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Protocol for the development and validation of a measure of persistent psychological and emotional distress in cardiac patients: The Cardiac Distress Inventory ForJournal: peerBMJ Open review only Manuscript ID bmjopen-2019-034946

Article Type: Protocol

Date Submitted by the 12-Oct-2019 Author:

Complete List of Authors: Jackson, Alun; Australian Centre for Heart Health,; Deakin University Faculty of Health Rogerson, Michelle; Australian Centre for Heart Health Le Grande , Michael; Australian Centre for Heart Health; University of Melbourne, Centre for Behaviour Change, Melbourne School of Psychological Sciences Thompson, David; Queen's University Belfast, School of Nursing and Midwifery; Australian Centre for Heart Health Ski, Chantal; Queen’s University, Belfast, School of Nursing and Midwifery; Australian Centre for Heart Health Alvarenga, Marlies; Federation University Australia - Berwick Campus, School of Health and Life Sciences; MonashHeart, Monash Cardiovascular

Research Centre http://bmjopen.bmj.com/ Amerena, John; Barwon Health, Cardiac Services; Deakin School of Medicine Higgins, Rosemary; Australian Centre for Heart Health; Deakin University, Faculty of Health Raciti, Michela; Australian Centre for Heart Health Murphy, Barbara; Australian Centre for Heart Health; Deakin University Faculty of Health

Adult cardiology < CARDIOLOGY, Protocols & guidelines < HEALTH Keywords: SERVICES ADMINISTRATION & MANAGEMENT, Cardiology < INTERNAL on October 1, 2021 by guest. Protected copyright. MEDICINE, MENTAL HEALTH

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1 2 3 4 5 BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 6 7 8 9 I, the Submitting Author has the right to grant and does grant on behalf of all authors of the Work (as defined 10 in the below author licence), an exclusive licence and/or a non-exclusive licence for contributions from authors 11 who are: i) UK Crown employees; ii) where BMJ has agreed a CC-BY licence shall apply, and/or iii) in accordance 12 with the terms applicable for US Federal Government officers or employees acting as part of their official 13 duties; on a worldwide, perpetual, irrevocable, royalty-free basis to BMJ Publishing Group Ltd (“BMJ”) its 14 licensees and where the relevant Journal is co-owned by BMJ to the co-owners of the Journal, to publish the 15 Work in this journal and any other BMJ products and to exploit all rights, as set out in our licence. 16 17 The Submitting Author accepts and understands that any supply made under these terms is made by BMJ to 18 the Submitting Author Forunless you peer are acting as review an employee on behalf only of your employer or a postgraduate 19 student of an affiliated institution which is paying any applicable article publishing charge (“APC”) for Open 20 Access articles. Where the Submitting Author wishes to make the Work available on an Open Access basis (and 21 intends to pay the relevant APC), the terms of reuse of such Open Access shall be governed by a Creative 22 Commons licence – details of these licences and which Creative Commons licence will apply to this Work are set 23 out in our licence referred to above. 24 25 Other than as permitted in any relevant BMJ Author’s Self Archiving Policies, I confirm this Work has not been 26 accepted for publication elsewhere, is not being considered for publication elsewhere and does not duplicate 27 material already published. I confirm all authors consent to publication of this Work and authorise the granting 28 of this licence. 29 30 31 32 33 34 35 36

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1 2 3 Protocol for the development and validation of a measure of persistent psychological and 4 emotional distress in cardiac patients: The Cardiac Distress Inventory BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 7 8 Alun C Jackson PhD (Corresponding author), Director, Australian Centre for Heart Health, 9 Melbourne, Victoria, Australia; Honorary Professor, Faculty of Health, Deakin University, Geelong, 10 11 Australia; Honorary Professor, Centre on Behavioural Health, University of Hong Kong, Pokfulam, 12 Hong Kong. Address: PO Box 2137, The Royal Melbourne Hospital, Victoria 3050 Australia; Ph: +61 3 13 9326 8544; Email: [email protected] 14 15 Michelle Rogerson PhD, Research Fellow, Australian Centre for Heart Health, Melbourne, Australia. 16 17 Michael R Le Grande MPH, Senior Research Fellow, Australian Centre for Heart Health, Melbourne, 18 Australia; Research Fellow,For Centre peer for Behaviour review Change, Melbourne only School of Psychological 19 Sciences, University of Melbourne, Melbourne, Australia. 20 21 David R Thompson PhD, Professor, School of Nursing and Midwifery, Queen’s University Belfast, UK; 22 Honorary Professorial Fellow, Australian Centre for Heart Health, Melbourne, Australia; Honorary 23 24 Professor, Department of Psychiatry, University of Melbourne, Melbourne, Australia. 25 Chantal F Ski PhD, Reader, School of Nursing and Midwifery, Queen’s University Belfast, UK; 26 27 Honorary Principal Research Fellow, Australian Centre for Heart Health, Melbourne, Australia; 28 Honorary Associate Professor, Department of Psychiatry, University of Melbourne, Melbourne, 29 Australia. 30 31 Marlies E Alvarenga PhD, Lecturer in Psychology, School of Health and Life Sciences, Federation 32 University Australia, Berwick, Australia; Consultant Clinical Psychologist, Monash Cardiovascular 33 Research Centre, MonashHEART, Melbourne, Australia & Monash Health & Department of Medicine, 34 Monash University, Melbourne, Australia & Australian Centre for Heart Health, Melbourne, Australia 35 36 John Amerena MB BS, Director of Cardiac Services, Barwon Health, Geelong, Australia; Clinical

37 http://bmjopen.bmj.com/ 38 Associate Professor, Deakin School of Medicine, University Hospital Geelong, Geelong, Australia. 39 Rosemary O Higgins DPsych, Clinical Consultant (Health Psychology), Australian Centre for Heart 40 41 Health, Melbourne, Australia; Honorary Associate Professor, Department of Psychology, Deakin 42 University, Geelong, Australia; Honorary Associate Professor, Department of Physiotherapy, 43 University of Melbourne, Melbourne, Australia. 44

45 Michela Raciti BPsych, Research Intern, Australian Centre for Heart Health, Melbourne, Australia on October 1, 2021 by guest. Protected copyright. 46 47 Barbara M Murphy PhD, Principal Researcher, Australian Centre for Heart Health, Melbourne, 48 Australia; Honorary Associate Professor, Faculty of Health, Deakin University, Geelong, Australia; 49 Honorary Senior Research Fellow, Department of Psychology, University of Melbourne, Melbourne, 50 Australia. 51 52 Key words: cardiac distress, anxiety, depression, psychometrics, instrument development 53 54 Word count: 4371 55 56 57 58 59 60

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1 2 3 ABSTRACT 4 5 Introduction Distress is experienced by the majority of cardiac patients, yet no cardiac-specific BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 6 measure of distress exists. The aim of this project is to develop and validate the Cardiac Distress 7 Inventory (CDI). Using the CDI, health professionals will be able to identify key clusters of 8 psychological, emotional and social concern to address with patients, post-cardiac event. 9 Psychometric testing of a long form questionnaire will also result in the development of a short form 10 screening version. 11 12 Methods and analysis An item pool will be generated through: identification of items by a 13 multidisciplinary group of clinician researchers; review of generic and condition-specific distress 14 measures; focus group testing with cardiac rehabilitation professionals; feedback from patients. The 15 COSMIN criteria will be used to inform the development of the methodology for determining the 16 17 CDI’s psychometric properties. The item pool will be tested with 400 cardiac patients and responses 18 subjected to exploratoryFor factor peer analysis, Rasch review analysis, test-retest only reliability, construct validity 19 testing, and latent class analysis. ROC analysis will be used to identify the optimal CDI cut off score 20 for distinguishing whether a person experiences clinically significant distress. The study will take 21 place over a 15 to 18-month period. 22 23 Ethics and dissemination This protocol has been approved by the Monash Health Human Research 24 Ethics Committee (Approval number – RES-19-0000631L-55979 0). The CDI will be made available to 25 clinicians and researchers without charge. The CDI will be translated for use with clinical populations 26 internationally with reporting of the psychometric properties of those versions. Study findings will 27 be shared with cardiac patient support groups; academic and medical communities via publications 28 and presentations; in the training of cardiac secondary prevention health professionals; and in 29 reports to funders. Authorship for all publications will be determined in line with the Uniform 30 31 Requirements for Manuscripts Submitted to Biomedical Journals. 32 Strengths and limitations of this study 33 34  This protocol describes the development and validation of the first available cardiac-specific 35 distress measure. 36  The measure is based on a multidisciplinary conceptualisation of the core construct, cardiac

37 http://bmjopen.bmj.com/ 38 distress, while building on similar scale development in oncology and diabetes. 39  The protocol describes a co-design process involving both cardiac patients and health 40 professionals in item-generation and involves a range of quantitative psychometric methods in 41 item-testing. 42 43  We will compare a statistically-driven and a clinically-driven method to develop a short-form of 44 the measure for use as a screening tool.

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1 2 3 BACKGROUND 4 5 Conceptualisation of cardiac distress BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 6 7 As high prevalence conditions, much attention has been paid to the measurement and 8 understanding of anxiety and depression as consequences of cardiac events. However, relatively 9 little attention has been given to the phenomenon of ‘cardiac distress’ which many patients 10 experience after acute coronary events such as myocardial infarction (AMI), unstable angina, or 11 coronary artery bypass graft surgery (CABGS). In an earlier paper, we discussed the 12 conceptualisation of cardiac distress and defined it as: 13 14 “a persistent negative emotional state rather than a transient state; involving multiple 15 psychosocial domains; that challenges a patient’s capacity to cope with living with their heart 16 condition, the treatment of the condition, and the resultant changes to daily living; and 17 challenges the person’s sense of self and future orientation”1. 18 For peer review only 19 A number of previous studies have attempted to examine the relationship between post-cardiac 20 event distress, symptom severity and mortality in relation to a range of specific heart conditions2, 3 21 and procedures4, 5, following cardiac rehabilitation6, and in cardiovascular disease more generally7. A 22 common characteristic of these studies, however, is the use of terms such as ‘distress’ without 23 explicit definition. In some cases, distress is simply defined as being that which is measured by an 24 instrument deemed to measure distress such as the Hospital Anxiety and Depression Scale8, the 25 General Health Questionnaire9 or the Kessler Psychological Distress Scale10. Typically, these studies 26 27 view psychological or emotional distress as a simple combination of anxiety and depression, as does 11 28 a recent analysis of post-cardiac event psychological distress trajectories . 29 A small number of studies, however, widen this narrow view of distress by adding other psychosocial 30 constructs to ‘anxiety plus depression’, including stress and stressful life events12-14; fear of death13, 31 15 12 14 32 ; hostility ; vital exhaustion and reduced quality of life ; vulnerabilities such as lack of pleasant 16 33 events, dysfunctional attitudes, role transitions and poor dyadic adjustment ; feelings of 15 6 34 helplessness, loss of control, and pain ; and psychological wellbeing . 35 The ‘cardiac blues’ 36

37 A broader approach to understanding the complexity of the psychological and emotional impacts of http://bmjopen.bmj.com/ 38 a cardiac event is evidenced in the concept of the ‘cardiac blues’ which describes a range of 39 emotional responses to an acute cardiac event. It has been suggested that almost all patients 40 experience at least some symptoms of the cardiac blues at the time of, or soon after, an acute 41 cardiac event17. Common emotions include shock, low or fluctuating mood, sadness, worry, guilt and 42 43 anger. Mood changes are displayed by tiredness, irritability, tearfulness, loss of pleasure in usual 44 activities, withdrawal from others, early waking and other sleep disturbance, and changes in

45 appetite and sex drive. Cognitive changes that typically co-occur include confusion and forgetfulness, on October 1, 2021 by guest. Protected copyright. 46 inability to concentrate, nightmares, reduced self-esteem, concerns about role changes, particularly 47 regarding paid work, physical health and independence; and pessimism about the future17-19. 48 Although generally a transient condition20, 21, if the cardiac blues does not resolve within around two 49 months of the cardiac event, the psychological and emotional impact of the event can result in 50 persistent cardiac distress18, 19. 51 52 Measuring condition-specific distress 53 54 Both the oncology and diabetes fields have at least a two decade-long history of screening and 55 psychosocial intervention for condition-specific distress. For oncology, this is reflected in the 56 National Comprehensive Cancer Network Guidelines for Distress Management22 where distress is 57 considered to be a multifactorial unpleasant experience of a psychological (i.e., emotional, 58 behavioural, cognitive), social, spiritual, and/or physical nature that may interfere with the ability to 59 cope effectively with cancer, its physical symptoms or its treatment. An excellent earlier attempt to 60

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1 2 3 conceptualise diabetes distress so that it could be recognised and addressed in nursing practice23, 4 24 has recently been extended by Dennick and colleagues . They characterise distress as a range of BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 negative emotional responses, such as worry, fear, frustration, guilt, sadness, anger, to aspects of 7 living with and managing the condition, balanced against an appraisal of available coping 24 8 resources . Snoek and colleagues argue that diabetes-distress and depression are correlated and 9 overlapping constructs, but are not interchangeable, and that distinguishing between them is an 10 important factor in shaping appropriate mental health interventions25. In a recent systematic review 11 of the impact of distress on health-related outcomes, Barry and colleagues agree also that distress is 12 distinct from depression and should be assessed using condition-specific measures, as early as 13 practicable in treatment26. 14 15 Cardiac-specific measures of the psychosocial impact of cardiac events 16 17 The cardiac field also has a two decade-long history of attempts to measure aspects of the 18 psychological and emotionalFor impact peer of cardiac review events. Examples only of cardiac-specific measures 19 include the Cardiac Depression Scale27 , the Cardiac Event Threat Questionnaire28, the Cardiac 20 Anxiety Questionnaire29, the MacNew Quality of Life measure30 and the Screening Tool for 21 Psychological Distress (STOP–D)31. These measures collectively assess a range of features associated 22 with cardiac distress such as impaired quality of life, anxiety, depression, fear, death anxiety, illness- 23 related dependency, feeling unable to cope, stress, worrying levels of pain, low perceived social 24 support, and anger. However, none of the measures provides a comprehensive or detailed 25 26 assessment of cardiac distress. Moreover, no currently existing measure would enable a psycho- 27 cardiology professional to identify priority areas clearly enough to offer timely tailored psychosocial 28 intervention for a distressed patient32, 33. Using the CDI, health professionals will be able to identify 29 key clusters of psychological, emotional and social concern to address with patients, post-cardiac 30 event. 31 32 Aims 33 The aims of the present study are: 34 1. To develop and validate the Cardiac Distress Inventory (CDI). 35 2. To develop a short form screening tool version of the CDI. 36

37 http://bmjopen.bmj.com/ 38 METHOD 39 40 Item generation 41 42 There are six steps in the item generation procedure: 43 44 i. Initial generation of items by a multidisciplinary group of researchers and clinicians including the disciplines of nursing, psychiatry, behavioural health, psychology and 45 on October 1, 2021 by guest. Protected copyright. 46 cardiology. 47 ii. Review of generic and condition-specific distress measures, to identify the elements 48 comprising the construct of ‘distress’ in those measures and to identify items which could 49 be adapted for the CDI. 50 iii. Review of cardiac-specific measures incorporating elements of distress as defined by the 51 present authors1. 52 53 iv. Review of items for appropriateness for a post-operative cardiac population by the 54 multidisciplinary investigator group. 55 v. Focus group testing with two multidisciplinary groups of cardiac rehabilitation 56 professionals: experienced practitioners undertaking intensive training in cardiac 57 rehabilitation through the Australian Centre for Heart Health; and the National Executive of 58 the Australian Cardiovascular Health and Rehabilitation Association (ACRA). 59 60

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1 2 3 vi. Consultation with, and feedback from, cardiac patients (key informants) on the structure 4 and content of the CDI. BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 Patient and public involvement 7 8 The need for a comprehensive measure of cardiac-related distress has been identified by the 9 multidisciplinary clinician researcher members of the CDI development group, through their clinical 10 practice in provision of psychosocial support to cardiac patients. This need has been endorsed by the 11 authors’ consultations with both individual patients and patient support groups such as the hospital- 12 based or regionally-based Heart Beat programs such as Heart Beat Victoria. As evident from step vi 13 14 in the item generation procedure, patients will be consulted as key informants about the structure 15 and content of the CDI. Only after this process of consultation is complete will the CDI item pool be 16 tested with 400 cardiac patients. 17 18 The result of the CDI Fordevelopment peer project, thereview psychometrically only sound Cardiac Distress Inventory, 19 will be made available to clinicians and researchers without charge, but with a request that data 20 collected in studies using the measure will be made available for aggregation and analysis in future. 21 The CDI will also be translated for use with clinical populations internationally with reporting of the 22 psychometric properties of those versions. Confirmed translations will be Italian, Hebrew, Arabic, 23 Farsi, and Spanish. Study findings will be shared with community members, particularly cardiac 24 patient support groups such as the Heart Beat groups and their equivalents internationally; 25 academic and medical communities via publications and presentations; in an online course in its 26 27 rationale and use provided at no cost by the Australian Centre for Heart Health. The short form will 28 be made available on the website of the Australian Centre for Heart Health for completion by 29 patients to self-screen with suggestions for follow up psychological support where indicated. 30 31 Cardiac Distress Inventory design 32 Items generated through the process outlined above will be reworded where appropriate to ensure 33 relevance to the measurement of cardiac distress, and appropriateness of fit with the following 34 35 instruction and response set: 36 Living with a heart condition can sometimes be difficult. Listed below are some issues that people

37 http://bmjopen.bmj.com/ living with a heart condition may experience. 38 39 Please indicate whether or not you have experienced each issue during the past four weeks by 40 checking ‘Yes’ or ‘No’. For each item you have checked ‘Yes’, indicate how much distress this issue 41 42 has caused you for the past four weeks, from 0 to 3, where “0” is no distress and “3” is severe 43 distress. 44 Issue Yes No If yes, indicate how much distress this causes for you

45 on October 1, 2021 by guest. Protected copyright. 46 No distress Slight Moderate Severe 47 at all distress distress distress 48 Example: Having more pain 0 1 2 3 49 than I expected to have   50 51 52 Trialling of the questionnaire for item reduction 53 54 Sample size required for trial 55 Recommendations of sample size for exploratory factor analysis in instrument development are that 56 there should be at least 5 cases for each item in the instrument being used34. Rasch modelling for 57 exploratory purposes should be based on at least N=100 and preferably N=25035. For the reliability 58 36 59 and validation study, power calculations were conducted using GPower . Given a probability level of 60 0.05, an anticipated effect size of 0.5, and a desired statistical power level of 0.8, a sample size of

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1 2 3 N=66 is required per group. A summary of the steps and the number required for each step in the 4 analysis is provided in Table 1. BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 7 8

9 10 11 Inclusion and exclusion criteria 12 Eligible patients will be those who have had an acute coronary event - namely acute coronary 13 14 syndrome (ACS), acute myocardial infarction (AMI) or coronary artery bypass graft surgery (CABGS) 15 in the previous 2 months and who are attending either a CR program or an outpatient clinic at a 16 participating hospital. Patients who do not have adequate English language proficiency to read and 17 understand the PICF and questionnaire will be excluded. 18 For peer review only 19 Participant recruitment 20 A Research Assistant (RA) will recruit patients at two months presentation directly through 21 outpatient clinics or CR programs associated with the investigators. Clinic staff will advise the RA of 22 potentially eligible patients and the RA will then approach these people to ascertain eligibility and 23 24 willingness to participate. Specific arrangements for site visits will be made between the RA and site 25 investigator by email and telephone. Overall and site-specific ethical approval will be in place. 26 In order to calculate a response rate, the RA will document the number of patients approached and 27 the number who agree to participate and who do not. No identifying information on either 28 29 participants or non-participants will be collected. 30 Data collection 31 32 Consenting participants will complete the PICF and the trial-version CDI, together with basic socio- 33 demographic and event-related information. No identifying information (name, address, date of 34 birth) will be collected as no patient follow-up is required. For reliability and validity testing, 35 participants will also be required to complete the four Emotion Thermometers37, the Kessler 36 Psychological Distress Scale-638 (K6) and the PHQ-439. In the event that the patient experiences 37 distress while completing the questionnaire, the patient will be reminded by the RA that he/she is http://bmjopen.bmj.com/ 38 free to withdraw from the study (i.e., not continue with completing the questionnaire) and will be 39 40 invited to contact the Australian Centre for Heart Health for a consultation with a clinical psychology 41 specialist at no cost to the patient. 42 Measures 43 44 In addition to the trial-version CDI, the following measures will be administered:

45 on October 1, 2021 by guest. Protected copyright. 46 Demographic questionnaire: Basic socio-demographic (e.g., age, sex, marital status, living 47 arrangement) and cardiac event-related information (event type, date of event) will be collected. 48 Emotion Thermometers. The Emotion Thermometers are single-item measures of distress (DT), 49 anxiety (AnxT), depression, (DepT) and anger (AngT). They consist of a “thermometer” with 50 51 numerals displayed vertically from 0 to 10. Patients rate their distress “over the last week”, with 0 52 indicating “no distress” and 10 indicating “high distress”. A total score from all four mood 53 thermometers (ETsum) indicates overall emotional problems. These thermometers, based on the 54 NCCN cancer distress thermometer (DT)22, have been shown to be a clinically sensitive measure of 55 distress in patients with mixed cardiovascular conditions37. 56 39 57 Patient Health Questionnaire-4 (PHQ-4): The PHQ is a validated brief screener (4-items) for anxiety 58 and depression, which combines the Patient Health Questionnaire-2 (PHQ-2) and the Generalized 59 Anxiety Disorder-2 (GAD-2)39. Total scores range from 0-12, with 0 indicating “no distress” and 12 60 indicating “severe distress”.

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1 2 3 Kessler Psychological Distress Scale-638 (K6): The Kessler 6 is a brief measure of psychological distress 4 38 which has been validated in an Australian general population . The K6 is both an effective screening BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 measure and an indicator of distress severity. Scores range from 6-30, with lower scores indicating 7 higher levels of distress. 8 Screening Tool for Psychological Distress31(STOP-D): This is a five-item, evidence-derived self-report 9 measure generating severity scores for depression, anxiety, stress, anger and poor social support. 10 The screening tool has been tested with patients before and after heart transplant, patients in 11 31 12 cardiac rehabilitation and adults with congenital heart disease . 13 Statistical analysis for the trial 14 15 Part A – Establishing dimensions of the CDI 16 Principal component analysis (PCA) using SPSS will be used to assess the dimensions of the CDI. PCA 17 18 is commonly used in Forthe development peer of new review instruments to provide only early indications of possible 40 19 dimensions before Rasch analysis is attempted . PCA is used to extract the factors followed by 20 oblique rotation of factors using Oblimin rotation (delta = 0). Kaiser's criterion, which retains eigen 21 values above 1, will be used to guide the identification of relevant factors. A second step in the PCA 22 is to conduct Horn's parallel analysis41, considered one of the most accurate approaches to estimate 23 the number of components42. The size of eigen values obtained from PCA are compared with those 24 obtained from a randomly generated data set of the same size. Only factors with eigen values 25 exceeding the values obtained from the corresponding random data set are retained for further 26 27 investigation. 28 Part B - Eliminating items per dimension of the CDI 29 30 Rasch analysis is a mathematical technique used to evaluate a latent variable not measurable 31 directly from a set of categorical items. Rasch methods can be used to assess the extent to which 32 individual items represent the underlying construct that an instrument intends to measure. The 33 Rasch model chosen for this analysis, the Partial Credit Model43 is applicable to polytomous rather 34 than dichotomous data and is therefore suitable for Likert scales and response ratings. 35 36 Rasch analysis will be conducted using RUMM2030 software (RUMM Laboratory Pty Ltd., Perth,

37 Australia). Three statistics are considered to determine the degree of fit for each CDI scale: overall http://bmjopen.bmj.com/ 38 fit; individual person fit; and individual item fit44. Adequate overall fit of the CDI to the Rasch model 39 is indicated by a non-significant Bonferroni adjusted Chi-square probability value45. Satisfactory 40 overall item and individual fit for each scale will be determined by a fit residual standard deviation 41 (SD) value of ≤1.5. Individual item fit is indicated by two statistics: fit residual values; and Chi-square 42 46 43 probability values. Item fit residual values −2.5 to 2.5 indicate adequate fit . Above this range 44 (underfit) suggests deviation from the model, below (overfit) suggests that some items in the scale 47

45 are similar to each other . A perfect model fit would be reflected by residuals with a mean of 0.00 on October 1, 2021 by guest. Protected copyright. 46 and a SD of 1.00. Any mis-fitting item in terms of infit/outfit is discarded and the analysis re-run. 47 This iterative process is continued until no further misfit is observed48. The Rasch analysis will 48 produce the person separation index (PSI), which indicates the degree to which study participants 49 can be differentiated into certain groups (PSI range 0–1). Values for PSI of 0.8 are acceptable49. A 50 sample size of at least 100 patients is required to perform a Rasch analysis which can estimate an 51 35 52 acceptable PSI value . 53 Statistical significance will be considered at the 5% level and Bonferroni correction for multiple 54 testing will be applied where appropriate. 55 56 Psychometric properties of the final Cardiac Distress Inventory 57 58 The COSMIN (Consensus-based Standards for the selection of health Measurement Instruments) 59 criteria for evaluating the methodological quality of health-related patient-reported outcomes will 60

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1 2 3 be used to inform the development of the methodology for determining the psychometric 4 50, 51 properties as far as possible . BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 Reliability 7 8 Internal consistency of the CDI will be determined using Cronbach’s alpha, standard test-retest 9 methods, and evaluation of the Person Separation Index (PSI) from the Rasch analysis. 10 Test-retest reliability indicates agreement between repeated assessments. The CDI will be 11 administered at two time points with at least 14 days separation, the first assessment taking place at 12 13 least 30 days after the cardiac event or surgery. The intra-class correlation coefficient (ICC) will be 14 used to examine the level of test-retest reliability. A 2-way analysis of variance (ANOVA) assuming 15 patients’ effects to be random, will be used to compute the variance needed to calculate the ICC. ICC 16 values in the range of 0.6–0.8 represent substantial reliability and ICC values > 0.8 indicate high 17 reliability52. In addition, a paired t-test will be performed to examine whether significant differences 18 exist between test-retestFor assessments. peer A sample review of at least N=66 only is required for test-retesting, given 19 an estimated effect size of 0.4, power of .90, standard deviation of 1.0 and alpha of 0.05. 20 21 Validity 22 23 Scale comparisons will be used to investigate the concurrent convergent validity of the CDI. Pearson 24 correlation coefficients will be calculated to explore the association between CDI scores and the 25 measure that is commonly used in clinical practice to assess distress, the six-item Kessler K638. 26 Subscale scores of the CDI will be compared with K6 scores where appropriate. We will assess the 27 discriminant validity and predictive validity of the CDI by assessing whether it distinguishes between 28 patients scoring high and low on the K6, using the Australian scoring cut-off of 19 to indicate 29 probable serious mental illness53. Again, both CDI total and factor scores will be investigated. It is not 30 possible to use a measure of cardiac distress for validity testing as no such measure exists. 31 32 Pearson correlation coefficients will also be calculated to explore the association between CDI scores 33 and the Patient Health Questionnaire–4 (PHQ4)39. Normative data are available from a nationally 34 representative face-to-face household survey sample of 5030 people, conducted in Germany in 35 200654. The measure has been translated and validated in Hispanic populations, for example55, and 36 has been used in studies of cancer patients56and emergency department patients57. As far as the

37 http://bmjopen.bmj.com/ 38 authors are aware, no validation study of the PHQ-4 has been undertaken with cardiac patients. 39 Comparison of CDI scores will also be conducted between the various types of cardiac patients (e.g. 40 AMI vs CABGS). Comparison of groups will be conducted via analysis of variance (ANOVA). 41 42 Latent Class Analysis 43 44 Latent class analysis (LCA) will be used in order to describe groups of participants that differ in their response patterns to the CDI. LCA explains inter-individual differences in response patterns by 45 on October 1, 2021 by guest. Protected copyright. 46 means of a given number of latent classes (subgroups of participants). LCA estimates the size of the 47 classes and a membership probability for each participant within each class58 and will be performed 48 using Mplus version 6.059. To select the most parsimonious number of classes and maximise model 49 fit, a series of latent class models will be applied to the data. First, the simplest 1-class model (all 50 patients are assumed to have the same pattern of cardiac distress) will be applied to the data, 51 followed by successive models with a unitary increase in the number of latent classes (up to eight). 52 53 Model solutions are evaluated on the basis of their Bayesian information criterion (BIC) and entropy. 54 The BIC has been shown to be a robust indicator of model fit, with lower values indicative of better 55 model fit60. BIC will be used in preference to Akaike information criteria, as the latter has been 56 shown to over-extract classes in simulation models61. The association of CDI latent class membership 57 with CDI scale scores, sociodemographic characteristics, diagnosis and K6 distress scores will also be 58 examined using Mplus59. Mplus generates overall chi-square values to assess significant associations 59 between variables as well as unadjusted chi-square values for exploratory post-hoc analysis. 60

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1 2 3 Development of a short form Cardiac Distress Inventory for screening purposes 4 5 A shorter version of the CDI, the CDI-S, will then be created. Importantly, item reduction based on BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 6 rigorous methodological guidelines is necessary to maintain validity when shortening composite 7 measurement scales62. In addition, there are a number of ways to achieve item reduction63. In light 8 of these two points, we will use two methods to develop the short form screening tool – a clinically 9 oriented method and a statistically-driven method. A concept-retention approach will create a short 10 version of the original measure by selection of the top performing item in each domain to become 11 64 12 part of the short, concept-retention version . Rasch analysis as used in a number of health-related 65, 66 13 item reduction exercises, will also be employed . The Rasch analysis and psychometric evaluation 14 of the CDI-S will follow the format described by Nishigami and colleagues66. Both versions of the CDI- 15 S will then be field tested. 16 17 Thermometer testing 18 Receiver operating characteristicFor peer (ROC) analysis review will be used to onlyidentify the optimal CDI scale cut off 19 score for distinguishing whether a person experiences clinically significant distress as defined by the 20 established cut-off thresholds for ETsum (the sum of all four mood thermometers). The Area Under 21 22 the Curve (AUC) will be used to estimate the overall discriminative accuracy of the CDI scale cut off 23 score relative to the established cut off scores of ETsum (a score >14 indicates moderate and >20 24 indicates severe emotional problems). Using qualitative guidelines for interpreting AUC values67, 25 namely AUC≤0.70 as acceptable discrimination, AUC≤0.80 as good discrimination and AUC≤0.90 as 26 excellent discrimination. ROC curves will be used to show the trade-off between the sensitivity (true- 27 positive rate) and specificity (true-negative rate) for every possible cut off score of the CDI Scale. 28 29 TIMELINE 30 Months 1-2: staff recruitment, CR site recruitment and liaison; Months 3-10: Administration of the 31 32 full item pool draft CDI to patients attending CR or outpatient appointments. This includes test- 33 retest of 66 cardiac patients; Months 11-12: completion of data analysis; Months 13-15: writing up 34 the study findings will be a continuous activity with completion in months 15-18. 35 SUMMARY 36

37 Cardiac distress is a common problem among cardiac patients. Before cardiac distress can be treated http://bmjopen.bmj.com/ 38 effectively, it needs to be properly measured by a reliable, valid and sensitive instrument. The 39 primary aim of the project is to develop a new clinical measure which health professionals can use to 40 identify and assess cardiac distress. They can use the fine-grained assessment provided by this 41 unique measure to structure psychological and emotional interventions to intervene in cases of 42 43 persistent distress in patients, following a cardiac event. No such measure currently exists. 44 While physical recovery remains the highest priority in preventive cardiology, psychological recovery 45 is now considered a primary concern for health professionals working in cardiac rehabilitation and on October 1, 2021 by guest. Protected copyright. 46 secondary prevention. The prevalence of clinical anxiety and depression in people who have had a 47 48 cardiac event is up to four times higher than in the general population, however both the prevalence 49 and nature of the broader concept of cardiac-related distress remains unknown. Post-event 50 psychological problems confer an increased mortality risk for patients, highlighting the importance 51 of identifying distressed patients early in order to ensure appropriate treatment is received. The new 52 CDI will not only enhance clinicians’ ability to identify distressed patients but will also enable them 53 to identify the specific nature of the distress, thereby optimising their ability to provide timely 54 support targeted to the specific psychosocial needs of the patient. The new CDI has the potential to 55 ensure that patients are provided with the specific support they require in their psychosocial 56 57 recovery after a cardiac event and, in doing so, has the potential to improve their quality of life, 58 enhance their behaviour change efforts and ultimately extend their survival. 59 60

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1 2 3 References 4 5 BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 6 7 1. Jackson AC, Murphy BM, Thompson DR, et al. What is cardiac distress and how should we 8 measure it? Brit J Card Nurs 2018; 13: 286-293. 9 2. Stewart RAH, Colquhoun DM, Marschner SL, et al. Persistent psychological distress and 10 mortality in patients with stable coronary artery disease. Heart 2017; 103: 1860-1866. 11 12 3. Lissaker CT, Wallert J, Held C, et al. Emotional distress as a predictor of statin non-adherence 13 among Swedish first-time myocardial infarction patients, 2006-2013. J Psychosom Res 2017; 14 97: 30-37. 15 16 4. Habibović M, Mudde L, Pedersen SS, et al. Sleep disturbance in patients with an implantable 17 cardioverter defibrillator: Prevalence, predictors and impact on health status. Eur J Cardiovasc 18 Nurs 2017; 17:For 390-398. peer review only 19 20 5. Sipotz J, Friedrich O, Hofer S, et al. Health related quality of life and mental distress after PCI: 21 restoring a state of equilibrium. Health Qual Life Outcomes 2013; 11: 144. 22 6. Gostoli S, Roncuzzi R, Urbinati S, et al. Clinical and subclinical distress, quality of life, and 23 24 psychological wellbeing after cardiac rehabilitation. App Psychol Health Wellbeing 2017; 9: 25 349-369. 26 7. Russ TC, Stamatakis E, Hamer M, et al. Association between psychological distress and 27 mortality: individual participant pooled analysis of 10 prospective cohort studies. BMJ Clinical 28 29 Res 2012; 345: e4933. 30 8. Snaith RP and Zigmond AS. The Hospital Anxiety and Depression Scale - Manual. Windsor, UK: 31 NFER-Nelson, 1994. 32 33 9. Goldberg DP and Hillier VF. A scaled version of the General Health Questionnaire. Psychol Med 34 1979; 9: 139-145. 35 36 10. Kessler RC, Andrews G, Colpe LJ, et al. Short screening scales to monitor population

37 prevalences and trends in non-specific psychological distress. Psychol Med 2002; 32: 959-976. http://bmjopen.bmj.com/ 38 11. Virtanen M, Elovainio M, Josefsson K, et al. Coronary heart disease and risk factors as 39 predictors of trajectories of psychological distress from midlife to old age. Heart 2017; 103: 40 41 659-665. 42 12. Kachur S, Menezes AR, De Schutter A, et al. Significance of comorbid psychological stress and 43 depression on outcomes after cardiac rehabilitation. Am J Med 2016; 129: 1316-1321. 44

45 13. Whitehead DL, Strike P, Perkins-Porras L, et al. Frequency of distress and fear of dying during on October 1, 2021 by guest. Protected copyright. 46 acute coronary syndromes and consequences for adaptation. Am J Cardiol 2005; 96: 1512- 47 1516. 48 49 14. Claesson M, Burell G, Birgander LS, et al. Psychosocial distress and impaired quality of life - 50 targets neglected in the secondary prevention in women with ischaemic heart disease. Eur J 51 Cardiovasc Prev Rehab 2003; 10: 258-266. 52 53 15. Malinauskaite I, Slapikas R, Courvoisier D, et al. The fear of dying and occurrence of 54 posttraumatic stress symptoms after an acute coronary syndrome: A prospective 55 observational study. J Health Psychol 2017; 22: 208-217. 56 57 16. Denton E-gD, Rieckmann N, Davidson KW, et al. Psychosocial vulnerabilities to depression 58 after acute coronary syndrome: The pivotal role of rumination in predicting and maintaining 59 depression. Front Psychol 2012; 3: 288. 60

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1 2 3 17. Murphy BM, Higgins RO, Jackson AC, et al. Patients want to know about the 'cardiac blues'. 4 Aust Fam Physician 2015; 44: 826-832. BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 18. Higgins RO, Murphy BM, Nicholas A, et al. Emotional and adjustment issues faced by cardiac 7 patients seen in clinical practice: a qualitative survey of experienced clinicians. J Cardiopulm 8 Rehabil Prev 2007; 27: 291-297. 9 10 19. Murphy BM, Higgins RO, Jackson AC. Anxiety, depression and psychological adjustment after 11 an acute cardiac event. In: Alvarenga ME and Byrne D (eds) Handbook of Psychocardiology. 12 Singapore: Springer, 2016. 13 14 20. Murphy BM, Elliott PC, Higgins RO, et al. Anxiety and depression after coronary artery bypass 15 graft surgery: most get better, some get worse. Eur J Cardiovasc Prev Rehabil 2008; 15: 434- 16 440. 17 18 21. Tully PJ and BakerFor RA. Depression, peer anxiety, review and cardiac morbidityonly outcomes after coronary 19 artery bypass surgery: a contemporary and practical review. J Geriatr Cardiol 2012; 9: 197- 20 208. 21 22. NCCN Clinical Guidelines in Oncology. Distress Management Version 22017. National 22 23 Comprehensive Cancer Network, 2017. 24 23. Ridner SH. Psychological distress: concept analysis. J Adv Nurs 2004; 45: 536-545. 25 26 24. Dennick K, Sturt J and Speight J. What is diabetes distress and how can we measure it? A 27 narrative review and conceptual model. J Diabet Compl 2017; 31: 898-911. 28 29 25. Snoek FJ, Bremmer MA and Hermanns N. Constructs of depression and distress in diabetes: 30 time for an appraisal. Lancet Diabet Endocrin 2015; 3: 450-460. 31 26. Barry V, Stout ME, Lynch ME, et al. The effect of psychological distress on health outcomes: A 32 systematic review and meta-analysis of prospective studies. J Health Psychol 2019: DOI: 33 34 1359105319842931. 35 27. Hare DL and Davis CR. Cardiac Depression Scale: validation of a new depression scale for 36 cardiac patients. J Psychosom Res 1996; 40: 379-386.

37 http://bmjopen.bmj.com/ 38 28. Bennett SJ, Puntenney PJ, Walker NL, et al. Development of an instrument to measure threat 39 related to cardiac events. Nurs Res 1996; 45: 266-270. 40 41 29. Eifert GH, Thompson RN, Zvolensky MJ, et al. The cardiac anxiety questionnaire: development 42 and preliminary validity. Behav Res Ther 2000; 38: 1039-1053. 43 30. Valenti L, Lim L, Heller RF, et al. An improved questionnaire for assessing quality of life after 44 acute myocardial infarction. Qual Life Res 1996; 5: 151-161.

45 on October 1, 2021 by guest. Protected copyright. 46 31. Young QR, Ignaszewski A, Fofonoff D, et al. Brief screen to identify 5 of the most common 47 forms of psychosocial distress in cardiac patients: validation of the screening tool for 48 psychological distress. J Cardiovasc Nurs 2007; 22: 525-534. 49 50 32. Pedersen SS and Andersen CM. Minding the heart: Why are we still not closer to treating 51 depression and anxiety in clinical cardiology practice? Eur J Prev Cardiol 2018; 25: 244–246 52 53 33. Richards SH, Anderson L, Jenkinson CE, et al. Psychological interventions for coronary heart 54 disease. Cochrane Database Syst Rev 2017; 4: Cd002902. . 55 34. Polit DF and Beck CT. Essentials of Nursing Research: Appraising Evidence For Nursing Practice, 56 57 9th Edition. Philadelphia, USA: Wolters Kluwer, 2018. 58 59 60

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1 2 3 35. Chen WH, Lenderking W, Jin Y, et al. Is Rasch model analysis applicable in small sample size 4 pilot studies for assessing item characteristics? An example using PROMIS pain behavior item BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 bank data. Qual Life Res 2014; 23: 485-493. 7 36. Faul F, Erdfelder E, Buchner A, et al. Statistical power analyses using G*Power 3.1: tests for 8 correlation and regression analyses. Beh Res Methods 2009; 41: 1149-1160. 9 10 37. Mitchell AJ, Morgan JP, Petersen D, et al. Validation of simple visual-analogue thermometer 11 screen for mood complications of cardiovascular disease: the Emotion Thermometers. J Affect 12 Disord 2012; 136: 1257-1263. 13 14 38. Furukawa TA, Kessler RC, Slade T, et al. The performance of the K6 and K10 screening scales 15 for psychological distress in the Australian National Survey of Mental Health and Well-Being. 16 Psychol Med 2003; 33: 357-362. 17 18 39. Kroenke K, SpitzerFor RL, Williams peer JBW, etreview al. An Ultra-Brief onlyScreening Scale for Anxiety and 19 Depression: The PHQ–4. Psychosomatics 2009; 50: 613-621. 20 40. Tennant A, Pallant J. Unidimensionality Matters. Rasch Measurement Transactions 2006; 20: 21 1048-1051. 22 23 41. Horn JL. A rationale and test for the number of factors in factor analysis. Psychometrika 1965; 24 30: 179-185. 25 26 42. Zwick WR, Velicer WF. Comparison of five rules for determining the number of components to 27 retain. Psychol Bull 1986; 99: 432-442. 28 29 43. Masters GN. A rasch model for partial credit scoring. Psychometrika 1982; 47: 149-174. 30 44. Bell RC. Person fit and person reliability. Educ Res Perspect 1982; 9: 105-113. 31 32 45. Shea TL, Tennant A, Pallant JF. Rasch model analysis of the Depression, Anxiety and Stress 33 Scales (DASS). BMC Psychiat 2009; 9: 21. 34 35 46. Ramp M, Khan F, Misajon RA, et al. Rasch analysis of the Multiple Sclerosis Impact Scale MSIS- 36 29. Health Qual Life Outcomes 2009; 7: 58.

37 47. Sharrack B, Hughes RA, Soudain S, et al. The psychometric properties of clinical rating scales http://bmjopen.bmj.com/ 38 used in multiple sclerosis. Brain 1999; 122: 141-159. 39 40 48. Wu M, Adams R. Applying the Rasch model to psycho-social measurement: A practical 41 approach. Educational Measurement Solutions, Melbourne 2007. 42 43 49. Prieto L, Alonso J and Lamarca R. Classical test theory versus rasch analysis for quality of life 44 questionnaire reduction. Health Qual Life Outcomes 2003; 1: 27.

45 on October 1, 2021 by guest. Protected copyright. 50. Mokkink LB, Terwee CB, Knol DL, et al. The COSMIN checklist for evaluating the 46 47 methodological quality of studies on measurement properties: a clarification of its content. 48 BMC Med Res Methodol 2010; 10: 22. 49 51. Terwee CB, Bot SD, de Boer MR, et al. Quality criteria were proposed for measurement 50 properties of health status questionnaires. J Clin Epidemiol 2007; 60: 34-42. 51 52 52. Shrout PE and Fleiss JL. Intraclass correlations: uses in assessing rater reliability. Psychol Bull 53 1979; 86: 420-428. 54 55 53. Kessler RC, Green JG, Gruber MJ, et al. Screening for serious mental illness in the general 56 population with the K6 screening scale: results from the WHO World Mental Health (WMH) 57 survey initiative. Int J Meth Psychiat Res 2010; 19: 4-22. 58 59 60

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1 2 3 54. Löwe B, Wahl I, Rose M, et al. A 4-item measure of depression and anxiety: Validation and 4 standardization of the Patient Health Questionnaire-4 (PHQ-4) in the general population. J BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 Affect Dis 2010; 122: 86-95. 7 55. Kocalevent R-D, Finck C, Jimenez-Leal W, et al. Standardization of the Colombian version of 8 the PHQ-4 in the general population. BMC Psychiat 2014; 14: 205-205. 9 10 56. Nipp RD, El-Jawahri A, Moran SM, et al. The relationship between physical and psychological 11 symptoms and health care utilization in hospitalized patients with advanced cancer. Cancer 12 2017; 123: 4720-4727. 13 14 57. Faessler L, Kutz A, Haubitz S, et al. Psychological distress in medical patients 30 days following 15 an emergency department admission: results from a prospective, observational study. BMC 16 Emerg Med 2016; 16: 33-33. 17 18 58. Lanza ST, RhoadesFor BL. Latent peer class analysis: review an alternative only perspective on subgroup analysis in 19 prevention and treatment. Prev Sci 2013; 14: 157-168. 20 59. MPLUS (Version 6.11). Los Angeles, Calif: Muthen & Muthen. 21 22 60. D'Unger AV, Land KC, McCall PL, et al. How many latent classes of delinquent/criminal 23 careers? Results from mixed Poisson regression analyses. Am J Sociol 1998; 103: 1593-1630. 24 25 61. Nylund KL, Asparouhov T and Muthén BO. Deciding on the number of classes in latent class 26 analysis and growth mixture modeling: A Monte Carlo simulation study. Struct Equat Modeling 27 2007; 14: 535-569. 28 29 62. Goetz C, Coste J, Lemetayer F, et al. Item reduction based on rigorous methodological 30 guidelines is necessary to maintain validity when shortening composite measurement scales. J 31 Clin Epidemiol 2013; 66: 710-718. 32 63. Coste J, Guillemin F, Pouchot J, et al. Methodological approaches to shortening composite 33 34 measurement scales. J Clin Epidemiol 1997; 50: 247-252. 35 64. Beaton DE, Wright JG, Katz JN, et al. Development of the QuickDASH: Comparison of three 36 item-reduction approaches. J Bone Joint Surg 2005; 87-A: 1038-1046.

37 http://bmjopen.bmj.com/ 38 65. Las Hayas C, Quintana JM, Padierna JA, et al. Use of Rasch methodology to develop a short 39 version of the health related quality of life for eating disorders questionnaire: a prospective 40 study. Health Qual Life Outcomes 2010; 8: 29-29. 41 42 66. Nishigami T, Tanaka K, Mibu A, et al. Development and psychometric properties of short form 43 of central sensitization inventory in participants with musculoskeletal pain: A cross-sectional 44 study. PLOS ONE 2018; 13: e0200152.

45 on October 1, 2021 by guest. Protected copyright. 46 67. Hosmer D, Lemeshow S. Applied Logistic Regression. Wiley-Interscience: New York. 2000. 47 68. Koo TK, Li MY. A Guideline of selecting and reporting intraclass correlation coefficients for 48 reliability research. J Chiropract Med 2016; 15: 155-163. 49 50 69. Chan DS, Chau JP, Chang AM. Acute coronary syndromes: cardiac rehabilitation programmes 51 and quality of life J Adv Nurs 2005; 49: 591-599. 52 53 54 55 56 57 58 59 60

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1 2 3 Authors contributions: AJ drafted the article with MLG drafting the psychometric testing 4 component. MR, MLG, DR, CS, MA, JA, RO, MR, BM made contributions to the resulting draft. All BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 authors approved the final version. 7 8 Funding: This project received no specific grant from any funding agency in the public, commercial 9 or not-for-profit sectors. 10 11 Competing interests: All authors declare that they have no competing interests. 12 13 Acknowledgements: The authors would like to thank the patients and patient support groups who 14 assisted in the development of the CDI version for testing. They would also like to acknowledge the 15 generous posthumous gift by Ms Angela Anita Reid to the Australian Centre for Heart Health which 16 is funding this project. 17 18 For peer review only 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

37 http://bmjopen.bmj.com/ 38 39 40 41 42 43 44

45 on October 1, 2021 by guest. Protected copyright. 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Table 1: Numbers required for each stage of the development and testing of the Cardiac Distress 4 Inventory BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 Steps Purpose N required with rationale 7 8 Development 9 Exploratory Establish (74 items X 5=370) cardiac patients (AMI, AF, CABGS, unstable 10 Factor Analysis number of angina plus heart failure patients with New York Heart 11 12 dimensions Association (NYHA) classification of mild (NYHA 11) or 13 moderate (NYHA 111) heart failure. Allowing for 10 percent 14 missing data, a sample size of (74 items X 5=370 + 10% = 407) 15 would therefore be required for this phase of the study. 16 Rasch Analysis Eliminate The Rasch Analysis will utilise the total baseline sample and will 17 18 itemsFor per peernot require review a sub-sample. only 19 dimension 20 Testing 21 22 Test-Retest Establish Relative reliability will be calculated using the intraclass 23 reliability reliability correlation coefficient (ICC), with 95% confidence interval 24 based on a mean-rating (k = 2), absolute-agreement, two-way 25 mixed-effects model68. The ICC is interpreted according to the 26 following criteria: values below 0.5 indicated low reliability, 27 28 values between 0.5 and 0.75 indicated moderate reliability, 29 values between 0.75 and 0.9 indicated good reliability, and 30 values greater than 0.90 indicated excellent reliability, as 31 suggested by Koo et al. 68. Given an expected ICC of 0.80, a 32 conservative 95% CI of ICC of 0.1, and alpha of 0.05, a sample 33 size of 201 is required. Given an expected attrition rate of 20%, 34 a total sample of N=252 from the baseline sample is required 35 for test-retesting. This attrition rate is compatible with rates 36 obtained in previous studies of cardiac rehabilitation (CR) 37 http://bmjopen.bmj.com/ 69 38 participants tested at two time points and is a conservative 39 estimate given the duration between testing in this study is 40 much shorter, at 14 days. This step uses reduced item version. 41 Construct 66 cardiac patients administered both the CDI and K6. (Using 42 43 validity the reduced item version of the CDI). 44

45 on October 1, 2021 by guest. Protected copyright. 46 Latent Class Identify The LCA analysis will utilise the total baseline sample and will 47 Analysis inter- not require a sub-sample. 48 individual 49 differences 50 in response 51 patterns 52 53 54 55 56 57 58 59 60

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Protocol for the development and validation of a measure of persistent psychological and emotional distress in cardiac patients: The Cardiac Distress Inventory ForJournal: peerBMJ Open review only Manuscript ID bmjopen-2019-034946.R1

Article Type: Protocol

Date Submitted by the 03-Apr-2020 Author:

Complete List of Authors: Jackson, Alun; Australian Centre for Heart Health,; Deakin University Faculty of Health Rogerson, Michelle; Australian Centre for Heart Health Le Grande , Michael; Australian Centre for Heart Health; University of Melbourne, Centre for Behaviour Change, Melbourne School of Psychological Sciences Thompson, David; Queen's University Belfast, School of Nursing and Midwifery; Australian Centre for Heart Health Ski, Chantal; Queen’s University, Belfast, School of Nursing and Midwifery; Australian Centre for Heart Health Alvarenga, Marlies; Federation University Australia - Berwick Campus, School of Health and Life Sciences; MonashHeart, Monash Cardiovascular

Research Centre http://bmjopen.bmj.com/ Amerena, John; Barwon Health, Cardiac Services; Deakin School of Medicine Higgins, Rosemary; Australian Centre for Heart Health; Deakin University, Faculty of Health Raciti, Michela; Australian Centre for Heart Health Murphy, Barbara; Australian Centre for Heart Health; Deakin University Faculty of Health

Primary Subject Cardiovascular medicine on October 1, 2021 by guest. Protected copyright. Heading:

Secondary Subject Heading: Mental health

Adult cardiology < CARDIOLOGY, Protocols & guidelines < HEALTH Keywords: SERVICES ADMINISTRATION & MANAGEMENT, Cardiology < INTERNAL MEDICINE, MENTAL HEALTH

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1 2 3 4 5 BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 6 7 8 9 I, the Submitting Author has the right to grant and does grant on behalf of all authors of the Work (as defined 10 in the below author licence), an exclusive licence and/or a non-exclusive licence for contributions from authors 11 who are: i) UK Crown employees; ii) where BMJ has agreed a CC-BY licence shall apply, and/or iii) in accordance 12 with the terms applicable for US Federal Government officers or employees acting as part of their official 13 duties; on a worldwide, perpetual, irrevocable, royalty-free basis to BMJ Publishing Group Ltd (“BMJ”) its 14 licensees and where the relevant Journal is co-owned by BMJ to the co-owners of the Journal, to publish the 15 Work in this journal and any other BMJ products and to exploit all rights, as set out in our licence. 16 17 The Submitting Author accepts and understands that any supply made under these terms is made by BMJ to 18 the Submitting Author Forunless you peer are acting as review an employee on behalf only of your employer or a postgraduate 19 student of an affiliated institution which is paying any applicable article publishing charge (“APC”) for Open 20 Access articles. Where the Submitting Author wishes to make the Work available on an Open Access basis (and 21 intends to pay the relevant APC), the terms of reuse of such Open Access shall be governed by a Creative 22 Commons licence – details of these licences and which Creative Commons licence will apply to this Work are set 23 out in our licence referred to above. 24 25 Other than as permitted in any relevant BMJ Author’s Self Archiving Policies, I confirm this Work has not been 26 accepted for publication elsewhere, is not being considered for publication elsewhere and does not duplicate 27 material already published. I confirm all authors consent to publication of this Work and authorise the granting 28 of this licence. 29 30 31 32 33 34 35 36

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45 on October 1, 2021 by guest. Protected copyright. 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Protocol for the development and validation of a measure of persistent psychological and 4 emotional distress in cardiac patients: The Cardiac Distress Inventory BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 7 8 Alun C Jackson PhD (Corresponding author), Director, Australian Centre for Heart Health, 9 Melbourne, Victoria, Australia; Honorary Professor, Faculty of Health, Deakin University, Geelong, 10 11 Australia; Honorary Professor, Centre on Behavioural Health, University of Hong Kong, Pokfulam, 12 Hong Kong. Address: PO Box 2137, The Royal Melbourne Hospital, Victoria 3050 Australia; Ph: +61 3 13 9326 8544; Email: [email protected] 14 15 Michelle Rogerson PhD, Research Fellow, Australian Centre for Heart Health, Melbourne, Australia. 16 17 Michael R Le Grande MPH, Senior Research Fellow, Australian Centre for Heart Health, Melbourne, 18 Australia; Research Fellow,For Centre peer for Behaviour review Change, Melbourne only School of Psychological 19 Sciences, University of Melbourne, Melbourne, Australia. 20 21 David R Thompson PhD, Professor, School of Nursing and Midwifery, Queen’s University Belfast, UK; 22 Honorary Professorial Fellow, Australian Centre for Heart Health, Melbourne, Australia; Honorary 23 24 Professor, Department of Psychiatry, University of Melbourne, Melbourne, Australia. 25 Chantal F Ski PhD, Reader, School of Nursing and Midwifery, Queen’s University Belfast, UK; 26 27 Honorary Principal Research Fellow, Australian Centre for Heart Health, Melbourne, Australia; 28 Honorary Associate Professor, Department of Psychiatry, University of Melbourne, Melbourne, 29 Australia. 30 31 Marlies E Alvarenga PhD, Lecturer in Psychology, School of Health and Life Sciences, Federation 32 University Australia, Berwick, Australia; Consultant Clinical Psychologist, Monash Cardiovascular 33 Research Centre, MonashHEART, Melbourne, Australia & Monash Health & Department of Medicine, 34 Monash University, Melbourne, Australia & Australian Centre for Heart Health, Melbourne, Australia 35 36 John Amerena MB BS, Director of Cardiac Services, Barwon Health, Geelong, Australia; Clinical

37 http://bmjopen.bmj.com/ 38 Associate Professor, Deakin School of Medicine, University Hospital Geelong, Geelong, Australia. 39 Rosemary O Higgins DPsych, Clinical Consultant (Health Psychology), Australian Centre for Heart 40 41 Health, Melbourne, Australia; Honorary Associate Professor, Department of Psychology, Deakin 42 University, Geelong, Australia; Honorary Associate Professor, Department of Physiotherapy, 43 University of Melbourne, Melbourne, Australia. 44

45 Michela Raciti BPsych, Research Intern, Australian Centre for Heart Health, Melbourne, Australia on October 1, 2021 by guest. Protected copyright. 46 47 Barbara M Murphy PhD, Principal Researcher, Australian Centre for Heart Health, Melbourne, 48 Australia; Honorary Associate Professor, Faculty of Health, Deakin University, Geelong, Australia; 49 Honorary Senior Research Fellow, Department of Psychology, University of Melbourne, Melbourne, 50 Australia. 51 52 Key words: cardiac distress, anxiety, depression, psychometrics, instrument development 53 54 Word count: 4371 55 56 57 58 59 60

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1 2 3 ABSTRACT 4 5 Introduction Distress is experienced by the majority of cardiac patients, yet no cardiac-specific BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 6 measure of distress exists. The aim of this project is to develop and validate the Cardiac Distress 7 Inventory (CDI). Using the CDI, health professionals will be able to identify key clusters of 8 psychological, emotional and social concern to address with patients, post-cardiac event. 9 10 Methods and analysis An item pool will be generated through: identification of items by a 11 multidisciplinary group of clinician researchers; review of generic and condition-specific distress 12 measures; focus group testing with cardiac rehab professionals; feedback from patients. The 13 COSMIN criteria will be used to inform the development of the methodology for determining the 14 CDI’s psychometric properties. The item pool will be tested with 400 cardiac patients and responses 15 subjected to exploratory factor analysis, Rasch analysis, construct validity testing, and latent class 16 17 analysis. ROC analysis will be used to identify the optimal CDI cut off score for distinguishing whether 18 a person experiencesFor clinically peersignificant distress. review only 19 Ethics and dissemination Approved by the Monash Health Human Research Ethics Committee 20 (Approval number – RES-19-0000631L-55979 0). The CDI will be made available to clinicians and 21 22 researchers without charge. The CDI will be translated for use internationally. Study findings will be 23 shared with cardiac patient support groups; academic and medical communities via publications and 24 presentations; in the training of cardiac secondary prevention professionals; and in reports to 25 funders. Authorship for publications will follow the Uniform Requirements for Manuscripts 26 Submitted to Biomedical Journals. 27 28 Strengths and limitations 29 30  This will be the first available cardiac-specific distress measure based on a multidisciplinary 31 32 conceptualisation of the core construct 33  It builds on scale development in oncology and diabetes 34  It will be developed using co-design principles. 35  It will compare a clinically-driven and a statistically-driven method of developing a short-form of 36 the measure for use as a screening tool 37 http://bmjopen.bmj.com/ 38 39 40 41 42 43 44

45 on October 1, 2021 by guest. Protected copyright. 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 BACKGROUND 4 5 Conceptualisation of cardiac distress BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 6 7 As high prevalence conditions, much attention has been paid to the measurement and 8 understanding of anxiety and depression as consequences of cardiac events. However, less attention 9 has been given to the phenomenon of ‘cardiac distress’ which many patients experience after acute 10 coronary events such as myocardial infarction (AMI), unstable angina, or coronary artery bypass 11 graft surgery (CABGS). In an earlier paper, we discussed the conceptualisation of cardiac distress 12 and defined it as: 13 14 “a persistent negative emotional state rather than a transient state; involving multiple 15 psychosocial domains; that challenges a patient’s capacity to cope with living with their heart 16 condition, the treatment of the condition, and the resultant changes to daily living; and 17 challenges the person’s sense of self and future orientation”1. 18 For peer review only 19 A number of previous studies have attempted to examine the relationship between post-cardiac 20 event distress, symptom severity and mortality in relation to a range of specific heart conditions2, 3 21 and procedures4, 5, following cardiac rehabilitation6, and in cardiovascular disease more generally7. A 22 common characteristic of these studies, however, is the use of terms such as ‘distress’ without 23 explicit definition. In some cases, distress is simply defined as being that which is measured by an 24 instrument deemed to measure distress such as the Hospital Anxiety and Depression Scale8, the 25 General Health Questionnaire9 or the Kessler Psychological Distress Scale10. Typically, these studies 26 27 view psychological or emotional distress as a simple combination of anxiety and depression, as does 11 28 a recent analysis of post-cardiac event psychological distress trajectories . 29 A small number of studies of cardiac patients, however, widen this narrow view of distress by adding 30 other psychosocial constructs to ‘anxiety plus depression’, including stress and stressful life events12- 31 14 13, 15 12 14 32 ; fear of death ; hostility ; vital exhaustion and reduced quality of life ; vulnerabilities such as 16 33 lack of pleasant events, dysfunctional attitudes, role transitions and poor dyadic adjustment ; 15 6 34 feelings of helplessness, loss of control, and pain ; and psychological wellbeing . In other chronic 35 conditions such as cancer, diabetes and rheumatic conditions, fear of disease progression has also 36 been identified as an important reason for distress17. This future-oriented component of distress is

37 expressed in an extreme form in cardiac-induced post-traumatic stress disorder (CDI-PTSD) with http://bmjopen.bmj.com/ 38 Vilchinsky and colleagues noting that fear of death dominates the experience of patients with CDI- 39 PTSD18. 40 41 Traumatic components of a cardiac event are the abruptness of the event, the risk of death, and a 42 strong sense of loss of control and helplessness during the event 18. These reactions, coupled with 43 the experience of surgery can lead to significant anxiety associated with death or recurrence, as well 44 as anger, sadness and grief 19, all symptoms associated with PTSD 20, 21. Differentiating distress from

45 on October 1, 2021 by guest. Protected copyright. cardiac disease induced-PTSD (CDI-PTSD), however, are a range of additional psychosocial factors 46 47 such as challenges to people’s coping with daily living, the impact of social isolation, role transitions 48 and challenges, and cognitive issues. 49 The ‘cardiac blues’ 50 51 A broader approach to understanding the complexity of the psychological and emotional impacts of 52 a cardiac event is evidenced in the concept of the ‘cardiac blues’ which describes a range of 53 emotional responses to an acute cardiac event. It has been suggested that almost all patients 54 experience at least some symptoms of the cardiac blues at the time of, or soon after, an acute 55 cardiac event22. Common emotions include shock, low or fluctuating mood, sadness, worry, guilt and 56 57 anger. Mood changes are displayed by tiredness, irritability, tearfulness, loss of pleasure in usual 58 activities, withdrawal from others, early waking and other sleep disturbance, and changes in 59 appetite and sex drive. Cognitive changes that typically co-occur include confusion and forgetfulness, 60 inability to concentrate, nightmares, reduced self-esteem, concerns about role changes, particularly

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1 2 3 regarding paid work, physical health and independence; and pessimism about the future22-24. 4 25, 26 Although generally a transient condition , if the cardiac blues does not resolve within around two BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 months of the cardiac event, the psychological and emotional impact of the event can result in 23, 24 7 persistent cardiac distress . 8 Measuring condition-specific distress 9 10 Both the oncology and diabetes fields have at least a two decade-long history of screening and 11 psychosocial intervention for condition-specific distress. For oncology, this is reflected in the 12 National Comprehensive Cancer Network Guidelines for Distress Management27 where distress is 13 considered to be a multifactorial unpleasant experience of a psychological (i.e., emotional, 14 behavioural, cognitive), social, spiritual, and/or physical nature that may interfere with the ability to 15 cope effectively with cancer, its physical symptoms or its treatment. An excellent earlier attempt to 16 28 17 conceptualise diabetes distress so that it could be recognised and addressed in nursing practice , 29 18 has recently been extendedFor by peerDennick and reviewcolleagues . They characteriseonly distress as a range of 19 negative emotional responses, such as worry, fear, frustration, guilt, sadness, anger, to aspects of 20 living with and managing the condition, balanced against an appraisal of available coping 21 resources29. Snoek and colleagues argue that diabetes-distress and depression are correlated and 22 overlapping constructs, but are not interchangeable, and that distinguishing between them is an 23 important factor in shaping appropriate mental health interventions30. In a recent systematic review 24 of the impact of distress on health-related outcomes, Barry and colleagues agree also that distress is 25 26 distinct from depression and should be assessed using condition-specific measures, as early as 31 27 practicable in treatment . 28 Cardiac-specific measures of the psychosocial impact of cardiac events 29 30 The cardiac field also has a two decade-long history of attempts to measure specific aspects of the 31 psychological and emotional impact of cardiac events. Examples of cardiac-specific measures 32 include the Cardiac Depression Scale32 , the Cardiac Event Threat Questionnaire33, the Cardiac 33 Anxiety Questionnaire34, the MacNew Quality of Life measure35, the Screening Tool for Psychological 34 Distress (STOP–D)36, the Myocardial Infarction Dimensional Assessment Scale (MIDAS)37, and the 35 European Society of Cardiology (ESC) brief (15-item) screen of psychosocial risk factors for cardiac 36 patients38. These measures collectively assess a range of features associated with cardiac distress 37 http://bmjopen.bmj.com/ 38 such as impaired quality of life, anxiety, depression, fear, death anxiety, illness-related dependency, 39 feeling unable to cope, work and family stress, worrying levels of pain, social isolation and low 40 perceived social support , anger and Type D personality. However, there remains no single 41 comprehensive assessment of cardiac distress as we have defined it1. While the Joint ESC Guidelines 42 psychosocial screen is an excellent start in this regard39, and provide an indicator for a health 43 professional that psychosocial support is warranted, a measure is needed that enables a cardiac 44 psychology professional to clearly identify priority areas in order to offer a timely tailored 45 40, 41 on October 1, 2021 by guest. Protected copyright. 46 intervention for a distressed patient . Using the Cardiac Distress Inventory (CDI), health 47 professionals will be able to identify key clusters of psychological, emotional and social concern to 48 address with patients, post-cardiac event at a depth not afforded by one or two questions per 49 construct as in the ESC core questions for the assessment of psychosocial risk factors in clinical 50 practice39. For good clinical intervention, we need to know not just that people are anxious, but they 51 are anxious about. Similarly, what is it that they fear: death, loss of function, loss of role, loss of 52 intimacy? Achieving this degree of granularity to guide intervention is the point of the Cardiac 53 Distress inventory. 54 55 Aims 56 57 The aims of the present study are: 58 1. To develop and validate the Cardiac Distress Inventory (CDI). 59 2. To develop a short form screening tool version of the CDI. 60

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1 2 3 This protocol has been approved by the Monash Health Human Research Ethics Committee 4 (Approval number – RES-19-0000631L-55979 0) BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 METHOD 7 8 The method described in this protocol for development and validation of the CDI conforms, we 9 believe, to the ‘best practices’ for undertaking such a task, outlined by Boateng and colleagues42. 10 11 12 13 Item generation 14 There are six steps in the item generation procedure: 15 16 i. Initial generation of items by a multidisciplinary group of researchers and clinicians 17 including the disciplines of nursing, psychiatry, behavioural health, psychology and 18 cardiology. For peer review only 19 20 ii. Review of generic and condition-specific distress measures, to identify the elements 21 comprising the construct of ‘distress’ in those measures and to identify items which could 22 be adapted for the CDI. 23 iii. Review of cardiac-specific measures incorporating elements of distress as defined by the 24 present authors1. 25 iv. Review of items for appropriateness for a post-operative cardiac population by the 26 multidisciplinary investigator group. 27 v. Focus group testing with two multidisciplinary groups of cardiac rehabilitation 28 29 professionals: experienced practitioners undertaking intensive training in cardiac 30 rehabilitation through the Australian Centre for Heart Health; and the National Executive of 31 the Australian Cardiovascular Health and Rehabilitation Association (ACRA). 32 vi. Consultation with, and feedback from, cardiac patients (key informants) on the structure 33 and content of the CDI. 34 35 Consistent with the approach taken to the PROMIS item bank development and testing43, and our 36 prior conceptualisation of the primary construct of cardiac distress as a multifactorial construct, we

37 expect that the CDI will be a multidimensional measure incorporating emotional, belief, http://bmjopen.bmj.com/ 38 behavioural, cognitive and social domains1 39 40 Patient and public involvement 41 42 The need for a comprehensive measure of cardiac-related distress has been identified by the 43 multidisciplinary clinician researcher members of the CDI development group, through their clinical 44 practice in provision of psychosocial support to cardiac patients. This need has been endorsed by the

45 authors’ consultations with both individual patients and patient support groups such as the hospital- on October 1, 2021 by guest. Protected copyright. 46 based or regionally-based Heart Beat programs such as Heart Beat Victoria. As evident from step vi 47 in the item generation procedure, patients will be consulted as key informants about the structure 48 and content of the CDI. Only after this process of consultation is complete will the CDI item pool be 49 50 tested with 400 cardiac patients. 51 The result of the CDI development project, the psychometrically sound Cardiac Distress Inventory, 52 will be made available to clinicians and researchers without charge, but with a request that data 53 54 collected in studies using the measure will be made available for aggregation and analysis in future. 55 The CDI will also be translated for use with clinical populations internationally with reporting of the 56 psychometric properties of those versions. Confirmed translations will be Italian, Hebrew, Arabic, 57 Farsi, and Spanish. Methods for translation vary44, 45 but we will adopt the following strategy. The CDI 58 will be translated independently by two bilingual cardiac psychologist clinician / researchers. These 59 translations will then be back translated into English by a bilingual psychologist independent of the 60 two original translators and not familiar with the CDI study. These back translations will be reviewed

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1 2 3 by a subgroup of the investigators. Discrepancies will be resolved by consensus between the original 4 translators and the review subgroup. BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 Study findings will be shared with community members, particularly cardiac patient support groups 7 such as the Heart Beat groups and their equivalents internationally; academic and medical 8 communities via publications and presentations; in an online course in its rationale and use provided 9 10 at no cost by the Australian Centre for Heart Health. The short form will be made available on the 11 website of the Australian Centre for Heart Health for completion by patients to self-screen with 12 suggestions for follow up psychological support where indicated. 13 14 Cardiac Distress Inventory design 15 Items generated through the process outlined above will be reworded where appropriate to ensure 16 relevance to the measurement of cardiac distress, and appropriateness of fit with the following 17 18 instruction and responseFor set: peer review only 19 Living with a heart condition can sometimes be difficult. Listed below are some issues that people 20 living with a heart condition may experience. 21 22 Please indicate whether or not you have experienced each issue during the past four weeks by 23 checking ‘Yes’ or ‘No’. For each item you have checked ‘Yes’, indicate how much distress this issue 24 25 has caused you for the past four weeks, from 0 to 3, where “0” is no distress and “3” is severe 26 distress. 27 Issue Yes No If yes, indicate how much distress this causes for you 28 29 No distress Slight Moderate Severe 30 at all distress distress distress 31 Example: Having more pain 0 1 2 3 32 than I expected to have   33 34 35 Trialling of the questionnaire for item reduction 36 Sample size required for trial 37 http://bmjopen.bmj.com/ 38 Recommendations of sample size for exploratory factor analysis in instrument development are that 39 there should be at least 5 cases for each item in the instrument being used46. Rasch modelling for 40 exploratory purposes should be based on at least N=100 and preferably N=25047. For the reliability 41 48 42 and validation study, power calculations were conducted using GPower . Given a probability level of 43 0.05, an anticipated effect size of 0.5, and a desired statistical power level of 0.8, a sample size of 44 N=66 is required per group. A summary of the steps and the number required for each step in the

45 analysis is provided in Table 1. on October 1, 2021 by guest. Protected copyright. 46 47 48

49 50 51 Inclusion and exclusion criteria 52 53 Eligible patients will be those who have had an acute coronary event - namely acute coronary 54 syndrome (ACS), acute myocardial infarction (AMI) or coronary artery bypass graft surgery (CABGS) 55 in the previous 6 months and who are attending either a CR program or an outpatient clinic at a 56 participating hospital. Patients who do not have adequate English language proficiency to read and 57 58 understand the PICF and questionnaire will be excluded. 59 Participant recruitment 60

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1 2 3 A Research Assistant (RA) will recruit patients at two months presentation directly through 4 outpatient clinics or CR programs associated with the investigators. Clinic staff will advise the RA of BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 potentially eligible patients and the RA will then approach these people to ascertain eligibility and 7 willingness to participate. Specific arrangements for site visits will be made between the RA and site 8 investigator by email and telephone. Overall and site-specific ethical approval will be in place. 9 In order to calculate a response rate, the RA will document the number of patients approached and 10 the number who agree to participate and who do not. No identifying information on either 11 12 participants or non-participants will be collected. 13 Data collection 14 15 Consenting participants will complete the PICF and the trial-version CDI, together with basic socio- 16 demographic and event-related information. No identifying information (name, address, date of 17 birth) will be collected as no patient follow-up is required. For reliability and validity testing, 18 participants will also Forbe required peer to complete review the four Emotion only Thermometers49, the Kessler 19 Psychological Distress Scale-650 (K6) and the PHQ-451. In the event that the patient experiences 20 distress while completing the questionnaire, the patient will be reminded by the RA that he/she is 21 22 free to withdraw from the study (i.e., not continue with completing the questionnaire) and will be 23 invited to contact the Australian Centre for Heart Health for a consultation with a clinical psychology 24 specialist at no cost to the patient. 25 Measures 26 27 In addition to the trial-version CDI, the following measures will be administered: 28 29 Demographic questionnaire: Basic socio-demographic (e.g., age, sex, marital status, living 30 arrangement) and cardiac event-related information (event type, date of event) will be collected. 31 Emotion Thermometers. The Emotion Thermometers are single-item measures of distress (DT), 32 33 anxiety (AnxT), depression, (DepT) and anger (AngT). They consist of a “thermometer” with 34 numerals displayed vertically from 0 to 10. Patients rate their distress “over the last week”, with 0 35 indicating “no distress” and 10 indicating “high distress”. A total score from all four mood 36 thermometers (ETsum) indicates overall emotional problems. These thermometers, based on the 27 37 NCCN cancer distress thermometer (DT) , have been shown to be a clinically sensitive measure of http://bmjopen.bmj.com/ 38 distress in patients with mixed cardiovascular conditions49. 39 51 40 Patient Health Questionnaire-4 (PHQ-4): The PHQ is a validated brief screener (4-items) for anxiety 41 and depression, which combines the Patient Health Questionnaire-2 (PHQ-2) and the Generalized 42 Anxiety Disorder-2 (GAD-2)51. Total scores range from 0-12, with 0 indicating “no distress” and 12 43 indicating “severe distress”. 44 Kessler Psychological Distress Scale-650 (K6): The Kessler 6 is a brief measure of psychological distress 45 on October 1, 2021 by guest. Protected copyright. 46 which has been validated in an Australian general population50. The K6 is both an effective screening 47 measure and an indicator of distress severity. Scores range from 6-30, with lower scores indicating 48 higher levels of distress. 49 36 50 Screening Tool for Psychological Distress (STOP-D): This is a five-item, evidence-derived self-report 51 measure generating severity scores for depression, anxiety, stress, anger and poor social support. 52 The screening tool has been tested with patients before and after heart transplant, patients in 53 cardiac rehabilitation and adults with congenital heart disease36. 54 55 Statistical analysis for the trial 56 Part A – Establishing dimensions of the CDI 57 58 Principal component analysis (PCA) using SPSS will be used to assess the dimensions of the CDI. PCA 59 is commonly used in the development of new instruments to provide early indications of possible 60 dimensions before Rasch analysis is attempted52. PCA is used to extract the factors followed by

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1 2 3 oblique rotation of factors using Oblimin rotation (delta = 0). Kaiser's criterion, which retains eigen 4 values above 1, will be used to guide the identification of relevant factors. A second step in the PCA BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 53 6 is to conduct Horn's parallel analysis , considered one of the most accurate approaches to estimate 54 7 the number of components . The size of eigen values obtained from PCA are compared with those 8 obtained from a randomly generated data set of the same size. Only factors with eigen values 9 exceeding the values obtained from the corresponding random data set are retained for further 10 investigation. 11 12 Part B - Eliminating items per dimension of the CDI 13 Rasch analysis is a mathematical technique used to evaluate a latent variable not measurable 14 directly from a set of categorical items. Rasch methods can be used to assess the extent to which 15 individual items represent the underlying construct that an instrument intends to measure. The 16 55 17 Rasch model chosen for this analysis, the Partial Credit Model is applicable to polytomous rather 18 than dichotomous dataFor and is thereforepeer suitable review for Likert scales only and response ratings. 19 Rasch analysis will be conducted using RUMM2030 software (RUMM Laboratory Pty Ltd., Perth, 20 Australia). Three statistics are considered to determine the degree of fit for each CDI scale: overall 21 56 22 fit; individual person fit; and individual item fit . Adequate overall fit of the CDI to the Rasch model 57 23 is indicated by a non-significant Bonferroni adjusted Chi-square probability value . Satisfactory 24 overall item and individual fit for each scale will be determined by a fit residual standard deviation 25 (SD) value of ≤1.5. Individual item fit is indicated by two statistics: fit residual values; and Chi-square 26 probability values. Item fit residual values −2.5 to 2.5 indicate adequate fit58. Above this range 27 (underfit) suggests deviation from the model, below (overfit) suggests that some items in the scale 28 are similar to each other59. A perfect model fit would be reflected by residuals with a mean of 0.00 29 and a SD of 1.00. Any mis-fitting item in terms of infit/outfit is discarded and the analysis re-run. 30 60 31 This iterative process is continued until no further misfit is observed . The Rasch analysis will 32 produce the person separation index (PSI), which indicates the degree to which study participants 61 33 can be differentiated into certain groups (PSI range 0–1). Values for PSI of 0.8 are acceptable . A 34 sample size of at least 100 patients is required to perform a Rasch analysis which can estimate an 35 acceptable PSI value47. 36 Statistical significance will be considered at the 5% level and Bonferroni correction for multiple 37 http://bmjopen.bmj.com/ 38 testing will be applied where appropriate. 39 Psychometric properties of the final Cardiac Distress Inventory 40 41 The COSMIN (Consensus-based Standards for the selection of health Measurement Instruments) 42 criteria for evaluating the methodological quality of health-related patient-reported outcomes will 43 be used to inform the development of the methodology for determining the psychometric 44 properties as far as possible62, 63.

45 on October 1, 2021 by guest. Protected copyright. 46 Reliability 47 48 Internal consistency of the CDI will be determined using Cronbach’s alpha, and evaluation of the 49 Person Separation Index (PSI) from the Rasch analysis. 50 . 51 52 Validity 53 54 Scale comparisons will be used to investigate the concurrent convergent validity of the CDI. Pearson 55 correlation coefficients will be calculated to explore the association between CDI scores and the 56 measure that is commonly used in clinical practice to assess distress, the six-item Kessler K650. 57 Subscale scores of the CDI will be compared with K6 scores where appropriate. We will assess the 58 discriminant validity and predictive validity of the CDI by assessing whether it distinguishes between 59 patients scoring high and low on the K6, using the Australian scoring cut-off of 19 to indicate 60

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1 2 3 probable serious mental illness64. Again, both CDI total and factor scores will be investigated. It is not 4 possible to use a measure of cardiac distress for validity testing as no such measure exists. BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 Pearson correlation coefficients will also be calculated to explore the association between CDI scores 7 and the Patient Health Questionnaire–4 (PHQ4)51. Normative data are available from a nationally 8 representative face-to-face household survey sample of 5030 people, conducted in Germany in 9 200665. The measure has been translated and validated in Hispanic populations, for example66, and 10 has been used in studies of cancer patients67and emergency department patients68. As far as the 11 12 authors are aware, no validation study of the PHQ-4 has been undertaken with cardiac patients. 13 Comparison of CDI scores will also be conducted between the various types of cardiac patients (e.g. 14 AMI vs CABGS). Comparison of groups will be conducted via analysis of variance (ANOVA). 15 16 Latent Class Analysis 17 18 Latent class analysis (LCA)For will bepeer used in order review to describe groups only of participants that differ in their 19 response patterns to the CDI. LCA explains inter-individual differences in response patterns by 20 means of a given number of latent classes (subgroups of participants). LCA estimates the size of the 21 classes and a membership probability for each participant within each class69 and will be performed 22 using Mplus version 6.070. To select the most parsimonious number of classes and maximise model 23 fit, a series of latent class models will be applied to the data. First, the simplest 1-class model (all 24 patients are assumed to have the same pattern of cardiac distress) will be applied to the data, 25 followed by successive models with a unitary increase in the number of latent classes (up to eight). 26 27 Model solutions are evaluated on the basis of their Bayesian information criterion (BIC) and entropy. 28 The BIC has been shown to be a robust indicator of model fit, with lower values indicative of better 29 model fit71. BIC will be used in preference to Akaike information criteria, as the latter has been 30 shown to over-extract classes in simulation models72. The association of CDI latent class membership 31 with CDI scale scores, sociodemographic characteristics, diagnosis and K6 distress scores will also be 32 examined using Mplus70. Mplus generates overall chi-square values to assess significant associations 33 between variables as well as unadjusted chi-square values for exploratory post-hoc analysis. 34 35 Development of a short form Cardiac Distress Inventory for screening purposes 36 A shorter version of the CDI, the CDI-S, will then be created. Importantly, item reduction based on

37 http://bmjopen.bmj.com/ 38 rigorous methodological guidelines is necessary to maintain validity when shortening composite 73 74 39 measurement scales . In addition, there are a number of ways to achieve item reduction . In light 40 of these two points, we will use two methods to develop the short form screening tool – a clinically 41 oriented method and a statistically-driven method. A concept-retention approach will create a short 42 version of the original measure by selection of the top performing item in each domain to become 43 part of the short, concept-retention version75. Rasch analysis as used in a number of health-related 44 item reduction exercises, will also be employed76, 77. The Rasch analysis and psychometric evaluation

45 on October 1, 2021 by guest. Protected copyright. of the CDI-S will follow the format described by Nishigami and colleagues77. Both versions of the CDI- 46 47 S will then be field tested. 48 Thermometer testing 49 50 Receiver operating characteristic (ROC) analysis will be used to identify the optimal CDI scale cut off 51 score for distinguishing whether a person experiences clinically significant distress as defined by the 52 established cut-off thresholds for ETsum (the sum of all four mood thermometers). The Area Under 53 the Curve (AUC) will be used to estimate the overall discriminative accuracy of the CDI scale cut off 54 score relative to the established cut off scores of ETsum (a score >14 indicates moderate and >20 55 indicates severe emotional problems). Using qualitative guidelines for interpreting AUC values78, 56 57 namely AUC≤0.70 as acceptable discrimination, AUC≤0.80 as good discrimination and AUC≤0.90 as 58 excellent discrimination. ROC curves will be used to show the trade-off between the sensitivity (true- 59 positive rate) and specificity (true-negative rate) for every possible cut off score of the CDI Scale. 60

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1 2 3 TIMELINE 4 5 Months 1-2: staff recruitment, CR site recruitment and liaison; Months 3-18: Administration of the BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 6 full item pool draft CDI to patients attending CR or outpatient appointments. Months 19-21: 7 completion of data analysis; Months 22-24: writing up the study findings will be a continuous activity 8 with completion in months 22-24. 9 10 SUMMARY 11 Cardiac distress is complex and various aspects of cardiac distress have been shown to be common 12 13 among cardiac patients. Before cardiac distress can be treated effectively, it needs to be properly 14 measured by a reliable, valid and sensitive instrument. Stress is increasingly being recognised as a 15 prognostic factor in those with pre-existing cardiovascular or cerebrovascular disease 79 and stress 16 management in cardiac rehabilitation shows promise 80. Even so, we are yet to see the totality of 17 cardiac distress, in all of its complexity, being addressed in this way. 18 For peer review only 19 The primary aim of the project, therefore, is to develop a new clinical measure which health 20 professionals can use to identify and assess cardiac distress. They can use the fine-grained 21 assessment provided by this unique measure to structure psychological and emotional interventions 22 to intervene in cases of persistent distress in patients, following a cardiac event. No such measure 23 currently exists. 24 25 While physical recovery remains the highest priority in preventive cardiology, psychological recovery 26 is now considered a primary concern for health professionals working in cardiac rehabilitation and 27 secondary prevention. The prevalence of clinical anxiety and depression in people who have had a 28 cardiac event is up to four times higher than in the general population, however both the prevalence 29 and nature of the broader concept of cardiac-related distress remains unknown. Post-event 30 psychological problems confer an increased mortality risk for patients, highlighting the importance 31 32 of identifying distressed patients early in order to ensure appropriate treatment is received. The new 33 CDI will not only enhance clinicians’ ability to identify distressed patients but will also enable them 34 to identify the specific nature of the distress, thereby optimising their ability to provide timely 35 support targeted to the specific psychosocial needs of the patient. The new CDI has the potential to 36 ensure that patients are provided with the specific support they require in their psychosocial

37 recovery after a cardiac event and, in doing so, has the potential to improve their quality of life, http://bmjopen.bmj.com/ 38 enhance their behaviour change efforts and ultimately extend their survival. 39 40 41 References 42 43 44 1. Jackson AC, Murphy BM, Thompson DR, et al. What is cardiac distress and how should we 45 measure it? British Journal of Cardiac Nursing 2018; 13: 286-293. DOI: 10.12968/bjca.2018.13.6.286. on October 1, 2021 by guest. Protected copyright. 46 2. Stewart RAH, Colquhoun DM, Marschner SL, et al. Persistent psychological distress and 47 48 mortality in patients with stable coronary artery disease. Heart 2017; 103: 1860-1866. 2017/06/28. 49 DOI: 10.1136/heartjnl-2016-311097. 50 3. Lissaker CT, Wallert J, Held C, et al. Emotional distress as a predictor of statin non-adherence 51 among Swedish first-time myocardial infarction patients, 2006-2013. J Psychosom Res 2017; 97: 30- 52 37. 2017/06/14. DOI: 10.1016/j.jpsychores.2017.02.015. 53 4. Habibović M, Mudde L, Pedersen SS, et al. Sleep disturbance in patients with an implantable 54 cardioverter defibrillator: Prevalence, predictors and impact on health status. European Journal of 55 Cardiovascular Nursing 2017; 17: 390-398. DOI: 10.1177/1474515117748931. 56 57 5. Sipotz J, Friedrich O, Hofer S, et al. Health related quality of life and mental distress after PCI: 58 restoring a state of equilibrium. Health Qual Life Outcomes 2013; 11: 144. 2013/08/29. DOI: 59 10.1186/1477-7525-11-144. 60

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1 2 3 6. Gostoli S, Roncuzzi R, Urbinati S, et al. Clinical and Subclinical Distress, Quality of Life, and 4 Psychological Well-Being after Cardiac Rehabilitation. Applied psychology Health and well-being BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 2017; 9: 349-369. 2017/11/25. DOI: 10.1111/aphw.12098. 7 7. Russ TC, Stamatakis E, Hamer M, et al. Association between psychological distress and 8 mortality: individual participant pooled analysis of 10 prospective cohort studies. BMJ (Clinical 9 research ed) 2012; 345: e4933. 2012/08/02. DOI: 10.1136/bmj.e4933. 10 8. Snaith RP and Zigmond AS. The Hospital Anxiety and Depression Scale - Manual. Windsor, 11 UK: NFER-Nelson, 1994. 12 9. Goldberg DP and Hillier VF. A scaled version of the General Health Questionnaire. Psychol 13 Med 1979; 9: 139-145. 1979/02/01. 14 10. Kessler RC, Andrews G, Colpe LJ, et al. Short screening scales to monitor population 15 16 prevalences and trends in non-specific psychological distress. Psychol Med 2002; 32: 959-976. 17 2002/09/07. 18 11. Virtanen M, ElovainioFor M,peer Josefsson K,review et al. Coronary heart only disease and risk factors as 19 predictors of trajectories of psychological distress from midlife to old age. Heart 2017; 103: 659-665. 20 2016/11/20. DOI: 10.1136/heartjnl-2016-310207. 21 12. Kachur S, Menezes AR, De Schutter A, et al. Significance of Comorbid Psychological Stress 22 and Depression on Outcomes After Cardiac Rehabilitation. Am J Med 2016; 129: 1316-1321. 23 2016/08/03. DOI: 10.1016/j.amjmed.2016.07.006. 24 25 13. Whitehead DL, Strike P, Perkins-Porras L, et al. Frequency of distress and fear of dying during 26 acute coronary syndromes and consequences for adaptation. Am J Cardiol 2005; 96: 1512-1516. 27 2005/11/29. DOI: 10.1016/j.amjcard.2005.07.070. 28 14. Claesson M, Burell G, Birgander LS, et al. Psychosocial distress and impaired quality of life - 29 targets neglected in the secondary prevention in women with ischaemic heart disease. European 30 Journal of Cardiovascular Prevention & Rehabilitation 2003; 10: 258-266. DOI: 31 10.1097/01.hjr.0000085255.65733.68. 32 15. Malinauskaite I, Slapikas R, Courvoisier D, et al. The fear of dying and occurrence of 33 posttraumatic stress symptoms after an acute coronary syndrome: A prospective observational 34 35 study. Journal of health psychology 2017; 22: 208-217. 2015/08/28. DOI: 36 10.1177/1359105315600233.

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1 2 3 24. Murphy BM, Higgins RO and Jackson AC. Anxiety, depression and psychological adjustment 4 after an acute cardiac event. In: Alvarenga ME and Byrne D (eds) Handbook of Psychocardiology. BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 Singapore: Springer, 2016. 7 25. Murphy BM, Elliott PC, Higgins RO, et al. Anxiety and depression after coronary artery 8 bypass graft surgery: most get better, some get worse. Eur J Cardiovasc Prev Rehabil 2008; 15: 434- 9 440. 2008/08/05. DOI: 10.1097/HJR.0b013e3282fbc945. 10 26. Tully PJ and Baker RA. Depression, anxiety, and cardiac morbidity outcomes after coronary 11 artery bypass surgery: a contemporary and practical review. Journal of Geriatric Cardiology 2012; 9: 12 197-208. 13 27. NCCN. NCCN Clinical Guidelines in Oncology. Distress Management Version 22017. National 14 Comprehensive Cancer Network, 2017. 15 16 28. Ridner SH. Psychological distress: concept analysis. J Adv Nurs 2004; 45: 536-545. 17 2004/03/11. 18 29. Dennick K, SturtFor J and Speightpeer J. What review is diabetes distress only and how can we measure it? A 19 narrative review and conceptual model. Journal of diabetes and its complications 2017; 31: 898-911. 20 2017/03/10. DOI: 10.1016/j.jdiacomp.2016.12.018. 21 30. Snoek FJ, Bremmer MA and Hermanns N. Constructs of depression and distress in diabetes: 22 time for an appraisal. The lancet Diabetes & endocrinology 2015; 3: 450-460. 2015/05/23. DOI: 23 10.1016/s2213-8587(15)00135-7. 24 25 31. Barry V, Stout ME, Lynch ME, et al. The effect of psychological distress on health outcomes: 26 A systematic review and meta-analysis of prospective studies. Journal of health psychology 2019: 27 1359105319842931. DOI: 10.1177/1359105319842931. 28 32. Hare DL and Davis CR. Cardiac Depression Scale: validation of a new depression scale for 29 cardiac patients. J Psychosom Res 1996; 40: 379-386. 1996/04/01. DOI: 0022399995006125 [pii]. 30 33. Bennett SJ, Puntenney PJ, Walker NL, et al. Development of an instrument to measure threat 31 related to cardiac events. Nursing research 1996; 45: 266-270. 1996/09/01. 32 34. Eifert GH, Thompson RN, Zvolensky MJ, et al. The cardiac anxiety questionnaire: 33 development and preliminary validity. Behav Res Ther 2000; 38: 1039-1053. 2000/09/27. 34 35 35. Valenti L, Lim L, Heller RF, et al. An improved questionnaire for assessing quality of life after 36 acute myocardial infarction. Quality of life research : an international journal of quality of life aspects

37 of treatment, care and rehabilitation 1996; 5: 151-161. 1996/02/01. http://bmjopen.bmj.com/ 38 36. Young QR, Ignaszewski A, Fofonoff D, et al. Brief screen to identify 5 of the most common 39 forms of psychosocial distress in cardiac patients: validation of the screening tool for psychological 40 distress. J Cardiovasc Nurs 2007; 22: 525-534. 2007/12/20. DOI: 41 10.1097/01.jcn.0000297383.29250.14. 42 37. Thompson DR, Jenkinson C, Roebuck A, et al. Development and validation of a short 43 44 measure of health status for individuals with acute myocardial infarction: the myocardial infarction dimensional assessment scale (MIDAS). Quality of life research : an international journal of quality of 45 on October 1, 2021 by guest. Protected copyright. 46 life aspects of treatment, care and rehabilitation 2002; 11: 535-543. 2002/09/11. 47 38. van Montfort E, Denollet J, Widdershoven J, et al. Validity of the European Society of 48 Cardiology's Psychosocial Screening Interview in Patients With Coronary Artery Disease-The 49 THORESCI Study. Psychosom Med 2017; 79: 404-415. 2016/12/07. DOI: 50 10.1097/psy.0000000000000433. 51 39. Piepoli MF, Hoes AW, Agewall S, et al. European Guidelines on cardiovascular disease 52 53 prevention in clinical practice: The Sixth Joint Task Force of the European Society of Cardiology and 54 Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by 55 representatives of 10 societies and by invited experts)Developed with the special contribution of the 56 European Association for Cardiovascular Prevention & Rehabilitation (EACPR). . Eur Heart J 2016; 37: 57 2315-2381. 58 59 60

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1 2 3 40. Pedersen SS and Andersen CM. Minding the heart: Why are we still not closer to treating 4 depression and anxiety in clinical cardiology practice? European Journal of Preventive Cardiology BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 2017: 2047487317744367. DOI: 10.1177/2047487317744367. 7 41. Richards SH, Anderson L, Jenkinson CE, et al. Psychological interventions for coronary heart 8 disease. Cochrane Database Syst Rev 2017; 4: Cd002902. 2017/04/30. DOI: 9 10.1002/14651858.CD002902.pub4. 10 42. Boateng GO, Neilands TB, Frongillo EA, et al. Best Practices for Developing and Validating 11 Scales for Health, Social, and Behavioral Research: A Primer. Frontiers in public health 2018; 6: 149- 12 149. DOI: 10.3389/fpubh.2018.00149. 13 43. Riley WT, Pilkonis P and Cella D. Application of the National Institutes of Health Patient- 14 reported Outcome Measurement Information System (PROMIS) to mental health research. The 15 16 journal of mental health policy and economics 2011; 14: 201-208. 2012/02/22. 17 44. Beaton DE, Bombardier C, Guillemin F, et al. Guidelines for the process of cross-cultural 18 adaptation of self-reportFor measures. peer Spine (Phila review Pa 1976) 2000; only 25: 3186-3191. 2000/12/22. DOI: 19 10.1097/00007632-200012150-00014. 20 45. Kinzie JD and Manson SM. The use of self-rating scales in cross-cultural psychiatry. Hospital 21 & Community Psychiatry 1987; 38: 190-195. 22 46. Polit DF and Beck CT. Essentials of Nursing Research: Appraising Evidence For Nursing 23 Practice, 9th Edition. Philadelphia, USA: Wolters Kluwer, 2018. 24 25 47. Chen WH, Lenderking W, Jin Y, et al. Is Rasch model analysis applicable in small sample size 26 pilot studies for assessing item characteristics? An example using PROMIS pain behavior item bank 27 data. Quality of life research : an international journal of quality of life aspects of treatment, care and 28 rehabilitation 2014; 23: 485-493. 2013/08/06. DOI: 10.1007/s11136-013-0487-5. 29 48. Faul F, Erdfelder E, Buchner A, et al. Statistical power analyses using G*Power 3.1: tests for 30 correlation and regression analyses. Behavior research methods 2009; 41: 1149-1160. 2009/11/10. 31 DOI: 10.3758/brm.41.4.1149. 32 49. Mitchell AJ, Morgan JP, Petersen D, et al. Validation of simple visual-analogue thermometer 33 screen for mood complications of cardiovascular disease: the Emotion Thermometers. J Affect Disord 34 35 2012; 136: 1257-1263. 2011/07/05. DOI: 10.1016/j.jad.2011.06.008. 36 50. Furukawa TA, Kessler RC, Slade T, et al. The performance of the K6 and K10 screening scales

37 for psychological distress in the Australian National Survey of Mental Health and Well-Being. Psychol http://bmjopen.bmj.com/ 38 Med 2003; 33: 357-362. 2003/03/08. 39 51. Kroenke K, Spitzer RL, Williams JBW, et al. An Ultra-Brief Screening Scale for Anxiety and 40 Depression: The PHQ–4. Psychosomatics 2009; 50: 613-621. DOI: https://doi.org/10.1016/S0033- 41 3182(09)70864-3. 42 52. Tennant A and Pallant J. Unidimensionality Matters Rasch Measurement Transactions 2006; 43 44 20: 1048-1051. 53. Horn JL. A rationale and test for the number of factors in factor analysis. Psychometrika 45 on October 1, 2021 by guest. Protected copyright. 46 1965; 30: 179-185. DOI: 10.1007/BF02289447. 47 54. Zwick WR and Velicer WF. Comparison of five rules for determining the number of 48 components to retain. Psychological bulletin 1986; 99: 432-442. 49 55. Masters GN. A rasch model for partial credit scoring. Psychometrika 1982; 47: 149-174. DOI: 50 10.1007/BF02296272. 51 56. Bell RC. Person fit and person reliability. Educational Research & Perspectives 1982; 9: 105- 52 53 113. 54 57. Shea TL, Tennant A and Pallant JF. Rasch model analysis of the Depression, Anxiety and 55 Stress Scales (DASS). BMC psychiatry 2009; 9: 21. 2009/05/12. DOI: 10.1186/1471-244x-9-21. 56 58. Ramp M, Khan F, Misajon RA, et al. Rasch analysis of the Multiple Sclerosis Impact Scale 57 MSIS-29. Health Qual Life Outcomes 2009; 7: 58. 2009/06/24. DOI: 10.1186/1477-7525-7-58. 58 59. Sharrack B, Hughes RA, Soudain S, et al. The psychometric properties of clinical rating scales 59 used in multiple sclerosis. Brain 1999; 122 ( Pt 1): 141-159. 1999/03/02. 60

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1 2 3 60. Wu M and Adams R. Applying the Rasch model to psycho-social measurement: A practical 4 approach. In: Educational Measurement Solutions, (ed.). Melbourne2007. BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 61. Prieto L, Alonso J and Lamarca R. Classical Test Theory versus Rasch analysis for quality of life 7 questionnaire reduction. Health Qual Life Outcomes 2003; 1: 27. 2003/09/04. DOI: 10.1186/1477- 8 7525-1-27. 9 62. Mokkink LB, Terwee CB, Knol DL, et al. The COSMIN checklist for evaluating the 10 methodological quality of studies on measurement properties: a clarification of its content. BMC 11 Med Res Methodol 2010; 10: 22. 2010/03/20. DOI: 10.1186/1471-2288-10-22. 12 63. Terwee CB, Bot SD, de Boer MR, et al. Quality criteria were proposed for measurement 13 properties of health status questionnaires. J Clin Epidemiol 2007; 60: 34-42. 2006/12/13. DOI: 14 10.1016/j.jclinepi.2006.03.012. 15 16 64. Kessler RC, Green JG, Gruber MJ, et al. Screening for Serious Mental Illness in the General 17 Population with the K6 screening scale: results from the WHO World Mental Health (WMH) survey 18 initiative InternationalFor Journal ofpeer Methods in review Psychiatric Research only 2010; 19: 4-22. 19 65. Löwe B, Wahl I, Rose M, et al. A 4-item measure of depression and anxiety: Validation and 20 standardization of the Patient Health Questionnaire-4 (PHQ-4) in the general population. Journal of 21 Affective Disorders 2010; 122: 86-95. DOI: https://doi.org/10.1016/j.jad.2009.06.019. 22 66. Kocalevent R-D, Finck C, Jimenez-Leal W, et al. Standardization of the Colombian version of 23 the PHQ-4 in the general population. BMC psychiatry 2014; 14: 205-205. DOI: 10.1186/1471-244X- 24 25 14-205. 26 67. Nipp RD, El-Jawahri A, Moran SM, et al. The relationship between physical and psychological 27 symptoms and health care utilization in hospitalized patients with advanced cancer. Cancer 2017; 28 123: 4720-4727. 2017/10/23. DOI: 10.1002/cncr.30912. 29 68. Faessler L, Kutz A, Haubitz S, et al. Psychological distress in medical patients 30 days 30 following an emergency department admission: results from a prospective, observational study. 31 BMC emergency medicine 2016; 16: 33-33. DOI: 10.1186/s12873-016-0097-y. 32 69. Lanza ST and Rhoades BL. Latent class analysis: an alternative perspective on subgroup 33 analysis in prevention and treatment. Prevention science : the official journal of the Society for 34 35 Prevention Research 2013; 14: 157-168. 2011/02/15. DOI: 10.1007/s11121-011-0201-1. 36 70. MPLUS (Version 6.11). Los Angeles, Calif.: Muthen & Muthen.

37 71. D'Unger AV, Land KC, McCall PL, et al. How many latent classes of delinquent/criminal http://bmjopen.bmj.com/ 38 careers? Results from mixed Poisson regression analyses. American Journal of Sociology 1998; 103: 39 1593-1630. 40 72. Nylund KL, Asparouhov T and Muthén BO. Deciding on the Number of Classes in Latent Class 41 Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study. Structural Equation 42 Modeling: A Multidisciplinary Journal 2007; 14: 535-569. DOI: 10.1080/10705510701575396. 43 44 73. Goetz C, Coste J, Lemetayer F, et al. Item reduction based on rigorous methodological guidelines is necessary to maintain validity when shortening composite measurement scales. J Clin 45 on October 1, 2021 by guest. Protected copyright. 46 Epidemiol 2013; 66: 710-718. 2013/04/10. DOI: 10.1016/j.jclinepi.2012.12.015. 47 74. Coste J, Guillemin F, Pouchot J, et al. Methodological approaches to shortening composite 48 measurement scales. J Clin Epidemiol 1997; 50: 247-252. 1997/03/01. DOI: 10.1016/s0895- 49 4356(96)00363-0. 50 75. Beaton DE, Wright JG, Katz JN, et al. Development of the QuickDASH: Comparison of three 51 item-reduction approaches. Journal of Bone and Joint Surgery 2005; 87-A: 1038-1046. 52 53 76. Las Hayas C, Quintana JM, Padierna JA, et al. Use of Rasch methodology to develop a short 54 version of the health related quality of life for eating disorders questionnaire: a prospective study. 55 Health and quality of life outcomes 2010; 8: 29-29. DOI: 10.1186/1477-7525-8-29. 56 77. Nishigami T, Tanaka K, Mibu A, et al. Development and psychometric properties of short 57 form of central sensitization inventory in participants with musculoskeletal pain: A cross-sectional 58 study. PLOS ONE 2018; 13: e0200152. DOI: 10.1371/journal.pone.0200152. 59 60

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1 2 3 78. Hosmer D and Lemeshow S. Applied Logistic Regression. Wiley-Interscience : New York. 4 2000. BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 79. Kivimaki M and Steptoe A. Effects of stress on the development and progression of 7 cardiovascular disease. Nat Rev Cardiol 2017. DOI: 10.1038/nrcardio.2017.189. 8 80. Blumenthal JA, Sherwood A, Smith PJ, et al. Enhancing Cardiac Rehabilitation With Stress 9 Management Training: A Randomized, Clinical Efficacy Trial. Circulation 2016; 133: 1341-1350. 10 2016/04/06. DOI: 10.1161/circulationaha.115.018926. 11 12 13 14 15 16 17 18 For peer review only 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

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1 2 3 Authors contributions: AJ drafted the article with MLG drafting the psychometric testing 4 component. MR, MLG, DR, CS, MA, JA, RO, MR, BM made contributions to the resulting draft. All BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 authors approved the final version. 7 8 Funding: This project received no specific grant from any funding agency in the public, commercial 9 or not-for-profit sectors. 10 11 Competing interests: All authors declare that they have no competing interests. 12 13 Acknowledgements: The authors would like to thank the patients and patient support groups who 14 assisted in the development of the CDI version for testing. They would also like to acknowledge the 15 generous posthumous gift by Ms Angela Anita Reid to the Australian Centre for Heart Health which 16 is funding this project. 17 18 For peer review only 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

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1 2 3 Table 1: Numbers required for each stage of the development and testing of the Cardiac Distress 4 Inventory BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 Steps Purpose N required with rationale 7 8 Development 9 Exploratory Establish (74 items X 5=370) cardiac patients (AMI, AF, CABGS, unstable 10 Factor Analysis number of angina plus heart failure patients with New York Heart 11 12 dimensions Association (NYHA) classification of mild (NYHA 11) or 13 moderate (NYHA 111) heart failure. Allowing for 10 percent 14 missing data, a sample size of (74 items X 5=370 + 10% = 407) 15 would therefore be required for this phase of the study. 16 Rasch Analysis Eliminate The Rasch Analysis will utilise the total baseline sample and will 17 18 itemsFor per peernot require review a sub-sample. only 19 dimension 20 Testing 21 22 Construct 66 cardiac patients administered both the CDI and K6. (Using 23 validity the reduced item version of the CDI). 24 25 26 Latent Class Identify The LCA analysis will utilise the total baseline sample and will 27 Analysis inter- not require a sub-sample. 28 29 individual 30 differences 31 in response 32 patterns 33 34 35 36

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Protocol for the development and validation of a measure of persistent psychological and emotional distress in cardiac patients: The Cardiac Distress Inventory ForJournal: peerBMJ Open review only Manuscript ID bmjopen-2019-034946.R2

Article Type: Protocol

Date Submitted by the 21-Apr-2020 Author:

Complete List of Authors: Jackson, Alun; Australian Centre for Heart Health,; Deakin University Faculty of Health Rogerson, Michelle; Australian Centre for Heart Health Le Grande , Michael; Australian Centre for Heart Health; University of Melbourne, Centre for Behaviour Change, Melbourne School of Psychological Sciences Thompson, David; Queen's University Belfast, School of Nursing and Midwifery; Australian Centre for Heart Health Ski, Chantal; Queen’s University, Belfast, School of Nursing and Midwifery; Australian Centre for Heart Health Alvarenga, Marlies; Federation University Australia - Berwick Campus, School of Health and Life Sciences; MonashHeart, Monash Cardiovascular

Research Centre http://bmjopen.bmj.com/ Amerena, John; Barwon Health, Cardiac Services; Deakin School of Medicine Higgins, Rosemary; Australian Centre for Heart Health; Deakin University, Faculty of Health Raciti, Michela; Australian Centre for Heart Health Murphy, Barbara; Australian Centre for Heart Health; Deakin University Faculty of Health

Primary Subject Cardiovascular medicine on October 1, 2021 by guest. Protected copyright. Heading:

Secondary Subject Heading: Mental health

Adult cardiology < CARDIOLOGY, Protocols & guidelines < HEALTH Keywords: SERVICES ADMINISTRATION & MANAGEMENT, Cardiology < INTERNAL MEDICINE, MENTAL HEALTH

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1 2 3 4 5 BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 6 7 8 9 I, the Submitting Author has the right to grant and does grant on behalf of all authors of the Work (as defined 10 in the below author licence), an exclusive licence and/or a non-exclusive licence for contributions from authors 11 who are: i) UK Crown employees; ii) where BMJ has agreed a CC-BY licence shall apply, and/or iii) in accordance 12 with the terms applicable for US Federal Government officers or employees acting as part of their official 13 duties; on a worldwide, perpetual, irrevocable, royalty-free basis to BMJ Publishing Group Ltd (“BMJ”) its 14 licensees and where the relevant Journal is co-owned by BMJ to the co-owners of the Journal, to publish the 15 Work in this journal and any other BMJ products and to exploit all rights, as set out in our licence. 16 17 The Submitting Author accepts and understands that any supply made under these terms is made by BMJ to 18 the Submitting Author Forunless you peer are acting as review an employee on behalf only of your employer or a postgraduate 19 student of an affiliated institution which is paying any applicable article publishing charge (“APC”) for Open 20 Access articles. Where the Submitting Author wishes to make the Work available on an Open Access basis (and 21 intends to pay the relevant APC), the terms of reuse of such Open Access shall be governed by a Creative 22 Commons licence – details of these licences and which Creative Commons licence will apply to this Work are set 23 out in our licence referred to above. 24 25 Other than as permitted in any relevant BMJ Author’s Self Archiving Policies, I confirm this Work has not been 26 accepted for publication elsewhere, is not being considered for publication elsewhere and does not duplicate 27 material already published. I confirm all authors consent to publication of this Work and authorise the granting 28 of this licence. 29 30 31 32 33 34 35 36

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1 2 3 Protocol for the development and validation of a measure of persistent psychological and 4 emotional distress in cardiac patients: The Cardiac Distress Inventory BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 7 8 Alun C Jackson PhD (Corresponding author), Director, Australian Centre for Heart Health, 9 Melbourne, Victoria, Australia; Honorary Professor, Faculty of Health, Deakin University, Geelong, 10 11 Australia; Honorary Professor, Centre on Behavioural Health, University of Hong Kong, Pokfulam, 12 Hong Kong. Address: PO Box 2137, The Royal Melbourne Hospital, Victoria 3050 Australia; Ph: +61 3 13 9326 8544; Email: [email protected] 14 15 Michelle Rogerson PhD, Research Fellow, Australian Centre for Heart Health, Melbourne, Australia. 16 17 Michael R Le Grande MPH, Senior Research Fellow, Australian Centre for Heart Health, Melbourne, 18 Australia; Research Fellow,For Centre peer for Behaviour review Change, Melbourne only School of Psychological 19 Sciences, University of Melbourne, Melbourne, Australia. 20 21 David R Thompson PhD, Professor, School of Nursing and Midwifery, Queen’s University Belfast, UK; 22 Honorary Professorial Fellow, Australian Centre for Heart Health, Melbourne, Australia; Honorary 23 24 Professor, Department of Psychiatry, University of Melbourne, Melbourne, Australia. 25 Chantal F Ski PhD, Reader, School of Nursing and Midwifery, Queen’s University Belfast, UK; 26 27 Honorary Principal Research Fellow, Australian Centre for Heart Health, Melbourne, Australia; 28 Honorary Associate Professor, Department of Psychiatry, University of Melbourne, Melbourne, 29 Australia. 30 31 Marlies E Alvarenga PhD, Lecturer in Psychology, School of Health and Life Sciences, Federation 32 University Australia, Berwick, Australia; Consultant Clinical Psychologist, Monash Cardiovascular 33 Research Centre, MonashHEART, Melbourne, Australia & Monash Health & Department of Medicine, 34 Monash University, Melbourne, Australia & Australian Centre for Heart Health, Melbourne, Australia 35 36 John Amerena MB BS, Director of Cardiac Services, Barwon Health, Geelong, Australia; Clinical

37 http://bmjopen.bmj.com/ 38 Associate Professor, Deakin School of Medicine, University Hospital Geelong, Geelong, Australia. 39 Rosemary O Higgins DPsych, Clinical Consultant (Health Psychology), Australian Centre for Heart 40 41 Health, Melbourne, Australia; Honorary Associate Professor, Department of Psychology, Deakin 42 University, Geelong, Australia; Honorary Associate Professor, Department of Physiotherapy, 43 University of Melbourne, Melbourne, Australia. 44

45 Michela Raciti BPsych, Research Intern, Australian Centre for Heart Health, Melbourne, Australia on October 1, 2021 by guest. Protected copyright. 46 47 Barbara M Murphy PhD, Principal Researcher, Australian Centre for Heart Health, Melbourne, 48 Australia; Honorary Associate Professor, Faculty of Health, Deakin University, Geelong, Australia; 49 Honorary Senior Research Fellow, Department of Psychology, University of Melbourne, Melbourne, 50 Australia. 51 52 Key words: cardiac distress, anxiety, depression, psychometrics, instrument development 53 54 Word count: 4371 55 56 57 58 59 60

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1 2 3 ABSTRACT 4 5 Introduction Distress is experienced by the majority of cardiac patients, yet no cardiac-specific BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 6 measure of distress exists. The aim of this project is to develop and validate the Cardiac Distress 7 Inventory (CDI). Using the CDI, health professionals will be able to identify key clusters of 8 psychological, emotional and social concern to address with patients, post-cardiac event. 9 10 Methods and analysis An item pool will be generated through: identification of items by a 11 multidisciplinary group of clinician researchers; review of generic and condition-specific distress 12 measures; focus group testing with cardiac rehab professionals; feedback from patients. The 13 COSMIN criteria will be used to inform the development of the methodology for determining the 14 CDI’s psychometric properties. The item pool will be tested with 400 cardiac patients and responses 15 subjected to exploratory factor analysis, Rasch analysis, construct validity testing, and latent class 16 17 analysis. ROC analysis will be used to identify the optimal CDI cut off score for distinguishing whether 18 a person experiencesFor clinically peersignificant distress. review only 19 Ethics and dissemination Approved by the Monash Health Human Research Ethics Committee 20 (Approval number – RES-19-0000631L-55979 0). The CDI will be made available to clinicians and 21 22 researchers without charge. The CDI will be translated for use internationally. Study findings will be 23 shared with cardiac patient support groups; academic and medical communities via publications and 24 presentations; in the training of cardiac secondary prevention professionals; and in reports to 25 funders. Authorship for publications will follow the Uniform Requirements for Manuscripts 26 Submitted to Biomedical Journals. 27 28 Strengths and limitations 29 30  This will be the first available cardiac-specific distress measure based on a multidisciplinary 31 32 conceptualisation of the core construct 33  It builds on scale development in oncology and diabetes 34  It will be developed using co-design principles. 35  It will compare a clinically-driven and a statistically-driven method of developing a short-form of 36 the measure for use as a screening tool 37 http://bmjopen.bmj.com/ 38 39 40 41 42 43 44

45 on October 1, 2021 by guest. Protected copyright. 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 BACKGROUND 4 5 Conceptualisation of cardiac distress BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 6 7 As high prevalence conditions, much attention has been paid to the measurement and 8 understanding of anxiety and depression as consequences of cardiac events. However, less attention 9 has been given to the phenomenon of ‘cardiac distress’ which many patients experience after acute 10 coronary events such as myocardial infarction (AMI), unstable angina, or coronary artery bypass 11 graft surgery (CABGS). In an earlier paper, we discussed the conceptualisation of cardiac distress 12 and defined it as: 13 14 “a persistent negative emotional state rather than a transient state; involving multiple 15 psychosocial domains; that challenges a patient’s capacity to cope with living with their heart 16 condition, the treatment of the condition, and the resultant changes to daily living; and 17 challenges the person’s sense of self and future orientation”1. 18 For peer review only 19 A number of previous studies have attempted to examine the relationship between post-cardiac 20 event distress, symptom severity and mortality in relation to a range of specific heart conditions2, 3 21 and procedures4, 5, following cardiac rehabilitation6, and in cardiovascular disease more generally7. A 22 common characteristic of these studies, however, is the use of terms such as ‘distress’ without 23 explicit definition. In some cases, distress is simply defined as being that which is measured by an 24 instrument deemed to measure distress such as the Hospital Anxiety and Depression Scale8, the 25 General Health Questionnaire9 or the Kessler Psychological Distress Scale10. Typically, these studies 26 27 view psychological or emotional distress as a simple combination of anxiety and depression, as does 11 28 a recent analysis of post-cardiac event psychological distress trajectories . 29 A small number of studies of cardiac patients, however, widen this narrow view of distress by adding 30 other psychosocial constructs to ‘anxiety plus depression’, including stress and stressful life events12- 31 14 13, 15 12 14 32 ; fear of death ; hostility ; vital exhaustion and reduced quality of life ; vulnerabilities such as 16 33 lack of pleasant events, dysfunctional attitudes, role transitions and poor dyadic adjustment ; 15 6 34 feelings of helplessness, loss of control, and pain ; and psychological wellbeing . In other chronic 35 conditions such as cancer, diabetes and rheumatic conditions, fear of disease progression has also 36 been identified as an important reason for distress17. This future-oriented component of distress is

37 expressed in an extreme form in cardiac-induced post-traumatic stress disorder (CDI-PTSD) with http://bmjopen.bmj.com/ 38 Vilchinsky and colleagues noting that fear of death dominates the experience of patients with CDI- 39 PTSD18. 40 41 Traumatic components of a cardiac event are the abruptness of the event, the risk of death, and a 42 strong sense of loss of control and helplessness during the event 18. These reactions, coupled with 43 the experience of surgery can lead to significant anxiety associated with death or recurrence, as well 44 as anger, sadness and grief 19, all symptoms associated with PTSD 20, 21. Differentiating distress from

45 on October 1, 2021 by guest. Protected copyright. cardiac disease induced-PTSD (CDI-PTSD), however, are a range of additional psychosocial factors 46 47 such as challenges to people’s coping with daily living, the impact of social isolation, role transitions 48 and challenges, and cognitive issues. 49 The ‘cardiac blues’ 50 51 A broader approach to understanding the complexity of the psychological and emotional impacts of 52 a cardiac event is evidenced in the concept of the ‘cardiac blues’ which describes a range of 53 emotional responses to an acute cardiac event. It has been suggested that almost all patients 54 experience at least some symptoms of the cardiac blues at the time of, or soon after, an acute 55 cardiac event22. Common emotions include shock, low or fluctuating mood, sadness, worry, guilt and 56 57 anger. Mood changes are displayed by tiredness, irritability, tearfulness, loss of pleasure in usual 58 activities, withdrawal from others, early waking and other sleep disturbance, and changes in 59 appetite and sex drive. Cognitive changes that typically co-occur include confusion and forgetfulness, 60 inability to concentrate, nightmares, reduced self-esteem, concerns about role changes, particularly

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1 2 3 regarding paid work, physical health and independence; and pessimism about the future22-24. 4 25, 26 Although generally a transient condition , if the cardiac blues does not resolve within around two BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 months of the cardiac event, the psychological and emotional impact of the event can result in 23, 24 7 persistent cardiac distress . 8 Measuring condition-specific distress 9 10 Both the oncology and diabetes fields have at least a two decade-long history of screening and 11 psychosocial intervention for condition-specific distress. For oncology, this is reflected in the 12 National Comprehensive Cancer Network Guidelines for Distress Management27 where distress is 13 considered to be a multifactorial unpleasant experience of a psychological (i.e., emotional, 14 behavioural, cognitive), social, spiritual, and/or physical nature that may interfere with the ability to 15 cope effectively with cancer, its physical symptoms or its treatment. An excellent earlier attempt to 16 28 17 conceptualise diabetes distress so that it could be recognised and addressed in nursing practice , 29 18 has recently been extendedFor by peerDennick and reviewcolleagues . They characteriseonly distress as a range of 19 negative emotional responses, such as worry, fear, frustration, guilt, sadness, anger, to aspects of 20 living with and managing the condition, balanced against an appraisal of available coping 21 resources29. Snoek and colleagues argue that diabetes-distress and depression are correlated and 22 overlapping constructs, but are not interchangeable, and that distinguishing between them is an 23 important factor in shaping appropriate mental health interventions30. In a recent systematic review 24 of the impact of distress on health-related outcomes, Barry and colleagues agree also that distress is 25 26 distinct from depression and should be assessed using condition-specific measures, as early as 31 27 practicable in treatment . 28 Cardiac-specific measures of the psychosocial impact of cardiac events 29 30 The cardiac field also has a two decade-long history of attempts to measure specific aspects of the 31 psychological and emotional impact of cardiac events. Examples of cardiac-specific measures 32 include the Cardiac Depression Scale32 , the Cardiac Event Threat Questionnaire33, the Cardiac 33 Anxiety Questionnaire34, the MacNew Quality of Life measure35, the Screening Tool for Psychological 34 Distress (STOP–D)36, the Myocardial Infarction Dimensional Assessment Scale (MIDAS)37, and the 35 European Society of Cardiology (ESC) brief (15-item) screen of psychosocial risk factors for cardiac 36 patients38. These measures collectively assess a range of features associated with cardiac distress 37 http://bmjopen.bmj.com/ 38 such as impaired quality of life, anxiety, depression, fear, death anxiety, illness-related dependency, 39 feeling unable to cope, work and family stress, worrying levels of pain, social isolation and low 40 perceived social support , anger and Type D personality. However, there remains no single 41 comprehensive assessment of cardiac distress as we have defined it1. While the Joint ESC Guidelines 42 psychosocial screen is an excellent start in this regard39, and provide an indicator for a health 43 professional that psychosocial support is warranted, a measure is needed that enables a cardiac 44 psychology professional to clearly identify priority areas in order to offer a timely tailored 45 40, 41 on October 1, 2021 by guest. Protected copyright. 46 intervention for a distressed patient . Using the Cardiac Distress Inventory (CDI), health 47 professionals will be able to identify key clusters of psychological, emotional and social concern to 48 address with patients, post-cardiac event at a depth not afforded by one or two questions per 49 construct as in the ESC core questions for the assessment of psychosocial risk factors in clinical 50 practice39. For good clinical intervention, we need to know not just that people are anxious, but they 51 are anxious about. Similarly, what is it that they fear: death, loss of function, loss of role, loss of 52 intimacy? Achieving this degree of granularity to guide intervention is the point of the Cardiac 53 Distress inventory. 54 55 Aims 56 57 The aims of the present study are: 58 1. To develop and validate the Cardiac Distress Inventory (CDI). 59 2. To develop a short form screening tool version of the CDI. 60

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1 2 3 METHOD 4 5 The method described in this protocol for development and validation of the CDI conforms, we BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 6 believe, to the ‘best practices’ for undertaking such a task, outlined by Boateng and colleagues42. 7 8 Item generation 9 10 There are six steps in the item generation procedure: 11 12 i. Initial generation of items by a multidisciplinary group of researchers and clinicians 13 including the disciplines of nursing, psychiatry, behavioural health, psychology and 14 cardiology. 15 ii. Review of generic and condition-specific distress measures, to identify the elements 16 comprising the construct of ‘distress’ in those measures and to identify items which could 17 be adapted for the CDI. 18 iii. Review of cardiac-specificFor peer measures review incorporating elements only of distress as defined by the 19 present authors1. 20 iv. Review of items for appropriateness for a post-operative cardiac population by the 21 22 multidisciplinary investigator group. 23 v. Focus group testing with two multidisciplinary groups of cardiac rehabilitation 24 professionals: experienced practitioners undertaking intensive training in cardiac 25 rehabilitation through the Australian Centre for Heart Health; and the National Executive of 26 the Australian Cardiovascular Health and Rehabilitation Association (ACRA). 27 vi. Consultation with, and feedback from, cardiac patients (key informants) on the structure 28 and content of the CDI. 29 30 Consistent with the approach taken to the PROMIS item bank development and testing43, and our 31 prior conceptualisation of the primary construct of cardiac distress as a multifactorial construct, we 32 expect that the CDI will be a multidimensional measure incorporating emotional, belief, 33 behavioural, cognitive and social domains1 34 35 Patient and public involvement 36

37 The need for a comprehensive measure of cardiac-related distress has been identified by the http://bmjopen.bmj.com/ 38 multidisciplinary clinician researcher members of the CDI development group, through their clinical 39 practice in provision of psychosocial support to cardiac patients. This need has been endorsed by the 40 authors’ consultations with both individual patients and patient support groups such as the hospital- 41 42 based or regionally-based Heart Beat programs such as Heart Beat Victoria. As evident from step vi 43 in the item generation procedure, patients will be consulted as key informants about the structure 44 and content of the CDI. Only after this process of consultation is complete will the CDI item pool be

45 tested with 400 cardiac patients. on October 1, 2021 by guest. Protected copyright. 46 47 Ethics approval and dissemination of the CDI measure 48 This study has been approved by the Monash Health Human Research Ethics Committee (Approval 49 50 number – RES-19-0000631L-55979 0) to run from May 2020 until May 2022. 51 The result of the CDI development project, the psychometrically sound Cardiac Distress Inventory, 52 will be made available to clinicians and researchers without charge, but with a request that data 53 54 collected in studies using the measure be made available for aggregation and analysis in future. The 55 CDI will also be translated for use with clinical populations internationally with reporting of the 56 psychometric properties of those versions. Confirmed translations will be Italian, Hebrew, Arabic, 57 Farsi, and Spanish. Methods for translation vary44, 45 but we will adopt the following strategy. The CDI 58 will be translated independently by two bilingual cardiac psychologist clinician / researchers. These 59 translations will then be back translated into English by a bilingual psychologist independent of the 60 two original translators and not familiar with the CDI study. These back translations will be reviewed

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1 2 3 by a subgroup of the investigators. Discrepancies will be resolved by consensus between the original 4 translators and the review subgroup. BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 Study findings will be shared with community members, particularly cardiac patient support groups 7 such as the Heart Beat peer support groups and their equivalents internationally; academic and 8 medical communities via publications and presentations in which authorship will follow the Uniform 9 10 Requirements for Manuscripts Submitted to Biomedical Journals. An online course and / or webinar 11 on the CDI rationale and use will be provided at no cost by the Australian Centre for Heart Health. 12 The short form will be made available on the website of the Australian Centre for Heart Health for 13 completion by patients to self-screen with suggestions for follow up psychological support where 14 significant distress is indicated. 15 16 Cardiac Distress Inventory design 17 18 Items generated throughFor the processpeer outlined review above will be reworded only where appropriate to ensure 19 relevance to the measurement of cardiac distress, and appropriateness of fit with the following 20 instruction and response set: 21 22 Living with a heart condition can sometimes be difficult. Listed below are some issues that people 23 living with a heart condition may experience. 24 25 Please indicate whether or not you have experienced each issue during the past four weeks by 26 checking ‘Yes’ or ‘No’. For each item you have checked ‘Yes’, indicate how much distress this issue 27 has caused you for the past four weeks, from 0 to 3, where “0” is no distress and “3” is severe 28 distress. 29 30 Issue Yes No If yes, indicate how much distress this causes for you 31 No distress Slight Moderate Severe 32 at all distress distress distress 33 Example: Having more pain 0 1 2 3 34 than I expected to have   35 36

37 Trialling of the questionnaire for item reduction http://bmjopen.bmj.com/ 38 39 Sample size required for trial 40 Recommendations of sample size for exploratory factor analysis in instrument development are that 41 46 42 there should be at least 5 cases for each item in the instrument being used . Rasch modelling for 47 43 exploratory purposes should be based on at least N=100 and preferably N=250 . For the reliability 44 and validation study, power calculations were conducted using GPower48. Given a probability level of

45 0.05, an anticipated effect size of 0.5, and a desired statistical power level of 0.8, a sample size of on October 1, 2021 by guest. Protected copyright. 46 N=66 is required per group. A summary of the steps and the number required for each step in the 47 analysis is provided in Table 1. 48 49 50

51 52 53 54 Inclusion and exclusion criteria 55 Eligible patients will be those who have had an acute coronary event - namely acute coronary 56 syndrome (ACS), acute myocardial infarction (AMI) or coronary artery bypass graft surgery (CABGS) 57 58 in the previous 6 months and who are attending either a CR program or an outpatient clinic at a 59 participating hospital. Patients who do not have adequate English language proficiency to read and 60 understand the PICF and questionnaire will be excluded.

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1 2 3 Participant recruitment 4 5 A Research Assistant (RA) will recruit patients at six months presentation directly through outpatient BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 6 clinics or CR programs associated with the investigators. Clinic staff will advise the RA of potentially 7 eligible patients and the RA will then approach these people to ascertain eligibility and willingness to 8 participate. Specific arrangements for site visits will be made between the RA and site investigator 9 by email and telephone. Overall and site-specific ethical approval will be in place. 10 11 In order to calculate a response rate, the RA will document the number of patients approached and 12 the number who agree to participate and who do not. No identifying information on either 13 participants or non-participants will be collected. 14 15 Data collection 16 Consenting participants will complete the PICF and the trial-version CDI, together with basic socio- 17 18 demographic and event-relatedFor peer information. review No identifying information only (name, address, date of 19 birth) will be collected as no patient follow-up is required. For reliability and validity testing, 20 participants will also be required to complete the four Emotion Thermometers49, the Kessler 21 Psychological Distress Scale-650 (K6) and the PHQ-451. In the event that the patient experiences 22 distress while completing the questionnaire, the patient will be reminded by the RA that he/she is 23 free to withdraw from the study (i.e., not continue with completing the questionnaire) and will be 24 invited to contact the Australian Centre for Heart Health for a consultation with a clinical psychology 25 specialist at no cost to the patient. 26 27 Measures 28 29 In addition to the trial-version CDI, the following measures will be administered: 30 Demographic questionnaire: Basic socio-demographic (e.g., age, sex, marital status, living 31 arrangement) and cardiac event-related information (event type, date of event) will be collected. 32 33 Emotion Thermometers. The Emotion Thermometers are single-item measures of distress (DT), 34 anxiety (AnxT), depression, (DepT) and anger (AngT). They consist of a “thermometer” with 35 numerals displayed vertically from 0 to 10. Patients rate their distress “over the last week”, with 0 36 indicating “no distress” and 10 indicating “high distress”. A total score from all four mood

37 http://bmjopen.bmj.com/ thermometers (ETsum) indicates overall emotional problems. These thermometers, based on the 38 27 39 NCCN cancer distress thermometer (DT) , have been shown to be a clinically sensitive measure of 49 40 distress in patients with mixed cardiovascular conditions . 41 Patient Health Questionnaire-451 (PHQ-4): The PHQ is a validated brief screener (4-items) for anxiety 42 and depression, which combines the Patient Health Questionnaire-2 (PHQ-2) and the Generalized 43 51 44 Anxiety Disorder-2 (GAD-2) . Total scores range from 0-12, with 0 indicating “no distress” and 12 indicating “severe distress”. 45 on October 1, 2021 by guest. Protected copyright. 46 Kessler Psychological Distress Scale-650 (K6): The Kessler 6 is a brief measure of psychological distress 47 which has been validated in an Australian general population50. The K6 is both an effective screening 48 49 measure and an indicator of distress severity. Scores range from 6-30, with lower scores indicating 50 higher levels of distress. 51 Screening Tool for Psychological Distress36(STOP-D): This is a five-item, evidence-derived self-report 52 measure generating severity scores for depression, anxiety, stress, anger and poor social support. 53 54 The screening tool has been tested with patients before and after heart transplant, patients in 36 55 cardiac rehabilitation and adults with congenital heart disease . 56 Statistical analysis for the trial 57 58 Part A – Establishing dimensions of the CDI 59 60

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1 2 3 Principal component analysis (PCA) using SPSS will be used to assess the dimensions of the CDI. PCA 4 is commonly used in the development of new instruments to provide early indications of possible BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 52 6 dimensions before Rasch analysis is attempted . PCA is used to extract the factors followed by 7 oblique rotation of factors using Oblimin rotation (delta = 0). Kaiser's criterion, which retains eigen 8 values above 1, will be used to guide the identification of relevant factors. A second step in the PCA 9 is to conduct Horn's parallel analysis53, considered one of the most accurate approaches to estimate 10 the number of components54. The size of eigen values obtained from PCA are compared with those 11 obtained from a randomly generated data set of the same size. Only factors with eigen values 12 exceeding the values obtained from the corresponding random data set are retained for further 13 investigation. 14 15 Part B - Eliminating items per dimension of the CDI 16 17 Rasch analysis is a mathematical technique used to evaluate a latent variable not measurable 18 directly from a set ofFor categorical peer items. Rasch review methods can be onlyused to assess the extent to which 19 individual items represent the underlying construct that an instrument intends to measure. The 20 Rasch model chosen for this analysis, the Partial Credit Model55 is applicable to polytomous rather 21 than dichotomous data and is therefore suitable for Likert scales and response ratings. 22 23 Rasch analysis will be conducted using RUMM2030 software (RUMM Laboratory Pty Ltd., Perth, 24 Australia). Three statistics are considered to determine the degree of fit for each CDI scale: overall 25 fit; individual person fit; and individual item fit56. Adequate overall fit of the CDI to the Rasch model 26 is indicated by a non-significant Bonferroni adjusted Chi-square probability value57. Satisfactory 27 overall item and individual fit for each scale will be determined by a fit residual standard deviation 28 (SD) value of ≤1.5. Individual item fit is indicated by two statistics: fit residual values; and Chi-square 29 probability values. Item fit residual values −2.5 to 2.5 indicate adequate fit58. Above this range 30 31 (underfit) suggests deviation from the model, below (overfit) suggests that some items in the scale 59 32 are similar to each other . A perfect model fit would be reflected by residuals with a mean of 0.00 33 and a SD of 1.00. Any mis-fitting item in terms of infit/outfit is discarded and the analysis re-run. 34 This iterative process is continued until no further misfit is observed60. The Rasch analysis will 35 produce the person separation index (PSI), which indicates the degree to which study participants 36 can be differentiated into certain groups (PSI range 0–1). Values for PSI of 0.8 are acceptable61. A

37 sample size of at least 100 patients is required to perform a Rasch analysis which can estimate an http://bmjopen.bmj.com/ 38 acceptable PSI value47. 39 40 Statistical significance will be considered at the 5% level and Bonferroni correction for multiple 41 testing will be applied where appropriate. 42 43 Psychometric properties of the final Cardiac Distress Inventory 44 The COSMIN (Consensus-based Standards for the selection of health Measurement Instruments)

45 on October 1, 2021 by guest. Protected copyright. criteria for evaluating the methodological quality of health-related patient-reported outcomes will 46 47 be used to inform the development of the methodology for determining the psychometric 62, 63 48 properties as far as possible . 49 Reliability 50 51 Internal consistency of the CDI will be determined using Cronbach’s alpha, and evaluation of the 52 Person Separation Index (PSI) from the Rasch analysis. 53 54 Validity 55 Scale comparisons will be used to investigate the concurrent convergent validity of the CDI. Pearson 56 correlation coefficients will be calculated to explore the association between CDI scores and the 57 50 58 measure that is commonly used in clinical practice to assess distress, the six-item Kessler K6 . 59 Subscale scores of the CDI will be compared with K6 scores where appropriate. We will assess the 60 discriminant validity and predictive validity of the CDI by assessing whether it distinguishes between

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1 2 3 patients scoring high and low on the K6, using the Australian scoring cut-off of 19 to indicate 4 64 probable serious mental illness . Again, both CDI total and factor scores will be investigated. It is not BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 possible to use a measure of cardiac distress for validity testing as no such measure exists. 7 Pearson correlation coefficients will also be calculated to explore the association between CDI scores 8 and the Patient Health Questionnaire–4 (PHQ4)51. Normative data are available from a nationally 9 representative face-to-face household survey sample of 5030 people, conducted in Germany in 10 200665. The measure has been translated and validated in Hispanic populations, for example66, and 11 67 68 12 has been used in studies of cancer patients and emergency department patients . As far as the 13 authors are aware, no validation study of the PHQ-4 has been undertaken with cardiac patients. 14 Comparison of CDI scores will also be conducted between the various types of cardiac patients (e.g. 15 AMI vs CABGS). Comparison of groups will be conducted via analysis of variance (ANOVA). 16 17 Latent Class Analysis 18 For peer review only 19 Latent class analysis (LCA) will be used in order to describe groups of participants that differ in their 20 response patterns to the CDI. LCA explains inter-individual differences in response patterns by 21 means of a given number of latent classes (subgroups of participants). LCA estimates the size of the 22 classes and a membership probability for each participant within each class69 and will be performed 23 using Mplus version 6.070. To select the most parsimonious number of classes and maximise model 24 fit, a series of latent class models will be applied to the data. First, the simplest 1-class model (all 25 patients are assumed to have the same pattern of cardiac distress) will be applied to the data, 26 27 followed by successive models with a unitary increase in the number of latent classes (up to eight). 28 Model solutions are evaluated on the basis of their Bayesian information criterion (BIC) and entropy. 29 The BIC has been shown to be a robust indicator of model fit, with lower values indicative of better 30 model fit71. BIC will be used in preference to Akaike information criteria, as the latter has been 31 shown to over-extract classes in simulation models72. The association of CDI latent class membership 32 with CDI scale scores, sociodemographic characteristics, diagnosis and K6 distress scores will also be 33 examined using Mplus70. Mplus generates overall chi-square values to assess significant associations 34 between variables as well as unadjusted chi-square values for exploratory post-hoc analysis. 35 36 Development of a short form Cardiac Distress Inventory for screening purposes

37 http://bmjopen.bmj.com/ 38 A shorter version of the CDI, the CDI-S, will then be created. Importantly, item reduction based on 39 rigorous methodological guidelines is necessary to maintain validity when shortening composite 40 measurement scales73. In addition, there are a number of ways to achieve item reduction74. In light 41 of these two points, we will use two methods to develop the short form screening tool – a clinically 42 oriented method and a statistically-driven method. A concept-retention approach will create a short 43 version of the original measure by selection of the top performing item in each domain to become 44 part of the short, concept-retention version75. Rasch analysis as used in a number of health-related

45 on October 1, 2021 by guest. Protected copyright. item reduction exercises, will also be employed76, 77. The Rasch analysis and psychometric evaluation 46 77 47 of the CDI-S will follow the format described by Nishigami and colleagues . Both versions of the CDI- 48 S will then be field tested. 49 Thermometer testing 50 51 Receiver operating characteristic (ROC) analysis will be used to identify the optimal CDI scale cut off 52 score for distinguishing whether a person experiences clinically significant distress as defined by the 53 established cut-off thresholds for ETsum (the sum of all four mood thermometers). The Area Under 54 the Curve (AUC) will be used to estimate the overall discriminative accuracy of the CDI scale cut off 55 score relative to the established cut off scores of ETsum (a score >14 indicates moderate and >20 56 78 57 indicates severe emotional problems). Using qualitative guidelines for interpreting AUC values , 58 namely AUC≤0.70 as acceptable discrimination, AUC≤0.80 as good discrimination and AUC≤0.90 as 59 excellent discrimination. ROC curves will be used to show the trade-off between the sensitivity (true- 60 positive rate) and specificity (true-negative rate) for every possible cut off score of the CDI Scale.

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1 2 3 TIMELINE 4 5 Months 1-2: staff recruitment, CR site recruitment and liaison; Months 3-18: Administration of the BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 6 full item pool draft CDI to patients attending CR or outpatient appointments. Months 19-21: 7 completion of data analysis; Months 22-24: writing up the study findings will be a continuous activity 8 with completion in months 22-24. 9 10 SUMMARY 11 Cardiac distress is complex and various aspects of cardiac distress have been shown to be common 12 13 among cardiac patients. Before cardiac distress can be treated effectively, it needs to be properly 14 measured by a reliable, valid and sensitive instrument. Stress is increasingly being recognised as a 15 prognostic factor in those with pre-existing cardiovascular or cerebrovascular disease 79 and stress 16 management in cardiac rehabilitation shows promise 80. Even so, we are yet to see the totality of 17 cardiac distress, in all of its complexity, being addressed in this way. 18 For peer review only 19 The primary aim of the project, therefore, is to develop a new clinical measure which health 20 professionals can use to identify and assess cardiac distress. They can use the fine-grained 21 assessment provided by this unique measure to structure psychological and emotional interventions 22 to intervene in cases of persistent distress in patients, following a cardiac event. No such measure 23 currently exists. 24 25 While physical recovery remains the highest priority in preventive cardiology, psychological recovery 26 is now considered a primary concern for health professionals working in cardiac rehabilitation and 27 secondary prevention. The prevalence of clinical anxiety and depression in people who have had a 28 cardiac event is up to four times higher than in the general population, however both the prevalence 29 and nature of the broader concept of cardiac-related distress remains unknown. Post-event 30 psychological problems confer an increased mortality risk for patients, highlighting the importance 31 32 of identifying distressed patients early in order to ensure appropriate treatment is received. The new 33 CDI will not only enhance clinicians’ ability to identify distressed patients but will also enable them 34 to identify the specific nature of the distress, thereby optimising their ability to provide timely 35 support targeted to the specific psychosocial needs of the patient. The new CDI has the potential to 36 ensure that patients are provided with the specific support they require in their psychosocial

37 recovery after a cardiac event and, in doing so, has the potential to improve their quality of life, http://bmjopen.bmj.com/ 38 enhance their behaviour change efforts and ultimately extend their survival. 39 40 41 References 42 43 44 1. Jackson AC, Murphy BM, Thompson DR, et al. What is cardiac distress and how should we 45 measure it? British Journal of Cardiac Nursing 2018; 13: 286-293. DOI: 10.12968/bjca.2018.13.6.286. on October 1, 2021 by guest. Protected copyright. 46 2. Stewart RAH, Colquhoun DM, Marschner SL, et al. Persistent psychological distress and 47 48 mortality in patients with stable coronary artery disease. Heart 2017; 103: 1860-1866. 2017/06/28. 49 DOI: 10.1136/heartjnl-2016-311097. 50 3. Lissaker CT, Wallert J, Held C, et al. Emotional distress as a predictor of statin non-adherence 51 among Swedish first-time myocardial infarction patients, 2006-2013. J Psychosom Res 2017; 97: 30- 52 37. 2017/06/14. DOI: 10.1016/j.jpsychores.2017.02.015. 53 4. Habibović M, Mudde L, Pedersen SS, et al. Sleep disturbance in patients with an implantable 54 cardioverter defibrillator: Prevalence, predictors and impact on health status. European Journal of 55 Cardiovascular Nursing 2017; 17: 390-398. DOI: 10.1177/1474515117748931. 56 57 5. Sipotz J, Friedrich O, Hofer S, et al. Health related quality of life and mental distress after PCI: 58 restoring a state of equilibrium. Health Qual Life Outcomes 2013; 11: 144. 2013/08/29. DOI: 59 10.1186/1477-7525-11-144. 60

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1 2 3 24. Murphy BM, Higgins RO and Jackson AC. Anxiety, depression and psychological adjustment 4 after an acute cardiac event. In: Alvarenga ME and Byrne D (eds) Handbook of Psychocardiology. BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 Singapore: Springer, 2016. 7 25. Murphy BM, Elliott PC, Higgins RO, et al. Anxiety and depression after coronary artery 8 bypass graft surgery: most get better, some get worse. Eur J Cardiovasc Prev Rehabil 2008; 15: 434- 9 440. 2008/08/05. DOI: 10.1097/HJR.0b013e3282fbc945. 10 26. Tully PJ and Baker RA. Depression, anxiety, and cardiac morbidity outcomes after coronary 11 artery bypass surgery: a contemporary and practical review. Journal of Geriatric Cardiology 2012; 9: 12 197-208. 13 27. NCCN. NCCN Clinical Guidelines in Oncology. Distress Management Version 22017. National 14 Comprehensive Cancer Network, 2017. 15 16 28. Ridner SH. Psychological distress: concept analysis. J Adv Nurs 2004; 45: 536-545. 17 2004/03/11. 18 29. Dennick K, SturtFor J and Speightpeer J. What review is diabetes distress only and how can we measure it? A 19 narrative review and conceptual model. Journal of diabetes and its complications 2017; 31: 898-911. 20 2017/03/10. DOI: 10.1016/j.jdiacomp.2016.12.018. 21 30. Snoek FJ, Bremmer MA and Hermanns N. Constructs of depression and distress in diabetes: 22 time for an appraisal. The lancet Diabetes & endocrinology 2015; 3: 450-460. 2015/05/23. DOI: 23 10.1016/s2213-8587(15)00135-7. 24 25 31. Barry V, Stout ME, Lynch ME, et al. The effect of psychological distress on health outcomes: 26 A systematic review and meta-analysis of prospective studies. Journal of health psychology 2019: 27 1359105319842931. DOI: 10.1177/1359105319842931. 28 32. Hare DL and Davis CR. Cardiac Depression Scale: validation of a new depression scale for 29 cardiac patients. J Psychosom Res 1996; 40: 379-386. 1996/04/01. DOI: 0022399995006125 [pii]. 30 33. Bennett SJ, Puntenney PJ, Walker NL, et al. Development of an instrument to measure threat 31 related to cardiac events. Nursing research 1996; 45: 266-270. 1996/09/01. 32 34. Eifert GH, Thompson RN, Zvolensky MJ, et al. The cardiac anxiety questionnaire: 33 development and preliminary validity. Behav Res Ther 2000; 38: 1039-1053. 2000/09/27. 34 35 35. Valenti L, Lim L, Heller RF, et al. An improved questionnaire for assessing quality of life after 36 acute myocardial infarction. Quality of life research : an international journal of quality of life aspects

37 of treatment, care and rehabilitation 1996; 5: 151-161. 1996/02/01. http://bmjopen.bmj.com/ 38 36. Young QR, Ignaszewski A, Fofonoff D, et al. Brief screen to identify 5 of the most common 39 forms of psychosocial distress in cardiac patients: validation of the screening tool for psychological 40 distress. J Cardiovasc Nurs 2007; 22: 525-534. 2007/12/20. DOI: 41 10.1097/01.jcn.0000297383.29250.14. 42 37. Thompson DR, Jenkinson C, Roebuck A, et al. Development and validation of a short 43 44 measure of health status for individuals with acute myocardial infarction: the myocardial infarction dimensional assessment scale (MIDAS). Quality of life research : an international journal of quality of 45 on October 1, 2021 by guest. Protected copyright. 46 life aspects of treatment, care and rehabilitation 2002; 11: 535-543. 2002/09/11. 47 38. van Montfort E, Denollet J, Widdershoven J, et al. Validity of the European Society of 48 Cardiology's Psychosocial Screening Interview in Patients With Coronary Artery Disease-The 49 THORESCI Study. Psychosom Med 2017; 79: 404-415. 2016/12/07. DOI: 50 10.1097/psy.0000000000000433. 51 39. Piepoli MF, Hoes AW, Agewall S, et al. European Guidelines on cardiovascular disease 52 53 prevention in clinical practice: The Sixth Joint Task Force of the European Society of Cardiology and 54 Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by 55 representatives of 10 societies and by invited experts)Developed with the special contribution of the 56 European Association for Cardiovascular Prevention & Rehabilitation (EACPR). . Eur Heart J 2016; 37: 57 2315-2381. 58 59 60

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1 2 3 40. Pedersen SS and Andersen CM. Minding the heart: Why are we still not closer to treating 4 depression and anxiety in clinical cardiology practice? European Journal of Preventive Cardiology BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 2017: 2047487317744367. DOI: 10.1177/2047487317744367. 7 41. Richards SH, Anderson L, Jenkinson CE, et al. Psychological interventions for coronary heart 8 disease. Cochrane Database Syst Rev 2017; 4: Cd002902. 2017/04/30. DOI: 9 10.1002/14651858.CD002902.pub4. 10 42. Boateng GO, Neilands TB, Frongillo EA, et al. Best Practices for Developing and Validating 11 Scales for Health, Social, and Behavioral Research: A Primer. Frontiers in public health 2018; 6: 149- 12 149. DOI: 10.3389/fpubh.2018.00149. 13 43. Riley WT, Pilkonis P and Cella D. Application of the National Institutes of Health Patient- 14 reported Outcome Measurement Information System (PROMIS) to mental health research. The 15 16 journal of mental health policy and economics 2011; 14: 201-208. 2012/02/22. 17 44. Beaton DE, Bombardier C, Guillemin F, et al. Guidelines for the process of cross-cultural 18 adaptation of self-reportFor measures. peer Spine (Phila review Pa 1976) 2000; only 25: 3186-3191. 2000/12/22. DOI: 19 10.1097/00007632-200012150-00014. 20 45. Kinzie JD and Manson SM. The use of self-rating scales in cross-cultural psychiatry. Hospital 21 & Community Psychiatry 1987; 38: 190-195. 22 46. Polit DF and Beck CT. Essentials of Nursing Research: Appraising Evidence For Nursing 23 Practice, 9th Edition. Philadelphia, USA: Wolters Kluwer, 2018. 24 25 47. Chen WH, Lenderking W, Jin Y, et al. Is Rasch model analysis applicable in small sample size 26 pilot studies for assessing item characteristics? An example using PROMIS pain behavior item bank 27 data. Quality of life research : an international journal of quality of life aspects of treatment, care and 28 rehabilitation 2014; 23: 485-493. 2013/08/06. DOI: 10.1007/s11136-013-0487-5. 29 48. Faul F, Erdfelder E, Buchner A, et al. Statistical power analyses using G*Power 3.1: tests for 30 correlation and regression analyses. Behavior research methods 2009; 41: 1149-1160. 2009/11/10. 31 DOI: 10.3758/brm.41.4.1149. 32 49. Mitchell AJ, Morgan JP, Petersen D, et al. Validation of simple visual-analogue thermometer 33 screen for mood complications of cardiovascular disease: the Emotion Thermometers. J Affect Disord 34 35 2012; 136: 1257-1263. 2011/07/05. DOI: 10.1016/j.jad.2011.06.008. 36 50. Furukawa TA, Kessler RC, Slade T, et al. The performance of the K6 and K10 screening scales

37 for psychological distress in the Australian National Survey of Mental Health and Well-Being. Psychol http://bmjopen.bmj.com/ 38 Med 2003; 33: 357-362. 2003/03/08. 39 51. Kroenke K, Spitzer RL, Williams JBW, et al. An Ultra-Brief Screening Scale for Anxiety and 40 Depression: The PHQ–4. Psychosomatics 2009; 50: 613-621. DOI: https://doi.org/10.1016/S0033- 41 3182(09)70864-3. 42 52. Tennant A and Pallant J. Unidimensionality Matters Rasch Measurement Transactions 2006; 43 44 20: 1048-1051. 53. Horn JL. A rationale and test for the number of factors in factor analysis. Psychometrika 45 on October 1, 2021 by guest. Protected copyright. 46 1965; 30: 179-185. DOI: 10.1007/BF02289447. 47 54. Zwick WR and Velicer WF. Comparison of five rules for determining the number of 48 components to retain. Psychological bulletin 1986; 99: 432-442. 49 55. Masters GN. A rasch model for partial credit scoring. Psychometrika 1982; 47: 149-174. DOI: 50 10.1007/BF02296272. 51 56. Bell RC. Person fit and person reliability. Educational Research & Perspectives 1982; 9: 105- 52 53 113. 54 57. Shea TL, Tennant A and Pallant JF. Rasch model analysis of the Depression, Anxiety and 55 Stress Scales (DASS). BMC psychiatry 2009; 9: 21. 2009/05/12. DOI: 10.1186/1471-244x-9-21. 56 58. Ramp M, Khan F, Misajon RA, et al. Rasch analysis of the Multiple Sclerosis Impact Scale 57 MSIS-29. Health Qual Life Outcomes 2009; 7: 58. 2009/06/24. DOI: 10.1186/1477-7525-7-58. 58 59. Sharrack B, Hughes RA, Soudain S, et al. The psychometric properties of clinical rating scales 59 used in multiple sclerosis. Brain 1999; 122 ( Pt 1): 141-159. 1999/03/02. 60

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1 2 3 60. Wu M and Adams R. Applying the Rasch model to psycho-social measurement: A practical 4 approach. In: Educational Measurement Solutions, (ed.). Melbourne2007. BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 61. Prieto L, Alonso J and Lamarca R. Classical Test Theory versus Rasch analysis for quality of life 7 questionnaire reduction. Health Qual Life Outcomes 2003; 1: 27. 2003/09/04. DOI: 10.1186/1477- 8 7525-1-27. 9 62. Mokkink LB, Terwee CB, Knol DL, et al. The COSMIN checklist for evaluating the 10 methodological quality of studies on measurement properties: a clarification of its content. BMC 11 Med Res Methodol 2010; 10: 22. 2010/03/20. DOI: 10.1186/1471-2288-10-22. 12 63. Terwee CB, Bot SD, de Boer MR, et al. Quality criteria were proposed for measurement 13 properties of health status questionnaires. J Clin Epidemiol 2007; 60: 34-42. 2006/12/13. DOI: 14 10.1016/j.jclinepi.2006.03.012. 15 16 64. Kessler RC, Green JG, Gruber MJ, et al. Screening for Serious Mental Illness in the General 17 Population with the K6 screening scale: results from the WHO World Mental Health (WMH) survey 18 initiative InternationalFor Journal ofpeer Methods in review Psychiatric Research only 2010; 19: 4-22. 19 65. Löwe B, Wahl I, Rose M, et al. A 4-item measure of depression and anxiety: Validation and 20 standardization of the Patient Health Questionnaire-4 (PHQ-4) in the general population. Journal of 21 Affective Disorders 2010; 122: 86-95. DOI: https://doi.org/10.1016/j.jad.2009.06.019. 22 66. Kocalevent R-D, Finck C, Jimenez-Leal W, et al. Standardization of the Colombian version of 23 the PHQ-4 in the general population. BMC psychiatry 2014; 14: 205-205. DOI: 10.1186/1471-244X- 24 25 14-205. 26 67. Nipp RD, El-Jawahri A, Moran SM, et al. The relationship between physical and psychological 27 symptoms and health care utilization in hospitalized patients with advanced cancer. Cancer 2017; 28 123: 4720-4727. 2017/10/23. DOI: 10.1002/cncr.30912. 29 68. Faessler L, Kutz A, Haubitz S, et al. Psychological distress in medical patients 30 days 30 following an emergency department admission: results from a prospective, observational study. 31 BMC emergency medicine 2016; 16: 33-33. DOI: 10.1186/s12873-016-0097-y. 32 69. Lanza ST and Rhoades BL. Latent class analysis: an alternative perspective on subgroup 33 analysis in prevention and treatment. Prevention science : the official journal of the Society for 34 35 Prevention Research 2013; 14: 157-168. 2011/02/15. DOI: 10.1007/s11121-011-0201-1. 36 70. MPLUS (Version 6.11). Los Angeles, Calif.: Muthen & Muthen.

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1 2 3 78. Hosmer D and Lemeshow S. Applied Logistic Regression. Wiley-Interscience : New York. 4 2000. BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 79. Kivimaki M and Steptoe A. Effects of stress on the development and progression of 7 cardiovascular disease. Nat Rev Cardiol 2017. DOI: 10.1038/nrcardio.2017.189. 8 80. Blumenthal JA, Sherwood A, Smith PJ, et al. Enhancing Cardiac Rehabilitation With Stress 9 Management Training: A Randomized, Clinical Efficacy Trial. Circulation 2016; 133: 1341-1350. 10 2016/04/06. DOI: 10.1161/circulationaha.115.018926. 11 12 13 14 15 16 17 18 For peer review only 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

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1 2 3 Authors contributions: AJ drafted the article with MLG drafting the psychometric testing 4 component. MR, MLG, DR, CS, MA, JA, RO, MR, BM made contributions to the resulting draft. All BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 authors approved the final version. 7 8 Funding: This project received no specific grant from any funding agency in the public, commercial 9 or not-for-profit sectors. 10 11 Competing interests: All authors declare that they have no competing interests. 12 13 Acknowledgements: The authors would like to thank the patients and patient support groups who 14 assisted in the development of the CDI version for testing. They would also like to acknowledge the 15 generous posthumous gift by Ms Angela Anita Reid to the Australian Centre for Heart Health which 16 is funding this project. 17 18 For peer review only 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

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1 2 3 Table 1: Numbers required for each stage of the development and testing of the Cardiac Distress 4 Inventory BMJ Open: first published as 10.1136/bmjopen-2019-034946 on 11 June 2020. Downloaded from 5 6 Steps Purpose N required with rationale 7 8 Development 9 Exploratory Establish (74 items X 5=370) cardiac patients (AMI, AF, CABGS, unstable 10 Factor Analysis number of angina plus heart failure patients with New York Heart 11 12 dimensions Association (NYHA) classification of mild (NYHA 11) or 13 moderate (NYHA 111) heart failure. Allowing for 10 percent 14 missing data, a sample size of (74 items X 5=370 + 10% = 407) 15 would therefore be required for this phase of the study. 16 Rasch Analysis Eliminate The Rasch Analysis will utilise the total baseline sample and will 17 18 itemsFor per peernot require review a sub-sample. only 19 dimension 20 Testing 21 22 Construct 66 cardiac patients administered both the CDI and K6. (Using 23 validity the reduced item version of the CDI). 24 25 26 Latent Class Identify The LCA analysis will utilise the total baseline sample and will 27 Analysis inter- not require a sub-sample. 28 29 individual 30 differences 31 in response 32 patterns 33 34 35 36

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