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Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
Published on: March 7, 2019
Does personalization improve the effectiveness of app-based mobile health interventions on physical activity? A
Victoria E Hill1, Kaileigh A Byrne1, Delaini Daughenbaugh1
1Department of Psychology, Clemson University, Clemson, SC, USA.
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.