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

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.

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.

A computerized random number generated by the Way to Health platform will assign children to 1 of 16 study conditions for a 6-month intervention period. The study conditions differ with respect to: sleep goal (fixed or modifiable), digital sleep guidance (active or active with virtual study visit), parent-directed incentive (inactive or active), and personalized feedback (inactive or active). Our design includes one constant: all participants need to self-monitor their sleep duration by wearing the sleep tracker to allow for daily capture of sleep duration and goal achievement status. The intervention period is therefore designed to test the effectiveness of 4 components, each with two levels, using a factorial design.

Investigators will be blinded, except the psychologist on the team who needs to train and direct the virtual study visit delivery for one of the intervention components.

Fixed guideline-based sleep goal, Digital sleep health messaging without virtual study visit consultation, Inactive caregiver-directed loss-framed incentive, Inactive supportive feedback.

Fixed guideline-based sleep goal, Digital sleep health messaging without virtual study visit consultation, Inactive caregiver-directed loss-framed incentive, Active supportive feedback.

Fixed guideline-based sleep goal, Digital sleep health messaging without virtual study visit consultation, Active caregiver-directed loss-framed incentive, Inactive supportive feedback.

Fixed guideline-based sleep goal, Digital sleep health messaging without virtual study visit consultation, Active caregiver-directed loss-framed incentive, Active supportive feedback.

Fixed guideline-based sleep goal, Digital sleep health messaging with virtual study visit consultation, Inactive caregiver-directed loss-framed incentive, Inactive supportive feedback.

Fixed guideline-based sleep goal, Digital sleep health messaging with virtual study visit consultation, Inactive caregiver-directed loss-framed incentive, Active supportive feedback.

Fixed guideline-based sleep goal, Digital sleep health messaging with virtual study visit consultation, Active caregiver-directed loss-framed incentive, Inactive supportive feedback.

Fixed guideline-based sleep goal, Digital sleep health messaging with virtual study visit consultation, Active caregiver-directed loss-framed incentive, Active supportive feedback.

Personalized sleep goal, Digital sleep health messaging without virtual study visit consultation, Inactive caregiver-directed loss-framed incentive, Inactive supportive feedback.

Personalized sleep goal, Digital sleep health messaging without virtual study visit consultation, Inactive caregiver-directed loss-framed incentive, Active supportive feedback.

Personalized sleep goal, Digital sleep health messaging without virtual study visit consultation, Active caregiver-directed loss-framed incentive, Inactive supportive feedback.

Personalized sleep goal, Digital sleep health messaging without virtual study visit consultation, Active caregiver-directed loss-framed incentive, Active supportive feedback.

Personalized sleep goal, Digital sleep health messaging with virtual study visit consultation, Inactive caregiver-directed loss-framed incentive, Inactive supportive feedback.

Personalized sleep goal, Digital sleep health messaging with virtual study visit consultation, Inactive caregiver-directed loss-framed incentive, Active supportive feedback.

Personalized sleep goal, Digital sleep health messaging with virtual study visit consultation, Active caregiver-directed loss-framed incentive, Inactive supportive feedback.

Core intervention, Sleep goal, Sleep guidance messaging, Caregiver-directed loss-framed incentive, Supportive feedback.

Investigators will determine if a fixed guideline-based goal (≥9 hours per night) is more efficacious for increasing sleep duration.

Investigators will determine if a personalized goal (≥9 hours per night, but can be lowered to a personalized level, capped at +30 minutes per night above baseline) is more efficacious for increasing sleep duration.

All participants will receive digital sleep health messaging. Messaging will focus on evidence-based sleep health recommendations, such as regulating evening electronics use, managing extracurricular activities, and setting consistent bedtime routines and sleep-wake schedules. This group will NOT have virtual psychological visits.

All participants will receive digital sleep health messaging. Messaging will focus on evidence-based sleep health recommendations, such as regulating evening electronics use, managing extracurricular activities, and setting consistent bedtime routines and sleep-wake schedules. The participants will be randomized to additionally receive virtual study visits where doctoral-level psychology trainees will be trained to implement evidence-based behavioral sleep health guidance.

Parents will receive a financial incentive when their child achieves their sleep goal. The incentive will be loss-framed; parents will receive an endowment of $10 at the start of each intervention week, in a virtual bank account; Investigators will deduct $2 each weeknight the sleep duration goal is not met; the funds remaining in the virtual account will be dispensed each Sunday. The weekly endowment-payment approach allows for fresh starts each week. The incentive will be directed at parents as a method to enhance engagement. Investigators will ask parents at baseline and at the end of each month to rate their perceived support in helping their child to meet their sleep duration goal.

Participants will receive a weekly performance summary message each Sunday during the intervention period, with supportive feedback included to motivate children to maintain their good performance in the week ahead, or to try and improve upon a weak or moderate performance in the week ahead. Investigators will ask children will complete an online survey each Sunday to measure how motivated they are to achieve their sleep goal in the week ahead.

The primary outcome for aims 1 and 3 is change in nighttime sleep duration (hours per night) on weeknights measured by a sleep tracker with high sensitivity and moderate specificity for measuring sleep.

Aim 2 primary outcome. Total body fat mass will be measured by DXA. Fat mass index (FMI, kg of fat divided by height in meters squared) will be calculated, and age and gender specific FMI Z-scores will be determined using U.S. specific FMI growth charts.

Change in sleep onset (time subject falls asleep). Weeknights and weekends will be measured separately.

Investigators will calculate "social jetlag" by subtracting the weekend night sleep midpoint from the weeknight sleep midpoint. Social jetlag provides an indication of the discrepancy between internal biological clocks and social requirements and has been linked to cardiometabolic risk.

Change in sleep efficiency (percentage of time spent asleep during overnight sleep periods). Weeknights and weekends will be measured separately.

Change in sleep onset latency (time to fall asleep). Weeknights and weekends will be measured separately.

Change in wake after sleep onset (time awake during overnight sleep periods). Weeknights and weekends will be measured separately.

Measured using the the Patient-Reported Outcomes Measurement Information System (PROMIS) item bank for pediatric sleep. This validated survey generates a sleep disturbance T-score based on items related to sleep onset, sleep continuity and sleep quality in the past week. The survey also generates a sleep-related impairment T-score based on items related to daytime sleepiness, cognition, affect and behavior, and daytime activities in the past week. Higher T-scores indicates poorer sleep quality. Participants will complete this survey at baseline and at the end of each month during the intervention and follow-up periods.

Trained Nutrition Core staff will measure heights and weights of participants. These data will be used to calculate body mass index (kg/m2).

Inclusion Criteria: Aged 8-12 years olds. Insufficient sleep duration (<8.5 hours per night). Body mass index (BMI) between the 50th and 95th percentile for age and sex. One child per family. Exclusion Criteria: Diagnosed with a chronic disease. Diagnosed with a behavioral health problem. Diagnosed with a condition that can impact sleep or growth. Diagnosed with a condition affecting physical growth and maturation or dietary intake. Children with a history of cancer, kidney, GI, musculoskeletal, or sleep disorders. Children who will transition to high-school during the study. Children using steroids/hormones. Children regularly taking medications

Steinberger J, Daniels SR, Hagberg N, Isasi CR, Kelly AS, Lloyd-Jones D, Pate RR, Pratt C, Shay CM, Towbin JA, Urbina E, Van Horn LV, Zachariah JP; American Heart Association Atherosclerosis, Hypertension, and Obesity in the Young Committee of the Council on Cardiovascular Disease in the Young; Council on Cardiovascular and Stroke Nursing; Council on Epidemiology and Prevention; Council on Functional Genomics and Translational Biology; and Stroke Council. Cardiovascular Health Promotion in Children: Challenges and Opportunities for 2020 and Beyond: A Scientific Statement From the American Heart Association. Circulation. 2016 Sep 20;134(12):e236-55. doi: 10.1161/CIR.0000000000000441. Epub 2016 Aug 11.

Daniels SR, Hassink SG; COMMITTEE ON NUTRITION. The Role of the Pediatrician in Primary Prevention of Obesity. Pediatrics. 2015 Jul;136(1):e275-92. doi: 10.1542/peds.2015-1558. Epub 2015 Jun 29.

Miller MA, Kruisbrink M, Wallace J, Ji C, Cappuccio FP. Sleep duration and incidence of obesity in infants, children, and adolescents: a systematic review and meta-analysis of prospective studies. Sleep. 2018 Apr 1;41(4). doi: 10.1093/sleep/zsy018.

Hatori M, Vollmers C, Zarrinpar A, DiTacchio L, Bushong EA, Gill S, Leblanc M, Chaix A, Joens M, Fitzpatrick JA, Ellisman MH, Panda S. Time-restricted feeding without reducing caloric intake prevents metabolic diseases in mice fed a high-fat diet. Cell Metab. 2012 Jun 6;15(6):848-60. doi: 10.1016/j.cmet.2012.04.019. Epub 2012 May 17.

Spaeth AM, Hawley NL, Raynor HA, Jelalian E, Greer A, Crouter SE, Coffman DL, Carskadon MA, Owens JA, Wing RR, Hart CN. Sleep, energy balance, and meal timing in school-aged children. Sleep Med. 2019 Aug;60:139-144. doi: 10.1016/j.sleep.2019.02.003. Epub 2019 Feb 16.

Honaker SM, Meltzer LJ. Sleep in pediatric primary care: A review of the literature. Sleep Med Rev. 2016 Feb;25:31-9. doi: 10.1016/j.smrv.2015.01.004. Epub 2015 Jan 24.

Wong CA, Miller VA, Murphy K, Small D, Ford CA, Willi SM, Feingold J, Morris A, Ha YP, Zhu J, Wang W, Patel MS. Effect of Financial Incentives on Glucose Monitoring Adherence and Glycemic Control Among Adolescents and Young Adults With Type 1 Diabetes: A Randomized Clinical Trial. JAMA Pediatr. 2017 Dec 1;171(12):1176-1183. doi: 10.1001/jamapediatrics.2017.3233.

Wheaton AG, Jones SE, Cooper AC, Croft JB. Short Sleep Duration Among Middle School and High School Students - United States, 2015. MMWR Morb Mortal Wkly Rep. 2018 Jan 26;67(3):85-90. doi: 10.15585/mmwr.mm6703a1.

Mitchell JA, Morales KH, Williamson AA, Huffnagle N, Eck C, Jawahar A, Juste L, Fiks AG, Zemel BS, Dinges DF. Engineering a mobile platform to promote sleep in the pediatric primary care setting. Sleep Adv. 2021 Apr 15;2(1):zpab006. doi: 10.1093/sleepadvances/zpab006. eCollection 2021.

Mitchell JA, Morales KH, Williamson AA, Huffnagle N, Ludwick A, Grant SFA, Dinges DF, Zemel BA. Changes in Sleep Duration and Timing During the Middle-to-High School Transition. J Adolesc Health. 2020 Dec;67(6):829-836. doi: 10.1016/j.jadohealth.2020.04.024. Epub 2020 Jun 20.

Mayne SL, Morales KH, Williamson AA, Grant SFA, Fiks AG, Basner M, Dinges DF, Zemel BS, Mitchell JA. Associations of the residential built environment with adolescent sleep outcomes. Sleep. 2021 Jun 11;44(6):zsaa276. doi: 10.1093/sleep/zsaa276.

Mitchell JA, Rodriguez D, Schmitz KH, Audrain-McGovern J. Sleep duration and adolescent obesity. Pediatrics. 2013 May;131(5):e1428-34. doi: 10.1542/peds.2012-2368. Epub 2013 Apr 8.

Paruthi S, Brooks LJ, D'Ambrosio C, Hall WA, Kotagal S, Lloyd RM, Malow BA, Maski K, Nichols C, Quan SF, Rosen CL, Troester MM, Wise MS. Consensus Statement of the American Academy of Sleep Medicine on the Recommended Amount of Sleep for Healthy Children: Methodology and Discussion. J Clin Sleep Med. 2016 Nov 15;12(11):1549-1561. doi: 10.5664/jcsm.6288.

Allen SL, Howlett MD, Coulombe JA, Corkum PV. ABCs of SLEEPING: A review of the evidence behind pediatric sleep practice recommendations. Sleep Med Rev. 2016 Oct;29:1-14. doi: 10.1016/j.smrv.2015.08.006. Epub 2015 Sep 1.

Meltzer LJ, Williamson AA, Mindell JA. Pediatric sleep health: It matters, and so does how we define it. Sleep Med Rev. 2021 Jun;57:101425. doi: 10.1016/j.smrv.2021.101425. Epub 2021 Jan 19.

Mindell JA, Sedmak R, Boyle JT, Butler R, Williamson AA. Sleep Well!: A Pilot Study of an Education Campaign to Improve Sleep of Socioeconomically Disadvantaged Children. J Clin Sleep Med. 2016 Dec 15;12(12):1593-1599. doi: 10.5664/jcsm.6338.

Njoroge WFM, Williamson AA, Mautone JA, Robins PM, Benton TD. Competencies and Training Guidelines for Behavioral Health Providers in Pediatric Primary Care. Child Adolesc Psychiatr Clin N Am. 2017 Oct;26(4):717-731. doi: 10.1016/j.chc.2017.06.002.

Corkum P, Lingley-Pottie P, Davidson F, McGrath P, Chambers CT, Mullane J, Laredo S, Woodford K, Weiss SK. Better Nights/Better Days-Distance Intervention for Insomnia in School-Aged Children With/Without ADHD: A Randomized Controlled Trial. J Pediatr Psychol. 2016 Jul;41(6):701-13. doi: 10.1093/jpepsy/jsw031. Epub 2016 May 16.

Quach J, Hiscock H, Ukoumunne OC, Wake M. A brief sleep intervention improves outcomes in the school entry year: a randomized controlled trial. Pediatrics. 2011 Oct;128(4):692-701. doi: 10.1542/peds.2011-0409. Epub 2011 Sep 2.

Chinoy ED, Cuellar JA, Huwa KE, Jameson JT, Watson CH, Bessman SC, Hirsch DA, Cooper AD, Drummond SPA, Markwald RR. Performance of seven consumer sleep-tracking devices compared with polysomnography. Sleep. 2021 May 14;44(5):zsaa291. doi: 10.1093/sleep/zsaa291.

de Zambotti M, Baker FC, Willoughby AR, Godino JG, Wing D, Patrick K, Colrain IM. Measures of sleep and cardiac functioning during sleep using a multi-sensory commercially-available wristband in adolescents. Physiol Behav. 2016 May 1;158:143-9. doi: 10.1016/j.physbeh.2016.03.006. Epub 2016 Mar 9.

Godino JG, Wing D, de Zambotti M, Baker FC, Bagot K, Inkelis S, Pautz C, Higgins M, Nichols J, Brumback T, Chevance G, Colrain IM, Patrick K, Tapert SF. Performance of a commercial multi-sensor wearable (Fitbit Charge HR) in measuring physical activity and sleep in healthy children. PLoS One. 2020 Sep 4;15(9):e0237719. doi: 10.1371/journal.pone.0237719. eCollection 2020.

Forrest CB, Meltzer LJ, Marcus CL, de la Motte A, Kratchman A, Buysse DJ, Pilkonis PA, Becker BD, Bevans KB. Development and validation of the PROMIS Pediatric Sleep Disturbance and Sleep-Related Impairment item banks. Sleep. 2018 Jun 1;41(6). doi: 10.1093/sleep/zsy054.

Mathew GM, Hale L, Chang AM. Social jetlag, eating behaviours and BMI among adolescents in the USA. Br J Nutr. 2020 Nov 14;124(9):979-987. doi: 10.1017/S0007114520001804. Epub 2020 May 28.

Cespedes Feliciano EM, Rifas-Shiman SL, Quante M, Redline S, Oken E, Taveras EM. Chronotype, Social Jet Lag, and Cardiometabolic Risk Factors in Early Adolescence. JAMA Pediatr. 2019 Nov 1;173(11):1049-1057. doi: 10.1001/jamapediatrics.2019.3089.

Weber DR, Moore RH, Leonard MB, Zemel BS. Fat and lean BMI reference curves in children and adolescents and their utility in identifying excess adiposity compared with BMI and percentage body fat. Am J Clin Nutr. 2013 Jul;98(1):49-56. doi: 10.3945/ajcn.112.053611. Epub 2013 May 22.