OBJECTIVE: Determine the optimal combination of digital health intervention component settings that increase average sleep duration by ≥30 minutes per weeknight.

METHODS: Optimization trial using a 2 factorial design. The trial included 2 week run-in, 7 week intervention, and 2 week follow-up periods. Typically developing children aged 9-12y, with weeknight sleep duration <8.5 hours were enrolled (N=97). All received sleep monitoring and performance feedback. The five candidate intervention components ( ) were: 1) sleep goal ( ); 2) screen time reduction messaging ( ); 3) daily routine establishing messaging ( ); 4) child-directed loss-framed financial incentive ( ); and 5) caregiver-directed loss-framed financial incentive ( ). The primary outcome was weeknight sleep duration (hours per night). The optimization criterion was: ≥30 minutes average increase in sleep duration on weeknights.

RESULTS: Average baseline sleep duration was 7.7 hours per night. The highest ranked combination included the core intervention plus the following intervention components: sleep goal (either setting was effective), caregiver-directed loss-framed incentive, messaging to reduce screen time, and messaging to establish daily routines. This combination increased weeknight sleep duration by an average of 39.6 (95% CI: 36.0, 43.1) minutes during the intervention period and by 33.2 (95% CI: 28.9, 37.4) minutes during the follow-up period.

CONCLUSIONS: Optimal combinations of digital health intervention component settings were identified that effectively increased weeknight sleep duration. This could be a valuable remote patient monitoring approach to treat insufficient sleep in the pediatric setting.

<p><strong>BACKGROUND: </strong>Pediatricians lack tools to support families at home for the promotion of childhood sleep. We are using the Multiphase Optimization Strategy (MOST) framework to guide the development of a mobile health platform for childhood sleep promotion.</p>

<p><strong>PURPOSE: </strong>Under the preparation phase of the MOST framework, to demonstrate feasibility of a mobile health platform towards treating children with insufficient sleep.</p>

<p><strong>METHODS: </strong>Children aged 10-12y were enrolled (Study #1: N=30; Study #2: N=43). Participants wore a sleep tracker to measure sleep duration. Data were retrieved by a mobile health platform, programmed to send introductory messages during run-in (2 weeks) and goal achievement messages during intervention (7 weeks) periods. In study #1, participants were randomized to control, gain-framed incentive or loss-framed incentive arms. In study #2, participants were randomized to control, loss-framed incentive, normative feedback or loss-framed incentive plus normative feedback arms.</p>

<p><strong>RESULTS: </strong>In study #1, 1,514 nights of data were captured (69%) and sleep duration during the intervention was higher by an average of 21 (95% CI: -8, 51) and 34 (95% CI: 7, 61) minutes per night for the gain-framed and loss-framed arms, respectively, compared to controls. In study #2, 2,689 nights of data were captured (81%), with no major differences in average sleep duration between the control and the loss-framed or normative feedback arms.</p>

<p><strong>CONCLUSION: </strong>We have developed and deployed a mobile health platform that can capture sleep data and remotely communicate with families. Promising candidate intervention components will be further investigated under the optimization phase of the MOST framework.</p>

<p><strong>Study Objectives: </strong>Pediatricians lack tools to support families at home for the promotion of childhood sleep. We are using the Multiphase Optimization Strategy (MOST) framework to guide the development of a mobile health platform for childhood sleep promotion. The objective of this study is to demonstrate feasibility of a mobile health platform towards treating children with insufficient sleep.</p>

<p><strong>Methods: </strong>Children aged 10-12 years were enrolled (Study #1: = 30; Study #2: = 43). Participants wore a sleep tracker to measure sleep duration. Data were retrieved by a mobile health platform, programmed to send introductory messages during run-in (2 weeks) and goal achievement messages during intervention (7 weeks) periods. In study #1, participants were randomized to control, gain-framed incentive or loss-framed incentive arms. In study #2, participants were randomized to control, loss-framed incentive, normative feedback or loss-framed incentive plus normative feedback arms.</p>

<p><strong>Results: </strong>In study #1, 1514 nights of data were captured (69%) and sleep duration during the intervention was higher by an average of 21 (95% CI: -8, 51) and 34 (95% CI: 7, 61) minutes per night for the gain-framed and loss-framed arms, respectively, compared to controls. In study #2, 2,689 nights of data were captured (81%), with no major differences in average sleep duration between the control and the loss-framed or normative feedback arms.</p>

<p><strong>Conclusions: </strong>We have developed and deployed a mobile health platform that can capture sleep data and remotely communicate with families. Promising candidate intervention components will be further investigated under the of the MOST framework.</p>

<p><strong>Clinical Trials: </strong>Both studies included in this manuscript were registered at clinicaltrials.gov:-Study #1: NCT03263338-Study #2: NCT03426644.</p>