Title

Engineering a Mobile Platform to Promote Sleep in the Pediatric Primary Care Setting.

Year of Publication

2020

Date Published

2020 Nov 07

Abstract

<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>

DOI

10.1101/2020.11.06.20223719

Alternate Title

medRxiv

PMID

33173886

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