Abstract
BackgroundA number of mobile health (mHealth) apps exist that focus specifically on promoting exercise behavior. To increase user engagement, prompts, such as text messages, emails, or push notifications, are often used. To date, little research has been done to understand whether, and for how long, these prompts influence exercise behavior.ObjectiveThis study aimed to assess the impact of prompts on mHealth self-monitoring and self-reported exercise in the days following a prompt and whether these effects differ based on exercise modality.MethodsOf the possible 99 adults at risk for developing type II diabetes who participated in a diabetes prevention program, 69 were included in this secondary analysis. Participants were randomly assigned to 1 of the following 2 exercise conditions: high-intensity interval training or moderate-intensity continuous training. In the year following a brief, community-based diabetes prevention program involving counseling and supervised exercise sessions, all participants self-monitored their daily exercise behaviors on an mHealth app in which they were sent personalized prompts at varying frequencies. mHealth self-monitoring and self-reported exercise data from the app were averaged over 1, 3, 5, and 7 days preceding and following a prompt and subsequently compared using t tests.ResultsIn the year following the diabetes prevention program, self-monitoring (t68=6.82; P<.001; d=0.46) and self-reported exercise (t68=2.16; P=.03; d=0.38) significantly increased in the 3 days following a prompt compared with the 3 days preceding. Prompts were most effective in the first half of the year, and there were no differences in self-monitoring or self-reported exercise behaviors between exercise modalities (P values >.05). In the first half of the year, self-monitoring was significant in the 3 days following a prompt (t68=8.61; P<.001; d=0.60), and self-reported exercise was significant in the 3 days (t68=3.7; P<.001; d=0.37), 5 days (t67=2.15; P=.04; d=0.14), and 7 days (t68=2.46; P=.02; d=0.15) following a prompt, whereas no significant changes were found in the second half of the year.ConclusionsThis study provides preliminary evidence regarding the potential influence of prompts on mHealth self-monitoring and self-reported exercise and the duration for which prompts may be effective as exercise behavior change tools. Future studies should determine the optimal prompting frequency for influencing self-reported exercise behaviors. Optimizing prompt frequency can potentially reduce intervention costs and promote user engagement. Furthermore, it can encourage consumers to self-monitor using mHealth technology while ensuring prompts are sent when necessary and effective.International Registered Report Identifier (IRRID)DERR2-10.2196/11226
Highlights
BackgroundMobile phones are ubiquitous and becoming an integral part of daily life
This study provides preliminary evidence regarding the potential influence of prompts on mobile health (mHealth) self-monitoring and self-reported exercise and the duration for which prompts may be effective as exercise behavior change tools
In the year following a diabetes prevention program, there were no significant increases in mHealth self-monitoring or self-reported exercise in 1, 5, and 7 days following a prompt compared with the days preceding a prompt
Summary
BackgroundMobile phones are ubiquitous and becoming an integral part of daily life. In 2015, global subscriptions of mobile phones were approximately 7 billion; this constitutes a substantial increase from 738 million subscriptions in 2000 [1]. As the widespread adoption of mobile phones increases, so too does the opportunity for the development and implementation of theory-driven, cost-effective, evidence-based mobile phone apps (ie, mobile health [mHealth] app) used to influence health behaviors. An mHealth app is any mobile phone app, which is used for tracking, guiding, teaching, or enabling individuals in any health-related behaviors and can range from tracking diet and exercise to guided meditation or monitoring of diabetic sugar level. The accessibility of these apps is advantageous for researchers who can monitor consumer behaviors remotely, provide real-time feedback, and aggregate data so as to improve monitoring systems [4]. Little research has been done to understand whether, and for how long, these prompts influence exercise behavior
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