| dc.description.abstract | 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 delivery and timing empirically. 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. 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. Using a special case of logistic regression, 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. Additionally, odds ratios for the interacting effects of physical activity timing and moderating variables were calculated by entering predictors, such as gender, Body Mass Index (BMI), sports participation, school day, self-efficacy, social support for exercise, and motivation, into the model as main effects and tested for interactions with time of day to determine conditional main effects of these predictors. On average, the likelihood that a participant would accumulate their own average MVPA increased and peaked between the hours of 6pm-8pm before decreasing sharply after 9pm. There were differences in the timing of exercise for boys, adolescents involved in sports, on non-school days, individuals with lower physical activity self-efficacy, and participants with lower autonomous motivation. Hazard and survival probabilities suggest that optimal decision points for digital physical activity programs should occur between 5pm and 8pm. Overall, findings from this study support the idea that the timing of physical activity can be empirically-identified to determine when users are receptive to exercise and potentially used as markers to signal intervention delivery for JITAIs. | |
