dementia and effort test performance

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Dementia and effort test performanceAndy C. Dean Ph.D. a , Tara L. Victor b , Kyle B. Boone a , Linda M.Philpott c & Ryan A. Hess ba Harbor-UCLA Medical Center , CA, USAb California State UniversityDominguez Hills , CA, USAc Huntington HospitalPasadena , CA, USAPublished online: 10 Jun 2009.

To cite this article: Andy C. Dean Ph.D. , Tara L. Victor , Kyle B. Boone , Linda M. Philpott & Ryan A.Hess (2009) Dementia and effort test performance, The Clinical Neuropsychologist, 23:1, 133-152,DOI: 10.1080/13854040701819050

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The Clinical Neuropsychologist, 23: 133152, 2009

http://www.psypress.com/tcn

ISSN: 1385-4046 print/1744-4144 online

DOI: 10.1080/13854040701819050

DEMENTIA AND EFFORT TEST PERFORMANCE

Andy C. Dean1, Tara L. Victor2, Kyle B. Boone1,Linda M. Philpott3, and Ryan A. Hess21Harbor-UCLA Medical Center, 2California State UniversityDominguez Hills,and 3Huntington HospitalPasadena, CA, USA

Research on the performance of patients with dementia on tests of effort is particularly

limited. We examined archival data from 214 non-litigating patients with dementia on 18

effort indices derived from 12 tests (WAIS-III/WAIS-R Digit Span and Vocabulary,

Dot Counting Test, Warrington Recognition Memory Test Words, WMS-III Logical

Memory, Rey Word Recognition Memory Test, Finger Tapping, b-Test, Rey 15-Item, Test

of Memory Malingering, Rey Auditory Verbal Learning Test, and Rey Complex

Figure Test). Results indicated that recommended cut-offs for Digit Span indicators

(Vocabulary Minus Digit Span and four-digit forward span time score) provided 90%specificity across participants, while the majority of other effort tests displayed specificities

in the 3070% range. Analyses of test specificity as a function of Mini Mental Status

Examination (MMSE) score and specific dementia diagnosis are provided, as well as

adjustments to cut-offs to maintain specificity where feasible.

Keywords: Effort; Dementia; Malingering; Noncredible; Alzheimers; Geriatric.

INTRODUCTION

In some circumstances, older individuals may be motivated to feign symptoms

of dementia; for example, in evaluations for competency to stand trial in criminal

proceedings, and in personal injury cases involving toxic exposure, medical

malpractice (e.g., poor surgical outcomes), head injury, etc. However, literature

on the performance of dementia groups on tests of effort is particularly scant.

Patients with dementia are often excluded from effort test validation samples,

and even replication validity studies with mixed clinical samples typically include

few to no dementia participants. For effort test interpretation to be meaningful

with a potentially demented patient, data are needed regarding which effort tests

provide the lowest rate of false positive error, the relationship between severity

of dementia and false positive rates, and the extent to which effort cut-offs need to

be adjusted in dementia groups. Further, information regarding the typical

performance of dementia patients on effort tests is crucial: Should a patient with

a much less severe condition (e.g., mild head injury) perform similarly to patients

Address correspondence to: Andy C. Dean, Ph.D., Harbor-UCLA Medical Center,

Neuropsychology Dept., 1000 W, Carson Street, Box 495, Torrance, CA 90509, USA

E-mail: [email protected]

Accepted for publication: November 12, 2007. First published online: April 8, 2008.

2008 Psychology Press, an imprint of the Taylor & Francis group, an Informa business

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with dementia on tests of effort, this could provide compelling evidence that his orher effort is noncredible.

REVIEW OF DEMENTIA/EFFORT TEST LITERATURE

Studies evaluating the performance of samples or subsamples ofdementia patients on tests of effort are displayed in Table 1. In the majorityof these studies, known external incentives to feign dysfunction (e.g., in litigation)appeared unlikely, or were specifically ruled out, as part of sample selection.The specificity of the effort tests (i.e., the percentage of dementiapatients appropriately passing the effort test) was calculated when possible fromarticle data.

Of all the free-standing effort measures examined, the Test of MemoryMalingering (TOMM; Tombaugh, 1996) has received the most attention.Across studies, the specificity of the TOMM in dementia samples has rangedfrom a high of 82% (Trial 2, Greve et al., 2006) to a low of 24% (Trial 2, Teichner& Wagner, 2004). The Digit Memory Test has shown similar variability: whileDArcy and McGlone (2000) found no false positives for a small sample of amnesticpatients on a short form of the Digit Memory Test (Hiscock & Hiscock, 1989), astudy by Prigatano and colleagues (Prigatano, Smason, Lamb, & Bortz, 1997)evidenced numerous false positives with the long form, with the meanperformance of dementia participants falling below index cut-offs. Other forced-choice measures have also produced high rates of false positive error. The VictoriaSymptom Validity Test (VSVT; Slick, Hopp, & Strauss, 1997) was found to have afalse positive rate of 38% in a sample of non-vascular dementia (Loring, Larrabee,Lee, & Meador, 2007). Of concern, indices of the Word Memory Test(WMT; Green, Allen, & Astner, 1996) demonstrated false positive rates of9095% (Merten, Bossink, & Schmand, 2007) in a probable Alzheimersdementia sample, and the similarly constructed forced-choice indices of theMedical Symptom Validity Test (MSVT; Green, 2004) demonstrated specificitiesof 1761% in a mixed dementia group (Howe, Anderson, Kaufman, Sachs,& Loring, 2007). However, Green (2007) and others (Howe et al., 2007) haveprovided an algorithm to discriminate dementia patients from noncrediblepatients based on profile analysis including the more difficult WMT and MSVTsubtests (e.g., Free Recall). In the Howe et al. MSVT study this algorithm produceda specificity of 9289%, in early and advanced dementia, respectively.

Free-standing measures that do not use the forced-choice paradigmhave also produced problematic specificities. Using recommended cut-offs forthe Dot Counting Test (DCT; Boone, Lu, & Herzberg, 2002c), Boone et al. (2002a)found false positive rates of 25% and 67% for mildly and moderatelydemented patients, respectively. However, these authors also reported specificityrates associated with alternate cut-off scores in the dementia subgroup,which can allow the clinician to select cut-offs to maintain adequate specificity(i.e., 90%), although with some mild sacrifice in test sensitivity (i.e., from 78.8%to 62.4%). Lastly, the Rey 15-Item test (Rey, 1964, in Lezak, 1983)has been reported to have unacceptable specificity in individuals with dementiausing a cut-off of 59 (Schretlen, Brandt, Krafft, & Van Gorp, 1991), although

134 ANDY C. DEAN ET AL.

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Table1

Studiesofeffortmeasure

perform

ance

anddem

entia

Measure/Study

Cut-off

NMMSErange

Samplecomposition

Incentive

tofeign?a

Specificityb

TOMM

Tombaugh

(1997)

Trial2and

Reten.545

40

Unknown

Amixed

DSM-diagnosed

sample

ofdem

entia

Unlikely

Trial273%

Reten.

82%

Teichner

&

Wagner(2004)

Trial2and

Reten.545

21

1128

Mean19.9

SD5.0

Amixed

dem

entiasample

diagnosedwithDSM,ADRA-

NIN

DS,orADDTCischem

ic

vasculardem

entiacriteria

Unlikely

Trial224%

Reten.

29%

Greveetal.

(2006)

Trial2

andReten.545

22

Unknown

Mem

ory

disorderpatients

suspected

ofhaving

Alzheimers

disease,vasculardem

entia,orboth

No

Trial282%

Reten.

77%

Mertenetal.

(2007)

Trial2and

Reten.545

20

18Mean22.2

SD2.9

ProbableAlzheimersdem

entia

basedonNIN

CDS-ADRAcriteria

Unlikely

Trial270%

Reten.

50%

DigitSpanACSS

Iverson&Tulsky

(2003)

56

38

1823

Patients

with

Alzheimers

disease

fromtheWAIS-IIIstandardization

sample

Unlikely

95%

Heinlyetal.

(2005)

56

228

Unknown

Anundefined

sampleofmem

ory

disorderpatients

No

90%

Babikianetal.

(2006)

56

8Unknown

Amixed

dem

entiasample

No

1falsepositive

(continued)

DEMENTIA AND EFFORT TEST PERFORMANCE 135

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Table1

Continued

Measure/Study

Cut-off

NMMSErange

Samplecomposition

Incentive

tofeign?a

Specificityb

ReliableDigitSpan

Heinlyetal.

(2005)

57

228

Unknown

Anundefined

sampleof

mem

ory

disorderpatients

No

68%

Babikianetal.

(2006)

57

8Unknown

Amixed

dem

entiasample

No

1falsepositive

Mertenetal.

(2007)

58

20

18

Mean22.2

SD2.9

ProbableAlzheimers

dem

entia

basedonNIN

CDS-ADRA

criteria

Unlikely

30%

Vocabulary

-DigitSpanACSS

Iverson&Tulsky

(2003)

45

38

1823

PatientswithprobableAlzheimers

disease

from

theWAIS-III

standardizationsample

Unlikely

97%

DigitMem

ory

Test

Prigatanoetal.

(1997)

595%

on

trials13

9Unknown

Patients

meetingADRDA

criteria

forprobableAlzheimersdisease

Unlikely

Low,meanperform

ance

belowcut-offs

DArcy&

McG

lone

(2000)

36-item

version

595%

14

Unknown

Patients

withchronic

amnesia,at

least

four

of

which

likely

met

criteriafordem

entia

No

100%


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VictoriaSymptom

ValidityTest

Loringetal.

(2007)

521Hard

item

s

50

Unknown

Amixed

dem

entiasample,without

clearcasesofvasculardem

entia

Unlikely

62%

Slick

etal.

(2003)

521Hard

item

s

6Unknown

Malepatientswithprofound

mem

ory

impairment

No

Nofalsepositives

Word

Mem

ory

Test

Green (2007)

82.5%

on

IR,DR,or

Consis.

25

Unknown

Undefined

earlydem

entia

patients

Unlikely

Meanperform

ance

nearor

belowcut-offs

Mertenetal.

(2007)

534onIR

,

DR,orConsis.

20

18

Mean22.2

SD2.9


entia

basedonNIN

CDS-ADRAcriteria

Unlikely

IR10%

DR10%

Consis.5%

MedicalSymptom

ValidityTest

Richmanetal.

(2006)

IRandDR

585%

GermanOral

Version

62

Unknown

An

unspecified

German

sample

withearlydem

entia(N48)and

advanceddem

entia(N14)

Unlikely

Unknown,meansabovecut-offs

forearlydem

entia,belowcut-offs

foradvanceddem

entia

Howeetal.

(2007)

IR,DRand

CNS585%

31

Unknown

Early

dem

entia

patients

(N13)

withLogicalMem

ory

(WMS-III)

scaledscores5.

Advanceddem

entiapatients

(N18)withLogicalMem

ory

scores5

5.

No

Earlydem

entia61%

Advanceddem

entia17%

Howeetal.

(2007)

Profilealgorithm

31

Unknown

Early

dem

entia

patients

(N13)

withLogicalMem

ory

(WMS-III)

scaledscores5.

Advanceddem

entiapatients

(N18)withLogicalMem

ory

scores5

5.

No

Earlydem

entia92%

Advanceddem

entia89% (continued)


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Table1

Continued

Measure/

Study

Cut-off

NMMSErange

Samplecomposition

Incentive

tofeign?a

Specificityb

WarringtonRecognitionMem

ory

Test

Diesfeldt

(1990)

534on

Wordsor

Faces

44

Unknown

PatientsmeetingNIN

CDS-

ADRDAcriteriaforprobable

Alzheimersdisease

ofmoderate

severity

Unlikely

16%

MeanWords33.8

MeanFaces27.8

Graham,

Becker,

&Hodges

(1997)

533Words

5Unknown

Twopatientswithearly

Alzheimersdisease

andthreewith

semanticdem

entia

Unlikely

3falsepositives

Rey

15-item

Test

Schretlen

etal.

(1991)

59

9Mean25.8

SD5.2

Amixed

dem

entiasample

Unknown

Unknown,obtained

ameanof

approximately9item

s

DArcy&

McG

lone

(2000)

57

14

Unknown

Patients

withchronic

amnesia,at

least

four

of

which

likely

met

criteriafordem

entia

No

86%

DotCounting

Booneetal.

(2002a)

17comb.

score

37

10

Inpatients

and

outpatients

with

DSM-diagnosedprobable

Alzheimersdem

entiaofmildand

moderateseverity

Unlikely

Milddem

entia75%

Mod.dem

entia33%

Finger

Tapping

Arnold

etal.

(2005)

Dominant

Hand

35men

28women

31

Unknown

Amixed

DSM-diagnosedsample

ofdem

entia

No

Men

87%

Women

75%


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TrialsBto

TrialsARatio

Mertenetal.

(2007)

51.50

20

18Mean22.2

SD2.9


entia

basedonNIN

CDS-ADRAcriteria

Unlikely

95%

WMS-R

GeneralMem

ory

Attention/C

oncentrationDifference

Score

Hilsabeck

etal.

(2003)

25

19

Unknown

PatientswithAlzheimersdem

entia

No

95%

Mittenberg

etal.

(1993)

WMS-R

DiscriminantFunction

Hilsabeck

etal.

(2003)

41.39

19

Unknown

PatientswithAlzheimersdem

entia

No

74%

SimulationIndex

Revised

Milanovich&

Axelrod

(1995)

328

Unknown

Patientswithvasculardem

entia

Unlikely

32%

Amsterdam

Short-Term

Mem

ory

Test

Mertenetal.

(2007)

585

20

18

Mean22.2

SD2.9


entia

basedonNIN

CDS-ADRAcriteria

Unlikely

10%

TOMMTestofMem

ory

Malingering;ACSSAgeCorrectedScaledScore;WMS-RWechsler

Mem

ory

ScaleRevised;aIncentiveto

feignwasestimatedas

accuratelyaspossiblebasedonavailablearticledata;bSpecificitywasoften

derived

bythecurrentauthorsfrom

availablearticledata.


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a second study observed nearly acceptable specificity values (i.e., 86%) when thecut-off was adjusted to six or fewer items (DArcy & McGlone, 2000).

Of the available literature on embedded effort measures (using indicesderived from traditional neuropsychological tests) in dementia, the Digit Span Age-Corrected Scaled Score (ACSS) has been found to be most robust against falsepositive identifications. Using a cut-off of less than 6, both Iverson and Tulsky(2003) and Heinly and colleagues (Heinly, Greve, Bianchini, Love, & Brennan,2005) observed specificity in dementia or memory disordered samples of 90%or greater. In contrast, the specificity for Reliable Digit Span was found to bemuch lower (3068%, Merten et al., 2007; see also Heinly et al., 2005), possiblyreflective of the fact that Reliable Digit Span is not adjusted forage. Other embedded indices that have provided promising specificities in dementiaare Vocabulary Minus Digit Span (97%, Iverson & Tulsky, 2003), Trails B to TrailsA Ratio (95%, Merten et al., 2007), and the WMS-R Memory Attention/Concentration Difference Score (95%, Hilsabeck et al., 2003). Recommended cut-offs for dominant-hand finger tapping have been associated withsuboptimal specificities in dementia (7587%, Arnold et al., 2005), but theprovision of performance data on specific diagnostic subgroups (includingdementia) allows for selection of alternative cut-offs to increase specificityin dementia groups.

Embedded measures with unacceptable false positives rates in dementiainclude the Mittenberg, Azrin, Millsaps, and Heilbronner (1993) WMS-R Discriminant Function (specificity 74%, Hilsabeck et al., 2003) and theWAIS-R/WMS Simulation Index Revised (specificity 32%, Milanovich &Axelrod, 1995). The specificity of the Warrington Recognition Memory Test (RMT;Warrington, 1984) was noted to be particularly low in an Alzheimersdementia sample (16%, Diesfeldt, 1990), although this was calculatedfrom performance on both the Words and Faces subtests, leaving unansweredthe question as to how the subtests operate independently.

In summary, relatively few effort indices have been adequatelyresearched in dementia samples, and of those that have, false positive rateshave been unacceptable perhaps with the exception of indicators involving DigitSpan, the Medical Symptom Validity Test (profile analysis), and Trailmaking.To further investigate the performance of multiple effort tests in dementia,we examined a large archival sample of mixed dementia patients on 18 effort indicesderived from 12 tests (WAIS-III/WAIS-R Digit Span and Vocabulary,Dot Counting, Warrington Recognition Memory Test Words, WMS-IIILogical Memory, Rey Word Recognition Memory Test, Finger Tapping,b-Test, Rey 15-Item, TOMM, Rey Auditory Verbal Learning Test [RAVLT], andRey Complex Figure Test), the results of which are presented below.

METHOD

Participants

Archival neuropsychological data were obtained from a total of 214patients with dementia. Potential participants were excluded from the original


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pool if there was indication of identifiable motive to feign (i.e., if they were applyingfor disability compensation or in litigation at time of testing). As an additionalcheck on patient credibility, the following forced-choice measures were analyzed forthe possibility of significantly below chance levels of responding: WMS-III LogicalMemory Recognition, WMS-III Visual Reproduction Recognition, WarringtonRecognition Memory Test Words, Warrington Recognition Memory Test Faces, TOMM Trial 1, and TOMM Trial 2 (TOMM Retention was notadministered). The lowest forced-choice scores were an 11/30 (Logical MemoryRecognition) obtained by a patient with dementia NOS and schizophrenia, and a20/50 (Warrington Recognition Memory Test Words) obtained by a patient withprobable Alzheimers dementia and schizophrenia. Because both of these scoreshave a 10% chance of occurring in random responding (see Frederick & Speed,2007, for computing forced-choice probabilities), these patients were not excludedfrom the sample. Further, none of the participants retained in the study weredetermined to be malingering or otherwise noncredible from a clinical standpoint,and any observed neuropsychological impairments were entirely consistent withbehavioral observations and information regarding how patients functioned inactivities of daily living.

Patient data were obtained from two settings: Sample # 1 (N 172) was drawnfrom a large municipal county hospital tertiary care neuropsychology servicelocated within a department of psychiatry, and sample # 2 (N 42) consisted ofdementia patients in a residential placement.

Most diagnoses were ascertained clinically using DSM-III-R (AmericanPsychiatric Association, 1987) or IV-TR (American Psychiatric Association, 2000)criteria. However, in contrast to DSM criteria, significant memory impairmentwas not required in the clinical diagnosis of frontotemporal dementia, given that thetypical early symptoms of the disorder involve behavioral/social disturbance(memory impairment was often present, but did not need to be for diagnosticinclusion). Instead, other non-memory DSM criteria for dementia were followed inmaking a frontotemporal diagnosis (e.g., disturbance in executive functioningand significant impairment in social or occupational functioning), and FTDparticipants met Lund-Manchester criteria (Brun et al., 1994). Patients suspected ofdelirium and patients with isolated memory disorders without other concomitantcognitive dysfunction (i.e., amnestic patients not meeting criteria for dementia)were excluded.

Patients from Sample # 1 were diagnosed with various types of dementia;patients in Sample # 2 were all diagnosed with probable Alzheimers dementia,and did not have a severe psychiatric disturbance, current alcohol/substance abuseproblems, or any other medical disturbance that could impair central nervoussystem function.1 In the combined sample, the frequencies of dementia diagnoseswere as follows: probable Alzheimers dementia (34%, N 73), dementia NOS(23%, N 49; including dementia due to multiple etiologies and probable mixed

1Data from Clinic # 2 was collected for L. Philpotts (1993) doctoral dissertation. The Dot Counting data

was subsequently published by Boone et al. (2002a) and comprises approximately 41% of the Dot

Counting data currently described. The Rey 15-Item data have not been published outside of the

dissertation manuscript.


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dementiaAlzheimers and Vascular dementia), probable frontotemporaldementia2 (17%, N 36), vascular dementia (12%, N 26), dementia due to headtrauma (5%, N 10; including closed and penetrating injuries), dementiaNOS with psychosis/schizophrenia (5%, N 10), dementia due to substanceabuse or Korsakoffs disease (2%, N 4), probable Lewy body dementia(1%, N 3), dementia due to AIDS (1%, N 2), and finally, dementia due tolupus (51%, N 1).

Age of the total sample ranged from 23 to 97, with a mean of 63.5 years(SD 15.1). Mean education was 13.1 years (SD 2.9), and 49% were female.Approximately 58% of the sample were Caucasian, while 18% were AfricanAmerican, 9% were Hispanic, 5% were Asian, 51% were Middle Eastern,and 10% were unknown/other. All patients were fluent in English; a minority of thesample (11%) learned English concurrent with another language or spoke Englishas a second language. Of those who spoke English as a second language, the meanage of learning English was 12.0 years old (SD 6.9). ESL/bilingualism was equallydistributed across the range of MMSE (2 5.11; p 0.28).

Available MMSE scores (N 125) ranged from 1 to 29, with a meanof 18.5 (SD 6.0). In the 121 participants administered enough subtests on theWAIS-III or WAIS-R to provide a Full Scale IQ (i.e., at least five Verbaland four Performance), mean FSIQ was 77.2 (SD 14.3). Excluding patientswith frontotemporal dementia, the mean delayed recall on WMS-R or WMS-IIIsubtests fell at approximately the third%tile (including frontotemporal dementiaM 4%tile). Excluding frontotemporal patients, the mean number of words ondelayed free recall of the RAVLT was less than one word (M 0.90, SD 1.5;N 67).

Procedure/Measures

Approval to utilize archival neuropsychological data was obtained fromboth institutional review boards. MMSE and effort indicators were typicallyadministered in the context of more comprehensive neuropsychological assessments(i.e., covering multiple domains including language, visuospatial functioning,memory, executive functioning, and motor function). The effort indices examined(citations for cut-offs reproduced in Table 2) were: Digit Span Age-CorrectedScaled Score (ACSS; Babikian, Boone, Lu, & Arnold, 2006); Reliable Digit Span(Babikian et al., 2006); Timed Digit Span (3- and 4- digits forward; Babikian et al.,2006); Vocabulary Minus Digit Span (Iverson & Tulsky, 2003; Mittenberg, Fichera,Zielinksi, & Heilbronner, 1995; Mittenberg et al., 2001); Dot Counting TestE-score (Boone et al., 2002c); TOMM Trial 2 (Tombaugh, 1996); WarringtonRecognition Memory Test Words (Iverson & Franzen, 1994); Rey 15-Item Test(free recall, Lezak, 1983, p. 619; Recognition Equation, Boone, Salazar, Lu,Warner-Chacon, & Razani, 2002d); WMS-III Logical Memory RarelyMissed Index (RMI; Killgore & DellaPietra, 2000); Finger Tapping dominant

2Approximately 60% of the current frontotemporal participants were previously used in studies by

Boone et al. (1999) and Razani, Boone, Miller, Lee, and Sherman (2001). See these articles for further

neuroimaging data and criteria for assignment to right/left cases of frontotemporal dysfunction.


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hand (Arnold et al., 2005); b-Test E-score (Boone et al., 2002b); Rey Word

Recognition Test (Nitch, Boone, Wen, Arnold, & Alfano, 2006); Rey AuditoryVerbal Learning Test (RAVLT) Effort Equation (Boone, Lu, & Wen, 2005); Rey-Osterreith (Rey-O) Effort Equation (Lu, Boone, Cozolino, & Mitchell, 2003); andthe Rey-Osterreith/RAVLT (Rey-O/RAVLT) discriminant function (Sherman,Boone, Lu, & Razani, 2002).

It is important to note that, given the clinical setting of the assessments, notall tests were administered to all participants. Patients in Sample # 2 only were giventhe MMSE, Rey 15-Item Test (free recall), and the Dot Counting Test. A total

of 80% (N 172) of patients completed some subtests from the WAIS, and of those,54% (N 93) were administered the WAIS-R and 46% (N 79) were given theWAIS-III. Because the WAIS-R only provides normative data up to age 74, theMayo Older Americans Normative Studies (MOANS) norms (Ivnik et al., 1992)were used for WAIS-R scores of patients 75 years and older. No patientadministered the WAIS-III exceeded the WAIS-III manuals normative age range.

Of patients evaluated with the WAIS-R, 69% (N 64) were administered theSatz-Mogel short form. (The Satz-Mogel short form does not alter administrationof Digit Span, but only every third item is administered on Vocabulary.) Thus, for

Table 2 Effort test specificity in patients with dementia

Effort test Cut-off Sample Size Mean MMSEa Specificity

Digit span ACSS 5 N 172 20.2 (4.6) 73%Reliable digits 6 N 172 20.2 (4.6) 70%Three digits timed 42.0 s N 50 20.0 (4.3) 82%Four digits timed 44.0 s N 48 20.3 (4.2) 90%Vocabulary digit span 45 N 149 20.4 (4.4) 97%Dot counting escore 517 N 80 18.8 (5.0) 50%TOMM Trial 25 45 N 20 19.2 (4.4) 45%Warrington words 533 N 39 20.7 (4.2) 59%Rey 15-Item free recall 59 N 105 17.5 (6.6) 26%Rey 15-Item recognition

equation

520 N 50 20.5 (4.2) 14%

Logical memory RMI 136 N 43 20.5 (4.0) 77%Fingertapping Men 35

Women 28N 55 20.6 (3.5) 69%

b-Test 160 N 34 20.2 (4.0) 47%Rey word recognition Men 5

Women 7N 32 20.5 (4.2) 78%

Rey word recognition

equation

9 N 32 20.5 (4.2) 56%

RAVLT equation 12 N 64 20.9 (4.6) 13%Rey-O equation 47 N 51 20.7 (4.3) 37%Rey-O/RAVLT equation 0.40 N 56 22.0 (3.9) 48%

ACSSAge corrected scaled score; TOMMTest of Memory Malingering; RMIRarely MissedIndex; RAVLTRey Auditory Verbal Learning Test; Rey-ORey-Osterreith Complex Figure Test;aBecause not all patients received the MMSE, mean MMSE scores only represent sample estimates based

on available data.


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the calculation of the Vocabulary minus Digit Span effort index, 42% (N 64) werecalculated with regular administration WAIS-III data, 16% (N 24) with regularadministration WAIS-R data, and 42% (N 64) with WAIS-R data using theSatz-Mogel procedure for the calculation of Vocabulary.

Of patients given subtests from the Weschler Memory Scale (WMS; N 140),57% were administered the WMS-R and 43% were administered the WMS-III.Only the WMS-III allows calculation of the Logical Memory Rarely Missed Index.Lastly, because patients with dementia often took excessive time in the completionof the b-Test, 44% (N 15) of the b-Test data are based on prorated scores(i.e., testing was discontinued early and with scores extrapolated from existing data).Of those that were prorated, the mean number of stimulus pages completed was 5.0pages (SD 3.9).

RESULTS

Table 2 provides the specificity of the various effort indictors per publishedcut-offs. Mean MMSE scores and standard deviations are provided to illustrate thetypical level of severity of dementia in the subsample completing each test; however,because not all patients completed the MMSE, mean scores should be interpreted asestimates only. Examination of the table reveals that the majority of effort indiceshad unacceptable false positive rates in dementia patients, with particularly poorspecificity values observed for Rey 15-item plus recognition and the RAVLT effortequation (i.e., 520%), but with substantially higher specificity rates (i.e.,475%)observed for Digit Span 3-digit time (82%), Digit Span 4-digit time (90%),Vocabulary minus Digit Span (97%), Logical Memory RMI (77%), and Rey WordRecognition (78%).

In order to investigate the effect of dementia severity on effort test specificity,we divided MMSE scores into three bands of severity: mild (MMSE 420),mild to moderate (MMSE 1520), and moderate to severe (MMSE 515).We then calculated the percentage of effort tests failed by each participant(e.g., if administered three effort tests and the patient failed cut-offs on one, he/shewas considered to fail 33% of the tests administered). Out of the possible effortmeasures listed in Table 2, the following five measures were excluded from thiscalculation because they were highly similar and/or overlapped with other indices(shown in parentheses): Reliable Digit Span (ACSS), Digit Span 3-digit time (4-digittime), Rey 15-Item plus recognition (Rey 15-item), Rey Word RecognitionEquation (Rey Word Recognition total), and the Rey-O/RAVLT discriminantfunction (RAVLT equation). Examination of the remaining 13 indicators revealedthat patients with MMSE scores420 failed an average of 36% of the measuresadministered to them (N 58; mean number of tests administered 4.7; SD 3.7),those with MMSE 1520 failed an average of 47% (N 40; mean testsadministered 4.3; SD 3.1), and those with MMSE 515 failed an average of83% (N 27; mean tests administered 2.6; SD 2.5).

For further examination of specificity by dementia severity, Table 3 providesthe specificity of each effort indicator by MMSE band. Although small sample sizespoint to the need for caution in interpretation, it can be seen that only Four DigitsTime and Vocabulary Minus Digit Span had acceptable specificity in mild dementia


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(MMSE 2130), while only the Vocabulary Minus Digit Span maintainedacceptable specificity with MMSE scores of 20 or less.

In order to consider the possible influence of specific dementia diagnosison effort test performance, as shown in Table 4, we also calculated the specificityof each test by the following diagnoses: probable Alzheimers dementia, probablevascular dementia, and probable frontotemporal dementia. However,it should be noted that these diagnostic groups were not equivalent on a numberof relevant dimensions, with the exception of gender (2 4.03; p .13),although some of the differences are in fact expected for disease characteristics(i.e., age, MMSE scores). The Alzheimers patients (M 72.5; SD 11.4) weresignificantly older than both the FTD patients (M 62.4; SD 9.5; p5 .001) andthe vascular patients (M 62.1; SD 12.9; p5 .001). The FTD patients (M 15.0;SD 2.9) had more years of education than both the Alzheimers patients(M 13.2; SD 2.8; p .01) and the vascular patients (M 11.4; SD 3.4;p5 .001), and the Alzheimers patients in turn had more education thanvascular patients (p .03). However, the Alzheimers patients (M 16.3;SD 7.0) had significantly lower MMSE scores than the FTD patients (M 20.9;SD 5.5; p .05), while other MMSE group comparisons did not differ (p4.05).Data are reproduced in the table only for those tests in which sample size was 10in at least one diagnostic category. Given the overall small ns, the data containedin Table 4 should be viewed as preliminary.

Lastly, using the total dementia sample (irrespective of dementia severityand diagnosis), cut-offs were adjusted to achieve 90% specificity: Digit Span

Table 3 Effort test specificity by Mini Mental Status Examination (MMSE) band

Effort test

MMSE 2130

(Mean 23.5, SD 2.1)

MMSE 1520

(Mean 17.6, SD 1.8)

MMSE5 15(Mean 9.4, SD 4.1)

Digit span ACSS N 44 84% N 30 67% N 9 33%Reliable Digits N 44 86% N 30 60% N 9 22%Three digits Timed N 15 73% N 14 86% N 2 100%Four digits Timed N 16 94% N 12 83% N 2 100%Vocabulary Digit span N 35 94% N 21 100% N 7 100%Dot Counting N 26 77% N 18 44% N 13 8%TOMM N 8 63% N 9 33% N 2 0%Warrington words N 15 73% N 5 20% N 3 0%Rey 15-Item free recall N 33 33% N 19 5% N 23 0%Rey 15-Item Recognition equation N 14 21% N 8 0% N 3 0%Logical Memory RMI N 17 82% N 10 50% N 2 100%Finger tapping N 20 70% N 12 83% N 2 100%b-Test N 10 50% N 8 38% N 2 0%Rey word recognition N 11 64% N 6 83% N 2 50%Rey word recognition equation N 11 46% N 6 50% N 2 50%RAVLT equation N 20 15% N 9 0% N 3 0%Rey-O equation N 16 44% N 13 15% N 1 0%Rey-O/RAVLT equation N 18 44% N 7 29% N 1 0%

ACSS Age corrected scaled score; TOMMTest of Memory Malingering; RMIRarely MissedIndex; RAVLTRey Auditory Verbal Learning Test; Rey-ORey-Osterreith Complex Figure Test.


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Age-Corrected Scaled Score 53 (95% specificity); Reliable Digit Span 54 (95%),3 Digits Timed 43 seconds (98%), 4 Digits Timed 44 seconds (90%; 45seconds 94%), Vocabulary Minus Digit Span43 (93%), Dot Counting escore442 (90%), TOMM Trial 25 28 (95%), Warrington Recognition Memory Test Words 526 (90%), Rey 15-Item free recall (51 still associated with 81%specificity), Rey 15-Item with Recognition Equation 53 (90%), Logical MemoryRarely Missed Index5104 (91%), Finger Tapping dominant hand521 taps (91%,genderless), b-Test escore43000 (91%), Rey Word Recognition Test 55 (91%;genderless), Rey Word Recognition Test Equation 57 (91%; genderless), RAVLTEquation 5 2 (95%), Rey-Osterreith Equation 516 (92%), and theRey-Osterreith/RAVLT discriminant function 5 2.62 (91%).

DISCUSSION

In a large heterogeneous sample of patients with dementia, the majorityof effort tests examined displayed unacceptably high false positive rates of error.This occurred despite the fact that the patients did not have an external incentive tofeign deficits and any observed neuropsychological impairments were consistentwith behavioral observations and activities of daily living (i.e., there was no clinicalsuspicion of poor effort). In particular, specificities for the total sample rangedfrom a high of 97% (Vocabulary minus Digit Span) to a low of 13% (RAVLT effort

Table 4 Effort test specificity by probable dementia diagnosis

Effort test Alzheimers Vascular Frontotemporal

Digit span ACSS N 31 74% N 26 73% N 36 75%Reliable digits N 31 74% N 26 58% N 36 75%Three digits timed N 7 100% N 12 100% N 3 33%Four digits timed N 7 100% N 10 100% N 3 67%Vocabulary digit span N 26 92% N 21 100% N 35 91%Dot counting N 39 54% N 11 27% N 4 50%TOMM

Warrington words

Rey 15-Item free recall N 47 6% N 15 27% N 4 25%Rey 15-Item recognition

equation

N 5 20% N 14 7% N 3 33%

Logical memory RMI

Finger tapping N 7 100% N 14 43% N 2 100%b-Test



equation

RAVLT equation N 8 0% N 13 15% N 4 25%Rey-O equation N 6 50% N 13 23% N 3 33%Rey-O/RAVLT

equation

N 6 33% N 10 50% N 4 25%

ACSSAge corrected scaled score; TOMMTest of Memory Malingering; RMIRarely MissedIndex; RAVLTRey Auditory Verbal Learning Test; Rey-ORey-Osterreith Complex Figure Test.


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equation), with most effort test specificities falling in the range of 30% to 70%.

Out of the 18 different effort measures examined, only published cut-offs

for Vocabulary minus Digit Span and Four Digits Forward Timed achieved

specificities 90%. In contrast, several other effort tests were prone tomisclassify half or more of the patients examined, including the RAVLT effort

equation (13% specificity), Rey 15-Item Test (1426%), Rey-Osterreith Effort

Equation (37%), TOMM Trial 2 (45%), and the Rey-Osterreith/RAVLT

Discriminant Function (48%). This suggests that, using traditional cut-offs,

commonly used effort indices are generally unacceptable in assessing effort in

potentially demented samples.When effort test specificity was examined according to stage of dementia

severity, unacceptable false positive rates continued to be the norm. Even in cases

where severity of dementia was relatively mild (MMSE 420), only Vocabularyminus Digit Span and Four Digits Forward Timed provided adequate levels

of specificity (i.e., greater than 90%). Furthermore, as MMSE scores dropped, most

test specificities likewise fell. In fact, some measures correctly classified none of

the patients within more severe MMSE bands (Rey 15-Item Test, TOMM, b-Test,

RAVLT equation, Rey-Osterreith equation, Rey-Osterreith/RAVLT equation),

although these data should be interpreted with caution given exceedingly

small sample sizes. Only the Vocabulary minus Digit Span index maintained

greater than 90% specificity across MMSE bands, although Four Digits Forward

Timed also performed reasonably well (specificity dropping to 83% in only the

mild to moderate range of dementia). When the percentage of non-redundant effort

tests failed by each patient was analyzed by MMSE band, we found that

those with MMSE scores420 failed an average of 36% of the tests administeredto them, those with MMSE 1520 failed an average of 47%, and patients

with MMSE scores 515 failed 83% of administered effort tests. This clearlyillustrates that lower MMSE scores are associated with increased effort test failure.

In actual practice, dementia patients with low MMSE scores are not likely to be

misidentified as noncredible due to their obvious limitations on behavioral

parameters (i.e., they require residential placement for 24-hour supervision,

they cannot manage IADLs, etc.). In contrast, the group with MMSE420 is ofparticular interest in that the question of actual versus feigned dementia is most

likely to occur in this subset. We realize that a MMSE band of 21 to 30 encompasses

a fairly wide range of function, but due to small sample size we could not

further subdivide this group. Future research should explore effort test performance

as a function of MMSE scores420.When effort test cut-offs were adjusted to provide 90% specificity in

our sample, it became apparent that several of the effort measures are

likely inappropriate for use in a demented population. The significant adjustment

to cut-offs required by several measures would likely make them too insensitive,

including the Digit Span Age-Corrected Scaled Score, Reliable Digits, Rey-

Osterreith Effort Equation, Rey-Osterreith/RAVLT Effort Equation, b-Test,

Rey 15-Item measures, Dot Counting, and the RAVLT Effort Equation. For

example, lowering the cut-off for the free recall portion of the Rey 15-Item test to

less than one item still resulted in a specificity of only 81%! Clearly, lowering


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cut-offs in this manner would sacrifice sensitivity (the ability to detect noncredibleperformance) to such an extent as to be useless.

In contrast, a few of the measures did provide some promise for use indemented groups. The Vocabulary minus Digit Span index cut-off could actually belowered to a cut score of greater than 3, while still maintaining 93% specificity in oursample. While such a cut-off score may not be appropriate for use in other clinicalsituations, it does suggest that large Vocabulary scores relative to Digit Spanare uncommon in demented groups. Further, in addition to the acceptablespecificity found for the traditional cut-off of Four Digits Timed (90%), ThreeDigits Timed resulted in a 98% specificity when the cut-off was only raised 1 second.Likewise, Finger Tapping (521, genderless) and the Rey Word RecognitionTest (55, genderless) required relatively minor cut-offs adjustments to maintainadequate specificity. Although the forced-choice measures of the WarringtonRecognition Memory Test Words and the TOMM required substantial cut-offchanges to maintain specificity, it should be mentioned that both retained 90%specificity with cut-offs slightly higher than 50% correct (Warrington526; TOMMTrial 25 28). This suggests that even in demented groups, correctly identifying halfor less of the items is quite uncommon. Thus, when chance or worseperformance occurs in, for example, a mild head injury case without grossimpairments in activities of daily living, this would be nearly incontrovertibleevidence that the patients effort was noncredible.

Several of our findings are similar to those found in previous researchon effort testing in dementia. Previous specificities for demented groups onthe second trial of the TOMM ranged from a high of 82% (Greve et al., 2006) to alow of 24% (Teichner & Wagner, 2004)our specificity fell in betweenthese findings at 45%. Similarly, our specificities for Reliable Digit Span (70%)and Vocabulary minus Digit Span (97%) were nearly identical to those previouslyreported (68%, Heinly et al., 2005; 97%, Iverson & Tulsky, 2003; respectively).Merten et al. (2007) found a much lower specificity for Reliable Digit Span (30%),but this was based on a more stringent cut-off than used currently or by Heinlyand colleagues (Merten et al. cut-off 58; Heinly et al. and current study 57).Previous findings from our lab on the Dot Counting Test were also similar to thosefound currently with a larger dementia sample (current mild dementia 77%,previous mild dementia 75%, Boone et al., 2002a), but it should be noted thatthe samples in these two analyses overlapped in slightly less than half of the casesexamined. Our specificity for the Warrington Recognition Memory Test Words(59%) was actually much better than previously described by Diesfeldt (1990; 16%),but since the Diesfeldt calculation was based on a cut-off for both the Wordsand Faces subtests, our results are likely to be more representative of the Wordssubtest in isolation.

Compared to the specificities found by Iverson and Tulsky (2003; 95%)and Heinly and colleagues (2005; 90%) for the Digit Span Age-Corrected ScaledScore, our specificity was considerably worse (73%). Because the Heinly et al. studywas comprised of undefined memory disorder patients, it is possible that someor many of their participants did not meet the full criteria for dementia.The participants for the Iverson and Tulsky study were Alzheimers outpatientsfrom the WAIS-III standardization sample with MMSE scores no less than 18 and a


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mean full scale IQ of 86 (see WAIS-III/WMS-III Technical Manual; PsychologicalCorp., 2002). Because our dementia patients were of mixed diagnosis withthe possibility of more severe MMSE scores (and a mean FSIQ of 77), oursample was likely more severely impaired in comparison. In fact, even the DigitSpan specificity from our probable Alzheimers dementia sample was much lower

(74%) than that reported by these authors. Lastly, previous findings from ourlab on the Finger Tapping test produced better specificities (8775%, Arnold et al.,2005) than found currently (69%), probably reflective of the more stringentexclusion criteria implemented in the former study (cases with motorimpairment were excluded).

Because of particularly small sample sizes and a lack of demographicequivalence between groups, our specificity results for different types of dementia

should be viewed as preliminary. Nonetheless, it is interesting to note possiblepatterns of performance. While probable vascular patients performed poorly on thetraditional cut-offs for the Finger Tapping test (43%), no false positives were foundon this test for those with probable Alzheimers dementia. This is likely reflectiveof the relative sparing of motor cortex in mild to moderate stage Alzheimersdisease.

In conclusion, data from the current study indicate that a minority of existingeffort indicators appear to be useful in the differential between actual and feigned

dementia. Hopefully these findings will provide an impetus for additional validationstudies on other effort indicators in dementia samples and the development ofnew effort measures that are insensitive to even the most severe forms of cognitiveimpairment. Until that time, we suggest that existing effort tests be administeredand carefully compared for consistency with the wealth of other data available

in clinical evaluations, including other cognitive scores, behavioral observations,self and collateral report, historical records, and the cliniciansknowledge of dementia and typical brainbehavior relationships. Further,the data from this study regarding cut-off adjustments and effort score/severityrelationships can be used as guidelines in interpreting effort test scores obtainedin clinical practice.

ACKNOWLEDGMENT

This study was graciously supported by a grant from the

Borchard Center for Law and Aging. We would also like to thank JillRazani, Ph.D., and Ashley R. Curiel, M.A. for their contributions to datacollection/entry.

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