improving medication adherence in patients with chronic ...377674/s...improving medication adherence...

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Improving medication adherence in patients with chronic disease

using a targeted and tailored approach

Thi-My-Uyen Nguyen

Bachelor of Pharmacy (Honours I)

A thesis submitted for the degree of Doctor of Philosophy at

The University of Queensland in 2015

School of Pharmacy

ii

Abstract

Improving adherence to medications is an opportunity that can yield great improvements in

health outcomes and reducing health costs. Supporting adherence to medicines requires

insight into a patient’s medication-taking behaviour and their reasons for non-adherence.

Adherence interventions that show most promise include multifaceted interventions, and

those targeted to non-adherent patients and/or tailored to patient-specific reasons for non-

adherence. To identify non-adherent patients and their reasons for non-adherence in the

practice setting, I argue that we require inexpensive measures that are easy to use and can

inform the discussion with patients about their adherence. Adherence scales are

inexpensive, easy-to-administer and have the potential to explore both medication-taking

behaviour and reasons for behaviour.

The overall aim of the thesis is to determine if a targeted and tailored intervention based on

a discussion informed by validated adherence scales, will improve adherence to a recently

initiated cardiovascular medication. I hypothesise that targeting and tailoring an intervention

to non-adherent participants based on a discussion informed by adherence scales, will

improve adherence at three months as measured by the four-item Medication Adherence

Questionnaire (MAQ). I will also test whether improvements in adherence at three months

are sustained at six months and explore the changes in adherence and reasons for non-

adherence over time.

The first part of the thesis involved identifying validated adherence scales suitable for use in

the intervention. A systematic review was conducted on adherence scales to explore their

use and validation. We found that adherence scales measured different aspects of

adherence: medication-taking behaviour, barriers to adherence and beliefs associated with

adherence. Adherence scales have been validated in different disease populations and

against different measures of adherence. We selected two adherence scales for our study:

the MAQ and Beliefs about Medicines Questionnaire-Specific (BMQ-S). The MAQ is one of

the most commonly used adherence scales that has been validated in many disease

populations and against different measures of adherence including electronic monitoring.

The BMQ-S has been extensively used to elicit medication beliefs associated with

medication adherence and validated in a number of diseases including cardiovascular

disease, asthma and depression.

A randomised controlled trial was conducted to determine if a targeted and tailored

intervention would improve medication adherence. Four hundred and eight patients were

iii

assessed for eligibility from two community pharmacies, from which 152 patients were

enrolled into the study. All enrolled participants completed the MAQ, BMQ-S and Brief Illness

Perceptions Questionnaire (BIPQ). There were 120 participants identified as non-adherent

using the MAQ, who were randomised into an intervention or control group. The remaining

32 participants were identified as adherent. In the intervention group, the results from the

MAQ, BMQ-S, and BIPQ were used by the researcher (TN) to identify reasons for non-

adherence and inform the implementation of a tailored strategy. There was no difference

between the mean MAQ scores at baseline: 1.58 ± 0.79 (intervention) and 1.60 ± 0.67

(control) (p=0.9008). At three months, the mean MAQ score in the intervention group was

significantly lower than the control group, reflecting an improvement in adherence (mean

MAQ 0.42 ± 0.59 v 1.58 ± 0.65; p<0.001). The significant improvement in the mean MAQ

score in the intervention group compared to control was sustained at six months (0.48 ±

0.68 vs 1.48 ± 0.83; p<0.001).

The intervention consisted of an interview and the implementation of a tailored strategy. The

participant’s reasons for non-adherence were explored using their responses to the MAQ,

BMQ-S and BIPQ. Where possible the researcher used responses to the adherence scales

to inform further discussion regarding the participant’s adherence and the factors that

supported or impeded them taking their medicine. The researcher and participant then

selected and implemented an evidence-based tailored strategy to support the participant’s

adherence based on the information discussed in the interview. Tailored strategies included

reminders, cognitive-educational strategies, both a reminder and cognitive-educational

strategy, behavioural-counselling and social support. For example, if the main barrier to

adherence is identified as forgetfulness, then the participant will receive a reminder strategy.

Changes in the responses to the questionnaires were explored in the adherent, intervention

and control groups, and also within the different types of strategies. In the intervention group,

patients who received a cognitive-educational strategy had improved perceived

understanding of their illness corresponding to improvements in their adherence score on

the MAQ. As expected, patients who received a reminder strategy on its own had no

significant changes in their beliefs about medicines and illness perceptions.

An intervention that targeted non-adherent participants and tailored to the participant-

specific reasons for non-adherence was successful at improving medication adherence.

Better understanding how a patient’s adherence and beliefs about their medicines change

over time, will inform improved interventions to support adherence. This intervention was

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quick and easy to administer and has the potential for clinical implementation if proven

successful in larger studies that assess clinical outcomes.

v

Declaration by author

This thesis is composed of my original work, and contains no material previously published

or written by another person except where due reference has been made in the text. I have

clearly stated the contribution by others to jointly-authored works that I have included in my

thesis.

I have clearly stated the contribution of others to my thesis as a whole, including statistical

assistance, survey design, data analysis, significant technical procedures, professional

editorial advice, and any other original research work used or reported in my thesis. The

content of my thesis is the result of work I have carried out since the commencement of my

research higher degree candidature and does not include a substantial part of work that has

been submitted to qualify for the award of any other degree or diploma in any university or

other tertiary institution. I have clearly stated which parts of my thesis, if any, have been

submitted to qualify for another award.

I acknowledge that an electronic copy of my thesis must be lodged with the University Library

and, subject to the policy and procedures of The University of Queensland, the thesis be

made available for research and study in accordance with the Copyright Act 1968 unless a

period of embargo has been approved by the Dean of the Graduate School.

I acknowledge that copyright of all material contained in my thesis resides with the copyright

holder(s) of that material. Where appropriate I have obtained copyright permission from the

copyright holder to reproduce material in this thesis.

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Publications during candidature

Peer-Reviewed Papers

Nguyen TMU, La Caze A, Cottrell WN. What are validated self-report adherence scales

really measuring?: a systematic review. British Journal of Clinical Pharmacology

2014;77(3):427-45.

Conference Abstracts Presented as an Oral Presentation

Nguyen TMU. Role of pharmacists in improving medication adherence in patients with

chronic diseases. In: Proceedings of the Australian College of Pharmacy Conference; 2013

July 8; Brisbane.

Nguyen TMU, La Caze A, Cottrell WN. Improving medication adherence in patients with

chronic disease using a targeted and tailored approach: a randomised controlled trial. In:

Proceedings of the National Medicines Symposium; 2014 May 21-23; Brisbane.

Nguyen U, La Caze A, Cottrell WN. A targeted and tailored intervention to improve and

sustain medication adherence: a randomised controlled trial. In: Proceedings of the Society

of Hospital Pharmacists of Australia Conference; 2014 Sep 11-14; Darwin.

Conference Abstracts Presented as a Poster Presentation


really measuring?: a systematic review. In: Proceedings of the Joint Australasian Society of

Clinical and Experimental Pharmacologists and Toxicologists – Australasian

Pharmaceutical Science Association Annual Conference; 2012 December 2-5; Sydney: 578.

Nguyen TMU, La Caze A, Cottrell WN. Developing a method to target and tailor interventions

to improve medication adherence in community pharmacy. In: Proceedings of the Joint

Australasian Society of Clinical and Experimental Pharmacologists and Toxicologists –

Australasian Pharmaceutical Science Association Annual Conference; 2012 December 2-5;

Sydney: 577.

vii

Publications included in this thesis


really measuring?: a systematic review. British Journal of Clinical Pharmacology

2014;77(3):427-45. – incorporated as Chapter Two

Contributor Statement of contribution

Thi-My-Uyen Nguyen Designed experiments (40%)

Data collection (100%)

Wrote and edited paper (40%)

Dr Adam La Caze Designed experiments (30%)


Associate Professor Neil Cottrell Designed experiments (30%)


Contributions by others to the thesis

My principal advisor, Associate Professor Neil Cottrell and associate advisor, Dr Adam La

Caze made significant contributions to the conception and design of the project. Both

advisors oversaw all aspects of the data collection and interpretation of the data.

Statements of parts of the thesis submitted to qualify for the award of another

degree

None

viii

Acknowledgments

Firstly, I would like to thank my academic advisors, Associate Professor Neil Cottrell and Dr

Adam La Caze, without whom this journey would not have been possible. Both Neil and

Adam have been immensely supportive throughout the past three years. I could not have

asked for better advisors. Their knowledge and experience has helped me grow and improve

on my research skills. The three years spent on my thesis has been extremely enjoyable,

especially because I was a part of such an incredible research team.

I would like to thank all academics and staff at the School of Pharmacy for their kindness,

encouragement and support throughout the past few years. They have made my journey

much more memorable. I would like to make a special mention to Associate Professor Marie-

Odile Parat, Associate Professor Alexandra Clavarino and Myrtle Sahabandu for their words

of wisdom.

I would like to acknowledge the financial support of my APA scholarship, without which this

journey would not have been possible.

I would also like to thank the participants in the study for their valuable time and support of

our research. Without whom we would not have learnt the great deal that we have during

my candidature.

Lastly, I would like to thank my family and friends for their undying support and

encouragement. In particular, my parents and husband, Rongzhen, for supporting me and

always believing in me.

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Keywords

medication adherence, non-adherence, chronic diseases, adherence interventions, targeted,

tailored interventions

Australian and New Zealand Standard Research Classifications (ANZSRC)

ANZSRC code: 111503, Clinical Pharmacy and Pharmacy Practice, 100%

Fields of Research (FoR) Classification

FoR code: 1115, Pharmacology and Pharmaceutical Sciences, 100%

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Table of Contents

Abstract ............................................................................................................................ ii

Declaration by author ....................................................................................................... v

Publications during candidature ....................................................................................... vi

Publications included in this thesis ................................................................................. vii

Contributions by others to the thesis .............................................................................. vii

Statements of parts of the thesis submitted to qualify for the award of another degree . vii

Acknowledgments ......................................................................................................... viii

Keywords ..................................................................................................................... ix

Australian and New Zealand Standard Research Classifications (ANZSRC) .................. ix

Fields of Research (FoR) Classification .......................................................................... ix

List of Tables .................................................................................................................. xv

List of Figures ................................................................................................................ xvi

List of Abbreviations ..................................................................................................... xviii

CHAPTER ONE: LITERATURE REVIEW ............................................................................ 1

1.1 Introduction ................................................................................................................. 1

1.2 Terms and Concepts Used to Describe Adherence .................................................... 1

1.2.1 Primary and Secondary Non-Adherence .............................................................. 4

1.2.2 New Taxonomy .................................................................................................... 4

1.2.3 Dynamic Nature of Adherence ............................................................................. 5

1.2.4 Unintentional and Intentional Non-Adherence ...................................................... 7

1.3 Epidemiology of Medication Non-Adherence .............................................................. 7

1.3.1 Prevalence ........................................................................................................... 8

1.3.2 Clinical Outcomes ................................................................................................ 8

1.3.3 Increased Health Care Expenditure ................................................................... 10

1.4 Barriers to and Determinants of Medication Adherence ........................................... 10

1.5 Measuring Medication Adherence ............................................................................ 16

1.5.1 Objective Measures ............................................................................................ 16

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1.5.2 Subjective Measures .......................................................................................... 19

1.5.3 Self-Report Adherence Scales ........................................................................... 20

1.6 Interventions to Improve Adherence ......................................................................... 24

1.6.1 Introduction......................................................................................................... 24

1.6.2 Examples of Interventions Focusing on a Single Aspect of Adherence .............. 26

1.7 Summary .................................................................................................................. 30

CHAPTER TWO: SYSTEMATIC REVIEW OF VALIDATED SELF-REPORT MEDICATION

ADHERENCE SCALES (PUBLISHED).............................................................................. 33

2.1 Introduction ............................................................................................................... 33

2.2 Published Paper ....................................................................................................... 33

2.2.1 Abstract .............................................................................................................. 33

2.2.2 Introduction......................................................................................................... 34

2.2.3 Methods ............................................................................................................. 36

2.2.4 Results ............................................................................................................... 37

2.2.5 Discussion .......................................................................................................... 62

2.2.6 Conclusions ........................................................................................................ 65

2.3 Additional Notes ....................................................................................................... 66

2.4 Summary .................................................................................................................. 66

CHAPTER THREE: METHODS OF RANDOMISED CONTROLLED TRIAL TO IMPROVE

MEDICATION ADHERENCE ............................................................................................. 67

3.1 Introduction ............................................................................................................... 67

3.2 Aims and Hypotheses ............................................................................................... 68

3.3 Methods .................................................................................................................... 69

3.3.1 Setting ................................................................................................................ 69

3.3.2 Inclusion Criteria ................................................................................................. 70

3.3.3 Participant Interviews ......................................................................................... 70

3.3.4 Intervention......................................................................................................... 79

3.3.5 Outcome Measures ............................................................................................ 81

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3.3.6 Sample Size ....................................................................................................... 81

3.3.7 Statistical Analyses ............................................................................................ 82

3.4 Summary .................................................................................................................. 82

CHAPTER FOUR: RESULTS 1 - A RANDOMISED CONTROLLED TRIAL OF A

TARGETED AND TAILORED INTERVENTION TO IMPROVE MEDICATION

ADHERENCE .................................................................................................................... 83

4.1 Introduction ............................................................................................................... 83

4.2 Results...................................................................................................................... 83

4.2.1 Participant Baseline Demographics .................................................................... 86

4.2.2 Intervention......................................................................................................... 88

4.2.3 Adherence .......................................................................................................... 88

4.2.4 Changes in mean BMQ-S scores between the three groups over time .............. 91

4.2.5 Changes in mean BIPQ scores between the three groups over time ................. 92

4.3 Conclusions .............................................................................................................. 94

CHAPTER FIVE: RESULTS 2 - TAILORING OF THE INTERVENTIONS TO THE

PARTICIPANT-SPECIFIC REASONS FOR NON-ADHERENCE ...................................... 95

5.1 Introduction ............................................................................................................... 95

5.2 Participant Baseline Interview ................................................................................... 96

5.3 Intervention ............................................................................................................... 96

5.3.1 Overview of Strategies Implemented .................................................................. 96

5.3.2 Overview of Radar Charts of the Responses to the Scales for each Tailored

Strategy and Case Examples ...................................................................................... 97

5.3.3 Reminder System ............................................................................................... 99

5.3.4 Cognitive-Educational Strategy ........................................................................ 104

5.3.5 Reminder and Cognitive-Educational Strategy ................................................. 109

5.3.6 Behavioural-Counselling Strategy .................................................................... 113

5.3.7 Social Support Strategy .................................................................................... 117

5.4 Flow Diagram of Tailoring Adherence Intervention (Post-Implementation) ............. 119

5.5 Conclusions ............................................................................................................ 122

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CHAPTER SIX: RESULTS 3 - CHANGES IN ADHERENCE OVER SIX MONTHS ........ 123

6.1 Introduction ............................................................................................................. 123

6.2 Differences between the Adherent, Intervention and Control Groups ..................... 123

6.2.1 Adherence over time ........................................................................................ 124

6.2.2 BMQ-S Necessity over time ............................................................................. 125

6.2.3 BMQ-S Concerns over time.............................................................................. 126

6.2.4 BIPQ Treatment Control over time ................................................................... 127

6.2.5 BIPQ Treatment Coherence over time ............................................................. 128

6.3 Changes in each of the Tailored Strategy Groups .................................................. 129

6.3.1 Reminder Strategy Group (n=27) ..................................................................... 129

6.3.2 Cognitive-Educational Strategy Group (n=9) .................................................... 133

6.3.3 Reminder and Cognitive-Educational Strategy Group (n=15) .......................... 137

6.3.4 Behavioural-Counselling Strategy Group (n=4) ................................................ 140

6.3.5 Social Support Strategy Group (n=5) ............................................................... 144

6.3.6 Overall View of the Changes in Adherence Scale Scores over time for each

Tailored Strategy ....................................................................................................... 147

6.4 Discussion .............................................................................................................. 150

6.5 Conclusions ............................................................................................................ 151

CHAPTER SEVEN: DISCUSSION .................................................................................. 153

7.1 Introduction ............................................................................................................. 153

7.2 Validated Adherence Scales................................................................................... 153

7.3 Targeted and Tailored Intervention ......................................................................... 154

7.4 Changes in Adherence, Beliefs about Medicines and Illness Perceptions over Time

..................................................................................................................................... 155

7.5 Limitations of the Study .......................................................................................... 156

7.6 Future Directions and Conclusion ........................................................................... 158

REFERENCES ................................................................................................................ 159

APPENDIX A: Ethics Approval Letter .............................................................................. 186

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APPENDIX B: Participant Information Sheet ................................................................... 187

APPENDIX C: Participant Consent Form ......................................................................... 189

APPENDIX D: Participant Survey .................................................................................... 190

APPENDIX E: Mean MAQ Scores Over Time ................................................................. 193

APPENDIX F: Mean BMQ-S Necessity and Concerns Scores Over Time ...................... 194

APPENDIX G: Illness Perceptions Over Time ................................................................. 195

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List of Tables

Table 1.1 The studies which show significant association or no association between a

number of different factors and medication adherence ...................................................... 14

Table 1.2 Advantages and disadvantages of objective measures of adherence ............... 18

Table 1.3 Validated adherence scales ............................................................................... 21

Table 2.1 Excluded self-report adherence scales .............................................................. 39

Table 2.2 Comparing the self-report adherence scales ..................................................... 40

Table 2.3 Self-report adherence scales - administration, response and validation ............ 49

Table 3.1 The Medication Adherence Questionnaire (MAQ) ............................................. 74

Table 3.2 The Beliefs about Medicines Questionnaire - Specific (BMQ-S) ........................ 76

Table 3.3 The Brief Illness Perception Questionnaire ........................................................ 78

Table 4.1 Baseline participant demographics .................................................................... 87

Table 4.2 Types of tailored strategies implemented to improve medication adherence ..... 88

Table 4.3 Mean BMQ-S necessity scores and concerns score at baseline, three months and

six months between the groups ......................................................................................... 92

Table 4.4 Mean scores of BIPQ at baseline, three months and six months, between groups

........................................................................................................................................... 93

Table 5.1 Individual scores to validated scales at baseline (Participant 47) .................... 100



Table 5.4 Individual scores to validated scales at baseline (Participant 5) ...................... 105




Table 5.8 Individual scores to validated scales at baseline (Participant 7) ...................... 114


Table 5.10 Individual scores to validated scales at baseline (Participant 80) .................. 118

Table 6.1 Change in mean MAQ, BMQ-S, and BIPQ treatment and coherence scores over

time in the REMINDER strategy group ............................................................................ 130


time in the COGNITIVE-EDUCATIONAL strategy group ................................................. 133


time in the REMINDER & COGNITIVE-EDUCATIONAL strategy group .......................... 137

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time in the BEHAVIOURAL-COUNSELLING strategy group ........................................... 141


time in the SOCIAL SUPPORT strategy group ................................................................ 144

List of Figures

Figure 1.1 The shared decision-making model .................................................................... 3

Figure 1.2 The six-phase dynamic adherence model: the continuum of adherence decisions

............................................................................................................................................. 6

Figure 1.3 Adherence scales originate from a number of different sources (Original source

unspecified: Barroso, Bell, Fodor, Grymonpre and VAS Scale) ......................................... 23

Figure 2.1 Flow chart of study selection process ............................................................... 38

Figure 2.2 Disease populations used to validate self-report adherence scales ................. 58

Figure 2.3 Comparison measures of medication-taking behaviour used to validate the self-

report adherence scales .................................................................................................... 60

Figure 3.1 Participant flow diagram: from identifying participants’ medication-taking

behaviour to final follow-up ................................................................................................ 72

Figure 4.1 Participant flow diagram ................................................................................... 85

Figure 4.2 Mean MAQ scores at baseline, 3-month and 6-month follow-ups, based on

intention to treat analysis ................................................................................................... 90

Figure 5.1 Radar Chart template ....................................................................................... 98

Figure 5.2 Radar chart of questionnaire responses of REMINDER group at baseline ....... 99

Figure 5.3 Radar chart of questionnaire responses of the COGNITIVE-EDUCATIONAL

strategy group at baseline ................................................................................................ 104

Figure 5.4 Radar chart of questionnaire responses of the REMINDER & COGNITIVE-

EDUCATIONAL strategy group at baseline ..................................................................... 109

Figure 5.5 Radar chart of questionnaire responses of the BEHAVIOURAL-COUNSELLING

strategy group at baseline ................................................................................................ 113

Figure 5.6 Radar chart of questionnaire responses of the SOCIAL SUPPORT strategy group

at baseline ....................................................................................................................... 117

Figure 5.7 Flow diagram of outcomes of the adherence scales used to inform the discussion

with the participant and implementation of the tailored strategy ...................................... 121

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Figure 6.1 Changes in mean MAQ scores (± 95% confidence intervals) in the adherent,

intervention and control groups over time ........................................................................ 124

Figure 6.2 Changes in mean BMQ-S necessity scores (± 95% confidence intervals) in the

adherent, intervention and control groups over time ........................................................ 125

Figure 6.3 Changes in mean BMQ-S concerns scores (± 95% confidence intervals) in the

adherent, intervention and control groups over time ........................................................ 126

Figure 6.4 Changes in mean BIPQ treatment control scores (± 95% confidence intervals) in

the adherent, intervention and control groups over time .................................................. 127

Figure 6.5 Changes in mean BIPQ treatment coherence scores (± 95% confidence intervals)

in the adherent, intervention and control groups over time .............................................. 128

Figure 6.6 Radar charts at baseline, 3 months and 6 months for the REMINDER strategy

group................................................................................................................................ 132

Figure 6.7 Radar charts at baseline, 3 months and 6 months for the COGNITIVE-

EDUCATIONAL strategy group ....................................................................................... 136

Figure 6.8 Radar charts at baseline, 3 months and 6 months for the REMINDER AND

COGNITIVE-EDUCATIONAL strategy group ................................................................... 140

Figure 6.9 Radar charts at baseline, 3 months and 6 months for the BEHAVIOURAL-

COUNSELLING strategy group ....................................................................................... 143

Figure 6.10 Radar charts at baseline, 3 months and 6 months for the SOCIAL SUPPORT

strategy group .................................................................................................................. 146

Figure 6.11 Change in Questionnaire Scores at three months for each Strategy Type in the

Intervention Group ........................................................................................................... 148

Figure 6.12 Change in Questionnaire Scores at six months for each Strategy Type in the

Intervention Group ........................................................................................................... 149

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List of Abbreviations

AAI Adherence Attitude Inventory

ACE-I Angiotensin Converting Enzyme Inhibitor

ARMS Adherence to Refills and Medications Scale

ASK-12 Adherence Starts with Knowledge-12

ASK-20 Adherence Starts with Knowledge-20

ASRQ Adherence Self-Report Questionnaire

BARS Brief Adherence Rating Scale

BBQ Beliefs and Behaviour Questionnaire

BEMIB Brief Evaluation of Medication Influences and Belief

BIPQ Brief Illness Perception Questionnaire

BJCP British Journal of Clinical Pharmacology

BMAS Brief Evaluation of Medication Influences and Belief

BMQ Beliefs about Medicines Questionnaire

BMQ-S Beliefs about Medicines Questionnaire - Specific

CASE Centre for Adherence Support Evaluation Adherence Index

CQR Compliance Questionnaire Rheumatology

DAI Drug Attitude Inventory

GP General Practitioner

HIV Human Immunodeficiency Virus

IPQ Illness Perception Questionnaire

ITAS Immunosuppressant Therapy Adherence Scale

MAAT Medication Adherence Assessment Tool

MAQ Medication Adherence Questionnaire

MARS Medication Adherence Rating Scale

MARS-5 Medication Adherence Rating Scale – 5

MASES Medication Adherence Self-Efficacy Scale

MASES-R Medication Adherence Self-Efficacy Scale – Revised

MEMS Medication Events Monitoring System

MGMM Measurement-Guided Medication Management

MMAS Morisky Medication Adherence Rating Scale

MPR Medication Possession Ratio

MR Modified-Release

MUAH Maastricht Utrecht Adherence in Hypertension Questionnaire

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OS-MMAS Osteoporosis-Specific Morisky Medication Adherence Scale

PBS Pharmaceutical Benefits Scheme

PIAQ Paediatric Inhaler Adherence Questionnaire

RAM Reported Adherence to Medication Scale

SEAMS Self-Efficacy for Appropriate Medication Use Scale

SEIFA Socio-Economic Index for Areas

SERAD Self-Reported Adherence Questionnaire

SMAQ Simplified Medication Adherence Questionnaire

SOCA Stages of Change for Adherence Measure

VAS Adherence Visual Analogue Scale

WHO World Health Organisation

1

CHAPTER ONE: LITERATURE REVIEW

1.1 Introduction

Medication non-adherence has been identified as one of the greatest areas of opportunity

to improve health outcomes and reduce health expenditure.1-3 Poor adherence to medicines

affects approximately 50% of patients taking chronic medicines,1,4-10 leading to adverse

health outcomes.11,12

Interventions have been employed to improve adherence to medications. These include:

reminder interventions (e.g. telephone reminders), educational interventions (e.g.

informational pamphlets), behavioural interventions (e.g. motivational interviewing) and

social support (e.g. peer support therapy).13-15 Adherence interventions have not always

been successful at improving medication adherence in clinical trials.13,15 This reflects the

complex nature of adherence.

Supporting a patient’s adherence to their medicines requires insight into their medication-

taking behaviour and the reasons for their behaviour. An intervention that targets non-

adherent patients and tailored to the patient-specific reasons for non-adherence that is

practical to translate into clinical practice is required. Adherence scales are easy to

administer, inexpensive and can explore both adherence and reasons for non-adherence.

This thesis explores an intervention that is targeted to non-adherent participants and tailored

to their specific reasons for non-adherence, informed by validated self-report adherence

scales.

This chapter outlines the issues associated with medication non-adherence, the measures

of adherence, the barriers to and determinants of adherence and the current interventions

implemented to improve adherence.

1.2 Terms and Concepts Used to Describe Adherence

The benefits of effective medicine use depend on a patient taking their medication.

Historically, this was referred to as “compliance.” Compliance is the degree to which the

patient follows the treatment instructions given by the health provider. This suggests that

2

the health provider knows what is best for the patient and would prescribe the ideal treatment.

It implies that patients play a passive role in their medical management and that deviating

from these instructions would put the blame on the patient.16-19 With healthcare adopting a

more patient-focussed approach, the terms to describe medication-taking behaviour have

evolved over time from “compliance” to “adherence." The shift from “compliance” to

“adherence” represents a desire to emphasise the patient’s active role in decision-

making.1,20

The World Health Organisation (WHO) defines adherence as:

“The extent to which a person’s behaviour – taking medication, following a diet, and/or

executing lifestyle changes, corresponds with agreed recommendations from a

health care provider.”1

The definition of “adherence” acknowledges the importance of the shared agreement

between the patient and the health care provider. Shared decision-making, which may be

implicit, involves the patient in the treatment decision process. It explores the ideas, fears

and expectations of the patient, with both the patient and health provider coming to a final

agreement on the treatment decision (Figure 1.1).21,22 By acknowledging shared decision-

making, the definition of adherence incorporates patient-provider collaboration focusing on

patient autonomy and patient-centred care. Therefore, the term “adherence” is preferred

over “compliance.”1,20 There are a few methods to explore whether shared decision-making

occurs, including tape recording medical consultations and computerised shared decision

support tools.22-24 Although shared decision-making is central to adherence, it is not how

adherence is typically operationalised.

Another term that is often used in adherence research is concordance. “Concordance” refers

to the agreement between the patient and physician about the therapeutic regimen. This

term implies active patient participation in the discussion and decisions about the treatment

plan.25

Given the difficulties of exploring shared decision-making, most research operationalises

adherence in terms of medication-taking behaviour. Medication-taking behaviour is

assessed by measuring the number of medicine doses taken, dose frequency and dose

administration according to the instructions on the dispensing label.20 Good medication-

taking behaviour in patients with high cardiovascular risk, such as in ischaemic heart disease,

3

has been shown to improve cardiovascular event-free survival.12,26,27 Furthermore, poor

medication-taking behaviour with antibiotics can lead to an increased likelihood of

developing bacterial resistance to antimicrobial agents.28-30 Measuring medication-taking

behaviour is important and hence why many studies on adherence have focused on this.

Figure 1.1 The shared decision-making model 31

Information

exchange

Deliberation about

preferences, beliefs,

and goals for care

Improved clinical outcomes

- Provider treatment

behaviour is adherent to

best practices of care

- Medical decisions are

concordant with patient-

physician shared plan of

treatment

- Appropriate patient self-

management

Patient-clinician

concordance

Shared treatment

plan

4

Medication adherence and non-adherence can be further described in a number of different

ways.18,19,32,33 Adherence to medications has been described in terms of primary and

secondary non-adherence, the dynamic nature of adherence and unintentional and

intentional non-adherence.

1.2.1 Primary and Secondary Non-Adherence

Patients who are non-adherent can exhibit primary or secondary non-adherence.18 Primary

non-adherence refers to when an initial prescription is not dispensed or when dispensed but

the medication never taken. Less research has been conducted on primary non-adherence;

however, there is an emerging interest in this area.34-36 Most adherence research has

studied secondary non-adherence: when prescriptions are filled, but the patient later

discontinues taking the medicine.37

These terms of describing medication non-adherence do not take into consideration the

complexity and dynamic nature of medication-taking behaviour. Section 1.2.2 and 1.2.3

introduces newer concepts in describing adherence.

1.2.2 New Taxonomy

Vrijens et al. developed a new taxonomy for medication adherence and defines adherence

in terms of medication-taking behaviour. This adherence taxonomy separates adherence

into three different phases: initiation, implementation and discontinuation. Initiation refers to

when the patient takes the first dose of a prescribed medication. Discontinuation occurs

when the prescribed medication is ceased. The extent that the patient’s actual dosing

regimen corresponds with the prescribed dose from initiation of treatment to the

discontinuation of treatment is termed implementation.38 A patient may be described as non-

adherent when they: do not initiate a prescription, delay initiating a prescription, implement

the regimen poorly or discontinue the prescription early.

This taxonomy is relatively new and is not yet well-established in the literature; however

presents as a significant opportunity for improving the consistency of describing medication-

taking behaviour. The taxonomy is relatively simple; however, identifies adherence solely

based on medication-taking behaviour. To strengthen the conceptualisation of adherence,

5

explicit recognition of the shared decision between the patient and healthcare professional

is required. Furthermore, methods to clearly identify initiation, implementation and

discontinuation of treatment would reinforce this taxonomy.

1.2.3 Dynamic Nature of Adherence

Most studies measuring adherence have been conducted using a cross-sectional study

design. Adherence has generally been dichotomously categorised: patients are adherent or

non-adherent at a single point in time. Though simple, describing adherence in this way has

a number of problems. Classifying patients as non-adherent does not distinguish between

different patient behaviours, such as not filling the prescription, reducing the dose, taking

medication sporadically or prematurely discontinuing the medication.39 Further,

dichotomously categorising adherence at a single time point implies that adherence is static,

when in fact it can change depending on a patient’s circumstances, information and

beliefs.40-44 Gearing et al. conceptualises adherence into six dynamic stages (Figure 1.2).19

6

Figure 1.2 The six-phase dynamic adherence model: the continuum of adherence decisions 19

The initial phase, treatment initiation, occurs when the patient is prescribed a medication

and either decides to accept or decline the treatment. If the patient is non-adherent in this

phase, it is known as primary non-adherence, as discussed in Section 1.2.1. In the second

phase, treatment trial, the patient has the prescription dispensed and takes the medicine;

however, the medication is discontinued before the next prescription refill. The partial

treatment acceptance phase refers to when patients fill the initial prescription, begins and

continues partial treatment (adjusted dosage or dose frequency) for an extended time period.

In the intermittent treatment adoption phase the patient accepts the full treatment as agreed

but discontinues after months of adherence and subsequently returns to partial or

intermittent adherence. The premature discontinuation following treatment adoption phase

refers to patients who are fully adherent and then prematurely discontinue treatment. The

last phase is when patients are fully adherent to treatment.19

7

Adherence is not static and is influenced by many different factors, which can change over

time. These six distinct phases represent decision points and incorporates patients’ varying

degrees of intent to take their medication as agreed. This dynamic system of adherence

also acknowledges the movement of patients between phases.19

1.2.4 Unintentional and Intentional Non-Adherence

Non-adherence can be described as unintentional or intentional or a mix of both.18,32,33,45-48

Unintentional non-adherence is characterised as poor medication-taking behaviour due to

circumstances beyond the patient’s control.32 Reasons why patients may be unintentionally

non-adherent include forgetfulness, carelessness, cognitive impairment and socioeconomic

issues.18,49,50 Intentional non-adherence arises when a patient makes a conscious decision

not to take the prescribed medication.48,50 It is important to distinguish between these types

of medication non-adherence to better implement appropriate interventions. For example,

patients identified as intentionally non-adherent are unlikely to benefit from the

implementation of dose administration aids, but may benefit from behavioural-counselling

interventions, such as motivational interviewing.32

1.3 Epidemiology of Medication Non-Adherence

Non-adherence to medications is highly prevalent, with approximately 50% of patients

consistently identified as non-adherent in studies focussing on chronic disease.4-8,51-58

Medication non-adherence can lead to adverse health outcomes, increased hospitalisations

and health care costs.3,12,18,55,59 The adverse impact of medication non-adherence grows as

the burden of chronic diseases increases.1

This section discusses the prevalence of non-adherence, and the clinical outcomes,

hospitalisations and health care expenditure associated with medication non-adherence.

8

1.3.1 Prevalence

The proportion of patients identified as non-adherent, commonly defined as taking less than

80% of their medicine, is similar across different disease states.5,53,60-63 This 80% cut-off has

been correlated with significantly improved clinical measures, such as blood pressure.18,64

Non-adherence rates to medicines are typically higher among patients with chronic

conditions in comparison with those suffering from acute illnesses.65,66 A study using a

prescription claims database showed that non-adherence to statins was present in 60% of

patients suffering from acute coronary syndromes, 64% with coronary artery disease and

75% for primary prevention of cardiovascular disease.65 Self-report adherence scales

identified 54% of patients with schizophrenia, 38% of patients with hypertension, 26% of

patients with diabetes, as non-adherent to their medication.5,53

There is a tendency for medication adherence in chronic illnesses to decline over time.7,8,56

Non-adherence to recently initiated statins increased between one-month and twelve

months in: hypertension (18% versus 47.9%), heart failure (16.3% versus 50%) and

coronary heart disease (28.2% versus 38.3%) populations.7 Alendronate non-adherence in

patients with osteoporosis increased, particularly during the first six to twelve months after

the initial prescription.8 Non-adherence to antiretroviral therapy in HIV increased from 48%

at one-month after initiating the therapy to 61% non-adherence at the six-month follow-up.60

This increasing trend in non-adherence suggests the need to measure adherence at

different time points. It has been suggested that important factors are involved during the

process of obtaining the initial prescription and treatment continuation.7 Patient

circumstances, information and beliefs may change over time.42 Therefore reasons for non-

adherence and interventions should be reassessed at different time points to maintain good

medication-taking behaviour. Changes in adherence over time support the dynamic model

of adherence, as described in Section 1.2.3.

1.3.2 Clinical Outcomes

Non-adherence to medications can lead to adverse health outcomes and an increase in

hospitalisation rates across various disease populations. Most of the literature has focused

on adverse outcomes associated with non-adherence in cardiovascular disease, diabetes,

schizophrenia and HIV.

9

Non-adherent patients with cardiovascular disease are more likely to have adverse health

outcomes in comparison with adherent patients.12,67,68 Medication non-adherence

contributes to poor blood pressure control, which can lead to further cardiovascular

complications including coronary heart disease and heart failure.69 Hospitalisation rates

were significantly higher in patients with poor medication adherence suffering from diabetes,

hypercholesterolaemia, hypertension and congestive heart failure.3,70 Gehi et al. determined

that medication non-adherence was associated with a greater than two-fold increase in the

rate of cardiovascular events in patients with stable coronary artery disease.12 Patients with

heart failure who were non-adherent to digoxin had a significant increase in the number and

duration of hospitalisations in comparison with adherent patients.70 Poor prescription refill

adherence (less than 40%) was significantly associated with a three-fold increase in the

incidence of hospitalisation due to heart failure compared with good prescription refill

adherence (at least 80%).71

Medication non-adherence in diabetes has been associated with poorer health outcomes

and an increase in hospitalisations.72,73 Non-adherence has been significantly associated

with a higher glycosylated haemoglobin level (HbA1c), reflecting poor management of

diabetes. A high HbA1c (greater than 7%) can increase the risk of developing cardiovascular

diseases, ocular problems and neurological complications.74,75

Non-adherence to antipsychotics can lead to symptom relapse, worse prognosis and

increased risk of hospitalisations.76-78 Patients with schizophrenia who did not fill their

antipsychotic prescription within the first week after hospital discharge had a higher risk of

early rehospitalisation.79,80 Poor adherence in schizophrenia has also been associated with

greater use of emergency psychiatric services, poorer mental functioning and violence. Non-

adherence has also been significantly associated with poorer life satisfaction, more alcohol-

related problems and more arrests.81

In order to suppress viral replication and reduce the risk of viral resistance in HIV, patients

should have good medication adherence.60,82,83 Non-adherence to HIV treatments has been

shown to cause treatment failure, clinical deterioration and development of viral resistance,

which leads to the increase risk of transmission of resistant virus.83,84

10

1.3.3 Increased Health Care Expenditure

Non-adherence to medications can lead to worsening of health outcomes and increased

hospitalisations, which results in an increase in health care costs. The costs of medication

non-adherence are largely derived from exacerbations of illnesses that require emergency

medical attention and hospitalisations.71 A reduction in medical costs offsets the cost of

medications and can thus lead to an overall reduction in health care costs.3 A government

report suggests that medication non-adherence costs the Australian health system

approximately $660 million annually, in terms of preventable hospital admissions.85 In the

United States, the annual burden of medication non-adherence has been estimated to be

$100 billion.20,86 More specifically, non-adherence to diabetes medication has been

estimated to cost the United States health system $5 billion per year. Medication non-

adherence plays a significant role in the financial burden upon health care systems.

Therefore, improving medication adherence should be a key goal for health care systems

and policy makers.1,73

1.4 Barriers to and Determinants of Medication Adherence

A number of factors can affect medication adherence. The WHO has divided the factors that

can affect medication adherence into five dimensions: social and economic, health system

and health care team, condition-related, therapy-related and patient-related factors.1

Although there has been extensive research into the barriers to and determinants of

medication adherence, more than half of the studied factors have not been consistently

associated with adherence (Table 1.1).18 Most of the studies below have defined adherence

as taking 80% of the medication; for example, in regards to dose counts, taking at least 80%

of your medicine would be defined as adherent. Some patients may have good reasons for

non-adherence. Determining the barriers to and determinants of medication adherence may

aid the implementation of tailored interventions to improve medication adherence.1,39

Sociodemographic and economic factors

Sociodemographic and economic factors such as age, sex, race, socioeconomic status and

education level have some association with medication adherence.4,8,54,57,87-91 Race has

been shown to have some impact on adherence, which can be explained by varying cultural,

11

health and medicinal beliefs.92 Studies showing a significant relationship between age and

adherence, have found that older patients were likely to be more adherent than younger

patients.8,50,57,87,93-95 However, the risk of cognitive and functional impairment increases with

age which can increase the likelihood of non-adherence in the elderly.96 Younger patients

may decide not to adhere to the treatment or may forget due to competing priorities in life.97

Health system and health care team factors

Less research has been conducted on the effects of health system and health care team

factors on medication adherence.1 Modifying cost at a health system level can improve

adherence to medications.98 Poor communication from health care professionals, shorter

patient-provider consultations and poorly developed health services can negatively impact

medication adherence.99-101 It has been shown that non-adherent patients were significantly

less likely to have established a close therapeutic alliance (the relationship between a

patient and health professionals) during hospitalisation, see Table 1.1.77

Health condition-related factors

Condition-related factors such as duration of the disease and co-morbidities can affect

medication adherence. In particular, severity of symptoms, cognitive impairment and

substance abuse have been shown to have a negative impact on medication

adherence.87,93,96,102-104 Many studies have found that patients with predominantly

asymptomatic conditions, such as hypertension are less adherent.105 Co-morbidities that

can impact adherence include depression and substance abuse.58,77,89,93,106

Therapy-related factors

Therapy-related factors, such as the complexity of the medication regimen, duration of

therapy, route of administration and side effects have been noted to affect

adherence.88,90,94,107-109 The greater the number of medications and higher dose frequencies

have been consistently associated with non-adherence.110,111 Patients with chronic

obstructive pulmonary disease (COPD) on once-daily dosing regimens had significantly

higher adherence than those on multiple daily dosing regimens.108 Another factor that can

impact adherence is the cost of the therapy. The greater the cost of the medication, the less

likely that patients will be adherent to the medication. The impact of cost is mitigated by the

patients beliefs towards how necessary their medicine is to them. If patients perceive their

medicine to be unnecessary, the cost of the medicine would theoretically not impact on their

12

decision to take their medicine. Patients will not pay for a medicine no matter how much it

costs if the patients believe the medicine is unnecessary.35,112,113

Patient-related factors

Patient-related factors include a patient’s tendency to forget to take their medications,

knowledge, attitude, beliefs and perceptions of their illness and medicines. Forgetting to take

medication is a common reason that has been consistently associated with non-

adherence.46,67,105,114-116

Patient medication beliefs and how these beliefs affect medication adherence have also

been extensively studied.4,41,42,44,88,89,117-122 One of the most commonly used adherence

scales, the Beliefs about Medicines Questionnaire-Specific (BMQ-S), elicits beliefs about

the necessity of medicines and concerns about medicines.4,49,87-89,118,123,124 These beliefs

have been shown to reflect a patient’s perceptions of illness and adherence.95,125,126

Generally, patients that believe their medicines are necessary and have minimal concerns

about their medicines have better medication adherence.95,120,126-131

Patient’s perceptions and understanding of their illness and treatment have been shown to

be associated with medication adherence.40,95,125-127,132-135 There are a number of different

scales used to assess health perceptions including the Health Perception Questionnaire

(HPQ), Illness Perception Questionnaire (IPQ), Illness Perception Questionnaire – Revised

(IPQ-R) and Brief Illness Perception Questionnaire (BIPQ).136-139 The IPQ was developed

based on the Self-Regulatory Theory to assess the cognitive representations of illness:

identity (symptoms perceived associated with illness), cause (patient ideas about aetiology),

timeline (perceived illness duration), consequences (expected effects and outcomes) and

cure control (how patient controls/recovers from illness).137 IPQ-R and BIPQ are shorter

forms of the IPQ and have been used extensively in the literature. Using the IPQ, it was

found that perceptions of poor personal ability to control illness, greater perceived effect of

illness on life and lower emotional response was significantly associated with better

medication adherence in patients with hypertension.95 In a chronic pain population,

perceptions of illness as chronic and uncontrollable, measured using the IPQ-R, were

associated with less concerns about their medicines and greater adherence. Patients in this

chronic pain population who perceived serious illness consequences had stronger beliefs

that medicines are necessary and were more adherent. Patients were less adherent to their

medication when they have a greater emotional response to their illness.125 Patients with

high blood pressure who were more likely to be adherent, had greater perceived personal

13

ability to control blood pressure, exhibited greater concerns about their illness and had less

emotional burden, based on the BIPQ.135

Past medication adherence has been shown to predict adherence.77,140 For example, the

best single predictor of future adherence in patients with schizophrenia was found to be non-

adherence in the prior six months.140 Furthermore, past prescription-refill behaviour was a

significant predictor of adherence to statins.141

Table 1.1 shows factors that have been studied in association with medication adherence.

There are factors which are consistently associated with non-adherence (e.g. forgetfulness,

beliefs about medicines) and factors where the association appear less clear (e.g.

socioeconomic status). Studies differ in the diseases included, methods used to measure

adherence, how adherence is defined and sample size.1,109 This may explain some of the

inconsistency in the association of factors with medication adherence.

Review articles exploring various barriers to and determinants of adherence, have

suggested the need to address a full range of influencing factors to improve adherence.68,142

Many studies have globally implemented interventions without identifying why the patient is

non-adherent. We need to better understand the patient-specific reasons for non-adherence

to better implement tailored interventions to improve adherence.68,143,144

14

Table 1.1 The studies which show significant association or no association between a number of different factors and medication adherence

Factor Significant Association No Association

Sociodemographic Factors

Socioeconomic status Akincigil57, Barclay87, Devold8,

Maqutu91

Gatti89, George100,

Khanderia103, Kleeberger90,

Laba94, Maqutu91

Employment status Ediger145 Fawzi88, Gatti89, Kim146

Education level Burra115, Ross95, Ruppar107s Devold8, Fawzi88, Gatti89,

Jacobs96, Khanderia103, Kim146,

Kleeberger90, Laba94, Mo147

Literacy - Gatti89

Age Atkins50, Barclay87,

Broekmans54, Cohn93, Devold8,

Ediger145, Gatti89, Jessop132,

Khanderia103, Krousel-Wood68,

Laba94, Mo147, Ross95

Bhattacharya148, Jacobs96,

Kim146, Kleeberger90, Raebel92,

Ruppar107, Shah

Sex Jessop132, Maqutu91, Ross95 Bhattacharya148, Fawzi88,

Gatti89, Jacobs96,

Khanderia103, Kim146, Krousel-

Wood68, Laba94, Mo147,

Raebel92, Shah35

Race Kleeberger90, Krousel-Wood68,

Raebel92

Gatti89, Khanderia103

Marital status Devold8, Sajatovic114 Fawzi88, Khanderia103, Kim146,

Mo147

Social support network Dean116, Fraser99, Frain149

Private health insurance Raebel92 Akincigil, Khanderia103,

Kleeberger90, Laba

Health literacy level - Gatti89

Number of people in household Gatti89 Khanderia103, Kim146, Laba

Healthcare Team and System

Factors

Patient-provider relationship Fraser99, George100 Frain149

Provider knowledge George100 -

Follow-ups - Akincigil57, Kim146, Raebel92

Condition-Related Factors

Severity of disease/symptoms Khanderia103, Phillips102 Frain149, Jacobs96, Mo147,

Level of disability - Fraser99, Mo147

Co-morbidities Raebel92 Akincigil57, Barclay87, Jacobs96,

Kim146, Shah35

Duration of condition Mo147 Jacobs96

Cognitive impairment Barclay87, George100 , Jacobs96 -

Psychiatric disorders Dean116, Gatti89, Manning106,

Sajatovic114

Akincigil57, Bartlett150,

Jacobs96, Raebel92,

Anxiety Sundbom104 Jacobs96

Substance abuse Akincigil57, Barclay87, Cohn93,

Mazer151, Raebel92, Sajatovic114

Cohn93, Kleeberger90

15

Factor (cont.) Significant Association

(cont.)

No Association (cont.)

Therapy-Related Factors

Complexity of medical regimen

(Number and Frequency)

Akincigil57, Dean116, Devold8,

Llor110, Kleeberger90,

Laliberte111, Raebel92,

Ruppar107, Toy108

Gatti89, Jacobs96, Kim146,

Phillips102, Ross95, Ruppar107

Duration of treatment Mo147 Bhattacharya148, Burra115,

Kim146, Kleeberger90

Previous treatment failures - Bhattacharya148

Use of CAMs Dean116 -

Dosage form Brnabic152 -

Cost Castaldi112, Shah35 Fawzi88, Frain149, Raebel92

History of medication-taking Laba94 -

Access to medications - Khanderia103

Side effects Fawzi88, Laba94 George100, Kim146

Patient-Related Factors

Knowledge, Attitudes, Expectations George100 George (Expectations)100,

Kim146

Forgetfulness Addison67, Burra115, Dean116,

Gadkari46, McHorney105,

Sajatovic114,

-

Concerns about medicines

(Beliefs)

Berglund128, Fawzi88, Gatti89,

Laba94, Mardby4

Aakre123, Frain149, Ruppar107

Necessity of medicines (Beliefs) Berglund128, Bhattacharya148,

Burra115, Clifford153, Fawzi88,

Gatti89, Laba94, Ross95,

Ruppar107,120

Aakre123

Poor attendance to follow-ups Kleeberger90 -

Lifestyle (Change in Routine etc.) Burra115 George100

Manual dexterity George100 -

Self-efficacy Barclay87, Gatti89, Kim146 Fraser99

Personality Ediger145, Williams154 -

Missed prenatal vitamins Cohn93 -

Sleep quality Phillips102 Burra115

NB: The surnames of the first author of the papers have been used in this table. These papers are written in collaboration

with other authors (et al.)

16

1.5 Measuring Medication Adherence

Accurate measurement of medication-taking behaviour is required to identify non-adherence

and help inform interventions to support adherence. Methods to measure medication-taking

behaviour can be categorised into two broad groups: objective and subjective

measures.18,155,156

1.5.1 Objective Measures

Objective measures include: direct observations of medication-taking, measurement of

clinical outcomes, dose counts, pharmacy records, electronic monitoring of medication

administration (e.g. the Medication Event Monitoring System, MEMS), ingestible sensor (e.g.

Raisin SystemTM) and blood or urine drug concentrations.157-163 Objective measures can be

either direct (e.g. blood drug concentrations) or indirect (e.g. dose counts and pharmacy

records). These types of adherence measures can provide detail on dose administration

over time. Measuring clinical outcomes include blood pressure for patients on hypertension

medications, blood glucose levels and HbA1c levels for diabetes and viral suppression in

HIV.64,72,83,157 Counting the number of medicine doses remaining in the container can be

conducted at home or in clinic and may be announced or unannounced. Unannounced dose

counts tend to be more accurate because it reduces the chances of dose dumping.164

Information about prescription refills can be obtained from pharmacy records to provide a

measure of medication-taking behaviour over long periods of time.20,158 Electronic

monitoring (e.g. MEMS) can record the time of dose-taking and can provide detailed

information on medication-taking behaviour.165-167 A newer form of electronic monitoring

known as the DoPill® has 28 compartments which can contain multiple tablets in each slot.

The DoPill® electronic dispenser beeps and flashes to remind patients to take their

medicines and consists of sensors which can send signals to health professionals alerting

a dose has been released.161 The Raisin SystemTM recently developed by Proteus

Biomedical is an ingestible micro-sensor that can be incorporated into each oral solid

dosage form. The sensor can obtain information on date and time of ingestion and

communicates this data with an externally-worn seven-day wear adhesive monitor that can

be routed to a software program.163

17

Objective measures (excluding those that utilise clinical outcomes) have been shown to

better predict clinical outcomes compared to subjective measures of adherence.83,168-172 For

example, Wu et al. found that adherence measured by MEMS, but not by a self-report

adherence scale, independently predicted event-free survival in patients with heart failure.168

Objective measures have some limitations (Table 1.2). First, objective measures are more

expensive and may not always be applicable, particularly in a setting with limited

resources.162,173 Second, although the ultimate aim of any intervention is to improve clinical

outcomes, using clinical outcomes as a proxy of adherence can be impacted by variability

in patient response to medicines, independent of medication-taking behaviour. This poses

challenges in using clinical outcomes to validate measures of adherence.175 A lack of

change in a clinical outcome may occur in an individual who is adherent to their medication

due to other factors impacting on their disease. Individual clinical response to a medicine

can be affected by diet, lifestyle, family history, genes and renal function.20,67,71,168,174,175 For

example, a patient on antihypertensive therapy may have uncontrolled blood pressure

despite being adherent to their medication. This could be due to an increase in their dietary

salt intake, or increases in body weight or alcohol consumption.71,174,175 Furthermore, a

patient may have genetic differences in their drug metabolising enzymes resulting in either

lack of activation of the drug (e.g. clopidogrel) or rapid metabolism of the drug (e.g.

warfarin).175 Third, objective measures, when used alone, are unable to identify the type of

non-adherence or the patient-specific barriers to adherence. These measures offer little

insight into why a patient may be non-adherent and thus implementing an appropriate

intervention would be difficult.

18

Table 1.2 Advantages and disadvantages of objective measures of adherence

Adherence Measure Advantages Disadvantages

Direct observation of

medication-taking 176

- Considered most

accurate measure of

medication-taking

behaviour

- Impractical, particularly

in an outpatient setting

- Patients may not swallow

medication

Pharmacy prescription

dispensing records 158,177

-

- Low burden and efficient

- Inexpensive

- Can provide estimates in

large populations over

extended periods of time

- Can be used to assess

primary adherence as

dispensed prescription is

first step to measure

adherence

- Does not capture

detailed medication-

taking behaviour

- Estimates medication

possession and not

consumption.

- Cannot be used for

short-term regimens

- Not practical in real-time

- Limited to specific

location, requires closed

pharmacy system

Pill counts 156,176 - Accurate

- Inexpensive

- Can provide data over

extended periods of time

- Easy to conduct

- Possible risk of dose

dumping

- Potential bias from not

having all pills at the time

- Time-consuming

- Labour intensive

Drug concentrations in

biological fluids (e.g. blood,

urine) 66,176

- Accurate

- Expensive

- Difficult in community

setting

- Invasive

- Labour intensive

- Affected by dose, dose

timing and

pharmacokinetics and

drug interactions

Medication Event

Monitoring System (MEMS)

caps 159,165

- Accurate

- Records data and time

of bottle opening

- Provides continuous

data and real-time

tracking

- Considered gold

standard

- Non-invasive

- Expensive

- One cap per drug

- Not all medicines can be

packaged in a bottle

- Risk of malfunctioning

- Can over- or under-

report

- Patient may not swallow

medication

19

Adherence Measure

(cont.)

Advantages (cont.) Disadvantages (cont.)

Intelligent Drug

Administration System

(IDAS)166

- Provides visual and

audible reminders

- Has to be customised to

accommodate specific

blister packs

- Not all medicines are

packed in blisters

Smart Blister167

- Can be used on

commercial blisters

- Can easily download

adherence data

- Provides visual and

audible reminders

- Technology not sensitive

enough to detect

individual tablet opening

- Not all medicines are

packed in blisters

Ingestible sensor (Raisin

SystemTM by Proteus

Biomedical Inc.)163

- Accurate

- Can obtain data on

dose, data and time of

ingestion

- Can also monitor heart

rate, body temperature

and blood pressure

- Expensive

- Limited research and

experience on its use

- Ethical issues due to

invasive nature of

measure

Clinical outcome (e.g. blood

pressure control, HIV viral

load)64,72,83,157

- Important - May be confounded by

factors such as lifestyle,

diet and family history

- Labour intensive

- Time consuming

1.5.2 Subjective Measures

Subjective measures of adherence rely on patient’s reporting their medication-taking

behaviour, barriers to adherence and/or their beliefs associated with adherence. Most

subjective measures are simple, inexpensive and relatively easy to administer.178 Subjective

measures include caregiver or physician adherence reports, patient interviews, self-reports

and adherence scales.4,18,179-181 Subjective measures, for example adherence scales can

identify medication-taking behaviour, categorise patients into types of non-adherence,

explore beliefs associated with adherence and explore patient-specific barriers to and

determinants of adherence.18,33,117,181

20

1.5.3 Self-Report Adherence Scales

Many self-report adherence scales are available and these have been briefly described in

two systematic reviews.178,182 Adherence scales are relatively easier to administer and can

provide an alternative to, or supplement objective measures of adherence. However, self-

report scales rely on respondents to recall information and provide truthful answers and

hence are prone to recall bias and social desirability bias.179,182 Adherence scales vary in

the number of items, measure different aspects of adherence and are validated against

different measures of adherence. Table 1.3 lists adherence scales that have been validated:

defined as scales that have been tested against a comparison measure of medication-taking

behaviour (objective or subjective).

21

Table 1.3 Validated adherence scales

Name of Adherence Scale Abbreviation

Adherence Attitude Inventory 183 AAI

Adherence Self-Report Questionnaire 184 ASRQ

Adherence Starts with Knowledge-12 185 ASK-12

Adherence Starts with Knowledge-20 186 ASK-20

Adherence to Refills and Medications Scale 187 ARMS

Adherence Visual Analogue Scale 164 VAS

Barroso et al. 30-day Adherence Question 60 -

Beliefs about Medicines Questionnaire 117 BMQ

Beliefs and Behaviour Questionnaire 188 BBQ

Bell et al. Adherence Question 189 -

Brief Adherence Rating Scale 181 BARS

Brief Evaluation of Medication Influences and Beliefs 79 BEMIB

Brief Medication Questionnaire 190 -

Brooks Medication Adherence Scale 191 BMAS

Centre for Adherence Support Evaluation Adherence Index 192 CASE

Choo et al. Questionnaire 156 -

Compliance Questionnaire Rheumatology 193 CQR

Drug Attitude Inventory 53 DAI

Fodor et al. Adherence Questionnaire 194 -

Gehi et al. Adherence Question 12 -

Godin et al. Self-Reported Adherence Questionnaire 195 -

Grymonpre et al. Adherence Question 196 -

Hill-Bone Compliance Scale 10 55 -

Hill-Bone Compliance Scale 14 197 -

Immunosuppressant Therapy Adherence Scale 198 ITAS

Kerr et al. Adherence Question 199 -

Maastricht Utrecht Adherence in Hypertension Questionnaire 200 MUAH

Medication Adherence Assessment Tool 201 MAAT

Medication Adherence Questionnaire 18 MAQ

Medication Adherence Reasons Scale 202 -

Medication Adherence Rating Scale 51 MARS

Medication Adherence Rating Scale - 5 127 MARS-5

Medication Adherence Self-Efficacy Scale 203 MASES

Medication Adherence Self-Efficacy Scale - Revised 204 MASES-R

Morisky Medication Adherence Rating Scale 205 MMAS

Osteoporosis-Specific Morisky Medication Adherence Scale 206 OS-MMAS

Patterns of Asthma Medication Use Questionnaire 207 -

Paediatric Inhaler Adherence Questionnaire 208 PIAQ

Reported Adherence to Medication Scale 117 RAM

Self-Efficacy for Appropriate Medication Use Scale 209 SEAMS

Self-Reported Adherence Questionnaire 210 SERAD

Simplified Medication Adherence Questionnaire 211 SMAQ

22

Stages of Change for Adherence Measure 212 SOCA

Validated self-report adherence scales have been developed using a number of different

approaches (Figure 1.3). Adherence scales have been developed from literature reviews,

expert panels, patient focus groups, other adherence scales, a number of health models

and for clinical trials. Many of the adherence scales were developed from literature reviews

and expert panels. Adherence scales developed using these techniques (literature reviews

and expert panels) differ in focus (e.g. different diseases, identifying barriers as opposed to

identifying medication-taking behaviour) as these studies were conducted on the basis of

different study aims.190,197,207 Other scales based their survey questions on themes that

surface from patient focus groups.192,193,200 Some adherence scales (AAI, BBQ, BMQ and

BEMIB) were based on a number of different health models.79,117,183,188 Adherence scales,

such as MMAS, MARS, ARMS and ASRQ have derived from previously developed

adherence scales. The majority of the scales that came from previous adherence scales

have been developed based on the 4-item Morisky Medication Adherence Questionnaire

(MAQ).18,51,187,191,198,205,211 Some of the adherence scales utilise a combination of strategies;

for example, the SEAMS was based on a literature review, patient focus groups and an

expert panel.209

23

Figure 1.3 Adherence scales originate from a number of different sources (Original source unspecified: Barroso, Bell, Fodor, Grymonpre and VAS Scale)

24

Different self-report adherence scales measure different aspects of adherence: medication-

taking behaviour, barriers to adherence, beliefs associated with adherence or a combination

of these aspects.213 Adherence scales have been correlated with a number of different

comparison measures of medication-taking behaviour including electronic monitoring, pill

counts, healthcare outcomes and pharmacy refill records. Chapter Two presents a

systematic review of validated adherence scales and discusses the validation of adherence

scales and what aspects of adherence each explores.

There are numerous methods to measure adherence, but no single method performs well

on all criteria (e.g. ease of administration, inexpensive, accurate, quick to complete, well-

validated in many diseases).20,176 An accurate measure of medication adherence would be

able to identify patients who are non-adherent to their medication, and inform an intervention

to support adherence. The following section discusses the interventions that have been

implemented to improve adherence.

1.6 Interventions to Improve Adherence

1.6.1 Introduction

Many interventions have been implemented to improve medication adherence in patients

with chronic diseases. However, most interventions have not significantly improved

medication adherence or clinical outcomes.13-15,214-221 Interventions that show promise in

improving medication adherence were multifaceted interventions.217,222,223 These

interventions employ a number of different strategies to improve adherence. Multifaceted

interventions address a greater number of potential barriers to adherence and thus tend to

be more successful than single interventions.223 However, multifaceted interventions are

intensive and have only produced modest improvements in adherence and clinical

outcomes.13,15,217,223

25

Adherence interventions have largely been implemented on a non-targeted population, that

is most of these studies did not identify patient’s adherence to their medication prior to

inclusion in the study. Interventions are thus implemented on a population without knowing

if the patient is adherent or non-adherent to their medications.215,224-227 This means that

interventions are implemented on patients who may be adherent at the time the intervention

was employed; therefore, would observe no improvement in adherence. This may explain

why some studies of plausible adherence interventions have not demonstrated an

improvement in adherence. By identifying patients at greater risk of medication non-

adherence, interventions can be targeted to those who would most benefit.228 An example

of a targeted intervention is Measurement-Guided Medication Management (MGMM), which

uses MEMS data on the patient’s adherence as feedback to guide the discussion on

adherence and implementation of an intervention.214

As discussed in Section 1.4, patients are non-adherent due to many different reasons, and

may be subjected to different types of non-adherence concurrently (Section

1.2.4).1,18,87,89,90,93,96,100,114,115,145,147 Both are important to consider when selecting an

appropriate intervention to address non-adherence.33 Identifying the reasons for non-

adherence facilitates a strategy to address these reasons, which can be described as a

tailored intervention. In the literature, tailored interventions are described in a number of

different ways. Some interventions were “tailored” to a specific disease population.229 Others

have selected a specific type of intervention and “tailored” that intervention to the

patient.130,153,230-233 For example, Insel et al. individualised memory strategies to improve

adherence in older patients.230 Greater focus is required on identifying the primary cause for

the patient’s non-adherence and tailoring interventions to these specific reasons for non-

adherence.68,130,228,234 For example, forgetfulness is one of the most common reasons for

non-adherence; however, implementing a reminder intervention would not improve

adherence if the patient is non-adherent due to negative beliefs about the medicine.224,235

To improve the outcomes of adherence interventions, interventions should be targeted to

patients identified as non-adherent and tailored to the patient-specific reasons for non-

adherence.

26

1.6.2 Examples of Interventions Focusing on a Single Aspect of Adherence

Current adherence interventions can be classified into five main categories: reminder

systems, behavioural-counselling, social support, cognitive-educational and measurement-

guided interventions, according to Demonceau et al.214 Examples include dose

administration aids, telephone reminders, education about illness and motivational

interviewing.13,215 Below are some examples and outcomes of the adherence interventions

to date:

Reminder interventions

Reminder interventions may benefit those that forget to take their medications by reminding

them. There are many reminder interventions that have been implemented, including

reminder phone calls, texts, pagers, interactive voice response systems and treatment

simplification interventions.130,220,236-243 Reminder packaging (dose administration aids,

dosette boxes and dose sachets) assembles medicine doses into days and/or times when

the medication has to be taken. This has been shown to increase the proportion of doses

taken, leading to a significantly reduced diastolic blood pressure and also HbA1c levels.244

A study using MEMS which consisted of electronic medication reminder caps with

medication-taking recording cards significantly improved adherence by 17% and reduced

systolic and diastolic blood pressure by 4.8 and 8.6 mmHg, respectively.245 Postal reminders,

dose administration aids and both used in combination all significantly improved medication

adherence, measured using pharmacy refill records, in patients with hypertension.246 Short

text message reminders was shown to reduce the rate of missed doses and delayed doses,

according to self-report in the general population.238Telephone and early postal reminders

implemented on patients taking pravastatin did not significantly improve self-reported

adherence.235

Cue-dose training involves advising patients to use cues as reminders to take their

medicines; for example, meal times, alarms (incorporated in MEMS) and locating medicines

in more noticeable areas. Cue-dose training in patients with type 2 diabetes significantly

improved adherence to metformin, but did not improve diabetes control.247

Simplification of drug and dose regimen has consistently improved medication adherence.

14,15,240-243 A systematic review on interventions implemented to improve adherence in

27

patients with hypertension found that simplifying dosing regimens increased adherence in

seven out of nine studies, with a relative increase of 8 to 19.6%.15 Patients on once-daily

trandolapril had significantly better adherence compared to patients on twice-daily captopril

treatment for hypertension, as measured using MEMS.240 Self-report adherence was

significantly higher in patients taking sustained-release nicardipine twice daily than

conventional nicardipine three times daily.241 Patients treated with a single combination

tablet regimen for hypertension had significantly less cardiovascular events compared to

those taking the components individually. This retrospective cohort study identified patients

on a number of different combination therapies for hypertension found that single

combination tablet regimens compared to the individual component treatment led to a

reduction in hospital costs, as measured using pharmacy prescription refill data.234

Behavioural-counselling interventions

Behavioural-counselling adherence interventions aim to change medication-taking

behaviour by modifying beliefs and motivating patients to make positive changes. Many

adherence interventions have used behavioural-counselling strategies to improve

adherence.15,130,248,249 A systematic review showed that 10 out of 24 interventions led to

small improvements in medication adherence.15

Health coaching aims to promote positive health behaviour changes, by establishing the

patient’s goals and beliefs about treatments and helping the patient to attain these goals.

Person-to-person health coaching every three months and telephone health coaching every

month over 12 months in patients with hypertension significantly improved adherence, as

measured by dose counts.250 Health coaching patients with hypertension from health

professional students significantly improved adherence, as measured by the Brief

Medication Questionnaire.226

Motivational interviewing involves counselling patients to recognise the discrepancy

between the patient’s behaviour and goals in the hope of eliciting positive behavioural

changes.251 Motivational interviewing and cognitive approaches in a convenience sample of

patients with schizophrenia or major depression showed no significant improvement in

adherence, measured with an adherence scale (DAI).252 Using MEMS to measure

adherence, pharmacist-led motivational counselling in patients on a diuretic for heart failure

28

showed a significant improvement in adherence.221 The number of medicine doses taken

according to MEMS was significantly increased in patients with hypertension using

motivational interviewing.219

Personalised nurse-counselling on modifiable and unmodifiable cardiovascular risk factors

was shown to significantly improve self-reported adherence to statins and lower low-density

lipoprotein cholesterol.253

“Adherence Therapy” is a patient-centred approach that explores patient attitudes and

beliefs about medicines in a manner similar to motivational interviewing. Once negative

beliefs about medicines are identified, patients generate evidence to support these beliefs

and the therapist modifies these beliefs to improve adherence. Adherence Therapy has

mainly been tested in psychiatric illnesses, in particular schizophrenia. There is no standard

approach to Adherence Therapy; varying in length ranging from four to eight sessions lasting

20 minutes to three-and-a-half hours.129,254-258 The most promising study using Adherence

Therapy to improve medication adherence was targeted to patients who were non-adherent,

resulting in significantly improved blood pressure and adherence measured using dose

counts.129

Social support interventions

Social support interventions include family support and peer support groups.259-261 A study

demonstrated that a supportive family environment was associated with better adherence

to diabetes medications.261 A six-month American study found that peer counselling for

adolescents did not have an effect on self-reported treatment completion rates.262 Peer

support group therapy for adolescents with HIV showed no change in adherence, according

to physician reports.263 A five-month clinic-wide social marketing campaign was conducted

to improve adherence to antiretroviral therapy. The campaign did not demonstrate an

improvement in medication adherence according to self-reported adherence.264 An online

social support intervention involving an interface that allows participants on antiretroviral

therapy to interact, self-report their adherence and watch videos about living with HIV,

significantly improved self-reported adherence. By targeting the online social support

intervention to patients reporting “imperfect” adherence, this may have improved the

outcomes of the intervention.259

29

Cognitive-educational interventions

Poor knowledge has been associated with medication non-adherence. Cognitive-

educational interventions involves providing information to improve a patient’s knowledge

on their medications and illnesses to better inform their medication-taking behaviour. Some

cognitive-educational interventions have been shown to improve medication adherence,

however, results have been inconsistent.215,218,225,226 Patient education alone has been

largely unsuccessful in improving medication adherence.15,231,265-268 A trial involving nurse

counselling via telephone increased the proportion of children with latent tuberculosis

completing treatment from 65% to 94%.269 Nurse-delivered home visits providing information

on HIV and the importance of medication adherence was associated with an increased

likelihood of patients reporting 100% adherence.215 A study on asthma patients showed that

repeated instructions on inhalation techniques significantly improved adherence measured

using the BMAS.225 Pharmacy-based education and counselling on adherence did not

improve medication adherence, measured using pill counts.270 Educating patients on

adherence and their medication by a pharmacist via weekly telephone calls for 12 weeks

did not significantly improve adherence to lipid-lowering medications in the short-term (6

weeks and 12 weeks). However, long-term (12 months and 24 months) adherence was

improved according to dose counts.229 Educational videotapes containing information on the

prescribed medicine and the respective medical condition did not improve medication

adherence, according to pharmacy records, in patients with chronic disease.267 Enhanced

in-hospital counselling on medications and adherence barriers by pharmacists coupled with

communication of discharge medications to community pharmacists and physicians did not

significantly improve adherence to aspirin and statins, as measured using pharmacy

records.231 In comparison, patients who received counselling sessions with a community

pharmacist at the start of statin treatment demonstrated greater adherence according to

pharmacy records.271 A mailed newsletter discussing the importance of adherence and

lifestyle modifications showed no improvement in adherence, as measured using physician

reports.266 Automated telephone patient monitoring and counselling on adherence and blood

pressure control led to an increase in self-reported adherence and a significant decrease in

diastolic blood pressure.220 Meducation®, calendars listing information about cardiovascular

medications, such as medication name, dose, dose frequency and clinical indication, did not

significantly improve adherence as measured using prescription refill data and self-report.

The Meducation® intervention did not significantly improve blood pressure control or

cholesterol levels.272

30

Electronic Adherence Monitoring Feedback Interventions

Measurement-Guided Medication Management (MGMM) is an approach to using drug

dosing history data as feedback to patients on their medication-taking behaviour to improve

adherence.273 This information facilitates a focused discussion between a health

professional and their patient about their medication-taking behaviour, reinforcing other

adherence interventions. Electronic monitoring feedback interventions showed improvement

in adherence.214 MGMM interventions have relatively consistent outcomes in improving

adherence. Electronically compiled drug dosing histories provide detailed information on a

patient’s medication-taking behaviour that can assist health professionals in identifying and

addressing the reasons for poor medication-taking behaviour. Participants provided with

weekly feedback on their medication-taking behaviour obtained from MEMS and repeated

instructions on improving adherence to bupropion had a significant improvement in

adherence.274 A pharmaceutical care program involved reviewing compiled drug history

using MEMS by both the patient and pharmacist, significantly improved medication

adherence.275 Interventions that were based on discussion informed by adherence feedback

using electronically compiled medication-taking history have consistently improved

adherence to medications. These interventions involve some degree of tailoring

interventions to non-adherent patients.

1.7 Summary

This literature review has raised a number of key issues surrounding medication adherence

scales and interventions to improve adherence.

There are a large number of adherence scales available. Deciding which adherence scale

to use is a difficult task. An important factor to consider when selecting an adherence scale

is validity; however there is no single measure of validity for an adherence scale. Further,

how the scales measure adherence differs. To address some of the issues surrounding the

use of adherence scales, we conducted a systematic review of self-reported adherence

scales which have been validated against a comparison measure of adherence (Chapter

Two).

31

Interventions to improve medication adherence have not universally improved adherence.

As discussed in Section 1.6, interventions that have shown some improvement in adherence

were complex and improvements in adherence were only modest. We believe that part of

the reason for these inconsistent results is that interventions have not been sufficiently

targeted to patients who are non-adherent nor tailored to the patient-specific reasons for

non-adherence. Self-report adherence scales provide the opportunity to identify some of the

reasons for non-adherence and may be used in a similar manner to MEMS in a MGMM

approach. These scales can either directly assess the patient’s medication-taking behaviour

and/or attempt to identify barriers to good medication-taking behaviour, as discussed in

Chapter Two. This provides information on how best to target and tailor interventions to

improve adherence.

A quick and simple intervention that is tailored to non-adherent patients would be good to

improve adherence in practice. An intervention applicable to the clinical setting is practical,

easily incorporated into clinical practice and used in more than one disease population.

Current interventional studies on medication adherence tend to focus on one disease state

as this would minimise the variability of adherence and improve understanding of adherence

in that disease state.219,226,227,269,276-279

The literature review and systematic review of validated adherence scales will allow the

selection of adherence scales that will be able to identify non-adherent patients with chronic

cardiovascular disease and explore the patient-specific reasons for non-adherence.

Responses to the validated adherence scales will facilitate further discussion between the

patient and researcher, which will guide the implementation of a tailored strategy to improve

adherence. Patients diagnosed with hypertension, type II diabetes, dyslipidaemia or

cardiovascular disease will be included in the study. These medical conditions are common

and contribute extensively to the burden of chronic diseases.280

The aim of the thesis is to determine if a targeted and tailored intervention based on a

discussion informed by validated scales, would improve adherence to a recently initiated

cardiovascular medication.

32

It is hypothesised that:

H1 Targeting and tailoring an intervention based on a discussion informed by adherence

scales in participants identified as non-adherent using the MAQ, will improve adherence at

three months.

H2 Improvements in adherence at three months, identified by the MAQ, will be sustained at

six months.

H3 Adherence, and reasons for non-adherence, will change over time in all groups studied.

33

CHAPTER TWO: SYSTEMATIC REVIEW

OF VALIDATED SELF-REPORT

MEDICATION ADHERENCE SCALES

(PUBLISHED)

2.1 Introduction

Many self-report adherence scales are available. Adherence scales are relatively simple,

easy to administer and inexpensive. Adherence scales may provide information on a

patient’s medication-taking behaviour and may also provide the opportunity to identify some

of the barriers to adherence. The available adherence scales have been briefly described in

two reviews.178,182 Although these reviews identified and briefly described some of the

available adherence scales, these reviews did not provide detailed information on what

adherence scales measured and how they were validated. A systematic review of validated

self-report adherence scales was conducted to determine what adherence scales really

measured and how these scales have been validated. The following paper has been

published in the British Journal of Clinical Pharmacology.213

2.2 Published Paper


really measuring?: a systematic review. Br J Clin Pharmacol 2014;77(3):427-45.

2.2.1 Abstract

Background Medication non-adherence is a significant health problem. There are numerous

methods for measuring adherence, but no single method performs well on all criteria.

Objectives The purpose of this systematic review is to (i) identify self-report medication

adherence scales that have been correlated with comparison measures of medication-

taking behaviour, (ii) assess how these scales measure adherence and (iii) explore how

these adherence scales have been validated.

34

Method Cinahl and PubMed databases were used to search articles written in English on

the development or validation of medication adherence scales dating to August 2012. The

search terms used were medication adherence, medication non-adherence, medication

compliance and names of each scale. Data such as barriers identified and validation

comparison measures were extracted and compared.

Results Sixty articles were included in the review, which consisted of 43 adherence scales.

Adherence scales include items that either elicit information regarding the patient’s

medication-taking behaviour, and/or attempts to identify barriers to good medication-taking

behaviour or beliefs associated with adherence. The validation strategies employed

depended on whether the focus of the scale was to measure medication-taking behaviour

or identify barriers or beliefs.

Conclusions Supporting patients to be adherent requires information on their medication-

taking behaviour, barriers to adherence and beliefs about medicines. Adherence scales

have the potential to explore these aspects of adherence, but currently there has been a

greater focus on measuring medication-taking behaviour. Selecting the “right” adherence

scale(s) requires consideration of what needs to be measured and how (and in whom) the

scale has been validated.

2.2.2 Introduction

There are many effective medicines available to treat illness, but the benefits of these

medicines will only accrue to the patients that take them. The World Health Organisation 1

defines adherence as:

The extent to which a person’s behaviour – taking medication, following a diet, and/or

executing lifestyle changes, corresponds with agreed recommendations from a

health care provider.

Medication non-adherence is common, with studies in a range of settings identifying up to

50% of patients as non-adherent to a medicine.4,5,53,54,88 Poor medication adherence results

in adverse health outcomes3,12,55 and increased healthcare costs.3

Patients may be non-adherent due to different beliefs, barriers and a range of other factors.

Patients may intentionally decide not to take their medicines based on well-informed or

35

mistaken beliefs about the benefits and risks of their medicines.49,117 Patients can

unintentionally non-adhere to medicines due to forgetfulness, carelessness, health literacy

and socioeconomic factors. Non-adherence can also occur at different stages of the

medication-taking process. A patient may exhibit non-adherence at the initiation of treatment,

during treatment (where the patient may exhibit sub-optimal implementation of the treatment

regimen), or the patient may discontinue the treatment early.38 Strong evidence for any

single approach to improve medication adherence is lacking, but interventions that are

tailored to a patient’s specific reasons and stage of non-adherence can be expected to better

support good medication-taking behaviour.13-15,216,236

Adherence to medicines is measured for different purposes. Common reasons to measure

adherence include better informing the assessment of an intervention (as unrecognised non-

adherence may lead to an underestimation of possible treatment effects); determining

influences on adherence to medicines in people with specific disease states (such as

hypertension or HIV); and identifying patients requiring education or support to improve

medication use. Ideally, clinicians and researchers wanting a comprehensive assessment

of adherence need measures that are inexpensive, relatively easy to administer, accurately

identify the patient’s current medication-taking behaviour, and any barriers or beliefs that

influence the patient’s use of medicines.

There are a number of ways of measuring adherence. Objective measures, including

measurement of clinical outcomes, dose counts, pharmacy records, electronic monitoring of

medication administration (e.g. the Medication Event Monitoring System, MEMS) and drug

concentrations,157-160 seemingly provide the best measure of a patient’s medication-taking

behaviour in many contexts.83,168-172 It is important to recognise that, while objective, most

of these measures have drawbacks. MEMS, arguably the best objective measure of

medication-taking behaviour, records package opening or device actuation, rather than

actual medication-taking; the possibility of intentional dose dumping remains. MEMS, or

MEMS-like devices, are also expensive and not readily available for some dose forms 159,165-

167. While clinical outcomes are the ultimate aim of any intervention to improve adherence,

the use of clinical outcomes as a proxy of adherence can be confounded by disease-specific

factors independent of medication-taking behaviour.

Subjective measures of adherence include physician or family reports, patient interviews

and self-report adherence scales.117,179-181,205 These measures have the potential to identify

the specific reasons for a patient’s non-adherence. Subjective measures can be relatively

simple to use and are less expensive; however, are prone to recall bias and the prospect

36

that respondents provide answers that conform to their perceived expectations of their

interviewer.281,282 There are a large number of adherence scales that are suitable for use in

research or clinical settings. A number of well-validated adherence scales have been

strongly correlated with objective measures of adherence in several different populations of

patients.

There is a need for scales that are easy to administer and correctly identify medication-

taking behaviour, key barriers to adherence and beliefs associated with medication use that

influence adherence. There have been few systematic attempts to describe the available

self-report adherence scales and their benefits and limitations with respect to both

medication-taking behaviour and the identification of barriers and beliefs associated with

adherence.178,182 The aim of this review is to (i) identify self-report medication adherence

scales that have been correlated with a comparison measure of medication-taking behaviour,

(ii) assess how these scales measure adherence and (iii) explore how these adherence

scales have been validated.

2.2.3 Methods

A literature search for adherence scales was conducted using Cinahl and PubMed electronic

databases. The initial search terms used to identify the articles were: medication adherence,

medication non-adherence, medication compliance and medication non-compliance. This

broad database search identified the names of the adherence scales, which were then

searched individually. This search was limited to English-language studies published

between 1981 and 2012. The date of the last search was on the 1st August, 2012. The

reference lists of the relevant studies were searched to identify additional articles.

Inclusion and exclusion criteria

Adherence scales were included if they had been correlated against a comparison measure

(objective or subjective) of medication-taking behaviour. To be included there needed to be

a full-text article, written in the English-language on the development and/or validation of the

adherence scale. Studies that used the self-report adherence scale without correlating the

adherence scale against a comparison measure of medication-taking behaviour were

excluded. The list of scales was reviewed for completeness with two adherence researchers.

37

Data extraction and analysis

The data extracted from the studies included: the number of items in the adherence scale,

study setting, criteria for identifying non-adherence, response rate and time to complete the

adherence scale. Each validated self-report adherence scale was categorised according to

whether it contained items that elicited information on (i) specific medication-taking

behaviours: dose taken, dose frequency, dose administration and prescription refills; (ii)

barriers to adherence: e.g. forgetfulness, treatment complexity and side effects; and/or (iii)

beliefs associated with adherence: e.g. perceived necessity of medicines and concerns

about medicines. Adherence scales were also assessed on whether or not the scale

identified the initiation, implementation or discontinuation of treatment as per the taxonomy

proposed by Vrijens et al.38

To assess the quality of the correlation study, the following criteria were extracted: how the

adherence scale was administered, sample size, the adherence comparison measures,

internal consistency, and where reported, the sensitivity and specificity of the scale against

a standard of adherence. Information on criterion, content and construct validity was also

extracted to assess the validation of the adherence scale. The results of the studies were

reviewed and compared.

2.2.4 Results

Search Strategy

The study selection process is illustrated in Figure 2.1. Twenty-one articles were retrieved

using the Cinahl search engine and the remaining were identified using the same strategy

in the PubMed database and from reference lists. Some adherence scales were excluded,

as shown in Table 2.1.

38

Figure 2.1 Flow chart of study selection process

39

Table 2.1 Excluded self-report adherence scales

Excluded Adherence Scale Reason for Exclusion

Adult AIDS Clinical Trials Group

(AACTG) Adherence Scale 283

No validation studies were found in the

literature search

Basel Assessment of Adherence Scale

(BAAS) 284

No validation studies were found in

literature search.

Medication Adherence Evaluation Scale

(MASS) 285

No full-text article available

Medication Adherence Measure (MAM)

interview 180

Semi-structured interview and thus was

not consistent between patients

Multicentre Aids Cohort Study (MACS)

adherence form 90

No adherence comparison measure

The literature search retrieved 60 articles that met the inclusion criteria (Figure 2.1,

Table 2.2). The sample size of the studies ranged from 40 to 1367 (Table 2.3).190,211

The median sample size of the studies was 228. Twenty-two of the studies reported

the response rate, ranging from 29 to 98%. The average response rate was 72% (Table

2.3). Forty-three self-report adherence scales were identified from the included studies.

40

Table 2.2 Comparing the self-report adherence scales

Self-Report Adherence Scale Based On Number of

Questions

Time to Complete

Barriers Identified

Stage of Medication-

Taking Identified

Number of Development and

Correlation Studies

GROUP 1: Medication-Taking Behaviour

Adherence Self-Report Questionnaire (ASRQ) 184

CQR 1 Not reported

- Nil Implementation 2

Adherence Visual Analogue Scale (VAS) Computerised 164

Literature review

1 Not reported


Brief Adherence Rating Scale (BARS) 181 CATIE trial 4 Not reported


Barroso et al. 30-day Adherence Question 60 Did not specify 1 Not reported


Bell et al. Adherence Question 189 Did not specify 1 Not reported


Centre for Adherence Support Evaluation (CASE) Adherence Index 192

Literature review

3 Not reported


Gehi et al. Adherence Question 12 Expertise 1 Not reported


Grymonpre et al. Adherence Question 196 Did not specify 1 Not reported


Kerr et al. Adherence Question 199 Expertise 1 Not reported


Medication Adherence Report Scale – 5 (MARS-5) 127,286

MARS-10 5 Not reported

- Nil Implementation Discontinuation

3

41

Stages of Change for Adherence (SOCA) 212 Stages of Change model

2 Not reported

- Stages of change

Initiation Implementation

1

GROUP 2: Medication-Taking Behaviour AND Barriers

Adherence to Refills and Medications Scale (ARMS) 187

Literature review, MAQ and Hill-Bone Compliance Scale

12 Not reported

- Correct administration

- Forgetfulness - Prescription

refill ability

Implementation Discontinuation

1

Adherence Starts with Knowledge-12 (ASK-12) 185

ASK-20 12 Not reported

- Patient-perceived barriers

- Inconvenience

- Forgetfulness - Medication

beliefs


1

Adherence Starts with Knowledge-20 (ASK-20) 186

Literature review, patient focus groups and expert panel input

20 Not reported

- Medication-taking behaviour

- Patient-perceived barriers


2

Brief Medication Questionnaire 190 Literature review and patient feedback

9 Not reported

- Evaluates regimen

- Medication-taking problems

Implementation 1

Brooks Medication Adherence Scale (BMAS) 191

MAQ 4 Less than 5 minutes

- Forgetfulness - Carelessness


2

42

- Adverse effects and efficacy

Choo et. al. 5-item Questionnaire 156 Brief Medication Questionnaire

5 Not reported

- Unintentional and intentional non-adherence

Implementation 1

Fodor et al. Adherence Questionnaire 194 Did not specify 9 Not reported

- Blood pressure awareness


1

Godin et al. Self-Reported Adherence Questionnaire 195

Expertise 6 5 minutes - Barriers to adherence

Implementation 1

Hill-Bone Compliance Scale – 10 55 The Hill-Bone Compliance Scale - 14

10 Not reported

- Adherence - Appointment-

making - Sodium intake

Implementation 1

Hill-Bone Compliance Scale – 14 197 Literature review and Clinical expertise

14 5 minutes - Adherence - Appointment-

making - Sodium intake

Implementation 1

Immunosuppressant Therapy Adherence Scale (ITAS) 198

MAQ 4 Less than 5 minutes

- Forgetfulness - Carelessness - Adverse

effects


1

Medication Adherence Assessment Tool (MAAT) 201

Literature review and Expert clinicians

12 Not reported

- Previous history

- Adverse effects

- Access to medications

Implementation 1

43

Morisky Medication Adherence Scale (MMAS) 205

MAQ 8 Not reported

- Forgetfulness - Medication-

taking behaviour

- Adverse effects and problems


3

Osteoporosis-Specific Morisky Medication Adherence Scale (OS-MMAS) 206

MMAS 8 Not reported


taking behaviour

- Adverse effects and problems


1

Pediatric Inhaler Adherence Questionnaire (PIAQ) 208

Literature review, expertise and focus groups,

6 1 to 3 minutes

- Missed and additional doses

- Barriers to adherence

Implementation 1

Reported Adherence to Medicine (RAM) Scale 117

Literature review

4 Not reported

- Forgetfulness - Dose

adjustments

Implementation 2

Self-Reported Adherence (SERAD) Questionnaire 210

SERAD study 13 Not reported

- Dose frequency adherence

- Barriers to adherence

Implementation 1

Simplified Medication Adherence Questionnaire (SMAQ) 211

MAQ 6 Not reported

- Forgetfulness - Adverse

effects


1

44

The Patterns of Asthma Medication Use Questionnaire 207

Literature review, Expertise

5 Not reported


taking strategy

Implementation 1

GROUP 3: Barriers to Adherence

Adherence Attitude Inventory (AAI) 183

Health Belief Model, Health Promotion Model, Reasoned Action

28

Not reported

- Cognitive functioning

- Patient-Provider

- Self-efficacy - Commitment

Implementation 1

Medication Adherence Questionnaire (MAQ) 18

5-item survey by Green et al.

4 Not reported

- Forgetfulness and Carelessness

- Adverse effects and Efficacy


8

Medication Adherence Self-Efficacy Scale (MASES) 203

Patient interviews

26 Not reported

- Self-efficacy - Access to

medications - Adverse

effects - Lifestyle

barriers

Implementation 1

Medication Adherence Self-Efficacy Scale Revised (MASES-R) 204

MASES 13 Not reported

- Self-efficacy - Lifestyle

barriers - Adverse

effects

Implementation 1

45

Medication Adherence Reasons Scale 202 Literature review

15 Not reported

- Managing issues

- Beliefs - Multiple

medication issues

- Availability issues

- Forgetfulness


1

The Self-Efficacy for Appropriate Medication Use Scale (SEAMS) 209

Literature, expertise and patient interviews

13 Not reported

- Specific problem areas

- Self-efficacy

Nil

1

GROUP 4: Beliefs associated with Adherence

Beliefs about Medicines Questionnaire 117 Health Belief Model and Patient Beliefs

18 Not reported

- Medication necessity beliefs

- Medication concerns

Nil 4

Drug Attitude Inventory (DAI) 53 Literature review and patient reports

30 Not reported

- Attitudes towards medications

- Beliefs on medications

Discontinuation 1

GROUP 5: Barriers AND Beliefs

Beliefs and Behaviour Questionnaire (BBQ) 188

Interviews of COPD patients

30 Not reported

- Beliefs - Experiences

Nil 1

Brief Evaluation of Medication Influences and Beliefs (BEMIB) 79

Health Belief Model and Patient/

8 Less than 5 minutes

- Forgetfulness - Access to

medications

Implementation 1

46

Investigator feedback

- Support network

- Benefits of medication

Compliance Questionnaire Rheumatology (CQR) 287

Patient interviews

19 ~ 12 minutes

- Forgetfulness - Value of

doctor instructions

Implementation 2

Maastricht Utrecht Adherence in Hypertension (MUAH) Questionnaire 200

Patient interviews

25 Average 25 minutes

- Medication attitude

- Discipline and aversions

- Coping with health problems

Implementation 1

Medication Adherence Report Scale (MARS) 51

MAQ and DAI 10 Not reported

- Forgetfulness - Adverse

effects - Value of

medication - Behaviour

and attitudes


2

47

Content of the scales

The adherence scales can be categorised into five groups based on the information they

seek to elicit (the number of scales is given in parentheses, full details in Table 2.2): Group

1 scales seek information only on medication-taking behaviour (11), Group 2 scales seek

information on medication-taking behaviour and barriers to adherence (19), Group 3 scales

seek information only on barriers to adherence (6), Group 4 scales seek information only

on beliefs associated with adherence (2) and Group 5 scales seek information on barriers

and beliefs associated with adherence (5).

Thirty of 43 scales contained items that asked specific questions about medication-taking

behaviour (Group 1 and 2). Most of these adherence scales measure the number of doses

taken12,42,181,184-186,189,195,196,199,206,208 and contain items such as “how many days over the

past month did you take less than prescribed?181” and “did you miss a tablet yesterday? 189”

Other adherence scales measuring medication-taking behaviour do so through exploring the

frequency of patients not refilling their prescription on time.185-187,190

Twenty adherence scales measuring medication-taking behaviour specified a timeframe for

the questions. The timeframe specified ranged from one day to 12

months.12,60,156,164,181,184,190-192,195,198,212 189,199,205-208,210,211

Thirty scales contained items that elicited information on barriers to, and determinants of

adherence (Group 2, 3 and 5). Some of these adherence scales are disease-specific and

thus explore common barriers that may influence adherence in these disease

populations.191,193,206-208 For example, the Pediatric Inhaler Adherence Questionnaire (PIAQ)

explores adherence in patients with asthma and assesses the patient’s difficulty in using

asthma inhalers and the cost of inhalers.208 Most of these adherence scales explore

forgetfulness as a barrier to adherence and identify some of the situations where

forgetfulness may be more common, such as when working or travelling.55,183,197,203,209 Some

adherence scales also explore physical barriers to adherence, such as vision problems,

dexterity issues and dysphagia.190,202,208

Seven scales elicited information on the patient’s beliefs about their medicines that may

relate to adherence (Group 4 and 5). These scales included items identifying beliefs that

medicines are necessary, harmful and unnatural.51,53,79,117,188,193,200 For example, the Beliefs

about Medicines Questionnaire explores whether the patient holds beliefs that their

medicines are necessary as well as whether they have any concerns about their medicines.

48

Forty of the 43 scales contained items that sought to identify aspects of adherence that are

consistent with the taxonomy provided by Vrijens et al.38 Most scales contain items that seek

to assess the extent of implementation of a dosing regimen (39/43) (Table 2.2). Thirteen of

the scales also contain items that seek to identify the discontinuation of treatment.18,185-

187,191,194,198,202,205,206,211,286,288 The DAI contained items that sought information on

discontinuation (alone),53 and the SOCA scale identified the initiation of treatment.212 Three

adherence scales do not contain any items that seek to identify the initiation, implementation

or discontinuation of treatment.117,188,209

Administration of the scales

The adherence scales have been administered in different ways. Indeed, for the scales with

more than one validation or correlation study, the additional studies often administered the

scale in a slightly different way. Details of who completed the scale (i.e. patient, clinician or

researcher) and where the scale was administered are provided in Table 2.3. There was a

roughly even split between studies that requested the patient to complete the scale and

those that had the researcher or clinician complete the scale in consultation with the patient.

The location of administration (clinic, home, via telephone or internet) varied between the

scales (as reported in Table 2.3). The time to complete the scale was reported in eight of

the 43 adherence scales. Reported times varied from less than five minutes79,191,198,208 to

approximately 25 minutes (Table 2.2).200 The scales taking less than five minutes to

complete consisted of 4 to 14 items. Twelve minutes was required to complete a 19-item

scale and 25 minutes to complete a 25-item scale.200,287

49

Table 2.3 Self-report adherence scales - administration, response and validation

Self-Report

Adherence Scale

Reference

Number

How Scale was

Administered

Response

Rate

Internal

Consistency

Sensitivity Specificity Correlation

(Criterion

Validity)

Comparison

Measure of

Adherence

Sample

Size

GROUP 1: Medication-Taking Behaviour

Adherence Self-

Report

Questionnaire

(ASRQ)

184

289

Clinician-administered

(Other HCP)


(Primary physician)

Not

reported

53%

Not reported

Not reported

Not reported

Not reported

Not reported

Not reported

Significant

Not

significant

Electronic

monitoring

(MEMS)

MEMS and Other

scale (VAS)

245

78

Adherence Visual

Analogue Scale

(VAS)

Computerised

164 Self-administered

(Home, Internet)

Not

reported

Not reported Not reported Not reported Significant Dose counts and

Clinical outcome

(Viral load)

290

Brief Adherence

Rating Scale

(BARS)

181 Researcher-

administered (Clinic)

Not

reported

α = 0.92 0.73 0.74 Significant MEMS 61

Barroso et al. 30-

day Adherence

Question

60 Researcher-


Not

reported

Not reported Not reported Not reported Significant Clinical outcome

(Viral load)

93

Bell et al.

Adherence

Question


(Clinic, Absent)

80% Not reported Not reported Not reported Not

significant

MEMS and Dose

count

80

50

Centre for

Adherence

Support

Evaluation

(CASE)

Adherence Index

192 Clinician-administered

(Primary physician)

Not

reported

Not reported 0.70 0.71 Significant Clinical outcome

(Viral load) and

Self-report

524

Gehi et al.

Adherence

Question

12 Researcher-


Not

reported


(Cardiovascular

events)

1015

Grymonpre et al.

Adherence

Question

196 Researcher-

administered (Home)

Not

reported

Not reported Not reported Not reported Significant Pharmacy records

and Dose counts

135

Kerr et al.

Question

199 Researcher-


Not

reported

Not reported Not reported Not reported Not

significant

Pharmacy records 88

Medication

Adherence

Report Scale – 5

(MARS-5) 127

5

286


(Primary physician)

Self-administered

(Clinic, Present)

Not

reported

Not

reported

Not reported

α = 0.78

0.085

Not reported

0.97

Not reported

Not

significant

Significant

Pharmacy records

Drug levels and

Self-report

128

255

Stages of

Change for

Adherence

(SOCA)


(Clinic, Absent)

Not

reported

Not reported Not reported Not reported Significant MEMS and Other

scale (BMAS)

731

GROUP 2: Medication-Taking Behaviour AND Barriers

Adherence to

Refills and

Medications

Scale (ARMS)

187 Researcher-


89% α = 0.81 Not reported Not reported Significant Clinical outcome

(BP control),

Pharmacy records

and Scale (MAQ)

435

51

Adherence Starts

with Knowledge-

12 (ASK-12)


(Clinic, Absent)

Not

reported

α = 0.75 Not reported Not reported Significant Pharmacy record

and Other scale

(MAQ)

112

Adherence Starts

with Knowledge-

20 (ASK-20)

186

290

Self-administered

(Home, Internet)

Self-administered

(Clinic, Present)

Not

reported

Not

reported

α = 0.85

α = 0.76

Not reported

Not reported

Not reported

Not reported

Significant

Significant

(Scale only)

Self-report

Pharmacy records

and Scale (MAQ)

605

112

Brief Medication

Questionnaire

190 Researcher-


92% Not reported 0.80 1.00 Significant MEMS 43

Brooks

Medication

Adherence Scale

(BMAS)

191

291

Self-administered

(Unclear)

Self-administered

(Home)

86%

63%

α = 0.69

α = 0.86

Not reported

Not reported

Not reported

Not reported

-

Significant

Nil

Pharmacy records

and Self-report

294

98

Choo et. al. 5-

item

Questionnaire

156 Researcher-

administered

(Telephone)

Not

reported

Not reported Not reported Not reported Significant MEMS 286

Fodor et al.

Adherence

Questionnaire

194 Researcher-


Not

reported


(BP control)

359

Godin et al. Self-

Reported

Adherence

Questionnaire


(Clinic, Absent)

Not

reported

Not reported 0.71 0.72 Not

significant

Clinical outcome

(Viral

suppression)

256

Hill-Bone

Compliance

Scale – 10

55 Researcher- and self-


Not

reported

α = 0.79 Not reported Not reported Significant Clinical outcome

(BP control)

98

52

Hill-Bone

Compliance

Scale – 14

197 Researcher- and self-


Not

reported

α = 0.84 Not reported Not reported Significant Clinical outcome

(BP control)

718

Immunosuppress

ant Therapy

Adherence Scale

(ITAS)


(Home)

91% α = 0.81 Not reported Not reported Significant

(all)

Pharmacy

records, Drug

levels and Clinical

outcome

(Rejection)

222

Medication

Adherence

Assessment Tool

(MAAT)


(Clinic)

29% α = 0.80 Not reported Not reported Significant Pharmacy records 289

Morisky

Medication

Adherence Scale

(MMAS)

205

158

292

Researcher-


Self-administered

(Unclear)

Researcher-


98%

66%

82%

α = 0.83

Not reported

α = 0.56

0.93

Not reported

0.73

0.53

Not reported

0.36

Significant

Significant

Significant

Clinical outcome

(BP control)

Pharmacy records

Pharmacy records

1367

87

151

Osteoporosis-

Specific Morisky

Medication

Adherence Scale

(OS-MMAS)


(Home)


Other scale

(Beliefs about

Medicines

Questionnaire)

197

Pediatric Inhaler

Adherence

Questionnaire

(PIAQ)


(Clinic, Absent)

Not

reported

Not reported 0.63 0.91

Significant Dose counts 64

53

Reported

Adherence to

Medicine (RAM)

Scale

117

42

Self-administered

(Clinic, Absent)

Self-administered

(Home)

Not

reported

Not

reported

α = 0.72

Not reported

Not reported

Not reported

Not reported

Not reported

-

Significant

Nil

Other scale

(Beliefs about

Medicines

Questionnaire)

524

271

Self-Reported

Adherence

(SERAD)

Questionnaire

210 Researcher-


Not

reported

Not reported Not reported Not reported Significant

(all)

MEMS, Dose

counts and Drug

levels

530

Simplified

Medication

Adherence

Questionnaire

(SMAQ)

211 Clinician-administered

(Primary physician)

Not

reported

α = 0.75 0.72 0.91 Significant

(all)

Electronic

monitoring

(MEMS) and

Clinical outcome

(Viral load)

40

The Patterns of

Asthma

Medication Use

Questionnaire


(Home)

70% Not reported Not reported Not reported Significant

(all)

Pharmacy records

and Clinical

outcome

(Asthma)

176

GROUP 3: Barriers to

Adherence

Adherence

Attitude Inventory

(AAI)


(Clinic, Absent)

Not

reported

α = 0.90 Not reported Not reported Not

significant

Self-report 165

54

Medication

Adherence

Questionnaire

(MAQ)

18

293

5

294

72

295

37

296

Researcher-


Researcher-



(Primary physician)

Researcher-


Researcher-


Researcher-

administered (Home)

Researcher-


Researcher-


73%

Not

reported

Not

reported

Not

reported

32%

88%

Not

reported

81%

α = 0.61

α = 0.32

Not reported

Not reported

Not reported

α = 0.42

Not reported

α = 0.62

0.81

Not reported

0.32

Not reported

Not reported

Not reported

Not reported

Not reported

0.44

Not reported

0.73

Not reported

Not reported

Not reported

Not reported

Not reported

Significant

Significant

Not

significant

Significant

Significant

Not

significant

Significant

Significant

Clinical outcome

(BP control)

Pharmacy records

Pharmacy records

MEMS, Dose

counts and Drug

levels

Clinical outcome

(Diabetes control)

Dose counts

Dose counts

Clinical outcome

(Diabetes control)

290

377

128

385

186

319

413

294

Medication

Adherence Self-

Efficacy Scale

(MASES)


(Unclear)

Not

reported

α = 0.95 Not reported Not reported Not

significant

Clinical outcome

(BP control)

72

55

Medication

Adherence Self-

Efficacy Scale

Revised

(MASES-R)


(Clinic, Present)

Not

reported

α = 0.91 Not reported Not reported Significant MEMS and Other

scale (MAQ)

168

Medication

Adherence

Reasons Scale


(Home, Internet)

Not

reported

α = 0.65 Not reported Not reported Significant Other scale

(MAQ)

840

Self-Efficacy for

Appropriate

Medication Use

Scale (SEAMS)


(Clinic)

Not

reported

α = 0.89 Not reported Not reported Significant Other scale

(MAQ)

436

Beliefs about

Medicines

Questionnaire

117

4

124

89

Self-administered

(Clinic, Absent)

Self-administered

(Clinic, Absent)

Self-administered

(Clinic)

Self-administered

(Clinic, Present)

Not

reported

57%

Not

reported

93%

α = 0.70

Not reported

α = 0.73

Not reported

Not reported

Not reported

Not reported

Not reported

Not reported

Not reported

Not reported

Not reported

Significant

Significant

Significant

Significant

Other scale

(RAM)

Other scale

(MARS-5)

Other scale

(MAQ)

Other scale

(MMAS)

524

324

192

275

Drug Attitude

Inventory (DAI)


(Home)

Not

reported

α = 0.93 0.72 0.63 Significant Therapist report 150

56

Legend: Home – completed adherence scale at home; Clinic – completed adherence scale in clinic, researcher or clinician may be present or absent while patient fills out form; Telephone – patients completed

adherence scale over the telephone; Primary physician = Patient’s usual physician; Other HCP = Other health care professionals looking after patient; α = Cronbach’s alpha of reliability; BP = Blood

pressure

GROUP 5: Barriers AND

Beliefs

Beliefs and

Behaviour

Questionnaire

(BBQ)


(Home, Post)

53% α = 0.65 Not reported Not reported Significant Other scale

(MARS)

276

Brief Evaluation

of Medication

Influences and

Beliefs (BEMIB)


(Clinic, Absent)

Not

reported

α = 0.63 0.83 0.71 Not

significant

Pharmacy records

and Other scale

(DAI)

63

Compliance

Questionnaire

Rheumatology

(CQR)

193

287

Researcher-

administered (Home)

Self-administered

(Home)

Not

reported

82%

α = 0.71

Not reported

0.98

0.62

0.67

0.95

Significant

Significant

Self-report

MEMS

127

127

Maastricht

Utrecht

Adherence in

Hypertension

(MUAH)

200 Researcher-



(all)

MEMS, Pharmacy

records and Other

scale (Brief

Medication

Questionnaire)

255

Medication

Adherence

Report Scale

(MARS)

51

297

Self-administered

(Clinic, Absent)

Self-administered

(Clinic, Absent)

Not

reported

Not

reported

α = 0.75

α = 0.62

Not reported

Not reported

Not reported

Not reported

Significant

(Drug

levels only)

Significant

Drug levels or

Caregiver report

Caregiver report

66

277

57

Figure 2.2 illustrates the conditions in which the scales have been validated. Most of the

adherence scales have been validated in a single disease population (Figure

2.2).12,53,55,60,156,187,189-192,194,195,197-199,208,210 The Medicines Adherence Questionnaire (MAQ),

which is a simple 4-item questionnaire, has been validated in a broad range of diseases,

including hypertension, dyslipidaemia, heart failure and Parkinson’s disease.18,37,293,294

58

Figure 2.2 Disease populations used to validate self-report adherence scales

59

Approaches to assessing self-report adherence scales

Assessing the validity of self-report adherence scales differed among the 60 included

studies. Details of the studies, assessment of internal consistency, comparison measures

and whether the scale was significantly correlated to the comparison measure is provided

in Table 2.3. Similar approaches to validation were seen from scales with similar content.

Medication-taking behaviour

The primary method for assessing Group 1 and Group 2 scales was to determine the

correlation between the scale and an objective measure of adherence. Twenty-eight of the

30 scales included in Group 1 and 2 assessed how well the scale correlated with an objective

measure of adherence, eight of these scales have been assessed against MEMS and 12

against clinical outcomes (Figure 2.3).

60

Figure 2.3 Comparison measures of medication-taking behaviour used to validate the self-report adherence scales

61

Barriers and beliefs

Scales in Groups 3–5 were more likely to rely on alternative approaches to validation.

Content validity was typically assessed via a panel of subject matter experts. A range of

approaches were utilised for construct validity, including item analysis against tools validated

to elicit specific types of health beliefs and factor analyses of responses to other scales or

semi-structured interviews.

Three of the six Group 3 scales (scales that contain items that elicit information on barriers

to adherence only) have been assessed against an objective measure of adherence (one

using MEMS, one using clinical outcomes and one using MEMS and clinical outcomes). All

six of these scales have been tested for content validity18,183,202-204,209 and four have also

been tested for construct validity.18,183,202,203

Adherence scales that solely focus on eliciting information regarding a patient’s beliefs about

their medicines (Group 4) have not been assessed against objective measures of adherence.

The Beliefs about Medicines Questionnaire and DAI have been significantly correlated with

other adherence scales (Table 2.3). Both scales have been tested for content validity, in

addition the Beliefs about Medicines Questionnaire has also been tested for construct

validity.53,117

Two out of the five Group 5 scales (beliefs and barriers) have assessed the correlation

between the scale and an objective measure of adherence (both against MEMS). All five of

the adherence scales have been correlated with subjective measures: other scale (n=3),

self-report (n=1) and caregiver reports (n=1). Four of these adherence scales have also

been correlated with objective measures of adherence (Figure 2.3). All of these adherence

scales have been tested for content validity and three (BBQ, BEMIB and MARS-10) have

been tested for construct validity.51,79,188

Identifying Non-Adherence

Many self-report adherence scales have recommended cut-offs for identifying non-adherent

patients. Twenty-eight scales categorised medication adherence by determining the overall

score and separating the population into two groups: adherent and non-

adherent.12,42,53,60,79,156,181,183,185-187,189,191-199,201,204,207-211 Where reported, the cut-off point to

identify non-adherence is most commonly the score that corresponds to patients that took

80% of their medicines as ascertained by an objective measure of adherence such as

62

MEMS. Some scales, such as the Beliefs and Behaviour Questionnaire (BBQ),188 suggest

a cut-off point that corresponds to the score of another self-report adherence scale which

has been seen to correspond to patients that took 80% of their medicines according to an

objective measure. Other adherence scales, such as the DAI, AAI and MASES-R first split

the population into adherent and non-adherent based upon responses to questions about

whether medicines were taken or not, and then compared the mean scores of the adherence

scales to determine the cut-off.53,183,204 The SERAD and Gehi et al. Adherence Question

contain direct medication-taking behaviour questions and answers to these questions are

utilised to determine the percentage of adherence and thus dichotomise adherence.12,210

A small number of adherence scales have taken a different approach at assigning the

adherence cut-off. The MAQ, MMAS, Brief Medication Questionnaire, ASRQ and VAS

divided non-adherence into more than two groups, ranging from three to

seven.18,164,184,190,205 This categorisation further differentiated between different levels of

patient’s adherence to their medicines. The MAQ and MMAS categorised the population into

high, medium and low levels of adherence.18,205 The MMAS cut-off points were selected

based on the correlation with blood pressure control. The Brief Medication Questionnaire

grouped the study population into repeat, sporadic and no non-adherence.190 The ASRQ

and VAS classified non-adherence into six and seven levels, respectively based on the

researchers’ expertise.164,184

A small number of scales (12) have assessed the sensitivity and specificity of their cut-off

against an objective measure of adherence. The results of these studies are reported in

Table 2.3.

2.2.5 Discussion

We identified 43 adherence scales that have been correlated with a comparison measure of

adherence. The identified adherence scales elicit information regarding different facets of

adherence including medication-taking behaviour, barriers to and determinants of

adherence and beliefs associated with adherence. This information, where accurate, can be

put to different uses. Self-report adherence scales can (i) measure medication-taking

behaviour, where use of the scale either complements objective measures, or is used as an

alternative to objective measures and/or (ii) identify reasons for a patient’s non-adherence,

by identifying patient-specific barriers or beliefs that impede adherence. The data obtained

63

in this systematic review provides information on how well specific adherence scales can be

expected to perform these tasks.

Most of the scales identified as Group 1–3 focus on measuring medication-taking behaviour

by asking direct questions about medication-taking behaviour or eliciting barriers to good

medication-taking behaviour. Group 3 scales focus on barriers to adherence and have the

potential to both measure medication-taking behaviour and identify barriers to adherence.

The purpose of some Group 3 scales is to measure medication-taking behaviour by eliciting

information on barriers, as opposed to providing a comprehensive assessment of patient

barriers to adherence. The Medication Adherence Questionnaire (MAQ), for example, is a

short four-item Group 3 scale that has been well validated against objective measures of

adherence. The demonstration of a significant correlation between the adherence scale and

a suitable objective measure in patients with the same disease seems a reasonable minimal

requirement on the use of a scale as an alternative to an objective measure. Of the 36 Group

1–3 adherence scales, 20 have been significantly correlated with either MEMS or clinical

outcomes. Nine of the 36 adherence scales exploring medication-taking behaviour

significantly correlated with the MEMS. The MEMS can record the time of dose actuation

and can provide detailed information on medication-taking behaviour over time.165-167 Fifteen

Group 1–3 adherence scales have been correlated with clinical outcomes. Few scales have

been shown to be correlated with MEMS or clinical outcomes in multiple disease states,

making the choice of a scale more difficult in patient groups other than those included in the

validation studies.

A link between specific levels of adherence and clinical outcomes has been demonstrated

in some disease states (e.g. HIV60,82,83 and cardiovascular disease12,67,68). For the vast

majority of disease states, however, no such link has been made. Most scales provide

suggested cut-offs for identifying “non-adherent” patients. Cut-offs permit the identification

of patients who may be non-adherent and benefit from education or support. However, the

arbitrary nature of the cut-offs provided for most self-report adherence scales needs to be

kept in mind. Dichotomising adherence does not differentiate between types of non-

adherence, repeat versus sporadic adherence or patients at different stages of the

medication-taking process. Recent taxonomies of adherence recognise the dynamic nature

of patient medication-taking behaviour. Vrijens et al. acknowledges that the process of

medication-taking starts when the patient takes the first dose of medicine (initiation)

continues with the implementation of the regimen and ends when the patient discontinues

the medicine.38 Gearing et al. proposes a six-phase dynamic model of adherence: treatment

64

initiation, treatment trial, partial treatment acceptance, intermittent treatment adoption,

premature discontinuation and adherent.19 An important area for future research is the use

of self-report adherence scales to identify the different types of non-adherence suggested

by Vrijens et al. 38 and Gearing et al.19

A substantial number of scales have been validated against clinical outcomes, but no direct

measure of medication-taking behaviour such as MEMS; examples include the Barroso 30-

day Adherence Question and the Hill-Bone Compliance Scales. A demonstrated correlation

between a self-report adherence scale and clinical outcomes in a specific patient population

has relatively clear benefits for use of the scale in similar populations of patients. Knowing

when this evidence is transferrable into new populations of patients, however, is challenging.

For most disease states there are influences on clinical outcomes in addition to medication-

taking behaviour. Factors that influence clinical outcomes play a part in addition to the many

factors that may separate measures of adherence by self-report adherence scales from

actual medication-taking behaviour. No doubt some of these scales have focused on clinical

outcomes due to the availability of clinical data and the relative cost or availability of MEMS.

However, validation of a scale against both clinical outcomes and direct measures of

medication-taking behaviour is beneficial.

Scales included in Group 2 to 5 include items that elicit reasons a patient may be non-

adherent. These scales may identify barriers the patient is experiencing to good medication-

taking behaviour, and any patient-specific beliefs about their medicines that may influence

adherence. While some Group 3 scales focus more on measuring medication-taking

behaviour (e.g. the Medication Adherence Questionnaire (MAQ)), others seek more detailed

information on barriers that an individual may be experiencing (e.g. the Pediatric Inhaler

Adherence Questionnaire). Scales included in Group 4 and 5 seek to identify patient beliefs

about medicines that may influence adherence. Of these scales, the most extensively

assessed is the Beliefs about Medicines Questionnaire (BMQ). The BMQ-Specific identifies

whether patients hold the belief that their medicine is necessary as well as whether the

patient has concerns about their medicine.

Scales that focus on identifying reasons for non-adherence appropriately employ validation

strategies focused on content and construct validity. The BMQ is a good example of a self-

report adherence scale focused on measuring an aspect of adherence other than

medication-taking behaviour. The items of the BMQ have been validated through

confirmatory principle components analysis and the criterion and divergent validity assessed

against similar items in the Illness Perceptions Questionnaire and the Sensitive Soma

65

Scale.117 The BMQ-Specific has been shown to correlate well with medication-taking

behaviour measured by self-report adherence scales. Patients who believe their medicine

to be necessary and have fewer concerns have consistently been shown to be more

adherent in a range of diseases.95,127-130

Scales such as the BMQ are not stand-alone comprehensive adherence scales. But, like

scales that focus on identifying barriers to adherence, they provide the opportunity for a

more comprehensive assessment of a patient’s adherence—and the drivers behind that

adherence—than subjective or objective measures that focus on measuring medication-

taking behaviour. The information provided by self-report adherence scales that seek to

identify barriers and beliefs that are influencing adherence may prove useful in addition to

accurate information on the patient’s medication-taking behaviour. Specifically, these scales

may help inform tailored interventions to improve medication adherence, but their use for

this purpose is yet to be assessed.

Limitations

This systematic review only included studies of self-report adherence scales that included a

comparison measure of medication-taking behaviour. This was deemed appropriate given

the importance of measuring medication-taking behaviour in assessing adherence. A

consequence of this criterion is that this study does not provide a comprehensive analysis

of the validation of self-report adherence scales.

2.2.6 Conclusions

Self-report adherence scales have the potential to measure both medication-taking

behaviour, and identify barriers and beliefs associated with adherence. Selecting an

adherence scale requires consideration of what the adherence scale measures and how

well it has been validated. Research on validating and using the existing adherence scales

as a measure for medication-taking behaviour is relatively strong. There has been less focus

on assessing how information gained from scales that identify patient-specific barriers and

beliefs associated with adherence may be used to support wise medicine use. This presents

an important and exciting avenue for further research.

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2.3 Additional Notes

Since publishing the systematic review on validated medication adherence scales in the

British Journal of Clinical Pharmacology (BJCP), a number of new adherence scales have

been developed. The Reasoning and Regulating Medication Adherence Instrument is

currently in the initial stages of development testing. This 16-item adherence scale is

designed to identify barriers to adherent behaviour in patients with coronary artery

disease.298 Krousel-Wood et al. recently developed a four-item adherence scale and

validated the scale in patients with uncontrolled hypertension against the MMAS and Hill-

Bone Compliance Scale. This adherence scale measures both medication-taking behaviour

and barriers to adherence.299 A new adherence scale was developed to assess a number

of structural barriers to adherence in patients prescribed antiretroviral therapy. The barriers

to adherence identified using this adherence scale included stigmatism from others,

forgetfulness, preference to use complementary medicines and cost barriers.300 The

Adherence Barriers Questionnaire was recently developed to identify barriers to adherence

and has been validated in participants with atrial fibrillation.301 Kleepe et al. developed the

Probabilistic Medication Adherence Scale and validated in elderly patients taking chronic

medications.302 A number of the adherence scales in the systematic review, such as the

MARS and OS-MMAS have been further validated.303,304

2.4 Summary

Self-report adherence scales have the potential to measure medication-taking behaviour,

and/or identify some of the barriers and beliefs that may be associated with adherence.

Selecting an adherence scale requires consideration of what the adherence scale measures

and how well it has been validated. Research on validating and using the existing self-report

adherence scales as a measure of medication-taking behaviour is relatively strong. There

has been less focus on assessing how information gained from scales that identify patient-

specific barriers and beliefs associated with adherence may be used to support wise

medicine use. This presents an important and exciting avenue for further research. Chapter

Three presents the methods of the randomised controlled trial of a targeted and tailored

intervention to improve adherence and how the MAQ and BMQ-S are integrated within this

intervention.

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CHAPTER THREE: METHODS OF RANDOMISED CONTROLLED TRIAL TO IMPROVE MEDICATION ADHERENCE

3.1 Introduction

Improving adherence to medications can reduce the risk of adverse health outcomes and

health care expenditure (Section 1.3). Insight into the patient’s medication-taking behaviour

and reasons for behaviour may aid the implementation of tailored strategies to support

patients to adhere to their medications. There are many objective and subjective measures

of adherence that can provide information in relation to a patient’s medication-taking

behaviour.15,231,245,256,268 Objective measures of adherence, include electronic monitoring of

medication administration (e.g. Medication Event Monitoring System, MEMS), prescription

records and dose counts. These measures are often good at measuring medication-taking

behaviour, but can be expensive, labour-intensive and do not provide information on

reasons for behaviour. Subjective measures of adherence include physician reports, self-

report and adherence scales. Subjective measures are prone to recall and social desirability

bias, but they are often easy to administer and provide the opportunity to explore why the

patient may be non-adherent.

Many interventions have been implemented to improve adherence to medications, including:

reminder systems (text reminders, dose administration aids); behavioural-counselling

(motivational interviewing); social support (peer support therapy); cognitive-educational

(verbal information) and measurement-guided management (Section 1.6).214,305 Many

adherence interventions have failed to improve adherence to medications and clinical

outcomes when tested in clinical trials.13-15,217 A systematic review by Haynes et al., found

36 out of 83 interventions improved adherence to a chronic medication and only 25 of the

interventions were shown to improve a clinical outcome.306 One of the challenges in this

area is that few studies of adherence interventions are sufficiently powered to show benefit

in important clinical outcomes. These studies may be reported as a negative result despite

an improvement in measures of adherence.306

Further reasons for the lack of success seen when assessing adherence interventions in

clinical studies are that many have not been targeted to participants who are non-

68

adherent215,221,225,227,229 or tailored to the participant-specific reasons for non-

adherence.13,15,217,223 Although a targeted and tailored approach to improve medication

adherence has been suggested in the literature,1,126,187,203 few studies to date have adopted

this approach.216,247 Measurement-Guided Medication Management (MGMM), which uses

electronic data on the patients’ medication-taking behaviour from MEMS to inform

discussion between the patient and their health professional about potential barriers to

adherence, is a good example of a targeted and tailored approach that has been observed

to improve medication adherence.214 We conducted a systematic review on validated

adherence scales (Chapter Two), and found that adherence scales were relatively easy to

administer and may elicit information in addition to medication-taking behaviour, such as

barriers to adherence and beliefs associated with adherence.213 A number of adherence

scales may be selected to identify key aspects of adherence required for the study. We

believe that validated adherence scales can be used to inform a measurement-guided

medication management approach to adherence in a way that is very similar to how MEMS

has been used.

This chapter will describe the methods of a randomised controlled trial of a targeted and

tailored intervention to improve adherence to cardiovascular medications. We chose

cardiovascular medications for this study because cardiovascular disease is a great burden

on society, particularly in developed countries.1 Over 50% of patients on cardiovascular

medications are non-adherent,7,65 resulting in increased hospital admissions and

cardiovascular events (See Section 1.3.2). Other risk factors for cardiovascular disease

include dyslipidaemia, hypertension and hyperglycaemia. Diabetes is considered a strong

independent risk factor for cardiovascular disease and as described in section 1.3.2, non-

adherence to diabetic medications resulting in hyperglycaemia increases the likelihood of

people developing cardiovascular disease.1,72,73 Therefore due to the close link between

medication non-adherence in these diseases and poor clinical outcomes, it was decided that

our target population should include both cardiovascular and diabetes medications.

3.2 Aims and Hypotheses

The primary aim of the study was to determine if a targeted and tailored intervention based

on a discussion informed by validated adherence scales, would improve adherence to a

recently initiated cardiovascular medication.

69

The secondary aims of the study were exploratory. We hoped to learn about changes in

adherence over time, in the groups studied.

It was hypothesised that:

H1 Targeting and tailoring an intervention based on a discussion informed by adherence

scales in participants identified as non-adherent using the MAQ, will improve adherence at

three months.

H2 Improvements in adherence at three months, identified by the MAQ, will be sustained at

six months.

H3 Adherence, and reasons for non-adherence, will change over time in all groups studied.

3.3 Methods

This was a randomised controlled trial recruiting participants who recently initiated a

medicine for chronic cardiovascular disease (hypertension, dyslipidaemia, type II diabetes

and other cardiovascular diseases). The recruitment of participants occurred between the

25th of March, 2013 and 24th July, 2013 at one of two community pharmacies in Brisbane.

Participants were followed for six months from recruitment, the last participant contact

occurring on the 10th February, 2014. This trial is registered on the Australian New Zealand

Clinical Trials Registry, which can be accessed at http://www.anzctr.org.au/ using trial ID

ACTRN12613000162718. Ethical approval was obtained from the School of Pharmacy

Ethics Committee, University of Queensland (approval number 92013/5) (Appendix A).

3.3.1 Setting

Participants were recruited from two community pharmacies in Brisbane, Australia. The two

pharmacies were selected based on convenience as the researcher has an established

relationship with these pharmacies. The pharmacies selected for participation in the study

serviced a broad range of patients with chronic diseases. These pharmacies were

approached by the researcher and were provided with information on the study. Once the

pharmacies agreed to the study taking place, the dates for participant recruitment were

organised.

70

Individuals waiting in the pharmacy for their prescription(s) to be dispensed were recruited

by the researcher. The researcher asked the individual if they were willing to take part in a

study and if they agreed to participate, the individual was provided with verbal and written

information about the study. If the individual still wished to participate in the study after reading

the provided information (Appendix B), written informed consent (Appendix C) was obtained.

Participants were interviewed in the semi-private counselling area of the pharmacies.

3.3.2 Inclusion Criteria

The inclusion of an individual in the study depended on the individual’s attendance at one

of the selected pharmacies on the days that the researcher was present at the pharmacy.

Individuals who were over 18 years of age, who were recently prescribed a medication for

hypertension, type 2 diabetes, dyslipidaemia or other cardiovascular diseases (myocardial

infarction, heart failure, arrhythmias, and stroke) within the last four to 12 weeks were

included in the study. If multiple medications were prescribed within the last four to 12 weeks,

then the most recently initiated medication was selected. This standardises the sample as

all participants would be at a similar phase of taking their medicine. All participants would

have had the opportunity to take their recently initiated medicine for at least four weeks and

thus have some experience with their medicine. Individuals were approached if they had

recently initiated an ACE inhibitor, angiotensin II receptor antagonist, calcium channel

blocker, lipid-lowering agent or an oral hypoglycaemic drug. Clinical practice guidelines were

taken into account and participants recently initiated on a diuretic for hypertension were not

included in the study. Individuals who were unable to complete the survey tool were

excluded from the study.

3.3.3 Participant Interviews

The Medication Adherence Questionnaire (MAQ) was used to identify medication-taking

behaviour based on the MAQ score. Participants with a MAQ score of zero were classified

as adherent and were enrolled and followed for six months. Participants with a MAQ score

of 1 to 4 were classified as non-adherent. Non-adherent participants were then randomised

71

into either the intervention or control group, using block randomisation and followed for six

months (Figure 3.1). The random allocation sequence was generated by an internet-based

randomisation software (Research Randomiser). The block size was ten, providing an

allocation ratio of 1:1 (e.g. ABBABABAAB). The intervention group received a tailored

intervention at baseline to improve medication adherence. Due to the nature of the

intervention, neither the researcher, nor the participants were blinded to the allocation at the

baseline interview. No data analysis occurred prior to completion of the study.

72

Figure 3.1 Participant flow diagram: from identifying participants’ medication-taking behaviour to final follow-up

Screened for eligibility

Enrolment of patients

ADHERENT Non-Adherent

Randomised

INTERVENTION CONTROL

Follow-Up

at 3 months

Follow-Up

at 3 months

Follow-Up

at 3 months

Final Follow-Up

at 6 months

Final Follow-Up

at 6 months

Final Follow-Up

at 6 months

73

All interviews were conducted by the principal researcher (TN), who is a registered

pharmacist. The researcher (TN) conducted the initial interview and follow-up telephone

calls at three and six months. The survey instruments used in the interview included the:

MAQ, Beliefs about Medicines Questionnaire – Specific (BMQ-S) and Brief Illness

Perception Questionnaire (BIPQ). Field notes were taken during the interviews.

Baseline demographic characteristics of the participants were also collected (Appendix D).

All participants were followed for six months with telephone interviews at three- and six-

month time points to complete the same three validated scales: the MAQ, BMQ-S and BIPQ.

Medication Adherence Questionnaire (MAQ)

The four-item MAQ was selected because it has been well-validated to identify adherence

in a number of chronic cardiovascular disease populations and scores have been shown to

correlate well with a range of objective adherence measures, as described in Chapter

Two.18,72,293,296 The MAQ has also been used to explore reasons for non-adherent

behaviour.18 Specifically, the MAQ has been used to identify unintentional non-adherence,

intentional non-adherence or a mix of both.49

Participants answering no to all items of the MAQ (MAQ score = 0) were identified as

adherent to their medicine (Table 3.1).72,95,204,307 These participants were followed for six

months in the “adherent” group. Participants answering yes to at least one of the MAQ items

(MAQ score = 1 to 4) were identified as “non-adherent” and were randomised to either the

intervention or control group. This cut-off was chosen for the study because it has been used

in the literature in previous studies,72,95,204,307 and the cut-off at this value provides a highly

sensitive tool for identifying medication non-adherence. It should be noted that the MAQ was

used as a measure of adherence, and does not differentiate between frequently missed

doses and occasional missed doses.

Participant responses to the MAQ were also used to identify the participant’s reasons for

non-adherence, for instance: unintentional non-adherence due to being forgetful or careless,

or intentional non-adherence by ceasing their medicines when they felt better or worse and,

a mix of both types (Table 3.1).

Unintentional non-adherence: participant answers yes to items 1 or 2 and no to both items

3 and 4

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Intentional non-adherence: participant answers no to both items 1 and 2 and yes to items 3

or 4

Both types (mixed): participant answers yes to items 1 or 2 and also yes for items 3 or 4

Table 3.1 The Medication Adherence Questionnaire (MAQ)

Item Question YES NO Score

1 Do you ever forget to take your medicine?

2 Are you careless at times about taking your medicine?

3 When you feel better, do you sometimes stop taking your

medicine?

4 Sometimes, if you feel worse when you take the

medicine, do you stop taking it?

Morisky DE, Green LW, Levine DM. Concurrent and predictive validity of a self-reported measure of medication

adherence. Med Care 1986;24(1):67-74.

Beliefs about Medicines Questionnaire – Specific (BMQ-S)

The BMQ-S has been validated in many disease populations, including hypertension,

coronary heart disease, asthma and depression, as shown in Chapter Two (Table 3.2).117,124

The BMQ-S elicits an individual’s beliefs about their medicines in the domains of necessity

of medicines and concerns about medicines. In general, individuals who have strong

concerns about their medicines or believe their medicines are not necessary tend to be less

adherent.4,117,126,131,153

All participants were interviewed using the BMQ-S to measure perceived necessity of and

concerns about medicines.117 The BMQ-S consists of ten statements about medicines: five

of the statements are related to beliefs about the necessity of medicines and the remaining

five statements are related to concerns that individuals may have about their medicines.

Statements 1, 3, 4, 7 and 10 refer to beliefs that medicines are necessary and statements

2, 5, 6, 8 and 9 refer to concerns about medicines (Table 3.2). The participants rated each

75

of the statements on a five-point Likert scale: strongly agree, agree, uncertain, disagree and

strongly disagree. The responses for each statement were scored as follows: strongly agree

= 5, agree = 4, uncertain = 3, disagree = 2 and strongly disagree= 1. Therefore, the scores

for the necessity or concerns domains range from 5 to 25. The information obtained from

the BMQ-S further informed the discussion to help tailor the adherence support strategy to

the participant based on their necessity and/or concerns score and therefore their beliefs

towards their medicines.

76

Table 3.2 The Beliefs about Medicines Questionnaire - Specific (BMQ-S)

Item Statement Strongly

Agree

Agree Uncertain Disagree Strongly

Disagree

1 My health at present,

depends on my medicines

2 Having to take medicines

worries me

3 My life would be impossible

without my medicines

4 Without my medicines I

would be very ill

5 I sometimes worry about

long-term effects of my

medicines

6 My medicines are a mystery

to me

7 My health in the future will

depend on my medicines

8 My medicines disrupt my life


becoming too dependent on

my medicines

10 My medicines protect me

from becoming worse

Horne R, Weinman J, Hankins M. The Beliefs about Medicines Questionnaire: the development and evaluation

of a new method for assessing the cognitive representation of medication. Psychol Health 1999;14(1):1-24.

77

Brief Illness Perception Questionnaire (BIPQ)

Illness representations identified in the BIPQ has been associated with adherence to

medications.135,139 For example, patients with hypertension were more likely to be adherent

if they felt they had good control over their illness, better understanding of their illness and

were not emotionally affected by their illness. The BIPQ consists of nine items that assess

the cognitive and emotional representations of illness.139 The first eight items were rated on

a scale of 0 to 10 (Table 3.3). This questionnaire provided insight into a participant’s

perceptions and understanding of their illness and treatment. The participant’s perceptions

and understanding of their illness and treatment was elicited to explore why the participant

may be non-adherent to their medication.

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Table 3.3 The Brief Illness Perception Questionnaire

How much does your illness affect your life? 0 1 2 3 4 5 6 7 8 9 10 no affect severely affects at all life

How long do you think your illness will continue? 0 1 2 3 4 5 6 7 8 9 10 a very forever short time

How much control do you feel you have over your illness? 0 1 2 3 4 5 6 7 8 9 10 absolutely extreme no control amount of control

How much do you think your treatment can help your illness? 0 1 2 3 4 5 6 7 8 9 10 not at all extremely helpful

How much do you experience symptoms from your illness? 0 1 2 3 4 5 6 7 8 9 10 no symptoms many severe at all symptoms

How concerned are you about your illness? 0 1 2 3 4 5 6 7 8 9 10 not at all extremely concerned concerned

How well do you feel you understand your illness? 0 1 2 3 4 5 6 7 8 9 10 don’t understand understand at all very clearly

How much does your illness affect you emotionally? (e.g. does it make you angry, scared, upset or depressed? 0 1 2 3 4 5 6 7 8 9 10 not at all extremely affected emotionally affected emotionally

Please list in rank-order the three most important factors that you believe caused your illness. The most important causes for me: 1. ________________ 2. _________________ 3. __________________

Broadbent E, Petrie KJ, Main J, Weinman J. The brief illness perception questionnaire. J Psychosom Res

2006;60(6):631-7.

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3.3.4 Intervention

This study employed a form of measurement-guided medication management to improve

adherence (Section 1.6.2). The intervention consisted of the following. Non-adherent

participants were identified using the MAQ. The participant’s type and reasons for non-

adherence were explored using their responses to the MAQ, BMQ-S and BIPQ. Where

possible the researcher used responses to the adherence scales to prompt further

discussion regarding the participant’s adherence and the factors that supported or impeded

them to take their medicine. Any issues with the participant’s other medications that were

brought up during the interview were discussed and formed part of the individualised

conversation with the participant. Any issues that could not be resolved were referred to the

pharmacist on duty in each pharmacy (See case examples in Chapter Five for more details).

From the information discussed in the interview, the researcher and participant then selected

and implemented a strategy from an evidence-based toolkit (based on literature review,

Section 1.6) to support the participant’s adherence. The evidence-based toolkit consisted of

strategies shown to improve adherence in specific situations. For example, some

participants who stated they forget to take their medicine on the MAQ may be asked: How

often they forget? Where they store their medicines? Or why they think they forget to take

their medicine? This information helped determine whether the participant would benefit

from a reminder and the specific type of reminder. Participants who indicated that they

intentionally ceased their medicine on the MAQ and indicated that they had a poor perceived

understanding of their illness on the BIPQ, were asked what they knew about their illness

and/or medicine to help tailor education or information provided to them on their illness or

medicines (cognitive-educational intervention). Notes from the discussion were transcribed

immediately after the interview.

Strategies employed to support the participant’s adherence included13,14,214,305:

reminder systems (dose administration aids, dosette boxes, alarm clock reminders,

text reminders, treatment simplification);

cognitive-educational interventions (pharmacist verbal information, written

information);

reminder systems coupled with cognitive-educational interventions;

behavioural-counselling interventions (reinforcing behaviour, empowering individuals

to actively participate in their healthcare and problem-solving) and

social support interventions (family member support).

80

Case Example

Below is an example of how interventions were tailored based on the survey responses and

discussion with the participant. For in-depth discussion on how the interventions were

tailored, see Chapter Five.

A married and retired 66 year old female participant with tertiary qualifications currently takes

four prescription medications for the treatment of hypertension, dyslipidaemia and

hypothyroidism. The participant has recently started ezetimibe 10mg once daily to lower

blood cholesterol levels.

Intervention

MAQ: The participant had a MAQ score of 1 and identified as unintentionally non-adherent

due to forgetfulness.

BMQ-S: The participant’s perceived necessity beliefs outweighed her concerns about the

medicine

BIPQ: The BIPQ suggests that she perceives her medicine as highly valuable and has a

good understanding of her illness.

Discussion: To better understand her medication-taking behaviour, the participant was

asked to elaborate where she stored her medicines and circumstances when she would

forget to take her medicines. The researcher learnt that the participant stored the medicines

in many different places (e.g. a medicine in her handbag when leaving home, in the kitchen

and some in the bathroom). She often forgets to take her medicines when she is out, when

she is busy with a task and often when travelling.

Adherence Strategy: The researcher recommended keeping all her medicines together at

one convenient location. The researcher also suggested using an alarm clock to help remind

her to take medicines on time and using a dosette box, especially when travelling.

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Summary of Intervention

The MAQ was used to identify participants who were non-adherent to their medication and

to determine whether participants were exhibiting unintentional, intentional or both types of

non-adherence. The BMQ-S elicited beliefs about medicines in regards to whether the

participant believed their medication was necessary and whether they had any concerns

towards their medication. The BIPQ was used to explore illness perceptions, such as the

effect of the illness on their lives, whether they believed their medication was helpful in

treating their illness and their understanding of their illness. The responses to the MAQ,

BMQ-S and BIPQ informed the discussion with the participant, which guided the

implementation of a tailored strategy to improve their adherence.

3.3.5 Outcome Measures

The primary outcome was the difference in the mean MAQ score between the intervention

and control group at three months. The difference in mean MAQ score between the

intervention and control group was also tested at six months. A post hoc analysis was

conducted to assess whether changes in survey responses were consistent with the specific

adherence strategy employed.

3.3.6 Sample Size

A power calculation was conducted based on the effect size observed in a hypertension

adherence study by Morisky et al.260 Morisky et al. implemented an educational intervention

to improve adherence in people with hypertension and observed a difference in mean MAQ

scores between intervention and control of 0.683, which was associated with a clinically

significant improvement in blood pressure control. For our study, a one-sided t-test was

conducted to calculate the target sample size. Forty-one participants per group (intervention

and control) provided 80% power to detect a statistically significant change in adherence at

a level of 0.05. Taking into account participants dropping out of the study, our sample size

target would be 60 per group (intervention and control).

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3.3.7 Statistical Analyses

Baseline demographics of the intervention and control groups were compared using t-tests

for continuous data and Pearson’s Chi-squared test and Fisher’s exact tests for categorical

data.

An independent-samples t-test was conducted to compare the mean MAQ score of the

intervention and control group, based on an intention-to-treat and per protocol population

using R (version 3.0.2) statistical software, at three months and six months.

Changes in the questionnaires scores at three months and six were compared for each of

the adherent, intervention and control groups using dependent-samples t-tests.

Changes in the questionnaires scores at three and six months were also observed in the

different strategy types in the intervention group.

3.4 Summary

This chapter describes the method of the randomised controlled trial of a targeted and

tailored interventions to improve adherence in participants identified as non-adherent.

Information obtained from the MAQ, BMQ-S, BIPQ and discussion with the participant was

used to help tailor an intervention to improve adherence. Chapter Four addresses the results

of the randomised controlled trial of a targeted and tailored intervention to improve

adherence to medications in participants with chronic diseases.

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CHAPTER FOUR: RESULTS 1 - A RANDOMISED CONTROLLED TRIAL OF A TARGETED AND TAILORED INTERVENTION TO IMPROVE MEDICATION ADHERENCE

4.1 Introduction

Chapter Three described the method of a randomised controlled trial of a targeted and

tailored intervention in participants recently initiated on a medicine for the treatment or

prevention of cardiovascular disease. The tailored strategy to improve adherence in non-

adherent participants was informed by a discussion with the participant, which was guided

by the participant’s responses to the Medication Adherence Questionnaire (MAQ), Beliefs

about Medicines Questionnaire-Specific (BMQ-S) and Brief Illness Perception

Questionnaire (BIPQ).

This chapter presents the main results of the randomised controlled trial of targeted and

tailored interventions to improve medication adherence.

Chapter Four addresses the following hypotheses:

- Hypothesis 1: Targeting and tailoring an intervention based on a discussion informed

by adherence scales in participants identified as non-adherent using the MAQ, will

improve adherence at three months.

- Hypothesis 2: Improvements in medication adherence, as measured by the MAQ, at

three months will be sustained at six months.

This chapter will report the beliefs and illness perceptions between the adherent,

intervention and control groups.

4.2 Results

A total of four hundred and eight individuals, visiting the two community pharmacies, were

assessed for eligibility, of which 152 participants were enrolled into the study (Figure 4.1).

The results from the MAQ classified 32 participants as adherent and 120 participants were

84

classified as non-adherent. Participants classified as non-adherent were randomised 1:1 to

intervention or control. At six months, there were 55 participants remaining in the

intervention group and 45 participants in the control group. The movement of participants

throughout the study is shown in Figure 4.1.

85

Figure 4.1 Participant flow diagram

Screened for eligibility (n=408)

Excluded (n =256)

- Not on a recently initiated medicine (n=163) - Not on medication of interest (n=76) - Declined to participate (n=12) - Judged unable to participate in study: (n=5)

Enrolment of patients (n=152)

ADHERENT (n=32) Non-Adherent (n=120)

Randomised (n=120)

INTERVENTION (n=60) CONTROL (n=60)

3 Months (n=57) 3 Months (n=28)

3 Months (n=52)

6 Months (n=55)

6 Months (n=45)

6 Months (n=28)

-Withdrew (n=8) -Withdrew (n=3) -Withdrew (n=4)

-Withdrew (n=1) -Death (n=1)

-Withdrew (n=6) -Death (n=1)

86

4.2.1 Participant Baseline Demographics

Participants in the adherent group had a mean age of 64.6 years and 59.4% were female.

The participants classified as non-adherent (intervention and control) using the MAQ had a

mean age of 63.5 years. Of these participants, 66 (55%) were female and 98 (81.7%) had

attained secondary school qualifications or higher. Most of these participants were married

(60.8%), retired (52.5%) and had an annual salary of less than $30000 (46.7%). There were

no significant differences in the demographics between the intervention and control groups

at baseline. There were also no significant differences in the baseline demographics

between the adherent and non-adherent (intervention and control) groups (Table 4.1).

87

Table 4.1 Baseline participant demographics

Adherent

n=32

Intervention

n=60

Control

n=60

Age (years), mean (SD) 64.6 (13.6) 64.4 (11.3) 62.6 (13.4)

Sex (males)

13 (40.6%) 29 (48.3%) 25 (41.7%)

Education level

Primary

Secondary

Tertiary

6 (18.8%)

16 (50.0%)

10 (31.2%)

13 (21.7%)

32 (53.3%)

15 (25.0%)

9 (15.0%)

37 (61.7%)

14 (23.3%)

Employment

Employed

Unemployed

Retired

11 (34.4%)

3 (9.4%)

18 (56.2%)

21 (35.0%)

5 (8.3%)

34 (56.7%)

19 (31.7%)

12 (20.0%)

29 (48.3%)

Annual Salary (before tax deduction)

≤ $30 000

$31 000 - 50 000

$51 000 - 70 000

$71 000 - 90 000

Over $90 000

13 (40.6%)

5 (15.6%)

7 (21.9%)

2 (6.3%)

5 (15.6%)

30 (50.0%)

10 (16.7%)

9 (15.0%)

8 (13.3%)

3 (5.0%)

26 (43.3%)

11 (18.3%)

16 (26.7%)

4 (6.7%)

3 (5.0%)

Marital Status

Married

Divorced

Widowed

Single

21 (65.6%)

4 (12.5%)

4 (12.5%)

3 (9.4%)

38 (63.4%)

8 (13.3%)

8 (13.3%)

6 (10.0%)

35 (58.3%)

11 (18.3%)

7 (11.7%)

7 (11.7%)

Total Number of Medicines

Medications, mean (SD)

6.4 (3.2)

5.7 (2.6)

5.0 (2.6)

Complementary medicines,

mean (SD)

1.4 (1.4)

0.85 (1.1)

0.93 (1.3)

Medical Conditions

Hypertension

Dyslipidaemia

Diabetes mellitus

Heart failure

Atrial Fibrillation

Myocardial infarction

Stroke

Asthma

COPD

Depression

Osteoarthritis

Osteoporosis

Gout

GORD

Thyroid conditions

Other

26 (81.3%)

21 (65.6%)

12 (37.5%)

3 (9.4%)

6 (18.8%)

5 (15.6%)

3 (9.4%)

7 (21.9%)

1 (3.1%)

7 (21.9%)

10 (31.2%)

0 (0.0%)

0 (0.0%)

4 (12.5%)

1 (3.1%)

7 (21.9%)

49 (81.7%)

39 (65.0%)

24 (40.0%)

8 (13.3%)

7 (11.7%)

5 (8.3%)

4 (6.7%)

9 (15.0%)

2 (3.3%)

12 (20.0%)

19 (31.7%)

6 (10.0%)

2 (3.3%)

10 (16.7%)

3 (5.0%)

17 (28.3%)

48 (80.0%)

39 (65.0%)

25 (41.7%)

5 (8.3%)

4 (6.7%)

10 (16.7%)

5 (8.3%)

9 (15.0%)

1 (1.7%)

12 (20.0%)

17 (28.3%)

3 (5.0%)

5 (8.3%)

5 (8.3%)

3 (5.0%)

20 (33.3%)

88

4.2.2 Intervention

The mean length of the baseline interview for the adherent group was 10.2 ± 1.6 minutes,

intervention group (including implementation of tailored strategy) was 13.5 ± 2.9 minutes

and control group was 11.8 ± 2.8 minutes.

The tailored strategies implemented by the principal researcher, are shown in Table 4.2.

Reminder systems accounted for 45% of the strategies that were implemented.

Table 4.2 Types of tailored strategies implemented to improve medication adherence

4.2.3 Adherence

The mean MAQ score at baseline in the intervention, 1.58: 95% CI [1.38, 1.78], and control,

1.60: 95% CI [1.43, 1.77], groups were not statistically different. At three months, based on

intention-to-treat, the mean MAQ score in the intervention group was significantly lower than

the control group, reflecting an improvement in adherence (mean MAQ score 0.42: 95% CI

[0.27, 0.57] vs 1.58: 95% CI [1.42, 1.75]; p<0.001). The significant improvement in MAQ

score in the intervention group compared to control was sustained at six months (0.48: 95%

Strategy Intervention

Group

n = 60

Examples of the Strategy

Reminder systems 27 (45.0%) - Dose administration aids

- Alarm reminders

- Simplifying treatment regimens

Reminder systems and

Cognitive-educational

15 (25.0%) - Dosette box and verbal or written

information

Cognitive-educational 9 (15.0%) - Disease-specific and medication

counselling

- Written information

Social support

5 (8.3%) - Support from a family member

Behavioural-counselling 4 (6.7%) - Health coaching

89

CI [0.31, 0.65] vs 1.48: 95% CI [1.27, 1.69]; p<0.001). This represents a statistically

significant improvement in the primary endpoint at three and also at six months (p<0.001)

(Figure 4.2). Similar results were observed on the per protocol analysis; mean MAQ score

intervention vs control at 3 months and 6 months was 0.33 vs 1.54, p<0.001 and 0.42 vs

1.44, p<0.001, respectively. From now on, only the results from the intention-to-treat

analysis are presented.

The mean MAQ score in the adherent group increased significantly from zero at baseline to

0.22: 95% CI [0.05, 0.39] at three months (p < 0.05). The significant increase in mean MAQ

score in the adherent group was not sustained at six months.

On a more individual level, we observed that at three months, 53 of the 60 (88.3%)

participants in the intervention group showed a reduction in their MAQ score, reflecting an

improvement in adherence. In the control group, seven of the 60 (11.7%) participants

showed an improvement in their MAQ score. The greatest individual improvement was a

MAQ score of four to zero.

90

Figure 4.2 Mean MAQ scores (± 95% CI) at baseline, 3-month and 6-month follow-ups, based on intention to treat analysis

(*** p <0.001 – Mean MAQ score in intervention group was significantly lower than control at both three and six months) Note: decreasing MAQ score reflects improvement in medication adherence

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

Baseline 3 Months 6 Months

Mea

n M

AQ

sco

re

Time

Adherent

Intervention

Control

*** ***

91

4.2.4 Changes in mean BMQ-S scores between the three groups over time

The changes in the BMQ-S necessity and concerns scores at three and six months are

shown in Table 4.3. At baseline there were no statistically significant differences in the mean

BMQ-S necessity and concerns scores between the adherent and non-adherent

(intervention and control) groups. At three and six months, the mean BMQ-S concerns

scores were significantly lower in the adherent group compared to the control group,

reflecting less concerns about their medicine in the adherent group. At six months, the mean

BMQ-S necessity score was significantly higher in the adherent group than the control

group, indicating that the adherent group had stronger beliefs that their medicine was

necessary (Table 4.3).

There were no statistically significant differences in the mean BMQ-S necessity score and

concerns score at baseline, between the intervention and control (Table 4.3). At three

months, the BMQ-S necessity score was significantly higher in the intervention group

compared to control (p<0.05). This result was sustained at six months (p<0.001). The mean

BMQ-S concerns score were not significantly different between the intervention and control

at both three and six months.

92

Table 4.3 Mean BMQ-S necessity scores and concerns score at baseline, three months and six months between the groups

BMQ

Scores

Time

Adherent n=32

Pa

Non-Adherent n=120

Pb

Intervention

n=60

Control

n=60

Mean Necessity Score ± sd

Baseline

3 months

6 months

20.25 ± 4.84

20.28 ± 4.17

20.22 ± 3.89

0.1925

0.0515

<0.05*

19.60 ± 3.18

19.80 ± 2.94

20.25 ± 3.17

18.48 ± 3.63

18.53 ± 3.71

17.95 ± 3.20

0.0758

<0.05*

<0.05*

Mean Concerns Score ± sd

Baseline

3 months

6 months

11.75 ±

3.13

11.41 ± 2.89

10.78 ± 2.81

0.0511

<0.05*

<0.05*

13.48 ± 3.50

13.00 ± 3.43

12.32 ± 3.75

12.63 ± 4.20

13.05 ± 3.75

12.92 ± 3.38

0.2312

0.9394

0.3591

pa: BASELINE - adherent vs. non-adherent (intervention and control)

: 3 MONTHS AND 6 MONTHS - adherent vs. control

pb: intervention vs. control

4.2.5 Changes in mean BIPQ scores between the three groups over time

At baseline, the mean BIPQ treatment control score was significantly higher in the adherent

group than the non-adherent participants (intervention and control groups). The mean BIPQ

treatment coherence score was significantly higher in the adherent group compared to the

non-adherent (intervention and control) group, at baseline. This indicates that at baseline,

participants identified as adherent using the MAQ felt that their medicine was more helpful

and felt they had a clearer understanding of their illness than participants classified as non-

adherent (Table 4.4).

At three months, the mean BIPQ personal control score was significantly higher in the

intervention group compared to the control. At both three and six months, the mean BIPQ

treatment control and coherence scores were significantly higher in the intervention group

compared to control. These scores indicate that the intervention group felt their treatment

was more helpful and had a clearer perceived understanding of their illness than the control

at three and six months. At all time points, the intervention group had a significantly higher

BIPQ timeline score than the control group, reflecting that the intervention group believed

their illness would last longer (Table 4.4).

93

Table 4.4 Mean scores of BIPQ at baseline, three months and six months, between groups

Mean BIPQ Scores ± sd

Time

Adherent

(n=32)

pa

Non-Adherent Pb Interventio

n (n=60)

Control

(n=60)

Consequences How much does your

illness affect your life?

(0 = no affect at all – 10 =

severely affects my life)

Baseline

3 months

6 months

5.13 ± 2.87

5.03 ± 3.17

4.06 ± 2.94

0.7411

0.9976

<0.05*

5.10 ± 3.02

4.98 ± 3.07

4.90 ± 2.86

4.77 ± 3.01

5.03 ± 3.09

5.45 ± 2.92

0.5459

0.9292

0.2995

Timeline How long do you think

your illness will continue?

(0 = very short time – 10 =

forever)

Baseline

3 months

6 months

8.72 ± 2.64

8.94 ± 2.35

9.09 ± 2.16

0.3298

0.9671

0.9597

9.57 ± 1.14

9.90 ± 0.66

9.83 ± 0.62

8.85 ± 2.28

8.92 ± 2.19

9.12 ± 1.87

<0.05*

<0.05*

<0.05*

Personal Control How much control do you

feel you have over your

illness?

(0 = absolutely no control –

10 = extreme amount)

Baseline

3 months

6 months

6.53 ± 2.73

7.22 ± 1.91

7.47 ± 1.90

0.2497

<0.05*

<0.05*

5.70 ± 2.82

6.50 ± 2.57

5.90 ± 2.93

6.08 ± 2.89

5.53 ± 2.61

4.98 ± 2.59

0.4639

<0.05*

0.0723

Treatment

Control How much do you think

your treatment can help

your illness?

(0 = not at all – 10 =

extremely helpful)

Baseline

3 months

6 months

9.00 ± 1.44

9.28 ± 1.39

9.16 ± 1.42

<0.05*

<0.05*

<0.05*

8.20 ± 1.94

8.55 ± 1.79

8.58 ± 1.70

8.00 ± 1.97

7.63 ± 2.15

7.22 ± 2.44

0.5757

<0.05*

<0.05*

Identity How much do you

experience symptoms

from your illness? (0 = no symptoms – 10 =

many severe symptoms)

Baseline

3 months

6 months

3.63 ± 3.12

4.16 ± 3.05

3.56 ± 2.71

0.2859

0.7510

<0.05*

4.32 ± 2.83

4.52 ± 3.06

4.18 ± 2.78

4.25 ± 2.90

4.37 ± 2.95

4.98 ± 2.69

0.8988

0.7850

0.1121

Concern How concerned are you

about your illness?

(0 = not at all concerned –

10 = extremely concerned)

Baseline

3 months

6 months

5.53 ± 3.16

5.34 ± 3.57

4.47 ± 3.32

0.8319

0.5539

<0.05*

5.97 ± 3.46

5.65 ± 3.21

5.53 ± 3.32

5.37 ± 3.11

5.78 ± 2.96

6.12 ± 2.92

0.3204

0.8135

0.3093

Coherence How well do you feel you

understand your illness? (0 = don’t understand – 10 =

understand very clearly)

Baseline

3 months

6 months

8.53 ± 1.92

8.66 ± 1.82

8.84 ± 1.74

<0.05*

<0.05*

<0.05*

7.28 ± 2.64

8.37 ± 2.09

8.37 ± 2.11

7.35 ± 2.36

7.12 ± 2.54

6.63 ± 2.71

0.8845

<0.05*

<0.05*

Emotional How much does your

illness affect you

emotionally?

(0 = not at all affected

emotionally – 10 = extremely

affected emotionally)

Baseline

3 months

6 months

3.56 ± 3.22

4.16 ± 3.07

3.38 ± 2.70

0.3845

0.7356

<0.05*

4.18 ± 3.41

4.27 ± 3.15

3.92 ± 3.02

4.07 ± 3.05

4.38 ± 3.04

4.97 ± 2.91

0.8436

0.8366

0.0547

pa: BASELINE - adherent vs. non-adherent (intervention and control)

: 3 MONTHS AND 6 MONTHS - adherent vs. control

pb: intervention vs. control

94

4.3 Conclusions

A targeted and tailored intervention guided by feedback from validated adherence scales

and discussion with the participant improved adherence to a recently initiated medication at

three months and this effect was sustained at 6 months. Use of validated adherence scales

to prompt a structured discussion, provided insight into the participant’s medication-taking

behaviour, beliefs towards their medicines and their illness perceptions. This is a variant of

an approach that used MEMS data and has been successful at improving adherence to

medications (MGMM).214 This intervention was easy to administer and quick enough that it

could be incorporated into day-to-day practice, if proven successful in larger studies

assessing clinical outcomes.

Chapter Five provides details on how the intervention was tailored to participants. The

changes in adherence, beliefs about medicines and illness perceptions in the adherent,

intervention and control groups and for each of adherence strategies are explored in Chapter

Six. Refer to Chapter Seven for discussion and the study limitations.

95

CHAPTER FIVE: RESULTS 2 - TAILORING OF THE INTERVENTIONS TO THE PARTICIPANT-SPECIFIC REASONS FOR NON-ADHERENCE

5.1 Introduction

In Chapter Two and Three we reported how adherence scales could be used to identify non-

adherence and the reasons for non-adherence. In Chapter Three we described the methods

of a randomised controlled trial to test the use of validated scales in an MGMM approach to

improve medication adherence. The intervention involved validated adherence scales,

discussion with the participant and the implementation of a tailored strategy to improve

adherence. Validated adherence scales were used to provide feedback on the participant’s

adherence. The participant’s responses to the scales informed the discussion with the

participants about their illnesses, medicines and/or reasons for their non-adherence to

provide context. The discussion guided the implementation of a tailored strategy to improve

adherence to a chronic cardiovascular disease. Chapter Four presented the results of the

randomised controlled trial of a targeted and tailored intervention to improve adherence.

This adherence intervention led to a significant improvement in adherence at three months

and this improvement in adherence was sustained at six months (Chapter Four).

It is important to explain how these interventions were tailored to the participant-specific

reasons for non-adherence to explore how the intervention may have improved adherence.

The purpose of Chapter Five is to describe how the information obtained from the validated

tools and discussion with the participant informed the implementation of the tailored

strategies. The tailored strategies included: reminder systems, cognitive-educational,

behavioural-counselling and social support interventions.

96

5.2 Participant Baseline Interview

The interview consisted of the: Medication Adherence Questionnaire (MAQ), Beliefs about

Medicines Questionnaire - Specific (BMQ-S), Brief Illness Perceptions Questionnaire (BIPQ)

and tailored strategy. The MAQ, BMQ-S and BIPQ were utilised to gather information about

the participants’ adherence and reasons for non-adherence.

The MAQ was used for two purposes: (i) identify participant’s adherence, and (ii)

identify the participant’s type of non-adherence (unintentional, intentional or a mix of

both types), as described in Section 3.3.3.18

The BMQ-S elicited commonly-held beliefs about medicines, as described in Section

3.3.3.117 The BMQ-S provided insight to whether the participant believed their

medicines were necessary and whether participants had any concerns about their

medicines.

The BIPQ was used to explore illness perceptions that may influence adherence to

medications.135,139 Items 4 and 7 in particular were used to identify if participants held

negative perceptions towards their medicines and whether or not they perceived that

they understood their illness, respectively (Section 3.3.3).

The participant’s responses to the validated tools informed further discussion regarding the

participant’s adherence and barriers to adherence. A tailored strategy to support the

participant’s adherence was selected and implemented based on the information discussed

in the interview.

5.3 Intervention

5.3.1 Overview of Strategies Implemented

Guided by the adherence scales, the researcher and participant selected and implemented

a strategy from an “evidence-based toolkit” to support the participant’s adherence to their

medicine (Chapter Four: Table 4.2). The commons strategies employed to improve

adherence were: reminder systems (45%), reminder system and a cognitive-educational

97

strategy (25%), a cognitive-educational strategy (15%), social support (8.3%) and a

behavioural-counselling strategy (6.7%).

5.3.2 Overview of Radar Charts of the Responses to the Scales for each

Tailored Strategy and Case Examples

For each of the tailored strategies, a radar chart has been used to provide a pictorial

representation of how the responses to the scales guided the selection of the strategy.

Figure 5.1 is a template of the radar chart. From the top of the radar chart, moving clockwise,

the first four axis lines represents the proportion of participants (%) who responded positively

to each of the MAQ items, indicating whether they were forgetful at taking their medicine,

careless at taking their medicine, ceased their medicine when they felt better or when they

felt worse. The next two axis lines represent the mean BMQ-S necessity and concerns

scores (expressed as a percentage). The higher the BMQ-S necessity and concerns scores,

the stronger the belief that their medicine was necessary and the greater the concerns were

about their medicine, respectively. The remaining two lines on the left of the radar chart are

the mean BIPQ treatment control and treatment coherence score, which are also expressed

as a percentage. A high BIPQ treatment control score reflects strong beliefs that their

medicine is helpful and a high BIPQ treatment coherence score indicates a clear perceived

understanding of their treatment (Figure 5.1). The radar charts (Figure 5.2 – 5.6) visually

depict key similarities and differences in responses to the survey tools at baseline between

patients who received the different tailored strategies. Since the type of strategy

implemented was informed by the participant’s responses to the MAQ, BMQ-S, BIPQ and

discussion with the participant, these groups are not randomised.

Individual examples are also provided below the individual radar charts, to explain and

illustrate in more detail how the interview was used to inform the selection of the tailored

strategy in specific participants.

98

Figure 5.1 Radar Chart template

0

10

20

30

40

50

60

70

80

90

100

% MAQ Q1 Forgetful

% MAQ Q2 Careless

% MAQ Q3 Ceased whenwell

% MAQ Q4 Ceased whenworse

Mean BMQ-S NecessityScore

Mean BMQ-S ConcernsScore

Mean BIPQ TreatmentControl Score

Mean BIPQ TreatmentCoherence Score

99

5.3.3 Reminder System

Reminder System Radar Chart

Reading the radar chart (Figure 5.2) clockwise from the top, we can see that all participants

who received a reminder to improve their medication adherence were identified as

unintentionally non-adherent (either forgetful or careless with their medicines). The mean

BMQ-S necessity score was high, indicating these participants had strong beliefs their

medicine was necessary. The mean BMQ-S concerns score was low, reflecting minimal

concerns about their medicine. The mean BIPQ treatment control and treatment coherence

scores were high, reflecting that these participants believed their medicine was helpful and

had a good perceived understanding of their illness (Figure 5.2). From these responses,

unintentional non-adherence due to forgetfulness and carelessness were identified as the

barrier to adherence and informed the discussion about adherence with these participants.

Figure 5.2 Radar chart of questionnaire responses of REMINDER group at baseline

0

10

20

30

40

50

60

70

80

90

100% MAQ Q1 Forgetful

% MAQ Q2 Careless







100

Case Examples of Individuals who received a Reminder System

Below are three case examples of participants who were provided with a reminder strategy

to improve their adherence (dose administration aid, self-managed dosette box and

treatment simplification).

Case 1: Participant 47 (Table 5.1)

Participant 47 is 73 years of age and takes a total of eight prescription medicines and two

vitamin supplements. She has been taking gliclazide modified-release (MR) tablets 60mg

once daily for the previous 12 weeks for type 2 diabetes.

Table 5.1 Individual scores to validated scales at baseline (Participant 47)

MAQ BMQ-S BIPQ

Score Type Necessity Concern

s

Treatment

Control

Treatment

Coherence

1 0 22 9 8 8

MAQ Score: 1 (low non-adherence) to 4 (high non-adherence). Type: 0 = Unintentional non-adherence, 1 = Intentional

non adherence, 2 = Mix of both types.

BMQ-S: Necessity: 5 (low BMQ-S necessity score) to 25 (high BMQ-S necessity score), Concerns: 5 (low BMQ-S

concerns score) to 25 (high BMQ-S concerns score).

BIPQ: Treatment Control: 1 (treatment not helpful at all) to 10 (extremely helpful), Treatment Coherence: 1 (do not

understand at all) to 10 (understand very clearly).

Intervention

MAQ: Score of 1, unintentionally non-adherent.

BMQ-S: High necessity score and low concerns score – believes medicine is necessary and

does not appear to be concerned about their medicine.

BIPQ: The participant felt she had a decent amount of control over her illness and perceived

her medicines to be very helpful. Participant 47 had a clear understanding of her illness and

was not emotionally affected by her illness.

101

Discussion: It was ascertained that all her medicines were taken either once daily or twice

daily. The discussion also determined that Participant 47 was usually careless and often

forgets to take the evening dose of her medicine. Furthermore, the participant mentioned

that she tended to forget to refill her repeat prescriptions on time.

Adherence Strategy: Agreed in discussion with participant that a fortnightly dose

administration aid would be helpful. This was initiated by her community pharmacy. A dose

administration aid is commonly made up by the pharmacy to help patients who may find it

difficult to organise and remember to take their medications, particularly if they are taking a

great number of medications. It is a plastic tray that compartmentalises medicines into the

appropriate days of the week and times of the day at which the medications should be taken.

The dose administration aid may help to remind her to take the evening doses of her

medicines and also shifts the responsibility of dispensing her repeat prescriptions to the

pharmacy.


Participant 49 takes four prescription medicines and one complementary medicine. He has

been taking perindopril 5mg, once daily for the past four weeks for hypertension.


MAQ BMQ-S BIPQ

Score Type Necessity Concerns Treatment

Control

Treatment

Coherence

1 0 25 10 9 8







102

Intervention


BMQ-S: High necessity score and low concerns score – believes medicine is necessary and

has minimal concerns about his medicine.

BIPQ: The participant seems to have a good understanding of his illness and perceives his

medicine as very helpful.

Discussion: Through discussion with the participant it was discovered that he was using a

once daily self-managed dosette box. Since he was also taking other medicines with a twice-

daily dosing regimen, he sometimes had difficulty distinguishing between the morning and

evening doses when the tablets were in one compartment in the dosette box.

Adherence Strategy: The researcher suggested a dose administration aid; however the

participant felt that they would be losing control over his medication-taking behaviour.

Therefore, the researcher and participant made a shared decision to use a twice-daily

dosette box (compartments for morning and evening doses for each day of the week).


Participant 25 is 52 years old and has been taking metformin 500mg three times daily for

the treatment of type 2 diabetes for the past twelve weeks.


MAQ BMQ-S BIPQ


Control

Treatment

Coherence

2 0 20 12 10 7







103

Intervention


BMQ-S: Participant’s perceived necessity beliefs outweighed his concerns about the

medicine

BIPQ: The BIPQ identified that the participant perceived that their medicines were extremely

beneficial, had minimal concerns about their illnesses and had good understanding of their

illnesses.

Discussion: The participant was prescribed metformin three times daily. The participant

advised that he tended to forget to take his noon dose while he was at work. The participant

was forgetful at taking his medication as prescribed due to the complexity of the treatment

regimen.

Adherence Strategy: The researcher advised that if the GP agrees, changing metformin

conventional dosage form to the extended release dosage form can reduce the dose

frequency from three times daily to once daily. The researcher liaised with the GP and the

GP agreed to replace the conventional metformin 500mg three times daily to extended-

release metformin 500mg three tablets once daily.

Summary of Reminder Strategies

A reminder strategy was implemented in participants identified with unintentional non-

adherence using the MAQ, with no other barriers identified using the BMQ-S, BIPQ and

during the discussion. These strategies included dose administration aids, dosette boxes,

alarm clock reminders and treatment regimen simplification. A shared decision was made

on which strategy would be the most appropriate for each participant. Most reminder

strategies involved employing a dose administration aid, which were organised by the

pharmacy. In our study, some participants did not like the idea of a third party “controlling”

their medicines (Case 2). For these participants, a dosette box was more ideal, as this allows

the participant to organise their medicines. The reminder strategies implemented in this

study are similar to those in the literature (Section 1.6.2).224,234,240,244,246

104

5.3.4 Cognitive-Educational Strategy

Most participants who were provided with education to improve adherence were identified

as intentionally non-adherent, with the majority scoring positively on questions 3 and/or 4 of

the MAQ. Similar to the reminder group, the mean BMQ-S necessity score was high and

BMQ-S concerns score was low. However, the mean BIPQ Treatment Coherence score was

low, indicating that these participants may benefit from information on their illness and

medicine to improve their adherence (Figure 5.3). In comparison to the participants who

received a reminder system these participants were less likely to be unintentionally non-

adherent and have a low mean BIPQ treatment coherence score (Figure 5.2).

Figure 5.3 Radar chart of questionnaire responses of the COGNITIVE-EDUCATIONAL strategy group at baseline

0102030405060708090


% MAQ Q2 Careless







105

Case Examples of Individuals who received a Cognitive-Educational Strategy


Participant 5 is 62 years old and is currently on eight prescription medicines. He was recently

prescribed rosuvastatin 5mg once daily for dyslipidaemia and for the secondary prevention

of ischaemic stroke. The rosuvastatin was prescribed 12 weeks ago; however, he has taken

rosuvastatin for a total of four weeks.


MAQ BMQ-S BIPQ


Control

Treatment

Coherence

3 2 25 14 8 2







Intervention

MAQ: Score of 3, both unintentionally non-adherent and intentionally non-adherent.

BMQ-S: The BMQ-S showed that the participant strongly believed his medicines were

necessary and had relatively minimal concerns.

BIPQ: Indicated a poor of understanding of his conditions

Discussion: The BIPQ indicated that the participant had a poor understanding of his illness.

This information together with the responses to the MAQ was used to guide the discussion

about his medication-taking behaviour and his current knowledge of his medication and

illnesses. It was discovered that he had not been taking the rosuvastatin because he did not

understand the purpose and importance of taking this medication. The participant self-

reported that he takes his other seven medicines “religiously” and also believed that the

106

rosuvastatin is causing his gout attacks. The participant also reported that his general

practitioner (GP) was unaware that he had ceased the rosuvastatin.

Adherence Strategy: The participant was educated on the purpose and benefits of the

rosuvastatin. The participant was advised that the rosuvastatin was not only to help reduce

cholesterol levels, but also to prevent another stroke incident along with his other medicines

taken for stroke prevention. The importance of taking his medicines was emphasised

throughout the interview. Since the participant believed that the rosuvastatin was causing

his gout, education was also provided on the causes of gout and the management of gout.

The researcher also provided information on his medications for gout (allopurinol for gout

prevention and indomethacin for controlling gout attacks) and the participant was advised

that it was unlikely that the rosuvastatin is the causing the gout.


Participant 16 was initiated on irbesartan 300mg once daily, five weeks ago for the treatment

of hypertension.


MAQ BMQ-S BIPQ


Control

Treatment

Coherence

1 1 12 21 10 2







Intervention

MAQ: Score of 1, intentionally non-adherent (ceased medicine when feeling unwell).

107

BMQ-S: The participant’s concerns about her medicine outweighed beliefs that her medicine

were necessary.

BIPQ: The BIPQ showed that the participant believed the medicine was very helpful, but

had a poor understanding of her treatment and condition.

Discussion: The responses to the BMQ-S showed that the participant had concerns about

their medication. Therefore, the interview with the participant involved discussing what her

concerns were and why she had those concerns. The participant advised the researcher

that she was experiencing palpitations ever since she started taking the irbesartan, which

gave her concerns about the medication. Therefore, the participant ceased her irbesartan

when she experienced palpitations. The BIPQ indicated that the participant did not have a

good understanding of her illness and treatment. This was also picked up during the

discussion with the participant about her medication-taking behaviour. Therefore, the

participant was asked about what she felt she knew about her medication and illness and

what she felt she did not know very well.

Adherence Strategy: The participant was educated on hypertension and on how irbesartan

will help with her hypertension. Information on the silent nature of hypertension, the causes

of hypertension and risks of hypertension was provided. Counselling on the benefits and

common adverse effects of irbesartan was provided, including how to manage the side

effects. The participant was advised that because irbesartan reduces blood pressure, it can

sometimes lead to an increase in heart rate and may explain her recent heart palpitations.

The researcher also measured the participant’s blood pressure and provided the participant

with a blood pressure monitoring diary, which included information on managing blood

pressure. The participant was also referred to the GP to discuss her heart palpitations.

Summary of Cognitive-Educational Strategies

Educating individuals on their health can influence a change in adherence through changes

in knowledge, attitudes and beliefs.144 A cognitive-educational strategy to support their

adherence was implemented in participants identified as having poor knowledge on their

medicines and medical conditions without other potential barriers to adherence (Figure 5.3).

Information that was provided to the participants included the benefits of their medicine, the

108

adverse effects and how to manage the adverse effects (Case 4). Depending on the

discussion with the participant, information on their medical condition and what to expect

was also provided (Case 5). Some participants were also provided with pharmacy pamphlets

on medical conditions when appropriate (Case 5). The cognitive-educational strategies

utilised in this study were similar to those implemented in the literature as described in

Chapter One, Section 1.6.2.

109

5.3.5 Reminder and Cognitive-Educational Strategy

All participants who received both a reminder and educational strategy indicated that they

were forgetful at taking their medicine according the MAQ (Figure 5.4). About 60% of the

participants were careless at taking their medicine and some participants intentionally

stopped taking their medicine when they felt well and when they felt worse. Similar to Figure

5.2 and Figure 5.3, the mean BMQ-S necessity score was high and mean BMQ-S concerns

score relatively low. The mean BIPQ treatment control score was also high, indicating that

these participants believed their medicine was helpful. However, unlike the participants who

received a reminder (Figure 5.2), the mean BIPQ treatment coherence score was noticeably

lower, similar to that of the cognitive-educational group (Figure 5.3).

Figure 5.4 Radar chart of questionnaire responses of the REMINDER & COGNITIVE-EDUCATIONAL strategy group at baseline

0102030405060708090


% MAQ Q2 Careless







110

Case Examples of Individuals who received a Reminder and Cognitive-Educational

Strategy


Participant 31, is 75 years old and has been taking metformin extended-release 500mg once

daily for the last 12 weeks for the treatment of type 2 diabetes. She takes five prescription

medications for the treatment of diabetes, depression, osteoarthritis and hypothyroidism.


MAQ BMQ-S BIPQ


Control

Treatment

Coherence

3 2 24 12 10 2







Intervention

MAQ: Score of 3, both unintentionally and intentionally non-adherent.

BMQ-S: The BMQ-S indicates that her beliefs that her medicines are necessary are strong

and concerns about her medicine are relatively weak.

BIPQ: From the BIPQ, the participant seems to have a poor understanding of her medical

condition.

Discussion: It was evident from the discussion that the participant lacked knowledge on

her medical conditions but also on the purpose and benefits of all her medicines. Through

further discussion, it was determined that the participant stopped taking the metformin when

she was feeling “better” and thus forgot to take the medicine. The participant was also

111

uncertain as to why it was important to continue to take the medicine when she felt better.

She did not understand why people have illnesses and how tablets “know where to go.”

Adherence Strategy: The participant was educated on her medical conditions and on her

medicines. Information provided on her illnesses, particularly type 2 diabetes, included the

characteristics of diabetes, symptoms and risks associated with uncontrolled blood glucose

levels. The participant was educated on how the metformin works, the benefits of taking

metformin and the common side effects. The importance of adhering to her medications was

emphasised throughout the discussion. Since she was quite forgetful and had difficulty

managing her medicines, a dose administration aid was initiated by the pharmacy.


Participant 41 is 57 years old and currently taking three prescription medicines and was

prescribed rosuvastatin 10mg once daily, four weeks ago for the treatment of dyslipidaemia.


MAQ BMQ-S BIPQ


Control

Treatment

Coherence

4 2 24 24 8 10







Intervention


BMQ-S: His beliefs that medicines are necessary are strong; however these beliefs are

balanced by his strong concerns about his medicines.

112

BIPQ: The BIPQ indicated that his illnesses significantly affected his life and he had strong

concerns about his illnesses. The BIPQ also suggested that he had a good understanding

of his illnesses, but discussion with the participant led the researcher to believe the contrary.

Discussion: The participant reported he was “terrible at taking medicines.” He is careless

at times when taking his medicine and forgets to take his medicine at least once a week.

Participant 41 often stops his medicines when he is feeling better and when experiencing

side effects, such as dizziness.

Adherence Strategy: The researcher supplied and showed the participant how to use a

dosette box to assist him with managing his medicines. Education was also provided on all

of his medicines, medical conditions and importance of adherence. The participant was

advised on the benefits of the medicines (e.g. rosuvastatin lowers cholesterol levels, which

minimises the risk of cardiovascular events), how taking each of the medications would

improve his medical conditions and hence the importance of taking his medications as

prescribed. Information about the common side effects was provided, including how to

manage the side effects, in particular, the dizziness he was experiencing. After discussion

with the participant’s GP, the participant was advised to take the rosuvastatin at night before

bed instead of in the morning to see whether that helps minimise the dizziness.

Summary of Reminder and Cognitive-Educational Strategy

These participants indicated that they were non-adherent due to forgetfulness or

carelessness and had poor knowledge about their illness and treatment. A combination of a

reminder and cognitive-educational strategy were implemented to support their adherence.

Indications for this type of strategy to be implemented included both unintentional non-

adherence identified using the MAQ and poor understanding on medicine and illness

identified using the BIPQ or through discussion. This was evident on the group radar chart

(Figure 5.4) and on an individual level.

113

5.3.6 Behavioural-Counselling Strategy

All participants in the behavioural-counselling group were identified by the MAQ as either

intentionally non-adherent or a mix of both types of non-adherence (Figure 5.5). There was

a low mean BMQ-S necessity score in this group when compared to the reminder (Figure

5.2) and cognitive-educational group (Figure 5.3). The mean BIPQ treatment control score

was high. Unlike the cognitive-educational group, the behavioural-counselling group had a

high mean BIPQ treatment coherence score, indicating that these participants had a clear

perceived understanding of their illness and treatment (Figure 5.5).

Figure 5.5 Radar chart of questionnaire responses of the BEHAVIOURAL-COUNSELLING strategy group at baseline

0

10

20

30

40

50

60

70

80

90


% MAQ Q2 Careless







114

Case Examples of Individuals who received a Behavioural-Counselling Strategy


Participant 7 is 35 years old and has been taking ramipril 10mg for the last four weeks.


MAQ BMQ-S BIPQ


Control

Treatment

Coherence

3 2 15 18 5 10







Intervention


BMQ-S: The BMQ-S indicated that her concerns about her medicine outweighed her

perceived necessity of the medicine.

BIPQ: The participant perceived that she had little control over her illness, that her treatment

was only moderately helpful and that she understood her condition very clearly.

Discussion: It was discovered that the participant has tried many other medicines to lower

blood pressure. The participant believes that it is highly unlikely that the new

antihypertensive medicine will improve her blood pressure. Pessimism about the new

medication to treat her hypertension was picked up during the discussion with the participant.

Adherence Strategy: The researcher provided health coaching by exploring the

participant’s views of treatment and helped the participant to establish goals of treatment;

for example, blood pressure target. Once goals of treatment were established, strategies to

115

attain these goals were discussed, including adhering to her medication and maintaining

daily physical exercise. The researcher measured the participant’s blood pressure and

provided her with a blood pressure monitoring diary. The participant was advised to check

her blood pressure at the pharmacy on a regular basis to help her observe the efficacy of

her medication.


Participant 54 initiated valsartan 40mg once daily 12 weeks ago for the treatment of

hypertension. The participant is 72 year old and is currently taking five prescription

medicines and one complementary medicine.


MAQ BMQ-S BIPQ


Control

Treatment

Coherence

1 1 20 17 8 5







Intervention

MAQ: Score of 1, intentionally non-adherent (ceased medicines when feeling better).

BMQ-S: The participant perceives their medicine is necessary; however, also holds strong

concerns about his medicine.

BIPQ: The responses to the BIPQ indicated that the participant has a moderate

understanding of his illness.

Discussion: The researcher further explored the participant’s beliefs and perceptions of his

medicines. The participant believes that “taking medicines for a long time would reduce the

116

effectiveness of the medicine.” The participant also believed that taking the same medication

for a long time “must not be good for the body.” Therefore, he had made an appointment

with a new GP to prescribe him a new medicine for hypertension (valsartan).

Adherence Strategy: The researcher also explored the participant’s treatment goals,

educated the participant on the silent nature of hypertension and the importance of

medication adherence. Education on his medications was provided in the hope of changing

his beliefs, including how medicines work and how some medicines may be effective for one

person and not another and hence sometimes medicines are prescribed based on a trial

and error approach. During the baseline interview, the researcher conducted a blood

pressure measurement and advised him to regular check his blood pressure to monitor the

effectiveness of the medication.

Summary of Behavioural-Counselling Strategies

Behavioural-counselling strategies implemented included health coaching and exploring

beliefs about medicines and illness perceptions in more depth. Health coaching is used as

an adherence intervention by facilitating the establishment of treatment goals to support

adherence to medications (Case 8). The health coaching provided in this study was

considerably more abbreviated compared to the health coaching described to improve

adherence in the literature.226,250 Health coaching with evidence in the literature usually

involves multiple sessions over a long period of time and conducted by a trained

personnel.250 Our goal was to provide a relatively quick intervention to improve medication

adherence that may have the potential to be readily translated into clinical practice.

117

5.3.7 Social Support Strategy

The discussion with the participant and caregiver was the driving force in the decision to

implement a social support strategy to improve adherence. Most participants were identified

as unintentionally non-adherent due to forgetfulness and carelessness using the MAQ

(Figure 5.6). The mean BMQ-S necessity score was high and BMQ-S concerns score was

low, compared to participants who received a behavioural-counselling strategy (Figure 5.5).

The mean BMQ-S scores appear similar to those that received a reminder strategy (Figure

5.2). Both the mean BIPQ treatment control score and mean BIPQ treatment coherence

score were high, showing that these participants believed the medicine was helpful and

believed that they had a clear understanding of their illness (Figure 5.6). From the discussion

with these participants, it was evident that they may need some support with managing their

medications. See individual cases for further details (Table 5.10 and Table 5.11).

Figure 5.6 Radar chart of questionnaire responses of the SOCIAL SUPPORT strategy group at baseline

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% MAQ Q2 Careless







118

Case Examples of Individuals who received a Social Support Strategy


Participant 80 is 65 years old and was prescribed amlodipine 10mg once daily, four weeks

ago to lower his blood pressure.


MAQ BMQ-S BIPQ


Control

Treatment

Coherence

2 0 24 9 10 8







Intervention


BMQ: Responses to the BMQ-S indicate that the participant believed their medicine was

necessary and had relatively minimal concerns about his medicine.

BIPQ: Participant 80 felt that he had moderate control over his illness, perceived that the

medicines were extremely helpful and had a good perceived understanding of his illness.

Discussion: From the discussion with the participant, the participant had great difficulty in

remembering to take his medicines due to early onset dementia. His daughter who was

there at the baseline interview told the researcher that she takes care of him at home;

however, did not look after his medicines.

119

Adherence Strategy: Therefore, the researcher advised the daughter to support the

participant with his medications. Since the participant was currently taking 12 medicines, a

dose administration aid was also initiated by the pharmacy to assist the daughter in

supporting the participant with his medications.

Summary of Social Support Strategy

Social support strategies were indicated in participant’s identified as requiring support with

managing their medications. Decision to implement this type of strategy relied on the

discussion with the participant and carer, more so than the responses to the adherence

scales. Discussion with these participants identified a need of support from a family member

with their medication-taking behaviour. In the literature, social support strategies to improve

medication adherence typically involved peer support group therapy. Overall these peer

support groups have not been very successful at improving adherence (Section 1.6.2). Our

study on the other hand, involved a close family member to support the participant with their

medication-taking behaviour or supporting their decision by discussing with their GP.

5.4 Flow Diagram of Tailoring Adherence Intervention (Post-Implementation)

After data collection was complete, we explored the common responses to the scales and

discussion with the participants in each of the types of tailored strategies. The MAQ was

used to identify medication-taking behaviour and whether the participant’s non-adherence

was unintentional, intentional or a mix of both. The BMQ-S provided information on the

participant’s beliefs that medicines were necessary and their concerns regarding their

medicines. The BIPQ explored the participant’s illness perceptions that have been

associated with adherence. This information guided the discussion about what may be

influencing the participant’s non-adherence. This helped inform the implementation of a

tailored strategy to improve their medication adherence. From this data, I was able to

generate a flow diagram that may help explain my thought process when deciding which

strategy to implement (Figure 5.7). Approximately 63% of the participants fit in this model.

The responses to the validated scales helped to inform the discussion with the participant

to identify or confirm the reason for non-adherence. The selection of the tailored strategy

120

relied on this discussion with the participant, which may explain why 37% of participants did

not fit into this model, as shown in Figure 5.7. It was quite easy to select an appropriate

tailored strategy to improve adherence for each individual based on the responses to the

MAQ, BMQ-S, BIPQ and discussion. However, to describe how each of these groups were

treated was much more difficult due to the many different variables identified in the

discussion. The groups were indistinct and there was some overlap, particularly between

the cognitive-educational and behavioural-counselling strategy groups.

We hope that with a larger study, a potential “toolkit”/flow diagram could be designed to

assist health professionals to implement a tailored intervention to improve medication

adherence based on their responses to the MAQ, BMQ-S and BIPQ. This flow diagram

would help health professionals to select the most appropriate intervention to improve the

patient’s adherence to the medication.

121

Figure 5.7 Flow diagram of outcomes of the adherence scales used to inform the discussion with the participant and implementation of the tailored strategy

122

5.5 Conclusions

Chapter Five described the targeted and tailored intervention which was informed by

responses to validated scales (MAQ, BMQ-S and BIPQ) and discussion with the participant.

The responses to the scales provided insight into the participant’s reasons for non-

adherence, which guided the discussion and implementation of a tailored strategy to

improve adherence. As illustrated in the case examples, this intervention is simple and easy

to administer, hence would have the potential for implementation in clinical practice.

The radar charts were presented in Chapter Five to provide a graphical representation of

the similarities and differences in responses to the scales between participants who received

different tailored strategies. From these radar charts, we can visually observe that these

participants had different barriers to adherence, beliefs and illness perceptions that may

explain their non-adherence. These responses to the adherence scales or patterns of the

radar charts may help in the implementation of a tailored intervention in practice.

Chapter Six will explore how adherence, beliefs about the medicine and illness perceptions

changed over time in the study sample

123

CHAPTER SIX: RESULTS 3 - CHANGES IN ADHERENCE OVER SIX MONTHS

6.1 Introduction

The intervention targeted to non-adherent participants and tailored to the participant-specific

reasons for non-adherence significantly improved adherence at three months, as presented

in Chapter Four. This significant improvement in adherence was sustained at six months.

Chapter Five provided detail on the intervention that included how the responses to the

adherence scales and discussion with the participant informed the tailored strategy.

This chapter addresses the following hypothesis:

- Hypothesis 3: Adherence, and reasons for non-adherence (beliefs about medicines

and illness perceptions), will change over time in all groups studied.

Chapter Six explores the differences between the intervention, control and adherent groups

in relation to adherence to the medication (MAQ), beliefs about the medicine (BMQ-S) and

illness perceptions (BIPQ) over the six months and changes over time. We were interested

in exploring the changes in the groups to see if there were patterns emerging in relation to

adherence. Changes in adherence, beliefs and illness perceptions were also explored for

each of the different types of adherence strategies implemented to determine if there were

any patterns to explain how the intervention improved medication adherence.

6.2 Differences between the Adherent, Intervention and Control Groups

At baseline, there were differences in medication adherence, beliefs about medicines and

illness perceptions between the adherent and non-adherent (intervention and control)

groups. Over time, adherence, beliefs about the medication and illness perceptions changed

differently in each of the groups.

124

6.2.1 Adherence over time

Medication adherence changed over time in the adherent, intervention and control groups,

as shown in Figure 6.1. At baseline, the mean MAQ score was not different between the

intervention and control group. However, at three and six months the mean MAQ score

reduced significantly in the intervention group, resembling more closer to that observed in

the adherent group. Conversely, the mean MAQ score did not change significantly in the

control group. In the adherent group, there was a small but significant rise in the MAQ score

at three months but this reduced at six months. See Appendix E for tables of mean MAQ

score over time in the adherent, intervention and control groups.

Figure 6.1 Changes in mean MAQ scores (± 95% confidence intervals) in the adherent, intervention and control groups over time

125

6.2.2 BMQ-S Necessity over time

Figure 6.2 presents the mean BMQ-S necessity scores at baseline, three and six months in

the adherent, intervention and control groups. At baseline there were no significant

differences in the BMQ-S necessity scores between the three groups. However, over the

study period, the BMQ-S necessity scores increased in the intervention group and

decreased in the control group. The BMQ-S necessity scores in the control group were

significantly lower than both the adherent and intervention groups at six months. This

suggests that the beliefs held by the participants in the adherent and intervention groups

towards the necessity of their medicines were similar and stronger than those held by

participants in the control group at the end of the study.

Figure 6.2 Changes in mean BMQ-S necessity scores (± 95% confidence intervals) in the adherent, intervention and control groups over time

126

6.2.3 BMQ-S Concerns over time

The changes in the mean BMQ-S concern scores in the adherent, intervention and control

groups over time are shown in Figure 6.3. At baseline there was no significant difference

between the three groups, although the BMQ-S concerns score was lower in the adherent

group compared with the non-adherent (intervention and control) group. Over the study

period the BMQ-S concerns score decreased for both the adherent group and the

intervention group and increased for the control group. This suggests that the strength of

concerns beliefs towards medicines reduced in those participants in the adherent and

intervention groups and increased in those participants in the control group. Appendix F

provides the mean BMQ-S necessity and concerns scores over time in the adherent,

intervention and control groups.

Figure 6.3 Changes in mean BMQ-S concerns scores (± 95% confidence intervals) in the adherent, intervention and control groups over time

127

6.2.4 BIPQ Treatment Control over time

Although not statistically significant, Figure 6.4 shows that the intervention and control group

had a lower mean BIPQ treatment control score at baseline than the adherent group,

reflecting that the non-adherent (intervention and control) group may have felt that their

medication was less helpful in treating their illness. As time progressed, this changed with

the BIPQ treatment control score increasing in the intervention group suggesting that they

perceived their medication was more helpful in treating their illness. In contrast the score

decreased in the control group suggesting that they perceived their medication was less

helpful in treating their illness. In other words, the intervention group moved in a direction

closer to that of the adherent group in regards to how helpful they perceived their medication

and the control group moved further away from the adherent group.

Figure 6.4 Changes in mean BIPQ treatment control scores (± 95% confidence intervals) in the adherent, intervention and control groups over time

128

6.2.5 BIPQ Treatment Coherence over time

Figure 6.5 presents the mean BIPQ treatment coherence scores in the three groups over

time. Participants in the adherent group at baseline had a better understanding of their

illness and treatment than the non-adherent (intervention and control) group at baseline. As

time progressed, the mean BIPQ treatment coherence scores increased in the intervention

group suggesting that their understanding of their illness and treatment improved. In the

control group the mean BIPQ treatment coherence scores decreased suggesting that their

understanding of their illness and treatment was not as clear over time. From Figure 6.5, we

can see that over time, the three groups had different changes in their understanding of their

illness and treatment. For more details on changes in illness perceptions over time in the

adherent, intervention and control group, see Appendix G.

Figure 6.5 Changes in mean BIPQ treatment coherence scores (± 95% confidence intervals) in the adherent, intervention and control groups over time

129

The targeted and tailored intervention changed beliefs about medicines and illness

perceptions over time, which was mirrored by a significant improvement in medication

adherence. The changes in beliefs about medicines and illness perceptions in the

intervention group moved towards a pattern similar to that of the adherent group. The control

group seemed to have more negative beliefs about the medicines and poorer illness

perceptions over time. To better understand how the intervention improved adherence, the

changes in beliefs about the medication and illness perceptions were explored within each

of the tailored strategies.

6.3 Changes in each of the Tailored Strategy Groups

6.3.1 Reminder Strategy Group (n=27)

Participants identified with forgetfulness or carelessness as a barrier to their adherence were

provided with a reminder strategy to support their adherence. The reminder strategy group

had a higher mean BMQ-S necessity score, a lower mean BMQ-S concerns score and a

higher mean BIPQ coherence score than the intervention group at baseline.

The mean MAQ score in the reminder strategy group reduced significantly at three and six

months (p<0.001). The mean BMQ-S concerns score was significantly lower at six months

compared to baseline and three months (Table 6.1). The mean BIPQ coherence score was

significantly higher at 3 months and 6 months, compared to baseline (Table 6.1).

130

Table 6.1 Change in mean MAQ, BMQ-S, and BIPQ treatment and coherence scores over time in the REMINDER strategy group

Reminder Time

p-value

Baseline 3 months 6 months 0 to 3 months

0 to 6 months

3 to 6 months

Mean MAQ score

1.30±0.47

0.33±0.55 0.30±0.54 <0.05* <0.05* 0.7457

Mean BMQ-S Necessity score

20.07±2.81 20.00±2.73 20.19±2.84 0.8591 0.8274 0.6959

Mean BMQ-S Concerns score

12.19±2.99 11.44±2.67 10.59±3.13 0.1546 <0.05* <0.05*

Mean BIPQ Treatment Control score

8.59±1.50 8.81±1.33 8.63±1.62 0.5229 0.9188 0.5971

Mean BIPQ Coherence score

8.26±1.53 8.81±1.39 9.15±0.95 <0.05* <0.05* 0.2403

At baseline, all participants who received a reminder strategy to improve adherence were

identified as unintentionally non-adherent due to forgetfulness or carelessness, based on

the MAQ (Figure 6.6). The radar charts in Figure 6.6 are a visual representation of how

adherence, beliefs about medicines and illness perceptions changed over time in the

reminder strategy group. It can be seen quite clearly in the three- and six-month radar charts

that most of these participants were no longer unintentionally non-adherent to their medicine.

As we progress through the radar charts, baseline to three months to six months, it can be

seen that adherence improves, concerns about medicines declines and treatment

coherence score improves (Figure 6.6).

131

0102030405060708090


% MAQ Q2 Careless







Baseline

0

10

20

30

40

50

60

70

80

90

100

% MAQ Q1

% MAQ Q2

% MAQ Q3

% MAQ Q4





3 months

132

Figure 6.6 Radar charts at baseline, 3 months and 6 months for the REMINDER strategy group

0102030405060708090

100

% MAQ Q1

% MAQ Q2

% MAQ Q3

% MAQ Q4





6 months

133

6.3.2 Cognitive-Educational Strategy Group (n=9)

The participants who received a cognitive-educational strategy to improve their adherence,

were identified with poor understanding of their illness and treatment (Chapter Five). In

comparison to the intervention group, the cognitive-educational strategy group had a lower

mean BIPQ coherence score at baseline. These participants were provided with information

on adherence, the benefits of their medication, potential adverse effects and how to manage

their illness. In this group the cognitive-educational strategy seems to have improved their

understanding of their illness and treatment, as evident from the increase in the mean BIPQ

coherence score (Table 6.2).

The mean MAQ score was significantly lower at three and six months than at baseline in the

cognitive-educational strategy group. There were no significant changes in the mean BMQ-

S scores. At three and six months, the mean BIPQ coherence score increased significantly

from baseline in the group that received a cognitive-educational strategy (Table 6.2). This

change reflects that the strategy improved the participant’s understanding of their illness

and treatment.

Table 6.2 Change in mean MAQ, BMQ-S, and BIPQ treatment and coherence scores over time in the COGNITIVE-EDUCATIONAL strategy group

Cognitive-Educational

Time

p-value


0 to 6 months

3 to 6 months

Mean MAQ score

1.33±0.71 0.22±0.44 0.33±0.71 <0.05* <0.05* 0.6811


19.33±4.18 19.56±4.03 19.89±4.04 0.7824 0.6625 0.6406


13.44±3.88 13.33±2.96 12.89±3.37 0.9019 0.7124 0.5776


7.56±2.60 8.33±1.94 9.00±1.12 0.1739 0.0827 0.0805


5.33±3.08 9.00±1.22 9.22±1.09 <0.05* <0.05* 0.6646

134

Changes in adherence, beliefs about medicines and illness perceptions over time in the

cognitive-educational strategy group can be observed in the radar charts in Figure 6.7. At

baseline, the mean BIPQ treatment coherence score was low, indicating poor understanding

of illness. As we move to the three- and six-month radar chart, we can see an increase in

this score, reflecting an improvement in understanding. Most participants in the cognitive-

educational strategy group were identified as being intentionally non-adherent. From the

radar charts, we can see that most of these participants were no longer intentionally non-

adherent (Figure 6.7).

135

0102030405060708090


% MAQ Q2 Careless




Mean BMQ-S Concerns Score



Baseline

0

10

20

30

40

50

60

70

80

90

100

% MAQ Q1

% MAQ Q2

% MAQ Q3

% MAQ Q4





3 months

136

Figure 6.7 Radar charts at baseline, 3 months and 6 months for the COGNITIVE-EDUCATIONAL strategy group

0

10

20

30

40

50

60

70

80

90

100

% MAQ Q1

% MAQ Q2

% MAQ Q3

% MAQ Q4





6 months

137

6.3.3 Reminder and Cognitive-Educational Strategy Group (n=15)

The reminder and cognitive-educational strategy group were identified with both

forgetfulness and poor understanding of illness and treatment as barriers to their adherence.

These participants were provided with a reminder strategy and information on their illness

and medication to support their adherence. At baseline, the mean BIPQ coherence score

was lower than the intervention group. In contrast to the cognitive-educational strategy group,

the mean BIPQ coherence score did not improve significantly over time. One explanation

may be the education provided on the medication and illness was not as thorough because

a reminder strategy was also implemented. For these participants, the main barrier to

adherence may have been forgetfulness and hence an improvement in adherence was

observed.

At three and six months, the mean MAQ score was lower than at baseline in the reminder

and cognitive-educational strategy group. There were no significant changes in the mean

BMQ-S and mean BIPQ scores (Table 6.3).

Table 6.3 Change in mean MAQ, BMQ-S, and BIPQ treatment and coherence scores over time in the REMINDER & COGNITIVE-EDUCATIONAL strategy group

Reminder and Cognitive-

Educational

Time

p-value


0 to 6 months

3 to 6 months

Mean MAQ score

2.07±1.03 0.60±0.63 0.73±0.70 <0.05* <0.05* 0.4985


18.67±3.44 18.87±3.00 19.80±3.41 0.7451 0.1713 0.1954


15.60±3.25 16.00±3.61 14.73±3.99 0.6158 0.3699 0.1916


7.73±2.09 8.13±2.29 8.13±2.03 0.3478 0.1887 1.0000


6.13±3.44 7.07±3.17 6.80±3.17 0.3265 0.3625 0.6946

138

The radar charts presented in Figure 6.8 show the changes in adherence, beliefs about

medicines and illness perceptions from baseline to six months in the reminder and cognitive-

educational strategy group. From the baseline radar chart, we can see that all participants

were unintentionally non-adherent to their medication due forgetfulness or carelessness,

and had a relatively poor understanding of their illness. Moving on to the three and six month

radar charts, it shows that most participants are no longer non-adherent and perceived

coherence has slightly improved (Figure 6.8).

139

0102030405060708090


% MAQ Q2 Careless







Baseline

0

10

20

30

40

50

60

70

80

90

100

% MAQ Q1

% MAQ Q2

% MAQ Q3

% MAQ Q4

Mean BMQ-S Necessity Score

Mean BMQ-S Concerns Score



3 months

140

Figure 6.8 Radar charts at baseline, 3 months and 6 months for the REMINDER AND COGNITIVE-EDUCATIONAL strategy group

6.3.4 Behavioural-Counselling Strategy Group (n=4)

A behavioural-counselling strategy was implemented in participants with negative beliefs

about their medicines and/or lacking optimism or motivation with their medication. In this

strategy group, the mean BMQ-S necessity score was lower and the mean BMQ-S concerns

score was relatively higher than the intervention group at baseline. The mean BIPQ

coherence score was higher than the intervention group, indicating that this group had a

better understanding of their illness. The mean BIPQ treatment control score in the

behavioural-counselling strategy group was relatively lower than the intervention group at

baseline. At six months, the mean BIPQ treatment control score increased to ten, indicating

the participants in this group perceived their medicine was more helpful.

0

10

20

30

40

50

60

70

80

90

100

% MAQ Q1

% MAQ Q2

% MAQ Q3

% MAQ Q4





6 months

141

Mean MAQ decreased significantly at three months in the behavioural-counselling strategy

group, but this was not sustained at six months. The mean BMQ-S necessity score

increased over time and the mean BMQ-S concerns score decreased over time. The mean

BIPQ treatment control score increased over time, reflecting that the medicine was

perceived as more helpful in treating their illness (Table 6.4). The changes in the mean

BMQ-S and BIPQ scores were not significant, which may be explained by the small sample

size in this group (n=4).

Table 6.4 Change in mean MAQ, BMQ-S, and BIPQ treatment and coherence scores over time in the BEHAVIOURAL-COUNSELLING strategy group

Behavioural-Counselling

Time

p-value


0 to 6 months

3 to 6 months

Mean MAQ score

2.00±1.15 0.25±0.50 0.50±1.00 <0.05* 0.0577 0.7177


18.50±2.65 20.50±2.08 21.75±2.87 0.4437 0.2444 0.2783


14.50±3.70 13.50±3.32 12.25±4.03 0.5137 0.2289 0.1411


7.75±2.06 8.25±2.06 10.00±0.00 0.6376 0.1170 0.1881


8.25±2.36 8.50±1.73 8.00±2.16 0.6376 0.3910 0.1817

Figure 6.9 is a pictorial representation of the changes in adherence, beliefs about medicines

and illness perceptions in the behavioural-counselling strategy group. As observed on the

baseline radar chart, all participants in this group were identified with intentional non-

adherence due to ceasing the medicine when feeling well. As we progress through the radar

charts from baseline to three months and six months, the mean BMQ-S necessity score

increases and the mean BMQ-S concerns score decreases in the behavioural-counselling

strategy group (Figure 6.9).

142

0102030405060708090


% MAQ Q2 Careless







Baseline

0

10

20

30

40

50

60

70

80

90

100

% MAQ Q1

% MAQ Q2

% MAQ Q3

% MAQ Q4





3 months

143

Figure 6.9 Radar charts at baseline, 3 months and 6 months for the BEHAVIOURAL-COUNSELLING strategy group

0

10

20

30

40

50

60

70

80

90

100

% MAQ Q1

% MAQ Q2

% MAQ Q3

% MAQ Q4





6 months

144

6.3.5 Social Support Strategy Group (n=5)

Five participants in the intervention group were identified as requiring social support with

their medication adherence; for example, support from a family member with taking their

medication. Compared to the intervention group, this strategy group had a higher mean

BMQ-S necessity score and a lower BMQ-S concerns score at baseline. The social support

strategy group had higher mean BIPQ treatment control and coherence scores than the

intervention group at baseline.

At three months, the mean MAQ score was lower than at baseline in the social support

strategy group. This significant decrease in mean MAQ score was not sustained at six

months. There were no significant changes in the mean BMQ-S and mean BIPQ scores

(Table 6.5).

Table 6.5 Change in mean MAQ, BMQ-S, and BIPQ treatment and coherence scores over time in the SOCIAL SUPPORT strategy group

Social Support Time

p-value


0 to 6 months

3 to 6 months

Mean MAQ score

1.80±0.45 0.80±0.84 1.00±0.71 <0.05* 0.0993 0.3739


21.20±2.59 21.40±2.19 21.40±3.36 0.8276 0.7489 1.0000


13.40±4.04 11.40±1.52 12.25±4.03 0.2577 1.0000 0.2204


9.00±2.24 9.00±2.24 7.80±2.17 1.0000 0.1778 0.1778


8.20±1.10 8.60±1.67 7.60±1.67 0.6213 0.3739 0.2663

Figure 6.10 is a visual representation of changes in adherence, beliefs about medicines and

illness perceptions in the social support strategy group. Over time, we can observe an

improvement in adherence; however, relatively little change in the beliefs about medicines

and illness perceptions were observed in this group (Figure 6.10).

145

0102030405060708090


% MAQ Q2 Careless







Baseline

0

10

20

30

40

50

60

70

80

90

100

% MAQ Q1

% MAQ Q2

% MAQ Q3

% MAQ Q4





3 months

146

Figure 6.10 Radar charts at baseline, 3 months and 6 months for the SOCIAL SUPPORT strategy group

0

10

20

30

40

50

60

70

80

90

100

% MAQ Q1

% MAQ Q2

% MAQ Q3

% MAQ Q4





6 months

147

6.3.6 Overall View of the Changes in Adherence Scale Scores over time for each

Tailored Strategy

Figure 6.11 and 6.12 are an overall summary of the changes in the mean scores of the MAQ,

BMQ-S and two items of the BIPQ (treatment control and coherence) in each of the tailored

strategy groups at three and six months, respectively. At three months, little change was

visually observed in the mean BMQ-S necessity score in all of the strategy groups, with the

exception of the behavioural-counselling strategy group. Concerns about medicine reduced

in the reminder, behavioural-counselling and social support strategy groups. All five groups

had little change in the mean BIPQ treatment control scores. At three months, the cognitive-

educational group had a significant improvement in the BIPQ treatment coherence score,

reflecting a better perceived understanding of their illness. These changes were sustained

at six months (Figure 6.12).

148

Figure 6.11 Change in Questionnaire Scores at three months for each Strategy Type in the Intervention Group

-3

-2

-1

0

1

2

3

4

Mean MAQ Score Mean BMQ-SNecessity Score

Mean BMQ-SConcerns Score



Ch

ange

in Q

ue

stio

nn

aire

Sco

res

Reminder systems


Reminder and Cognitive-educational

Behavioural-counselling

Social support

149

Figure 6.12 Change in Questionnaire Scores at six months for each Strategy Type in the Intervention Group

-3

-2

-1

0

1

2

3

4

5

Mean MAQ Score Mean BMQ-SNecessity Score

Mean BMQ-SConcerns Score



Ch

ange

in Q

ues

tio

nn

aire

Sco

re

Reminder systems


Reminder and Cognitive-educational

Behavioural-counselling

Social support

150

6.4 Discussion

Improved adherence during the study period reflected reduced concerns towards medicines

and improved perceived understanding of illness and treatment. A close relationship

between good adherence and strong beliefs that the medicine is necessary and fewer

concerns about the medicine has been well-documented in the literature.88,131 In the

intervention group, there was an improvement in perceived understanding of their illness

and treatment over the study period, which may help to explain the sustained improvement

in adherence.

When we consider the individual adherence strategies employed, the results from the

adherence questionnaires explain how the intervention impacted on an individual’s

knowledge, understanding and beliefs and how this translated into improved adherence. In

participants where forgetfulness or carelessness was a barrier to adherence and they

received a reminder intervention their changes in beliefs towards their medicines or their

illness as measured by the BMQ-S and BIPQ were minimal. This is to be expected as the

adherence strategy was purely to support their forgetfulness. In contrast, participants who

received a cognitive-educational intervention (information on their treatment and illness) had

significant changes in their knowledge and understanding of their illness. For these

individuals this change reflected an improvement in their adherence. Studies providing

education to improve participant’s knowledge on their treatment and illness have shown to

improve understanding of illness and treatment, similar to that observed in this study.

However, these studies did not show an improvement in adherence, which may be because

the intervention was not targeted to non-adherent participants.268,308 Those participants with

negative beliefs about their medicine, discussing their concerns and motivation and/or

establishing health goals resulted in changes in their beliefs towards their medicines,

particularly a reduction in concerns towards medicines. Reduced concerns in regards to

medicines has been significantly associated with better adherence.44,131 These changes in

beliefs and illness perceptions may explain the significant improvement in adherence

observed in the behavioural-counselling strategy group.

There were differences in the beliefs towards medicines and illness perceptions between

the control (non-adherent) group and the adherent group over time. The adherent group felt

that over time their illness had a reduced impact on their lives, they had a greater control

over their illness and they had less concerns about their illness. Other studies have found

that participants with good adherence to their medication, felt that they had greater control

151

over their illness and were less emotionally affected by their illness.125,135 The adherent

group held strong beliefs that their medicine was necessary, which remained steady over

the six month study period. The adherent group also had fewer concerns in regards to their

medicine and this declined over time. These changes may be a reflection of participants

who are established on their medication and their medical condition may now be well-

controlled, reinforcing beliefs in the necessity of their medicines to achieve this control.

In contrast, the control group felt their illness was affecting their lives more, felt that their

medicine was less helpful, experienced more severe symptoms and were more emotionally

affected by their illness at six months. Since these participants were non-adherent to their

medication, these participants may not have received the full benefits of their medication,

leading to the negative view observed in this control group. It cannot be confirmed whether

the negative changes in the beliefs about medicines and illness perceptions over time are a

cause of non-adherence or an effect of non-adherence. For example, did non-adherence to

their medication lead to poor control of illness, which led to more severe symptoms of illness

and greater concerns, or did poor control of illness, severe symptoms and greater concerns

lead to non-adherence? Studies have found a relationship between the effect of the illness,

emotional response towards the illness and adherence.40,95,125,134 Nicklas et al. found that

participants non-adherent to their chronic pain medication were more emotionally affected

by their illness.125 Beliefs that their medicine was necessary was relatively weaker in the

control group than the adherent group. A declining trend in the beliefs that the medicine was

necessary was observed over time. This was also observed in a study which implemented

a text message program designed to modify beliefs to improve adherence to asthma

medications. At 18 weeks, the control group had a decline in the BMQ-S necessity score.130

Massey et al. measured self-reported adherence, beliefs about medicines (BMQ-S) and

illness perceptions (BIPQ) in participants six weeks and six months after kidney

transplantation. Medication non-adherence significantly increased from 17% at six weeks to

27% at six months port-transplantation. This study found the mean BMQ-S necessity score

in the population was significantly lower at six months. The mean BMQ-S concerns score

did not significantly change over time.41

6.5 Conclusions

Improvements in adherence in the intervention group were supported by the positive

changes in the beliefs about medicines and illness perceptions. The targeted and tailored

152

intervention changed beliefs about medicines and illness perceptions in a direction that

mirrors the beliefs observed in an adherent population. The intervention group had less

concerns about their medicines, better control over their illness and a clearer understanding

of their illness and treatment over time. Changes in adherence, beliefs about medicines and

illness perceptions in the intervention group at three and six months reflect patterns seen in

the adherent group. These pattern changes in adherence, beliefs about medicines and

illness perceptions are different to that observed in the control group. Improvement in beliefs

about medicines and illness perceptions may help to explain how the intervention improved

adherence.

153

CHAPTER SEVEN: DISCUSSION

7.1 Introduction

Medications remains one of the most frequently used treatments for managing chronic

diseases.309 However, many patients do not adhere to their medications due to an

unconscientious and uninformed decision, leading to adverse health outcomes.11,27,73 As

discussed in Chapter One, medication non-adherence affects approximately 50% of patients

prescribed chronic medications. Patients are non-adherent to their medication due to many

different reasons, including forgetfulness, concerns about medicines and poor

understanding of their treatment. Previous studies have aimed to improve medication

adherence through interventions, such as reminders, education and motivational

interviewing.219,236,266 Current interventions to improve adherence have had mixed

results.13,15 Adherence interventions to date have often been implemented in a population

without first identifying whether the patient was currently adherent or non-adherent and

hence may provide an intervention to an individual who was already adherent to their

medication. Interventions that have been tailored, were often tailored to a specific disease

population or tailored a particular type of intervention, rather than tailored to the participant-

specific reasons for non-adherence. Promising interventions include multifaceted

interventions, tailored interventions and targeted interventions, such as the Measurement-

Guided Medication Management (MGMM).214,216 To target and tailor an adherence

intervention we require a measure that can identify medication-taking behaviour and explore

the reasons for non-adherence in a practical way. The overall aim of this thesis was to

improve medication adherence using a targeted and tailored intervention informed by

validated adherence scales.

7.2 Validated Adherence Scales

Chapter Two presented the systematic review on validated adherence scales. The

systematic review identified 43 adherence scales that have been correlated with a

comparison measure of adherence. The adherence scales elicit different facets of

adherence: medication-taking behaviour, barriers to adherence and beliefs associated with

adherence.

154

Measurement-Guided Medication Management uses a measure of adherence to guide the

intervention. In the literature, MEMS is used to identify medication-taking behaviour and this

information is used to guide the feedback.214 Eliciting barriers to adherence and beliefs

associated with adherence can be used to identify patient-specific reasons for non-

adherence. Adherence scales can be used in a similar manner to MEMS in the MGMM

intervention to inform the discussion with the participant about reasons for non-adherence

and guide the implementation of a tailored strategy to improve adherence.

From the systematic review, the MAQ and BMQ-S were selected for use in a targeted and

tailored intervention.213 The MAQ was used to identify medication-taking behaviour and the

type of non-adherence the participant was exhibiting. The MAQ is one of the most commonly

used scales and has been validated against a range of objective measures including MEMS

and clinical outcomes.18,72,293,296 The BMQ-S has been extensively used in many different

disease populations to elicit patient’s beliefs that the medicine is necessary and concerns

about their medicine.4,89,117,124 The relationship between illness perceptions and medication

adherence has also been well-established in the literature.136-139 The BIPQ was also

included in the intervention to shed more light on the complex nature of adherence.139

7.3 Targeted and Tailored Intervention

In Chapter Three and Five of the thesis, the use of validated scales in a similar manner to

an MGMM approach was described. The intervention involved the use of questionnaires

(MAQ, BMQ-S and BIPQ), discussion with the participant about their adherence and the

implementation of a tailored strategy to improve adherence (Chapter Five). The MAQ was

used to identify non-adherence and to distinguish whether non-adherence to the medication

was unintentional, intentional or a mix of both. The BMQ-S elicited beliefs about medicines

and the BIPQ was used to explore the participant’s illness representations. The responses

to these tools informed the discussion with the participant about reasons for their non-

adherence. This guided the implementation of an evidence-based tailored strategy to

support adherence. This intervention was simple and quick to administer. The improvement

in adherence observed in our study, reported in Chapter Four, is consistent with other

studies that targeted an intervention to a non-adherent sample,247,310 and tailored an

adherence strategy to the participant-specific reasons for non-adherence.130,153,219,229,230

The changes that were observed in the participant’s beliefs and illness perceptions in the

intervention group compared to the control group may help explain how the intervention

155

improved adherence (Chapter Four). The intervention group had a significantly higher

necessity score on the BMQ-S than the control group, reflecting an increase in the strength

of the participant’s belief in the necessity of medicines due to the intervention. The

association between beliefs that medicines are necessary and medication adherence has

been well-established in the literature.4,95,126,127,130,131 However, few studies have used the

BMQ-S, as we did in our study, to explain how an intervention may have impacted

adherence. The BIPQ was used to explore the participant’s illness perceptions, in particular,

the participant’s understanding of their illness and whether they perceived their medicines

as helpful. This information helped to identify participants who may benefit from information

on their medicine and illness. The intervention group had a significantly higher BIPQ

treatment coherence score than the control at three and six months, which indicates a

clearer perceived understanding of their illness. Similarly, the intervention group believed

their medicine was more helpful than the control group at three and six months.

Improvement in adherence observed in the intervention group at three months was

sustained at six months. The sustained improvement in adherence was mirrored by

sustained improvements in beliefs about medicines and illness perceptions. Improvement in

adherence, beliefs about medicines and illness perceptions is likely due to the impact of the

targeted and tailored nature of the intervention.

7.4 Changes in Adherence, Beliefs about Medicines and Illness Perceptions

over Time

At the start of the study, the adherent group and non-adherent (intervention and control)

group were distinctly different in terms of not only their adherence but their beliefs towards

the medicine and illness perceptions. Over time these differences changed. In the

intervention group, there was a significant improvement in adherence, which was mirrored

by a strengthening in their beliefs about medicines and an improvement in their illness

perceptions, in particular, in their understanding of their treatment and illness. These

changes reflected the beliefs towards medicines and illness perceptions in the adherent

group, suggesting that the intervention had improved adherence and impacted on beliefs

and illness perceptions in a way that facilitated adherent behaviour. The changes in

adherence, beliefs about medicines and illness perceptions were also explored in the

different tailored strategy groups. Exploring the changes in each of the tailored strategy

groups demonstrates how the intervention impacted the beliefs about medicines, illness

156

perceptions and how this translated into an improvement in adherence (Chapter Six).

Changes in the BIPQ treatment coherence and treatment control scores were driven by

participants who received a cognitive-educational intervention (see Chapter Six, Figure 6.11

and 6.12). Improved BIPQ treatment coherence and treatment control scores has been

associated with improved adherence.40

Participants in the control group had negative changes in their illness perceptions over time.

These participants had poorer understanding of their illness, perceived their medicine as

less helpful and were more emotionally affected by their illness over time. Similar

observations can be seen in other studies. For example, a study found that perceived

necessity of immunosuppressant after kidney transplantation significantly declined over time,

which was associated with a worsening of medication adherence six months after

transplantation.41 Shiyanbola et al. examined whether concerns about medicines changed

over time and the characteristics of the patients in whom beliefs changed over two years. In

this study, good medication adherence was associated with less concerns about their

medicines, which may be due to better health or a reduction in symptoms.44

7.5 Limitations of the Study

Our study had a number of limitations. One of the limitations of this study was the use of a

subjective measure of adherence. A systematic review on validated adherence scales was

conducted, from which we selected the most appropriate measure of adherence, the MAQ.

There are limitations to using self-report methods to identify medication adherence. Self-

report measures are prone to overestimating adherence due to social desirability bias. This

is unlikely to be a problem in this study given our use of a highly sensitive indicator of

possible non-adherence: an MAQ score > 0. This cut-off has been used in previous

studies.72,95,204,307 Indeed, with approximately 80% of the enrolled population being identified

as non-adherent, a more likely problem is that participants identified as non-adherent

according to the MAQ may have been classified as adherent using a different measure (such

as MEMS or a medication possession ratio based on dispensing history). In any case, the

overall effect of the MAQ incorrectly identifying non-adherence would be expected to reduce

rather than increase the effects of the intervention. Assessing Pharmaceutical Benefits

Scheme (PBS) data was also attempted; however, the high cost of receiving this information

made this option not possible. This data would have provided us with information on the

date of prescribing, date of dispensing of the medicines. Pharmacy prescription refill data

157

was another option that was attempted; however, we were only able to obtain consent to

assess this data from fourteen participants and hence were not able to model these results.

Some studies have shown that improving adherence to medications, improves clinical

outcomes, such as blood pressure control, blood glucose levels, and lower lipid levels.311-

313 Our study was not powered to measure clinical outcomes (but was powered on the basis

of a change in MAQ that has been demonstrated to influence clinical outcomes). Given the

success of the intervention, we hope to conduct a study powered to show the effect of the

intervention on clinical outcomes.

The process of following up participants at three months and six months may have

influenced adherence to medications independently of the intervention. Whether or not this

effect occurred is hard to judge, but any effect would be small and affect both the control

and intervention group. MAQ scores in the control group did not change to a statistically

significantly degree during the follow up.

Recruiting participants from a convenience sample of only two community pharmacies would

have led to selection bias, and may have led to over- and/or under-representation of

participant demographics. The two selected pharmacies service a broad range of patients

and were located in different socioeconomic areas. Based on the Socio-Economic Index for

Areas (SEIFA) that ranges from 1 (low) to 10 (high), one pharmacy had an index of 2 and

the other 9. SEIFA is an index that ranks Australian suburbs based on socioeconomic factors,

such as income and level of education, which was developed by the Australian Bureau of

Statistics.314 Furthermore, participants were recruited from two community pharmacies that

were known to the researcher. Some participants were known to the researcher prior to the

study, which may have influenced the results. However, this effect, if any, would have been

observed in both the intervention and control group. Conducting the study in pharmacies

known to the researcher improved the ease of data collection. The research may be more

difficult in pharmacies that do not have an established relationship with the researchers.

This study could be further strengthened with an exit survey to explore the participant’s

opinions and thoughts about the intervention. This information could be used to better tailor

interventions. An exit survey will be considered for further studies.

158

7.6 Future Directions and Conclusion

A targeted and tailored intervention, based on discussion informed using validated

adherence scales improved medication adherence. This intervention was easy to administer

and quick enough that it could be incorporated into day-to-day practice. In our study we

utilised the validated adherence questionnaires to assess patients on newly initiated therapy.

The questionnaires have been utilised previously in patients prescribed chronic medication

to assess their adherence to these. We believe that there should be no reason why the study

method would not also have utility in supporting adherence in patients on chronic medication.

If this targeted and tailored intervention proves successful in larger studies that assess

clinical outcomes, it has the potential for widespread implementation for improving

adherence to both recently initiated medications and existing therapy.

159

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186

APPENDIX A: Ethics Approval Letter

187

APPENDIX B: Participant Information Sheet

Full Project Title Targeted and tailored interventions to improve medication adherence in chronic diseases

Principal investigator: Ms Uyen Nguyen, BPharm (Hons), PhD Candidate

Associate investigators: Dr Neil Cottrell, BSc (Hons) MSc PhD, Senior Lecturer Dr Adam La Caze, BPharm (Hons) BA (Hons) PhD, Lecturer

All investigators are affiliated with the School of Pharmacy, The University of Queensland.

Your Consent

You are invited to participate in this research project because you are presenting a medication started in the last 4 to 12 weeks for one of the following medical conditions: high blood pressure, diabetes, high cholesterol or other heart conditions. This Participant Information contains detailed information about the research project. Its purpose is to explain to you as openly and clearly as possible all the procedures involved in this project before you decide whether or not to take part in it. Please read this Participant Information carefully. Feel free to ask questions about any information in the document. If you wish, feel free to discuss the project with a relative or friend or your local health worker. Once you understand what the project is about and if you agree to take part in it, you will be asked to sign the Consent Form. By signing the Consent Form, you indicate that you understand the information and that you give your consent to participate in the research project. This information and consent form is 3 pages long and you will be given a copy to keep as a record.

Purpose and Background

The purpose of this project is to assess whether people who forget or choose not to take their medicines benefit from personalised support. A total of approximately 200 people will participate in this project.

People with chronic medical conditions often have to take a number of medicines for a long period of time. People in this situation often do not take their medicines as agreed due to many different reasons. Identifying why this occurs and how best to support people in their medication taking may help manage their medical conditions.

Procedures

Participation in this project will involve completing a questionnaire in an interview on three occasions. The first interview will be today and the two other interviews will take place over the telephone at 3 months and 6 months after today. The questionnaire will take about ten minutes to complete. The first section consists of 4 Yes or No questions on the way you take your medicines. The next section will consist of 10 statements about your view and opinion of your medicines. In this section you will be asked to state your level of agreement or disagreement with each statement. The last section will consist of 8 questions on your view of illness. You will be asked to rate your answers on a scale of 0 to 10. You will be also asked to provide some information about yourself, such as your age and marital status. About a third of the participants in this study will have a longer interview with the researcher to discuss ways to help support the participants taking their medicines.

188

You will be contacted by telephone 3 months after the interview and then again at 6 months after this interview. The telephone calls will last for about 10 minutes. These telephone calls will involve the same questionnaire that you answered at the interview. There are no right or wrong answers to any of the questions in the interview; it is your view and opinion that is important.

Possible Benefits

Possible benefits include better understanding of medication and ways that may help you to improve medication-taking behaviour.

Possible Risks

This study involves completing a questionnaire through one interview and two telephone calls. There is no foreseeable added risk to you above the risks of everyday living.

Privacy, Confidentiality and Disclosure of Information

In all reports from this research, information will be provided in such a way that you cannot be identified. The results will be such that the individual issue could not be linked to that participant. The information collected will be stored in a locked filing cabinet in a locked office, with access only to the three researchers stated above. The information will be stored for a period of 5 years and then destroyed. Results of the Project You may request the study results when it is completed by providing an address that the report can be sent to or at a later date by contacting Uyen Nguyen (contact details below).

Participation is Voluntary

Participation in any research project is voluntary. If you do not wish to take part, you are not obliged to. If you decide to take part and later change your mind, you are free to withdraw from the project at any stage. Your decision whether to take part or not to take part, or to take part and then withdraw, will not affect your routine treatment or your relationship with the pharmacy staff. Before you make your decision, a member of the research team will be available to answer any questions you have about the research project. Sign the Consent Form only after you have had a chance to ask your questions and have received satisfactory answers. If you decide to withdraw from this project, please notify a member of the research team before you withdraw.

Reimbursements

No payment will be provided for participation in this study. If you have any queries or any problems concerning this project, please contact Uyen Nguyen: phone 07 3346 1996 or email [email protected].

This study has been cleared by one of the human ethics committees of the University of Queensland in accordance with the National Health and Medical Research Council's guidelines. You are of course, free to discuss your participation in this study with project staff (contactable on 3346 1996 or email [email protected]). If you would like to speak to an officer of the University not involved in the study, you may contact the Ethics Officer on 3365 3924.

mailto:[email protected]

189

APPENDIX C: Participant Consent Form

Full Project Title

Targeted and tailored interventions to improve medication adherence in chronic diseases

Principal investigator: Ms Uyen Nguyen, BPharm (Hons), PhD Candidate Associate investigators: Dr Neil Cottrell, BSc (Hons) MSc PhD, Senior Lecturer Dr Adam La Caze, BPharm (Hons) BA (Hons) PhD, Lecturer

All investigators are affiliated with the School of Pharmacy, The University of Queensland.

I acknowledge that:

(a) my participation is voluntary and that I am free to withdraw from the project at any time without explanation;

(b) I will be given a copy of the participant information sheet to which this consent form relates to and the consent form to keep;

(c) this project is for the purpose of research and not for profit;

(d) any identifiable information about me which is gathered in the course of and as the result of my participating in this project will be (i) collected and retained for the purpose of this project and (ii) accessed and analysed by the researcher(s) for the purpose of conducting this project;

(e) my anonymity is preserved and I will not be identified in publications or otherwise without my express written consent.

(f) I may not directly benefit from participation in this project.

By signing this document I agree to participate in this project.

Full Name of Participant (printed):………………….……………….…………………………….……….…………………….

Signature of Participant: ……………………………………….………..…. Date: ……………/……………/………………

Full Name of Witness to Signature of Participant (printed):…………………………………………………….…....

Signature of Witness: ……………………………………...…….………..…. Date: ……………/……………/……………..

Full Name of Researcher (printed): ………………………………………………………………………………………………

Signature of Researcher: …………………………………………………….. Date: …………../…………../………………

190

APPENDIX D: Participant Survey

Below are questions about how you take your recently prescribed medicine. There

are no right or wrong answers. Please answer YES or NO.

Item Question YES NO

1 Do you ever forget to take your medicine? 1 0

2 Are you careless at times about taking your medicine? 1 0

3 When you feel better, do you sometimes stop taking your

medicine?

1 0

4 Sometimes, if you feel worse when you take the medicine,

do you stop taking it?

1 0

Below are statements other people have made about their medicines. We are

interested in your personal views. There are no right or wrong answers. Please

indicate the extent to which you agree or disagree with them.

Item Statement Strongly

Agree

Agree Uncertain Disagree Strongly

Disagree

1 My health at present,

depends on my medicines

5 4 3 2 1

2 Having to take medicines

worries me

5 4 3 2 1

3 My life would be impossible

without my medicines

5 4 3 2 1

4 Without my medicines I

would be very ill

5 4 3 2 1


long-term effects of my

medicines

5 4 3 2 1

6 My medicines are a mystery

to me

5 4 3 2 1

7 My health in the future will

depend on my medicines

5 4 3 2 1

8 My medicines disrupt my life

5 4 3 2 1


becoming too dependent on

my medicines

5 4 3 2 1

10 My medicines protect me

from becoming worse

5 4 3 2 1

191

These questions are about your views on your illness. For the following questions, please circle the number that best corresponds to your views: How much does your illness affect your life?

0 1 2 3 4 5 6 7 8 9 10

no affect severely affects

at all my life

How long do you think your illness will continue?

0 1 2 3 4 5 6 7 8 9 10

a very forever

short time

How much control do you feel you have over your illness?

0 1 2 3 4 5 6 7 8 9 10

absolutely extreme amount

no control of control

How much do you think your treatment can help your illness?

0 1 2 3 4 5 6 7 8 9 10

not extremely

at all helpful

How much do you experience symptoms from your illness?

0 1 2 3 4 5 6 7 8 9 10

no symptoms many severe

at all symptoms

How concerned are you about your illness?

0 1 2 3 4 5 6 7 8 9 10

not at all extremely

concerned concerned

How well do you feel you understand your illness?

0 1 2 3 4 5 6 7 8 9 10

don’t understand understand

at all very clearly

How much does your illness affect you emotionally? (e.g. does it make you angry, scared,

upset or depressed?

0 1 2 3 4 5 6 7 8 9 10

no at all extremely

affected emotionally affected emotionally

Please list in rank-order the three most important factors that you believe caused your

illness. The most important causes for me:

1. _____________________ 2. _____________________ 3. __ ________________

192

Below are questions about your background. Please tick one box for each question.

1. Gender: Male Female

2. Age: ______________________

3. Highest Education Level:

Primary Secondary Tertiary

4. Employment Status

Employed Unemployed Retired

From the list below please select the number closest to YOUR FAMILY’s annual income (before tax).

≤ $30 000 $51 000 to $70 000 $91 000 to $110 000 $131 000 - $150 000

$31 000 to $50 000 $71 000 to $90 000 $111 000 to $130 000 Over $150 000

5. Marital Status (select the one that best describes you)

Married Divorced Widowed Single

6. Number of Medications Currently Taken _____________

7. Number of Vitamin/Herbal/Mineral supplements taken (if applicable)_______________

8. Medical Conditions: select all that apply to you from the following list

High blood pressure Asthma Diabetes Heart failure

High cholesterol levels Depression Osteoarthritis Stroke

Other(s) __________________________________________________________________

Thank you for your time

193

APPENDIX E: Mean MAQ Scores Over Time

Mean MAQ scores at baseline, 3 months and 6 months (Adherent Group)

Time p-value

Baseline 3 months 6 months 0 to 3

months

0 to 6

months

3 to 6

months

Mean MAQ

Score ± sd

0.00 0.22 ± 0.49 0.03 ± 0.18 <0.05* 0.3251 0.0564

Mean MAQ scores at baseline, 3 months and 6 months (Intervention Group)

Time p-value


months

0 to 6

months

3 to 6

months

Mean MAQ

Score ± sd

1.58 ± 0.79 0.42 ± 0.59 0.48 ± 0.68 <0.05* <0.05* 0.4543

Mean MAQ scores at baseline, 3 months and 6 months (Control Group)

Time p-value


months

0 to 6

months

3 to 6

months

Mean MAQ

Score ± sd

1.60 ± 0.67 1.58 ± 0.65 1.48 ± 0.83 0.7987 0.1961 0.2034

194

APPENDIX F: Mean BMQ-S Necessity and Concerns Scores Over Time

Mean BMQ-S Necessity and Concerns scores at baseline, 3 months and 6 months (Adherent Group)

Mean BMQ-S Scores

± sd

Time p-value


0 to 6 months

3 to 6 months

Mean Necessity Score

20.25 ± 4.84 20.28 ± 4.17 20.22 ± 3.89 0.9545 0.9608 0.8523

Mean Concerns Score

11.75 ± 3.13 11.41 ± 2.89 10.78 ± 2.81 0.4855 0.0594 <0.05*

Mean BMQ-S Necessity and Concerns scores at baseline, 3 months and 6 months (Intervention Group)

Mean BMQ-S Scores

± sd

Time p-value


0 to 6 months

3 to 6 months


19.60 ± 3.18 19.80 ± 2.94 20.25 ± 3.17 0.5160 0.0963 0.1475

Mean Concerns Score

13.48 ± 3.50 13.00 ± 3.43 12.32 ± 3.75 0.1837 <0.05* 0.0511

Mean BMQ-S Necessity and Concerns scores at baseline, 3 months and 6 months (Control Group)

Mean BMQ-S Scores

± sd

Time p-value


0 to 6 months

3 to 6 months


18.48 ± 3.63 18.53 ± 3.71 17.95 ± 3.20 0.8699 0.1854 0.0874

Mean Concerns Score

12.63 ± 4.20 13.05 ± 3.75 12.92 ± 3.38 0.1456 0.4558 0.6663

195

APPENDIX G: Illness Perceptions Over Time

Mean BIPQ scores at baseline, 3 months and 6 months (Adherent Group)

Mean BIPQ Scores

± sd

Time p-value


months

0 to 6

months

3 to 6

months

Consequences How much does your

illness affect your life? (0 = no affect at all – 10 =


5.13 ± 2.87

5.03 ± 3.17

4.06 ± 2.94 0.7932 <0.05* <0.05*

Timeline How long do you think

your illness will

continue? (0 = very short time – 10 =

forever)

8.72 ± 2.64

8.94 ± 2.35

9.09 ± 2.16 0.4148 0.1359 0.3776

Personal Control How much control do

you feel you have over

your illness? (0 = absolutely no control – 10

= extreme amount of control)

6.53 ± 2.73

7.22 ± 1.91

7.47 ± 1.90 0.1367 <0.05* 0.2833

Treatment Control How much do you think


your illness? (0 = not at all – 10 = extremely

helpful)

9.00 ± 1.44

9.28 ± 1.39

9.16 ± 1.42 0.1525 0.4926 0.5014

Identity How much do you

experience symptoms

from your illness? (0 = no symptoms at all – 10 =


3.63 ± 3.12 4.16 ± 3.05

3.56 ± 2.71 0.1142 0.8523 0.1054


about your illness? (0 = not at all concerned – 10 =

extremely concerned)

5.53 ± 3.16

5.34 ± 3.57

4.47 ± 3.32 0.7251 <0.05* <0.05*


understand your illness? (0 = don’t understand at all –

10 = understand very clearly)

8.53 ± 1.92

8.66 ± 1.82

8.84 ± 1.74 0.6767 0.2991 0.1606

Emotional

Response How much does your

illness affect you

emotionally? (0 = not at all affected



3.56 ± 3.22

4.16 ± 3.07

3.38 ± 2.70 0.2082 0.6720 <0.05*

196

Mean BIPQ scores at baseline, 3 months and 6 months (Intervention Group)

Mean BIPQ

Scores

± sd

Time p-value


0 to 6 months

3 to 6 months

Consequences How much does your illness affect your life? (0 = no affect at all – 10 = severely affects my life)

5.10 ± 3.02

4.98 ± 3.07

4.90 ± 2.86 0.7188 0.5654 0.7744

Timeline How long do you think your illness will continue? (0 = very short time – 10 = forever)

9.57 ± 1.14

9.90 ± 0.66

9.83 ± 0.62 <0.05* 0.0808 0.2086

Personal Control How much control do you feel you have over your illness? (0 = absolutely no control – 10 = extreme amount of control)

5.70 ± 2.82

6.50 ± 2.57

5.90 ± 2.93 <0.05* 0.5578 0.0832

Treatment Control How much do you think your treatment can help your illness? (0 = not at all – 10 = extremely helpful)

8.20 ± 1.94

8.55 ± 1.79

8.58 ± 1.70 0.0961 0.1210 0.8836

Identity How much do you experience symptoms from your illness? (0 = no symptoms at all – 10 = many severe symptoms)

4.32 ± 2.83

4.52 ± 3.06 4.18 ± 2.78 0.5912 0.7171 0.3140

Concern How concerned are you about your illness? (0 = not at all concerned – 10 = extremely concerned)

5.97 ± 3.46

5.65 ± 3.21

5.53 ± 3.32 0.2739 0.2604 0.6598

Coherence How well do you feel you understand your illness? (0 = don’t understand at all – 10 = understand very clearly)

7.28 ± 2.64

8.37 ± 2.09

8.37 ± 2.11 <0.05* <0.05* 1.0000

Emotional Response How much does your illness affect you emotionally? (0 = not at all affected emotionally – 10 = extremely affected emotionally)

4.18 ± 3.41

4.27 ± 3.15

3.92 ± 3.02 0.8211 0.5745 0.2740

197

Mean scores of BIPQ at baseline, 3 months and 6 months (Control group)

Mean BIPQ Scores

± sd

Time p-value


months

0 to 6

months

3 to 6

months

Consequences

How much does your

illness affect your life? (0 = no affect at all – 10 =


4.77 ± 3.01

5.03 ± 3.09

5.45 ± 2.92 0.2199 <0.05* <0.05*

Timeline

How long do you think

your illness will

continue? (0 = very short time – 10 =

forever)

8.85 ± 2.28

8.92 ± 2.19

9.12 ± 1.87 0.7632 0.2995 0.1928

Personal Control How much control do

you feel you have over

your illness? (0 = absolutely no control – 10

= extreme amount of control)

6.08 ± 2.89

5.53 ± 2.61

4.98 ± 2.59 0.1186 <0.05* 0.0506

Treatment Control How much do you think


your illness? (0 = not at all – 10 = extremely

helpful)

8.00 ± 1.97

7.63 ± 2.15

7.22 ± 2.44 <0.05* <0.05* <0.05*

Identity

How much do you

experience symptoms

from your illness? (0 = no symptoms at all – 10 =


4.25 ± 2.90

4.37 ± 2.95

4.98 ± 2.69 0.6831 <0.05* <0.05*


about your illness? (0 = not at all concerned – 10 =

extremely concerned)

5.37 ± 3.11

5.78 ± 2.96

6.12 ± 2.92 0.2780 <0.05* 0.3238


understand your illness? (0 = don’t understand at all –

10 = understand very clearly)

7.35 ± 2.36

7.12 ± 2.54

6.63 ± 2.71 0.4235 0.0525 <0.05*

Emotional

Response How much does your

illness affect you

emotionally? (0 = not at all affected



4.07 ± 3.05

4.38 ± 3.04

4.97 ± 2.91 0.2897 <0.05* <0.05*

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