ArticleDigital health
A personalized mobile app for physical activity: An experimental mixed-methods study.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Impact of ChatGPT-assisted personalized learning on teaching acute abdomen to undergraduate medical students: A randomized crossover study.Pakistan journal of medical sciences · 2026Article
- Sleep as an Effect Modifier for Physical Activity Intervention Efficacy: Secondary Analysis of Data from Two Randomized Controlled Trials.International journal of behavioral medicine · 2026Article
- Automatically tailored exercise app training is feasible, usable, and safe for people with paraplegia: a parallel mixed methods pilot study.BMC sports science, medicine & rehabilitation · 2026Article
- The role of smartphone-based functional metrics in pain medicine.Interventional pain medicine · 2026Article
- Designing interfaces for digital physical ability self-assessment: a user-centered iterative approach.Frontiers in digital health · 2026Article
- College Community-Based Physical Activity Support at a Public University During the COVID-19 Pandemic: Retrospective Longitudinal Analysis of Intra- Versus Interpersonal Components for Uptake and Outcome Association.JMIR mHealth and uHealth · 2025Article
- User Experience With a Personalized mHealth Service for Physical Activity Promotion in University Students: Mixed Methods Study.JMIR formative research · 2025Article
- MoodMover: Development and usability testing of an mHealth physical activity intervention for depression.Digital healthArticle
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: To investigate the feasibility of the be.well app and its personalization approach which regularly considers users' preferences, amongst university students. Methods: We conducted a mixed-methods, pre-post experiment, where participants used the app for 2 months. Eligibility criteria included: age 18-34 years; owning an iPhone with Internet access; and fluency in English. Usability was assessed by a validated questionnaire; engagement metrics were reported. Changes in physical activity were assessed by comparing the difference in daily step count between baseline and 2 months. Interviews were conducted to assess acceptability; thematic analysis was conducted. Results: Twenty-three participants were enrolled in the study (mean age = 21.9 years, 71.4% women). The mean usability score was 5.6 ± 0.8 out of 7. The median daily engagement time was 2 minutes. Eighteen out of 23 participants used the app in the last month of the study. Qualitative data revealed that people liked the personalized activity suggestion feature as it was actionable and promoted user autonomy. Some users also expressed privacy concerns if they had to provide a lot of personal data to receive highly personalized features. Daily step count increased after 2 months of the intervention (median difference = 1953 steps/day, Conclusions: Incorporating users' preferences in personalized advice provided by a physical activity app was considered feasible and acceptable, with preliminary support for its positive effects on daily step count. Future randomized studies with longer follow up are warranted to determine the effectiveness of personalized mobile apps in promoting physical activity.
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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.