving schizophrenia: A manual for families, consumers and

providers. New York, NY: Harper Collins.

Van der Linden, M. , Beerten, A., & Pesenti, M. (1998). Age-related differences in

random generation. Brain and Cognition, 38(1), 1–16.

doi:10.1006/brcg.1997.0969

van Hooren, S. A., Valentijn, S. A., Bosma, H., Ponds, R. W., Van Boxtel, M. P.,

Levine, B., ... Jolles, J. (2007). Effect of a structured course involving Goal

Management Training in older adults: a randomised controlled trial. Patient

Education and Counseling, 65(2), 205–213. doi:10.1016/j.pec.2006.07.010

http://dx.doi.org/10.1016/j.addbeh.2014.01.019

http://dx.doi.org/10.1006/brcg.1997.0969

http://dx.doi.org/10.1016/j.pec.2006.07.010


Velligan, D. I., Mahurin, R. K., Diamond, P. L., Hazleton, B. C., Eckert, S. L., &

Miller, A. L. (1997). The functional significance of symptomatology and

cognitive function in schizophrenia. Schizophrenia Research, 25(1), 21–31.

doi:10.1016/s0920-9964(97)00010-8

Verdejo-García, A., Benbrook, A., Funderburk, F., David, P., Cadet, J. L., & Bolla, K. I.

(2007). The differential relationship between cocaine use and marijuana use on

decision-making performance over repeat testing with the Iowa Gambling Task.

Drug and Alcohol Dependence, 90(1), 2–11.

doi:10.1016/j.drugalcdep.2007.02.004

Verdejo-García, A., Fagundo, A. B., Cuenca, A., Rodriguez, J., Cuyás, E., Langohr, K.,

... de la Torre, R. (2013). COMT val158met and 5-HTTLPR genetic

polymorphisms moderate executive control in cannabis users.

Neuropsychopharmacology, 38(8), 1598–1606. doi: 10.1038/npp.2013.59

Verdoux, H., Magnin, E., & Bourgeois, M. (1995). Neuroleptic effects on

neuropsychological test performance in schizophrenia. Schizophrenia Research,

14(2), 133–139. doi:10.1016/0920-9964(94)00018-4

Voruganti, L. N., Heslegrave, R. J., & Awad, A. G. (1997). Neurocognitive correlates of

positive and negative syndromes in schizophrenia. Canadian Journal of

Psychiatry, 42(10), 1066–1071.

Wang, Y., Cui, J., Chan, R. C., Deng, Y., Shi, H., Hong, X., ... Shum, D. (2009).

Meta-analysis of prospective memory in schizophrenia: nature, extent, and

correlates. Schizophrenia Research, 114(1), 64-70.

doi: 10.1016/j.schres.2009.07.009

http://dx.doi.org/10.1016/j.drugalcdep.2007.02.004

http://dx.doi.org/10.1038/npp.2013.59



Warkentin, S., & Passant, U. (1997). Functional imaging of the frontal lobes in organic

dementia. Dementia and Geriatric Cognitive Disorders, 8(2), 105–109.

doi:10.1159/000106614

Warner, R., Taylor, D., Wright, J., Sloat, A., Springett, G., Arnold, S., & Weinberg, H.

(1994). Substance use among the mentally ill: Prevalence, reasons for use and

effects on illness. American Journal of Orthopsychiatry, 64(1), 30–39. doi:

10.1037/h0079489

Wechsler, D. (1981). Wechsler Adult Intelligence Scale - Revised. New York: The

Psychological Corporation.

Wechsler, D. (1987). Wechsler Memory Scale - Revised. San Antonio, TX: The


Wechsler, D. (1997). Wechsler Adult Intelligence Scale (Third Edition). San

Antonio, TX: The Psychological Corporation.

Wechsler, D. (1997). Wechsler Memory Scale (Third Edition). San Antonio, TX: The


Wechsler, D. (2008). Wechsler Adult Intelligence Scale (Fourth Edition). San Antonio,

TX: NCS Pearson.

Weinstein, C. S., & Shaffer, H. J. (1993). Neurocognitive aspects of substance abuse

treatment: A psychotherapist's primer. Psychotherapy: Theory, Research,

Practice, Training, 30(2), 317–333. doi:10.1037/0033-3204.30.2.317

West, R. L. (1996). An application of prefrontal cortex function theory to cognitive

aging. Psychological Bulletin, 120(2), 272–292. doi:10.1037/0033-

2909.120.2.272



Whitlow, C. T., Liguori, A., Brooke Livengood, L., Hart, S. L., Mussat-Whitlow, B. J.,

Lamborn, C. M., ... Porrino, L. J. (2004). Long-term heavy marijuana users

make costly decisions on a gambling task. Drug and Alcohol Dependence, 76(1),

107–111. doi:10.1016/j.drugalcdep.2004.04.009

Whyte, J., Polansky, M., Cavallucci, C., Fleming, M., Lhulier, J., & Coslett, H. B.

(1996). Inattentive behavior after traumatic brain injury. Journal of the

International Neuropsychological Society, 2(4), 274–281.

doi:10.1017/s1355617700001284

Wilder, K. E., Weinberger, D. R., & Goldberg, T. E. (1998). Operant conditioning and

the orbitofrontal cortex in schizophrenic patients: Unexpected evidence for

intact functioning. Schizophrenia Research, 30(2), 169–174. doi:10.1016/s0920-

9964(97)00135-7

Wilk, C. M., Gold, J. M., Humber, K., Dickerson, F., Fenton, W. S., & Buchanan, R. W.

(2004). Brief cognitive assessment in schizophrenia: normative data for the

Repeatable Battery for the Assessment of Neuropsychological Status.


Williams, L. M., Whitford, T. J., Flynn, G., Wong, W., Liddell, B. J., Silverstein, S., ...

& Gordon, E. (2008). General and social cognition in first episode

schizophrenia: identification of separable factors and prediction of functional

outcome using the IntegNeuro test battery. Schizophrenia Research, 99(1), 182–

191. doi:10.1016/j.schres.2007.10.019

Wilson, B. A., Alderman, N., Burgess, P., Emslie, H., & Evans, J. J. (1996).

Behavioural Assessment of the Dysexecutive Syndrome. Bury St. Edmunds,

Suffolk: Thames Valley Test Company.




Wilson, B. A., Evans, J. J., Emslie, H., Alderman, N., & Burgess, P. (1998). The

development of an ecologically valid test for assessing patients with a

dysexecutive syndrome. Neuropsychological Rehabilitation, 8(3), 213–228.

doi:10.1080/713755570

Wilson, B. A., Evans, J. J., Emslie, H., & Malinek, V. (1997). Evaluation of NeuroPage:

a new memory aid. Journal of Neurology, Neurosurgery & Psychiatry, 63(1),

113–115. doi:10.1136/jnnp.63.1.113

Wobrock, T., Sittinger, H., Behrendt, B., D’Amelio, R., Falkai, P., & Caspari, D.

(2007). Comorbid substance abuse and neurocognitive function in recent-onset

schizophrenia. European Archives of Psychiatry and Clinical Neuroscience,

257(4), 203–210. doi:10.1007/s00406-006-0707-x

World Health Organisation (1993). Composite International Diagnostic Interview,

Version 1.1. Geneva: WHO.

Wykes, T., Reeder, C., Landau, S., Everitt, B., Knapp, M., Patel, A., & Romeo, R.

(2007). Cognitive remediation therapy in schizophrenia: Randomised controlled

trial. The British Journal of Psychiatry, 190(5), 421–427. doi:

10.1192/bjp.bp.106.026575

Yücel, M., Bora, E., Lubman, D. I., Solowij, N., Brewer, W. J., Cotton, S. M., ...

Pantelis, C. (2010). The impact of cannabis use on cognitive functioning in

patients with schizophrenia: A meta-analysis of existing findings and new data

in a first-episode sample. Schizophrenia Bulletin, 38(2), 316–330.

doi:10.1093/schbul/sbq079


Zalla, T., Joyce, C., Szöke, A., Schürhoff, F., Pillon, B., Komano, O., ... & Leboyer, M.

(2004). Executive dysfunctions as potential markers of familial vulnerability to

bipolar disorder and schizophrenia. Psychiatry Research, 121(3), 207–217.

doi:10.1016/S0165-1781(03)00252-X

Zalla, T., Plassiart, C., Pillon, B., Grafman, J., & Sirigu, A. (2001). Action planning in a

virtual context after prefrontal cortex damage. Neuropsychologia, 39(8), 759–

770. doi:10.1016/s0028-3932(01)00019-7

Zhang, L., Abreu, B. C., Seale, G. S., Masel, B., Christiansen, C. H., & Ottenbacher, K.

J. (2003). A virtual reality environment for evaluation of a daily living skill in

brain injury rehabilitation: Reliability and validity. Archives of Physical

Medicine and Rehabilitation, 84(8), 1118–1124. doi:10.1016/s0003-

9993(03)00203-x

http://dx.doi.org/10.1016/S0165-1781(03)00252-X


Appendices

Appendix A: Structured Interview

Demographic Information

“I’d like to ask you a few questions regarding some personal information about yourself”

(1) What is your age?_____ years _____ months (DOB:___________)

(2) Gender Male Female

(3) How many years of full-time education have you completed? ______ years

What grades (on average) did you achieve? _______

(4) Have you experienced any of the following medical conditions/disabilities:

Head/Brain injury specify ______________________

Neurological conditions (e.g. epilepsy, MS) specify ______________________

Mental Illness specify ______________________

Intellectual disability/learning difficulties specify ______________________

Stroke

Cardiac Arrest

(5) Are you currently using medication? Yes No

If yes, please specify___________________________

Approximately, how long have you been taking this medication? ____________

(6) Do you use drugs/alcohol (including cigarettes)? Yes No

If yes:

Please specify and how often? ________________________(days per week)

Approximately, how much of the drug do you use per using-day __________(e.g., cones, joints)

Approximately, how long have you been using the drug ________(months/years)

When was the last time you used the drug?______________

Has your use of drugs/alcohol ever:

Had a negative effect on your interpersonal specify ______________________

relationships

Interfered with your ability to attend/persist specify ______________________

with work/school activities

Put your physical safety (e.g. while driving a specify ______________________

vehicle or operating machinery), at risk

Resulted in legal issues (e.g. arrests for specify ______________________

substance related disorderly conduct)


Appendix B(i): Advertisement for Clinical Participants – Cannabis Users

RESEARCH STUDY

Do you want to contribute to valuable new research???

This study is about schizophrenia, cannabis use and thinking processes. Your

contribution would be most appreciated.

We’re asking for adults, both male and female aged between 18 and 55 years

with a diagnosis of schizophrenia (no other mental illness diagnoses included), and who

are also regular cannabis users (but do not use any other illicit drug), to come and be a

part of this research. Participation is voluntary and confidentiality will be strictly

maintained!!!

If you agree to volunteer, you will be asked some questions about you (e.g., age,

gender, educational level, health status, symptoms, and cannabis use), as well as asked

to fill out a questionnaire about your mood. In addition you will also be asked to

complete a range of tasks involving solving puzzles, planning trips and card

games.

As a token of appreciation for your participation you will receive a $25

voucher for Coles-Myer.

The researcher Khristin Highet (Doctor of Psychology (Clinical) student), can be

contacted on the following email address for more information:

[email protected]

or on:

0415 494 551

OR

Alternatively, you can leave your contact details on the form provided at the

reception desk, in order for the researcher to contact you.

mailto:[email protected]


Appendix B(ii): Advertisement for Clinical Participants – Non-drug Users

RESEARCH STUDY





with a diagnosis of schizophrenia (no other mental illness diagnoses included), and who

do not use any illicit drug, to come and be a part of this research. Participation is

voluntary and confidentiality will be strictly maintained!!!


gender, educational level, health status, and symptoms), as well as asked to fill out a

questionnaire about your mood. In addition you will also be asked to complete a range

of tasks involving solving puzzles, planning trips and card games.





[email protected]

or on:

0415 494 551

OR

Alternatively, you can leave your contact details on the form provided at the

reception desk, in order for the researcher to contact you.



Appendix C: Clinical Participant Information Form

CENTRAL NORTHERN ADELAIDE HEALTH SERVICE

(CNAHS)

The Queen Elizabeth Hospital & Lyell McEwin Hospital

PARTICIPANT INFORMATION SHEET

Title: Relationships between schizophrenia and cannabis use on everyday adjustment

Application Number: 2009010

INVITATION TO PARTICIPATE We invite you to participate in a study which we believe is of potential importance to

people with schizophrenia. But, before you decide whether you wish to participate, we

need to be sure that you understand:

why we are doing it, and

what it would involve if you agreed.

So, please read the following carefully and be sure to ask any questions you have. I will

be happy to discuss it with you and answer your questions. You are also free to discuss

it with others if you wish (i.e., family, friends, your local Doctor and / or your clinical

treatment team).

You do not have to make an immediate decision.

PARTICIPATION IS VOLUNTARY

This is a research project and you do not have to be involved. Your medical care or

clinical treatment will not be affected in any way if you choose not to participate. Also,

if you agree to participate, you are free to change your mind and withdraw at any stage.

BACKGROUND TO THE STUDY

What is the research about?

My name is Khristin Highet. I am completing this research as part of my Doctor of

Psychology (Clinical) degree through Murdoch University in Western Australia. I’m

looking at the relationship between schizophrenia, cannabis use, thinking processes and

everyday life skills.

Who is sponsoring it, and are they paying the researcher or her department to do the

research?

I’m a post-graduate student of Murdoch University and the university is sponsoring this

study. I will not be paid for conducting this research.

Why is the research being done?

I hope that the study will help treating professionals to make better informed decisions

about treatment plans for people with schizophrenia. In addition, it may be of help when

developing treatment plans for patients who may also use cannabis.


Who can participate?

I’m inviting both male and female adults with schizophrenia, aged between 18 and 55

years, and who do NOT have a history of serious head/brain injury, mental illness

diagnoses other than schizophrenia, learning disability, chronic substance use (other than

cannabis use), stroke and/or a neurological condition, to take part in the study.

How many other people have been asked to consider participating?

Around 60 participants will be included in the study. This will include people with

schizophrenia who attend The Queen Elizabeth Hospital and the Lyell McEwin

Hospital, or any other affiliated public mental health service under CNAHS.

What is involved if I choose to participate?

If you agree to participate, a testing session will be scheduled. During this session, I will

then ask some questions about you (e.g., your age, gender, years of education, health

status, cannabis use, symptoms) and your mood. This will take about 30-45 minutes.

Afterwards, I will ask you to do some tasks looking at your reading abilities, memory,

planning, attention and everyday skills, which will take about 60-90 minutes. Most

people find these tasks enjoyable and you can have a break at any time.

With your permission, I will also ask a member of your treatment team, or your

community support worker (if applicable), to fill in a questionnaire outlining your

everyday skills. If you do not want your treatment team or support person to be

involved, this will not stop you from being involved in the study. A family member or

significant other may answer the questions related to your everyday skills.

DISCOMFORTS, RISKS AND SIDE EFFECTS

Who should I contact if I am worried about any effects that I experience?

No risks or side effects are anticipated as a result of the current research. But, if you

should experience undue emotional distress, or I observe a significant change in your

condition during the research process, you can stop the session, and I will encourage

you to contact your clinical treatment team for consultation. You can recommence the

study at a later stage if you wish to.

WHAT WILL HAPPEN TO THE INFORMATION COLLECTED?

All information you give is confidential. No names or other information that might

identify you will be used in any publication arising from the study. The information

collected from the research will be stored in locked cabinets located at Murdoch

University. Only my research supervisors and I will have access to the data.

WHAT ARE MY RIGHTS?

If you become injured during this study, and your injury is a direct result of the effects

of study procedures, The Queen Elizabeth Hospital will provide reasonable medical

treatment. Your participation in this study shall not affect any other right to

compensation you may have under common law. Should you wish to obtain more

information about your rights as a participant, you can contact the Executive Officer of

the Ethics Of Human Research committee, on (08) 8222 6841.


IS THERE ANY PAYMENT FOR PARTICIPATION?

We understand that involvement in this study requires a time commitment and we are

extremely appreciative of your participation and time given. As a token of appreciation

for your participation you will receive a $25 voucher for Coles-Myer.

BENEFITS OF THE RESEARCH

I hope that this study will assist in helping people with schizophrenia to successfully

transition out of hospital care and return to community living. However, these benefits

may not directly affect you.

WHAT IF I HAVE A QUESTION ABOUT THE STUDY?

If you have any questions or concerns about your involvement in the study, you may

contact the chief project supervisor, Dr Marjorie Collins via email:

[email protected]

The Central Northern Adelaide Health Service Ethics of Human Research Committee

(TQEH & LMH) has approved this study.

Should you wish to speak to a person not directly involved in the study in relation to

matters concerning policies,

information about the conduct of the study

your rights as a participant, or

should you wish to make a confidential complaint, you may contact The Executive

Officer of this committee, on (08) 8222 6841.

Thank you,

Khristin Highet



Appendix D: Advertisement for Control Participants

RESEARCH STUDY





who do not have any mental illness diagnosis and are regular cannabis users (but do

not use any other illicit drug), to come and be a part of this research. Participation is

voluntary and confidentiality will be strictly maintained!!!


gender, educational level, health status, and cannabis use), as well as asked to fill out a

questionnaire about your mood. In addition you will also be asked to complete a range

of tasks involving solving puzzles, planning trips and card games.





[email protected]

or on:

0415 494 551



Appendix E: Control Participant Information Form

MURDOCH UNIVERSITY

School of Psychology

PARTICIPANT INFORMATION SHEET


Permit Number: 2008/168

INVITATION TO PARTICIPATE We invite you to participate in a study which we believe is of potential importance to

people with schizophrenia. But, before you decide whether you wish to participate, we

need to be sure that you understand:

why we are doing it, and

what it would involve if you agreed.

So, please read the following carefully and be sure to ask any questions you have. We

will be happy to discuss it with you and answer your questions. You are also free to

discuss it with others if you wish (i.e., family, friends, and/or your local Doctor).

You do not have to make an immediate decision.

PARTICIPATION IS VOLUNTARY

This is a research project and you do not have to be involved. Participation is voluntary.

Also, if you agree to participate, you are free to change your mind and withdraw at any

stage.

BACKGROUND TO THE STUDY

What is the research about?

My name is Khristin Highet. I am completing this research as part of my Doctor of

Psychology (Clinical) degree through Murdoch University in Western Australia. I’m

looking at the relationship between schizophrenia, cannabis use, thinking processes and

everyday life skills.

Who is sponsoring it, and are they paying the researcher or her department to do the

research?

I’m a post-graduate student of Murdoch University and the university is sponsoring this

study. I will not be paid for conducting this research.

Why is the research being done?

I hope that the study will help treating professionals to make better informed decisions

about treatment plans for people with schizophrenia. In addition, it may be of help when

developing treatment plans for patients who may also use cannabis. Please note: The

involvement of participants without a mental illness, such as yourself, will help me

to better understand the effects of both cannabis use and schizophrenia, in

comparison to the effects of cannabis use alone (i.e., your results will be used in a

comparison group; comparing your results to those who have schizophrenia, but

also use cannabis in addition).


Who can participate?

I’m inviting both male and female current or past regular cannabis users, aged between

18 and 55 years, who do NOT have a history of serious head/brain injury, mental illness

diagnosis, learning disability, chronic substance use (other than cannabis use), stroke

and/or a neurological condition, to take part in the study.

How many other people have been asked to consider participating?

Around 60 participants will be included in the study. This will include individuals with

schizophrenia who use cannabis, as well as members of the community who do not have

a mental illness diagnosis who are either current or past cannabis users.

What is involved if I choose to participate?

If you agree to participate, I will initially ask you some questions via telephone about

you (e.g. your age, gender, years of education, health status, cannabis use) in order to

determine your eligibility for the study. This will take about 10-15 minutes. If you are

considered eligible for the study, you will be invited to a testing session where you will

be asked some questions about your mood, as well as I will ask you to complete some

tasks looking at your reading abilities, memory, planning, and attention, which will take

about 45-60 minutes. Most people find these tasks enjoyable and you can have a break at

any time.

DISCOMFORTS, RISKS AND SIDE EFFECTS

Who should I contact if I am worried about any effects that I experience?

No risks or side effects are anticipated as a result of the current research. But, if you

should experience undue emotional distress, you can stop the session, and I will

encourage you to contact your local doctor for consultation. You can recommence the

study at a later stage if you wish to.

WHAT WILL HAPPEN TO THE INFORMATION COLLECTED?

All information you give is confidential. No names or other information that might

identify you will be used in any publication arising from the study. The information

collected from the research will be stored in locked cabinets located at Murdoch

University. Only my research supervisors and I will have access to the data.

IS THERE ANY PAYMENT FOR PARTICIPATION?

We understand that involvement in this study requires a time commitment and we are

extremely appreciative of your participation and time given. As a token of appreciation

for your participation you will receive a $25 voucher for Coles-Myer.

BENEFITS OF THE RESEARCH

I hope that this study will assist in helping people with schizophrenia who may use

cannabis to successfully transition out of hospital care and return to community living.

However, these benefits may not directly affect you.

WHAT IF I HAVE A QUESTION ABOUT THE STUDY?

If you have any questions or concerns about your involvement in the study, you may

contact the chief project supervisor, Dr Marjorie Collins via email:

[email protected]



If you have any ethical concerns about the project or questions about your rights as a

participant, please contact The Murdoch University Human Research Ethics Committee

on (08) 9360 6677 or e-mail: [email protected]

Thank you,

Khristin Highet


Appendix F: Consent Form for Clinical Participants

CENTRAL NORTHERN ADELAIDE HEALTH SERVICE

(CNAHS)

The Queen Elizabeth Hospital & Lyell McEwin Hospital

CONSENT FORM

Title: Relationships between schizophrenia and cannabis use on everyday adjustment.

Researcher’s name: Khristin Highet

Supervisor’s name: Dr Marjorie Collins

Protocol Number: 2009010

I, the undersigned ..................................................................................... hereby consent

to my involvement in the research project explained above.

I have read the information sheet, and I understand the reasons for this study. The

researcher has explained the ways in which it will affect me. My questions have

been answered to my satisfaction. My consent is given voluntarily. I am also aware

that I may change my mind and stop at any time without this affecting my treatment,

either now or in the future.

I have been given the opportunity to have a family member, a friend or a member of

my clinical treating team present while the project was explained to me.

I understand that I may not directly benefit from taking part in the study.

I understand the statement on the information sheet concerning payment for taking

part in this study.

I understand that parts of the testing session will be audio-taped and that all records

and responses (including those audio-taped) will be kept in a safe and secure place

at Murdoch University where only the researcher and supervisors will have access.

I understand that all information provided is treated as confidential and will not be

released by the researcher unless required to do so by law.

I agree that research data gathered for this study may be published provided my

name or other information which might identify me is not used.

PATIENT SIGNATURE....................................................... DATE ……./……./…….

WITNESS (optional)............................................................... DATE ……./……./…….

______________________________________________________________________

I have provided information about the research to the research participant and believe

that he/she understands what is involved.

RESEARCHER........................................................................ DATE ……./……./…….


Appendix G: Consent Form for Control Participants

MURDOCH UNIVERSITY

School of Psychology

CONSENT FORM


Researcher’s name: Khristin Highet

Supervisor’s name: Dr Marjorie Collins

Permit Number: 2008/168

I, the undersigned .................................................................................. hereby consent

to my involvement in the research study explained above.

I have read the information sheet, and I understand the reasons for this study. The

researcher has explained the ways in which it will affect me. My questions have

been answered to my satisfaction. My consent is given voluntarily. I am also aware

that I may change my mind and stop at any time without this resulting in prejudice,

either now or in the future.

I understand that I may not directly benefit from taking part in the study.

I understand the statement on the information sheet concerning payment for taking

part in this study.

I understand that parts of the testing session will be audio-taped and that all records

and responses (including those audio-taped) will be kept in a safe and secure place

at Murdoch University where only the researcher and supervisors will have access.

I understand that all information provided is treated as confidential and will not be

released by the researcher unless required to do so by law.

I agree that research data gathered for this study may be published provided my

name or other information which might identify me is not used.

PARTICIPANT’S SIGNATURE.......................................... DATE ……./……./…….

______________________________________________________________________

I have provided information about the research to the research participant and believe

that he/she understands what is involved.

RESEARCHER....................................................................... DATE ……./……./…….


Appendix H: Debrief Information

ABOUT THIS STUDY

Thank you for participating in this study. Your time and efforts are much appreciated.

The aim of the research is to examine the relationship between schizophrenia, cannabis

use, and ‘executive functions’. Executive functions are a group of thinking processes

that generally involve planning, problem solving, self-monitoring, and stopping a

response that is not the best one for the task at hand. The tasks you have undertaken

today are thought to assess such processes.

Another aim of our research is to look at the relationship between these thinking

abilities and everyday skills. We hope that the results of the research project will help to

better inform treating professionals in developing more effective treatment plans for

individuals with schizophrenia who may present with cannabis abuse issues.

If any aspect of the research process has raised any concerns, we encourage you to

consult with your clinical treatment team/doctor. You may also contact the following

service for help if necessary:

Assessment & Crisis Intervention Service (ACIS) - 24 hour Emergency Mental Health

Service Ph. No: 13 14 65

Thank you once again for your contribution and participation in our project.

by khristin highet, b.psych (hons); m.psych...

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