Identifying Psychologically Vulnerable Diabetes Populations - the role of a genetic polymorphism, individual traits and psychological morbidity

Dr. Jaya Prakash Reddy Bhakti Reddy

A thesis submitted for the degree of Doctor of Philosophy, University of New South Wales

2011 PLEASE TYPE THE UNIVERSITY OF NEW SOUTH WALES Thesis/Dissertation Sheet

Surname or Family name: Bhakti Reddy

First name: Jaya Other name/s: Prakash Reddy

Abbreviation for degree as given in the University PhD calendar:

School: Psychiatry Faculty: Medicine

Title: Identifying Psychologically Vulnerable Diabetes Populations - the role of a genetic polymorphism, individual traits and psychological morbidity

ABSTRACT

Diabetes Mellitus (DM) is commonly associated with psychological distress and psychiatric comorbidity including depressive and anxiety disorders. DM consensus guidelines recommend psychosocial interventions as part of routine care. There is evidence that individually tailored interventions improve psychological outcomes and glycaemic control in DM. This thesis was part of a larger project focusing on a brief minimal contact psychosocial intervention in patients with Type 1 and 2 DM (T1DM and T2DM) attending two general hospital-based specialist clinics in Sydney. The objective of this thesis is to establish whether individual differences (personality styles, coping patterns, and the serotonin transporter genotype), and illness factors (DM type, diabetes-related distress) could determine psychologically vulnerable sub- populations of DM patients who would benefit from brief psychosocial interventions. A total of 274 T1DM and T2DM patients were recruited into the study. Baseline data (clinical interview, self-administered questionnaires: PHQ, K10, PAID, COPE, NEO and SF-12, and glycosylated haemoglobin levels) were collected upon recruitment. Cheek swabs were taken for serotonin transporter gene (5HTTLPR 6CLA4) genotyping. The rates of common psychological disorders (including depression, anxiety and specific diabetes-related distress) varied according to demographic profiles such as age and gender; disease factors such as medical comorbidity; and coping styles. Participants who predominantly used avoidance coping styles had higher PHQ-9 depression (p < 0.01) and PAID DM-specific distress (p < 0.01) scores. DM-specific distress predicted significantly higher levels of PHQ-9 depression (p < 0.01) and glycosylated haemoglobin (HbA1c) (p < 0.01). Females, with the 5HTTLPR s/s genotype, had significantly higher levels of anxiety (p < 0.01) as measured by the K-10 anxiety subscale. The intervention study experienced a high attrition rate, and factors determining attrition are discussed in this thesis. The Problem Areas in Diabetes (PAID) questionnaire in this study demonstrated the ability to detect a significantly distressed population that could potentially benefit from psychological interventions and is therefore an effective screening tool for psychological morbidity in DM. The implications of these findings for the design of future consultation liaison psychiatry services and brief intervention programs for people with T1DM and T2 DM are discussed in this thesis.

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‘I hereby grant the University of New South Wales or its agents the right to archive and to make available my thesis or dissertation in whole or part in the University libraries in all forms of media, now or here after known, subject to the provisions of the Copyright Act 1968. I retain all proprietary rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation. I also authorise University Microfilms to use the 350 word abstract of my thesis in Dissertation Abstract International (this is applicable to doctoral theses only). I have either used no substantial portions of copyright material in my thesis or I have obtained permission to use copyright material; where permission has not been granted I have applied/will apply for a partial restriction of the digital copy of my thesis or dissertation.'

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Date ……………………………………………...... TABLE OF CONTENTS

THESIS ABSTRACT ...... 10

THESIS OVERVIEW ...... 12

GLOSSARY ...... 14

CHAPTER 1: PSYCHOLOGICAL MORBIDITY IN DIABETES MELLITUS: A LITERATURE REVIEW ...... 15

1.1. Introduction ...... 15

1.2. Common psychiatric disorders in DM ...... 15

1.3. Depression ...... 16

1.4. Anxiety Disorders ...... 19

1.5. Eating disorders ...... 21

1.6. Stress of Daily Hassles and Life Events ...... 22

1.7. The Deficit ...... 23

1.8. Conclusion ...... 24

CHAPTER 2: PSYCHOSOCIAL INTERVENTIONS IN DIABETES MELLITUS: A LITERATURE REVIEW ...... 25

2.1. Introduction ...... 25

2.2. Definition ...... 25

2.3. Key Review Papers ...... 27

2.4. Common Psychosocial Interventions in DM ...... 32 2.4.1. Cognitive Behaviour Based Therapies (CBT)ǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤ͵͵ 2.4.2. Motivational Interviewing (M.I.)ǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤ͵ͷ 2.4.3. Other Interventions of noteǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤ͵͸

2.5. Identification of Psychologically Vulnerable PWD Subpopulations ..... 38 2.5.1. Target PopulationǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤ͵ͺ

1 2.5.2. Method of delivery of interventionsǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤ͵ͻ

2.6. Factors to Consider When Tailoring Psychosocial Interventions for PWD Sub-populations ...... 40 2.6.1. Individual Biopsychosocial characteristics (personality, genetic factors, previous coping)ǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͶͲ 2.6.2. Illness FactorsǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͶͳ

2.7. Conclusion ...... 42

CHAPTER 3: RESEARCH OBJECTIVES, QUESTIONS AND METHODOLOGY ...... 43

3.1. Research Objectives: ...... 43

3.2. Research Questions: ...... 43

3.3. Procedure ...... 44

3.4. Study Design ...... 45

3.5. Materials ...... 47 3.5.1. PHQ (Patient Health Questionnaire)ǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͶ͹ 3.5.2. K 10 (Kessler-10 item)ǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͶ͹ 3.5.3. SF12 (Short-form health survey)ǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͶͺ 3.5.4. PAID (Problem Areas in Diabetes)ǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͶͺ 3.5.5. COPEǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͶͻ 3.5.6. NEO-FFI (NEO Five Factor Instrument)ǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͶͻ

3.6. DNA extraction and genetic analysis ...... 50

3.7. Sample Size Calculation ...... 51

3.8. Intervention Sheets ...... 51

CHAPTER 4: IDENTIFYING SUBPOPULATIONS WITHIN A DIABETES SAMPLE WITH SPECIFIC NEEDS FOR PSYCHOSOCIAL INTERVENTIONS ...... 54

ABSTRACT ...... 54

4.1. Introduction ...... 55 2 4.2. Statistical Analyses and Principal Components Analysis of the COPE Questionnaire ...... 56 4.2.1. Statistical analysesǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͷ͸ 4.2.2. Principal Components Analysis of the COPE QuestionnaireǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͷ͹ 4.2.3. Principal Components Analysis (PCA) of the K-10ǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͷͺ

4.3. Results ...... 59 4.3.1. DemographicsǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͷͻ 4.3.2. Analysis of the cohort sub-populationsǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤ͸Ͳ

4.4. Discussion ...... 61 4.4.1. Age-related characteristicsǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤ͸ͳ 4.4.2. DM-related characteristicsǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤ͸ʹ 4.4.3. Implications of physical and mental health comorbiditiesǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤ͸ʹ 4.4.4. Screening measuresǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤ͸͵

4.5. Limitations ...... 64

4.6. Conclusion ...... 65

CHAPTER 5: PREDICTORS OF ATTRITION AMONGST PARTICIPANTS OF A PSYCHOLOGICAL INTERVENTION TRIAL IN DIABETES MELLITUS ...... 77

ABSTRACT ...... 77

5.1. Introduction ...... 78

5.2. Methodology ...... 81

5.3. Statistics ...... 82

5.4. Results ...... 82 5.4.1. General comparisons of variables of interest between drop-outs and completersǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͺͷ 5.4.2. Logistic regression analysis with intervention group as predictor variable and retention status as outcome variableǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͺͷ

5.5. Discussion ...... 88

5.7. Conclusion ...... 93 3 CHAPTER 6: Coping Styles, Personality Factors and the Serotonin Transporter Genotype in Patients with Diabetes Mellitus ...... 95

ABSTRACT ...... 95

6.1. Introduction ...... 96

6.2. Study Objectives ...... 101

6.3. Methodology ...... 101

6.4. Statistical Analyses ...... 101

6.5. Results ...... 102 6.5.1. DemographicsǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳͲʹ 6.5.2. Coping ScoresǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳͲʹ 6.5.3. Relationship between Coping factors and personality scales of the NEO-FFI ǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳͲ͵

6.6. Regression Analyses ...... 104 6.6.1. Avoidant copingǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳͲͶ 6.6.2. Problem-focused copingǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳͲͶ 6.6.3. Emotional-expression copingǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳͲͶ

6.7. Discussion ...... 107

6.8. Limitations ...... 110

6.9. Implications ...... 111

CHAPTER 7: COPING, DEPRESSION AND GLYCAEMIC CONTROL IN TYPE 1 AND TYPE 2 DIABETES MELLITUS ...... 112

ABSTRACT ...... 112

7.1. Introduction ...... 113

7.2. Methodology ...... 118 7.2.1. Participants / ProcedureǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳͳͺ 7.2.2. Statistical analysesǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳͳͺ

7.3. Results ...... 119 7.3.1. Demographics and Mean Coping Scores for each FactorǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳͳͻ 4 7.3.2. Correlation between coping, psychological outcomes and HbA1cǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳͳͻ 7.3.3. Regression analysisǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳʹͲ

7.4. Discussion ...... 125

7.5. Conclusion ...... 128

CHAPTER 8: GENDER DIFFERENCES IN THE ASSOCIATION BETWEEN THE SEROTONIN TRANSPORTER PROMOTER POLYMORPHISM (5-HTTLPR SLC6A4) AND PSYCHOLOGICAL DISTRESS IN A CHRONIC ILLNESS POPULATION...... 129

ABSTRACT ...... 129

8.1. Introduction ...... 130

8.2. Methodology ...... 134 8.2.1. ParticipantsǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳ͵Ͷ 8.2.2. DNA extraction and genetic analysisǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳ͵Ͷ 8.2.3. Statistical analysesǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳ͵Ͷ

8.3. Results ...... 135

8.4. Discussion ...... 139

8.5. Conclusion ...... 142

CHAPTER 9: DIABETES-SPECIFIC EMOTIONAL DISTRESS AND ITS RELATIONSHIP TO DEPRESSION AND GLYCAEMIC CONTROL IN TYPE 1 AND TYPE 2 DM ...... 143

ABSTRACT ...... 143

9.1. Introduction ...... 144

9.2. Research Design and Methods ...... 145

9.3. Statistics ...... 146

9.4. Results ...... 146 9.4.1. Psychometric properties of PAID – Principal Components Analysis and Internal Reliability (Cronbach’s alpha)ǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳͶ͸

5 9.4.2. Common DM distress itemsǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳͶ͹ 9.4.3. Discriminant Validity of PAID in relation to presence of major depressionͳͶ͹ 9.4.4. Correlations between variables of interestǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳͶͻ 9.4.5. Effect of past depression history on PAID scoresǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳͶͻ 9.4.6. Hierarchical Multiple Linear Regression AnalysesǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤǤͳͷͲ 9.4.6.1.Model1:PAIDaspredictorofHbA1c...... 150 9.4.6.2.Model2:PAIDaspredictorofPHQǦ9...... 151

9.5. Discussion ...... 152

9.6. Limitations ...... 157

9.7. Conclusion ...... 157

CHAPTER 10: FINAL CONCLUSION AND CLOSING REMARKS ...... 159

REFERENCES ...... 166

ACKNOWLEDGEMENTS ...... 193

APPENDICES ...... 197

6 LISTOFTABLES  Table 2.1: Summary of key review papers on psychosocial interventions in DM 28 Table 4.1: Distribution by Ethnic Group 65 Table 4.2: COPE Subscales: Internal Reliability 68 Table 4.3: COPE Subscales: Component Matrix factor loadings after Principal Components Analysis 69 Table 4.4: Oblimin rotated factor structure, loadings and correlations for K10 scores 71 Table 4.5: Comparison of the 274 study participants by DM type and current age 73 Table 4.6: Outcome instruments and COPE scores according to current and past depression history status 76 Table 5.1: Comparison of proportions or mean scores of variables of interest for study completers versus dropouts 86 Table 5.2: Logistic Regression with Intervention Group as Independent Variable and Retention Status as Dependent Variable 88 Table 6.1: Mean coping scores for each factor 105 Table 6.2: Correlations between coping factors and the five NEO factors 105 Table 6.3: Regression analysis with NEO personality factors as the predictor and each of the three coping factors as dependent variables (3 models) 106 Table 6.4: Hierarchical Regression Analysis summary for Neuroticism and relevant covariates as predictors of avoidance coping 107 Table 7.1: Correlations between coping factors and psychological outcomes and glycaemic control 121 Table 7.2: Correlations between problem-focused coping subscales and K10 122

7 Table 7.3: Hierarchical Multiple Linear Regression Analyses Model: Coping factors as predictors of depression scores (PHQ-9) 123 Table 7.4: Hierarchical Regression Analysis predicting Avoidance Coping scores 124 Table 8.1 Gender-5HTTLPR genotype interaction effects on K10 anxiety and depression subscales 137 Table 8.2 Hierarchical Regression analysis with gender-genotype interaction factor as independent variable and K 10 total score as dependent variable 138 Table 8.3: Hierarchical Regression analysis with gender-genotype interaction factor as independent variable and K 10 anxiety subscale score as dependent variable 138 Table 9.1: Percentage of “somewhat serious/serious” responses on the individual items of the PAID comparing major depression cases vs. non- cases 148 Table 9.2: Intercorrelations, Means and Standard Deviations for instruments of interest and glycosylated haemoglobin (HbA1c) 149 Table 9.3: Hierarchical Regression Analysis summary for specific diabetes distress (PAID) predicting glycosylated haemoglobin (HbA1c) 151 Table 9.4: Hierarchical Regression Analysis summary for specific diabetes distress (PAID) predicting depression scores (PHQ-9) 152

LIST OF FIGURES Figure 3.1 Study Flow-Chart 53 Figure 4.1: Bar-Chart showing distribution of Participants by Educational Level 66 Figure 4.2: Distribution of Participants according to Marital Status 66 Figure 4.3: Distribution of Participants according to Occupational Status 67 Figure 4.4: Scree plot for the COPE questionnaire after Principal Components Analysis 70

8 Figure 4.5: Scree plot for the K-10 questionnaire after Principal Components Analysis 72 Figure 5.1: Flow-chart of participants through the first 6 weeks of the study 84 Figure 10.1 Suggested pathways for using screening instruments to guide provision on psychiatric assessment and treatment and psychosocial interventions in a diabetic service 165

9 THESIS ABSTRACT

Diabetes Mellitus (DM) is commonly associated with psychological distress and psychiatric comorbidity including depressive and anxiety disorders. DM consensus guidelines recommend psychosocial interventions as part of routine care. There is evidence that individually tailored interventions improve psychological outcomes and glycaemic control in DM.

This thesis was part of a larger project focusing on a brief minimal contact psychosocial intervention in patients with Type 1 and 2 DM (T1DM and T2DM) attending two general hospital-based specialist clinics in Sydney.

The objective of this thesis is to establish whether individual differences (personality styles, coping patterns, and the serotonin transporter genotype), and illness factors (DM type, diabetes-related distress) could determine psychologically vulnerable sub-populations of DM patients who would benefit from brief psychosocial interventions.

A total of 274 T1DM and T2DM patients were recruited into the study. Baseline data (clinical interview, self-administered questionnaires: PHQ, K10, PAID, COPE, NEO and SF-12, and glycosylated haemoglobin levels) were collected upon recruitment. Cheek swabs were taken for serotonin transporter gene (5HTTLPR 6CLA4) genotyping.

The rates of common psychological disorders (including depression, anxiety and specific diabetes-related distress) varied according to demographic profiles such as age and gender; disease factors such as medical comorbidity; and coping styles. Participants who predominantly used avoidance coping styles had higher PHQ-9 depression (p < 0.01) and PAID DM-specific distress (p < 0.01) scores. DM-specific distress predicted 10 significantly higher levels of PHQ-9 depression (p < 0.01) and glycosylated haemoglobin (HbA1c) (p < 0.01). Females, with the 5HTTLPR s/s genotype, had significantly higher levels of anxiety (p < 0.01) as measured by the K-10 anxiety subscale. The intervention study experienced a high attrition rate, and factors determining attrition are discussed in this thesis.

The Problem Areas in Diabetes (PAID) questionnaire in this study demonstrated the ability to detect a significantly distressed population that could potentially benefit from psychological interventions and is therefore an effective screening tool for psychological morbidity in DM.

The implications of these findings for the design of future consultation liaison psychiatry services and brief intervention programs for people with T1DM and T2 DM are discussed in this thesis.

11 THESIS OVERVIEW

This study resulted from a need to develop psychosocial interventions for people with diabetes (PWD). The Consultation Liaison Psychiatry service at St.Vincent’s Hospital sought to collaborate with the Diabetes Clinic and Centre in the hope of learning how to identify and target specific PWD groups that would be interested in brief interventions to deal with stress, anxiety and depression. This later also included PWD from the Diabetes Service at the neighboring Prince of Wales Hospital.

The main objective of this thesis is to study the extent of psychological morbidity in DM and whether individual differences like coping, personality and a polymorphism in the serotonin transporter gene (5HTTLPR 6CLA4) could identify subpopulations with DM who would benefit from psychological interventions.

The thesis was part of a larger study comprising of a randomized controlled trial to test the efficacy of brief minimal contact psychological interventions in people with T1 and T2DM.

The research data were gleaned from a sample of T1 and T2DM patients attending two public hospitals in Sydney. All the chapters (studies) were based on the same dataset. The response rates for the various instruments varied, hence the different sample sizes reported in each chapter. The thesis was also meant to report on the outcome of the intervention arm of the study, however as the longitudinal data were not satisfactory due to high attrition rates, this is not reported. I have instead reported a chapter on factors influencing retention rates in the intervention study (Chapter 5).

12 The chapters are laid out as follows:

x The first 2 chapters are literature reviews on psychological issues and morbidity, and psychological interventions in DM respectively.

x Chapter 3 describes research questions and methodology.

x Chapter 4 is a descriptive study of the sub-populations in this DM sample and their psychological correlates.

x Chapter 5 is an account on factors that influence retention/attrition (a post-hoc account on factors influencing participation in the study).

x Chapter 6 studies personality factors and the 5HTTLPR 6CLA4 polymorphism influence on coping styles.

x Chapter 7 explores the relationship between coping and psychological outcomes in DM.

x Chapter 8 focuses on the 5HTTLPR 6CLA4 polymorphism in the serotonin transporter gene, and gender interaction in DM.

x Chapter 9 focuses on DM-related distress and its relationship with psychological morbidity.

x Chapter 10 summarises the study findings and discusses future implications.

13 GLOSSARY

HbA1c – glycosylated haemoglobin

DM – diabetes mellitus

T1DM – Type 1 diabetes mellitus

T2DM – Type 2 diabetes mellitus

PWD – reference to ‘people with diabetes’

HbA1c – glycosylated haemoglobin

5HTTLPR-6CLA4 – a functional polymorphism in the promoter region of the serotonin transporter gene

RCT: randomised controlled trial

HRQOL: Health related quality of life

Participants – specific reference to study participants

14 CHAPTER 1: PSYCHOLOGICAL MORBIDITY IN DIABETES MELLITUS: A LITERATURE REVIEW

1.1. Introduction

This chapter reviews the literature on psychological morbidity in adults with diabetes mellitus (DM). The focus is on the impact of the following on DM:

ƒ Common frank psychiatric disorders ƒ Sub-threshold states ƒ Problems arising from living with DM (daily hassles).

These are not mutually exclusive entities but the distinction is useful in the implementation of screening and interventional programs and in the planning and designing of services to target specific needs of individuals.

1.2. Common psychiatric disorders in DM

DM is a chronic condition that demands the strictest of routines in terms of monitoring blood glucose levels, charting food intake and continuous adjustment of medications. The daily hassles of adhering to a treatment regimen frequently take their toll on patients, ranging from frustration to frank psychiatric disorders.

Evidence points towards higher rates of common psychiatric disorders among people with diabetes (PWD) than the general population. An analysis from a large population sample drawn from the 2000 UK National Psychiatric Morbidity Survey in Great Britain found that PWD were 50% 15 more likely to suffer from common mental disorders, particularly mixed anxiety and depression, than people without DM (Das-Munshi, et al., 2007). The authors also found that people with comorbid mental disorders had poorer health-related quality of life (HRQOL) and DM self-care. Another study of community-based adults with DM in 17 countries, (Lin, et al., 2008) found that the risk of depression (odds ratio) was 1.38 and that of anxiety was 1.20. The authors found that rates of common mental health disorders were consistent cross-culturally and across the 17 countries.

1.3. Depression

Depression is the most widely reported psychiatric comorbidity in DM. A meta-analysis (Anderson, et al., 2001) of 42 studies including 20 with a non-DM control group revealed that the odds of developing depression in PWD were twice that of healthy non-DM controls. The prevalence rates were higher for women than men, in clinical than community samples, in uncontrolled than controlled studies and when assessed using self-report instruments compared to standardised diagnostic interviews, but did not differ by type of DM. A review of 20 studies by Gavard et al. (1993), including 9 controlled samples derived from treatment and community groups, reported depression prevalence rates from 8.5% to 27.3% for the controlled studies and 11.0% to 19.9% for the uncontrolled studies. The authors comment that these rates are at least three times the rates of major depression found in the general adult population in the U.S.A. While there is a range of prevalence rates in the various studies reflecting methodological and demographic nuances, these two meta-analyses are consistent in finding significantly higher prevalence rates of depression among PWD than non-DM populations.

16 Depression influences the outcome of DM and is significantly associated with a range of DM complications. A meta-analysis of 27 studies (de Groot, et al., 2001) found a small to moderate effect size (0.17 to 0.32) in the relationship between depression and such DM-related complications as nephropathy, retinopathy and neuropathy. The authors obtained statistical significance for all subgroups of patients with consistent effect sizes for all the complications and for both types of DM. Depression has also been linked with higher glycaemic levels in both types of DM. In a meta-analysis of 24 studies, Lustman et al. (2000) found a statistically significant effect size of 0.17 for this relationship. The evidence to date however does not indicate direction of causality for depression and DM. Comment [a1]:

Depressive symptoms are also associated with lower adherence to diet and exercise regimes among PWD. Ciechanowski et al. (2003) demonstrated Comment [a2]: Have you defined this? Yes – the first time I have used it this relationship together with greater DM symptom reporting in PWD (T1 is on page 11 – and I have introduced the PWD abbreviation there. and T2). Non-adherence to the diabetes self-care regime in turn contributes to worse depression outcomes, creating a vicious cycle (Katon 2008). The physical, cognitive and emotional burden of depressive symptoms may cause PWDs to lapse into a state of self-neglect manifest by poor dietary control, irregular blood glucose monitoring and non- compliance with medication.

The persistence and recurrence of depression in DM is an important issue. Peyrot & Rubin (1999) report that up to 13% of PWD (Type 1 or 2 DM) were persistently depressed over a 6-month period and cited lack of education and presence of multiple DM complications as associated with greater rates of chronicity of depression. Lustman et al. (1997b) followed up 25 PWD over a five-year period and reported recurrence or persistence of depression in 92% of the patients with an average of 4.8 episodes over the five-year period. They noted the chronicity of pain in neuropathy and early discontinuation of antidepressant treatment as potential perpetuating

17 factors for the persistence or recurrence of depression. Routine screening and treatment of depression in DM is thus warranted to prevent a chronic course.

The focus thus far has been on clinical depressive disorder. It has to be said however that approximately 40% of PWDs have significantly elevated depressive symptomatology (Gavard, Lustman, & Clouse, 1993). Gonzalez et al. (2007) found that two thirds of people with T2DM surveyed (n = 879) reported symptoms of depression. While patients in these studies did not all meet criteria for clinical depression, the symptoms of depression directly correlated with poor self-care behaviours (Gonzalez, et al. 2007). Another study (Fisher, et al., 2007) utilising the Center for Epidemiologic Studies Depression Scale (CES-D) questionnaire to screen for depression in people with T2DM found that 70% of PWD who scored above the cut-off score were not clinically depressed (when cross-interviewed using the Composite International Diagnostic Interview CIDI). However this group still demonstrated adverse outcomes including high HbA1c, saturated fat and non-HDL cholesterol levels. Sub-clinical depression is therefore a significant entity in DM that needs to be addressed through appropriate interventions. These authors recommend that future research focus on developing different interventions such as problem solving and social skills training for distressed but not necessarily clinically depressed patients. These reports recommend that the threshold for detecting depression in PWDs should be lower than that for the general population and research trialing interventions for depression in diabetes should target subthreshold states and not simply clinical depression.

The evidence for treatment efficacy of depression in DM is limited to pharmacotherapy and the more established psychotherapies, such as cognitive behavior therapy (CBT). A review by Petrak (2009) considers the efficacy of CBT as reported in T2DM by Lustman (1998). The review

18 summarises the evidence for antidepressants, namely nortriptyline (Lustman 1997a), fluoxetine (Lustman 2000, from Petrak) and sertraline (Lustman 2006, from Petrak). There has been a lack of research on other modalities or newer psychotherapies. As minimal contact psychotherapies are gaining popularity in the depression literature, there is great potential for research trialing such treatments in PWD with comorbid depression. The need is especially for therapies that can be easily disseminated by heath care workers in various settings from primary to tertiary care. This will be discussed in the next chapter.

The disease impact of depression is compounded by the economic burden of a 50% – 75% increase in health service costs (Simon 2005) for PWD. It is also recognised that there is excess in mortality rates among patients with T2DM with both major and minor depression (Katon, et al., 2005). These factors and others discussed here highlight the significance of depression in DM for clinicians, researchers and policy makers alike.

1.4. Anxiety Disorders

While there has been broad coverage of depression, there is less coverage of anxiety disorders in DM. A review by Roy-Byrne et al. (2008) had noted a similar trend in relation to medical illness and speculated that this trend could be partly explained by anxiety symptoms not being seen as ‘serious’ or were subsumed by depressive disorders or the mixed anxiety-depressive concept. The reviewers recommend more research programs in future focusing on the impact of anxiety disorders and efficacy of evidenced based-interventions in medical illnesses. Das-Munshi’s meta-analysis (2007) found that mixed anxiety depressive disorder (MADD) had an odds ratio of 1.7 (95% CI 1.1 – 2.6, p <0.05) contributing significantly to the psychiatric morbidity in DM. Although the authors used a less restrictive

19 criteria for MADD than that used in the Diagnostic and Statistical Manual 4th Edition (DSMIV, APA), this finding suggests that in the majority of cases anxiety symptoms co-exist with depressive symptoms and exist on a continuum with DM-related distress. A meta-analysis of anxiety disorders in DM (Allison, et al., 2002) reported a prevalence rate of 14% for generalised anxiety disorder (GAD) in PWD in clinic populations and 3% to 4% in general community populations, with significantly higher rates in women but no difference between T1DM and T2DM. Another report described significant anxiety symptoms to be as high as 49.2% among PWD compared to 9% in the general population (Peyrot & Rubin, 1997).

Free-floating anxiety (of the variety described in GAD) in DM may be better conceptualised as specific worry towards issues surrounding DM. Symptoms of anxiety, particularly panic, may be mistaken for hypoglycaemia and a diagnosis of anxiety disorder may be missed in PWD with recurrent hypoglycaemia (Rubin & Peyrot 2001). Thus, PWD with frequent presentation to DM clinics complaining of hypoglycaemic symptoms with normal blood glucose levels on testing would benefit from screening for anxiety disorders. Here, the usage of a brief self-administered screening instrument such as the Patient Health Questionnaire (PHQ) anxiety module is recommended (Spitzer, et al., 1999).

Fear of hypoglycaemia, needle and injection phobia are specific phobias that occur in DM (Green 2000) and there are increased prevalence rates in PWD, with figures ranging between 21-26% for simple phobias, 11-16% for agoraphobia and 7-11 % for social phobia (Popkin 1988, Lustman 1986). These phobias lead to avoidance behaviors such as omission or manipulation of insulin dosages and avoidance of situations or places in which previous hypoglycaemic episodes had taken place. Recognised treatment for phobias includes cognitive behavior therapy (CBT)

20 incorporating graded exposure, although there is lack of research trialing specific psychotherapies in PWD per se.

1.5. Eating disorders

The evidence points towards a significantly higher prevalence of eating disorders in adolescent females with T1DM (Jones 2000, Daneman 1998, 2002, Crow, et al. 1998). Specifically, bulimia nervosa, eating disorder not otherwise specified (EDNOS) and subthreshold eating disorders are twice as common among adolescent girls with T1DM compared to non-DM subjects.

There is a trend for a research focus on adolescent females with T1DM but a noticeable lack of emphasis on teasing out preoccupation with food symptoms amongst adults with T2DM (Crow, et al. 2001). Compared to frank eating disorders in T1DM, eating disorders in T2DM are likely to fall into subthreshold eating disorders including binge eating disorder. Fairburn’s review (2005) critiques the nosological issues of eating disorder, particularly EDNOS, emphasising that while this entity is the most common form of eating disorder in routine clinical practice, there have been no efforts to conduct research to develop appropriate interventions. It seems prudent thus to document preoccupations and behaviours related to eating and inappropriate dietary control, and to target the specific behaviours using simple screening instruments – for example, the PHQ that has a useful eating disorder module. Comment [a3]: I thought this was getting a bit off the point and have shortened.

21 1.6. Stress of Daily Hassles and Life Events

The daily hassles of managing DM can result in a need to address practical lifestyle adjustments and the emotional and mental stresses that accompany it. Rubin & Peyrot (2001) divide these hassles into stressors associated with the illness itself (e.g. complications or disability) and those associated with needing to adjust lifestyle due to the illness (eg. diet, exercise, relationships, social and occupational demands). Chronic DM- related stress will be described further in Chapter 9.

Besides chronic stressors, the impact of acute life events should be considered in PWD. From the DCCT (The Diabetes Control and Complications Trial Research, 1993) in T1DM, Lorenz (1996) recommends guidance from health-care practitioners for PWD facing major life stressors, realising that times of stress impose a greater burden than that already incurred by the chronic demands of the illness. This multicentre randomised controlled trial (RCT) is currently the longest and largest prospective study to show that lowering blood glucose slows or prevents the development of DM related complications in T1DM. PWD were randomised to either an intensive or conventional treatment group. The trial used more behaviour change strategies in the intensive group. The success of the DCCT in reducing the risk for the development of DM complications has been said to be largely attributable to the impact of the behavioural or psychosocial component (Lorenz, et al., 1996). The relative impact of acute and chronic stressors has not been compared in PWD populations. Particular emphasis should be on identifying sub-populations who are vulnerable to the effect of various types of stressors.

22 1.7. The Deficit

Routine DM services have not been able to address the psychological needs of PWD and often these psychological co-morbidities remain undetected, as described earlier. The DAWN (Diabetes Attitudes, Wishes and Needs) project that studied the use of current psychosocial strategies employed by health care providers (Peyrot 2006) interviewed physicians and nurses in 13 countries on their awareness and usage of psychosocial interventions when managing PWD. The study found that nurses and DM specialists used more psychosocial strategies than non-specialist physicians. This may be due to lack of resources, consultation time in busy practices or the lack of prioritisation of psychological strategies amongst non-specialist physicians. Peyrot (2005) also commented on the lack of psychological support towards PWD especially by primary care practitioners, and suggested that future research target the development of models that addressed better delivery of services. There is evidence that monitoring and discussing psychological well-being have positive effects on the mood of PWD (Pouwer 2001).

DM practice guidelines have in recent years acknowledged the need for the provision of psychological interventions as part of standard DM treatment. This is an important step towards recognising the burden of psychological morbidity and taking steps to ensure that psychological needs of PWD are addressed. The American Diabetes Association in its 2009 Practice

Guidelines (2009) recommends psychological screening and treatment as Comment [JR4]: ?reference part of routine care. The guidelines suggest that psychosocial screening should be considered at key opportunities for example, at diagnosis or when there is a change in medical status, including change in treatment regime or development of complications. The Royal Australian College of

General Practitioners (http://www.racgp.org.au) Practice Guidelines 2009- Comment [JR5]: Make sure that this is in the reference 2010 for T2DM mention the stresses of living with DM and the role of 23 counseling, but do not elaborate on pathways to assessment, screening methods or on appropriate psychosocial treatment modalities.

1.8. Conclusion

Psychological comorbidity in DM exists in the form of frank psychiatric disorders, such as depression, anxiety and eating disorders; subthreshold disorders, and the emotional burden associated with managing the condition. The impact of these conditions on DM-related outcomes is enormous. Clinicians working with PWD need to continue to develop practices that incorporate psychological support. Consultation-liaison psychiatry services play a major role in developing psychosocial interventions to people with chronic conditions including DM. With limited resources and heavy workload, the emphasis should be on stratification of interventions according to various PWD subpopulation needs. Brief interventions would need to be assessed as potential modalities in view of the practicality of implementation.

Though the emphasis of research has been generally to address frank psychiatric disorders, it is obvious that subthreshold emotional states and daily hassles associated with DM pose a significant burden. Screening and intervention strategies should attempt to target these conditions besides the standard psychiatric disorders that fulfill traditional diagnostic criteria such as the DSM-IV and ICD-10.

24 CHAPTER 2: PSYCHOSOCIAL INTERVENTIONS IN DIABETES MELLITUS: A LITERATURE REVIEW

2.1. Introduction

In the last chapter, it was established that PWD experience significant psychological comorbidity. In view of this, DM treatment guidelines in several countries have called for the inclusion of psychosocial interventions as part of routine DM care.

This chapter reviews the literature in adult PWD and addresses the following questions: 1) What are the common psychosocial interventions in DM? 2) On what basis should we design psychosocial interventions to meet PWD subpopulation needs? 3) What is the role of brief interventions in DM?

The chapter begins with a definition of psychosocial interventions. A critique of review papers in this field follows and gaps in the literature are identified with recommendations for future research/clinical practice focus.

2.2. Definition

The term “psychosocial intervention” as a category encompasses a wide variety of interventions. There is little consensus on what constitutes psychological or psychosocial interventions in DM. The boundaries between psychologically based therapies and interventions aimed at modifying lifestyle and other behaviours specifically related to DM care are blurred, as acknowledged by two separate reviews more than a decade 25 apart (Rubin & Peyrot, 1992) (Ismail, et al., 2004). Furthermore, in their review, Steed et al. (2003) found that many studies did not provide adequate details of the theoretical basis and components of the interventions. They described “psychosocial outcomes following interventions in diabetes”, which they divided into: education, self- management and psychological interventions. Educational interventions were more prominent in early research and focused on the dissemination of knowledge. Self-management interventions consisted of problem-solving, technical skills training (such as blood glucose self-monitoring) and behavioural components that aim to improve adherence and address attitudes and beliefs towards DM; while psychological interventions aimed to decrease negative mood states such as depression and significant anxiety or stress problems. The same authors found that educational interventions alone were not effective in improving psychosocial outcomes compared to self-management and psychological interventions and argued for the classification of didactic educational interventions as a separate entity.

Norris et al. (2001) argued for the division of educational interventions into didactic and collaborative (which encompassed interactive, hands-on interventions) and noted the evolution of the literature from didactic to collaborative ‘empowerment’ from the 1970s to the 1990s. They advocated for the inclusion of collaborative educational interventions in future psychosocial studies, incorporating the study of mediating factors such as coping skills and problem solving. Thus the field has moved away from interventions that merely target knowledge and attitudes, towards behavioural and psychological interventions targeting behaviour modification and mood states.

More recent meta-analyses ((Ismail, et al., 2004) (Winkley, et al., 2006)) have taken heed of the recommendation to separate educational

26 interventions from psychosocial interventions. This chapter will therefore focus on the state of the current literature for psychological and self- management interventions in DM, while acknowledging some overlap with educational interventions. The term “psychosocial interventions” shall be used throughout this thesis unless individual emphasis on psychological interventions and self-management interventions is required.

2.3. Key Review Papers

There have been several systematic reviews and meta-analyses on psychosocial interventions in DM. Key papers reviewing psychosocial interventions in adult DM populations since the year 2000 are discussed here (Table 2.1). Although the focus is on interventions in adult populations, reviews incorporating both children and adults will be mentioned.

27 Table 2.1: Summary of key review papers on psychosocial interventions in DM Author DM Type No. of Result/Effect sizes Key studies (Adults only) recommendation selected by authors Winkley Type I 29 RCTs Adults: To include patient et al. Adults and (21MA) HbA1c (ES = 0.17)# preference in (2006) Children Adults Psych distress(ES = 0.25)# future trials. Children: (11 Psych distress (ES = 0.46)* studies, n=516) Children (10 studies, n=543) Ismail Type 2 25 RCTs HbA1c (ES =-0.32)* To target specific et al. Adults (12MA) Psych distress(ES = -0.58)* psychological (2004) (n= 522) problems.

Steed Type 1, 36 (PSYCH & SM) more To assess et al. Type 2 and studies; efficacious than EDUC. positive well- (2003) combined RCTs, No evidence of didactic being. Adults CTs and EDUC alone. To determine pre-post target population trials for interventions. (SR only)

Snoek Type 1 and 11 RCTs No effect sizes, due to small To explain & Type 2 (SR only) sample size. theoretical basis. Skinner Adults To conduct more (2002) multi-centre studies.

28 Norris Type 2 72 RCTs Patient collaboration more To assess quality et al. Adults effective than didactic of life as outcome (2001) interventions in improving indicator. weight, glycaemic control and lipid profiles.

# not significant * significant Abbreviations: RCTs: randomised controlled trials, CTs: controlled trials, EDUC: educational interventions, PSYCH: psychological interventions, SM: self- management interventions, SR: systematic review, MA: meta-analyses, ES: effect size

29 Overall, the reviews found evidence for the efficacy of psychological interventions in improving outcomes in DM. Taking glycosylated haemoglobin (HbA1c) as an outcome indicator, moderate effect sizes were detected by Ismail et al. (2004) (ES = 0.32) and Winkley et al. (2006) (ES = 0.17 for adults). HbA1c was well represented as an outcome indicator in the meta-analyses in contrast to psychological outcome indicators, which featured in only 25% of the studies in Ismail’s meta-analysis and 50% of papers in Winkley’s meta-analysis. A reason for the lack of psychological outcome indicators such as depression and DM-specific distress scores may be that most studies targeted generic DM populations rather than PWD with specific psychological problems or frank psychiatric disorders. Ismail et al. (2004) identified only four studies (16%) addressing specific psychological problems such as depression, binge eating, and stress; while the review on T1DM revealed only one study out of 29 studies targeting a specific population (Winkley, et al., 2006). Snoek (2003) reviewed specific targeted RCTs towards depression, anxiety, eating disorders, self- destructive behavior and interpersonal conflicts and found only 11 studies addressing these areas, and commented on the lack of properly designed trials addressing specific psychological conditions in PWD. It is evident therefore that there is a lack of interventions tailored to the psychological needs of specific PWD subpopulations.

Self-management interventions have been widely described in the DM literature. A review by Norris et al. (2001) on RCTs in adult T2DM highlighted the role of self-management interventions particularly for those experiencing daily hassles that increased DM related morbidity. These authors identified coping skills training, emotional-regulation interventions as well as problem-focused interventions as the common varieties of self- management interventions. The relative indications for problem-focused and emotional-regulation interventions with respect to PWD sub-population needs have not been addressed. Though one can argue for SM

30 interventions to be principally administered by DM clinicians, it cannot be denied that its implementation involves multidisciplinary team members, including mental health/consultation-liaison psychiatry clinicians, thus consuming resources. It is also obvious from Chapter 1 that DM-related daily hassles pose a significant morbidity to PWD and constitute an area that requires intervention.

Combining the analyses by Ismail, Winkley, Steed and Snoek together, cognitive behaviour based therapies (CBT) were the most reported (35 studies or 70%), followed by supportive- and counseling-based therapies (10 or 20%), family systems (3 or 6%), and psychodynamic psychotherapy (2 or 4%). The reviewers acknowledged that the bias towards CBT-based therapies prevented comparison of the relative efficacy of the various psychotherapies. The interventions generally involved multiple sessions with the involvement of trained therapists suggesting that minimal-contact interventions have been largely unstudied in DM.

The lack of emphasis on well-being and positive psychological adjustment outcome indicators is apparent in research in this field. Steed et al. (2003) highlights the relative dominance of morbidity outcome indicators over well- being indicators, adding that the emphasis on specific disease outcomes has minimised the usage of quality of life outcome indicators in research trialing psychosocial interventions. Future research in this area could thus take these comments on board, as for instance the recommendations by Norris et al. (2001) to include such outcome indicators of positive wellbeing as self-efficacy and coping. Outcomes to be measured should be carefully selected and tailored to the objectives of the intervention. Positive psychosocial outcomes such as quality of life should be included as these are lacking in the literature to date (Norris, et al., 2001), (Steed, et al, 2003).

31 There is lack of research comparing psychological interventions between T1DM and T2DM. Although Steed et al. (2003) included studies on T1DM, T2DM and combined populations; there were insufficient studies to make comparisons on the relative efficacy of interventions for both types of DM. There are major differences between T1DM and T2DM both physiologically and psychologically. The relative early onset of T1DM means that the individual is likely to be negotiating an earlier developmental life phase when compared to a largely adult population experiencing the onset of T2DM. Furthermore T1DM requires the administration of insulin from the outset, while in T2DM oral hypoglycaemics are the mainstay of treatment. These factors contribute to potential differences in the appraisal, coping and nature of daily hassles that accompany the illness. The differences in the psychological profiles of people with T1DM and T2DM create a need to develop tailored interventions.

Based on the reviews discussed above, the system of classifying intervention categories into PSYCH, EDUC, and SM seems practical as evidenced by the way the reviewers have grouped these categories of interventions in their reviews. Putting together the findings and recommendations from these systematic reviews and the other literature, some common threads with respect to gaps in the literature and future pathways will be discussed in this chapter. A discussion on the common psychosocial interventions in DM follows.

2.4. Common Psychosocial Interventions in DM

The classification of types of psychosocial interventions in DM is made complex, as the majority of studies have not provided adequate details of the actual components. In their review, Ismail et al (2004) state that the

32 actual conceptual framework on how each intervention works and what it targets has not been addressed in most research papers. Additionally, some studies have combined modes of therapies, which lead to the difficulty in identifying the effective components of each. Nevertheless, the reviews described in Table 2.1 have identified several major schools of psychosocial interventions in DM, which will be discussed below.

2.4.1. Cognitive Behaviour Based Therapies (CBT)

The most widely reported studies in systematic reviews of DM involve variants of CBT. There is wide variation in the indications, mode of delivery and design of these therapies making it a heterogeneous group rather than a single entity. The interventions comprise of either comprehensive targeted programs designed specifically for frank psychiatric disorders; non- specific stress management techniques taught to generic PWD populations, or as behavioural interventions targeting lifestyle modification and better DM control. The mode of delivery of interventions is varied, from face-to- face interventions to minimal contact or self-help therapies.

Lustman et al. (1998) described a CBT trial targeting PWD with a frank psychiatric disorder. This RCT treatment of adults with T2DM with comorbid major depression found that 85% of subjects in the CBT treatment group (n = 20) compared to 27.3% of controls (n = 22) achieved remission. Though this trial had a small sample size, it remains to date the only CBT trial targeting depression in T2DM. The authors found that in the CBT treatment group, there was a statistically significant decrease in self-monitoring of blood glucose compared to the control group (who received DM education). They postulate that the focus on monitoring of cognitions in the interventional group may have distracted participants from attending to their routine DM monitoring.

33 Another CBT-based study incorporated a time-limited problem orientated therapy in people with T1DM receiving intensified insulin therapy who had microvascular complications (Didjurgeit, et al., 2002). This trial measured several outcomes, and demonstrated that there was significant improvement in the intervention group for HbA1c levels and non–significant decreases in depression scores and improvement in quality of life. The authors concluded that the lack of specific focus on depression might have contributed to the lack of significant improvement in depression scores, a point that supports the argument to tailor interventions and outcomes to meet specific sub-populations.

The heterogeneity of CBT-based therapies can be reconciled if researchers design interventions to meet specific DM sub-populations and measure relevant outcomes according to the targeted problem area. Van der Ven et al. (2005) sought to answer the question of which sub-group of T1DM with poor glycaemic control should be targeted for cognitive behavioural group therapy (CBGT). They concluded that female PWD who had high levels of psychological dysfunction and high levels of DM-specific distress were more likely to participate in the intervention. It may be that females who have high levels of emotional arousability are more likely to realise the need and therefore take-up particular interventions in DM.

CBT-based psychotherapies cover a wide range of interventions and are often bracketed with stress management. The stress management component implies health promotion or measures that can help prevent morbidity in the general population, and their place in the DM psychosocial intervention literature deserves consideration. As early as 1936, field trials were published to show that practising relaxation techniques could lead to a significant reduction in insulin requirements (Surwit, et al., 1983). This was one of the earliest documents suggesting that periods of extended emotional stress raise insulin requirements; a hypothesis that prompted

34 study of the detrimental effects of stress, initially on glycaemic control in ob/ob mice (Surwit, et al, 1984) and subsequently in PWD (Surwit, et al., 2002). In the latter RCT, a total of 108 Type 2 PWD were randomised to receive a five-session group based education program with stress management training (n = 60) or without stress management training (n = 58). The intervention group experienced a small (0.5%) but significant reduction in HbA1c levels post-intervention. The authors recommend stress management interventions as the fourth most important component for the treatment of all PWD (Surwit, et al., 2004) after diet, exercise and medication. Thus, stress management interventions are suitable for generic PWD populations, particularly those with high emotional reactivity.

PWD with frank psychiatric disorders require rigorous screening and intervention. Those with DM hassles and sub-threshold syndromes may benefit from such interventions that can be offered with minimal therapist contact for example through the use of handouts and books, with minimal telephone monitoring or through the internet. The efficacy and feasibility of these modes of delivery of intervention have to be addressed in PWD populations in future studies. Identification of suitable sub-populations who would accept and benefit from such interventions is vital.

2.4.2. Motivational Interviewing (M.I.)

M.I. was reported to be the second most common therapy among people with T2DM (Ismail et al., 2004). An RCT examining the effect of adding M.I. strategies to a behavioural obesity program on adherence and glucose control in older obese women with T2DM (Smith et al., 1997) found that the M.I. group had greater adherence to standard self-management strategies and better blood glucose control than the standard group, although weight loss did not differ significantly between the groups. Motivational Interviewing is increasingly seen as useful in changing illness related

35 behaviours and for guiding patients through the stages of motivation to achieve desired goals. Rollnick (2008) highlights that the “collaborative” and “honouring of patient autonomy” principles of the spirit of motivational interviewing are appropriate for patients with chronic illnesses. Furthermore, using Prochaska’s stages of change, the clinician is able to assess each of the targeted PWD’s behaviours, for example, dietary and weight control, or compliance in self-monitoring of blood sugar, and guide the client through the stages until ready with an action plan.

While not necessarily a therapeutic intervention by itself, motivational interviewing can be integrated into chronic illness care frameworks, and is a useful skill that can be taught to various members of health care teams. For example, Channon (2003) reported on the benefits of using problem solving and goal setting strategies in tandem with M.I. for adolescents with T1DM. M.I. is therefore versatile and a good strategy as an adjunct to structured interventions (e.g., problem-solving therapy). Ciechanowski et al. (2004) considers the benefit of motivational interviewing in PWD with dismissive attachment styles, stating that the collaborative empowerment style found in motivational interviewing may be beneficial for this group of people.

In summary, there is wide potential for the usage of motivational interviewing in DM, particularly to address adherence and lifestyle change issues and their emotional implications.

2.4.3. Other Interventions of note

There are no published studies to date on the efficacy of interpersonal psychotherapy (IPT) in DM. Research trialing IPT in PWDs is warranted given the various issues attached to loss, and role transitions in chronic

36 illnesses. There have been studies reporting on the efficacy of IPT in chronic illness populations. PWD undergoing transitional phases in their illness journey, or who experience losses with respect to DM and its implications are potential target groups.

Gregg (2007) reports on the usage of Acceptance and Commitment Therapy (ACT) in DM. ACT has been used for chronic conditions for instance chronic pain, with positive outcomes (Dahl 2004). ACT empowers the client to reflect on the present moment (for example, through mindfulness) making it a suitable therapeutic option for PWD who are constantly exposed to cues surrounding the illness, particularly in high stress-reactive individuals. There is a case for ACT in DM particularly for those with high emotional reactivity. Highly stress-reactive PWD can be identified through individual and illness factors, which will be discussed in the following chapters.

The benefits of expressive writing as a form of emotional regulation in improving physical parameters in chronic conditions like rheumatoid arthritis and bronchial asthma have been reported (Smyth 1999). More recent work in this area has focused on selection of appropriate populations that would stand to benefit from this intervention according to individual factors, for example personality and coping (Baikie 2008). This knowledge can be transferred towards identifying PWD sub-populations with high levels of arousability who may be candidates for expressive writing.

37 2.5. Identification of Psychologically Vulnerable PWD Subpopulations

2.5.1. Target Population

There have been differing opinions on whether to offer psychosocial interventions to all PWDs or just those with specific issues. While some systematic reviews included studies targeting the general DM population (Ismail, et al., 2004; Winkley, et al., 2006; Steed, et al., 2003), others focused on PWDs with specific needs, such as psychological and physical comorbidity, and DM complications (Snoek & Skinner, 2002; Rubin & Peyrot, 1992). Authors such as Steed et al. (2003) suggest studying depressed and non-depressed populations to better understand whether psychological treatment is beneficial to the general DM population or only for those with emotional problems. Vamos (2006) comments that the issue of who should be offered psychological interventions in chronic medical illness has not been given due consideration in the literature and that target groups have to be identified before meaningful interventions can be offered to address the diverse needs of patient populations. Rubin & Peyrot (1992) argued that interventions should target specific populations rather than the general PWD population. There is thus adequate consensus for identifying the appropriate target population and for choosing appropriate interventions to meet individual and sub-population needs. It has been said that “Interventions tailored to meet the specific needs of an individual are more likely to lead to change compared to untailored interventions” (Clark, et al., 2004). Therefore there is a need to study individual and illness variables with respect to suitability and tailoring of interventions.

38 2.5.2. Method of delivery of interventions

Stratification of psychological interventions is an effective method of disseminating treatment modalities to specific populations according to need. Katon’s group (2004) have reported their Pathways Study, which aimed to examine the effect of a collaborative care intervention on PWD with major depression and/or dysthymia within a primary care setting. The study design featured an RCT with a case management intervention (enhanced education + choice of either antidepressant medication or problem-solving therapy) versus ‘usual care’. PWD in the intervention arm had improved depression outcomes resulting in a significant reduction in health-care costs over a five-year period (Katon, et al., 2008). This model addresses the diversity issue of PWD with depression by providing a ‘stepped care approach’ based on depression symptom severity after the first 12 weeks of treatment. This is an example of the usage of targeted interventions stratified according to specific PWD groups as dictated by illness variables. Here problem solving was used as an evidence-based short-term intervention. Research using ‘stepped care’ designs like the Pathways Study can help determine how to best deploy limited resources to PWD who are in need of psychosocial services. Training of DM personnel in providing psychosocial care within the service needs should be considered. Counseling, problem- solving strategies and goal setting can be used by nurses and DM educators as part of their routine management.

PWD may benefit from minimal contact psychotherapies where the key ingredient is patient empowerment rather than therapeutic relationship. Willemse (2004) reported on the efficacy of minimal-contact psychotherapy for subthreshold depression in primary care, vouching for its benefits, particularly in the prevention of the onset of major depression. This is a cost-effective format that deserves further study in PWD populations.

39 2.6. Factors to Consider When Tailoring Psychosocial Interventions for PWD Sub-populations

2.6.1. Individual Biopsychosocial characteristics (personality, genetic factors, previous coping)

Individual factors such as genetic variation, personality traits and predispositional coping styles are important factors that might determine how people handle stressful situations. Personality traits and coping have been studied widely but not much in the way of designing interventions. The relationship between personality traits and coping styles will be explored in Chapter 6.

Recent research has highlighted the link between a polymorphism in the serotonin transporter (5HTTLPR) gene and emotional arousability (Hariri, et al., 2005). A candidate endophenotype for the 5HTTLPR is predispositional coping style. Coping styles can be modified and are amenable to intervention. Wilhelm et al. (2007) found that people with at least one “s” allele of the 5-HTT gene had the tendency to use lesser problem-solving strategies than those with the “l” allele whenever they encountered stressful situations. This finding suggests that people with the “s” allele may use emotional regulation techniques to successfully negotiate a stressful life event, a hypothesis that requires further testing in future research. The hypothesis is that highly emotionally arousable individuals (as indicated by the 5HTTLPR “s” allele) are more vulnerable to depression in the face of adverse life events or chronic stress (as in the case of DM). Identifying these individuals and imparting emotional regulation coping skills training may provide resilience towards the chronic stressors of a condition like DM. 40 Research in this area is in its infancy and the focus should be on delineating stress pathways implicating the 5HTTLPR and DM with the aim of eliciting possible endophenotypes and clear end phenotypes. The relationships between the 5HTTLPR and coping, followed with gender in a chronically stressed population will be explored in forthcoming chapters.

2.6.2. Illness Factors

Daily hassles in life are formidable stressors that can be as demanding and have an equal impact on PWDs as adverse life events. Interventions targeted at daily hassles have been neglected as has been highlighted by Van der Ven (2005). The authors argue that interventions designed for people with T1DM have focused on intensive psychotherapies, which may not be appropriate at addressing the pertinent issues associated with DM. It is important therefore to design interventions targeting specific subpopulations of PWD with respect to issues arising from DM care.

Preliminary trials to stratify DM subpopulations according to specific groups will enable streamlined clinical trials targeting specific groups, for example PWD with depression, multiple medical comorbidities or those who use maladaptive coping strategies. There is a need to develop psychosocial interventions to address the needs of PWD subpopulations (Rubin & Peyrot, 2001) with emphasis in improving constructs such as coping strategies. Perhaps more important is the need for research to prove that implementation of such intervention strategies will indeed improve physical parameters in DM such as glycosylated haemoglobin (HbA1c) and reduce systemic complications e.g., retinopathy, neuropathy and nephropathy; as well as psychological (depression, anxiety, DM-related distress) and well- being parameters (coping, quality of life).

41 Psychosocial interventions could also be developed to focus on specific sub-threshold psychological morbidity states. A method of screening that identifies these populations early in their illness journey and provides appropriate pathways to care will ensure that interventions are available at an appropriate stage.

2.7. Conclusion

While there have been a wide variety of psychosocial interventions in DM reported in the literature as evidenced by the systematic reviews mentioned in this chapter, there is a need to study the tailoring of interventions for specific sub-populations. Effectiveness interventions studying various individual and illness PWD sub-populations could be key to identifying vulnerable populations and those who will benefit from tailored interventions. The practicality of brief interventions or minimal contact interventions should be studied with the intention of targeting specific populations. The following chapters shall define these sub-populations and discuss relevant psychosocial interventions tailored for these groups of PWD.

42 CHAPTER 3: RESEARCH OBJECTIVES, QUESTIONS AND METHODOLOGY

3.1. Research Objectives:

The primary objective of this thesis is to establish the ability of individual differences (personality styles, coping patterns, and the serotonin transporter genotype); and illness factors (DM type, diabetes-related distress) to determine psychologically vulnerable DM sub-populations who would benefit from brief psychosocial interventions. The secondary objectives of this thesis are to determine if brief psychological interventions are effective for people with diabetes and to identify useful screening measures for psychological distress in DM. The research hypotheses will be discussed in the individual chapters.

3.2. Research Questions:

Q 1: Can individual (personality, coping, serotonin transporter genotype), and illness (DM type, diabetes-related distress) characteristics determine psychologically vulnerable subpopulations that may potentially benefit from brief psychological interventions in DM?

Q 2: Are brief psychological interventions effective for people with DM?

Q 3: Which measures are most useful for screening for psychological distress among people with DM?

43 3.3. Procedure

This thesis is based on the Stress Sampler Study, which was carried out at the Diabetes Clinic, St.Vincent’s Hospital and the Diabetes Centre, Prince of Wales Hospital, Sydney. Recruitment was conducted from July 2006 till March 2008. Patients waiting to see their doctor at the clinic were approached by a research assistant and handed a flyer explaining the study and a consent form. They were given time to read through and consider participation, and the research assistant was on hand to answer any queries.

Patients who had given consent were given a set of the study questionnaires to fill in the waiting room. They were then taken into a consultation room to be interviewed by research psychiatrists, Dr. Jaya Reddy (JR) or Prof. Kay Wilhelm (KW). The interview consisted of an inclusion/exclusion criteria checklist, questions pertaining to past and present psychiatric and medical history and a list of current diabetic medications and psychotropic medications. The past psychiatric history had particular emphasis on depressive disorder that was obtained subjectively from the participant. Only those who indicated that they had been diagnosed and had received some form of treatment for a depressive disorder were recorded as having had a positive past history of depression. Glycosylated haemoglobin (HbA1c) levels on the day of recruitment (as done routinely on every clinic visit) were obtained from the case notes.

A cheek swab was then taken for genotyping (Procedure in Appendix E). Subjects recruited into the study were then referred back to their respective research assistants who performed a randomised allocation to one of three groups according to a computer generated block randomisation sequence. This procedure was carried out to ensure that the research psychiatrists, JR

44 and KW remained blind to the intervention groups throughout the course of the study. The intervention arm of the study shall be discussed below.

3.4. Study Design

Though the interventional aspect of this study was a randomised controlled trial (RCT), it was designed to be an effectiveness trial, representative of real practice. Hence the inclusion criteria were relatively lax to include a wide population of PWD, including those without any psychiatric comorbidity, to ensure a broad and representative sample. PWD who were on psychotropic medications or who were receiving psychotherapy were included. These were documented in the clinical interview sheet. The inclusion and exclusion criteria were as follows:

Inclusion Criteria: x PWD with T1DM or T2DM x Ability to read and write in English.

Exclusion Criteria: x Presence of psychosis or cognitive impairment.

A flow-chart of the longitudinal study is presented in Figure 3.1 The research assistants explained the interventions and worksheets (Appendix F) and that they will be in contact via telephone one week later to answer any questions regarding the interventions. This was followed up by a phone call at week four of each phase to answer any questions and explain the next phase. The two intervention groups received the opposite (cross- over) interventions after 6 weeks (Study Point 2), and at the same time a set of study questionnaires were sent with a self addressed envelope to be returned to the researchers. At three months, (Study Point 3) the same sets of questionnaires were circulated to the participants.

45 The control group was allocated a mood monitoring exercise (Appendix G), in which they were asked to monitor their moods on a daily basis for 12 weeks. At the end of 12 weeks, they were offered an intervention of their choice.

The interventions were explained by the worksheets with instructions on how they could be best used to address a particular stressful situation (including those related to their diabetes) or generic situations. Worked examples of such situations were given, for example problem-solving around a diabetes stressor, or setting goals for given time frames around issues surrounding their personal lives. The participants were encouraged to fill up the worksheets and send them back to the research team at 6 weeks and 3 months. For the emotional regulation interventions, the participants were encouraged to practise breathing and mindfulness exercises (techniques and examples of applications given) and to note down occasions when they had used the exercises.

In between study time periods, the investigators called the participants to find out how they were progressing with the study and if there were any questions regarding the techniques or approach of carrying out the strategies. It was not the intention of the study to offer supportive psychotherapy or specific guidance regarding psychosocial issues over the phone. The participants’ diabetes clinicians were not involved with the study; therefore the participants did not receive any guidance form their regular clinicians regarding the usage of the interventions included in the study.

46 3.5. Materials

These are attached as Appendix D. Principal Components Analyses, which were performed for the COPE, K10 and PAID questionnaires, are described in Chapters 4 and 9.

3.5.1. PHQ (Patient Health Questionnaire)

This self-administered diagnostic questionnaire generates 8 criteria-based categories – somatisation disorder, major depression or other depressive disorder, panic and other anxiety disorder, eating disorder and alcohol dependence. The PHQ-9 is a sub-section of the PHQ, which not only establishes DSM-IV based depressive disorders, but also measures depression severity on a scale of 0-27. It has established criterion, construct and external validity (Kroenke 2001) and has established usage in primary care (Spitzer 1999) and general hospital inpatient settings (Diez- Quevedo 2001). It has been used in research on PWD in primary care settings (Katon 2004). It was demonstrated to have a sensitivity of 73% and a specificity of 98% when validated for major depression diagnosis against a structured psychiatric interview (Spitzer 1999).

3.5.2. K 10 (Kessler-10 item)

The K10 is a 10-item self-rated scale that measures symptoms of psychological distress during the past 30 days (Kessler, et al., 2002). It is suitable for screening in the general population (Perini 2006) and has an internal consistency (Cronbach’s alpha) of 0.93 (Kessler, et al., 2002). It is sensitive to symptom change in anxiety disorders, making it a useful instrument to measure outcomes in interventional research.

47 3.5.3. SF12 (Short-form health survey)

The 12-item short-form health survey (SF-12) (Ware 1996) was derived from the original Medical Outcomes Study 36-item Short-Form Health Survey (SF-36). It is a quality of life questionnaire (QOL) with lower scores indicating poorer health. Its utility as a brief questionnaire to measure physical and psychological health has been demonstrated. It comprises of two summary measures: the physical component summary (PCS-12) and the mental component summary (MCS-12). The PCS-12 and MCS-12 was demonstrated to have test-retest reliabilities of 0.864 to 0.890 and 0.760 to 0.774 respectively, with a predictive validity of 0.91 for the PCS-12 and 0.94 for the MCS-12.

3.5.4. PAID (Problem Areas in Diabetes)

The PAID is a 20-item questionnaire designed to measure emotional responsiveness to DM (Polonsky 1995). It is a screening instrument for clinical and research use in diabetes, designed to help clinicians to identify PWD with high levels of distress. The emphasis is on the measurement of DM-related emotional distress as opposed to general emotional distress. Each item is rated on a 5-point Likert scale measuring DM-specific emotional distress and psychosocial adjustment to DM. It has items measuring treatment related issues (3 items), food related problems (3 items), social support related problems (2 items), and DM-related emotional distress (12 items). Total scores are multiplied by 1.25 to give a definitive score with the range of possible scores being 0 – 100, (with higher scores indicating greater emotional distress). It has been demonstrated to have sensitivity to change (Welch, et al., 2003) thus making it suitable as an outcome measure. An internal reliability of Į = 0.90 and test-retest reliability of r = 0.83 (Welch, et al., 2003) has been established.

48 3.5.5. COPE

The COPE inventory (Carver, et al., 1989) is a 60-item self-administered questionnaire with responses graded on a 5-point Likert scale. It was developed to address a broad variety of coping styles, resulting in 4 factors with 15 subscales comprising of 4 items each. The subscales are “active coping”, “planning”, “suppression of competing activities”, “restraint coping”, “instrumental social support”, “positive reinterpretation, “acceptance”, “denial”, “turning to religion”, “emotional social support”, “focus on & venting emotions”, “behavioural disengagement”, “mental disengagement”, “substance use”, and “humour”. The authors suggest factors comprising of problem-focused, emotion-focused, social support strategies and avoidance focused strategies. However they recommend that researchers perform independent factor analyses to organise subscales into appropriate factors. The COPE is designed to assess both situational and dispositional coping strategies. This study used a dispositional version, where respondents were instructed to report how they usually attempt to cope with life situations. Response choices were from 1 (‘I usually don’t do this at all’) to 4 (‘I usually do this a lot’).

3.5.6. NEO-FFI (NEO Five Factor Instrument)

The NEO Personality Inventory (Costa 1992) measures personality traits based on a five-factor model, Neuroticism, Extraversion, and Openness to Experience, Agreeableness, and Conscientiousness. More than measuring psychopathology, the NEO has demonstrated usefulness in the measurement of personality traits in research as well as clinical practice. This information can be used to inform decision-making processes when determining diagnoses and treatment modalities. It is a 60 item self-report

49 questionnaire with responses graded on a 5-point Likert scale (‘strongly disagree’ to ‘strongly agree’).

3.6. DNA extraction and genetic analysis

Participants’ 5-HTT-promoter genotype (s/s, s/l or l/l) was determined via cheek swab analysis. To extract genomic DNA, cheek swabs were collected in a solution containing 10 mM Tris-HCl pH 7.5, 10 mM EDTA, 0.5% sarkosyl. Samples were treated by overnight digestion at 42oC with 0.4 mg/ml proteinase K, followed by addition of 0.90 M guanidine HCl and 0.56 M ammonium acetate and incubation for 1 h at 60oC. DNA was purified by standard chloroform extraction and ethanol precipitation, and was re-suspended in 1 mM Tris-HCl pH 7.5, 0.1 mM EDTA. The 5- HTTLPR was amplified with the following primers: forward 5'- TGCCGCTCTGAATGCCAGCAC-3', and reverse 5'- GCGGGATTCTGGTGCCACCTA-3', to generate a 464-base pair (bp) product for the 16-repeat (l) allele, and a 420-bp product for the 14-repeat (s) allele. The polymerase chain reaction (PCR) was performed in 25-μl volumes containing Platinum Taq PCR reaction buffer (Invitrogen), 1.5mmol/l MgCl2, 400 mM betaine, 0.16 mM each of dATP, dCTP and dTTP, 0.08 mM each of dGTP and 7-deaza-2'deoxyguanosine 5'- triphosphate, 40 ng template DNA, 20 pmol of each primer, and 0.5 U of Platinum Taq DNA polymerase (Invitrogen). Reactions included initial denaturation at 94oC for 2 min, followed by 35 cycles at 94oC for 30 s, 65oC for 45 s, 72oC for 90 s, and a final extension of 10 min at 72oC. After electrophoresis in 2% agarose gels, ethidium bromide-stained products were visualised under ultraviolet light.

50 3.7. Sample Size Calculation

The sample size calculation was based on the intervention arm of the study. This study aimed to compare 3 groups - two intervention (treatment) groups and one control group. Sample size was calculated using the PHQ- 9 as the major outcome measure. The desired improvement in PHQ-9 score was set at a clinically significant difference of 5 points. This was calculated based on the 3 study groups, with a clinically significant difference of 5 points (anticipated mean change score on PHQ-9) and the anticipated standard deviation is 6.1. The sample size required for an D of 0.05 and a power of 80% was determined to be 24 cases per group (Change scores, mean, standard deviation based on Lowe et al. (2004)).

Approval was obtained from the St.Vincent’s Hospital and University of New South Wales Ethics Committees. This study received funding from the NHMRC Program Grant 222708 and by an Infrastructure Grant from the Centre for Mental Health, NSW Department of Health. The following chapters will re-visit parts of the methodology as relevant to the particular chapter as necessary.

3.8. Intervention Sheets

The intervention sheets were designed by the research team, based on those already used in the St.Vincent’s Consultation-Liaison Service (Appendix F).

51 They comprised:

A) Problem-Focused Interventions: (Appendix G) 1) Problem-Solving 2) Goal-Setting 3) Making Changes

B) Emotional-Regulation Interventions: (Appendix G) 1) Mindfulness Meditation 2) Relaxation Exercises

C) Mood-monitoring Charts: (Appendix H)

52 Figure 3.1 Study Flow-Chart

53 CHAPTER 4: IDENTIFYING SUBPOPULATIONS WITHIN A DIABETES SAMPLE WITH SPECIFIC NEEDS FOR PSYCHOSOCIAL INTERVENTIONS

ABSTRACT

Introduction: The Stress Sampler Study sought to identify subpopulations within patients attending a diabetic service that may have specific needs for psychosocial interventions. These subpopulations were analysed in relation to individual variables such as personality traits and coping; illness variables including HbA1c and physical comorbidity; and psychological outcome variables including current depression (measured by the PHQ), DM-related distress (PAID), generic psychological distress (K10) and health-related quality of life (SF-12). Methodology: 274 Type 1 and Type 2 PWD were recruited into the study. Participants were administered questionnaires and interviewed by the investigators as detailed in Chapter 3. Results: Younger PWD (aged 59 years and less) experienced significantly higher levels of psychological distress as measured by the K10 (p<0.05), and used more avoidance coping (p<0.01). Older PWD had higher levels of medical comorbidity, and significantly lower SF-12 PCS (p < 0.01) scores than younger PWD. Past history of depression was associated with higher DM-specific distress (as measured by the PAID, p< 0.01), after controlling for current depression (PHQ-9) scores. Conclusion: Simple means of identifying subpopulations of PWD with specific psychosocial needs can provide a useful means of tailoring psychosocial intervention strategies to meet the needs of these groups.

54 4.1. Introduction

The implications of psychological illness and distress in DM are enormous in terms of individual, caregiver and socio-economic burden. This burden contributes to an increased likelihood of DM-related complications and higher mortality rates. Chapter 1 discussed the psychological burden and comorbidity of DM. The review found consistently higher rates of psychological morbidity in DM compared to the general population. In Chapter 2, I summarised the current state of the literature on psychosocial interventions in DM, highlighting that psychological interventions incorporating effective coping, self-efficacy and self-management skills are of great benefit to PWD. The chapter also stressed the need to tailor interventions to ensure feasibility and acceptability to specific PWD populations, as highlighted by Delamater et al. (2001). On a broader scale, Guthrie (2007) stressed the need to develop and test brief interventions for chronic illness populations. Taken together, with the lack of resources for psychological interventions in PWD, the benefits of triaging vulnerable sub- populations according to levels of priority is worthy of consideration.

PWD comprise a heterogeneous group. The choice of psychosocial interventions for specific subgroups could be influenced by social factors such as age of onset, gender, employment status; illness factors such as type, duration and severity of DM, medical complications and comorbidities; and factors related to the personality, coping style, emotional responsivity to stress and individual life context for each patient. Clinicians need guidance on how to select targeted interventions in “real world” clinical settings.

This chapter describes the individual parameters (coping, personality traits), DM illness variables (HbA1c, physical comorbidity) psychological morbidity

55 (DM-specific distress, general psychological distress, depression, anxiety) and health-related quality of life of the DM cohort admitted into the study. The specific aim is to determine differences in the said parameters among different subpopulations (type of DM, age group) of people with DM, as this could later assist in determining tailored or stratified interventions to suit specific needs of the population.

Results of Principal Components Analysis of the COPE and K-10 questionnaires are presented in this chapter. A detailed description of the methodology and instruments used is provided in Chapter 3.

4.2. Statistical Analyses and Principal Components Analysis of the COPE Questionnaire

4.2.1. Statistical analyses

All statistical analyses were conducted using SPSS Version 16.0. Principal Components Analysis was performed for the COPE and K-10 questionnaires. The t-test and chi-square statistic were used to compare means and proportions between groups respectively. Where analyses involved more than two categorical groups, a series of ANOVAs with relevant post-hoc tests were employed. Analysis of covariance (ANCOVA) was used to control for covariates where applicable.

56 4.2.2. Principal Components Analysis of the COPE Questionnaire

Following the approach of Ingledew et al. (1996) and Litman (2006), principal components analysis (PCA) of the COPE questionnaire was performed according to the subscale scores rather than individual items.

The COPE includes five emotion-focused subscales (seeking emotional- support, positive reinterpretation, denial, turning to religion, acceptance). The “Focus and venting of emotions” is separate – considered “less useful” - and not designed to be factored together with “emotion-focused coping”. This is in comparison with the Coping Inventory for Stressful Situations (CISS) (Endler & Parker 1990) which has three subscales, among which the emotional-orientated items portray efforts to reduce stress through emotional responses, for example through self-preoccupation and fantasising, which is comparable to the COPE “focus on and venting of emotions scale”. It is important to take into account the different nosological concepts of emotion-focused coping - these will be discussed in the literature review in Chapters 6 and 7. Through PCA, it was hoped that a clear distinction of these factors would be obtained to enable further analysis in this PWD population.

Prior to performing PCA, suitability of the data for factor analysis was established through the Kaiser-Meyer-Olkin value which was 0.79, exceeding the recommended value of 0.6 (Kaiser 1970, 1974) and Bartlett’s Test of Sphericity (Bartlett 1954) reached statistical significance, supporting the factorability of the correlation matrix. Reliability was established via Cronbach’s alpha with all the subscales recording alpha values > 0.5. Principal Components Analysis of the 15 subscales revealed five factors

57 accounting for 68.5% of the variance in the scale. However only the first three factors were retained, since examination of the scree plot, following Cattell’s (1966) scree test (Figure 4.4) revealed a clear break after the third factor and parallel analysis confirmed this. These three factors explained 53.7% of the variance. Factor 1 (problem-focused coping) comprised of a combination of socially supported, self-restraint and self-sufficient problem focused subscales as described by Litman et al. (2006). Factor 2 (avoidance coping) consisted of avoidance-based strategies, while the single-subscale Factor 3 (emotional-expression coping) consisted of the focus and venting emotions items. Factor 3 will be referred to in thesis as “emotional-expression coping”, in order not to confuse it with the traditionally labeled “emotion-focused” coping factor which has more “adaptive” strategies such as social support seeking and positive reinterpretation (which have factored together with “problem-focused” strategies in this study). Table 4.2 presents the internal reliability (Cronbach’s alpha) values while the subscale factor loadings are presented in Table 4.3.

4.2.3. Principal Components Analysis (PCA) of the K-10

Prior to performing PCA, suitability of the data for factor analysis was established through the Kaiser-Meyer-Olkin value which was 0.89, exceeding the recommended value of 0.6 (Kaiser 1970, 1974) while Bartlett’s Test of Sphericity (Bartlett 1954) reached statistical significance, supporting the factorability of the correlation matrix. PCA of the K10 questionnaire responses revealed the presence of two components with eigenvalues exceeding 1, explaining 61.56% and 9.91% of the variance, respectively. Inspection of the scree plot revealed a clear break after the second component. Using Catell’s (1966) scree test (Figure 4.5), it was decided to retain two components for further investigation. Oblimin rotation

58 revealed the presence of a structure in which both components showed a number of strong loadings with all variables loading strongly on only one component, with the exception of Item 1 “in the past four weeks about how often did you feel tired out for no good reason?” which loaded strongly on both components (Table 4.4.). Depression items loaded strongly on Component 1 and anxiety items loaded strongly on Component 2. Interpretation of the two components was consistent with previous research on the K10 scale (Brooks, Beard, & Steel, 2006). Internal reliability (Cronbach’s alpha) was 0.918 for the depression scale and 0.860 for the anxiety scale.

4.3. Results

4.3.1. Demographics

A total of 274 participants aged between 23 and 84 (mean age = 57.3 [SD=13.7]) were recruited between July 2006 and July 2008. Table 4.1 shows the distribution of the participants by ethnic group, the majority (90%) being of Caucasian background. A total of 73.2% received education at 6th Form (Higher School Certficate) level or higher, with the average duration of education being 14.23 years (Figure 4.1). A total of 43.4% of the cohort were either currently married or in a de-facto relationship (Figure 4.2). Of the total cohort, 50.8% were either pensioners, retired or unemployed (Figure 4.3). One-hundred-and-forty-six (53%) were male and 68 (25%) had Type I DM. Table 4.5 compares groups based on type of DM and age which was divided into younger (59 or less years) and older (60 or more years).

59 4.3.2. Analysis of the cohort sub-populations

ƒ Diabetes type: Compared to those with T2DM, the T1DM group had an earlier age of onset (p<0.01), longer duration of living with DM (p< 0.01), higher mean extraversion scores (p< 0.01), less perceived physical disability as measured by the SF12-PCS (p < 0.01), less use of avoidance coping (Non- significant, NS) and lower rates of depression history (NS).

ƒ Age groups: The group was split into the two age groups based on the median age (59). The older group had significantly higher rates of comorbid illnesses, with 70% having two or more illnesses, but less use of avoidance coping style. Older participants had lower scores on PAID (p<0.01), SF-12PCS (p<0.01), K-10 (p<0.05), and NEO neuroticism (p<0.01), with no main effect of DM type or interaction. Younger participants had lower scores on the SF-12 MCS (p<0.01) scale implying a lower degree of emotional well-being.

ƒ Past and present depression history: Comparing groups in terms of presence or absence of current depression, those with current PHQ major depression (n = 30) were found to have significantly higher PAID (F=47, p =0.00) and K10 (F=173.4, p= 0.00) scores than nondepressed patients. PWD with a past history of depression (n = 56) had significantly higher PAID scores but did not differ in levels of K10 psychological distress. The significant effect of past depression history on PAID (DM-related distress) persisted after controlling for current (PHQ- 9) depression score (F = 4.2, p = 0.043) (ANCOVA). This will be discussed further in chapter 9.

60 ƒ Retention in study: In terms of retention status in the study, 47 (17.8%) men and 31 (11.7%) women persisted with the intervention study while 99 (37.5%) men and 87 (33.0%) women left the study before the 1st follow-up point (6 weeks). Table 4.5 reports the breakdown for the various subgroups. Factors influencing retention/attrition in the study will be discussed in Chapter 5.

4.4. Discussion

The specific groups within the PWD population who might benefit from psychosocial interventions will be considered.

4.4.1. Age-related characteristics

Younger participants were more emotionally reactive, as evidenced by their neuroticism scores. Neuroticism scores have been shown to decrease with age due to emotional mellowing, in the absence of comorbidity factors such as alcohol use and repeated episodes of depression (Jorm, et al., 2005). These authors suggest that differences in psychological distress according to age could reflect changes in emotional responsiveness or coping strategies. The SF-12 MCS which produced significantly lower scores (p<0.01) in the younger age group may be related to increased emotional responsiveness and adjustment to a chronic illness in young people. This trend is seen in higher scores on the K-10 in younger people, implying increased non-specific psychological distress in this group.

It could be beneficial to provide interventions to deal with adjustment and methods of modulating with emotional arousal and stress regulation in younger PWD. These interventions may ameliorate the risk of the onset of depression, as well as maximise coping with DM. Older people have more

61 life experience but poorer physical health, both in terms of numbers of comorbid diseases and perceived physical function. The group with at least two other physical illnesses reported high physical disability (on the SF-12 PCS). Interventions targeted at this group could be in the form of goal- setting interventions addressing the impact of living with multiple medical conditions.

4.4.2. DM-related characteristics

T2DM was much more common in the older group, this together with a later adult onset means that people with T1DM and T2DM are likely to be at very different points along their ‘illness journey’. However, people with T2DM may have had a long history of other medical illnesses, with a more recent onset of DM. Therefore the relative impact of the onset of other medical comorbidities has to be taken into consideration when discussing phases of adjustment to illnesses and how this affects coping responses.

4.4.3. Implications of physical and mental health comorbidities

It was almost the rule for those with T2DM to have other physical illnesses and this was reflected in the differences in perceived physical disability (SF- 12 PCS) scores, with significantly lower scores (p < 0.01) in the older age group.

There was a higher proportion of people with T2DM with binge eating disorder (11.2%) compared to T1DM (2.9 %), though this difference was not significant. A study of females with T2DM found that 20.9% of the participants were regular binge eaters (Kenardy, et al., 2001), with poorer weight and blood glucose control. The lack of research and interventions for binge eating disorder in DM populations was noted in Chapter 1. This 62 group of PWD would need practical interventions to address their concerns about eating, compounded with the constant need to balance their food requirements. Kenardy et al. (2002) compared the relative efficacy of group CBT and non-prescriptive therapy (NPT) on people with T2DM. The main component of NPT was focused on emotional regulation (through acceptance of negative affect) and reduction of avoidance behaviours. The authors found similar efficacy for both interventions in reducing binge-eating episodes; however the effect was only sustained in the CBT group. This study illustrates that there may be sub-populations with binge-eating disorder in DM that require a combination of emotional regulation and problem-focused interventions, the relative efficacy of which have not been studied. There is also a lack of reports on the usage of brief minimal contact interventions for binge eating disorder in DM.

People with T2DM were more likely to use avoidance as a coping style. The association of coping styles and health outcomes in this cohort will be explored further in Chapter 7. There were also higher avoidance scores in the younger age group and this may also reflect a struggle in adjusting to the diagnosis. The avoidant coping style is likely to be associated with ambivalent and dismissing attachment styles that have been investigated in the DM service setting (Ciechanowski 2004). The same author found that people with dismissing attachment styles used avoidant behaviours, for example, poor adherence and smoking. The association between past depression and current DM-related distress (PAID scores) highlights a specific DM sub-group that would need to be screened for further interventions. This will be covered in more detail in Chapter 9.

4.4.4. Screening measures

This study has utilised the PAID and K10 as screening instruments to good effect as high scores on both these measures can be used to raise an

63 alarm and warrant further assessment and intervention. This will be discussed in Chapter 10, together with a flow-chart to indicate how these instruments can be utilised in a DM service setting. The K10 is a guide to current distress and can provide a ‘first pass’ screen for anxiety and depression to indicate a need for more formal psychiatric assessment. Those who have persistently high scores may also need attention to their social context and require interventions to assist with emotional arousal.

There were other self-report measures of enduring personality characteristics that may prove useful in individualising treatment options. The NEO inventory can help predict acceptability and suitability of individuals to particular modalities of treatment. The COPE is a good indicator of preferred coping styles and interventions can aim to modify maladaptive coping styles to more adaptive ones. The COPE can be used in both a predispositional and current coping form rendering it a suitable instrument for usage to detect change in coping post-intervention. The relationship between coping and personality traits in PWD will be explored in Chapter 6.

4.5. Limitations

Participants were a select population who attended a public hospital DM service with a tendency to have more medical and psychological comorbidities than people in the general community. Overall the participants enrolled into the study were relatively in the older age groups. Although they reflected the composition of the service attendees it would be interesting to observe how these measures perform in other settings. Also participants were largely Caucasian (90%). There were a few PWD who were interested in joining the study but who had difficulties in understanding the study details and in expressing themselves due to difficulties in the

64 mastery of the English language. These participants should be targeted in future with questionnaires translated into the major languages represented by the catchment population. Participants who had a past history of depression but were unsure or vague about it were considered as not having had depression in the past, creating the possibility of false negative cases. Finally, the representativeness of the population could not be determined as there were no appropriate data on those who declined participation.

4.6. Conclusion

The heterogeneity of this chronic illness population means that their needs are likely to be diverse. This chapter has used ‘real life’ variables to identify specific PWD sub-groups by individual, demographic and illness characteristics each of which would have to be considered separately when designing psychosocial interventions, particularly brief psychosocial interventions. The specific features determining the suitability of brief psychosocial interventions for these sub-populations will be discussed in the forthcoming chapters.

Table 4.1: Distribution by Ethnic Group

Ethnic Group N % Caucasian 248 90.51% East Asian 7 2.56% South Asian 6 2.19% Indigenous Australian 1 0.36% Middle-Eastern 1 0.36% South American/Hispanic 1 0.36% Pacific Islander 4 1.46% Jewish 6 2.19%

65 Figure 4.1: Bar-Chart showing distribution of Participants by Educational level

Figure 4.2: Distribution of Participants according to Marital Status

66 Figure 4.3: Distribution of Participants according to Occupational Status

67 Table 4.2: COPE Subscales: Internal Reliability

COPE Subscale Cronbach’s Alpha Active Coping 0.751 Planning 0.829 Suppression of Competing Activities 0.521 Restraint Coping 0.692 Instrumental Social Support 0.835 Emotional Social Support 0.890 Positive Reinterpretation 0.805 Acceptance 0.726 Religion 0.946 Focus on and Venting of Emotions 0.798 Denial 0.646 Behavioural Disengagement 0.762 Mental Disengagement 0.546 Substance Use 0.943 Use of Humour 0.890

68 Table 4.3: COPE Subscales: Component Matrix factor loadings after Principal Components Analysis

I II III IV V Planning 0.854 -0.218 -0.072 0.075 0.152 Active 0.815 -0.243 -0.076 0.056 0.151 Instrumental 0.765 -0.174 0.339 -0.100 -0.065 social Positive 0.745 -0.009 -0.268 0.095 -0.249 reinterpretation Suppression 0.707 0.073 0.022 -0.070 0.214 Emotional 0.653 -0.102 0.546 -0.168 -0.115 social supp Acceptance 0.601 0.183 -0.495 -0.036 -0.005 Restraint 0.509 0.214 -0.398 0.167 0.322 Humour 0.326 0.213 -0.215 -0.528 -0.590 Behavioural -0.093 0.811 0.019 0.102 0.002 disengagement Denial -0.031 0.713 0.040 0.121 -0.065 Mental 0.276 0.644 -0.004 -0.076 -0.176 disengagement Focus 0.354 0.321 0.660 0.026 0.040 emotions Religion 0.257 0.171 0.121 0.788 -0.184 Substance 0.031 0.449 0.055 -0.399 0.588

69 Figure 4.4: Scree plot for the COPE questionnaire after PCA

70 Table 4.4: Oblimin rotated factor structure, loadings and correlations for K10 scores

Factor Loadings Correlations between variables Component 1 Component 2 Component 1 Component 2 (depression) (anxiety) (depression) (anxiety) Worthless .981 .904 .531 Hopeless .977 .914 .549 Sad .831 .896 .646 Depressed .764 .871 .667 Effort .638 .787 .647 Tired no reason .401 .347 .630 .611 Hyper restless .950 .525 .883 Restless .811 .586 .844 Hyper nervous .782 .544 .800 Nervous .691 .613 .795

71 Figure 4.5: Scree plot for the K-10 questionnaire after Principal Components Analysis

72 Table 4.5: Comparison of the 274 study participants by DM type and current age

Type 1 overall Type 2 overall Age 59 or less Age 60+ Gender: male (%) 38.8% 63.1% 55.5% 56.5% Age; mean (SD) 46.9 (14.3)** 60.57 (11.3) 47.0 (9.9)** 68.6 (6.1) Age of onset of 23.9 (13.7)** 52.3 (13.0) 33.5 (15.3)** 55.3 (14.3) diabetes; mean (SD) Duration of 23.8 (13.9)** 10.1 (8.3) 14.5 (11.3) 13.5 (12.4) diabetes; mean (SD) Comorbid None: 24(36%) None: 20 (11%) None:37(28%) None: medical illness; One: 18(27%) One: 36 (20%) One: 37(28%) 9(7.4%)

N (%) 2-3: 12(18%) 2: 84 (46%) 2-3: 37(28%) One: Comment [a6]: Some have decimal places, some not 4+: 8(12%) 4+: 24 (13%) 4+: 12(9%) 17(14%) 2-3: 65(53.7%) 4+:

21(17.4%) Comment [JR7]: Check percentages HbA1c; 8.2 (1.5)* 7.7 (1.7) 7.9 (1.7) 7.6 (1.6) mean(SD)

73 Table 4.5 (cont’d) PSYCHIATRIC DIAGNOSES; N (%)

Type 1 overall Type 2 overall Age 59 or less Age 60+ No PHQ 43 (64%) 101 (55.8%) 80 (60%) 71 (59%) psychiatric diagnosis PHQ 8 (11.9%) 21 (11.6%) 19 (13.9%) 11 (9.1%) Major Depressive Disorder PHQ Other 4 (6%) 13 (7.2%) 8 (5.8%) 9 (7.3%) Depressive or anxiety Disorder PHQ 6(9%) 15 (8.3%) 14 (10.2%) 7 (5.8%) Somatoform Disorder PHQ Panic 4 (6%) 12 (6.6%) 9 (6.6%) 7 (5.8%) Disorder PHQ Other 2 (3%) 12 (6.6%) 11 (8.0%) 4 (3.3%) Anxiety Disorder PHQ Bulimia 0 (0%) 2 (1.1%) 2 (1.5%) 0 (0%) Nervosa PHQ Binge 2 (3%) 21 (11.6%) 12 (8.8%) 12 (10.0)% Eating Disorder Past 11(16.4%) 45(24.8%) 30 (21.9%) 26 (21.7%) Depressive disorder

74 SELF REPORT MEASURES; Mean (SD)

Type 1 overall Type 2 overall Age 59 or less Age 60+ PHQ-9 5.4 (5.1) 6.22 (5.7) 6.6 (5.9) 5.1 (5.1) K-10 16.6 (6.6) 17.5 (7.5) 18.2 (7.5)* 15.9 (7.1) NEO 34.4 (9.0) 32.8 (9.3) 35.5 (9.3)** 30.4 (8.0) neuroticism NEO 41.1 (5.6)** 37.9 (6.6) 38.9 (7.0) 38.6 (5.2) extraversion NEO 40.7 (7.2) 40.0 (5.9) 40.1 (6.3) 39.7 (6.3) openness SF-12 MCS 48.0 (9.9) 48.4 (11.6) 45.7 (11.6)** 51.2 (9.7) (mental) SF-12 PCS 48.0 (9.4)** 40.7 (10.4) 44.9 (9.9)** 39.7 (11.1) (physical) PAID 26.6 (23.5) 27.5 (23.4) 31.6 (23.2)** 20.3 (21.6) COPE Problem 92.3 (18.0) 91.8 (18.0) 93.4 (16.8) 89.3 (19.0) solving COPE 9.7 (3.5) 9.2 (3.0) 10.0 (3.1)** 8.4 (3.0) Emotional Expression COPE 20.4 (4.7) 22.1 (6.0) 22.6 (5.9)** 20.0 (5.1) Avoidance Participation in study at 6 weeks; N (%) Completed 20 (8.1%) 51 (20.6%) 38 (13.9%) 40 (14.6%) Dropped Out 47 (19.0%) 130 (52.4%) 99 (36.1%) 97 (35.4%) * p <0.05 ** p <0.01

75 TABLE 4.6: Outcome instruments and COPE scores according to current and past depression history status

Current PHQ major Past History of depression depression status status Questionnaires; Currently Not currently Positive past No past Mean (SD) depressed depressed depression history history PAID 52.2 (27.2)** 23.0 (20.3) 39.0 (26.3)** 21.6 (19.5) K10 30.6 (8.0)** 15.4 (5.1) 21.6 (7.4)**# 15.9 (6.9) PHQ9 17.8 (3.8)** 4.5 (3.8) 9.5 (6.2)**# 4.8 (4.9) SF12 MCS 35.7 (12.6) ** 50.0 (9.8) 41.1 (11.6)** 50.4 (10.0) SF12 PCS 36.4 (8.9)** 43.1 (10.8) 40.9 (1100) 43.0 (10.8) COPE Problem 89.4 (16.9) 91.7 (18.2) 90.7 (16.8) 91.4 Solving (18.5) COPE Emotion 10.4 (3.0) 9.0 (3.2) 10.3 (3.4)**# 8.9 (3.0) Expression COPE Avoidance 26.5 (5.5)** 20.7 (5.4) 24.5 (6.1)** 20.6 (5.2) *p < 0.05, ** p < 0.01 # not significant after controlling for PHQ9 scores (current depression)

76 CHAPTER 5: PREDICTORS OF ATTRITION AMONGST PARTICIPANTS OF A PSYCHOLOGICAL INTERVENTION TRIAL IN DIABETES MELLITUS

ABSTRACT

Introduction: Participant attrition is a widely reported problem in longitudinal intervention trials. Objectives: This chapter compares the profiles of participants who completed the first phase with those who dropped-out of a study trialing minimal contact psychological interventions in a population of people with T1DM and T2DM. Methodology: Participants were randomised to one of three groups; receiving either emotional-regulation (EF) or problem-focused (PF) interventions or to a control group. The latter were given mood-monitoring charts and were wait-listed to receive an intervention of their choice at 12 weeks. Results: A total of 274 participants attending two general hospital DM clinics were enrolled into the study. At the first follow-up point (6 weeks), only 79 participants remained in the study. Those who persisted were more likely to have lower Problem Areas in Diabetes (PAID) scores (p < 0.05). PAID score (p < 0.05) and emotion-regulation intervention group (p < 0.05) significantly predicted dropping out of the study. Conclusion: This chapter highlights the benefits of studying individual, illness and psychological variables that motivate people to persist in psychological intervention studies. Knowledge of individual factors contributing to adherence to psychological intervention trials can help enhance retention rates in future trials.

77 5.1. Introduction

Participant attrition in longitudinal intervention trials is a major problem encountered by researchers. In order to ensure adequate study power and generalisability of findings, maximal retention of participants throughout the duration of longitudinal studies is vital. Attrition rates in longitudinal studies vary from 15% to 70% as reported by Moser et al. (2000). These authors who reported on factors contributing to study attrition stressed the importance of identifying these reasons to aid the design of future studies.

Generally, the focus of the literature on attrition in longitudinal research has been on study methodology, particularly recruitment and retention strategies ((Dobscha, et al., 2005), (Gallagher-Thompson, et al., 2004), (Lyons, et al., 2004), (Davis, et al., 2002), (Stasiewicz & Stalker 1999), and investigator factors (Cassidy 2001). Retention strategies are well discussed in a review by Davis et al. (2002) who have suggested nine strategies to enhance retention rates. This review and the work of other authors have suggested that the use of multiple retention strategies is the most effective means of achieving higher retention rates (Carroll 1997), (Robinson 2007), (Davis, et al., 2002). Reports of strategies taken to improve retention rates throughout the course of the study include offering participants incentives (Bull 2008), altering study methods, particularly related to contacting patients, and offering participants more explanation regarding the research. Bull (2008) studied Human Immunodeficiency Virus (HIV) patients in an internet-based prevention trial and found that a combination of automated and personalized techniques were helpful for promotion and retention. There is thus growing evidence for the usage of incentives to improve retention rates in the literature.

78 There is a relative lack however, of studies reporting on participant factors influencing retention, such as those by Siddiqui et al. (1996) and Moser et al. (2000). Although demographic factors have been reported, measurement of individual characteristics, for instance personality traits is not usually performed. Psychological factors however deserve consideration as they have been found to be more compelling than demographic factors in predicting dropouts, as for example, in a longitudinal study on an intervention in parents and caretakers of infants at risk of cardiopulmonary arrest by Moser et al. (2000). Another longitudinal study on smoking prevention by Siddiqui et al. (1996) found demographic differences between dropouts and those who were adherent to the intervention. The authors emphasise the value of studying the differences between dropouts and completers, suggesting that this information can be used for design of future trials.

Several authors have highlighted the justification for publishing retention and attrition data. An editorial by Froelicher (2002) noted an article by Toobert (2002), which was initially not favoured for publication by the editors of that particular journal. The reviewer (Froelicher 2002) defended the article, which provided recruitment and retention data on a lifestyle improvement program among women with T2DM (Toobert 2002). The reviewer also stated that it is scientifically important for researchers to understand factors determining retention in intervention trials; particularly how to improve on study methodology for future trials. Furthermore, Prinz (2001) recommends that recruitment and retention are critical facets of prevention research stating, “the field could benefit from research studies aimed at testing strategies to enhance recruitment and retention, as well as studies about the factors that influence participation”. There are grounds therefore for researchers conducting trials to report on factors influencing retention or attrition in studies with significant attrition rates.

79 The aim of this chapter is to describe issues related to participant retention and attrition in “The Stress Sampler”, a minimal-contact psychological intervention trial for patients with T1 and T2DM. The study was designed as a minimal-contact intervention in order to resemble normal clinical practice as much as possible. Furthermore, by minimising the exclusion criteria, the objective was to recruit a diverse group of PWD, an effectiveness trial, thus ensuring that the benefits of the interventions were made available to a wide patient base. A key aim of the study was to assess which stress-reduction strategies were most effective and acceptable for various profiles of patients, with particular emphasis on highly stress-reactive PWD sub-populations that have been described in the previous chapters. Given that DM is a chronic and fairly time- consuming condition, brief interventions, which were time efficient and self- directed, were designed, allowing participants to fit the strategies in a way that best suited their personal schedule and lifestyle demands. Such self- directive interventions allow the patient to take control of their own health issues. However, despite this minimal contact, self-directed approach, there was substantial participant attrition.

Problems of attrition are not uncommon in DM populations. Gucciardi et al. (2007) reported on factors influencing attrition in a self-management education program for people with T2DM. They found withdrawal rates of almost 50 per cent. Although the study was a retrospective case-notes study on a service-based program for newly diagnosed patients rather than an interventional trial, some insights can be drawn from that report. The authors highlight the need to study factors influencing retention and how to improve rates in DM self-management programs, especially in view of the chronic and demanding nature of the condition.

To my knowledge, there are no studies reporting the relationship of retention rates with a wide-range of participant variables such as

80 personality traits, coping styles, psychological and physical morbidity, in a study on a population with a chronic condition.

The hypothesis is that PWD who stand to benefit more from the intervention (higher psychological and physical morbidity and less adaptive coping styles (avoidance and emotional-regulation coping)) would be more likely to persist with the study.

5.2. Methodology

The detailed methodology of this study has been described in Chapter 3. An account of the follow-up method of participants follows. After randomisation and an interview by the author, the participants were asked to indicate on the demographic data sheet (see Appendix C) their preferred method of contact, (e-mail, telephone etc.). The benefits of the study and the intention to include all PWD were emphasised. This was done to avoid the participants thinking that they had been earmarked for the study due to individual or illness circumstances. A follow-up phone call or e-mail within a week of recruitment was performed to ensure proper understanding of the interventions and to entertain questions (as described by Aaronson et al. 1996).

The research team established a clear system of follow-up and designed follow-up assessments of minimal contact. At 6 weeks, the assigned research assistant reminded the participants through a phone call to send the completed questionnaires (found in Appendix E), which were mailed out a week before the scheduled date. The participants were also encouraged to fill-in the relevant intervention sheets and mood charts (see Appendix G and Appendix H), and mail them back to the team at relevant study points (6 weeks and 3 months). This strategy was implemented to provide

81 evidence of compliance with the interventions. Inability to contact individual participants through telephone calls or e-mail was followed by mailing out of reminders.

5.3. Statistics

SPSS version 16.0 was used. Chi-square test was used to compare proportions between the group of participants that dropped out and those who stayed on at 6 weeks. To study the predictive value of intervention group on retention/attrition, logistic regression analysis was performed with the outcome being staying on or dropping out of the study. The significance level was set at 0.05 for all tests.

5.4. Results

A total of 276 participants were recruited (see Figure 5.1). It proved impractical to obtain data on refusers, however approximately 60% of those approached agreed to participate in the study. The research assistants involved reported that those who refused were more likely to be young or middle-aged males. The primary reasons for refusal varied approximately equally between (i) those that thought they were already “involved with too many people at the clinic”, (ii) those who were in a rush to go to work or other commitments and (iii) those who did not think they were “stressed” or that the intervention study would be useful.

Two participants were excluded, one due to active psychosis (delusions) and another to voluntary withdrawal soon after recruitment. The remaining 274 participants were randomised to one of three groups shown on the chart. The characteristics that differentiate the 79 participants that

82 persisted up to the 6-week mark, with the 195 participants who dropped out are described here.

83 Figure 5.1: Flow-chart of participants through the first 6 weeks of the study

84 5.4.1. General comparisons of variables of interest between drop-outs and completers

Table 5.1 compares demographic data and outcome measure scores for participants who dropped against those who persisted with the study. Of the outcome measures, only PAID score was significant (p < 0.05). There were also differences among neuroticism scores (p = 0.063) and emotional- expression coping (p = 0.076), though these were not significant. There was a higher proportion of retention at 6 weeks among participants in the control group, whilst those in the emotional-regulation intervention group were more likely to drop-out (p = 0.053). It is also worth noting the tendency of participants with greater medical comorbidity to persist with the study, though the proportions were not significant.

5.4.2. Logistic regression analysis with intervention group as predictor variable and retention status as outcome variable

Direct logistic regression was performed to assess the impact of intervention group on retention in the study. The model contained the sole independent variable intervention group with three categories, problem- focused intervention, emotional-regulation intervention and control group as the default comparator category. The three intervention group categories were dummy coded to reflect the control intervention group as the reference group. The model as a whole was not statistically significant, x2 (2, N = 274) = 5.90, p = 0.052, however, the emotional-regulation intervention category as predictor of attrition was statistically significant (p < 0.05). The model as a whole correctly explained between 2.2% and 3.2 % of the variance in completing the first 6 weeks of the trial.

85 Table 5.1: Comparison of proportions or mean scores of variables of interest for study completers versus dropouts

Whole Drop-Outs Phase 1 Probability Group (n = 195) (n=79) (n = 274) Completers Gender 53.1% male 50.0% Male 60.8% male #NS

Age (years); 57.3 (13.65) 57.2 (13.99) 57.4 (13.0) NS mean (SD)

DM Type 65.8 % 65.8% T2DM 65.8% T2DM NS T2DM Duration of illness (years); 13.8 (11.74) 14.28 (11.81) 12.61 (11.56) P = 0.353 mean (SD) Intervention Groups 32.0% PF 32.1% PF 31.6% PF, P = 0.053 32.4% EF 35.7% EF 24.1% EF, 31.6 27.0% control 43.0% control %control Avoidance Coping; 21.37 (5.68) 21.56 (5.8) 21.1 (5.56) NS mean (SD) Problem Coping; 91.4 (18.01) 91.8(18.1) 90.9(18.03) NS mean (SD) Emotional-Expression 9.2 (3.18) 9.5 (3.30) 8.7 (2.93) P = 0.076 Coping; mean (SD) Past Depression; N (%) 56 (20.4%) 44 (22.56%) 12 (15.19%) NS Current PHQ Depressive 47 (17.15%) 38 (19.49%) 9 (11.4%) NS Disorder; N (%) PHQ Anxiety Disorder; 31 (11.31%) 25 (12.82%) 6 (7.6%) NS N(%)

86 PHQ Somatisation; 21 (7.7%) 15 (7.7%) 6 (7.6%) NS N (%) PHQ Eating Disorder; 26 (9.5%) 20 (10.3%) 6 (7.6%) NS N (%)

PHQ9_Baseline; 5.87 (5.6) 6.2 (5.7) 5.1 (5.3) NS mean (SD) K10_Baseline; 17.2 (7.4) 17.5 (7.6) 16.5 (7.0 NS mean (SD) PAID Baseline; 26.3 (23.1) 29.2 (24.57) 22.6* (20.3) P = 0.047 mean (SD) SF_12_MCS_Baseline 48.4 (11.1) 48.7 (10.94) 47.7 (11.5) NS mean (SD) SF_12_PCS_Baselinemea 42.4 (10.8) 42.9 (10.56) 41.3 (11.3) NS n (SD) NEO Neuroticism; 33.10 (9.1) 34.06 (9.18) 31.7 (8.8) P = 0.063 mean (SD) NEO Extraversion; 38.73 (6.3) 38.8 (5.85) 38.6 (6.9) NS mean (SD) Current Medical Illness; N NS (%) None 46 (16.8%) 30 (15.38%) 16 (20.3%) 1 55 (20.1%) 44 (22.56%) 11 (13.9%) 2 63 (23.0%) 43 (22.1%) 20 (25.3%) 3 41 (15.0%) 31 (15.9%) 10 (12.7%) 4 or more 34 (12.4%) 21 (10.9%) 13 (16.5%) HbA1c %; mean (SD) 7.8 (1.6) 7.8 (1.6) 7.64 (1.6) NS

#NS = Not Significant

Table 5.2: Logistic Regression with Intervention Group as Independent Variable and Retention Status as Dependent Variable

87 B S.E. Wald df Sig. Exp(B) 95 % CI for Exp (B) Lower Upper EF and 0.432 0.324 1.781 1 0.182 1.540 0.817 2.904 PF vs. Control (EF vs. 0.812 0.340 5.691 1 0.017 2.251 1.156 4.386 PF) Constant 0.907 0.138 43.136 1 0.000 2.477

EF: Emotion-focused Intervention Group PF: Problem-focused Intervention Group

5.5. Discussion

This study was designed to be naturalistic, with the intention that PWD with high levels of emotional distress would benefit from the interventions. However, the study revealed a tendency towards discontinuation from the trial amongst individuals with high levels of psychological distress. This is contrary to the hypothesis that people who were most emotionally troubled by their DM would find the interventions useful and persist with the study. PWD with high levels of DM-specific distress (high PAID scores) may thus prefer practical interventions targeted at the DM-care aspects of their daily lives rather than generic stress management interventions. There may have been a higher adherence rate if the interventions were integrated into their routine DM treatment. For instance the goal-setting exercise could have been administered by a dietitian to an individual whose eating habits were of utmost concern to the treating team. In a naturalistic psychosocial

88 intervention study in cancer patients, Gilbar et al. (2002), reported that among the 68% who dropped out, depression was the only significant predictor of retention, with those more severely depressed more likely to persist. Thus, there are possibly factors influencing depressed subjects to persist in an intervention offered by familiar clinicians, as compared to this study which was conducted by a team of researchers not familiar to the participants.

PWD who have a higher likelihood of venting their emotions (predominant usage of emotional-expression coping) during stressful situations may prefer having more face-to-face contact with a therapist and therefore may not have taken to the interventions in this study. Similarly, the higher attrition rates amongst participants randomised to the emotional-regulation intervention group may also indicate that the PWD in this trial may have preferred that the particular interventions were facilitated face-to-face by a therapist rather than through a minimal contact approach, thus contributing to lower persistence with the trial.

The need to modulate hyperarousal associated with neuroticism could be a factor that precludes individuals with high trait neuroticism scores from persisting with an intervention that lasts for weeks, as observed in this study. This group may benefit from immediate reassurance and an avenue to discuss their worries, which the minimal contact with researchers did not allow.

Those with higher medical comorbidity had higher adherence rates, though this was not significant. While the interventions were not specifically designed as a means to improve coping with physical illnesses, those with multiple medical problems may have found the exercises beneficial. Older cohort members were generally less psychologically distressed than younger participants (see Chapter 4) but had concerns about their medical

89 comorbidities. These concerns may have been better targeted by interventions designed to target specific issues related directly to the medical comorbidities or the emotions related to them.

A study identifying the needs of this population is warranted before any conclusion can be drawn about the acceptability of minimal contact interventions. The comparatively higher retention rates for participants in the control ‘mood monitoring’ group suggest that this may have been an effective minimal contact exercise in itself. A trial by Boyd et al. (1992) on dietary fat reduction in women also found that participants in the intervention group were more likely to drop out than participants in the control group. In a study investigating the psychosocial impact of cardiopulmonary resuscitation training among parents and caretakers of infants at risk of cardiopulmonary arrest, Moser et al. (2000) found that dropouts were more likely to be in the intervention group and to have higher levels of psychological distress. These findings provide some evidence that there are factors working within control groups that prompt participants to persist with the intervention. According to Davis et al. (2000), a control group treatment that is appealing to participants may enhance retention.

In addition to general participant characteristics, it is likely that methodological factors influenced the attrition rate of the current study. Recruitment methods have the potential to influence retention. The diabetes clinic was considered the most suitable setting to recruit because patients were accessible and had some time while waiting to fill in self- report measures and ask questions of the research team. Furthermore, medical records were available; there were clinic rooms available to conduct a screening clinical interview by the author and one other psychiatrist and the diabetes clinicians were available if required.

90 This study aimed to include the broad range of mental health problems seen in a diabetes service and did not use the “if in doubt, screen out” method proposed by Shumaker et al. (2000) for traditional RCTs. However, this “over-inclusiveness” could have contributed to the high attrition rates in this study, in that a significant proportion of the cohort may not have considered themselves as candidates for stress management interventions. However if the study had only targeted individuals with significant psychological distress, it would have missed out cohort members with lower distress levels who eventually demonstrated compliance and this approach would have been against the philosophy of this study (i.e., to provide all PWD with access to psychosocial interventions).

Evidence suggests that people avoid negatively framed information (Baumeister, et al., 2001). As the cohort members were not necessarily emotionally stressed, it is possible that the emphasis on stress and depression in the participant information sheets and questionnaires was unattractive to some potential participants. This may have deterred them from persisting with the study, as they did not believe they required such help. There was some anecdotal evidence, gleaned through verbal feedback from participants, to support this. In retrospect, information about the potential benefits of the study could have been framed more clearly, though it was stressed by the investigators at the beginning of the study that all PWD could benefit from some aspect.

When considering the desired total number of participant follow-up attempts, the issue of trying to maintain a naturalistic stance on the study comes into question. Persistence of follow-up and coercion may bias the actual effectiveness and compliance of the interventions. Adhering to set guidelines on how many attempts to contact errant participants is a wise approach. This will also minimise “passive withdrawal” (Davis, et al., 2000) by participants who simply fail to return calls for various reasons such as

91 busy schedules, but who may actually be practicing the interventions. This cohort needs to be differentiated from people who really do not want to continue the intervention. A review of the existing literature demonstrates that intervention trials are varied in terms of methodology appropriate to the research questions. A naturalistic trial to mirror regular clinical practice as far as possible is likely to face the challenge of attrition as not all potential participants will be ready to sign up or use the interventions.

There has been recent research interest on studies employing patient preference trials (McPherson, et al., 2008) where potential participants are given the opportunity to partake in their preferred choice of intervention. Patient preference trials can compare intervention group/s offering the preferred intervention with a fixed ‘no choice’ intervention or wait-list control group and it has been suggested (Shumaker, et al., 2000) that in such studies, patients should be asked about their preferences regarding any particular intervention group before randomisation. There is a lack of research however focusing on the needs and personal preferences of PWD regarding psychosocial interventions (Delamater, et al., 2001). Patient preference is increasingly seen as a strategy with the potential to encourage participation in psychosocial interventions and has been recommended as part of future research on psychosocial interventions in DM (Winkley, et al., 2006). Research and real world clinical practice should allow participants to choose their options from a range of intervention strategies or what worked best for them (Steed, et al., 2003). Perhaps the most effective method of identifying individual needs is to offer patients an array of interventions from which to choose.

The overall method of dissemination of the interventions in this study could have influenced retention rates by itself. Willemse et al. (2004) in their study on minimal contact psychotherapy for subthreshold depression in primary care practice obtained a 60% attrition rate amongst participants

92 randomised to the minimal contact group. The authors found that older people and those with more years of education were more likely to complete the 12-month interview, whereas men and those with worse mental health were less likely to do so. It remains to be seen if minimal contact interventions enhance participation generally, or only to specific targeted groups, a conclusion that can only be considered if a similar trial to that used here is repeated for PWD through a different method of delivery, for instance a guided approach incorporating face-to-face sessions.

As described by Ciechanowski et al. (2006), attachment styles have the potential to influence compliance with interventions. These authors found that PWD with dismissing attachments styles had a greater number of missed appointments compared to those with secure styles. The role of motivational interviewing in addressing PWD with attachment styles has been noted in Chapter 2.

Integrating the interventions into routine clinical management and involving DM team clinicians would be an effective strategy considering the level of engagement of PWD with the DM service. Offering participants incentives, as documented by other researchers is a positive move, as long as ethical considerations are adhered to. A limitation of this study is that demographic data were not obtained from PWD who had declined participation. As such, it is not clear if the study population is representative of the general DM population attending the clinics.

5.7. Conclusion

While psychosocial interventions as part of routine care are strongly recommended for PWD, specific groups within the diabetes service may

93 have different preferences both in terms of the content and delivery of interventions. It is for this reason that these findings are reported in this chapter, with the hope that future trials could adopt some of the learning points gleaned from this exercise to ensure maximal participant adherence and satisfaction, while maintaining a naturalistic effectiveness stance. It is not just about incentives, persistence and retention strategies; consumer wishes and needs should be taken into consideration too. A routine brief intervention program would have to be tested for feasibility to suit individual needs AND preferences prior to implementation.

94 CHAPTER 6: Coping Styles, Personality Factors and the Serotonin Transporter Genotype in Patients with Diabetes Mellitus

ABSTRACT

Background: For patients with chronic health conditions such as Diabetes Mellitus (DM), effective coping skills are crucial and may influence mental and physical health outcomes. However, much coping research within this population has been outcome-based, with little consideration of predisposing factors which might shape individual preference for certain coping styles. Both personality factors and a polymorphism in the serotonin transporter genotype (5HTTLPR 6CLA4) have been shown to influence coping in healthy populations, and their effect on coping in people with diabetes requires consideration. Aim: This study aims to identify the association of personality traits and the serotonin transporter genotype polymorphism (5HTTLPR 6CLA4) on coping patterns in a sample of patients with T1DM or T2DM. Method: The 60-item COPE inventory and NEO-FFI personality inventory were administered to 178 patients with DM (49 T1DM and 129 T2DM). Serotonin transporter genotype (s/s, s/l and l/l) was determined by cheek- swab analysis. Results: Principal components analysis of the COPE revealed 3 factors reflecting 3 main coping styles: (i) problem-focused coping (ii) emotional- expression coping and (iii) avoidant coping. The effect of genotype and personality on each factor was assessed via regression analyses. Genotype was not significantly related to any of the three coping factors. The five personality factors of the NEO-FFI were differentially associated 95 with the three coping factors, with neuroticism and extraversion being most consistently and significantly related. Conclusion: This sample of PWD used a variety of coping styles to manage the demands of their chronic condition. These coping factors were strongly related to personality factors, but not associated with genotype. Knowledge of the ways in which personality factors effect choice of coping styles may be used to identify those patients with a tendency toward maladaptive forms of coping, and create interventions which would best meet their needs.

6.1. Introduction

Coping is defined as the variety of cognitive and behavioral strategies individuals use to manage stress (Folkman & Moskowitz, 2004). Conventional classification categorised dispositional coping into problem- focused and emotion-focused types (Folkman & Lazarus 1980, 1985). Problem-focused coping involves attempts to address the source of stress, such as seeking information or making an action plan, while emotion- focused coping describes efforts to manage the negative thoughts and feelings associated with the stressor, such as seeking out social support or venting of feelings. While the distinction between emotion-focused and problem-focused coping is useful and has been widely adopted, some research has suggested that it is too simplistic and does not acknowledge the range of coping strategies which an individual may use in times of stress.

Problem and emotion-focused coping strategies often load on the same factor during analysis, as reported in the Principal Components Analysis of the COPE in this study in Chapter 4, suggesting that they are not as distinct as theory suggests. In particular, Tennen et al. (2000) demonstrated that, 96 when under stress, individuals may use multiple coping strategies of both types. In response to this, more recent research (Litman, 2006) has begun to suggest that the self-sufficient versus socially-supported division of coping styles may be more informative. This distinction encompasses the context in which coping strategies are applied, wherein self-sufficient coping strategies are undertaken individually, while socially-supported coping strategies involve turning to others for advice or sympathy. Furthermore, the complexity of coping styles have also led to the definition and testing of additional coping factors, including avoidance and substance abuse, religious and humorous coping (Carver, et al., 1989), (Moos & Holahan, 2003), (Roth & Cohen, 1986).

Austenfeld & Stanton (2004) have provided a critique on the problem focused- emotion focused dichotomy and argued for the role of emotion- focused coping strategies in the successful negotiation of stressors, taking into consideration the environment and specific stressor involved. Whilst exploring the adaptive potential of emotional-approach coping in the context of several types of health-related stressors, they challenge the “bad reputation” of emotion-focused coping stating that items in most coping questionnaires are “confounded with distress and self-deprecation.” They opine further that some studies had combined items designed to tap emotion-focused coping with those of expressions of emotional distress & self-deprecation (Stanton, et al., 1994). These authors suggest that researchers make a clear distinction between emotion-approach coping and other coping strategies often included in “emotion-focused” scales that contain items confounded with distress or self-deprecation.

While some strategies may intuitively seem better than others, the utility of any coping strategy is likely to depend on the nature of the stressor and individual factors (Girgus & Nolen-Hoeksema, 2006; Snyder, et al., 1999). A range of primary factors influences an individual’s predisposition to certain 97 types of coping, and how beneficial these coping styles are for them. Somerfield & McCrae (2000) note that the study of individual differences in coping has not received adequate coverage in the coping literature. One variable of particular interest is personality style. In the early 1990s, emerging consensus from more than three decades of research led to the development of the NEO five factor concept of personality (McCrae, 1991), which comprised neuroticism, extraversion, conscientiousness, agreeableness, and openness to experience. In the ensuing years this five-factor personality concept, as measured by the NEO-PI and NEO-FFI, which is a shorter version, has been widely applied to research involving coping in both healthy and clinical populations.

There is evidence to suggest that individual NEO personality traits influence coping strategies. Generally studies have found a positive association between high neuroticism levels and avoidant coping (Endler & Parker 1990, Watson & Hubbard 1996, Lee-Baggley, et al., 2005) and emotion focused coping (Penley & Tomaka 2002), and a negative correlation between neuroticism and problem-focused coping (Watson & Hubbard 1996). There have been mixed reports on the association between extraversion and coping strategies. A few earlier studies have reported a positive relationship between extraversion and social-support based coping (Rim 1986, Amirkhan 1995), but more recent studies (O’Brien & De Longis 1996, David & Suls 1999 and Lee-Baggley, et al., 2005) found no significant relationship. Conscientiousness has been shown to have a strong positive relationship to active, problem-focused coping responses (O’Brien & De Longis 1996, Watson & Hubbard 1996, Penley & Tomaka 2002). Finally, openness and agreeableness are generally unrelated or only modestly related to coping strategies. However, when considering these findings, it is important to note that there may be some inconsistency in the relationships between personality traits and coping styles, depending

98 on the nature of the populations and stressors studied, as described by Penley and Tomaka (2002).

The role of personality factors in influencing coping in PWD has received little attention and deserves consideration, as the daily management of DM is a source of chronic stress for this population (Rubin & Peyrot 2001, Hermanns, et al., 2006) resulting in a greater need for effective coping skills. A review of the literature revealed several studies (Bosworth, et al., 2001; Chochinov, et al., 2006; Knoll, et al.,, 2005) addressing the impact of specific medically associated stressors (including cardiac cathetherisation, cataract surgery and terminal cancer) on coping in specific personality subtypes. Just as in the literature on general populations, neuroticism and extraversion were the personality traits most consistently linked with coping with illness and medically related stressors. In view of this, there may be considerable benefit in identifying vulnerable PWD sub-populations who are most likely to turn to maladaptive coping strategies in times of stress.

Personality factors are not the only overarching dimensions that shape coping responses. Biological factors, in particular genetic factors, are believed to influence an individual’s preference for particular coping styles in times of stress. In recent years, research has begun to identify genetic factors, which can manifest in predispositions to certain ways of coping, leading to greater risk of psychological morbidity. Kozak et al. (2005) found that each of problem-focused, emotion-focused and avoidance-focused coping (social diversion and distraction) styles demonstrated evidence of genetic variance, and recommended the need to study relationships between personality styles and coping. The heritability of coping styles has also been described by Jang et al. (2007), who found that problem-focused and emotion-focused coping styles including social-support seeking were modestly heritable, unlike distraction-focused styles. The author speculates that coping may be an endophenotype of the polymorphism in the serotonin

99 transporter gene (5HTTLPR), particularly strategies used by highly stress- reactive individuals.

The serotonin transporter gene is of particular interest, as it is known to affect emotional regulation (Canli & Lesch, 2007; Szily, et al., 2008) and has been linked to onset of depressive disorders upon exposure to a series of adverse life events (Caspi, et al., 2003, Kendler, et al., 2005, Wilhelm, et al., 2006). The transporter genotype polymorphism consists of two alleles (‘s’ short and ‘l’ long) with the ‘s’ allele associated with less effective serotonin transporter transcription. Szily et al. (2008) found that ‘s’ allele carriers experience negative emotions more intensely and feel unable to cope with such emotions. The authors speculate that ‘s’ allele individuals may experience negative events differently from those with the ‘l’ allele, citing neural mechanisms such as the cingulate cortex-amygdala circuit described by Pezawas et al. (2005) and Kalisch et al. (2006) as possible pathways.

More recent research has demonstrated an association between the serotonin transporter polymorphism (5HTTLPR) and the coping styles that individuals adopt in times of stress. Wilhelm et al. (2007) found that those with two ‘l’ alleles used relatively more problem-focused strategies and reported more benefit from them. They speculated that higher levels of emotional reactivity to stress among ‘s’ allele carriers may lead them to perceive adverse life events as more overwhelming and uncontrollable than those with the ‘l’ allele. Thus they are less likely to employ problem- focused coping as their emotional reactions inhibit them from employing these strategies productively. This hypothesis raises the possibility that ‘s’ allele carriers may first need to reduce their emotional reactivity through coping styles such as mindfulness or relaxation, before being introduced to problem-focused strategies. The study by Wilhelm et al. (2007) was the first of its kind and used a general population sample. Thus it is in need of 100 replication in other populations, particularly clinical populations, and was considered a relevant factor of interest for the current study.

6.2. Study Objectives

This study has the following aims: 1. To identify the main coping styles used by PWD.

2. To determine the influence of personality traits and serotonin transporter genotype (5HTTLPR) on coping styles and preferences in a population with diabetes mellitus.

Hypotheses: 1) High levels of neuroticism are associated with more use of maladaptive coping styles (avoidance coping and emotional-expression coping),

2) The 5HTTLPR ‘s’ allele predisposes individuals to use more maladaptive coping styles (avoidance coping and emotional-expression coping).

6.3. Methodology

The methodology has been described in Chapter 3.

6.4. Statistical Analyses

Statistical Analyses were carried out using SPSS for Windows (v.16). Gender and genotype differences were assessed via a series of one-way ANOVAs. Associations between coping factors, and personality

101 dimensions were examined in a correlations matrix. These factors were then examined via standard multiple linear regressions, to determine the extent to which personality dimensions would predict usage of particular coping styles.

6.5. Results

6.5.1. Demographics

The sample consisted of 178 PWD, with a mean age of 57.1 (range 23-84). Of the patients, 55% (n = 98) were male, and 71% (n = 126) had T2DM. The mean duration of illness was 13.9 years (range = 0.25 - 59). The three genotype groups were in Hardy-Weinberg equilibrium (F2 =3.26, df = 2, p = 0.07). There were no differences in allele frequency between males and females (F2 =3.81, df = 2, p = 0.149).

6.5.2. Coping Scores

As the factors consisted of different numbers of items, the mean score on each factor was calculated to create comparable factor scores. The mean rates of coping for each factor are shown in Table 6.1. The most used coping strategies were problem-focused (mean score per item = 2.54), followed by emotional-expression (mean score = 2.30), and finally avoidance coping, (mean score = 1.78). There were no gender differences in the usage of the major coping factors, but when the social support based coping subscales (emotion and instrumental) of the problem-focused factor were analysed individually, both were used significantly (p < 0.01) more among women, in keeping with research in a general population (Wilhelm & Parker, 1993) and in PWD (Enzlin, et al., 2002, Gafvels, et al., 2006). There was also a strong trend, though not significant (p = 0.056) for people

102 with T2DM to use more avoidance-based coping strategies. There were no significant effects of genotype on rates of coping. There was a tendency towards more usage of emotional-expression strategies and emotional social support among ‘s’ allele carriers, but not statistically significant. The effect of type of DM on coping style will be explored further in the next chapter.

6.5.3. Relationship between Coping factors and personality scales of the NEO-FFI

The correlations between the coping factors and the five personality dimensions measured by the NEO-FFI are presented in Table 6.2. Neuroticism, extraversion and conscientiousness are the dimensions most frequently associated with specific coping styles. Neuroticism was positively correlated with avoidance-based coping and emotional- expression coping (p<0.01) and negatively correlated with problem-focused coping (p<0.05). Both extraversion and conscientiousness were significantly (p<0.05) positively correlated with problem-focused coping and negatively correlated with avoidant coping, but unrelated to the emotional- expression factor. Openness was positively correlated with problem- focused coping (p<0.01) while agreeableness did not correlate with any coping factors. Subscale correlations were also examined in order to develop a more nuanced understanding of the relationships between personality and more specific coping styles within the overarching factors. This analysis showed that extroverts tended to seek more social support for both emotional and instrumental reasons (p<0.01).

There were no significant associations between the 5HTTLPR and any NEO personality factors, though there was a tendency toward higher neuroticism among ‘s’ allele carriers and higher extraversion among ‘l’ allele carriers.

103 6.6. Regression Analyses

A series of multiple regression analyses were performed using each of the coping factors as the dependent variable and the NEO personality factors as the independent variables (Table 6.3).

6.6.1. Avoidant coping

Avoidance coping was the factor that was the most strongly predicted by personality factors, with the five dimensions explaining 23.1% of variance in rates of avoidant coping (p<0.01) but only neuroticism (p<0.01) was a significant predictor.

6.6.2. Problem-focused coping

Only openness (p < 0.01) and extraversion (p < 0.01) remained significant predictors of problem-focused coping. This model explained 17.7% of the variance in problem-focused coping rates, which was significant (p<0.01).

6.6.3. Emotional-expression coping

Neuroticism (p < 0.01) and extraversion (p < 0.05) significantly predicted rates of usage. Together, the five personality factors accounted for 21.6% of variance in emotional-expression coping, which was significant (p<0.01). Next, a hierarchical multiple regression analysis was performed (Table 6.4) with type of DM, age and duration of illness as covariates (Step 1) and neuroticism as predictor (Step 2) of avoidance coping. Neuroticism explained an additional 15.4% of the variance in avoidance coping even when the effects of type of DM, age and duration of illness were statistically

104 controlled for. The model as a whole explained 22.8% of the variance [(F (4,147) =10.584, p < 0.001] in avoidance coping.

Table 6.1: Mean coping scores for each factor

Coping Factor (n) items) Mean per item S.D. Problem (36 items) 2.54 18.01 Emotional Expression (4 items) 2.30 5.68 Avoidance (12 items) 1.78 3.18

Table 6.2: Correlations between coping factors and the five NEO factors

N E O C A Problem-focused -0.19* 0.31** 0.28** 0.17* -0.08 Avoidance-focused 0.44** -0.27** 0.10 -0.27** 0.02 Emotion-focused 0.41** 0.05 0.08 -0.06 0.02

*p < 0.05 **p < 0.01

105 Table 6.3: Regression analysis with NEO personality factors as the predictor and each of the three coping factors as dependent variables (3 models)

N E O C A R Std.Beta Square (t-test) (S.E.) Avoidance 0.38 -0.13 0.12 -0.07 0.01 0.23 Coping (4.97)** (-1.78) (1.65) (-0.88) (0.16) (5.06)**

Problem- focused -0.06 0.22 0.27 0.12 -0.022 0.18 coping (-0.77) (2.73)** (3.57)** (1.43) (-0.294) (16.60)**

Emotional- 0.50 0.17 0.11 0.08 0.03 0.22 expression (6.58)** (2.252* (1.46) (1.04) (0.39) (2.85)** coping *p < 0.05 **p < 0.01

106 Table 6.4: Hierarchical Regression Analysis summary for Neuroticism and relevant covariates as predictors of avoidance coping

Variable B SEB Ǻ R2 ¨R2

Step 1 0.07*

Age -0.11 0.04 -0.27**

Duration of 0.04 0.05 0.08 Illness

DM Type 3.74 1.36 0.29**

Step 2 0.23** 0.15**

Neuroticism 0.27 0.05 0.43**

*p < 0.05 **p < 0.01

6.7. Discussion

PWD within this sample used a mix of coping styles, including problem and restraint-focused strategies, socially supported approaches, emotional- expression strategies and avoidant coping. Rates of problem-focused and emotional-expression coping were greater than that of avoidant coping, a finding generally in keeping with other research in the field (Macrodimitris & Endler, 2001; Maes,et al., 1996). A previous study however found high

107 rates of avoidant coping styles in PWD (Coelho, et al., 2003). While this was not the case in this study, rates of avoidant coping were still moderate.

In this sample, neuroticism, extraversion and conscientiousness significantly influenced coping styles. This finding highlights the potential for tailoring interventions to suit particular groups of patients according to their personality profiles and coping preferences. For instance, since those with high neuroticism appear to have a preference for emotional-expression coping, clinicians could provide education regarding the more adaptive strategies within the emotion-focused approach, such as social support seeking or emotional regulation strategies. Instead of avoiding the emotions attached to the stressor, these individuals may then regulate their emotions and move on to more task- oriented activities, once the acute emotional intensity of the stressor has been alleviated. This approach may be preferable to attempts to introduce problem-focused coping approaches, as these strategies were negatively correlated with neuroticism in this study, suggesting that those with predominant neurotic traits may find problem-focused coping methods both unfamiliar and hard to adopt. Offering strategies that are compatible with patient preferences may make them more open to trying out new approaches and ultimately lead to greater uptake of more adaptive coping strategies.

In contrast to the work by Wilhelm et al. (2007), genotype did not significantly influence participants’ scores on the coping factors derived in this study but there were trends in the same direction. This result may have been a product of the relatively small sample size examined or may have been due to the nature of the coping measure used. The COPE inventory employed in the current study was a broader measure of a range of coping styles and the factors derived from this analysis consisted of composite coping strategies, such as problem-focused combined with social support seeking and restraint. In contrast, the study of genotype and coping by

108 Wilhelm et al. (2007) used a very specific measure of coping, which assessed problem-focused and emotion-focused techniques as two distinct domains. This more narrow approach may have allowed for a clearer observation of the effect of genotype on coping styles.

Another possibility however, is the existence of population-specific differences in the influence of genotype. The study by Wilhelm et al. (2007) focused on a general population sample, not a sample with a chronic condition. The chronicity of common stressors in DM and possibly other populations with chronic conditions contrast against the acute life events measured by Wilhelm et al. (2007). It may be that the current PWD sample and possibly other populations with chronic conditions are not affected in the same way by underlying genotype differences, perhaps because the very act of living with a chronic condition such as DM requires high levels of problem-focused skills. If this were the case, then the effect of genotype on coping may have been overridden by the ongoing demands of the illness, which required all patients, regardless of genotype, to adapt and re-align their coping skills. These possibilities could be considered in future research with other populations with ongoing physical conditions.

The results of this study suggest that levels of avoidant coping within the DM population are still higher than would be desirable. While avoidant coping may be effective in negotiating certain types of stressors (e.g. the benefit of denial which has been well established) and during particular stages of coping, such as at the onset of the stressor of diagnosis (Suls & Fletcher, 1985), it seems that certain personality factors may predispose some individuals to continue using such strategies throughout the course of chronic stressors, with potentially detrimental effects. Research in general populations (Moos & Holahan, 2003) and those with chronic illness (Anderson, et al., 2001) has shown that persistent use of avoidant coping leads to negative outcomes. The findings of the current study suggest that

109 those high in neuroticism and low in conscientiousness may be particularly prone to avoidant coping and may be regarded as a high priority group for selective interventions by clinicians. Screening for personality styles could provide a brief and simple way to identify the group most likely to adopt avoidant coping styles and at the same time demonstrate a lack of the active coping skills that are so crucial for effective DM management. Lee- Baggley et al. (2005) notes that individuals with high neuroticism scores are inflexible in their coping repertoire and are less likely to alter coping strategies to match the stressor. Gunthert et al. (1999) add that this inflexibility in coping among high neuroticism individuals may lead to poorer outcomes. These findings suggest that these individuals may require guidance from health-care providers to successfully negotiate stressors associated with their chronic condition.

6.8. Limitations

This study has several limitations. The stage of illness of the participants was not considered and as such issues related to a particular stage of the illness, such as switching of treatment regimes or the onset of DM-related complications may have been overlooked. These areas may well influence the types of coping used by PWD and should be considered in future research. In addition, the cross-sectional design of the study did not allow for exploration of individual and inter-individual changes across time.

The usage of a generic rather than illness-specific coping measure may have created a dilution effect of coping to DM per se. Finally, the small sample size of the current study may have been inadequate to address the effect of 5HTTLPR on coping or personality traits, particularly for the detection of genotypic differences. Assessing specific coping styles at various illness stages in DM may help us to better understand the

110 connection between possible genotypes, personality styles and coping when faced with selective stressors.

6.9. Implications

Future research should consider the development of coping-based interventions for use in DM clinics. The role of psychosocial interventions has received increased attention in recent years, particularly interventions aimed at modifying ineffective coping (Heim, et al., 1995). In view of the personality factors that influence people’s coping styles; simple and distinct interventions, which can be used in different combinations to form a program that meets the needs of each individual, are recommended.

111 CHAPTER 7: COPING, DEPRESSION AND GLYCAEMIC CONTROL IN TYPE 1 AND TYPE 2 DIABETES MELLITUS

ABSTRACT

Background: Coping styles influence psychological outcomes and glycaemic levels in diabetes mellitus. Objectives: This chapter examines the relationships between coping styles and psychological outcomes and glycaemic control and compares coping styles between patients with Type 1 and Type 2 diabetes mellitus (T1DM and T2DM). Method: Patients attending two general hospital diabetes clinics in Sydney, Australia responded to the 60-item COPE, the 20–item Problem Areas in Diabetes (PAID), the Patient Health Questionnaire (PHQ-9), and Kessler-10 item (K10) questionnaires. As a measure of glycaemic control, the latest glycosylated haemoglobin (HbA1c) levels were obtained from participants’ medical records. Results: A total of 49 T1DM and 129 T2DM patients completed the questionnaires. Avoidance and emotional-expression coping correlated significantly with PHQ-9 depression scores and DM-related psychological distress (measured by the PAID). Linear regression analysis revealed a significant predictor effect of avoidance coping on depression scores. After controlling for age, type of DM significantly predicted avoidance coping, with a higher frequency of usage by people with T2DM. There were no significant correlations between either avoidance coping or emotional- expression coping and glycaemic control (HbA1c levels).

112 Conclusion: Psychological interventions in DM should be designed to target sub-populations with high levels of emotional reactivity with a focus on coping-based interventions aimed at emotional regulation.

7.1. Introduction

The last chapter explored the relationship between personality traits, serotonin transporter genotype and coping strategies in a cohort of PWD. In this chapter, the role of predispositional coping in shaping psychological and glycaemic outcomes in DM is explored. Of interest is the study of specific vulnerable sub-populations with particular maladaptive coping styles and how this influences DM illness-related variables and emotional health.

In chronic medical illness, the daily demands of managing symptoms or adhering to treatment regimes take the form of chronic stressors, demanding a wide repertoire of coping or the learning of new strategies. A chronic illness may be viewed as an ongoing stressor, and as such, an individual’s adaptation to, and management of this stressor may be crucial in determining the progression of the illness and their psychological wellbeing. Endler et al. (2001) have reported on the role of preferred coping in chronic illness, making a differentiation from coping in acute illnesses. These authors found that compared to acutely ill patients, people with chronic illness use a wider range of coping strategies including instrumental, emotional preoccupation and avoidance strategies. People with chronic illness thus have a tendency to focus and act on the emotional aspects of their illness while acutely ill patients concentrate on alleviating the burden of the actual somatic symptoms of the illness.

113 Adaptive coping strategies can be used as building blocks for constructing interventions for chronic illness populations. A review of coping-based interventions in chronic disease revealed 35 studies in seven different chronic disease types (de Ridder, et al., 2001). They note the bias in the literature favouring problem-focused coping strategies and the usage of cognitive behavioural approaches over other strategies. There is a need therefore, to develop brief interventions using a wider range of coping strategies, for example the incorporation of emotion regulation techniques, or those that enhance social support, for example communication and interpersonal skills training.

Although traditional psychotherapies incorporate coping-based strategies, for example relaxation exercises and problem solving strategies in cognitive behaviour therapy, these treatments are generally targeted towards people with specific psychiatric morbidity, for example depression or panic disorder. Requiring specifically trained therapists and multiple sessions, they are not cost effective when delivered to people with chronic physical conditions. Brief coping based interventions on the other hand, can be incorporated into chronic disease management protocols and disseminated to general medical populations without exhausting resources.

Teaching of effective coping skills are of great benefit to populations who are managing long-term health conditions, especially those at risk of developing concurrent mental health problems. Studies have demonstrated that effective coping is associated with a greater sense of control and self- esteem (McWilliams, et al., 2003), as well as lower distress levels and a decreased risk of depression and anxiety (Flett, et al., 1996). Further, coping strategies can be developed and enhanced via education, suggesting that such skills are malleable, not fixed (Peyrot & Rubin, 2007). Evidence thus far has suggested that coping-based interventions are effective in a range of populations with chronic health conditions (de Ridder 114 & Schreurs, 2001), including asthma (Boulet, et al., 1995; Sommaragu, et al., 1995), chronic low back pain (Turner, et al.,, 1990; Turner & Jensen, 1993; Vlaeyen, et al., 1995) and DM (Gilden, et al.,, 1992; Henry, et al., 1997). However, a key finding of this research has been the need to consider each illness population individually, as specific populations may benefit from particular coping styles depending on the nature and conditions of their illness.

The literature describes a variety of coping strategies used by PWD. There seems to be a preference for the use of problem focused coping over other strategies (Maes, et al., 1996, Macrodimitris & Endler 2001) although one study (Coelho, et al., 2003) cited avoidance coping as the most frequently used. Generally problem-focused coping resulted in better psychological and physiological outcomes (Sultan, et al., 2008, Nakahara, et al., 2006, Gafvels, et al., 2002), whilst emotion-focused coping was associated with negative psychological outcomes in DM (Smari & Valtysdottir 1997, Nakahara, et al., 2006). However these differences in coping associations become more complex when nomenclature of coping and specific context is taken into consideration, as described below.

In Chapter 4, it was demonstrated that Principal Components Analysis (PCA) of the COPE questionnaire established the existence of three major coping factors in this cohort. The PCA differentiated between emotional expression and emotion-focused coping strategies. Emotional expression encompasses ‘venting out of feelings of frustration or anger’. Emotion- focused or emotional regulation coping strategies refer to ‘attempts to modulate distress associated with stressful situations’. These include the COPE items “I discuss my feelings with someone” and “I get sympathy and understanding from someone, which in this study factored together with “problem-focused” strategies.

115 The adaptive benefits of emotional-expression coping strategies and their role in the prevention of long-term emotional disorders, for example, depression are questionable. Emotional-regulation strategies on the other hand, aim to modulate the experiencing of intense emotions as a result of stressful situations through effective channels such as re-appraisal or positive reinterpretation. Some individuals may be more prone to use emotional focused or regulation strategies to good effect, while others may prefer emotional expression techniques. This argument becomes evident when the literature on “emotion-focused coping” in DM is examined.

The disparity in findings related to emotion-focused coping in DM can be firstly attributed to nosological issues of this construct, as has been discussed in the previous chapter. Secondly, assuming that the concept of emotion-focused coping has been consistently defined by researchers for use in DM, differences may arise due to specificity of stressors or individual characteristics, for example personality traits or trait anxiety as described by Sultan et al. (2008). In a longitudinal study on people with T1DM, these authors established that individuals with high baseline trait anxiety who used less emotion-focused strategies had the tendency towards higher HbA1c levels at the end of their two-year study. On the other hand, Nakahara et al. (2006) assessed the causal relationship between psychosocial factors and glycaemic control in T2DM, and found that emotion-focused coping aggravated daily hassles and DM-related distress and correlated directly with HbA1c at 6 months.

Drawing evidence from Sultan et al. (2008) and Nakahara et al. (2006), it is feasible to suggest that there is a vulnerable sub-population within DM that may benefit from emotional regulation strategies to cope with a high degree of stress-reactivity in order to maintain good DM-related health outcomes. Inconsistency in the definition of emotion-focused coping in the DM literature precludes generalisation on the relationships between emotion

116 focused coping and psychological and DM-related outcomes. Therefore individual papers should be reviewed critically for classification and situational context before any conclusions can be drawn about coping in DM.

If the highly stress-reactive DM population were to confront persistently high levels of stress using problem-focused interventions, there is a risk of burnout, assuming of course that on the average, individuals with DM have a higher stress loading than the general population. A combination of primarily emotional-regulation followed by problem-focused coping strategies may thus be a good approach in negotiating stressors for sub- populations with high stress-reactivity.

T1DM and T2DM differ in their stage of illness journey and common DM- related hassles. It can be hypothesised therefore, that the predominant coping styles used by these individuals will differ. Coping styles among people with T1DM and T2DM have not been widely described as most studies enrolled people with either T1DM or T2DM. One study (Karlsen & Bru, 2002) found that people with T1DM sought more social support, planned more and were more self-blaming although the latter two behaviours were explained by differences in age and educational level between the two types of DM. The specific differences regarding age of onset, physiological mechanisms and treatment regime between the two types of DM all have the potential to influence stress response and coping patterns which require further investigation.

The aims of this chapter are: (i) To study the association between coping and depression and glycaemic control in DM. ii) To compare coping styles between T1DM and T2 DM.

117 The hypotheses are that: 1) PWD with coping styles involving emotional-expression and avoidance coping will have higher levels of depression. 2) PWD with coping styles involving emotional-expression and avoidance coping will have poorer glycaemic control (HbA1c levels).

7.2. Methodology

7.2.1. Participants / Procedure

A total of 178 people with T1DM and T2DM from the Prince of Wales and St Vincent’s Hospital Diabetes Clinics in Sydney recruited as part of the Stress Sampler Study trialing brief minimal contact interventions in DM responded to the COPE, PHQ, PAID, K10 and SF-12 questionnaires. The HbA1C level taken on the day of consultation was obtained from the DM clinic case notes. The detailed methodology and details of the instruments used in this chapter are documented in chapter 3.

7.2.2. Statistical analyses

All statistical analyses were conducted using SPSS Version 16.0. A principal components analysis (PCA) with oblimin rotation was carried out on the COPE questionnaire as described in Chapter 4. Student’s t-test was used to compare means between demographic groups, while Pearson’s correlation coefficient was used to study associations between coping factors and outcome variables. Hierarchical linear regression analysis was performed in separate models using the coping factors as predictor variables and PHQ-9 depression scores as the outcome variable in the first model, and with type of DM as predictor variable of avoidance coping, while controlling for age, in the second model. 118 7.3. Results

Principal Components Analysis (PCA) of the COPE revealed three factors (see Chapter 4), a problem focused factor (Factor 1), an avoidance factor (Factor 2) and an emotional-expression coping factor (Factor3).

7.3.1. Demographics and Mean Coping Scores for each Factor

Of the 178 participants who responded to all questionnaires, 98 were males (55%) and 80 were females (45%). People with T1DM (n=49) comprised 27.5% of the total while those with T2DM (n=129) made up a further 72.5%. As described in Chapter 6, problem-focused coping (mean score per item =2.54) was the most commonly used coping strategy, followed by emotional-expression (2.30) and avoidance strategies (1.78) (Table 6.1). There was a trend for those with T2DM to demonstrate higher rates of avoidance coping that was not significant (p = 0.056).

7.3.2. Correlation between coping, psychological outcomes and HbA1c

These data are presented in Table 7.1. There was a significant positive correlation between problem-focused and emotional-expression coping factors (r = 0.261, p < 0.01). Avoidance coping correlated significantly with PHQ-9 (p < 0.01), K-10 (p < 0.01), SF-12 MCS (p < 0.01) and PAID (p < 0.01), while emotional-expression coping correlated significantly with PHQ- 9 (p < 0.05), K-10 (p < 0.01), SF-12 MCS (p < 0.01) and PAID (p < 0.01). There were no significant correlations between either avoidance coping or emotional-expression coping with HbA1c. There were also no significant

119 correlations between the problem-focused coping factor and other dependent variables. However, when the problem-focused coping sub- factors were analysed separately, there were significant negative correlations for the more active-based coping sub-factors only with the K10 (Table 7.2) (active coping, r = -0.176, p < 0.05; positive reinterpretation, r = -0.146, p = 0.05; planning, r = -0.146, p < 0.05). Restraint and acceptance coping did not correlate with K10 or any other outcome measures. Therefore the more “proactive” problem-focused strategies (active coping, positive reinterpretation and planning) resulted in better outcomes with regard to the K10 rather than the “passive” ones (restraint, suppression and acceptance). There were statistically significant correlations between age and avoidance coping (r = -0.146, p < 0.05) and emotional-expression coping (r= -0.230, p < 0.01).

7.3.3. Regression analysis

In the first model, hierarchical regression analysis was performed to assess the ability of the different coping factors to predict PHQ-9 depression scores (Table 7.3). Age, gender, type and duration of DM were entered as co- variates in the first block, followed by the three coping factors in the second block. After the variables in Block 1 (gender, age, duration and type of DM) were entered, the overall model explained 8.4 % of the total variance. After Block 2 variables (problem-focused, emotional-expression and avoidance coping) were included, the model as a whole explained 21.8% of the variance [(F (7,141) = 5.33, p < 0.01]. Thus coping factors explained an additional 13.4% of the variance in PHQ-9 scores, even when the effects of gender, age, duration and type of DM were controlled for. Avoidance coping significantly predicted PHQ-9 (p <0.01) with a ß value of 0.355.

Next, a hierarchical regression model was constructed to test the predictive ability of DM type on avoidance coping, with age and duration of DM as

120 covariates (Table 7.4). The model as a whole explained 7.4% of the variance [(F (3, 147) =3.846, p < 0.05]. Age (ȕ = -0.272, p < 0.01) and DM type (ȕ = 0.292, p < 0.01) were significant predictors of avoidance coping.

Table 7.1: Correlations between coping factors, psychological outcomes and glycaemic control

Variable 1 2 3 4 5 6 7 8 1. Avoidance _ 0.07 0.27** 0.41* 0.37* 0.47** -0.34** 0.06 coping * * 2. Problem- _ 0.26** -0.02 -0.14 0.09 0.04 -0.01 focused coping 3. Emotional- _ 0.19* 0.25* 0.40** -0.24** 0.05 expression * coping 4. Depression _ 0.83* 0.50** -0.62** 0.12 PHQ-9 * 5. _ 0.56** -0.69** 0.12 Psychological distress K-10 6. PAID _ -0.48** 0.34**

7.SF-12_MCS - -0.03 8. HbA1c _ - * p < 0.05 **p < 0.01

121 Table 7.2: Correlations between problem-focused coping subscales and K10

Coping factor K10_Total K10_Anxiety K10_Depression

Active -0.176* -0.170* -0.161*

Planning -0.146* -0.167* -0.121

Positive -0.146* -0.157* -0.125 Reinterpretation

*p < 0.05

122 Table 7.3: Hierarchical Multiple Linear Regression Analyses Model: Coping factors as predictors of depression scores (PHQ-9)

Variable B SEB Ǻ R2 ¨ R2 Step 1 0.084

Gender 0.862 0.938 0.077

Age -0.110 0.038 -0.270**

Duration of 0.103 0.046 0.217* DM Type of DM 3.50 1.379 0.280* Step 2 0.218 0.134

Avoidance 0.348 0.080 0.355** Coping Problem- -0.015 0.025 -0.050 focused coping Emotional- 0.137 0.147 0.078 expression coping *p < 0.05 **p < 0.01

123 Table 7.4: Hierarchical Regression Analysis predicting Avoidance Coping scores

Variable B SEB Ǻ R2 ¨ R2 Step 1 0.026 Age -0.113 0.038 -0.272** Duration of 0.036 0.046 0.075 DM Step 2 0.074 0.048 Type of 3.736 1.364 0.292** DM **p < 0.01

124 7.4. Discussion

Generally, participants with T1 or T2DM used a combination of coping strategies. Problem-focused strategies were the most frequently used, as described elsewhere (Maes, et al., 1996, Macrodimitris & Endler, 2001). This study demonstrates significant associations between avoidance coping and negative psychological outcome indicators, thus replicating studies by Coelho et al. (2003), Macrodimitis & Endler (2001) and Maes et al. (1996). In a chronic condition like DM, coping strategies are an important link between daily stressors and eventual illness outcomes.

A recent meta-analysis on coping in DM however failed to establish any significant relationships between avoidance coping and depression or anxiety (Duangdao & Roesch 2008). The sample derived for the meta- analysis was largely T1DM (72.7%), compared to this study, which largely comprised of T2DM participants (72.5%). The literature at large could therefore be addressing a population in which avoidance coping may have proven benefits, for example in newly diagnosed T1DM, as avoidance coping is believed to relate to effective short-term adjustment to illness diagnosis (Duangdao & Roesch 2008, Suls & Fletcher 1985). To test the hypothesis that avoidance coping is beneficial in the acute aftermath of an illness event; studies on newly diagnosed DM patients, those reporting acute events such as diabetic keto-acidosis, or change in treatment regimes are required.

It is likely that motivational interviewing strategies would be useful to determine level of preparedness of PWD to deal actively with the stressors encountered, particularly those using predominantly avoidance strategies. Acknowledging some early benefit of avoidance coping to the individual also reinforces the need to consider the stage of DM in coping research. In

125 a review on coping-based intervention strategies in medical illness, Heim (1995) emphasises the importance of differentiating between coping with a given illness as a whole or towards particular illness stages. The author proposes interventions that provide step-wise coping strategies incorporating problem analysis, for example, goal setting tailored to each change of illness stage. Drawing evidence from the coping literature, Heim (1995) concludes that these interventions, though brief, have proven to be effective in DM, cancer, and hypertension. A study on the relative benefits of problem-focused and emotional regulation interventions will thus have to take an intra-individual approach to coping throughout illness stages.

Type 2 PWD used avoidance coping strategies more frequently after controlling for age in this study. It is possible that those with T2DM generally experience more overwhelming stressors in the form of higher rates of DM-related complications and medical comorbidity and thus use avoidance strategies as a short-term measure. Self-blame and guilt are common themes associated with avoidance coping (Duangdao & Roesch 2008) and these may be prominent in people with T2DM who may attribute the onset of the illness to self-neglect and unhealthy lifestyles. Differences in the qualitative illness experience among the DM types can thus dictate the choice and efficacy of coping strategies. The illness journey has the potential to shape coping patterns. This shift of preferred coping strategies in a chronic illness has not been described and therefore deserves further study.

The significant negative correlations between active forms of problem- focused coping and K10 scores were more consistent for the anxiety rather than the depression subscale. These findings reiterate the reported benefits of task or problem-oriented coping on alleviating state anxiety in DM (Sultan, et al., 2008, Duangdao & Roesch 2008). These strategies are commonly used by PWD to manage the day-to-day requirements of the

126 condition. By establishing a relationship with the active forms of problem- focused coping, this study has also demonstrated the benefit of the K-10 as an instrument in identifying a DM subpopulation that has used a sub-set of coping strategies to good effect.

The lack of significant associations between coping factors and HbA1c is contrary to the findings of three longitudinal studies (Nakahara, et al, 2006, Sultan, et al., 2008, Spiess, et al., 1994) and the meta-analysis by Duangdao & Roesch (2008), which summarised evidence that patients who used predominantly approach-coping strategies (task and emotion-focused) had better HbA1c control. In order to replicate these findings, studies incorporating longitudinal design, serial coping, HbA1c and physiological stress indicators such as cortisol levels as described by Reinehr & Andler (2004) should be carried out.

There were a few limitations to this study. The cross sectional design did not allow for a study of the predictive value of coping on DM outcomes across time. The concept of coping was simplified by using the dispositional form only but in reality PWD have the tendency to use coping strategies to suit specific situations, especially with regard to DM specific stressors or with stages of the illness. The sample was biased, originating from a general hospital specialist clinic. Future studies of this nature could recruit community samples (or from a variety of health-care settings), for example through DM registers. The outcome instruments used in this study were all designed to capture “pathological” outcomes, or in the case of PAID, distress. Well-being questionnaires with positively phrased items designed to elicit positive adjustment to chronic illnesses should be incorporated. This will enable more effective analysis of adaptive forms of coping on psychological adjustment in DM. It has to be emphasised that anxiety and depressive states can cloud coping patterns or responses so results must be interpreted with caution. The bidirectionality of coping and

127 depression or psychological distress has to be considered before establishing any predictive capacity of these constructs.

7.5. Conclusion

Though the cross-sectional design of the study does not determine whether PWD are more likely to use avoidance coping strategies early in their illness, the findings suggest that avoidance coping is related to negative outcomes. Psychological interventions should therefore aim at minimising usage of avoidance coping and encourage other forms of adaptive coping strategies, taking into consideration specific stressors and illness stage. Longitudinal studies will do well to assess the natural course of coping strategies across the illness span and also to determine the impact of coping based interventions in determining positive outcomes in DM. This study also suggests a more critical appraisal to the use of emotional regulation or emotion-focused strategies. Strategies that encourage emotional regulation will be of benefit to some individuals. PWD using predominantly emotional-expression strategies, such as venting of frustration could benefit from emotional-regulation interventions. Coping- based interventions have to be tailored to meet the needs of individual PWD.

128 CHAPTER 8: GENDER DIFFERENCES IN THE ASSOCIATION BETWEEN THE SEROTONIN TRANSPORTER PROMOTER POLYMORPHISM (5- HTTLPR SLC6A4) AND PSYCHOLOGICAL DISTRESS IN A CHRONIC ILLNESS POPULATION.

ABSTRACT

Objective: To investigate the interaction effect of gender and the serotonin transporter genotype (5-HTTLPR SLC6A4) on psychological distress in a population with T1 or T2DM. Method: Type 1 and 2 PWD attending two tertiary clinics provided cheek swab samples for DNA analysis. The NEO Five Factor (NEO-FFI), Kessler- 10 (K10) and Patient Health Questionnaire (PHQ) instruments were administered to the participants. Results: Analysis of a total of 254 participants revealed an effect of genotype in females for K10 anxiety subscale scores with a statistically significant difference at the p < 0.01 levels. Post hoc comparisons indicated that the mean score for females with s/s genotype (M=3.94, SD=3.78) was significantly higher than the mean scores of females with s/l (M=1.74, SD=2.36) and l/l genotypes (M=1.55 SD=2.54). Multiple regression analysis established a gender-genotype interaction effect on the K-10 anxiety component (p < 0.05). Conclusions: The findings suggest that in a population experiencing chronic stress, gender differences exist in the effect of serotonin transporter promoter polymorphism on levels of psychological distress. Future studies are needed to delineate specific pathways mediating the 5-HTTLPR- genotype effect in females experiencing chronic stressors.

129 8.1. Introduction

There has been much interest in recent years in the relationship between variants of the relatively common genetic polymorphism in the promoter region of the human serotonin transporter gene (5-HTTLPR SLC6A4) located on chromosome 17q11.1-q12 and proneness to stress adaptation, anxiety and depression. A functional polymorphism in the promoter region of this gene (5-HTTLPR) is characterised by a short (‘s’) and a long (‘l’) allele, with the short allele being associated with lower transcriptional efficiency of the promoter and thereby decreased serotonin transporter (5- HTT) expression (Heils 1996, Lesch, et al., 1996). There is growing recognition of the relationship between the 5-HTT genotype and response to stress, particularly with respect to onset of depression. Individuals with at least one short allele (s/s or s/l genotypes) have been reported to have higher trait anxiety and neuroticism than those homozygous for the long allele (l/l) (Lesch, et al., 1996; Schinka, et al., 2004; Sen, et al., 2004) and are also at greater risk for depression, in the presence of multiple stressful life events (Caspi, et al., 2003). This gene x environment (G x E) interaction has been replicated in a number of subsequent studies (Kendler, et al., 2005; see Uher & McGuffin, 2008 for review; Wilhelm, et al., 2006) incorporating a variety of populations, including children and adolescents, chronically stressed individuals with post traumatic stress disorder and those with chronic medical illness, including cardiac disease, Parkinson’s disease and migraine (Gonda, et al., 2007; Lenze, et al., 2004; Mossner, et al., 2001; Nakatani, et al., 2005; Otte, et al., 2007).

Recent meta-analyses by Munafo et al. (2009) and Risch et al. (2009) however found that the 5HTTLPR main effect and G x E interaction on risk of depression are negligible. The authors cited small sample sizes and chance positive findings as possible reasons. Further than that, the lack of definition of endophenotypes and heterogeneity of stressors examined 130 across individual studies could have accounted for these negative meta- analyses. It is important therefore to consider other alternatives with respect to stressors (acute vs. chronic) and the influence of gender in such G x E interactions.

A number of these studies have investigated the effect of gender on reported interactions between anxiety, depression, neuroticism and genotype, though results are inconsistent. Several studies have examined the effect of genotype in samples that are predominantly female while one study featured an exclusively male sample. Some investigations suggest that the 5-HTTLPR genotype confers a vulnerability to neuroticism only in males, implicating either the s allele (Du, et al., 2000) or the l allele (Brummett, et al., 2003; Flory, et al., 1999). Other research suggests a vulnerability to stress specific to the ‘s’ allele in females (Brummett, et al., 2008; Eley, et al., 2004; Flory, et al., 1999; Grabe, et al., 2005; Sjoberg, et al., 2006).

There is increasing support for the view that chronic ‘minor’ hassles are at least as important as major life events in contributing to disease burden. This view has been proposed by Kendler et al. (2005) who found that “common, low threat events”, rather than severe life events, trigger depression in people with the s/s genotype. He concludes that daily hassles are important environmental factors in chronic illness, which are capable of interacting with the 5-HTTLPR. Daily hassles like strict dietary and medication regimes, the threat of complications and the frustrations of poor control despite strict adherence may outweigh the impact of one-off life events and interact with vulnerable 5HTTLPR alleles resulting in risk of depression in those with chronic physical illness. There is therefore a need to unravel the specific environmental triggers at work in medical illnesses.

131 There are several possible mechanisms for a greater impact of chronic stressors on s/s genotype females. The observed female preponderance of depression rates (Jorm, et al., 1987; Kessler, et al., 1993; Weissman, et al., 1984; Wilhelm, et al., 2003) has been thought to correlate with a higher rate of pre-existing anxiety in females (Breslau, et al., 1995) (also Wilhelm, et al., 1997) and higher neuroticism scores throughout the life span (Jorm, et al., 2000) (Jorm, et al., 2005); furthermore females’ vulnerability to the depressogenic effects of anxiety (Wilhelm, et al., 2008; Wilhelm, et al., 1997); heightened stress responsivity and exposure to a broader range and greater number of chronic stressors particularly of an interpersonal nature (McDonough & Walters, 2001) (Turner, et al., 1995), may well have greater salience in those with the s/s genotype. Women also show greater tendency to emotional-expression coping style and rumination, which may lengthen the duration and burden of chronic stress (Matud, 2004) (Nolen- Hoeksema, et al., 1999).

Despite the lack of coherence amongst these findings, these apparent discrepancies may be a result of differences in the stressors examined in the various studies. Stressors vary on a continuum from acute to chronic. Studies reporting vulnerability specific to the ‘s’ allele in females appear to have shared a common methodology whereby participants are drawn from a population experiencing one or more chronic stressors. For example, Brummett et al. (2008) report a vulnerability specific to ‘s’ allele females in two distinct samples, one experiencing long-term care-giving stress and the other low childhood socio-economic status. Family conflict and psychosocial risk was also found to increase the risk of state depression scores in girls with the s allele (Sjoberg, et al., 2006), while another study found that a composite measure of family and social adversity increased risk for depression in adolescent females with the s allele whilst males evidenced no difference by genotype (Eley, et al., 2004). A population- based study reported that long-term unemployment and number of chronic

132 diseases interacted with genotype to confer risk for psychological distress amongst females but not males (Grabe, et al., 2005). Results in these chronically stressed samples appear to indicate that females, but not males, with the ‘s’ allele are more vulnerable to the effects of chronic stress.

The hypothesis of a specific relationship between the type of stress and genotype is consistent with other research suggesting that females in general are more vulnerable to the effects of chronic stress (see Bale, 2006 for review). Heightened stress sensitivity in females may contribute to the observed female preponderance in depressive disorders (Breslau, et al., 1995; Wilhelm, et al., 2008; Wilhelm, et al., 1997), indeed females who experience childhood sexual abuse are significantly more likely to experience major depressive disorder in adulthood (Heim, et al., 2004). Animal studies suggest that hypothalamic pituitary adrenal (HPA) axis dysregulation may be implicated in such vulnerability; compared to male rodents, female rodents show elevated adreno-corticotrophic hormone (ACTH) and corticosterone levels in response to stress, with such heightened levels of these hormones persisting for a longer duration, suggesting a slower recovery time (McCormick, et al., 2002).

This study examines the interaction effect between gender and the 5- HTTLPR genotype on depression, anxiety and anxiety-related traits in a population exposed to chronic stressors. DM has an impact on mental and physical health as described in Chapter 1; PWD have twice the risk of depression (Anderson, et al., 2001) and up to four times the risk of generalised anxiety disorder (Grigsby, et al., 2002) compared to healthy populations, in addition to significantly increased risk for sub-threshold anxiety and depressive symptoms. Specifically, the study aimed to examine whether any observed effect of gender and 5-HTTLPR genotype is manifested by levels of psychological distress in a population with DM.

133 The hypothesis is that females with the ‘s’ allele experiencing chronic stressors related to their DM would be more susceptible to higher levels of anxiety and depressive symptoms.

8.2. Methodology

8.2.1. Participants

The detailed methodology is explained in Chapter 3. In this chapter the PHQ, K-10, and NEO-FFI questionnaires, which were administered to the participants, are considered for analysis.

8.2.2. DNA extraction and genetic analysis

This is described in Chapter 3.

8.2.3. Statistical analyses

All analyses were carried out using SPSS Version 16 for Windows. Differences in baseline characteristics between participants with and without the ‘l’ allele were determined using chi-square tests for categorical variables and t-tests for continuous variables. Mean scores on the K10, PHQ-9 and NEO-FFI were compared for each of the three genotypes (s/s, s/l and l/l) separately for males and females by one-way analysis of variance (ANOVA). One-way ANOVA was used to compare mean scores of genotype groupings on K10 items that loaded strongly on component 2 (anxiety) separately for males and females. Hierarchical logistic regression was used to assess the contribution of gender and genotype to the diagnosis of anxiety and depression. Post hoc comparisons were made using the Tukey Honestly Significant Difference (HSD) test.

134 To test the main hypothesis, multiple linear regression analysis was used to assess the main effect of the independent variables, gender, and the 5HTTLPR genotype, and the interaction terms gender x genotype, with K10 scores as the dependent variable. Prior to the regression analysis, the independent variables were coded via the contrast coding technique (Cohen, et al. 2003).

8.3. Results

Of the 274 participants, twenty provided samples that were inadequate for DNA analysis. Forty-four (17.3%) were homozygous for the ‘s’ allele (s/s genotype), 140 (55.1%) were heterozygous (s/l genotype) and 68 (26.8%) were homozygous for the ‘l’ allele (l/l genotype). Two (0.8%) had ambiguous genotypes so were not included in the statistical analyses. The three groups were in Hardy-Weinberg equilibrium (F2 =3.26, df = 2, p = 0.07). There were no differences in allele frequency between males and females (F2 =3.813 (2), p = 0.149).

Neither males nor females showed any difference according to genotype on scores on NEO-FFI subscales or the PHQ-9. Analysis of variance (ANOVA) produced a significant genotype effect in females only for K10 total and K10 anxiety subscale scores (Table 8.1). Females showed a statistically significant difference at the p <0.01 levels on K10 anxiety subscale scores according to genotype (F [2, 96] = 5.16, p = 0.007). Post hoc comparisons using the Tukey HSD test indicated that the mean K10 anxiety subscale scores for females in the genotype groups s/l (M=1.74, SD=2.36) and l/l (M=1.55., SD=.2.54) were significantly lower than the mean score for group s/s (M=3.94, S=3.78) (p <0.01). There were no differences in DM type, age, gender, marital status or level of education between the three genotypic groups. Logistic regression analyses 135 indicated that neither gender (OR 0.333 [95% CI 0.53–2.115], p=0.244) nor genotype (OR 0.529 [95% CI 0.1-2.811], p=0.455) were significant predictors of diagnosis of PHQ anxiety disorder. Neither were gender (OR 2.647 [95% CI 0.248–28.24], p = 0.420) nor genotype (OR 2.7 [95% CI 0.316–23.065], p = 0.364) significant predictors of PHQ depressive disorder or PHQ-9 scores. There was a main effect of gender on the Extraversion and Agreeableness subscales only, where females scored significantly higher on Extraversion and Agreeableness than males. There was no main effect of genotype on any of the five subscales of the NEO-FFI.

To test the gender-genotype interaction hypothesis in a regression model, the variables gender and genotype and the interaction variable gender- genotype were contrast coded according to Cohen & Cohen (2003). Hierarchical regression analyses were then conducted constructing two models, with the independent main effects variables gender and genotype (contrast coded) in the first block and the gender-genotype interaction variable in the 2nd block. For the first model the outcome variable was K10 total score, while for the second model the K10 anxiety subscale was used. In the first model (Table 8.2), the gender-genotype interaction significantly predicted K10 total score explaining 2.9% of the variance, F (3,228) = 2.3, p < 0.05. The model testing the gender-genotype interaction predicting K10 anxiety subscale score (Table 8.3) explained 4.6% of the variance, F (3,235) = 3.75, p < 0.01.

136 Table 8.1 Gender-5HTTLPR genotype interaction effects on K10 anxiety and depression subscales

s/s 95% CI s/l 95% CI l/l 95% CI K10 Factor Gender genotype genotype genotype p mean Lower Upper mean Lower Upper mean Lower Upper

Male 2.13 1.18 3.08 2.66 1.95 3.29 2.26 1.18 3.12 0.672 Anxiety Female 3.94 2.06 5.82 1.74 1.13 2.34 1.55 0.38 1.40 0.009*

Depression Male 4.52 2.40 6.64 5.72 4.30 7.15 4.53 3.09 5.98 0.439

Female 6.28 3.88 8.68 4.18 2.99 5.38 3.63 1.58 5.68 0.166

Male 16.65 13.88 19.42 18.42 16.41 20.43 16.79 14.54 19.04 0.453 Total Female 2.22 16.28 24.16 15.92 14.28 17.55 15.15 12.22 18.08 0.035

*(Post Hoc: Tukey HSD indicated significant difference for s/s genotype vs. s/l and l/l, p < 0.01)

137 Table 8.2 Hierarchical Regression analysis with gender-genotype interaction factor as independent variable and K10 total score as dependent variable

Variable B SEB Ǻ R2 ¨ R2 Step 1 0.007

Gender 0.273 0.476 0.038 Genotype -0.490 0.415 -0.078

Step 2 0.029 0.022 Gender x 0.942 0.415 0.161* Genotype Interaction *p < 0.05

Table 8.3: Hierarchical Regression analysis with gender-genotype interaction factor as independent variable and K10 anxiety subscale score as dependent variable

Variable B SEB Ǻ R2 ¨ R2 Step 1 0.013

Gender 0.100 0.181 0.036 Genotype -0.262 0.158 -0.108

Step 2 0.046 0.033 Gender x 0.449 0.157 0.199** Genotype Interaction **p < 0.01

138 8.4. Discussion

This study investigated the relationship between a variant of a functional polymorphism in the serotonin transporter gene-linked promoter region (5- HTTLPR) and anxiety-related traits, state anxiety and depression in a sample of T1 or T2DM. Results of the current study replicate previous findings in which a population facing significant chronic stress were found to experience a selective increase in psychological symptoms in s/s genotype females but not males (Brummett, et al., 2008; Eley, et al., 2004; Grabe, et al., 2005; Sjoberg, et al., 2006).

This study has not addressed whether the gender-genotype interaction is applicable to the whole female cohort or just to those with high levels of chronic distress. Comparable research into interactions of 5-HTTLPR genotype and chronic stress should measure the presence of daily hassles in a quantifiable way before a conclusion can be made as to the gene x environment (chronic stress) effect. Alternatively, future studies could perhaps elicit gender and genotypic differences in stress levels among PWD by assaying stress hormone levels, for example salivary cortisol. A control group of participants without DM would have enabled assessment of the effects of genotype and gender in the absence of a chronic stressor; indeed, previous studies reporting gender x genotype interactions among chronically stressed caregivers and children in adverse psychosocial circumstances report no such interaction among demographically matched control samples not experiencing chronic stress (Brummett, et al., 2008; Eley, et al., 2004). A longitudinal study with repeated measures over time would have been a better method of establishing chronicity of stress, and assessment of the relationship between levels of chronic stress and development of depressive or anxiety disorders, the central tenet of this chapter.

Whilst K10 scores suggest an effect of genotype in females, an effect of gender or genotype on diagnosis of PHQ anxiety or depression or on trait anxiety 139 (neuroticism) was not observed, suggesting that the gender specific effect of genotype was primarily exhibited in subthreshold anxiety. This is consistent with previous studies which have used continuous measures to detect subthreshold states of either depression (Brummett, et al., 2008; Eley, et al., 2004; Sjoberg, et al., 2006) or mental and physical distress (Grabe, et al., 2005),or sub-threshold state anxiety (Gonda, et al., 2007). The latter authors investigated the association of 5HTTLPR on sub-threshold anxiety in migraine in women and found that ‘s’ allele carriers had significantly higher levels of state anxiety than those homozygous for the ‘l’ allele. The K10 scale in the present study detected psychological distress across a continuum of severity, which allowed identification of sub-threshold symptoms of anxiety. Alternatively a larger sample size may have been required to produce a higher yield of depression and anxiety caseness in order to detect significant 5HTTLPR associations.

While there was no significant gender-specific effect of genotype on neuroticism scores, females demonstrated a trend towards higher neuroticism scores among the s/s genotype group. To date there have been two published studies that also report no association between the ‘s’ allele and neuroticism as measured by the NEO-FFI (Ball, et al., 1997; Deary, et al., 1999). Both compared prevalence of the s allele amongst participants selected from the top and bottom extremes of the distribution of neuroticism scores and concluded that negative findings may reflect the fact that 5-HTT polymorphisms may be associated with a normal range of neuroticism scores but not the extremes.

There may also be specific sex differences in serotonergic function; rates of 5HT synthesis are approximately fifty percent higher in males than females (Nishizawa, et al., 1997) and density of the 5HT1A autoreceptor is lower in the brains of women than men (Costes, et al., 2005). However, this does not explain the effect of 5-HTTLPR genotype. Gotlib and colleagues found in a sample of female subjects that s/s genotype individuals show greater and more prolonged cortisol release in response to a laboratory stressor (Gotlib, et al.

140 2008). Increased stress responsivity in females may be explained by gender differences in susceptibility to HPA axis dysregulation (as evidenced by rodent studies discussed earlier) in which the hypothalamus may continuously stimulate pituitary production of ACTH irrespective of blood cortisol concentrations. Sustained cortisol release in turn results in higher basal stress levels, predisposing the individual to further anxiety and depression. Female susceptibility to HPA axis dysregulation is hypothesised to be due to activity of gonadal steroid hormones; castration of male rats increases the secretion of adrenalin in response to physical stressors, whilst in both male and female rats, oestrogen administration increases basal corticosterone secretion as well as ACTH and corticosterone response to stress (Handa, et al., 1994). Prospective evidence for an interaction between serotonin transporter genotype and physiological effects of chronic stress is provided by a study on rhesus macaques which found that stress in the form of peer rearing interacts with serotonin transporter gene to promote increased ACTH response to acute stress, but only among female animals (Barr, et al., 2004). Thus preliminary evidence from animal studies suggests that adversity interacts with genotype to promote gender-specific distress later in life.

DM compromises monoaminergic neurotransmission, as evidenced by two studies on rodents. In the first (Petrisiü, et al., 1997), the authors found that DM contributes to decreased 5HT turnover in the central nervous system, while the second featuring Streptozocin-induced T1DM in rats (Miyata, et al., 2007) demonstrated decreased 5HT response to stress in the prefrontal cortex. Taken together, these studies suggest a potential role for the 5-HTTLPR in stress regulation in PWD. Further investigation is required featuring healthy control populations before any conclusions implicating 5-HTTLPR moderated stress pathways specific to DM can be drawn.

Szily et al. (2008) found in their study on the 5-HTTLPR and emotional appraisal that participants with the ‘s’ allele experience negative emotions as more intense and felt less able to cope with stressors. The search for endophenotypes mediating between the ‘s’ allele and emotional reactivity will

141 enhance understanding of the mechanisms related to emotional regulation and designing of appropriate interventions to meet the need of this sub-population. Emotional regulation techniques such as mindfulness meditation can target higher emotional reactivity in ‘s’ allele carriers. Those whose genotypes have been identified may benefit from appropriate interventions.

8.5. Conclusion

This study suggests that females with the s/s genotype of the 5-HTTLPR are a potentially vulnerable group. Future gene x environment studies with larger sample sizes and longitudinal design should consider the relative contribution of acute and chronic stressors with the 5-HTTLPR. Identification of PWD sub- populations according to gender and genotype in future research and the measuring of physiological stress markers in particular can help determine the benefit of emotional regulation interventions in highly susceptible genetically predisposed individuals.

142 CHAPTER 9: DIABETES-SPECIFIC EMOTIONAL DISTRESS AND ITS RELATIONSHIP TO DEPRESSION AND GLYCAEMIC CONTROL IN TYPE 1 AND TYPE 2 DM

ABSTRACT

Introduction: Negative emotional reactions to daily DM care are a significant issue for most people with diabetes (PWD). These problems are not routinely discussed with clinicians, resulting in significant illness burden and morbidity. Objectives: This chapter aims to identify a subpopulation of PWD experiencing specific DM-related distress and to examine its relationship with depressive disorder and glycaemic control. Methods: A total of 184 participants recruited into the Stress Sampler Study responded to the PAID, PHQ, K10 and SF-12 questionnaires. Glycosylated haemoglobin (HbA1c) taken on the day of recruitment was recorded from the case notes. Results: DM-related distress as measured by the PAID correlated positively with PHQ-9 depression scores (p< 0.01), with generic psychological distress as measured by the K10 (p< 0.01), health-related quality of life as measured by the SF-12 MCS (p< 0.01) and with HbA1c (p< 0.01). PAID correlated negatively with age (p<0.01). Regression analysis revealed a significant predictive ability of PAID on depression scores (having controlled for SF-12 scores). Past history of depression also predicted PAID scores (p< 0.05) after having controlled for current depression scores. Conclusion: PWD with high levels of DM-specific distress, as measured by the PAID, constitute a group who are at significant risk of depression and impaired glycaemic control. The PAID has potential as a screening tool for its simplicity and prediction of other adverse psychological outcomes.

143 9.1. Introduction

People with diabetes (PWD) encounter many chronic stressors related to their condition, including worry about complications, fear of hypoglycaemia and obligatory preoccupation with food, exercise and dietary regimens (Rubin & Peyrot 2001). These “daily hassles” present as problems associated with the illness itself (eg. complications or disability) or with enforced changes brought about by the illness (eg. diet and exercise). Distress can also arise out of misplaced illness beliefs, lack of knowledge or social support or from simply being overwhelmed by the illness and its requirements. Chronic DM-related distress is also associated with increased rates of frank psychiatric disorders such as depression (Hermanns 2006), (Pouwer 2005), as well as DM-related complications, poor glycaemic control and non-adherence (Polonsky, et al., 1995).

Fisher et al. (2007) distinguished between clinical depression, general psychological distress and DM-specific distress, measured with the Diabetes Distress Scale (Polonsky, et al., 2005). They reported that many PWD experience high levels of depressive symptoms but are not clinically depressed. They also noted that psychological interventions for distress are predicated on the treatment experience with depression and may not be as appropriate for DM-specific distress. Gonzalez et al. (2008) reinforced the position of DM- specific distress as a separate entity by establishing different outcomes than that of depression in T2DM. These studies suggest that DM-specific distress is a unique psychological adjustment entity that taps into a separate area of distress (from depressive disorder or general distress) and that the PAID has established validity to detect levels of distress in different DM populations.

This chapter aims to assess the performance of the PAID in identifying the main areas of distress resulting from DM and to test the PAID’s association with glycaemic control, current depression and history of past depression in a

144 population of people with T1 and T2DM attending two public hospital specialist DM services.

The hypotheses are that: 1) Higher levels of DM-related distress are associated with higher depression scores and impaired glycaemic control (higher HbA1c levels);

2) PWD with present, but not past, history of depression have higher levels of DM-related distress.

9.2. Research Design and Methods

The detailed methodology of this study has been described in Chapter 3. A summary of the methodological procedures relevant to this chapter is described here.

The study was carried out at the Diabetes Clinics at St.Vincent’s Hospital and the Prince of Wales Hospital, Sydney. Recruitment was conducted from July 2006 till March 2008. Research assistants who explained the research methodology approached PWD waiting for their appointments at these two clinics. PWD who provided written consent were directed to the main investigator who obtained a brief clinical history and administered the relevant questionnaires. Responses on the PAID, PHQ and SF-12 questionnaires will be analysed in this chapter. The latest glycosylated haemoglobin (HbA1c) levels were recorded from individual case notes or on-line records.

145 9.3. Statistics

Principal Components Analysis was performed on the PAID Questionnaire to ascertain its factor structure. Student’s t-tests were used to compare mean scores of relevant scales between comparison groups. Chi-square tests were utilised to compare proportions and PAID item-specific differences between major depressive cases and non-cases. Pearson correlation tests were used to measure correlations between the continuous scales. ANCOVA was used to assess the effect of past depression history on PAID scores, while controlling for current depression (PHQ-9) scores. Multiple Regression analyses to assess the predictive ability of the PAID on PHQ-9 depressive scores and glycosylated haemoglobin (HbA1c) were carried out. All statistical analyses were conducted using SPSS Version 16.0.

9.4. Results

9.4.1. Psychometric properties of PAID – Principal Components Analysis and Internal Reliability (Cronbach’s alpha)

A Principal Components Analysis (PCA) performed to assess factor structure of the PAID found that the total variance explained produced only 2 factors with eigenvalues more than 1, explaining 63.44 % of the variance, with the first factor explaining 57.00 % of the variance. The scree plot demonstrated a clear break between the first two factors. The PAID was thus maintained as a single factor instrument, as described elsewhere (Welch, et al., 2003). The internal reliability of the scale (Cronbach’s Į) was 0.96.

146 9.4.2. Common DM distress items

A total of 184 participants responded to the questionnaires. For the whole sample, the most commonly reported issues as “somewhat serious” or “serious” were “ worry about future and complications” (30.9%), “constant concern with eating” (24.1%) and “feeling guilty when off track management” (23.1%) respectively. For people with T1DM, the most important issues were “worry about future and complications”, “feeling burnt-out” and “worry about low blood sugar reactions”, and for people with T2DM, “lack of DM goals”, “feeling discouraged by DM treatment plan” and “feeling deprived of food” were the most important issues. There were no statistically significant differences in total PAID scores related to type of DM or gender.

9.4.3. Discriminant Validity of PAID in relation to presence of major depression

There was a significant difference in mean total PAID scores between those with and without a diagnosis of current PHQ-derived major depression (t = - 5.95, p < 0.01). An item-by-item comparison of those reporting each item as “somewhat serious” or “serious” with those reporting as “none”, “minor” or “moderate” demonstrated that every item discriminated between those who did and did not have major depression (see Table 9.1).

147 Table 9.1: Percentage of “somewhat serious”/”serious” responses on the individual items of the PAID comparing major depression cases vs. non-cases

PAID Item Major Non-Cases Chi-square P value Depression N = 155 statistic Cases N = 29 1 31.8 % 12.4 % 5.85 0.036 2 50.0 % 7.7 % 31.71 0.000 3 54.5 % 9.5 % 31.62 0.000 4 45.5 % 13.0 % 14.69 0.000 5 54.5 % 11.2 % 26.85 0.000 6 59.1 % 11.9 % 30.18 0.000 7 59.1 % 13.7 % 26.11 0.000 8 45.5 % 11.8 % 16.62 0.000 9 40.9 % 13.6 % 10.40 0.003 10 36.4 % 8.9 % 13.89 0.001 11 54.5 % 20.1 % 12.62 0.001 12 63.6 % 26.6 % 12.49 0.001 13 59.1 % 18.3 % 18.23 0.000 14 36.4 % 6.6 % 19.06 0.000 15 19.0 % 1.8 % 15.50 0.001 16 36.4 % 9.5 % 12.81 0.001 17 45.5 % 7.7 % 9.28 0.000 18 27.3 % 7.1 % 9.28 0.008 19 54.5 % 11.8 % 25.46 0.000 20 54.5 % 16.0 % 17.82 0.000

148 9.4.4. Correlations between variables of interest

There was a significant negative correlation between PAID scores with participant age (r = -0.288, p <0.01) but not with duration of illness (r = 0.081, p = 0.325), mirroring the finding of cross-sectional studies described elsewhere (Welch, et al., 1997, Delahanty, et al., 2007). Looking at results from Table 9.2 (below) the PAID was significantly correlated with all of these measures and also with HbA1c levels but not the SF12-PCS.

Table 9.2: Intercorrelations, Means and Standard Deviations for instruments of interest and glycosylated haemoglobin (HbA1c)

Measure SF-12 SF-12 K-10 PHQ-9 HbA1c Mean SD MCS PCS PAID -0.48** -0.12 0.56** 0.50** 0.34** 26.32 23.07 SF- -0.03 - -0.62** -0.03 48.36 11.07 12MCS 0.69** SF- --0.24** 0.02 42.39 10.80 12PCS 0.19** K-10 0.83** 0.12 17.16 7.36 PHQ-9 0.12 5.87 5.57 HbA1c 7.75 1.63 **p < 0.01

9.4.5. Effect of past depression history on PAID scores

A one-way between-groups analysis of covariance (ANCOVA) was conducted to test the effect of past depression history on PAID score having controlled for current depression (PHQ-9) score. PWD with a past depression history

149 exhibited significantly higher PAID scores than those without [(F1, 149) = 4.179, p = 0.043, partial eta squared = 0.026].

9.4.6. Hierarchical Multiple Linear Regression Analyses

Tests of multicolinearity were carried out for the variables involved in both regression equations and were found to be negative.

9.4.6.1. Model 1: PAID as predictor of HbA1c

Hierarchical regression analysis was used to assess the ability of the PAID (as a DM-specific psychological distress measure) to predict glycosylated haemoglobin (HbA1c) scores after controlling for type of DM, duration of illness and age, SF-12 MCS and PHQ-9 scores (Table 9.3). After the variables in Block 1 (duration of illness, age, and Type of DM) were entered, the overall model explained 6.2% of the total variance. After Block 2 variables SF-12 MCS and PHQ-9 were entered, the model explained 7.1% (an extra 0.9% only) of the variance. After entering the variable of interest PAID, the model explained 17.8% of the variance [(F (6,150) = 5.181, p < 0.01]. Thus, the PAID explained an additional 10.7% of the variance in HbA1c scores and was the only variable that significantly predicted HbA1c levels (ß =0.404, p < 0.01).

150 Table 9.3: Hierarchical Regression Analysis summary for specific diabetes distress (PAID) predicting glycosylated haemoglobin (HbA1c)

Variable B SEB Ǻ R2 ¨R2 Step 1 0.062 Age -0.015 0.011 -0.127 Duration of 0.031 0.013 0.227* Illness Diabetes 0.120 0.389 0.033 Type Step 2 0.071 0.009 PHQ-9 0.037 0.031 0.127 SF-12MCS 0.011 0.016 0.074 Step 3 0.178 0.106 PAID 0.029 0.007 0.404** *p < 0.05 **p < 0.01

9.4.6.2. Model 2: PAID as predictor of PHQ-9

A further hierarchical regression analysis was performed to assess the PAID’s ability to predict PHQ-9 depression scores after controlling for type of DM, duration of illness, age and SF-12 MCS. The model explained 42.3% of the variance when SF12-MCS was included, which increased to 46.1% [(F (5,150) = 24.76, p < 0.001] when the PAID was added.

151 Table 9.4: Hierarchical Regression Analysis summary for specific diabetes distress (PAID) predicting depression scores (PHQ-9)

Variable B SEB Ǻ R2 ¨R2 Step 1 0.078 Age -0.111 0.037 -0.272 Duration of 0.101 0.045 0.213 Illness Type of DM 3.697 1.319 0.295** Step 2 0.423 0.345 SF-12MCS -0.308 0.033 -0.613** Step 3 0.461 0.037 PAID 0.056 0.018 0.231** *p < 0.05, **p < 0.01

9.5. Discussion

The PAID proved ‘user friendly’ and was well accepted by the patient group. Although a large amount of the variance in the model predicting present depression scores in this study was explained by generic emotional concerns about health (SF-12 MCS), DM-specific distress, measured by the PAID, contributed significantly to the variance in current depression scores after controlling for the effect of SF-12 MCS. This suggests that DM-specific distress measures distress over and above the general distress scores from other measures that contribute an added risk for depression in PWD.

There are several possibilities to consider in the relationship between depression and DM-related distress in this cohort. Depressive symptoms may exacerbate the psychological burden of DM or lead to exaggerated reporting of DM-distress items. Also, chronic DM-related distress may be a risk factor for

152 greater reporting of depressive symptoms or there may be a common underlying mechanism to both diabetes-related distress and depression, such as anger (Yi, et al., 2008). It would be useful to be able to repeat the PAID when depression symptoms have subsided or when depressive disorder is in remission as a means of eliminating the possibility of biased reporting in depressed PWD.

The persistence and recurrence of episodes of depression in PWD is an important issue. Peyrot & Rubin (1999) report that up to 13% of people with T1DM or T2DM were persistently depressed over a 6-month period. Lustman et al. (1997) followed up 25 PWD over a five-year period and reported recurrence or persistence of depression in 92% of the patients with an average of 4.8 episodes over the five-year period. The finding in this study of high levels of DM-related distress in PWD with past history of depression but in current remission raises several issues. Importantly, people with a past history of depression were prone to experience high levels of DM-related distress, even after recovery from their depressive episode. This may be due to premorbid psychological vulnerability and/or lingering depressive symptoms, or negative cognitions that could be present even in a state of complete remission. The negative cognitions could give rise to intense emotional responses to issues surrounding DM for example, self-blame, guilt and worry. It is likely that longitudinal studies following PWD from the time of diagnosis, through the various stages of the illness, charting concerns and reactions towards the illness and screening for symptoms of depression could reveal more insights into possible pathways between past depression and DM-related distress.

As Surwit (1993) demonstrated that stress triggers several pathways, including the HPA axis, and contribute to persistently elevated glycaemic levels, it would be reasonable to expect that both generic psychological measures of stress (K10) or depression (PHQ-9) would be predictive of HbA1c. However, DM- related distress, as measured by the PAID, was the only psychological construct in this study to significantly predict glycosylated haemoglobin (HbA1c) levels. Polonsky’s group (1995) had previously reported a 9% variance on the 153 effect of PAID on baseline HbA1c in their longitudinal study. This suggests that a contribution from specific diabetes-related behaviours with persistently high PAID scores is associated with poor DM compliance or maladaptive treatment behaviours leading to high HbA1c levels. The attempt to improve glycaemic control by knowledge transfer alone is often shown to be without benefit, possibly at least in part due to failure to consider the connections described between diabetes related stress, depression and maladaptive behaviours.

The association between lower PAID scores and increased age suggests either better emotional regulation in older patients and/or increased capacity of dealing with daily hassles. This could be with accrual of life experience or as the result of specific interventions to learn self-management skills that have been shown to decrease HbA1c levels.

Through the life span, DM’s impact is likely to relate to the relevant developmental tasks and the stage of ‘illness journey’, personality and coping style, social support, general life experience and cultural context. For example, a new diagnosis of T1DM in a young person in the throes of adolescent turmoil is likely to have a different impact than the same diagnosis in a married middle- aged adult with a career and a family. There are claims that shaping of desirable DM-related habits early on in the condition predisposes individuals to better longer-term adaptation (Snoek & Skinner 2005). All these are plausible factors explaining the potential role of adaptation to stressors longitudinally. Rapaport et al. (2000) in their article on DM through the lifespan focused on T2DM, citing losses, shame, guilt, self-blame, denial and lifestyle changes as significant issues contributing to daily hassles. The task of appreciating and assisting PWD in negotiating the various phases of the illness and moving to new challenges can be shared between patients, carers and their clinicians. The usage of a wide array of brief psychosocial intervention strategies within a multi-disciplinary team would be an effective approach to address these daily hassles of diverse PWD sub-populations.

154 Although there were no significant differences in total PAID scores between T1DM and T2DM, qualitative differences in terms of the major areas of DM- distress were reported similar to that described by Polonsky et al. (1995) and Welch et al. (1997). It is useful to understand the different areas of DM-related distress with respect to Type of DM. In this study, these related to anxieties about hypoglycaemic reactions and diabetic complications for those with T1DM and concerns about lack of goal-setting and food intake for those with T2DM. It would be possible to design specific psychological interventions to address these concerns for the two groups. A Norwegian program (Karlsen 2004) designed to assist people in adjusting to DM reported improvement in HbA1C levels for those participating. Such programs could fruitfully use the PAID to identify specific problems and provide feedback about progress. The findings about the importance of identifying past and present episodes of depression resonate with a recent study reporting that the presence of depression in DM is associated with significantly increased mortality, which was not restricted to cardiovascular causes (Lin 2009). Thus, early detection of distress with appropriate help could improve glycaemic control as well as prevent more serious outcomes.

In the first chapter, it was established that the rates for nondetection of depression in PWD are high, especially among non-psychiatrist physicians. It is often difficult to broach emotional issues in general medical settings, due to the physical context, time constraints of routine consultations and perceived irrelevance or obstacles to raising emotional topics by clinicians and patients. It is possible that both clinicians and PWD may be more willing to discuss emotional issues in the context of ‘DM-related distress’ rather than generic psychological distress or “open-ended” questions about depression or anxiety and the PAID seems to offer an entry point to such a discussion.

Administering the PAID to patients before consultation with their diabetes clinician could facilitate patient-clinician discussion about particular psychological issues which are a bane to the patient. The PAID has some utility as a depression screen but is best complemented with a depression or generic 155 psychological distress measure such as the K10, or PHQ-9. This practice forms a basis for the designing of psychosocial interventions to meet individual patient needs.

Early detection and intervention is vital to ensuring good psychological adaptation and perhaps prevention of frank psychiatric disorders in DM. Further research is needed to establish if early screening and intervention of DM helps enhance healthy coping and reduce the onset of frank psychological disorders such as depression in the long term. In Chapter 7, it was reported that emotional–expression and avoidance coping was significantly positively correlated with PAID scores. This finding suggests that the effect of avoidance coping in DM is visible in emotional reactions to DM, besides depression.

While the DM-related approach suggests a more problem-orientated coping approach, some patients may be overwhelmed by their condition and/or have more general problems with emotional regulation. Here interventions improving emotional regulation may be more suitable. The benefit of offering emotional- regulation interventions for this group have been emphasised by other authors. Smyth (2009) has noted that importance should be given to emotional- regulation interventions in people with chronic conditions. The PAID therefore may help identify specific areas causing emotional distress in PWD. Delahanty et al. (2007) suggested that interventions target the common themes of “worry about the future and complications” and feelings of guilt and anxiety which was also prominent in this study, while Fisher et al. (2007) recommended designing and tailoring coping-based interventions for PWD with high levels of DM-related distress as distinct from those with sub-clinical or clinical depression.

The findings from this study suggest that the PAID can discriminate between depressed and non-depressed subjects, consistent with results elsewhere (Hermanns, et al., 2006, Pouwer et al., 2006). The proposal to use the PAID as a screening instrument requires discussion on cut-off score. Hermanns et al. (2006) suggest a cut-off score of 38 as a means of screening for clinical depression and a cut-off score of 33 for sub-clinical depressions. While a cut- 156 off score is useful, the qualitative aspects could be more useful to identify key issues for discussion and possibly referral to a mental health or behavioural expert. Welch et al. (1997) reports using (mean score + 1 standard deviation) as a cut-off score in their clinical practice but also suggest that clinicians and patients could identify and target individual items that are a source of great distress.

9.6. Limitations

The population in this study generally comprised of PWD who were likely to have significant medical issues (being a specialist clinic). Moreover the design of the study was cross-sectional meaning that any interpretation and recommendation to clinical service development has to be interpreted with caution. The PAID items are all negatively worded and are an issue when measuring “adjustment” to diabetes as conceptualised by its designers. A mixed “positively” and “negatively” worded instrument could be designed to capture DM-related emotional distress in the future, which would be useful also to gauge the progress of coping-based interventions. Past history of depression in this cohort was measured by a subjective clinical interview, rather than a semi-structured diagnostic interview.

9.7. Conclusion

Chronic DM-related distress is a significant component of DM and is significantly related to HbA1C levels. DM-related hassles should be identified and require attention by clinicians. It appears that failure to address them may lead to adverse illness outcomes and comorbidity in DM. Screening using the PAID is justified, as the majority do not readily volunteer emotional aspects around their DM care. The results from this study suggest that PWD experiencing higher levels of DM-related psychological distress are more likely to be currently depressed. Distress is also associated with past history of 157 depression, and depression in diabetes is itself associated with higher morbidity and mortality. The association with past and present depression, whatever the direction of causality, suggests the need to screen for current and past depressive symptoms and also to consider depression in PWD who have high PAID scores.

158 CHAPTER 10: FINAL CONCLUSION AND CLOSING REMARKS

This thesis was part of a research project aiming to identify individuals who would benefit from minimal contact stress management interventions for PWD. The original idea was to identify factors that could predict who would benefit overall and whether there were PWD who would differentially benefit from emotional-regulation compared to problem-focused interventions. The factors considered included personality factors, medical illness (DM and other comorbidity), psychological health and psychiatric comorbidity, with an emphasis on depression. There was a particular focus on identifying highly stress-reactive individuals (typified here by those who were younger, with high neuroticism scores and females with the s/s genotype) who were more prone to distress and may require more attention to emotional regulation rather than a standard problem solving approach. The high dropout rates however prevented the investigators from drawing conclusions about the efficacy of the interventions (as discussed in Chapter 5).

This chapter seeks to integrate the study findings and to consider their practical clinical and research applications.

The thesis reports several important findings that are of relevance with regard to tailoring interventions to meet individual need. The first literature review chapter established the extent of the psychological burden of DM and recommended the provision of stratified brief psychosocial interventions as part of the armamentarium of routine DM care. The next chapter focused on the state of the literature on psychosocial interventions in DM. This section uncovered a need for tailored brief psychosocial interventions, which were found to be lacking in the literature. A majority of interventions targeted generic PWD populations, rather than specific sub-populations, and the outcomes measured

159 were largely DM related for example, HbA1c. The chapter suggested that a feasible method of streamlining psychosocial interventions for PWD would be to study the demographic, individual and disease characteristics of PWD subpopulations before designing tailored interventions.

Chapter 4 identified probable PWD subpopulations from within the study cohort that could benefit from tailored brief interventions. The subsequent chapters built on the preliminary findings by further exploring the psychosocial needs of these subpopulations. The role of coping strategies in predicting psychological outcomes in DM was explored with results establishing significant relationships between independent and dependent variables of interest. The psychological endophenotypes of interest were avoidance and emotional-expression coping. PCA separated emotional-expression coping strategies from “adaptive” emotion-focused strategies. The avoidance coping factor and the emotional- expression factor showed significant associations with DM-related psychological distress (PAID) and depression scores. By identifying this subpopulation, I have suggested that these generally “maladaptive” coping styles can be modified by the provision of brief coping-based interventions for example, emotional regulation techniques. The emphasis on coping style in the current study is consistent with moves in recent research away from “pathologising” psychological morbidity in DM to a more positive perspective, to the science of healthy adjustment and coping, of re-enforcing positive attitudes and behaviours.

It was of interest to identify an emotionally reactive group based on genetic predisposition, in this case the 5-HTTLPR. In the process of trying to establish a highly emotionally reactive group, this study identified one such sub- population, females with the s/s genotype, who had significantly higher levels of psychological distress, reflected by K10 anxiety subscale scores. New findings concerning the 5-HTTLPR in female PWD from this study contribute to the growing scientific evidence of this polymorphism. This finding though should be interpreted with caution due to the small sample size and lack of control group or physiological stress indicators in this study. The findings are in line with 160 other studies in chronically stressed populations as discussed in chapter 8. The results from this genetic study suggest that chronic DM-related distress could be an environmental factor in the G x E interaction for 5-HTTLPR links with anxiety or depressive phenotypes. The search for endophenotypes mediating these interactions has not been given adequate consideration, particularly in populations facing chronic stressors like DM. Discovery of endophenotypes will give us insights into pathways mediating the gene x environment interactions, paving the way for the trialing of interventions to address individual needs.

This study also highlighted the significant psychological burden of those with a high degree of daily DM hassles (as measured by the PAID questionnaire). Higher PAID scores were associated with higher levels of non-specific psychological distress and depression. Also a positive past depression history was associated with elevated PAID scores, after controlling for current depression scores. Most interestingly, DM-related distress was the only psychological entity in this study to be significantly associated with HbA1c levels. The learning point from this section is that interventions could have a psychological focus with an aim to regulate emotions, running in parallel with structured problem-orientated strategies. Thus the attention of both DM clinicians and PWD with significant daily hassles would have to be drawn towards stress modulation, besides focusing on problem-focused strategies that directly tackle the issues related to DM care.

It is desirable to take into account individual preferences when designing interventions. The individual perspective also takes into consideration what the PWD thinks is important, that is to address patient priorities and preference. Taking into account the attrition rates in this study, it was discussed that some effort to study the individual preferences of PWD, in choosing from a selection of practical yet effective interventions would be the mainstay for future work in this area. In the planning stages of the study, a design that was based on patient preference rather than allocating patients to intervention groups was considered and in retrospect, this could have led to greater retention rates.

161 Future research could focus on patient preference trials, which have been receiving coverage in the literature in recent years.

The need to interface with DM clinic services provides the consultation-liaison (CL) psychiatry team with an opportunity to use collaborative approaches in delivering an effective service. Faced with limited resources and a need to provide services across and the entire general hospital, it is important to have an efficient, workable system that meets the needs of clinicians and patients. The DM service had also requested the CL service to provide education and training. The CL Psychiatry service offered modules including psychological screening and management of common psychological issues and DM-related distress and the application of the principles of motivational interviewing in the diabetes service context. These workshop modules were well received by the team and were complemented by periodic updates about the progress of the study.

A major issue for CL psychiatrists is that the needs of patients seen in a public hospital DM service are complex and the simple application of conventional diagnostic criteria to determine management care plans is insufficient. The DM service at St. Vincent’s Hospital had asked the CL service to provide assistance in screening and triaging to meet the diverse needs of PWD within the Diabetes Service. The study findings suggest useful screening approaches for psychological morbidity in DM using quick and reliable instruments. This approach could result in more effective consultations and liaison by the CL team member within the DM service. The PAID has been discussed in detail in Chapter 9 and is proposed as a suitable measure to screen for daily hassles as well as the likelihood of a depressive disorder. It is worthwhile taking into account that Hermanns et al. (2006) found that the PAID performed better than a normal clinical interview as a screening method for depressive disorder in DM.

The K10 is selected as the other standard screening instrument for general psychological distress. Furukawa et al. (2003) found that the K10 had better discriminatory validity than the GHQ-12 in detecting DSM-IV depressive and 162 anxiety disorders. The K10 is thus suitable for use for screening in general health-care settings including DM clinics. In this study, the K10 (discussed in Chapters 7 and 8) demonstrated sensitivity in identifying a vulnerable group, females with the s/s genotype.

The PHQ proved useful as a ’first pass’ mechanism to generate diagnostic information that can be followed up by a psychiatric interview. The suggested emphasis on DM stressors and individual coping styles as well as formal psychiatric diagnoses helps to create a broader understanding of PWD. These added insights have been well accepted by the diabetes service.

Figure 10.1 describes the recommended screening strategy and intervention pathways using the PHQ-9, PAID and K10 questionnaires.

Figure 10.1 provides a proposed scheme for incorporating screening measures into a diabetes service but could also be used in a primary care setting. It is intended as a guide to creating care pathways to meet the potential needs of patients, including provision of brief interventions. These measures can be supplemented by the other data I have reported that are readily obtainable from medical file (age, type of diabetes and comorbidities). The scheme is a top down ‘stepped care’ approach, suggesting that depression and other psychiatric disorders be identified and managed first.

The proposed care scheme does not discriminate between DM types but uses diabetes-related problems as a guide to the need for psychological interventions. The specific differences related to current age and specific illness-related issues will also be relevant to the provision of psychological interventions.

In summary, as a means of broad dissemination in a diabetes clinic, brief psychological interventions such as those used in this study are ineffective unless stratified according to individual patient needs. This includes taking into account individual preferences and psychological needs. Totally unsupported 163 interventions may not be ideal for everyone; some guidance from a clinician involved in the individual’s health-care may help enhance individual interest and engagement in such interventions.

As a consultant psychiatrist with a special interest in consultation-liaison psychiatry, I had been searching for appropriate models of care that can be easily applied to general medical settings. In the past I adhered steadfastly with the various diagnostic criteria including the DSM-IV. The 3-year stint with the CL-DM service and this research project has provided me with new insights. I now appreciate the importance of identifying and screening for sub-populations who could benefit from brief psychological interventions. I have derived personal satisfaction from exchanging ideas with the DM team – simple suggestions, encouragement, just being there to support each other in a shared-care environment. These skills can be taken to other medical disciplines, too. I had embarked on the research thinking that the focus would be just like any other RCT, with treatment efficacy as the main outcome. In the end it was the bigger picture that was the focus of this thesis - that of a service- based perspective, rather than merely a clinical research perspective. It has been a fulfilling experience working with the staff and patients at the DM clinics in the two hospitals, one that has inspired me to look forward to further contribution in this field.

My philosophy as a medical practitioner has always been to approach my patients from a holistic model of care. Psychiatry is everyday medicine. We attend to the psychological health of our patients directly or indirectly everyday, in every field of medicine. Bridging this mind-body interface is what I hope to achieve in my future clinical work.

164 Figure 10.1 Suggested pathways for using screening instruments to guide provision on psychiatric assessment and treatment and psychosocial interventions in a diabetic service

K-10, PHQ, PAID used routinely as screening tools

High PAID + High K10 High PAID Low PAID Low K10 Low K10 Psychiatric conditions

Check past and present Check illness stage, Check DM information, depression, other coping style, life context lifestyle, wellbeing, NOÎ NOÎ psychiatric conditions and any previous self-management

YES YES YES Aim: to treat depression, Aim: to improve Aim: to improve self other psychiatric resilience, emotional care, address specific conditions*, then review regulation+, then review issues using education

* multimodal approach tailored to individual, delivered by CL psychiatrist, psychologist and/or GP 165 + group or individual approach for brief interventions delivered by psychologist, in conjunction with diabetes service # chronic disease self management involving DM educator and other team members REFERENCES

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192 ACKNOWLEDGEMENTS

For my wife, Mary, and I, this thesis is the culmination of a four-year journey. When I embarked on this pathway in 2005, the idea was a year’s stint to get some experience and training in consultation-liaison psychiatry. In December 2004, I corresponded with Professor Kay Wilhelm at the St. Vincent’s Consultation-Liaison Psychiatry service, Sydney. Preliminary discussions paved the way for a clinical attachment with the service, and the idea to collaborate with the Diabetes Centre to help develop practical psychological intervention strategies for people with diabetes. This is when the idea of doing a PhD. came about.

The first person to thank is Kay Wilhelm for your supervision and dedication and support throughout the tenure of my stay and work in Sydney. Many, many coffee sessions later, here I am! Thank you for sharing your philosophy and your outlook towards the practice of psychiatry in general. Thank you most of all for your belief in my ability, especially during those difficult days when I doubted myself.

A word of gratitude goes out to my co-supervisor, Professor Philip Mitchell for always taking a step back and providing constructive feedback on my work. I would like to thank Dr Karen Baikie, for her guidance in methodology and intervention design, especially during the early days of the research project. Professor Peter Schofield provided the research project with the vital link with facilities for genetics testing. Thank you and your team at the Prince of Wales Medical Research Institute for your guidance and constant interest in the study.

The research team was based at the Black Dog Institute. I would like to thank Professor Gordon Parker, Director of the Black Dog Institute for supporting the team throughout the study duration.

193 My fellow researchers at the Black Dog Institute provided a sounding board whenever I needed someone to test my hypotheses and ideas. Thank you also for following up the participants and critiquing my work.

The participants of the study deserve a big word of thanks; they made the study possible and worthwhile.

The Diabetes centre staff, firstly at St. Vincent’s Hospital. A special word of thanks goes out to Professor Lesley Campbell and Jan Alford for collaborating and providing feedback throughout the study. At the Prince of Wales Hospital, Kirsty Boltong was the central figure, providing access to the clinic facilities and services. A round of thanks goes out to all staff at both diabetes centres.

The CL Psychiatry team at St.Vincent’s Hospital who made me feel part of the team, with a special thanks to Andrea Millar for assisting with some of the research material.

The opportunity to pursue the PhD in Sydney was made possible with the support of my colleagues and head of department at the Department of Psychiatry, Hospital Universiti Kebangsaan Malaysia (HUKM) in Kuala Lumpur. Thank you so much for giving me your blessings to take the time off my duties to pursue this dream. I hope that my work will contribute towards the development of consultation-liaison psychiatry at HUKM.

In Sydney, Mary and I had the pleasure of an extended family, which included my ex-schoolmates, Andrew Ong and Brian De Padua. Andrew particularly was an inspiration, having recently completed his PhD in interventional cardiology. Thank you, Andrew and Brian, for opening your homes to us and being family.

Our circle of friends and relatives in Sydney with whom we spent many a day enjoying a meal or a weekend out at the Blue Mountains, thank you for the

194 memories, you certainly made my journey easier, especially when the going was tough.

In Sydney, I also had the opportunity of renewing family ties with my maternal uncle, Fabian Reddy and cousin Rajiv. I am grateful to have had this pleasure of ‘getting to know’ you all having lived in different countries all these years.

I have left the people who are the closest to the last: This journey was encountered with great difficulty when my mother passed away in the final year of my candidature. During that difficult time, my siblings and I rallied together to provide support for each other. My parents migrated to Malaysia from India in the 1950s. They worked hard to ensure we all received a good education. My mother was always there for me and constantly encouraged me to achieve the best in my educational pursuits. My father worked hard as a teacher and a headmaster to ensure that we were all provided with the basic needs and comforts. To my father, I would like to express my love and appreciation for all that you have done for me. This thesis would not have been possible without your endurance and sacrifices.

I would like to appreciate my deepest words of love and gratitude to my four siblings.

To Jaypaul, for always believing in my ability and giving me the gift of your taste of music through the years. The short holidays in New Zealand with you, Cecilia, Mark and Katrina were certainly welcome breaks from the arduous thesis writing. To Viji, for being a strong source of support and “holding the fort” in Kuala Lumpur. Thank you also for accompanying me on registration day for the PhD (just like you had done for my primary school and undergraduate registration ironically!). To Cecy, for accompanying me during the walks we had after our mother’s passing. To Sujatha, for being the closest family member in Melbourne. Thank you for caring for me and preparing excellent meals during my short breaks at your house, not forgetting the company of Roland, Gerard and Gerald.

195 Lastly, to my wife, Mary, who walked with me through all the ups and downs during my candidature. Your constant support and encouragement is more than I can ever ask for. Staying up till the wee hours of morning to format this work is testimony of your sharing in my vocation and future success.

This thesis is dedicated to my late mother, Maria Theresa Reddy, for being there, for making sure I pushed myself that extra mile in the pursuit of excellence.

196 APPENDICES

197