Does personalization improve the effectiveness of app-based mobile health interventions on physical activity? A systematic review and meta-analysis
Bibliographic Data
| ID | 21579984 |
|---|---|
| Authors | Victoria E Hill (Clemson University), Kaileigh A Byrne (0000-0002-3935-3108, Clemson University, corresponding author), Delaini Daughenbaugh (Clemson University), Matthew Caymol (Clemson University) |
| Year | 2026 |
| Pages | 1-20 |
| Publication date | 2026-05-24 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Psychology & Health (JOURNAL) |
| Journal identifiers | ISSN: 0887-0446 • E-ISSN: 1476-8321 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/08870446.2026.2677085 |
| PMID | 42178731 |
| OpenAlex | W7162344078 |
| Language | EN |
| References cited | 69 |
Objective The primary study aim is to evaluate the impact of app-based mobile Health (mHealth) interventions on physical activity in healthy populations and examine whether personalisation moderates their effectiveness. The secondary aim is to explore the potential moderating role of social features.Methods and measures A systematic review and meta-analysis examined the effect of mHealth apps on physical activity, measured by step count, moderate-to-vigorous physical activity (MVPA), or total activity. A total of 16,257 articles were identified via five databases in November 2023. After screening, 20 studies (n = 2,159 participants) were included with 23 total comparisons between postintervention and control groups.Results Random effects model results for all eligible studies showed a small-to-medium effect of mHealth apps in increasing physical activity compared to controls (g = 0.42, 95% CI [0.1540, 0.6874]; p = 0.002). Personalisation p = 0.22), social features (p = 0.12), and intervention duration p = 0.99) did not predict physical activity. However, a sensitivity analysis for step count only showed a negative effect of social features on step count (β=-0.50, p = 0.02).Conclusion While mHealth interventions increase physical activity, personalisation features do not significantly influence their effectiveness. Additional research is needed to elucidate the impact of mHealth social features and potential individual difference factors on intervention effectiveness
Behavior change methods · mHealth · Mobile device · Mobile technology · Personalization · Physical activity · Psychological intervention · Digital Mental Health Interventions · Mobile Health and mHealth Applications · Physical Activity and Health
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| Highly cited | No |
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