Evaluating the Impact of the HeartHab App on Motivation, Physical Activity, Quality of Life, and Risk Factors of Coronary Artery Disease Patients: Multidisciplinary Crossover Study

Supraja Sankaran, Paul Dendale, Karin Coninx, Supraja Sankaran, Paul Dendale, Karin Coninx

Abstract

Background: Telerehabilitation approaches have been successful in supporting coronary artery disease (CAD) patients to rehabilitate at home after hospital-based rehabilitation. However, on completing a telerehabilitation program, the effects are not sustained beyond the intervention period because of the lack of lifestyle adaptations. Furthermore, decline in patients' motivation lead to recurrence of disease and increased rehospitalization rates. We developed HeartHab, using persuasive design principles and personalization, to enable sustenance of rehabilitation effects beyond the intervention period. HeartHab promotes patients' understanding, motivates them to reach personalized rehabilitation goals, and helps to maintain positive lifestyle adaptations during telerehabilitation.

Objective: This study aimed to investigate the impact of the HeartHab app on patients' overall motivation, increasing physical activities, reaching exercise targets, quality of life, and modifiable risk factors in patients with CAD during telerehabilitation. The study also investigated carryover effects to determine the maintenance of effects after the conclusion of the intervention.

Methods: A total of 32 CAD patients were randomized on a 1:1 ratio to telerehabilitation or usual care. We conducted a 4-month crossover study with a crossover point at 2 months using a mixed-methods approach for evaluation. We collected qualitative data on users' motivation, user experience, and quality of life using questionnaires, semistructured interviews and context-based sentiment analysis. Quantitative data on health parameters, exercise capacity, and risk factors were gathered from blood tests and ergo-spirometry tests. Data procured during the app usage phase were compared against baseline values to assess the impact of the app on parameters such as motivation, physical activity, quality of life, and risk factors. Carryover effects were used to gather insights on the maintenance of effects.

Results: The qualitative data showed that 75% (21/28) of patients found the HeartHab app motivating and felt encouraged to achieve their rehabilitation targets. 84% (21/25) of patients either reached or exceeded their prescribed physical activity targets. We found positive significant effects on glycated hemoglobin (P=.01; d=1.03; 95% CI 0.24-1.82) with a mean decrease of 1.5 mg/dL and high-density lipoprotein (HDL) cholesterol (P=.04; d=0.78; 95% CI 0.02-1.55) with a mean increase of 0.61 mg/dL after patients used the HeartHab app. We observed significant carryover effects on weight, HDL cholesterol, and maximal oxygen consumption (VO2 max), indicating the maintenance of effects.

Conclusions: Persuasive design techniques integrated in HeartHab and tailoring of exercise targets were effective in motivating patients to reach their telerehabilitation targets. This study demonstrated significant effects on glucose and HDL cholesterol and positive carryover effects on weight, HDL cholesterol, and VO2 max. There was also a perceived improvement in quality of life. A longer-term evaluation with more patients could possibly reveal effectiveness on other risk factors and maintenance of the positive health behavior change.

Trial registration: ClinicalTrials.gov NCT03102671; https://ichgcp.net/clinical-trials-registry/NCT03102671 (Archived by WebCite at http://www.webcitation.org/76gzI9Pvd).

Keywords: cardiac rehabilitation; evaluation studies; heart diseases; human factors engineering; mobile app; multidisciplinary research; telerehabilitation.

Conflict of interest statement

Conflicts of Interest: None declared.

©Supraja Sankaran, Paul Dendale, Karin Coninx. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 04.04.2019.

Figures

Figure 1
Figure 1
The process of randomization showing change in phases of the study for both groups before and after crossover.
Figure 2
Figure 2
Qualitative and quantitative data collected across different time points of the study. IPAQ: International Physical Activity Questionnaire; EQ-5D: EuroQol 5-Dimensions questionnaire.
Figure 3
Figure 3
Flowchart showing the statistical analysis process to evaluate the effect of HeartHab on various health metrics.
Figure 4
Figure 4
Flowchart showing the process of statistical analysis to identify significant carryover effects. UC: under control; SUM: summation.
Figure 5
Figure 5
Representation of all patients recruited in the study, their randomization sequence, and app usage.
Figure 6
Figure 6
Results of sentiment analysis using NVivo on increasing physical activity levels, promoting medication adherence and adopting healthier lifestyles after using the HeartHab app.
Figure 7
Figure 7
Results of sentiment analysis using NVIVO on patients' motivation to continue using HeartHab and the impact of the app on improving their overall understandability and comprehension.
Figure 8
Figure 8
Patients' perceptions on the impact of HeartHab on motivation to achieve physical activity targets as collected in the intermediate questionnaire.
Figure 9
Figure 9
Sentiment analysis using NVivo on the impact of various aspects of HeartHab on motivation to be more physically active.
Figure 10
Figure 10
Chart showing weekly physical activity targets and totals METs achieved each week by patients that used the physical activity module of the HeartHab app. The chart depicts only complete data for weeks when a patient registered activities. MET: Metabolic Equivalents of Task.
Figure 11
Figure 11
Graphs showing increase or decrease in total Metabolic Equivalents Of Task across different phases of the study for both groups of patients as collected from the International Physical Activity Questionnaire. MET: Metabolic Equivalents of Task.
Figure 12
Figure 12
Changes in various assessments of quality of life across different phases of the study. QALY: quality-adjusted life years; VAS: visual analog scale.

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