European Journal of Preventive Cardiology http://cpr.sagepub.com/
A mobile phone intervention increases physical activity in people with cardiovascular disease: Results from the HEART randomized controlled trial Ralph Maddison, Leila Pfaeffli, Robyn Whittaker, Ralph Stewart, Andrew Kerr, Yannan Jiang, Geoffrey Kira, William Leung, Lance Dalleck, Karen Carter and Jonathan Rawstorn European Journal of Preventive Cardiology published online 9 May 2014 DOI: 10.1177/2047487314535076 The online version of this article can be found at: http://cpr.sagepub.com/content/early/2014/05/07/2047487314535076
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European Association for Cardiovascular Prevention and Rehabilitation
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EURO PEAN SO CIETY O F CARDIOLOGY ®
Original scientific paper
A mobile phone intervention increases physical activity in people with cardiovascular disease: Results from the HEART randomized controlled trial
European Journal of Preventive Cardiology 0(00) 1–9 ! The European Society of Cardiology 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/2047487314535076 ejpc.sagepub.com
Ralph Maddison1, Leila Pfaeffli1, Robyn Whittaker1, Ralph Stewart2, Andrew Kerr3, Yannan Jiang1, Geoffrey Kira4, William Leung5, Lance Dalleck6, Karen Carter1 and Jonathan Rawstorn1
Abstract Aim: To determine the effectiveness and cost-effectiveness of a mobile phone intervention to improve exercise capacity and physical activity behaviour in people with ischaemic heart disease (IHD). Methods and results: In this single-blind, parallel, two-arm, randomized controlled trial adults (n ¼ 171) with IHD were randomized to receive a mobile phone delivered intervention (HEART; n ¼ 85) plus usual care, or usual care alone (n ¼ 86). Adult participants aged 18 years or more, with a diagnosis of IHD, were clinically stable as outpatients, able to perform exercise, able to understand and write English, and had access to the Internet. The HEART (Heart Exercise And Remote Technologies) intervention involved a personalized, automated package of text messages and a secure website with video messages aimed at increasing exercise behaviour, delivered over 24 weeks. All participants were able to access usual community-based cardiac rehabilitation, which involves encouragement of physical activity and an offer to join a local cardiac support club. All outcomes were assessed at baseline and 24 weeks and included peak oxygen uptake (PVO2; primary outcome), selfreported physical activity, health-related quality of life, self-efficacy and motivation (secondary outcomes). Results showed no differences in PVO2 between the two groups (difference 0.21 ml kg1 min1, 95% CI: 1.1, 0.7; p ¼ 0.65) at 24 weeks. However significant treatment effects were observed for selected secondary outcomes, including leisure time physical activity (difference 110.2 min/week, 95% CI: 0.8, 221.3; p ¼ 0.05) and walking (difference 151.4 min/week, 95% CI: 27.6, 275.2; p ¼ 0.02). There were also significant improvements in self-efficacy to be active (difference 6.2%, 95% CI: 0.2, 12.2; p ¼ 0.04) and the general health domain of the SF36 (difference 2.1, 95% CI: 0.1, 4.1; p ¼ 0.03) at 24 weeks. The HEART programme was considered likely to be cost-effective for leisure time activity and walking. Conclusions: A mobile phone intervention was not effective at increasing exercise capacity over and above usual care. The intervention was effective and probably cost-effective for increasing physical activity and may have the potential to augment existing cardiac rehabilitation services.
Keywords Exercise, mobile phones, text messaging, rehabilitation, self-efficacy, trials Received 19 November 2013; accepted 16 April 2014 1
National Institute for Health Innovation, University of Auckland, Auckland, New Zealand 2 Department of Cardiology, Auckland City Hospital, Auckland, New Zealand 3 Department of Epidemiology and Biostatistics, University of Auckland, Auckland, New Zealand 4 School of Sport and Exercise, Massey University, Auckland, New Zealand
5 Department of Medicine, University of Auckland, Auckland, New Zealand 6 Department of Sport and Exercise Science, University of Auckland, Auckland, New Zealand
Corresponding author: Ralph Maddison, National Institute for Health Innovation, University of Auckland, Private Bag 92019, Victoria Street West, Auckland 1142, New Zealand. Email: [email protected]
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Introduction
Aim
Cardiac rehabilitation (CR), a programme of medication and risk factor education as well as psychological support is an essential part of the contemporary management of people with ischaemic heart disease (IHD).1 International guidelines consistently identify exercise therapy as a central element of CR1–4 and exercise-based CR programmes have been shown to be cost-effective for those who participate.5,6 A Cochrane systematic review7 of exercise-based CR reported that all-cause mortality was reduced by 26% (RR 0.74, 95% CI 0.63, 0.87). Despite the documented benefits of CR, participation is inadequate in all countries in which it has been measured.8 Adherence with supervised exercise CR is low with between 10% and 36% of individuals dropping out of supervised CR exercise programmes.8,9 It is evident that current centre-based CR practices do not suit all patients and alternative approaches are needed.10 Common reasons people give for not accepting the invitation to attend centre-based CR classes, which include supervised exercise, are distance to CR, problems with access and parking, lack of time11 and work or domestic commitments.12–14 Telephone-based interventions can be effective for physical activity behaviour change;15 however because of high penetration and relatively low costs,16 mobile phones have the potential to increase the reach of disease self-management or lifestyle coaching interventions for the secondary prevention of IHD.17,18 The benefits of mobile phone programmes are that they can be delivered anywhere at any time and for extended periods, facilitating regular communication and behavioural maintenance; they can be designed to send messages in a time-sensitive manner that fits with the individual’s lifestyle; they are proactive and do not require prompting by the user before support is offered; they can be personalized and tailored to suit specific demographic and health needs; they increase access (e.g. less travel); allow cheaper provision of services than face-to-face contacts; and they provide a way of reducing inequalities due to their widespread adoption by all cultural and socioeconomic groups.19,20 A systematic review supports the delivery of mobile phone text messaging interventions21 for achieving behaviour change. Of the 14 studies reviewed, 13 resulted in positive behaviour change outcomes for smoking cessation and diabetes management. However, to date a mobile phone delivered text message intervention to enhance exercise behaviour has not been examined in a CVD population. A randomized controlled trial was required to determine the effectiveness, safety and acceptability of such an approach.
The aim of this trial was to determine the effectiveness and cost-effectiveness of a mobile health (mHealth) delivered exercise CR programme for people with IHD to improve exercise capacity and physical activity levels compared to current services. We hypothesized that an mHealth intervention would increase exercise capacity. Secondary hypotheses were that the mHealth intervention would increase physical activity levels and would be associated with increased self-efficacy to be active.
Design The HEART (Heart Exercise and Remote Technologies) study was a parallel, two-arm, randomized controlled trial of exercise prescription and behavioural support by mobile phone text messages and Internet. The trial was undertaken in New Zealand between 2010 and 2012 (protocol published in 2011)22 and no changes were made to the study design in this time. Participants were adults aged 18 years or more, with a diagnosis of IHD, defined as angina, myocardial infarction, revascularization, including angioplasty, stent or coronary artery bypass graft within the previous 3–24 months. All participants were clinically stable as outpatients, able to perform exercise, able to understand and write English, and had access to the Internet (e.g. at home, work, library or through friends or relatives). Eligible participants were randomized to either receive an exercise intervention delivered via mobile phone, or to usual care, with encouragement to be physically active and attend a cardiac club. Participants were excluded if they had been admitted to hospital with heart disease within the previous 6 weeks; had terminal cancer, or had significant exercise limitations other than IHD. Study procedures and terms were approved by the New Zealand Multi-region Ethics Committee (NTX/10/10/099). Eligible participants were recruited from two metropolitan hospitals, and were identified by nurses as inpatients, through outpatient clinics and existing databases. Nurses contacted potential participants and those agreeing to participate were screened for eligibility.
Procedures All participants were free to participate in any other CR service or support that they wished to use. In Auckland, New Zealand, this typically involves participating in community-based CR education sessions on modifying CVD risk factors and psychological support, as well as encouragement to be physically active and an
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offer to join a local cardiac club that provides supervised exercise. In addition, participants in the intervention group received the HEART programme—a personalized, automated package of text messages via their mobile phones aimed at increasing exercise behaviour over 24 weeks. They received six messages per week for the first 12 weeks, five messages per week for 6 weeks and then four messages per week for the remaining 6 weeks (total 24 weeks).
Intervention The primary goal of the HEART programme was to have all individuals participate in moderate to vigorous aerobic-based exercise for a minimum of 30 minutes (preferably more) most days (at least 5) of the week, in line with current recommendations.23 The homebased programme consisted of (1) regular exercise prescription, (2) provision of behaviour change strategies and (3) technical support. The intervention focused on increasing leisure time physical activity – walking in particular – as well as encouragement to accrue incidental activity through daily tasks such as household chores and active transport. The intervention also focused on altering the key mediators of behaviour change, including self-efficacy, social support and motivation. Self-efficacy refers to an individual’s beliefs in his or her capabilities to execute necessary courses of action to satisfy situational demands.24 Self-efficacy is theorized to influence the activities that individuals choose to approach, the effort expended on such activities and the degree of persistence demonstrated in the face of adverse stimuli.24 Within the cardiac setting, self-efficacy has been the most examined psychological variable and has consistently been shown to be related to exercise behaviour,25 and treadmill test performance.26,27 Additional information was provided via a secure website that participants could log on to. This included role model video vignettes, an opportunity to self-monitor progress, as well as information on various forms of physical activity and exercise, energy expenditure, healthy eating advice, and links to other websites (e.g. local exercise programmes and cardiac clubs). Participants received 3–5 text messages per week (total of 118 messages over 24 weeks). Participants were encouraged to log onto the website once per week to view new information and video messages (three new messages added per week, 30–60 s in length). In total it was estimated that using the intervention to its full extent (maximum dose ¼ reading all text messages and using the website) took participants an average of 10 minutes per week. The intervention followed the mHealth development and evaluation framework28 and was pre-tested and
refined prior to conducting the trial.29 Full details of the intervention are described in the protocol.22
Outcomes The primary outcome of the trial was change in peak oxygen uptake (PVO2) from baseline to 24 weeks, which was determined using respiratory gas analysis during a standardized treadmill exercise testing protocol. A Moxus (AEI Technologies Inc., Pittsburgh, USA) metabolic cart was used to obtain breathby-breath measurements of VO2 and carbon dioxide production (VCO2). All testing was conducted in accordance with the ACSM guidelines30 by a trained exercise physiologist blinded to treatment allocation. A graded protocol was initiated at a comfortable walking speed, and the gradient was increased by two degrees every 60 s until volitional exhaustion. Care was taken to ensure that participants exceeded the anaerobic threshold or a respiratory exchange ratio (RER) greater than 1.15 to indicate adequate effort. Secondary outcomes included self-reported physical activity, self-efficacy and motivation to exercise, and health-related quality of life at 24 weeks. An economic evaluation was also conducted. Self-reported physical activity levels were assessed using the International Physical Activity Questionnaire long form (IPAQLF).31 Self-efficacy (task and barrier) were assessed using validated measures and a scale of 0 ‘‘no confidence’’ to 100% ‘‘complete confidence’’.32 For example, ‘‘how confident are you that you can complete 30 minutes of physical activity at a moderate effort on most days of next week?’’ For task efficacy, scores were summed with greater values indicating greater efficacy to exercise for longer periods of time and at a greater level of intensity. For barrier efficacy, participants rated their confidence to overcome seven common reasons (e.g. bad weather, lack of time, pain or discomfort) preventing people from participating in exercise sessions. Efficacy strength was calculated by summing the scores and dividing by total number of items used. Health-related quality of life was assessed using the standard version of the Short Form SF36 version 233 and EQ-5D.34 All questionnaires were administered during the clinic visits by trained research assistants, who also observed participant’s completion.
Economic evaluation For the cost-effectiveness analyses, we collected information on the costs of implementing and delivering the intervention only. Healthcare utilization and wider societal costs were not collected as this was a post hoc economic evaluation. Staff costs included a 50% overhead rate, and Web hosting fees, although not
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charged, were included for the purposes of this evaluation. Reported costs are in 2012 $NZ exclusive of Goods and Services Tax. In 2012, the purchasing power parity of NZ$1 ¼ E0.53. The EQ-5D (NZ tariff 2) was used to obtain a single preference index for the estimation of quality-adjusted life years (QALYs). Incremental cost-effectiveness ratios (ICERs) per QALY and for outcomes with a significant treatment effect were calculated. The ICER summarizes the additional cost per unit of health benefit gained by switching from usual care to the HEART intervention. To evaluate uncertainty in the ICER, cost-effectiveness acceptability curves were calculated from non-parametric bootstrapping with 10,000 replications. In scenario analysis, the intervention was evaluated as an ongoing nationwide programme rather than as a trial. Set-up costs were amortized at 3.5% over 4 years (the minimum estimated lifetime of the technological investment) over the potential national participant pool. As all contacts are automated and staff attention was rarely required, the trial’s monthly staff maintenance and web-hosting costs are scalable nationally. However, to provide a conservative estimate, the monthly maintenance costs were doubled and split over potential participants for the 6-month intervention period.
Randomization and blinding On completion of the baseline assessment, eligible participants were randomly allocated at a 1:1 ratio to either intervention or control group by means of a central computerized service. Randomization was conducted using the minimization method, stratifying by sex (male and female), ethnicity (Maori – indigenous – and non-Maori), and exercise history (attendance or not at least one CR session). Allocation concealment was maintained up to the point of randomization. This was a single-blind trial, where outcome assessors were blinded to treatment allocation. However, it was not possible to blind trial participants to their allocation.
Statistical analyses Based on previous research,35 an a priori sample size estimate indicated that 170 participants (85 per group) would provide 90% power at 5% level of significance (two-sided) to detect a treatment difference of at least 2.5 ml1 kg min1 between the two groups, on change in PVO2 from baseline to 24 weeks assuming a standard deviation of 5 ml1 kg min1. A formal statistical analysis plan (SAP) was approved by the Trial Steering Committee before datalock. Statistical analyses were performed using SAS
version 9.3 (SAS Institute Inc. Cary NC) and R version 2.15 (R Foundations for Statistical Computing). All statistical tests were two-tailed and a 5% significance level maintained throughout the analyses. Treatment evaluations were performed on the principle of intention to treat (ITT), using data collected from all randomized participants. Multiple imputations method was applied to the missing data for the primary outcome only. Analysis of covariance (ANCOVA) regression model was used to evaluate the main treatment effect on the primary outcome between the two treatment groups, adjusting for its baseline measure, age, sex, ethnicity and exercise history (i.e. stratification factors). A similar approach was used for other continuous secondary outcome measures.
Results A total of 171 eligible participants were randomized to the trial (Figure 1). Eligible participants were recruited from May 2011 to October 2012 via two Auckland (population 1.4 million) hospitals. Participants attended clinic visits at the time of randomization (baseline) and six months later. The majority of participants were male (139/171, 81%), New Zealand European (131/171, 76%), with a mean age of 60 years (SD ¼ 9.3). Treatment groups were well balanced at baseline (Table 1 and 2). During the trial 82% of participants in the intervention read some or all of the HEART text messages and 57% of participants viewed some or all of the video messages on the website. On average participants viewed the website once every two weeks. The primary outcome was measured for 75 (88%) participants in the intervention group and 78 (90%) in the control group at 24 weeks (Figure 1). Four participants in each of the respective groups were unable to complete the PVO2 assessments for medical reasons. As shown in Table 3, both groups showed a small increase in PVO2 from baseline to 24 weeks; however there were no differences between the HEART intervention and control groups (difference 0.2 ml1 kg min1, 95% CI: 1.1, 0.7; p ¼ 0.65) at 24 weeks. There was a significant increase in self-reported leisure time physical activity (difference 110.2 min/week, 95% CI: 0.8, 221.3; p ¼ 0.05) and walking (difference 151.4 min/ week, 95% CI: 27.6, 275.2; p ¼ 0.02) at 24 weeks in favour of the HEART intervention, which represented increases of 40% and 42%, respectively. For the other activity domains (total activity, active transport and domestic/gardening, and reduced sitting time), there were no statistically significant differences. There were also significant improvements in selfefficacy to be active (difference 6.2%, 95% CI: 0.2, 12.2; p ¼ 0.04) and the general health domain of the
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Screening registration (N=288) Excluded from study (n=108) -Declined to proceed (n=60) -Could not contact (n=17) -Not eligible to participate (n=31)
Study registration (N=180) Excluded from study (n=9) -Attended clinic but were medically unstable to complete VO2 test (n=9)
Randomization (N=171)
Intervention (N=85)
Baseline (N=85)
Lost to follow up (n=10) -Could not contact (n=5) -Unable to complete assessment for medical reason (n=4) -Did not wish to return (n=1)
24 weeks (N=75)
Control (N=86)
Baseline (N=86)
24 weeks (N=78)
Lost to follow up (n=8) -Could not contact (n=3) -Unable to complete assessment for medical reason (n=4) -Did not wish to return (n=1)
Figure 1. Flow of participants in study.
SF36 (difference 2.1, 95% CI: 0.1, 4.1; p ¼ 0.03) at 24 weeks (Table 4). No statistically significant differences were observed in other outcomes between the two groups. Twenty-two participants reported 31 serious adverse events. Of these, 15 were cardiac related (angina/chest pain ¼ 4; stenosis ¼ 2; heart palpitations ¼ 1; shortness of breath ¼ 2; dizziness ¼ 1; pericarditis ¼ 3; ventricular tachycardia ¼ 2). The remaining serious adverse events included cancer diagnosis (n ¼ 3); injury (n ¼ 3) and other illness (n ¼ 10). Only one serious adverse event was related to the study treatment with a participant hospitalized following a cycling accident.
Costs and cost-effectiveness The total non-protocol cost to set-up and deliver the HEART intervention during the trial was $20,313 (E10,803) or $239 (E127) per intervention participant. For the within-trial economic evaluation, the ICER per QALY was $28,768 (E15,247). If the decision-
maker was willing to pay $20,000 (E10,600) – a threshold commonly accepted as cost-effective in New Zealand – and $50,000 (E26,500) per QALY, there would be a 72% and 90% probability, respectively, that the intervention would be cost-effective. The ICERs per MET-hour of walking and leisure activity a week were $48 (E26) and $74 (E39), respectively. To evaluate the HEART intervention as an ongoing national programme, age-standardized publicly funded hospital discharge rates for ICD codes I20-251 only (diagnosis – ‘‘ischaemic heart diseases’’) in 2009– 10, reported at 383.9 per 100,000 population,36 the current New Zealand population of 4,458,000, and the 59% consent rate at the metropolitan hospitals for this study, were used to estimate that over 10,000 potential participants per annum for this programme may exist nationally. We then halved both the potential participant pool and consent rate for a more conservative estimate of 2500. Under these circumstances, the incremental cost per HEART participant would be $22.37 (E11.90) giving an ICER of $2693 (E1427) per
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QALY, with a 95% probability the intervention is costeffective at a willingness to pay of $20,000 (E10,600) per QALY, The ICERs per MET-hour of walking and
leisure activity a week were, respectively, $4.45 (E2.37) and $6.95 (E3.70).
Discussion Table 1. Participant demographics.
Age (mean, SD) Male Female Ethnicity NZ Maori Pacific Asian NZ European/other Medical historya High blood pressure High cholesterol Heart attack Angina Diabetes Current smoker Ex-smoker Never smoked
Intervention (n ¼ 85)
Control (n ¼ 86)
Total (n ¼ 171)
61.4 n 69 16
(8.9) (%) (81) (19)
59.0 n 70 16
(9.5) (%) (81) (19)
60.2 n 139 32
(9.3) (%) (81) (19)
6 5 8 66
(7) (6) (9) (78)
7 5 9 65
(8) (6) (10) (76)
13 10 17 131
(8) (6) (10) (76)
40 65 61 43 11 6 36 43
(47) (76) (72) (51) (13) (7) (42) (51)
49 61 65 42 16 5 34 47
(57) (71) (76) (49) (19) (6) (40) (55)
89 126 126 85 27 11 70 90
(52) (74) (74) (50) (16) (6) (41) (53)
a
Participants could select as many medical conditions as applied.
To our knowledge, HEART is the first RCT to evaluate the effectiveness and cost-effectiveness of a mHealth CR exercise programme for people with IHD. Exercise support delivered via mobile phone and the Internet was not effective at increasing cardiorespiratory exercise capacity over and above usual care, but did have positive effects on selected secondary outcomes, including levels of self-reported physical activity, walking, self-efficacy and physical aspects of health-related quality of life. The intervention is likely to be cost-effective compared to usual care for increasing walking among people with IHD.
Strengths and limitations This study has several strengths. The use of computer randomization ensured allocation concealment was maintained, and baseline prognostic factors were well balanced. An objective measure was used for the primary outcome, to which assessors were blinded to group allocation. This study also used intention to treat analyses and provided an economic evaluation of the intervention. The major limitation of this trial was the self-reported measure of physical activity behaviour, which is associated with recall bias. In the present study,
Table 2. Baseline assessments.
BMI Waist (cm) Peak VO2 (ml1 kg min1) Systolic BP (mmHg) Diastolic BP (mmHg) TPA (min/week) LTPA (min/week) Walking (min/week) Sitting (min/week) Task self-efficacy Barrier self-efficacy Locus of causality EQ-5D SF36 Physical Component SF36 Mental Component
Intervention (n ¼ 85) Mean (SD)
Control (n ¼ 86) Mean (SD)
Total (n ¼ 171) Mean (SD)
28.6 102.2 26.8 131.9 78.2 1313.9 320.3 449.8 2283.4 76.7 65.5 4.2 0.8 51.6 52.87
28.7 102.3 27.1 131.2 78.4 1257.6 275.5 416.8 2265.3 74.5 62.4 4.3 0.8 51.9 51.53
28.7 102.3 26.9 131.5 78.5 1285.4 297.6 433.1 2274.3 75.6 63.9 4.2 0.8 51.7 52.19
(4.4) (10.0) (6.4) (15.7) (9.8) (1220) (377) (467) (988) (16.0) (21.4) (1.7) (0.1) (5.9) (6.94)
(4.9) (13.4) (6.5) (15.0) (9.9) (1285) (277) (374) (1147) (18.3) (21.7) (1.5) (0.1) (5.8) (8.40)
(4.6) (11.8) (6.4) (15.3) (9.8) (1250) (330) (421.2) (1068) (17.2) (21.6) (1.6) (0.1) (5.8) (7.72)
BMI, body mass index; VO2, peak oxygen uptake; BP, blood pressure; MET, metabolic equivalent; TPA, total physical activity, LTPA, leisure time physical activity.
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we focused on domain specific physical activity (leisure time), which is consistent with recommendations by developers of the IPAQ.37 We chose the IPAQ-LF because it is considered appropriate for research purposes, provides domain specific information, and permits international comparison; however, its responsiveness to change is less clear.37 In addition, there are concerns regarding the interpretation of the high prevalence estimates obtained from this measure.37 There was a null effect of the HEART intervention on increasing exercise capacity (PVO2) over and above usual care, which suggests the intensity of activity undertaken was insufficient to increase cardiorespiratory fitness. It is possible that our exercise regimen may have lacked sufficient progression and intensity to improve exercise capacity. Alternatively, the intensity aspect of the text messages may not have resonated
with participants, such that their own perceptions of moderate to vigorous intensity were likely to be lower than the true physiological intensity required to impact on exercise capacity. Maximal exercise capacity is a strong predictor of mortality in people with CVD38,39 and previous studies have demonstrated a dose–response relationship between levels of physical fitness and risk of both CHD and CVD mortality.40 The gradient is shaped such that relatively greater health benefits occur at the lower rather than higher end of the fitness spectrum.40 Physical inactivity is also associated with greater cardiovascular and all-cause mortality.41 Moreover, a strong (but less dramatic than for fitness) gradient dose–response relationship also exists between energy expenditure from weekly physical activity and prediction of all-cause mortality.42 Therefore from a public
Table 3. Treatment effects at 24 weeks for fitness and exercise outcomes. Adjusted means
Treatment difference
Variable
Intervention
Control
Difference
Lower 95% CI
Upper 95% CI
P
PVO2a (ml1 kg min1) TPA (min/week)b LTPA (min/week) Walking (min/week)
27.8 1555.0 383.2 512.3
27.9 1321.1 273.0 360.9
0.2 233.9 110.2 151.4
1.1 146.5 0.8 27.6
0.7 614.2 221.3 275.2
0.65 0.22 0.04c 0.02
a PVO2 data were missing at follow-up from 28 participants (16 in the intervention and 12 in the control group); bIPAQ data were missing at follow-up from 27 participants (17 in the intervention and 10 in the control group); cSignificant treatment effect.; VO2, peak oxygen uptake; TPA, total physical activity; LTPA, leisure time physical activity.
Table 4. Treatment effects at 24 weeks for psychological variables and health-related quality of life. Adjusted means
Treatment difference
Variable
Intervention
Control
Task efficacya Barrier efficacy Locus of causality EQ-5Db SF36 domains Physical functioning Role physical Bodily pain General health Vitality Social Functioning Role emotional Mental health
78.3 63.7 4.4 0.86
72.2 63.4 4.1 0.83
52.9 52.6 52.4 55.3 55.7 53.3 51.4 54.6
51.9 50.8 51.9 53.2 55.9 52.4 51.6 54.0
Difference 6.2 0.4 0.3 0.03 1.0 1.8 0.5 2.1 0.3 0.9 0.2 0.5
Lower 95% CI
Upper 95% CI
P
0.2 5.4 0.0 0.02
12.2 6.1 0.7 0.08
0.04c 0.90 0.07 0.23
0.6 0.3 2.1 0.1 2.2 1.3 2.5 1.5
2.7 3.9 3.1 4.1 1.7 3.1 1.9 2.6
0.2 0.08 0.71 0.03c 0.79 0.42 0.81 0.61
a Self-efficacy data were missing at follow-up from 27 participants (17 intervention; 10 control); bEQ5D and SF36 data were missing at follow-up from 18 participants (10 intervention; 8 control); cSignificant treatment effect.
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health and clinical perspective, our findings indicate that a relatively inexpensive and easy to implement intervention could have sustained impact on physical activity, which has considerable health benefits, particularly for those who are least active.42 This is particularly relevant for the cardiac population who are among the most recalcitrant to exercise. Notwithstanding these positive effects, the findings on physical activity must be interpreted with caution, given they were secondary outcomes assessed using a selfreported measure. The HEART intervention also resulted in greater efficacious beliefs to exercise for greater intensity and increasing duration (task self-efficacy) but not to overcome barriers to be active (barrier efficacy). These data provide some support for the intervention successfully manipulating key constructs of Social Cognitive Theory and offer some insight into the potential mechanism of the intervention on physical activity. The lack of effect on barrier efficacy was surprising given that text messages did target this variable. The barriers (e.g. weather, pain, work commitments, feeling unwell) assessed in the present study were drawn from a previous study of New Zealand patients with CVD;43 however we did not pre-determine whether these barriers were salient for our participants, which may have contributed to these results. The HEART intervention also had a positive effect on participant’s perception of general health, with a 1.6 point increase in the physical component score of the SF-36, which is consistent with previous telehealth trials in people with CVD.44 The post-hoc economic evaluation of the secondary outcomes, both within-trial and as an ongoing programme, found the HEART intervention was likely to be cost-effective in increasing MET-hours per week for walking and leisure activity. As an ongoing programme, it may also be cost-effective for improving health-related quality of life. There are no other similar interventions for comparison; however, previous economic evaluations have shown that CR is cost-effective for those who participate.5 Further economic evaluation of mHealth interventions are needed to elucidate whether they indeed offer a cost-effective approach to healthcare delivery.
Conclusions A mobile phone intervention was not effective at increasing exercise capacity over and above usual care. Positive effects were found for physical activity in favour of the intervention, which was likely to be cost-effective, and may have potential to augment existing CR services. More intensive exercise prescription may result in greater improvement of exercise capacity.
Acknowledgements The authors would like to acknowledge Paul Nolan, Brighid McCaffrey, Dr Aaron Lin and Dr Jocelyn Benetar for their contributions to data collection.
Funding This was an investigator-initiated study funded by a grant from the Health Research Council of New Zealand (10/446) and the Heart Foundation (1429). Dr Maddison was supported by a Heart Foundation Research Fellowship and a Health Research Council Sir Charles Hercus Research Fellowship. Trial registration: Australian New Zealand Clinical Trials Registry. Study ID number: ACTRN 12611000117910. Date of registration: 2 February 2011.
Conflict of interest None declared
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12. Cannistra L, Balady GJ, O’Malley C, et al. Comparison of the clinical profile and outcome of women and men in cardiac rehabilitation. Am J Cardiol 1992; 69: 1274–1279. 13. Evenson KR, Rosamond WD and Luepker RV. Predictors of outpatient cardiac rehabilitation utilization: The Minnesota Heart Surgey Registry. J Cardiopulm Rehabil 1998; 18: 192–198. 14. Pell J, Pell A, Morrison C, et al. Retrospective study of influence of deprivation on uptake of cardiac rehabilitation. BMJ 1996; 313: 267–268. 15. Castro CM and King AC. Telephone-assisted counselling for physical activity. Exerc Sport Sci Rev 2002; 30: 64–68. 16. World Health Organization Global Observatory for eHealth. mHealth: New horizons for health through mobile technologies. Based on the findings of the second global survey on health. Global Observatory for eHealth series, Vol 3. Geneva: World Health Organization, 2011. 17. Kwan G and Balady GJ. Cardiac Rehabilitation 2012: Advancing the Field Through Emerging Science. Circulation 2012; 12: e369–e73. 18. Redfern J, Thiagalingam A, Jan S, et al. Development of a set of mobile phone text messages designed for prevention of recurrent cardiovascular events. Eu J Prev Cardiol 2014; 21: 492–499. 19. Fox S. Mobile Health 2010. Pew Internet and American Life Project. http://www.pewinternet.org//media//Files/ Reports/2010/PIP_Mobile_Health_10.pdf (accessed 7 July 2010). 20. Smith A. Mobile access 2010. Pew Internet and American Life Project. http://www.pewinternet.org//media//Files/ Reports/2010/PIP_Mobile_Access_10.pdf (accessed 7 July 2010). 21. Fjeldsoe BS, Marshall AL and Miller YD. Behavior change interventions delivered by mobile phone telephone short-message service. Am J Prev Med 2009; 36: 165–173. 22. Maddison R, Whittaker R, Stewart R, et al. HEART: Heart Exercise and Remote Technologies: A Randomized Controlled Trial Study Protocol. BMC Cardiovasc Dis 2011; 11: doi:10.1186/471-2261-11-26. 23. U.S. Department of Health & Human Services. Physical Activity and Health: A report of the Surgeon General. Atlanta, GA: U.S. Department of Health & Human Services, Centres of Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, 1996:137. 24. Bandura A. Social foundations of thought and action. New-York: Prentice-Hall, 1986. 25. Oka RK, Gortner SR, Stotts NA and Haskell WL. Predictors of physical activity in patients with chronic heart failure secondary to either ischemic or ideopathic dilated cardiomyopathy. Am J Cardiol 1996; 77: 159–163. 26. Ewart CK, Taylor CB, Reese CB and Debusk RF. Effects of early post myocardial infarction exercise testing on self-perception and subsequent physical activity. Am J Cardiol 1983; 12: 1076–1080. 27. Maddison R, Prapavessis H, Armstrong G and Hill C. Modeling to increase Peak VO2 in people with heart failure. Ann Behav Med 2008; 36(1): 64–69. DOI: 10.1007/s12160-008-9050-y.
28. Whittaker R, Dorey E, Merry S, et al. A development and evaluation process for mHealth. J Health Comm 2012; 17(Suppl 1): 11–21. 29. Pfaeffli L, Maddison R, Whittaker R, et al. mHealth cardiac rehabilitation exercise intervention: findings from content development studies. BMC Cardiovasc Dis 2012; 12: 36. 30. American College of Sports Medicine. ACSM’S Guidelines for Exercise Testing and Prescription, 8th ed. Baltimore: Lippincott, 2009. 31. Craig CL, Marshall AJ, Sjo¨stro¨m M, et al. International Physical Activity Questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003; 35: 1381–1395. 32. McAuley E and Mihako SL. Measuring exercise-related self-efficacy. In: Duda JL (ed.) Advances in exercise psychology measurement. Morgantown: Fitness Information Technology, Inc., 1998, pp.371–389. 33. Ware JH, Kosinkski M and Dewey J. How to score version 2 of the SF-36 health survey: Standards and acute forms. Lincoln: Quality Metric Inc, 2000. 34. Rabin R and de Charro F. EQ-5D: a measure of health status from the EuroQol Group. Ann Med 2001; 33: 337–343. 35. Balady GJ, Jette D, Scheer J, et al. Changes in exercise capacity following cardiac rehabilitation in patients stratified according to age and gender. J Cardiopulm Rehabil 1996; 16(1): 38–46. 36. New Zealand Ministry of Health. Hospital Events 2008/ 09 and 2009/10. Wellington: Ministry of Health, 2012: http://www.health.govt.nz/system/files/documents/ publications/hospital-events-2008-09-09-10.pdf (accessed 28 November 2012). 37. Bauman A, Ainsworth BE, Bull F, et al. Progress and pitfalls in the use of the International Physical Activity Questionnaire (IPAQ) for adult physical activity surveillance. J Phys Act Health 2009; 6(Suppl 1): S5–S8. 38. Kavanagh T, Mertens DJ, Hamm LF, et al. Prediction of long-tern prognosis in 12 169 men referred for cardiac rehabilitation. Circulation 2002; 106: 661–671. 39. Kavanagh T, Mertens DJ, Hamm LF, et al. Peak oxygen inatke and cardiac mortality in women referred for cardiac rehabilitation. J Am Coll Cardiol 2003; 42: 2139–2143. 40. Williams PT. Physical fitness and activity as separate heart disease risk factors: a meta-analysis. Med Sci Sports Exerc 2001; 33: 754–761. 41. Pate R, Pratt M, Blair S, et al. Physical activity and public health: a recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA 1995; 273: 402–407. 42. Myers J, Kaykha A, George S, et al. Fitness versus physical activity patterns in predicting mortality in men. Am J Med 2004; 116: 912–918. 43. Maddison R and Prapavessis H. Using self-efficacy and intention to predict exercise compliance in patients with ischaemic heart disease. J Sport Exerc Psychol 2004; 26: 511–524. 44. Neubeck L, Redfern J, Fernandez R, et al. Telehealth interventions for the secondary prevention of coronary heart disease: a systematic review. Eur J Cardiovasc Prev Rehab 2009; 16: 281–289.
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A mobile phone intervention increases physical activity in people with cardiovascular disease: Results from the HEART randomized controlled trial Ralph Maddison, Leila Pfaeffli, Robyn Whittaker, Ralph Stewart, Andrew Kerr, Yannan Jiang, Geoffrey Kira, William Leung, Lance Dalleck, Karen Carter and Jonathan Rawstorn European Journal of Preventive Cardiology published online 9 May 2014 DOI: 10.1177/2047487314535076 The online version of this article can be found at: http://cpr.sagepub.com/content/early/2014/05/07/2047487314535076
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On behalf of: European Society of Cardiology
European Association for Cardiovascular Prevention and Rehabilitation
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EURO PEAN SO CIETY O F CARDIOLOGY ®
Original scientific paper
A mobile phone intervention increases physical activity in people with cardiovascular disease: Results from the HEART randomized controlled trial
European Journal of Preventive Cardiology 0(00) 1–9 ! The European Society of Cardiology 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/2047487314535076 ejpc.sagepub.com
Ralph Maddison1, Leila Pfaeffli1, Robyn Whittaker1, Ralph Stewart2, Andrew Kerr3, Yannan Jiang1, Geoffrey Kira4, William Leung5, Lance Dalleck6, Karen Carter1 and Jonathan Rawstorn1
Abstract Aim: To determine the effectiveness and cost-effectiveness of a mobile phone intervention to improve exercise capacity and physical activity behaviour in people with ischaemic heart disease (IHD). Methods and results: In this single-blind, parallel, two-arm, randomized controlled trial adults (n ¼ 171) with IHD were randomized to receive a mobile phone delivered intervention (HEART; n ¼ 85) plus usual care, or usual care alone (n ¼ 86). Adult participants aged 18 years or more, with a diagnosis of IHD, were clinically stable as outpatients, able to perform exercise, able to understand and write English, and had access to the Internet. The HEART (Heart Exercise And Remote Technologies) intervention involved a personalized, automated package of text messages and a secure website with video messages aimed at increasing exercise behaviour, delivered over 24 weeks. All participants were able to access usual community-based cardiac rehabilitation, which involves encouragement of physical activity and an offer to join a local cardiac support club. All outcomes were assessed at baseline and 24 weeks and included peak oxygen uptake (PVO2; primary outcome), selfreported physical activity, health-related quality of life, self-efficacy and motivation (secondary outcomes). Results showed no differences in PVO2 between the two groups (difference 0.21 ml kg1 min1, 95% CI: 1.1, 0.7; p ¼ 0.65) at 24 weeks. However significant treatment effects were observed for selected secondary outcomes, including leisure time physical activity (difference 110.2 min/week, 95% CI: 0.8, 221.3; p ¼ 0.05) and walking (difference 151.4 min/week, 95% CI: 27.6, 275.2; p ¼ 0.02). There were also significant improvements in self-efficacy to be active (difference 6.2%, 95% CI: 0.2, 12.2; p ¼ 0.04) and the general health domain of the SF36 (difference 2.1, 95% CI: 0.1, 4.1; p ¼ 0.03) at 24 weeks. The HEART programme was considered likely to be cost-effective for leisure time activity and walking. Conclusions: A mobile phone intervention was not effective at increasing exercise capacity over and above usual care. The intervention was effective and probably cost-effective for increasing physical activity and may have the potential to augment existing cardiac rehabilitation services.
Keywords Exercise, mobile phones, text messaging, rehabilitation, self-efficacy, trials Received 19 November 2013; accepted 16 April 2014 1
National Institute for Health Innovation, University of Auckland, Auckland, New Zealand 2 Department of Cardiology, Auckland City Hospital, Auckland, New Zealand 3 Department of Epidemiology and Biostatistics, University of Auckland, Auckland, New Zealand 4 School of Sport and Exercise, Massey University, Auckland, New Zealand
5 Department of Medicine, University of Auckland, Auckland, New Zealand 6 Department of Sport and Exercise Science, University of Auckland, Auckland, New Zealand
Corresponding author: Ralph Maddison, National Institute for Health Innovation, University of Auckland, Private Bag 92019, Victoria Street West, Auckland 1142, New Zealand. Email: [email protected]
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Introduction
Aim
Cardiac rehabilitation (CR), a programme of medication and risk factor education as well as psychological support is an essential part of the contemporary management of people with ischaemic heart disease (IHD).1 International guidelines consistently identify exercise therapy as a central element of CR1–4 and exercise-based CR programmes have been shown to be cost-effective for those who participate.5,6 A Cochrane systematic review7 of exercise-based CR reported that all-cause mortality was reduced by 26% (RR 0.74, 95% CI 0.63, 0.87). Despite the documented benefits of CR, participation is inadequate in all countries in which it has been measured.8 Adherence with supervised exercise CR is low with between 10% and 36% of individuals dropping out of supervised CR exercise programmes.8,9 It is evident that current centre-based CR practices do not suit all patients and alternative approaches are needed.10 Common reasons people give for not accepting the invitation to attend centre-based CR classes, which include supervised exercise, are distance to CR, problems with access and parking, lack of time11 and work or domestic commitments.12–14 Telephone-based interventions can be effective for physical activity behaviour change;15 however because of high penetration and relatively low costs,16 mobile phones have the potential to increase the reach of disease self-management or lifestyle coaching interventions for the secondary prevention of IHD.17,18 The benefits of mobile phone programmes are that they can be delivered anywhere at any time and for extended periods, facilitating regular communication and behavioural maintenance; they can be designed to send messages in a time-sensitive manner that fits with the individual’s lifestyle; they are proactive and do not require prompting by the user before support is offered; they can be personalized and tailored to suit specific demographic and health needs; they increase access (e.g. less travel); allow cheaper provision of services than face-to-face contacts; and they provide a way of reducing inequalities due to their widespread adoption by all cultural and socioeconomic groups.19,20 A systematic review supports the delivery of mobile phone text messaging interventions21 for achieving behaviour change. Of the 14 studies reviewed, 13 resulted in positive behaviour change outcomes for smoking cessation and diabetes management. However, to date a mobile phone delivered text message intervention to enhance exercise behaviour has not been examined in a CVD population. A randomized controlled trial was required to determine the effectiveness, safety and acceptability of such an approach.
The aim of this trial was to determine the effectiveness and cost-effectiveness of a mobile health (mHealth) delivered exercise CR programme for people with IHD to improve exercise capacity and physical activity levels compared to current services. We hypothesized that an mHealth intervention would increase exercise capacity. Secondary hypotheses were that the mHealth intervention would increase physical activity levels and would be associated with increased self-efficacy to be active.
Design The HEART (Heart Exercise and Remote Technologies) study was a parallel, two-arm, randomized controlled trial of exercise prescription and behavioural support by mobile phone text messages and Internet. The trial was undertaken in New Zealand between 2010 and 2012 (protocol published in 2011)22 and no changes were made to the study design in this time. Participants were adults aged 18 years or more, with a diagnosis of IHD, defined as angina, myocardial infarction, revascularization, including angioplasty, stent or coronary artery bypass graft within the previous 3–24 months. All participants were clinically stable as outpatients, able to perform exercise, able to understand and write English, and had access to the Internet (e.g. at home, work, library or through friends or relatives). Eligible participants were randomized to either receive an exercise intervention delivered via mobile phone, or to usual care, with encouragement to be physically active and attend a cardiac club. Participants were excluded if they had been admitted to hospital with heart disease within the previous 6 weeks; had terminal cancer, or had significant exercise limitations other than IHD. Study procedures and terms were approved by the New Zealand Multi-region Ethics Committee (NTX/10/10/099). Eligible participants were recruited from two metropolitan hospitals, and were identified by nurses as inpatients, through outpatient clinics and existing databases. Nurses contacted potential participants and those agreeing to participate were screened for eligibility.
Procedures All participants were free to participate in any other CR service or support that they wished to use. In Auckland, New Zealand, this typically involves participating in community-based CR education sessions on modifying CVD risk factors and psychological support, as well as encouragement to be physically active and an
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offer to join a local cardiac club that provides supervised exercise. In addition, participants in the intervention group received the HEART programme—a personalized, automated package of text messages via their mobile phones aimed at increasing exercise behaviour over 24 weeks. They received six messages per week for the first 12 weeks, five messages per week for 6 weeks and then four messages per week for the remaining 6 weeks (total 24 weeks).
Intervention The primary goal of the HEART programme was to have all individuals participate in moderate to vigorous aerobic-based exercise for a minimum of 30 minutes (preferably more) most days (at least 5) of the week, in line with current recommendations.23 The homebased programme consisted of (1) regular exercise prescription, (2) provision of behaviour change strategies and (3) technical support. The intervention focused on increasing leisure time physical activity – walking in particular – as well as encouragement to accrue incidental activity through daily tasks such as household chores and active transport. The intervention also focused on altering the key mediators of behaviour change, including self-efficacy, social support and motivation. Self-efficacy refers to an individual’s beliefs in his or her capabilities to execute necessary courses of action to satisfy situational demands.24 Self-efficacy is theorized to influence the activities that individuals choose to approach, the effort expended on such activities and the degree of persistence demonstrated in the face of adverse stimuli.24 Within the cardiac setting, self-efficacy has been the most examined psychological variable and has consistently been shown to be related to exercise behaviour,25 and treadmill test performance.26,27 Additional information was provided via a secure website that participants could log on to. This included role model video vignettes, an opportunity to self-monitor progress, as well as information on various forms of physical activity and exercise, energy expenditure, healthy eating advice, and links to other websites (e.g. local exercise programmes and cardiac clubs). Participants received 3–5 text messages per week (total of 118 messages over 24 weeks). Participants were encouraged to log onto the website once per week to view new information and video messages (three new messages added per week, 30–60 s in length). In total it was estimated that using the intervention to its full extent (maximum dose ¼ reading all text messages and using the website) took participants an average of 10 minutes per week. The intervention followed the mHealth development and evaluation framework28 and was pre-tested and
refined prior to conducting the trial.29 Full details of the intervention are described in the protocol.22
Outcomes The primary outcome of the trial was change in peak oxygen uptake (PVO2) from baseline to 24 weeks, which was determined using respiratory gas analysis during a standardized treadmill exercise testing protocol. A Moxus (AEI Technologies Inc., Pittsburgh, USA) metabolic cart was used to obtain breathby-breath measurements of VO2 and carbon dioxide production (VCO2). All testing was conducted in accordance with the ACSM guidelines30 by a trained exercise physiologist blinded to treatment allocation. A graded protocol was initiated at a comfortable walking speed, and the gradient was increased by two degrees every 60 s until volitional exhaustion. Care was taken to ensure that participants exceeded the anaerobic threshold or a respiratory exchange ratio (RER) greater than 1.15 to indicate adequate effort. Secondary outcomes included self-reported physical activity, self-efficacy and motivation to exercise, and health-related quality of life at 24 weeks. An economic evaluation was also conducted. Self-reported physical activity levels were assessed using the International Physical Activity Questionnaire long form (IPAQLF).31 Self-efficacy (task and barrier) were assessed using validated measures and a scale of 0 ‘‘no confidence’’ to 100% ‘‘complete confidence’’.32 For example, ‘‘how confident are you that you can complete 30 minutes of physical activity at a moderate effort on most days of next week?’’ For task efficacy, scores were summed with greater values indicating greater efficacy to exercise for longer periods of time and at a greater level of intensity. For barrier efficacy, participants rated their confidence to overcome seven common reasons (e.g. bad weather, lack of time, pain or discomfort) preventing people from participating in exercise sessions. Efficacy strength was calculated by summing the scores and dividing by total number of items used. Health-related quality of life was assessed using the standard version of the Short Form SF36 version 233 and EQ-5D.34 All questionnaires were administered during the clinic visits by trained research assistants, who also observed participant’s completion.
Economic evaluation For the cost-effectiveness analyses, we collected information on the costs of implementing and delivering the intervention only. Healthcare utilization and wider societal costs were not collected as this was a post hoc economic evaluation. Staff costs included a 50% overhead rate, and Web hosting fees, although not
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charged, were included for the purposes of this evaluation. Reported costs are in 2012 $NZ exclusive of Goods and Services Tax. In 2012, the purchasing power parity of NZ$1 ¼ E0.53. The EQ-5D (NZ tariff 2) was used to obtain a single preference index for the estimation of quality-adjusted life years (QALYs). Incremental cost-effectiveness ratios (ICERs) per QALY and for outcomes with a significant treatment effect were calculated. The ICER summarizes the additional cost per unit of health benefit gained by switching from usual care to the HEART intervention. To evaluate uncertainty in the ICER, cost-effectiveness acceptability curves were calculated from non-parametric bootstrapping with 10,000 replications. In scenario analysis, the intervention was evaluated as an ongoing nationwide programme rather than as a trial. Set-up costs were amortized at 3.5% over 4 years (the minimum estimated lifetime of the technological investment) over the potential national participant pool. As all contacts are automated and staff attention was rarely required, the trial’s monthly staff maintenance and web-hosting costs are scalable nationally. However, to provide a conservative estimate, the monthly maintenance costs were doubled and split over potential participants for the 6-month intervention period.
Randomization and blinding On completion of the baseline assessment, eligible participants were randomly allocated at a 1:1 ratio to either intervention or control group by means of a central computerized service. Randomization was conducted using the minimization method, stratifying by sex (male and female), ethnicity (Maori – indigenous – and non-Maori), and exercise history (attendance or not at least one CR session). Allocation concealment was maintained up to the point of randomization. This was a single-blind trial, where outcome assessors were blinded to treatment allocation. However, it was not possible to blind trial participants to their allocation.
Statistical analyses Based on previous research,35 an a priori sample size estimate indicated that 170 participants (85 per group) would provide 90% power at 5% level of significance (two-sided) to detect a treatment difference of at least 2.5 ml1 kg min1 between the two groups, on change in PVO2 from baseline to 24 weeks assuming a standard deviation of 5 ml1 kg min1. A formal statistical analysis plan (SAP) was approved by the Trial Steering Committee before datalock. Statistical analyses were performed using SAS
version 9.3 (SAS Institute Inc. Cary NC) and R version 2.15 (R Foundations for Statistical Computing). All statistical tests were two-tailed and a 5% significance level maintained throughout the analyses. Treatment evaluations were performed on the principle of intention to treat (ITT), using data collected from all randomized participants. Multiple imputations method was applied to the missing data for the primary outcome only. Analysis of covariance (ANCOVA) regression model was used to evaluate the main treatment effect on the primary outcome between the two treatment groups, adjusting for its baseline measure, age, sex, ethnicity and exercise history (i.e. stratification factors). A similar approach was used for other continuous secondary outcome measures.
Results A total of 171 eligible participants were randomized to the trial (Figure 1). Eligible participants were recruited from May 2011 to October 2012 via two Auckland (population 1.4 million) hospitals. Participants attended clinic visits at the time of randomization (baseline) and six months later. The majority of participants were male (139/171, 81%), New Zealand European (131/171, 76%), with a mean age of 60 years (SD ¼ 9.3). Treatment groups were well balanced at baseline (Table 1 and 2). During the trial 82% of participants in the intervention read some or all of the HEART text messages and 57% of participants viewed some or all of the video messages on the website. On average participants viewed the website once every two weeks. The primary outcome was measured for 75 (88%) participants in the intervention group and 78 (90%) in the control group at 24 weeks (Figure 1). Four participants in each of the respective groups were unable to complete the PVO2 assessments for medical reasons. As shown in Table 3, both groups showed a small increase in PVO2 from baseline to 24 weeks; however there were no differences between the HEART intervention and control groups (difference 0.2 ml1 kg min1, 95% CI: 1.1, 0.7; p ¼ 0.65) at 24 weeks. There was a significant increase in self-reported leisure time physical activity (difference 110.2 min/week, 95% CI: 0.8, 221.3; p ¼ 0.05) and walking (difference 151.4 min/ week, 95% CI: 27.6, 275.2; p ¼ 0.02) at 24 weeks in favour of the HEART intervention, which represented increases of 40% and 42%, respectively. For the other activity domains (total activity, active transport and domestic/gardening, and reduced sitting time), there were no statistically significant differences. There were also significant improvements in selfefficacy to be active (difference 6.2%, 95% CI: 0.2, 12.2; p ¼ 0.04) and the general health domain of the
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Screening registration (N=288) Excluded from study (n=108) -Declined to proceed (n=60) -Could not contact (n=17) -Not eligible to participate (n=31)
Study registration (N=180) Excluded from study (n=9) -Attended clinic but were medically unstable to complete VO2 test (n=9)
Randomization (N=171)
Intervention (N=85)
Baseline (N=85)
Lost to follow up (n=10) -Could not contact (n=5) -Unable to complete assessment for medical reason (n=4) -Did not wish to return (n=1)
24 weeks (N=75)
Control (N=86)
Baseline (N=86)
24 weeks (N=78)
Lost to follow up (n=8) -Could not contact (n=3) -Unable to complete assessment for medical reason (n=4) -Did not wish to return (n=1)
Figure 1. Flow of participants in study.
SF36 (difference 2.1, 95% CI: 0.1, 4.1; p ¼ 0.03) at 24 weeks (Table 4). No statistically significant differences were observed in other outcomes between the two groups. Twenty-two participants reported 31 serious adverse events. Of these, 15 were cardiac related (angina/chest pain ¼ 4; stenosis ¼ 2; heart palpitations ¼ 1; shortness of breath ¼ 2; dizziness ¼ 1; pericarditis ¼ 3; ventricular tachycardia ¼ 2). The remaining serious adverse events included cancer diagnosis (n ¼ 3); injury (n ¼ 3) and other illness (n ¼ 10). Only one serious adverse event was related to the study treatment with a participant hospitalized following a cycling accident.
Costs and cost-effectiveness The total non-protocol cost to set-up and deliver the HEART intervention during the trial was $20,313 (E10,803) or $239 (E127) per intervention participant. For the within-trial economic evaluation, the ICER per QALY was $28,768 (E15,247). If the decision-
maker was willing to pay $20,000 (E10,600) – a threshold commonly accepted as cost-effective in New Zealand – and $50,000 (E26,500) per QALY, there would be a 72% and 90% probability, respectively, that the intervention would be cost-effective. The ICERs per MET-hour of walking and leisure activity a week were $48 (E26) and $74 (E39), respectively. To evaluate the HEART intervention as an ongoing national programme, age-standardized publicly funded hospital discharge rates for ICD codes I20-251 only (diagnosis – ‘‘ischaemic heart diseases’’) in 2009– 10, reported at 383.9 per 100,000 population,36 the current New Zealand population of 4,458,000, and the 59% consent rate at the metropolitan hospitals for this study, were used to estimate that over 10,000 potential participants per annum for this programme may exist nationally. We then halved both the potential participant pool and consent rate for a more conservative estimate of 2500. Under these circumstances, the incremental cost per HEART participant would be $22.37 (E11.90) giving an ICER of $2693 (E1427) per
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QALY, with a 95% probability the intervention is costeffective at a willingness to pay of $20,000 (E10,600) per QALY, The ICERs per MET-hour of walking and
leisure activity a week were, respectively, $4.45 (E2.37) and $6.95 (E3.70).
Discussion Table 1. Participant demographics.
Age (mean, SD) Male Female Ethnicity NZ Maori Pacific Asian NZ European/other Medical historya High blood pressure High cholesterol Heart attack Angina Diabetes Current smoker Ex-smoker Never smoked
Intervention (n ¼ 85)
Control (n ¼ 86)
Total (n ¼ 171)
61.4 n 69 16
(8.9) (%) (81) (19)
59.0 n 70 16
(9.5) (%) (81) (19)
60.2 n 139 32
(9.3) (%) (81) (19)
6 5 8 66
(7) (6) (9) (78)
7 5 9 65
(8) (6) (10) (76)
13 10 17 131
(8) (6) (10) (76)
40 65 61 43 11 6 36 43
(47) (76) (72) (51) (13) (7) (42) (51)
49 61 65 42 16 5 34 47
(57) (71) (76) (49) (19) (6) (40) (55)
89 126 126 85 27 11 70 90
(52) (74) (74) (50) (16) (6) (41) (53)
a
Participants could select as many medical conditions as applied.
To our knowledge, HEART is the first RCT to evaluate the effectiveness and cost-effectiveness of a mHealth CR exercise programme for people with IHD. Exercise support delivered via mobile phone and the Internet was not effective at increasing cardiorespiratory exercise capacity over and above usual care, but did have positive effects on selected secondary outcomes, including levels of self-reported physical activity, walking, self-efficacy and physical aspects of health-related quality of life. The intervention is likely to be cost-effective compared to usual care for increasing walking among people with IHD.
Strengths and limitations This study has several strengths. The use of computer randomization ensured allocation concealment was maintained, and baseline prognostic factors were well balanced. An objective measure was used for the primary outcome, to which assessors were blinded to group allocation. This study also used intention to treat analyses and provided an economic evaluation of the intervention. The major limitation of this trial was the self-reported measure of physical activity behaviour, which is associated with recall bias. In the present study,
Table 2. Baseline assessments.
BMI Waist (cm) Peak VO2 (ml1 kg min1) Systolic BP (mmHg) Diastolic BP (mmHg) TPA (min/week) LTPA (min/week) Walking (min/week) Sitting (min/week) Task self-efficacy Barrier self-efficacy Locus of causality EQ-5D SF36 Physical Component SF36 Mental Component
Intervention (n ¼ 85) Mean (SD)
Control (n ¼ 86) Mean (SD)
Total (n ¼ 171) Mean (SD)
28.6 102.2 26.8 131.9 78.2 1313.9 320.3 449.8 2283.4 76.7 65.5 4.2 0.8 51.6 52.87
28.7 102.3 27.1 131.2 78.4 1257.6 275.5 416.8 2265.3 74.5 62.4 4.3 0.8 51.9 51.53
28.7 102.3 26.9 131.5 78.5 1285.4 297.6 433.1 2274.3 75.6 63.9 4.2 0.8 51.7 52.19
(4.4) (10.0) (6.4) (15.7) (9.8) (1220) (377) (467) (988) (16.0) (21.4) (1.7) (0.1) (5.9) (6.94)
(4.9) (13.4) (6.5) (15.0) (9.9) (1285) (277) (374) (1147) (18.3) (21.7) (1.5) (0.1) (5.8) (8.40)
(4.6) (11.8) (6.4) (15.3) (9.8) (1250) (330) (421.2) (1068) (17.2) (21.6) (1.6) (0.1) (5.8) (7.72)
BMI, body mass index; VO2, peak oxygen uptake; BP, blood pressure; MET, metabolic equivalent; TPA, total physical activity, LTPA, leisure time physical activity.
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we focused on domain specific physical activity (leisure time), which is consistent with recommendations by developers of the IPAQ.37 We chose the IPAQ-LF because it is considered appropriate for research purposes, provides domain specific information, and permits international comparison; however, its responsiveness to change is less clear.37 In addition, there are concerns regarding the interpretation of the high prevalence estimates obtained from this measure.37 There was a null effect of the HEART intervention on increasing exercise capacity (PVO2) over and above usual care, which suggests the intensity of activity undertaken was insufficient to increase cardiorespiratory fitness. It is possible that our exercise regimen may have lacked sufficient progression and intensity to improve exercise capacity. Alternatively, the intensity aspect of the text messages may not have resonated
with participants, such that their own perceptions of moderate to vigorous intensity were likely to be lower than the true physiological intensity required to impact on exercise capacity. Maximal exercise capacity is a strong predictor of mortality in people with CVD38,39 and previous studies have demonstrated a dose–response relationship between levels of physical fitness and risk of both CHD and CVD mortality.40 The gradient is shaped such that relatively greater health benefits occur at the lower rather than higher end of the fitness spectrum.40 Physical inactivity is also associated with greater cardiovascular and all-cause mortality.41 Moreover, a strong (but less dramatic than for fitness) gradient dose–response relationship also exists between energy expenditure from weekly physical activity and prediction of all-cause mortality.42 Therefore from a public
Table 3. Treatment effects at 24 weeks for fitness and exercise outcomes. Adjusted means
Treatment difference
Variable
Intervention
Control
Difference
Lower 95% CI
Upper 95% CI
P
PVO2a (ml1 kg min1) TPA (min/week)b LTPA (min/week) Walking (min/week)
27.8 1555.0 383.2 512.3
27.9 1321.1 273.0 360.9
0.2 233.9 110.2 151.4
1.1 146.5 0.8 27.6
0.7 614.2 221.3 275.2
0.65 0.22 0.04c 0.02
a PVO2 data were missing at follow-up from 28 participants (16 in the intervention and 12 in the control group); bIPAQ data were missing at follow-up from 27 participants (17 in the intervention and 10 in the control group); cSignificant treatment effect.; VO2, peak oxygen uptake; TPA, total physical activity; LTPA, leisure time physical activity.
Table 4. Treatment effects at 24 weeks for psychological variables and health-related quality of life. Adjusted means
Treatment difference
Variable
Intervention
Control
Task efficacya Barrier efficacy Locus of causality EQ-5Db SF36 domains Physical functioning Role physical Bodily pain General health Vitality Social Functioning Role emotional Mental health
78.3 63.7 4.4 0.86
72.2 63.4 4.1 0.83
52.9 52.6 52.4 55.3 55.7 53.3 51.4 54.6
51.9 50.8 51.9 53.2 55.9 52.4 51.6 54.0
Difference 6.2 0.4 0.3 0.03 1.0 1.8 0.5 2.1 0.3 0.9 0.2 0.5
Lower 95% CI
Upper 95% CI
P
0.2 5.4 0.0 0.02
12.2 6.1 0.7 0.08
0.04c 0.90 0.07 0.23
0.6 0.3 2.1 0.1 2.2 1.3 2.5 1.5
2.7 3.9 3.1 4.1 1.7 3.1 1.9 2.6
0.2 0.08 0.71 0.03c 0.79 0.42 0.81 0.61
a Self-efficacy data were missing at follow-up from 27 participants (17 intervention; 10 control); bEQ5D and SF36 data were missing at follow-up from 18 participants (10 intervention; 8 control); cSignificant treatment effect.
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health and clinical perspective, our findings indicate that a relatively inexpensive and easy to implement intervention could have sustained impact on physical activity, which has considerable health benefits, particularly for those who are least active.42 This is particularly relevant for the cardiac population who are among the most recalcitrant to exercise. Notwithstanding these positive effects, the findings on physical activity must be interpreted with caution, given they were secondary outcomes assessed using a selfreported measure. The HEART intervention also resulted in greater efficacious beliefs to exercise for greater intensity and increasing duration (task self-efficacy) but not to overcome barriers to be active (barrier efficacy). These data provide some support for the intervention successfully manipulating key constructs of Social Cognitive Theory and offer some insight into the potential mechanism of the intervention on physical activity. The lack of effect on barrier efficacy was surprising given that text messages did target this variable. The barriers (e.g. weather, pain, work commitments, feeling unwell) assessed in the present study were drawn from a previous study of New Zealand patients with CVD;43 however we did not pre-determine whether these barriers were salient for our participants, which may have contributed to these results. The HEART intervention also had a positive effect on participant’s perception of general health, with a 1.6 point increase in the physical component score of the SF-36, which is consistent with previous telehealth trials in people with CVD.44 The post-hoc economic evaluation of the secondary outcomes, both within-trial and as an ongoing programme, found the HEART intervention was likely to be cost-effective in increasing MET-hours per week for walking and leisure activity. As an ongoing programme, it may also be cost-effective for improving health-related quality of life. There are no other similar interventions for comparison; however, previous economic evaluations have shown that CR is cost-effective for those who participate.5 Further economic evaluation of mHealth interventions are needed to elucidate whether they indeed offer a cost-effective approach to healthcare delivery.
Conclusions A mobile phone intervention was not effective at increasing exercise capacity over and above usual care. Positive effects were found for physical activity in favour of the intervention, which was likely to be cost-effective, and may have potential to augment existing CR services. More intensive exercise prescription may result in greater improvement of exercise capacity.
Acknowledgements The authors would like to acknowledge Paul Nolan, Brighid McCaffrey, Dr Aaron Lin and Dr Jocelyn Benetar for their contributions to data collection.
Funding This was an investigator-initiated study funded by a grant from the Health Research Council of New Zealand (10/446) and the Heart Foundation (1429). Dr Maddison was supported by a Heart Foundation Research Fellowship and a Health Research Council Sir Charles Hercus Research Fellowship. Trial registration: Australian New Zealand Clinical Trials Registry. Study ID number: ACTRN 12611000117910. Date of registration: 2 February 2011.
Conflict of interest None declared
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