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For peer review onlyDESIGN AND RATIONALE OF THE MYHEARTMATE STUDY: A RANDOMISED CONTROLLED TRIAL OF A GAME-BASED APP

TO PROMOTE BEHAVIOUR CHANGE IN PATIENTS WITH CARDIOVASCULAR DISEASE.

Journal: BMJ Open

Manuscript ID bmjopen-2018-024269

Article Type: Protocol

Date Submitted by the Author: 18-May-2018

Complete List of Authors: Gallagher, Robyn; University of Sydney, Sydney Nursing SchoolChow, Clara; University of Sydney, Faculty of Medicine and HealthParker, Helen; University of Sydney, Sydney Nursing School; University of Sydney, School of Health SciencesNeubeck, Lis; Edinburgh Napier University, Health and Social CareCelermajer, David; University of Sydney, Faculty of Medicine and Health; Royal Prince Alfred Hospital, Department of CardiologyRedfern, Julie; University of Sydney, Westmead Clinical SchoolTofler, Geoffrey; University of Sydney, Faculty of Medicine and Health; Royal North Shore Hospital, Department of CardiologyBuckley, Thomas; University of Sydney, Sydney Nursing SchoolSchumacher, Tracy; University of Newcastle, Faculty of Health and MedicineFerry, Cate ; Heart FoundationWhitley, Alexandra; University of Sydney, Charles Perkins CentreChen, Lily; Westmead Hospital, Department of CardiologyFigtree, Gemma; University of Sydney, Faculty of Medicine and Health; Kolling Institute of Medical Research

Keywords: Cardiovascular Disease, Secondary Prevention, Mobile Technology, Gamification, Behaviour Change

For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml

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1

DESIGN AND RATIONALE OF THE MYHEARTMATE STUDY: A RANDOMISED

CONTROLLED TRIAL OF A GAME-BASED APP TO PROMOTE BEHAVIOUR

CHANGE IN PATIENTS WITH CARDIOVASCULAR DISEASE.

Robyn Gallagher1 2, Clara K Chow3, Helen Parker26, Lis Neubeck1,2,7, David Celermajer 8-10, Julie Redfern3 11, Geoffrey Tofler 8 12, Thomas Buckley 1, Tracy Schumacher 13 14,

Cate Ferry15, Alexandra Whitley2, Lily Chen34, Gemma Figtree8 16

1 Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health,

University of Sydney, NSW, 2006, Australia

2 Charles Perkins Centre, University of Sydney, NSW, 2006, Australia

3 Westmead Applied Research Centre, Faculty of Medicine and Health, University of

Sydney, NSW, 2006, Australia

4 Department of Cardiology, Westmead Hospital, NSW, 2145, Australia

5 The George Institute for Global Health, NSW, 2042, Australia

6 School of Health Sciences, Faculty of Medicine and Health, University of Sydney,

NSW, 2006, Australia

7 School of Health and Social Care, Edinburgh Napier University, Sighthill, EH11 4QD,

United Kingdom

8 Faculty of Medicine and Health, University of Sydney, NSW, 2006, Australia

9 Department of Cardiology, Royal Prince Alfred Hospital, NSW, 2050, Australia

10 The Heart Research Institute, NSW, 2042, Australia

11 Westmead Clinical School, Faculty of Medicine and Health, University of Sydney,


12 Department of Cardiology, Royal North Shore Hospital, NSW, 2065, Australia

13 Faculty of Health and Medicine, Department of Rural Health, University of Newcastle,


14 Priority Research Centre for Physical Activity and Nutrition, University of Newcastle,


15 National Heart Foundation of Australia (NSW Division), NSW, 2011, Australia

16 Kolling Institute of Medical Research, NSW, 2065, Australia

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Keywords: cardiovascular disease, secondary prevention, mobile technology,

gamification, behaviour change

Corresponding author:

Professor Robyn Gallagher

Room 2210, level 2, building D17

The University of Sydney, NSW, 2006

Email: [email protected]

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Abstract

Introduction

Recurrence of cardiac events is common after a first event, leading to hospitalisations

and increased health burden. Patients have difficulties achieving the lifestyle changes

required for secondary prevention and access to secondary prevention programs is

limited. This study aims to evaluate the impact of a game-based mobile app,

MyHeartMate, which is designed to motivate engagement in secondary prevention

behaviours on cardiovascular risk factors.

Methods and analysis

The MyHeartMate study is a single-blind randomised controlled trial with 6 months

follow up and blinded assessment. Participants (n = 394) with coronary heart disease

will be recruited from hospitals in metropolitan Sydney and randomly allocated to

standard care or the MyHeartMate app intervention. The intervention group will receive

the app, which uses game techniques to promote engagement and lifestyle behaviour

change for secondary prevention. The primary outcome is difference between the

groups in physical activity (MET mins/week) at 6 months. Secondary outcomes include

change in low-density lipoprotein cholesterol, systolic blood pressure, medication

adherence, body mass index, waist circumference, mood and dietary changes at 6

months. Data on app engagement, and patient perspectives of usability and

acceptability, will also be analysed.

Ethics and dissemination

The study has received ethics approval from Northern Sydney Local Health District

Human Research Ethics Committee. The study findings will be disseminated via peer-

reviewed publications and presentation at international scientific meetings/conferences.

Clinical trial registration number: ACTRN12617000869370p

Trial status: Recruitment commenced

Data sharing statement: Data will not be made available as data sharing is not

permitted by our ethics approval.

Word Count: 2597

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Strengths and limitations of this study

• The study evaluates a novel game-based mobile app strategy of accessing

secondary prevention support for reducing CVD risk factors in patients at high

risk of further CVD events.

• A stand-alone freely-available mobile app on iOS and Android platforms is being

tested on coronary heart disease patients.

• This study will be the first to provide rigorous data on effectiveness of a

gamification approach through a randomised controlled trial in CHD patients.

• This initial study is only being conducted in NSW (Australia) and in English,

which may limit potential generalisability to other countries and languages. In the

initial stages of testing, participants may discuss the app during outcome

assessment, limiting blinding; further blinding may be affected by participant

comments.

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Introduction

Globally, coronary heart disease (CHD) is a leading cause of death.1 Recurrent events

are common, leading to hospitalisations and an increased burden on the individual and

the health system.2 Secondary prevention has a key role in limiting recurrence;

however, patients have difficulty achieving the lifestyle changes required, including

increasing levels of physical activity, and medication adherence.3 Data from registries

indicate that 6 months post myocardial infarction (MI) only 68% of patients are taking all

cardioprotective medications prescribed,4 and less than 60% are engaging in sufficient

exercise.5 When patients do engage in secondary prevention, with the support of

effective programs they can reduce cardiovascular mortality and hospital admission.6 7

Despite these benefits, patients often do not participate in these programs; only one

third of MI patients attend cardiac rehabilitation (CR).8 The limited times and location of

conventional CR mean that many patients cannot attend due to travel requirements,

conflict with work and carer demands, and group-based delivery not being a personal

preference.6 8 Therefore, new strategies are needed to enable access to secondary

prevention support.

Advances in technology, particularly through the growth of smartphone use, provide an

opportunity to overcome barriers to secondary prevention access. The adoption of

smartphones has been widespread in developed countries, and adoption by seniors

shows the fastest increase.9 A recent study of 285 cardiac patients reported that 70.9%

used mobile phones, and 54.6% were using technology for health purposes.10

Furthermore, 68% of cardiac patients were interested in receiving CR support via their

mobile phone.11 Mobile technology offers immediate access to information, and the

potential to personalise secondary prevention support and incentivise behaviour

change. In line with the increased availability and affordability of smartphones, there has

been huge expansion in availability of mobile health apps.

Mobile apps show promise for improving CHD risk factor and lifestyle behaviours,

although the evidence is still accumulating for CHD-specific apps.12 A recent systematic

review identified 10 stand-alone apps for adults that had evidence supporting their use

in CHD.13 Benefits were demonstrated for risk factors including blood pressure, body

mass index, cholesterol and exercise capacity, as well as reduction in hospitalisation

rates.13 The reviewers noted that sustained engagement with the app was crucial for

benefits to be achieved, and also reported app features participants preferred. Goal

setting, recognition of achievements, challenges, data entry, team-based competition

and other game-related design techniques were identified as elements most preferred

by app users.

Game-design techniques (gamification) harness innate human desires for competition

and social connection.14 Game techniques include undertaking challenges/quests that

are increasingly difficult, and incorporating rewards and the opportunity for comparison

with other players at each level.15 Game attributes, both alone and in combination, are

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evident in many well-established health behaviour change interventions, regardless of

whether they have that label.16 17 Despite identifying 64 health behaviour apps in the

Apple and Google Play stores in a comprehensive systematic review, the reviewers

concluded that few use game techniques.17 Stand-alone game-based mobile apps

designed specifically for CHD patients are even rarer.

Game strategies accessed through mobile tablets offer insights. Two games, one for

heart failure patients, Heart Health,18 and another for CHD patients and their families,

The Heart Game, have pilot studies which report high levels of engagement19 and

benefits for self-care behaviours. Interest and enjoyment are critical to the feasibility of

game-based apps, and 67% of older cardiac patients are reported to be interested in

game-based CR (67%).11 Both studies reported stronger interest in younger patients.18

19 To date there is very limited research testing of game-based apps for CHD patients,

therefore, the primary objective of this study is to determine the impact of a game-based

app on physical activity. The secondary objective is to determine the impact of the app

on CHD risk factors, lifestyle-based risk factor behaviours, and psychological status. An

additional objective is to determine level of engagement and acceptability of the app in

practice.


Study Design

The MyHeartMate study is a single-blind randomised controlled trial with six-months

follow-up (ACTRN12617000869370p). The study will be conducted in three tertiary

referral hospitals in Sydney, Australia serving ethnically, culturally and

socioeconomically diverse populations. Participants with CHD will be randomly

allocated to either the control group for standard care, or to the intervention group,

whom will be provided the MyHeartMate app to engage with to receive support for

secondary prevention behaviours. Outcomes will be assessed using objective measures

at six months in-person.

Randomisation

Participants will be randomly allocated to either the control group or intervention group

(1:1) via a computerised randomisation schedule (www.randomization.com). After

enrolment, recruiting staff will call the study coordinator (blinded) who will register the

participant and provide the allocation. Participants will be asked not to discuss their

group allocation or the study app during the study and at outcome assessment to

optimise blinding.

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Study population

Eligible patients will be those presenting to hospital for management of coronary heart

disease (CHD). Patients will be eligible if they have 1) presented with acute coronary

syndrome (ACS) and/or have documented CHD on angiography (>50% stenosis in at

least one epicardial vessel), 2) own a smartphone and self-report using apps most days

of the week, 3) provide informed consent, and 4) have sufficient English proficiency to

adequately/successfully interact with the app. Exclusions will apply to candidates who

have visual, fine motor or diagnosed neurocognitive disorder which limits engagement

with the app. A screening log will be used to identify ineligible patients or those who

refuse and include age, gender and reasons for refusal.

Interventions

The control group will receive standard care for CHD, which will include medication

prescription and risk factor reduction advice according to their medical provider’s

determination and the Heart Foundation, My Heart My Life information booklet. The

MyHeartMate group (intervention) will receive standard care, plus an introduction and

access to the MyHeartMate app, and a freely-available brief instructional video on the

app goals and optimal use of the app functions. The MyHeartMate group will be

encouraged to use the app regularly within the 6-month follow up, but may choose how

they do this, including returning to use the app after a period of not using it. Multiple

methods are used within the app design to promote participant’s engagement with the

app and with secondary prevention behaviours (Table 1). The app encourages

participants to take their medications as prescribed and engage with their treating

doctors, undertake regular physical activity, eat a healthy diet, manage their weight and

lipid levels, manage stress and quit smoking if applicable.

All participants will be provided with the research staff contact details and contacted

once during the follow-up period to maximise follow-up. If the MyHeartMate backend log

indicates that a participant has not engaged with the app in the two days following

recruitment a single phone call will be made to the participant for troubleshooting.

Participants may withdraw at any time by contacting the researchers.

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Table 1. MyHeartMate game strategies

Game strategy Examples

Reward systems

Encourage engagement through earning coins for completing health-related challenges, monitoring health data, correctly answering quizzes

I discussed quitting smoking with my doctor today – 20 coins Entry of exercise, weight, blood pressure and cholesterol – 20 coins Correctly answer a multiple choice question on high cholesterol treatment – 10 coins

Undertake challenges

Encourage participation in immediate and ongoing behaviours through selection and performance of health-related challenges (smoking, disease management and medications, activity, healthy eating and weight and wellbeing) of increasing difficulty

I talked to my doctor about getting active today I tracked my activity with a pedometer every day this week I exercised for 30 minutes today I exercised for 30 minutes on 5 days this week

Monitor and track performance

Encourage awareness and goal attainment through regular entry of health data (blood pressure, weight, exercise, medication taking, cholesterol) then displayed on graphs

Activity data are synced with a wearable tracker and updated in real-time and displayed in a graph

Games and quizzes

Promote engagement and enjoyment through fun and challenging games

Moving a red blood cell through junk food hazards

Avatar

A virtual heart which flourishes when provided healthy food, exercise, relaxation and medications purchased through earned coins

Coins earned on activity are used to purchase a bike ride for the avatar which improves in appearance and activity level

Social connection and competition

Engagement and participation in health challenges and app features through a community leader board

Users select a name and their coin tally is ranked against the entire community and their friends

Notifications

Engagement is encouraged through a notification when participation has dropped

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MyHeartMate app intervention development

The MyHeartMate smartphone app is designed to engage CHD patients in secondary

prevention behaviours identified in national guidelines.20 The app is built on an award-

winning behaviour change platform (Habitat the Game) developed by Elevator

Entertainment and has been developed through an iterative process involving experts

and patients. The central feature is a heart avatar, which requires the same care as the

CHD patient, namely healthy food, exercise, mental health/stress-reduction time, and

cardiac-relevant medications. Multiple game strategies are incorporated that are known

to harness innate goal-driven, competition and playful human motivations to promote

engagement in healthy behaviours (Table 1).15 21

The user earns virtual coins to purchase care items for their heart avatar by completing

short- and long-term health-related challenges. These are real-world secondary

prevention tasks including healthy eating, physical activity, achieving a healthy weight,

activities to reduce blood pressure and control blood cholesterol, medication adherence,

quitting smoking (where relevant), and engaging in activities to enhance psychological

wellbeing. A bank of 100 challenges were developed for this purpose based on national

guidelines and then reviewed by an expert multidisciplinary panel, which included

leading clinicians (cardiologists, nurses, a physiotherapist, dietitians, exercise scientist)

as well as academics and researchers. Coins can also be earned by completing real-

world missions, health quizzes, and playing games, which increase in difficulty as the

user progresses. Users can compete with others including their friends via the

community leader board. Performance can be assessed by entering and tracking their

own health data over time through graphs.

The heart avatar appearance and animation was developed in consultation with a

purposive sample of older people who had CHD. (Figure 1) The beta version of the app

was tested and evaluated by CR participants (n = 18) who were requested to interact

with the app most days over two weeks. Feedback on understanding and usefulness

was collected during five focus groups. Changes made based on this feedback included

an introduction to the app and game purpose, acknowledging the serious nature of CHD

and the serious intent of the game (YouTube video tutorials and a Facebook page).

Other changes included brief pop-up instructions for each part of the app when it is first

used, weekly push notifications to use the game if not being used for 7 days (ceasing at

21 days), open availability on the app store for family and friends, easier tracking and

data entry through syncing with a wearable tracker (FitBit Flex TM), easy-to-read graphs

on their data, easy log-in and forgotten password tab and visual reminder of scrolling.

Back-end data from the app, emailed to the research team and viewed via a password-

protected internet interface, allows the research team to send congratulatory emails to

users when they have achieved a particular goal, such as “My blood pressure is less

than 130/90 for the first time”, or “My weight is in the healthy range for the first time”.

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These are more tangible rewards for using the app, and are expected to result in

improved user perception of the app and increased likelihood of continuing to use the

app and continuing to record user achievement of real-world missions in the app.

Study Outcomes

The primary outcome of the study is improvement (difference between intervention and

control groups) in physical activity in terms of Metabolic Equivalent of Task (MET)

minutes/week (MET-min/week), as measured by the wearable activity tracker FitBit Flex

TM. Physical activity has been selected given the strong association with survival in

CHD patients.22 Automated upload ensures blinding of assessment. Secondary

outcomes include improvement (difference between intervention and control groups) in

physical activity components, lipid levels, body mass index and waist circumference,

blood pressure, dietary intake, psychological state, cardiac events including myocardial

infarction, death or any hospital presentation or admission, participation in CR or other

secondary prevention strategies, and visits to healthcare providers. Outcomes and

measures are provided in detail in Table 2. Additional outcomes assessed include

engagement with the My Heart Mate app. The combined/ absolute number of modifiable

risk factors above/below target thresholds will be calculated. Participants will be

assessed during an in-person interview at 6 months.

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Table 2. Primary and secondary outcomes measured at baseline and outcome

Outcome Measure

Primary

Physical activity - MET-min/week Fitbit Flex TM activity tracker worn on the non-dominant wrist for four consecutive days (three weekdays plus one weekend day)21

Secondary

Physical activity - average steps/day, minutes of moderate and vigorous physical activity/day

Fitbit Flex TM as above and Global Physical Activity Questionnaire (GPAQ)(16-item questionnaire measuring activity at work, travel and leisure)23

Lipid levels - total cholesterol, low-density lipoprotein cholesterol, triglycerides

Fasting blood sample

Systolic blood pressure Mean of three seated digital recordings

Body mass index (kg/m2) and waist circumference

Mean of three using digital scale and metal tape

Dietary intake – average daily fruit and vegetable portion intake

Self-report 25

Smoking status Self-report 25

Psychological state - anxiety and depression symptoms

Hospital Anxiety and Depression Scale (HADS)24 (14-item questionnaire, depression and anxiety scores categorised as normal (0-7), mild or more (8-21)

Combined CHD risk Calculation of absolute number of modifiable risk factors above/below target thresholds

Process measures

Level of competence with technology will be assessed at baseline using 2 questions on

confidence,10 and the e-Health Literacy Scale (eHEALS) with 8 items.25 Engagement

with the app will be assessed using the app log file for number and type of challenges

and quizzes undertaken, total coins earned and completion of profile data.

Communication with staff will be noted in detailed recruitment logs.

MyHeartMate acceptability and feasibility will be assessed through a questionnaire after

the 6 month follow-up assessment. Items will include acceptability of the game format,

reminders, identification of game aspects participants liked or disliked, their perceptions

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of the utility of game aspects for their cardiac health, use of tutorial videos and

suggestions for improvement.

Potential facilitators and barriers to the effectiveness of the app will be assessed

through four focus groups of a subsample of 20-25 participants of intervention group

participants. Recruitment will occur on the basis of ensuring diversity in gender, age and

geography. Sampling will occur until theoretical saturation (no new themes emerge),

which is expected to occur at 20-25 interviews.26 Focus groups will address individual

app use, likes and dislikes, the effectiveness of different game aspects for behaviour

change, the appropriateness of the visual elements, the ease and understanding of the

app features, language and content, and any discussion or sharing of the app with

others. All interviews will be audio-recorded and transcribed, and entered into NVIVO 7

for analyses. An iterative process of reading, identifying themes and checking will be

used for analyses.26

Statistical considerations

Study data will be analysed using intention-to-treat principles. The primary analysis will

use analysis of covariance (ANCOVA) with baseline values of the study outcome

measures used as covariates where appropriate for continuous variables. This method

will be used for the primary outcome of MET-min/week and for secondary outcomes of

mean daily step count and minutes of moderate-vigorous exercise, lipid levels, BMI,

waist, blood pressure, anxiety and depression at 6-months. Categorical variables

(smoking, achieving risk factors at guideline level) will be compared using Chi-squared

tests for categorical variables. Additionally, relative risks, with 95% confidence intervals

will be calculated to compare groups using log-binomial regression.

Sample size has been calculated based on detecting a difference of 345 MET-min/wk

between the control and intervention groups based on the TEXT ME secondary

prevention study in a similar population.27 Assuming r=0.5 correlation between baseline

and final outcome measurement with alpha=0.05 and power (1-Beta)=0.95, the required

sample size is 164 patients per group, assuming a 1:1 allocation ratio for control and

intervention groups. The total sample size, of 328 with an additional allowance of 20%

loss to follow-up, is 394 patients.


The study will be administered by the University of Sydney. A research management

committee including experts in large-scale trials, CHD treatment, qualitative analyses

and translation into practice, will be overseeing the design and conduct of the research.

The study has received Human Research Ethics approval from Northern Sydney Local

Health District and governance approval from all recruitment sites. The study is guided

by, and adheres to, the National Health and Medical Research Council of Australia

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ethical guidelines for human research. All participants will have provided written and

informed consent, verified by a witness. The study findings will be disseminated via

publication of peer-reviewed manuscripts, and presentations at international

conferences, as well as through media publications. It is anticipated that the findings will

help to inform future developments in the delivery of secondary prevention of CHD.

Conclusions

This study will evaluate a novel strategy of accessing secondary prevention support for

reducing CHD risk factors in patients at high risk of further CHD events. No published

study has evaluated a game-based mobile app designed specifically for CHD patients in

a randomised controlled trial; therefore, this study will be the first to provide rigorous

data on effectiveness of this approach in CHD patients.

Smartphone technology has the potential to address many of the obstacles CHD

patients face in accessing secondary prevention programs.13 However, strategies are

not clearly articulated in study methods or engagement with individual components is

poorly quantified. The study will address these deficits and explore relationships

between strategies and outcomes. Furthermore, the app may be used in conjunction

with evidence-based programs such as CR to provide additional support for behaviour

change and scaled-up for large numbers of CHD patients.

The MyHeartMate study will test the efficacy of a game-based smartphone app to

improve CHD risk factors and lifestyle behaviours in patients who have CHD. The

MyHeartMate app provides a potential platform for smartphone apps for secondary

prevention in patients with other chronic diseases, and, as an openly available app, the

potential for standalone access to large numbers of people affected by CHD and their

families.

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References

1. World Health Organisation. WHO fact sheet no. 317: World Health Organisation,;

2011 [Available from: http://www.who.int/en/news-room/fact-

sheets/detail/cardiovascular-diseases-(cvds).

2. Atkins ER, Geelhoed EA, Knuiman M, et al. One third of hospital costs for

atherothrombotic disease are attributable to readmissions: a linked data analysis. BMC

health services research 2014;14:338. doi: 10.1186/1472-6963-14-338 [published

Online First: 2014/08/12]

3. Shore S, Jones PG, Maddox TM, et al. Longitudinal persistence with secondary

prevention therapies relative to patient risk after myocardial infarction. Heart (British

Cardiac Society) 2015;101(10):800-7. doi: 10.1136/heartjnl-2014-306754 [published


4. Brieger DB, Chow C, Gullick J, et al. Improving patient adherence to secondary

prevention medications 6 months after an acute coronary syndrome: observational

cohort study. Internal medicine journal 2018 doi: 10.1111/imj.13736 [published Online

First: 2018/01/19]

5. Urbinati S, Olivari Z, Gonzini L, et al. Secondary prevention after acute myocardial

infarction: drug adherence, treatment goals, and predictors of health lifestyle habits. The

BLITZ-4 Registry. European journal of preventive cardiology 2015;22(12):1548-56. doi:

10.1177/2047487314561876 [published Online First: 2014/12/03]

6. Clark AM, Hartling L, Vandermeer B, et al. Meta-analysis: secondary prevention

programs for patients with coronary artery disease. Annals of internal medicine

2005;143(9):659-72. [published Online First: 2005/11/03]

7. Anderson L, Thompson DR, Oldridge N, et al. Exercise-based cardiac rehabilitation

for coronary heart disease. The Cochrane database of systematic reviews

2016(1):Cd001800. doi: 10.1002/14651858.CD001800.pub3 [published Online First:

2016/01/06]

8. Peters AE, Keeley EC. Trends and Predictors of Participation in Cardiac

Rehabilitation Following Acute Myocardial Infarction: Data From the Behavioral Risk

Factor Surveillance System. Journal of the American Heart Association 2017;7(1) doi:

10.1161/jaha.117.007664 [published Online First: 2017/12/31]

9. Deloitte. Australian media and digital preferences - 4th edition Deloitte; 2015

[Available from: https://www2.deloitte.com/content/dam/Deloitte/

au/Documents/technology-media-telecommunications/deloitte-au-tmt-media-consumer-

survey-2015-100815.pdf accessed 8 October 2017.

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15

10. Gallagher R, Roach K, Sadler L, et al. Mobile Technology Use Across Age Groups

in Patients Eligible for Cardiac Rehabilitation: Survey Study. JMIR mHealth and uHealth

2017;5(10):e161. doi: 10.2196/mhealth.8352 [published Online First: 2017/10/27]

11. Buys R, Claes J, Walsh D, et al. Cardiac patients show high interest in technology

enabled cardiovascular rehabilitation. BMC medical informatics and decision making

2016;16:95. doi: 10.1186/s12911-016-0329-9 [published Online First: 2016/07/20]

12. Neubeck L, Lowres N, Benjamin EJ, et al. The mobile revolution--using smartphone

apps to prevent cardiovascular disease. Nature reviews Cardiology 2015;12(6):350-60.

doi: 10.1038/nrcardio.2015.34 [published Online First: 2015/03/25]

13. Coorey GM, Neubeck L, Mulley J, et al. Effectiveness, acceptability and usefulness

of mobile applications for cardiovascular disease self-management: Systematic review

with meta-synthesis of quantitative and qualitative data. European journal of preventive

cardiology 2018;25(5):505-21. doi: 10.1177/2047487317750913 [published Online First:

2018/01/10]

14. King D, Greaves F, Exeter C, et al. 'Gamification': influencing health behaviours with

games. Journal of the Royal Society of Medicine 2013;106(3):76-8. doi:


15. Cugelman B. Gamification: what it is and why it matters to digital health behavior

change developers. JMIR serious games 2013;1(1):e3. doi: 10.2196/games.3139

[published Online First: 2013/01/01]

16. Michie S, Richardson M, Johnston M, et al. The behavior change technique

taxonomy (v1) of 93 hierarchically clustered techniques: building an international

consensus for the reporting of behavior change interventions. Annals of behavioral

medicine : a publication of the Society of Behavioral Medicine 2013;46(1):81-95. doi:

10.1007/s12160-013-9486-6 [published Online First: 2013/03/21]

17. Edwards EA, Lumsden J, Rivas C, et al. Gamification for health promotion:

systematic review of behaviour change techniques in smartphone apps. BMJ open

2016;6(10):e012447. doi: 10.1136/bmjopen-2016-012447 [published Online First:

2016/10/07]

18. Radhakrishnan K, Toprac P, O'Hair M, et al. Interactive Digital e-Health Game for

Heart Failure Self-Management: A Feasibility Study. Games for health journal

2016;5(6):366-74. doi: 10.1089/g4h.2016.0038 [published Online First: 2016/12/16]

19. Dithmer M, Rasmussen JO, Gronvall E, et al. "The Heart Game": Using

Gamification as Part of a Telerehabilitation Program for Heart Patients. Games for

health journal 2016;5(1):27-33. doi: 10.1089/g4h.2015.0001 [published Online First:

2015/11/19]

20. National Heart Foundation of Australia, Cardiac Society of Australia and New

Zealand. Reducing risk in heart disease: an expert guide to clinical practice for

Page 15 of 21


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secondary prevention of coronary heart disease. Melbourne: National Heart Foundation

of Australia,, 2012.

21. Alharbi M, Bauman A, Neubeck L, et al. Validation of Fitbit-Flex as a measure of

free-living physical activity in a community-based phase III cardiac rehabilitation

population. European journal of preventive cardiology 2016;23(14):1476-85. doi:


22. Loprinzi PD, Addoh O. The Effects of Free-Living Physical Activity on Mortality After

Coronary Artery Disease Diagnosis. Clinical cardiology 2016;39(3):165-9. doi:

10.1002/clc.22508 [published Online First: 2016/01/11]

23. World Health Organisation. Global Physical Activity Questionnaire (GPAQ) Analysis

Guide Geneva: World Health Organisation; 2013 [Available from:

https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=

8&ved=0ahUKEwiCrcfA6OnaAhWHq5QKHVq2A1QQFggsMAA&url=http%3A%2F%2F

www.who.int%2Fchp%2Fsteps%2Fresources%2FGPAQ_Analysis_Guide.pdf%3Fua%3

D1&usg=AOvVaw2hx6U8xpTGKLegxzLp_NP-.

24. Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta

psychiatrica Scandinavica 1983;67(6):361-70. [published Online First: 1983/06/01]

25. Norman CD, Skinner HA. eHEALS: The eHealth Literacy Scale. Journal of medical

Internet research 2006;8(4):e27. doi: 10.2196/jmir.8.4.e27 [published Online First:

2007/01/11]

26. Brod M, Tesler LE, Christensen TL. Qualitative research and content validity:

developing best practices based on science and experience. Quality of life research : an

international journal of quality of life aspects of treatment, care and rehabilitation

2009;18(9):1263-78. doi: 10.1007/s11136-009-9540-9 [published Online First:

2009/09/29]

27. Chow CK, Redfern J, Hillis GS, et al. Effect of Lifestyle-Focused Text Messaging on

Risk Factor Modification in Patients With Coronary Heart Disease: A Randomized

Clinical Trial. Jama 2015;314(12):1255-63. doi: 10.1001/jama.2015.10945 [published


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Author Contributions

LN, GF and RG conceived the original concept of the study, and all authors were

involved in the design of the study. All authors contributed to the design of the study,

are involved in the study implementation, critical revision of the drafting and final

approval of the manuscript.

Funding Statement

This work was supported by a Charles Perkins Centre Michael Hintze Incubator Fund, a

Heart Foundation Vanguard Grant (VG 1013632), and a Ramsay Research Training

Fund Grant. The funders have no influence on study design, data collection or the

decision to submit reports for publication. GF is supported by an NHMRC Practitioner

Fellowship.

Competing Interests

The authors have no competing interests to declare.

Acknowledgements

The authors wish to acknowledge Kylee Ingram and Elevator Entertainment for their

contribution to development of the MyHeartMate app.

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Figure 1. MyHeartMate avatar

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Figure 2. Study flow chart

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For peer review onlyDESIGN AND RATIONALE OF THE MYHEARTMATE STUDY: A RANDOMISED CONTROLLED TRIAL OF A GAME-BASED APP

TO PROMOTE BEHAVIOUR CHANGE IN PATIENTS WITH CARDIOVASCULAR DISEASE.

Journal: BMJ Open

Manuscript ID bmjopen-2018-024269.R1

Article Type: Protocol

Date Submitted by the Author: 29-Nov-2018

Complete List of Authors: Gallagher, Robyn; University of Sydney, Sydney Nursing SchoolChow, Clara; University of Sydney, Faculty of Medicine and HealthParker, Helen; University of Sydney, Sydney Nursing School; University of Sydney, Faculty of Health SciencesNeubeck, Lis; Edinburgh Napier University, Health and Social CareCelermajer, David; University of Sydney, Faculty of Medicine and Health; Royal Prince Alfred Hospital, Department of CardiologyRedfern, Julie; University of Sydney, Westmead Clinical SchoolTofler, Geoffrey; University of Sydney, Faculty of Medicine and Health; Royal North Shore Hospital, Department of CardiologyBuckley, Thomas; University of Sydney, Sydney Nursing SchoolSchumacher, Tracy; University of Newcastle, Faculty of Health and MedicineFerry, Cate ; Heart FoundationWhitley, Alexandra; University of Sydney, Charles Perkins CentreChen, Lily; Westmead Hospital, Department of CardiologyFigtree, Gemma; University of Sydney, Faculty of Medicine and Health; Kolling Institute of Medical Research

<b>Primary Subject Heading</b>: Cardiovascular medicine

Secondary Subject Heading: Public health

Keywords: Cardiovascular Disease, Secondary Prevention, Mobile Technology, Gamification, Behaviour Change


BMJ Open on June 12, 2020 by guest. P

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1

DESIGN AND RATIONALE OF THE MYHEARTMATE STUDY: A RANDOMISED CONTROLLED TRIAL OF A GAME-BASED APP TO PROMOTE BEHAVIOUR

CHANGE IN PATIENTS WITH CARDIOVASCULAR DISEASE.

Robyn Gallagher1 2, Clara K Chow3, Helen Parker26, Lis Neubeck1,2,7, David Celermajer 8-10, Julie Redfern3 11, Geoffrey Tofler 8 12, Thomas Buckley 1, Tracy Schumacher 13 14, Cate Ferry15, Alexandra Whitley2, Lily Chen34, Gemma Figtree8 16

1 Susan Wakil School of Nursing and Midwifery, Faculty of Medicine and Health, University of Sydney, NSW, 2006, Australia 2 Charles Perkins Centre, University of Sydney, NSW, 2006, Australia3 Westmead Applied Research Centre, Faculty of Medicine and Health, University of Sydney, NSW, 2006, Australia4 Department of Cardiology, Westmead Hospital, NSW, 2145, Australia5 The George Institute for Global Health, NSW, 2042, Australia6 School of Health Sciences, Faculty of Medicine and Health, University of Sydney, NSW, 2006, Australia 7 School of Health and Social Care, Edinburgh Napier University, Sighthill, EH11 4QD, United Kingdom8 Faculty of Medicine and Health, University of Sydney, NSW, 2006, Australia9 Department of Cardiology, Royal Prince Alfred Hospital, NSW, 2050, Australia10 The Heart Research Institute, NSW, 2042, Australia11 Westmead Clinical School, Faculty of Medicine and Health, University of Sydney, NSW, 2006, Australia12 Department of Cardiology, Royal North Shore Hospital, NSW, 2065, Australia13 Faculty of Health and Medicine, Department of Rural Health, University of Newcastle, NSW, 2308, Australia14 Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, NSW, 2308, Australia15 National Heart Foundation of Australia , NSW, 2011, Australia16 Kolling Institute of Medical Research, NSW, 2065, Australia

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Keywords: cardiovascular disease, secondary prevention, mobile technology, gamification, behaviour change

Corresponding author:

Professor Robyn GallagherRoom 2210, level 2, building D17The University of Sydney, NSW, 2006Email: [email protected]

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Abstract

Introduction

Recurrence of cardiac events is common after a first event, leading to hospitalisations and increased health burden. Patients have difficulties achieving the lifestyle changes required for secondary prevention and access to secondary prevention programs is limited. This study aims to evaluate the impact of a game-based mobile app, MyHeartMate, which is designed to motivate engagement in secondary prevention behaviours for cardiovascular risk factors.


The MyHeartMate study is a randomised controlled trial with 6 months follow up and blinded assessment of the primary outcome. Participants (n = 394) with coronary heart disease will be recruited from hospitals in metropolitan Sydney and randomly allocated to standard care or the MyHeartMate app intervention. The intervention group will receive the app, which uses game techniques to promote engagement and lifestyle behaviour change for secondary prevention. The primary outcome is difference between the groups in physical activity (MET mins/week) at 6 months. Secondary outcomes include change in low-density lipoprotein cholesterol, systolic blood pressure, medication adherence, body mass index, waist circumference, mood and dietary changes at 6 months. Data on app engagement, and patient perspectives of usability and acceptability, will also be analysed.


The study has received ethics approval from Northern Sydney Local Health District Human Research Ethics Committee. The study findings will be disseminated via peer-reviewed publications and presentation at international scientific meetings/conferences.

Clinical trial registration number: ACTRN12617000869370

Trial status: Recruitment commenced

Data sharing statement: Data will not be made available as data sharing is not permitted by our ethics approval.

Word Count: 3670

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Strengths and limitations of this study

The study evaluates a novel game-based mobile app strategy of accessing secondary prevention support for reducing CVD risk factors in patients at high risk of further CVD events.

A stand-alone freely-available mobile app on iOS and Android platforms is being tested on coronary heart disease patients.

This study will be the first to provide rigorous data on effectiveness of a gamification approach through a randomised controlled trial in CHD patients.

This initial study is being conducted in a single city (Sydney, Australia) and in English, which may limit potential generalisability to other countries and languages. Contamination of the control group is possible as participants may choose to use the app. Blinding of the primary outcome is enabled by automatic upload of activity data, however, other assessments are nonblinded.

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Introduction

Globally, coronary heart disease (CHD) is a leading cause of death.1 Recurrent events are common, leading to hospitalisations and an increased burden on the individual and the health system.2 Secondary prevention has a key role in limiting recurrence; however, patients have difficulty achieving the lifestyle changes required, including increasing levels of physical activity, and medication adherence.3 Data from registries indicate that 6 months post myocardial infarction (MI) only 68% of patients are taking all cardioprotective medications prescribed,4 and less than 60% are engaging in sufficient exercise.5 When patients do engage in secondary prevention, with the support of effective programs they can reduce cardiovascular mortality and hospital admission.6 7 Despite these benefits, patients often do not participate in these programs; only one third of MI patients attend cardiac rehabilitation (CR).8 The limited times and location of conventional CR mean that many patients cannot attend due to travel requirements, conflict with work and carer demands, and group-based delivery not being a personal preference.6 8 Therefore, new strategies are needed to enable access to secondary prevention support.

Advances in technology, particularly through the growth of smartphone use, provide an opportunity to overcome barriers to secondary prevention access. The adoption of smartphones has been widespread in developed countries, and adoption by seniors shows the fastest increase.9 A recent study of 285 cardiac patients reported that 70.9% used mobile phones, and 54.6% were using technology for health purposes.10 Furthermore, 68% of cardiac patients were interested in receiving CR support via their mobile phone.11 Mobile technology offers immediate access to information, and the potential to personalise secondary prevention support and incentivise behaviour change. In line with the increased availability and affordability of smartphones, there has been huge expansion in availability of mobile health apps.

Mobile apps show promise for improving CHD risk factor and lifestyle behaviours, although the evidence is still accumulating for CHD-specific apps.12 A recent systematic review identified 10 stand-alone apps for adults that had evidence supporting their use in CHD.13 Benefits were demonstrated for risk factors including blood pressure, body mass index, cholesterol and exercise capacity, as well as reduction in hospitalisation rates.13 The reviewers noted that sustained engagement with the app was crucial for benefits to be achieved, and also reported app features participants preferred. Goal setting, recognition of achievements, challenges, data entry, team-based competition and other game-related design techniques were identified as elements most preferred by app users.

Game-design techniques (gamification) harness innate human desires for competition and social connection and incorporate multiple behaviour change techniques.14 Game techniques include undertaking challenges/quests that are increasingly difficult, and incorporating rewards and the opportunity for comparison with other players at each

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level.15 These game strategies are congruent with social cognitive theory based techniques for the development of self-efficacy.16 Game attributes, both alone and in combination, are evident in many well-established health behaviour change interventions, regardless of whether they have that label.17 18 Despite identifying 64 health behaviour apps in the Apple and Google Play stores in a comprehensive systematic review, the reviewers concluded that few use game techniques.18 Stand-alone game-based mobile apps designed specifically for CHD patients are even rarer.

Game strategies accessed through mobile tablets offer insights. Two games, one for heart failure patients, Heart Health,19 and another for CHD patients and their families, The Heart Game, have pilot studies which report high levels of engagement20 and benefits for self-care behaviours. Interest and enjoyment are critical to the feasibility of game-based apps, and 67% of older cardiac patients are reported to be interested in game-based CR (67%).11 Both studies reported stronger interest in younger patients.19

20 To date there is very limited research testing of game-based apps for CHD patients, therefore, the primary objective of this study is to determine the impact of a game-based app on physical activity. EUROASPIRE IV demonstrated that having little or no physical activity was the most prevalent modifiable risk factor in CHD patients.21 Given the well-established dose-response benefits for mortality by increasing the volume and intensity of habitual physical activity in CHD patients a focus on physical activity outcomes is justified.22 The secondary objective is to determine the impact of the app on CHD risk factors, lifestyle-based risk factor behaviours, and psychological status. An additional objective is to determine level of engagement, acceptability of the app in practice and identification of game strategies participants find useful.


Study Design

The MyHeartMate study is a parallel group, two-arm, superiority randomised controlled trial with 1:1 allocation ratio and six-months follow-up (ACTRN12617000869370). The study will be conducted in three university teaching hospitals in Sydney, Australia serving ethnically, culturally and socioeconomically diverse populations. Participants with CHD will be randomly allocated to either the control group for standard care, or to the intervention group, who will be provided the MyHeartMate app to engage with to receive support for secondary prevention behaviours (Figure 1). Outcomes will be assessed using objective measures at six months in-person at the hospital site. Recruitment to the study began in December 2017 and will be concluded in December 2019.

Randomisation

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Participants will be randomly allocated to either the control group or intervention group (1:1) via a computerised randomisation schedule (www.randomization.com). After enrolment, recruiting research staff will call the study coordinator who will first provide the allocation, and then register the participant. Participants will be asked not to discuss their group allocation or the study app with any other heart patients except with immediate family during the study to avoid contamination. The intervention is self-delivered and the primary outcome data automatically uploaded from the Fitbit tracker to the database. However, staff undertaking all other outcome assessments are not blinded.

Study population

Eligible patients will be those presenting to hospital for management of coronary heart disease (CHD). Patients will be eligible if they have 1) presented with acute coronary syndrome (ACS) and/or have documented CHD on angiography (>50% stenosis in at least one epicardial vessel), 2) own a smartphone and self-report using apps most days of the week, 3) provide informed consent, and 4) have sufficient English proficiency to adequately/successfully interact with the app. Exclusions will apply to candidates who have visual, fine motor or diagnosed neurocognitive disorder which limits engagement with the app. Research staff will approach, screen and recruit patients at each study site. A screening log will be used to identify ineligible patients or those who refuse and include age, gender and reasons for refusal.

Interventions

The control group will receive standard care for CHD, which will include medication prescription and risk factor reduction advice according to their medical provider’s determination and the Heart Foundation, Managing My Heart Health information booklet. Control group participants are requested to not access the app during the study, but may do so at study end. The MyHeartMate group (intervention) will receive standard care, plus access to the MyHeartMate app, a brief (5-minute) in person information provision for participants to upload and log in to the app for the first time and location of the freely-available brief instructional video on the app goals and optimal use of the app functions. The MyHeartMate group will be encouraged to use the app at least twice weekly within the 6-month follow up, but may choose how they do this, including returning to use the app after a period of not using it. Multiple methods are used within the app design to promote participant’s engagement with the app and with secondary prevention behaviours (supplementary file Table 1). The app has a focus on promoting regular physical activity but also encourages participants to take their medications as prescribed and engage with their treating doctors, eat a healthy diet, manage their weight and lipid levels, manage stress and quit smoking if applicable.

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All participants will be provided with the research staff contact details and will be contacted once by these staff by phone during the follow-up period to check contact details and book the follow-up appointment. If the MyHeartMate backend log indicates that a participant has not engaged with the app in the two days following recruitment a single phone call will be made to the participant for troubleshooting. Participants may withdraw at any time by contacting the researchers.

MyHeartMate app intervention development

The MyHeartMate smartphone app is designed to engage CHD patients in secondary prevention behaviours identified in national guidelines.23 The app is built on an award-winning behaviour change platform (Habitat the Game) developed by Elevator Entertainment and has been developed through an iterative process involving experts and patients. The central feature is a heart avatar, which requires the same care as the CHD patient, namely healthy food, exercise, mental health/stress-reduction time, and cardiac-relevant medications. Multiple game strategies are incorporated that are known to harness innate goal-driven, competition and playful human motivations to promote engagement in healthy behaviours (supplementary file Table 1).15 Specifically, feedback and monitoring, comparison of behaviour, reward and threat, associations, self-belief and goals and planning are incorporated as classified in Michie et al (2016) behaviour change taxonomy.17 Improving participant’s self-efficacy for lifestyle change is a key goal so specific techniques derived from social cognitive theory proven to be effective are central and include mastery of graded behaviours such as exercise, understanding responses to behaviours and persuasion.24

The user earns virtual coins to purchase care items for their heart avatar by completing short- and long-term health-related challenges. These are real-world secondary prevention tasks including healthy eating, physical activity, achieving a healthy weight, activities to reduce blood pressure and control blood cholesterol, medication adherence, quitting smoking (where relevant), and engaging in activities to enhance psychological wellbeing. A bank of 100 challenges were developed for this purpose based on national guidelines and then reviewed by an expert multidisciplinary panel, which included leading clinicians (cardiologists, nurses, a physiotherapist, dietitians, exercise scientist) as well as academics and researchers. Coins can also be earned by completing real-world missions, health quizzes, and playing games, which increase in difficulty as the user progresses. Users can compete with others including their friends via the community leader board. Performance can be assessed by entering and tracking their own health data over time through graphs.

The heart avatar appearance and animation was developed in consultation with a purposive sample of older people who had CHD and aims to personalise the effects of health behaviours undertaken.25 (Figure 2) The beta version of the app was tested and evaluated by CR participants (n = 18) who were requested to interact with the app most days over two weeks. Feedback on understanding and usefulness was collected during five focus groups. Changes made based on this feedback included an introduction to

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the app and game purpose, acknowledging the serious nature of CHD and the serious intent of the game (YouTube video tutorials and a Facebook page). Other changes included brief pop-up instructions for each part of the app when it is first used, weekly push notifications to use the game if not being used for 7 days (ceasing at 21 days), open availability on the app store for family and friends, easier tracking and data entry through syncing with a wearable tracker (FitBit Flex TM), easy-to-read graphs on their data, easy log-in and forgotten password tab and visual reminder of scrolling.

The app is stand-alone and completely automated, with the exception of congratulatory emails. These emails are written by research staff using a template when the app automatically generates an email to the staff that a participant has reached a key goal for the first time such as such as “My blood pressure is less than 130/90 for the first time”, or “My weight is in the healthy range for the first time”. These are more tangible rewards for using the app, and are expected to result in improved user perception of the app and increased likelihood of continuing to use the app and continuing to record user achievement of real-world missions in the app.

Study Outcomes

The primary outcome of the study is improvement (difference between intervention and control groups) in physical activity in terms of Metabolic Equivalent of Task (MET) minutes/week (MET-min/week), as measured by the wearable activity tracker FitBit Flex TM.26 Physical activity has been selected given the strong association with survival in CHD patients.27 Automated upload ensures blinding of assessment. Secondary outcomes include improvement (difference between intervention and control groups) in physical activity components, lipid levels, body mass index and waist circumference, blood pressure, dietary intake, psychological state, medication adherence, cardiac events including myocardial infarction, death or any hospital presentation or admission, participation in CR or other secondary prevention strategies, and visits to healthcare providers. Outcomes and measures are provided in detail in supplementary file Table 2.28 29 30 Additional outcomes assessed include engagement with the My Heart Mate app. The combined/ absolute number of modifiable risk factors above/below target thresholds will be calculated. Participants will be assessed during an in-person interview by research staff at 6 months. Additional data collected will be used to characterise the sample, enable subgroup analyses and insight into app uptake. These data include age, gender, marital status, employment, ethnicity, home language, education level and residential suburb.

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Process measures

Level of competence with technology will be assessed at baseline using 2 questions on confidence,10 and the e-Health Literacy Scale (eHEALS) with 8 items.31 Engagement with the app will be assessed using the app log file for number and type of challenges and quizzes undertaken, total coins earned and completion of profile data. Communication by staff for the congratulatory emails will be timed and noted in detailed logs. Assessment of contamination to the control group will be undertaken by scanning the user registry log of the app.

MyHeartMate acceptability and feasibility will be assessed through a questionnaire after the 6 month follow-up assessment. Items will include acceptability of the game format, reminders, identification of game aspects participants liked or disliked, their perceptions of the utility of game aspects for their cardiac health, use of tutorial videos and suggestions for improvement.

Potential facilitators and barriers to the effectiveness of the app will be assessed through four focus groups of a subsample of 20-25 participants of intervention group participants. Recruitment will occur on the basis of ensuring diversity in gender, age and geography. Sampling will occur until theoretical saturation (no new themes emerge), which is expected to occur at 20-25 interviews.32 Focus groups will be facilitated by research staff independent of the recruiting and outcomes assessment staff. Focus groups will address individual app use, likes and dislikes, the effectiveness of different game aspects for behaviour change, including monitoring and tracking and participation in the community leaderboard, the appropriateness of the visual elements, the ease and understanding of the app features, language and content, and any discussion or sharing of the app with others. All interviews will be audio-recorded and transcribed, and entered into NVIVO 7 for analyses. An iterative process of reading, identifying themes and checking will be used for analyses.32

Patient and Public Involvement

Cardiac patients’ preferences in relation to using mobile apps and activity trackers10

were assessed and directly informed app development and design. Volunteers (past patients) who support cardiac rehabilitation in Northern Sydney Local Health District also provided feedback on the app interface and avatar appearance. Patients were not involved in designing the study. Study participants will receive a summary of the study results by email at the study conclusion.

Statistical considerations

Study data will be analysed using intention-to-treat principles. The primary analysis will use analysis of covariance (ANCOVA) with baseline values of the study outcome measures used as covariates where appropriate for continuous variables. This method will be used for the primary outcome of MET-min/week and for secondary outcomes of

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mean daily step count and minutes of moderate-vigorous exercise, lipid levels, BMI, waist, blood pressure, anxiety and depression at 6-months. Categorical variables (smoking, achieving risk factors at guideline level) will be compared using Chi-squared tests for categorical variables. Additionally, relative risks, with 95% confidence intervals will be calculated to compare groups using log-binomial regression.

Sample size has been calculated based on detecting a difference of 345 (SD 114) MET-min/wk between the control and intervention groups based on the TEXT ME secondary prevention study in a similar population.29 Assuming r=0.5 correlation between baseline and final outcome measurement with alpha=0.05 and power (1-Beta)=0.95, the required sample size is 164 patients per group, assuming a 1:1 allocation ratio for control and intervention groups. The total sample size, of 328 with an additional allowance of 20% loss to follow-up, is 394 patients.


The study will be administered by the University of Sydney. A research management committee including experts in large-scale trials, CHD treatment, qualitative analyses and translation into practice, will be overseeing the design and conduct of the research. The study has received Human Research Ethics approval from Northern Sydney Local Health District and governance approval from all recruitment sites. The study is guided by, and adheres to, the National Health and Medical Research Council of Australia ethical guidelines for human research. All participants will have provided written and informed consent, verified by a witness. No reimbursement is provided to study participants. The study findings will be disseminated via publication of peer-reviewed manuscripts, and presentations at international conferences, as well as through media publications. It is anticipated that the findings will help to inform future developments in the delivery of secondary prevention of CHD.

Strengths and limitations

A strength of the study is that recruitment is from ethnically, culturally and socioeconomically diverse sites, however, external generalisability is limited by the English language requirements and single city context. An additional strength is the use of multiple objectively assessed outcomes, including physical activity, however, several outcomes are self-report, which has inherent risk of bias, for example from poor recall and social desirability, and this data is collected by nonblinded staff. Contamination of the control group is possible as participants may choose to use the app.

Conclusions

This study will evaluate a novel strategy of accessing secondary prevention support for reducing CHD risk factors in patients at high risk of further CHD events. No published

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study has evaluated a game-based mobile app designed specifically for CHD patients in a randomised controlled trial; therefore, this study will be the first to provide rigorous data on effectiveness of this approach in CHD patients.

Smartphone technology has the potential to address many of the obstacles CHD patients face in accessing secondary prevention programs. However, strategies are not clearly articulated in study methods or engagement with individual components is poorly quantified. The study will address these deficits and explore relationships between strategies and outcomes. Furthermore, the app may be used in conjunction with evidence-based programs such as CR to provide additional support for behaviour change and scaled-up for large numbers of CHD patients.

The MyHeartMate study will test the efficacy of a game-based smartphone app to improve CHD risk factors and lifestyle behaviours in patients who have CHD. The MyHeartMate app provides a potential platform for smartphone apps for secondary prevention in patients with other chronic diseases, and, as an openly available app, the potential for standalone access to large numbers of people affected by CHD and their families.

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References

1. World Health Organisation. WHO fact sheet no. 317: World Health Organisation,; 2011 [Available from: http://www.who.int/en/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds) Accessed 2018 March 15

2. Atkins ER, Geelhoed EA, Knuiman M, et al. One third of hospital costs for atherothrombotic disease are attributable to readmissions: a linked data analysis. BMC Health Services Research 2014;14:338.

3. Shore S, Jones PG, Maddox TM, et al. Longitudinal persistence with secondary prevention therapies relative to patient risk after myocardial infarction. Heart 2015;101(10):800-7.

4. Brieger DB, Chow C, Gullick J, et al. Improving patient adherence to secondary prevention medications 6 months after an acute coronary syndrome: observational cohort study. Intern Med J 2018;48(5):541-9.

5. Urbinati S, Olivari Z, Gonzini L, et al. Secondary prevention after acute myocardial infarction: drug adherence, treatment goals, and predictors of health lifestyle habits. The BLITZ-4 Registry. Eur J Prev Card 2015;22(12):1548-56.

6. Clark AM, Hartling L, Vandermeer B, et al. Meta-analysis: secondary prevention programs for patients with coronary artery disease. Ann Intern Med 2005;143(9):659-72.

7. Anderson L, Thompson DR, Oldridge N, et al. Exercise-based cardiac rehabilitation for coronary heart disease. Cochrane Database Syst Rev 2016 Jan 5;(1):Cd001800.

8. Peters AE, Keeley EC. Trends and predictors of participation in cardiac rehabilitation following acute myocardial infarction: Data from the Behavioral Risk Factor Surveillance System. J Am Heart Assoc 2017;7(1). pii e007664.

9. Deloitte. Australian media and digital preferences - 4th edition Deloitte; 2015 [Available from: https://www2.deloitte.com/content/dam/Deloitte/

au/Documents/technology-media-telecommunications/deloitte-au-tmt-media-consumer-survey-2015-100815.pdf accessed 8 October 2017.

10. Gallagher R, Roach K, Sadler L, et al. Mobile technology use across age groups in patients eligible for cardiac rehabilitation: survey study. JMIR mHealth and uHealth 2017;5(10):e161.

11. Buys R, Claes J, Walsh D, et al. Cardiac patients show high interest in technology enabled cardiovascular rehabilitation. BMC Med Inform Decis Mak 2016;16:95.

12. Neubeck L, Lowres N, Benjamin EJ, et al. The mobile revolution--using smartphone apps to prevent cardiovascular disease. Nat Rev Cardiol 2015;12(6):350-60.

13. Coorey GM, Neubeck L, Mulley J, et al. Effectiveness, acceptability and usefulness of mobile applications for cardiovascular disease self-management: Systematic review

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http://www.who.int/en/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds

http://www.who.int/en/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds

https://www2.deloitte.com/content/dam/Deloitte/



14

with meta-synthesis of quantitative and qualitative data. Eur J Prev Card 2018;25(5):505-21.

14. King D, Greaves F, Exeter C, et al. 'Gamification': influencing health behaviours with games. J Royal Soc Med 2013;106(3):76-8.

15. Cugelman B. Gamification: what it is and why it matters to digital health behavior change developers. JMIR Serious Games 2013;1(1):e3.

16. Bandura A. Social Foundations of Thought and Action. A Social Cognitive Theory. 1986 Prentice Hall Upper Saddle River, New Jersey

17. Michie S, Richardson M, Johnston M, et al. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med 2013;46(1):81-95.

18. Edwards EA, Lumsden J, Rivas C, et al. Gamification for health promotion: systematic review of behaviour change techniques in smartphone apps. BMJ Open 2016;6(10):e012447.

19. Radhakrishnan K, Toprac P, O'Hair M, et al. Interactive Digital e-Health Game for Heart Failure Self-Management: A Feasibility Study. Games For Health J 2016;5(6):366-74.

20. Dithmer M, Rasmussen JO, Gronvall E, et al. "The Heart Game": Using Gamification as Part of a Telerehabilitation Program for Heart Patients. Games For Health J 2016;5(1):27-33.

21. Kotseva K, Wood D, De Bacquer D, et al., EUROASPIRE Investigators. EUROASPIRE IV: A European Society of Cardiology survey on the lifestyle, risk factor and therapeutic management of coronary patients from 24 European countries. Eur J Prev Cardiol. 2016 Apr;23(6):636-48.

22. Stewart RAH, Held C, Hadziosmanovic N et al., STABILITY Investigators. Physical Activity and Mortality in Patients with Stable Coronary Heart Disease. J Am Coll Cardiol. 2017;70(14):1689-1700.

23. National Heart Foundation of Australia, Cardiac Society of Australia and New Zealand. Reducing risk in heart disease: an expert guide to clinical practice for secondary prevention of coronary heart disease. Melbourne: National Heart Foundation of Australia, 2012.

24. Olander EK, Fletcher H, Williams S, et al., What are the most effective techniques in changing obese individuals' physical activity self-efficacy and behaviour: a systematic review and meta-analysis. Int J Behav Nutr Phys Act. 2013;Mar 3;10:29.

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https://www.ncbi.nlm.nih.gov/pubmed/?term=Olander%20EK%5BAuthor%5D&cauthor=true&cauthor_uid=23452345

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15

25. Morie J, Haynes E, Chance E, Purohit D. Virtual Worlds and Avatars as the New Frontier of Telehealth Care. In Wiederhold BK, Riva G (Eds) Annual Review of Cybertherapy and Telemedicine 2012 pp 27-3226. Alharbi M, Bauman A, Neubeck L, et al. Validation of Fitbit-Flex as a measure of free-living physical activity in a community-based phase III cardiac rehabilitation population. Eur J Prev Cardiol 2016;23(14):1476-85.

27. Loprinzi PD, Addoh O. The effects of free-living physical activity on mortality after coronary artery disease diagnosis. Clin Card 2016;39(3):165-9.

28. World Health Organisation. Global Physical Activity Questionnaire (GPAQ) Analysis Guide Geneva: World Health Organisation; 2013 [Available from: www.who.int/ncds/surveillance/steps/resources/GPAQ_Analysis_Guide.pdf

29. Chow CK, Redfern J, Hillis GS, et al. Effect of Lifestyle-Focused Text Messaging on Risk Factor Modification in Patients With Coronary Heart Disease: A Randomized Clinical Trial. JAMA 2015;314(12):1255-63.

30. Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatrica Scandinavica 1983;67(6):361-70.

31. Norman CD, Skinner HA. eHEALS: The eHealth Literacy Scale. JMIR 2006;8(4):e27.

32. Brod M, Tesler LE, Christensen TL. Qualitative research and content validity: developing best practices based on science and experience. Quality Of Life Res 2009;18(9):1263-78.

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Author Contributions

LN, GF and RG conceived the original concept of the study. RG, GF, CC, HP, LN, DC, JR, GT, TB, TS, CF, AW and LC contributed to the design of the study, and are involved in the study implementation. RG, GF, CC, HP, JR, GT, TB, TS and CF wrote the content for the MyHeartMate app. RG prepared the first draft of the manuscript. RG, CC, HP, LN, DC, JR, GT, TB, TS, CF, AW, LC and GF were involved in the critical revision of the manuscript for important intellectual content, and final approval of the manuscript.

Funding Statement

This work was supported by a Charles Perkins Centre Michael Hintze Incubator Fund, a Heart Foundation Vanguard Grant (VG 1013632), and a Ramsay Research Training Fund Grant. The funders have no influence on study design, data collection or the decision to submit reports for publication. GF is supported by an NHMRC Practitioner Fellowship.

Competing Interests

The authors have no competing interests to declare.

Acknowledgements

The authors wish to acknowledge Kylee Ingram and Elevator Entertainment for their contribution to development of the MyHeartMate app. The authors also wish to acknowledge the invaluable assistance of volunteers working in cardiac rehabilitation services of Northern Sydney Local Health District.

Figure 1 Study Design and participant flow through study

Figure 2 MyHeartMate avatar

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Figure 1 Participant Flow Chart

234x212mm (300 x 300 DPI)

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Figure 2 MyHeartMate

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Table 1. MyHeartMate game strategies

Game strategy Examples

Reward systems

Encourage engagement through earning coins for completing health-related challenges, monitoring health data, correctly answering quizzes and receiving congratulatory emails personalised through participant’s name and specific achievement.

I discussed quitting smoking with my doctor today – 20 coins Entry of exercise, weight, blood pressure and cholesterol – 20 coins Correctly answer a multiple choice question on high cholesterol treatment – 10 coins

Undertake challenges

Encourage participation in immediate and ongoing behaviours through selection and performance of health-related challenges (smoking, disease management and medications, activity, healthy eating and weight and wellbeing) of increasing difficulty

I talked to my doctor about getting active today I tracked my activity with a pedometer every day this week I exercised for 30 minutes today I exercised for 30 minutes on 5 days this week

Monitor and track performance

Encourage awareness and goal attainment through regular entry of health data (blood pressure, weight, exercise, medication taking, cholesterol) then displayed on graphs

Activity data are synced with a wearable tracker and updated in real-time and displayed in a graph

Games and quizzes

Promote engagement and enjoyment through fun and challenging games

Moving a red blood cell through junk food hazards

Avatar personalises effects of health behaviour

A virtual heart which flourishes when provided healthy food, exercise, relaxation and medications purchased through earned coins

Coins earned on activity are used to purchase a bike ride for the avatar which improves in appearance and activity level

Social connection and competition

Engagement and participation in health challenges and app features through a community leader board

Users select a name and their coin tally is ranked against the entire community and their friends

Notifications

Engagement is encouraged through a notification when participation has dropped

No activity for 7 days generates an automated notification to participants to remember to engage, to a maximum of three notifications.

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Table 2. Primary and secondary outcomes measured at baseline and six months

Outcome Measure

Primary

Physical activity – MET-min/week Fitbit Flex TM activity tracker worn on the non-dominant wrist for four consecutive days (three weekdays plus one weekend day)25

Secondary

Physical activity – average steps/day, minutes of moderate and vigorous physical activity/day

Fitbit Flex TM as above and Global Physical Activity Questionnaire (GPAQ)(16-item questionnaire measuring activity at work, travel and leisure)28

Lipid levels – total cholesterol, low-density lipoprotein cholesterol (LDL-C), triglycerides

Venous blood sample taken from the antecubital fossa with participants fasting for 6 hours prior. Analyses are conducted at the study hospital sites using standard laboratory techniques by staff blinded to study outcomes and participant group, reported in mg/dL.

Systolic blood pressure (BP) Mean of three seated digital recordings

Body mass index (BMI) (kg/m2) and waist circumference

Mean of three using digital scale and flexible metal tape

Dietary intake – average daily fruit and vegetable portion intake

Self-report 29

Smoking status Self-report 29

Psychological state – anxiety and depression symptoms

Hospital Anxiety and Depression Scale (HADS)30 (14-item questionnaire, depression and anxiety scores categorised as normal (0-7), mild or more (8-21)

Medication adherence – ACE inhibitor/ARB, Aspirin, β-blocker, statin

Self-report, yes/no

Combined CHD risk Calculation of absolute number of modifiable risk factors above/below target thresholds

Cardiac events - myocardial infarction, death or any hospital presentation or admission

Self-report and medical record audit

Participation in secondary prevention programs such as cardiac rehabilitation

Self-report

Visits to healthcare providers Self-report

Combined number of modifiable risk factors above/below target level for physical activity, LDL-C, BP, smoking, BMI

Targets defined as achieving moderate-vigorous exercise ≥ 30 min/day 5 days/week (Fitbit), LDL-C <77 mg/dL, BP < 140/90 mm Hg, not smoking, BMI < 25 kg/m2

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m CONSORT 2010 checklist of information to include when reporting a randomised trial*

ShUon/Topic

Title and abstract

Introduction

Background and

objectives

Methods

Trial design

Participants

Interventions

Outcomes

Sample size

Randomisation:

Sequence

generation

Allocation

concealment

mechanism

Implementation

Blinding

CONSORT 2010 checklist

Item

No Checklist item

1 a Identification as a randomised trial in the title

1 b Structured summary of trial design, methods, results, and conclusions (for specific guidance see CONSORT for abstracts)

2a Scientific background and explanation of rationale

2b Specific objectives or hypotheses

3a Description of trial design (such as parallel, factorial) including allocation ratio

3b Important changes to methods after trial commencement (such as eligibility criteria), with reasons

4a Eligibility criteria for participants

4b Settings and locations where the data were collected

5 The interventions for each group with sufficient details to allow replication, including how and when they were

actually administered

6a Completely defined pre-specified primary and secondary outcome measures, including how and when they

were assessed

6b Any changes to trial outcomes after the trial commenced, with reasons

7a How sample size was determined

7b When applicable, explanation of any interim analyses and stopping guidelines

8a Method used to generate the random allocation sequence

8b Type of randomisation; details of any restriction (such as blocking and block size)

9 Mechanism used to implement the random allocation sequence (such as sequentially numbered containers),

describing any steps taken to conceal the sequence until interventions were assigned

10 Who generated the random allocation sequence, who enrolled participants, and who assigned participants to

interventions

11 a If done, who was blinded after assignment to interventions (for example, participants, care providers, those

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11 b Statistical methods 12a

12b

Results

Participant flow (a 13a diagram is strongly recommended) 13b Recruitment 14a

14b Baseline data 15 Numbers analysed 16

Outcomes and 17a estimation

17b Ancillary analyses 18

Harms 19

Discussion

Limitations 20 Generalisability 21 Interpretation 22

Other information

Registration 23 Protocol 24 Funding_ 25

assessing outcomes) and how If relevant, description of the similarity of interventions Statistical methods used to compare groups for primary and secondary outcomes Methods for additional analyses, such as subgroup analyses and adjusted analyses

For each group, the numbers of participants who were randomly assigned, received intended treatment, and were analysed for the primary outcome For each group, losses and exclusions after randomisation, together with reasons Dates defining the periods of recruitment and follow-up Why the trial ended or was stopped A table showing baseline demographic and clinical characteristics for each group For each group, number of participants (denominator) included in each analysis and whether the analysis was by original assigned groups For each primary and secondary outcome, results for each group, and the estimated effect size and its precision (such as 95% confidence interval) For binary outcomes, presentation of both absolute and relative effect sizes is recommended Results of any other analyses performed, including subgroup analyses and adjusted analyses, distinguishing pre-specified from exploratory All important harms or unintended effects in each group (for specific guidance see CONSORT for harms)

Trial limitations, addressing sources of potential bias, imprecision, and, if relevant, multiplicity of analyses Generalisability (external validity, applicability) of the trial findings Interpretation consistent with results, balancing benefits and harms, and considering other relevant evidence

Registration number and name of trial registry Where the full trial protocol can be accessed, if available Sources of funding and other support (such as supply of drugs), role of funders

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*We strongly recommend reading this statement in conjunction with the CONSORT 2010 Explanation and Elaboration for important clarifications on all the items. If relevant, we also

recommend reading CONSORT extensions for cluster randomised trials, non-inferiority and equivalence trials, non-pharmacological treatments, herbal interventions, and pragmatic trials.

Additional extensions are forthcoming: for those and for up to date references relevant to this checklist, see www.consort-statement.org.

CONSORT 2010 checklist Page2

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