ArticleJMIR mHealth and uHealth2017
How Do Apps Work? An Analysis of Physical Activity App Users' Perceptions of Behavior Change Mechanisms.
Article in JMIR mHealth and uHealth, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
20 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Assessing the Acceptability and Effectiveness of Mobile-Based Physical Activity Interventions for Midlife Women During Menopause: Systematic Review of the Literature.JMIR mHealth and uHealth · 2022Pooled it
- Associations Between Digital Health Intervention Engagement, Physical Activity, and Sedentary Behavior: Systematic Review and Meta-analysis.Journal of medical Internet research · 2021Pooled it
- Experiences of mobile health in promoting physical activity: A qualitative systematic review and meta-ethnography.PloS one · 2018Pooled it
- Efficacy of a theory-based and tailored mHealth intervention promoting walking behavior: a preliminary randomized controlled trial.Scientific reports · 2025Trial
- User Perception of a Smartphone App to Promote Physical Activity Through Active Transportation: Inductive Qualitative Content Analysis Within the Smart City Active Mobile Phone Intervention (SCAMPI) Study.JMIR mHealth and uHealth · 2020Trial
- Mobile applications, physical activity, and health promotion.BMC health services research · 2025Article
- Navigating the design of simulated exercising peers: insights from a participatory design study.Frontiers in digital health · 2025Article
- Preconception and Diabetes Information (PADI) App for Women with Pregestational Diabetes: a Feasibility and Acceptability Study.Journal of healthcare informatics research · 2021Article
- Factors related to the adoption and adherence of physical activity mobile applications by older people: a scoping review protocol.BMJ open · 2021Article
- Smartphone-Based Interventions for Physical Activity Promotion: Scoping Review of the Evidence Over the Last 10 Years.JMIR mHealth and uHealth · 2021Article
- Exercise and Physical Activity eHealth in COVID-19 Pandemic: A Cross-Sectional Study of Effects on Motivations, Behavior Change Mechanisms, and Behavior.Frontiers in psychology · 2021Article
- Adoption of Mobile Health Apps in Dietetic Practice: Case Study of Diyetkolik.JMIR mHealth and uHealth · 2020Article
- Current Developments in Digital Quantitative Volume Estimation for the Optimisation of Dietary Assessment.Nutrients · 2020Review
- Associations of Health App Use and Perceived Effectiveness in People With Cardiovascular Diseases and Diabetes: Population-Based Survey.JMIR mHealth and uHealth · 2019Article
- Assessing the Quality of Mobile Phone Apps for Weight Management: User-Centered Study With Employees From a Lebanese University.JMIR mHealth and uHealth · 2019Article
- Article
- Parents' Perspectives on the Theoretical Domains Framework Elements Needed in a Pediatric Health Behavior App: A Crowdsourced Social Validity Study.JMIR mHealth and uHealth · 2018Article
- Identifying Evidence-Informed Physical Activity Apps: Content Analysis.JMIR mHealth and uHealth · 2018Article
- How Mobile App Design Impacts User Responses to Mixed Self-Tracking Outcomes: Randomized Online Experiment to Explore the Role of Spatial Distance for Hedonic Editing.JMIR mHealth and uHealth · 2018Article
- Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPhysical activity apps are commonly used to increase levels of activity and health status. To date, the focus of research has been to determine the potential of apps to influence behavior, to ascertain the efficacy of a limited number of apps to change behavior, and to identify the characteristics of apps that users prefer.
objectiveThe purpose of this study was to identify the mechanisms by which the use of physical activity apps may influence the users' physical activity behavior.
methodsThis study used a cross-sectional survey of users of health-related physical activity apps during the past 6 months. An electronic survey was created in Qualtrics' Web-based survey software and deployed on Amazon Mechanical Turk. Individuals who had used at least one physical activity app in the past 6 months were eligible to respond. The final sample comprised 207 adults living in the United States. 86.0% (178/207) of respondents were between the ages of 26 and 54 years, with 51.2% (106/207) of respondents being female. Behavior change theory informed the creation of 20 survey items relating to the mechanisms of behavior change. Respondents also reported about engagement with the apps, app likeability, and physical activity behavior.
resultsRespondents reported that using a physical activity app in the past 6 months resulted in a change in their attitudes, beliefs, perceptions, and motivation. Engagement with the app (P<.001), frequency of app use (P=.03), and app price (P=.01) were related to the reported impact of the behavior change theory or mechanisms of change. The mechanisms of change were associated with self-reported physical activity behaviors (P<.001).
conclusionsThe findings from this study provide an overview of the mechanisms by which apps may impact behavior. App developers may wish to incorporate these mechanisms in an effort to increase impact. Practitioners should consider the extent to which behavior change theory is integrated into a particular app when they consider making recommendations to others wishing to increase levels of physical activity.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.