BACKGROUND
mHealth approaches are gaining popularity to address low levels of physical activity (PA).
OBJECTIVE
This study aimed to: (1) develop an mHealth suite, combining PA wearables and an interactive smartphone application (App) supported by a web-based data management system, (2) determine the validity of the wearables in measuring steps per day and floor-count, and (3) assess feasibility and effects of a 6-week team challenge intervention.
METHODS
Staff and students from a public university were recruited between 2015 and 2016. In Phase 1, every participant was requested to wear a Fitbit tracker (Charge™ or Charge HR™) and an ActiGraph™ for 7 days to measure daily step counts under free-living condition. They were also asked to climb 4 bouts of floors in an indoor stairswell to measure floor-counts. Steps per day and floor-counts estimated by Fitbit™ were compared against ActiGraph and direct observation, respectively. In Phase 2, participants were allocated to control or intervention group and received a Fitbit tracker synced to the Fitbit App. Further, the intervention participants were randomized to 4 teams and used the developed mHealth suite. Teams competed in 6 weekly (Monday - Friday) real-time challenges. A valid day was defined as having accumulated ≥1,500 steps per day. Outcomes were: (i) adherence to wearing Fitbit (i.e. number of days in which all participants in each group was classified as valid users aggregated across entire study period), (ii) mean proportion of valid participants over the study period, and (iii) the effects of intervention on steps and floor-counts determined using multiple linear regressions models and generalized estimating equations (GEE) for longitudinal data analysis.
RESULTS
In Phase one, 32/40 (steps) and 40/40 (floors) participants provided valid data. The Fitbit trackers demonstrated a high to very high correlation (steps: Spearman Rho=0.89, P < .001, floors: Spearman Rho=0.98, P < .001), respectively. The trackers over-estimated step-counts in free-living condition (median absolute error: 17%) but accurately estimated floor-counts. In Phase two, 20 participants each were allocated to intervention and control. 24 completers (i.e. provided complete covariates and valid PA data) were included in the analyses. Multiple linear regressions revealed 15.9% higher average steps/day (95% CI: -8.9, 47.6, P= .21) and 39.4% higher average floors/day (95% CI: 2.4, 89.7, P= .04) in the intervention group during the final two intervention weeks. GEE results indicated no significant interaction effects between groups and intervention week for weekly step counts, whereas a significant effect (P< .001) was observed for weekly floor counts.
CONCLUSIONS
The consumer wearables integrated in our mHealth suite provided acceptable validity in estimating stepping and stairs climbing activities. The mHealth suite was feasible for implementing real-time team-challenge interventions. Compared to the controls, the intervention participants performed more stairs climbing which could be introduced as an additional PA promotion target in the context of mHealth strategies. Methodologically rigorous studies with larger sample-size and long-term follow-up are warranted to strengthen the evidence for the proposed mHealth strategy.
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