JMIR Form Res. 2026 May 5;10:e75133. doi: 10.2196/75133.
ABSTRACT
BACKGROUND: Wearable activity trackers are useful tools to track and monitor physical activity (PA), especially considering their use in free-living environments. Users often see moderate improvements in step count, but consistent increases at various intensities of PA are inconclusive. While wearable research is growing, no known studies specifically examine the relationship between how the use of self-selected social features on wearables affects PA and exercise self-efficacy.
OBJECTIVE: This study aims to compare weekly PA, approximating moderate-to-vigorous intensity, of adults from the New York City metropolitan area assigned to either use or not use social engagement PA features on their device. Exercise self-efficacy was also measured. Additionally, a preliminary examination into the use of 3 different social features was conducted to inform where controlled parameters on feature use may be needed in future work.
METHODS: The researchers conducted a real-world pilot study by recruiting wearable users aged 18 years and older in the New York City area to wear their devices in free-living environments. After consent, participants were randomized into 1 of 2 conditions: the condition that involved use of the social engagement PA features or the condition that did not for 8 weeks. Participants submitted objective data from their device and completed a self-efficacy measure at baseline, week 4, and week 8. Those in the intervention group also answered questions about which social feature they used the most throughout the study.
RESULTS: Data from 123 participants were analyzed using mixed methods analysis. Principal findings included no difference between wearable social feature users and nonusers in weekly PA (P=.55) or exercise self-efficacy (P=.47). There was an overall effect of time across the repeated measures on PA (P=.006) with an average increase of 72 (SD 3) minutes. Secondary findings highlight the need to control for the use of only a single social feature to identify more concrete effects. An effect of time was found across the repeated measures (P=.01) in the intervention group, showing an increase of 49 to 126 minutes of PA, depending on the feature used most. The mixed methods analysis also found that exercise self-efficacy did not significantly change based on which social feature was used most (P=.24).
CONCLUSIONS: Consistent with other literature, this pilot study demonstrates that using wearables can lead to increases in PA and that sharing one’s PA data with others may amplify the effect. However, the novelty of this study is that although carefully implied, specific social features on a wearable may have a greater effect than others. This study identified the need for further investigation into which features may be more effective. With the increased prevalence of device ownership, knowing if certain social features lead to greater increases in PA may help those encouraging PA behavior change.
PMID:42085670 | DOI:10.2196/75133
