Optimizing a Mobile Health Platform for Sleep Promotion and Obesity Prevention in Children

Summary

The overall objective of this application is to develop a mobile health platform for the pediatric care setting to promote longer sleep duration for childhood obesity prevention.

Detailed Description

Insufficient sleep duration is highly prevalent in childhood and is associated with incident obesity, especially among middle school-aged children. Investigators therefore need to identify strategies to increase sleep duration among children for obesity prevention. The overall objective of this application is to develop a mobile health platform for the pediatric care setting to promote longer sleep duration for childhood obesity prevention. This is a single-site study being conducted at the Children's Hospital of Philadelphia (CHOP). Investigators will randomize 325 children, aged 8-12y, with a body mass index (BMI) between the 50th-95th percentile, and who sleep \<8.5 hours per night. Clinical measurements will be acquired at CHOP and sleep will be measured in the home setting. The Way to Health mobile platform will facilitate remote communication and data collection. A validated multi-channel sleep tracker will estimate sleep for 12-months (2-week run-in; 6-month intervention; ≈5.5-month follow-up). A randomized 24 factorial design will assess four components: sleep goal (fixed or modifiable), digital guidance (active or active with virtual study visit), parent incentive (inactive or active), and personalized feedback (inactive or active). The optimal component settings will have to meet the following criteria: increase average baseline sleep duration by ≥30 minutes for ≥75% of intervention weeks and for ≥50% of follow-up weeks. Fat mass will be measured at baseline, 6-, and 12-months using dual energy X-ray absorptiometry (DXA). Total energy intake and the timing and composition of meals will be measured using 24-hour dietary recalls at baseline, 6-, and 12-months. Sociodemographic data will be measured using self-report approaches (e.g., sex, race/ethnicity) and home addresses will be geocoded for geo-spatial analyses.

Eligibility Criteria

Interventions