Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Dec 12, 2019
Date Accepted: Feb 26, 2020
Developing Empirical Decision Points to Improve the Timing of Adaptive Digital Health Physical Activity Interventions in Youth: A Survival Analysis
ABSTRACT
Background:
Background:
Current digital health interventions primarily utilize interventionist-defined rules to guide the timing of intervention delivery. As new temporally dense datasets become available, it is possible to make decisions about intervention timing empirically.
Objective:
Objective:
The purpose of this study was to explore the timing of physical activity in youth to inform decision points (e.g., timing of support) for future digital physical activity interventions.
Methods:
Methods:
This study was comprised of 113 adolescents between the ages of 13-18 (M = 14.64, SD = 1.48) who wore an accelerometer for 20 days. Multilevel survival analyses were used to estimate the most likely time of day (via odds ratios and hazard probabilities) when adolescents accumulated their average physical activity. Interacting effects of physical activity timing and moderating variables were calculated by entering predictors, such as gender, sports participation, school day, into the model as main effects and tested for interactions with time of day to determine conditional main effects of these predictors.
Results:
Results:
On average, the likelihood that a participant would accumulate a typical amount of MVPA increased and peaked between the hours of 6pm-8pm before decreasing sharply after 9pm. Hazard and survival probabilities suggest that optimal decision points for digital physical activity programs could occur between 5pm and 8pm.
Conclusions:
Conclusions:
Overall, findings from this study support the idea that the timing of physical activity can be empirically-identified and these markers may be useful as intervention triggers.
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Copyright
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