Does parental and adolescent participation in an e-health lifestyle modification intervention improve weight outcomes?

Abstract

BackgroundFew studies have evaluated the effect of adherence to a lifestyle intervention on adolescent health outcomes. The objective of this study was to determine whether adolescent and parental adherence to components of an e-health intervention resulted in change in adolescent body mass index (BMI) and waist circumference (WC) z-scores in a sample of overweight/obese adolescents.MethodsIn total, 159 overweight/obese adolescents and their parents participated in an 8-month e-health lifestyle intervention. Each week, adolescents and their parents were asked to login to their respective website and to monitor their dietary, physical activity, and sedentary behaviours. We examined participation (percentage of webpages viewed [adolescents]; number of weeks logged in [parents]) and self-monitoring (number of weeks behaviors were tracked) rates. Linear mixed models and multiple regressions were used to examine change in adolescent BMI and WC z-scores and predictors of adolescent participation and self-monitoring, respectively.ResultsAdolescents and parents completed 28% and 23%, respectively, of the online component of the intervention. Higher adolescent participation rate was associated with a decrease in the slope of BMI z-score but not with change in WC z-score. No association was found between self-monitoring rate and change in adolescent BMI or WC z-scores. Parent participation was not found to moderate the relationship between adolescent participation and weight outcomes.ConclusionsDeveloping strategies for engaging and promoting supportive interactions between adolescents and parents are needed in the e-health context. Findings demonstrate that improving adolescents’ adherence to e-health lifestyle intervention can effectively alter the weight trajectory of overweight/obese adolescents.

Lessons learned from a blended telephone/e-health platform for caregivers in promoting physical activity and nutrition in children with a mobility disability

“…While this is the first known study targeting parents of children with a mobility disability, a small but growing number of studies have been published examining feasibility and preliminary behavior change outcomes among parents with children with other conditions including cancer, mental health conditions, substance abuse, and chronic kidney disease. [38][39][40][41][42] In many of these studies, parents reported acceptability of the web-based interventions and many noted they found the material helpful, but none have reported significant change in parental or child behavior. This underscores the need to find digital interventions that are beneficial in providing resources and supporting engagement, while balancing the time constraints and mental fatigue experienced by caregivers.…”

A cluster randomised controlled trial of a sugar-sweetened beverage intervention in secondary schools: Pilot study protocol

“…The ACAES has been validated in a sample of 224 students aged between nine and 16 years from the Hunter region in NSW, reporting validity coefficients of 0.21 and 0.24 for energy and sugar respectively when compared with assisted food records (Watson et al, 2009). The ACAES will be Parents will receive six fortnightly notifications in the second term via the school's electronic communication channel (Head et al, 2013;Sharifi et al, 2013;Tu et al, 2017). The notifications will provide advice on reducing SSB consumption and availability in the home environment, suggestions of healthier drink alternatives and role modelling (Denney-Wilson et al, 2009;Wold, 2009).…”

Mobile Health Apps in Pediatric Obesity Treatment: Process Outcomes From a Feasibility Study of a Multicomponent Intervention

“…Despite improved technologies and access to mHealth tools for the purpose of monitoring health status and implementing interventions for health behavior change [ 22 , 23 ], challenges with adherence and exposure remain [ 24 , 25 ]. Planned exposure, impact, and potential outcomes are altered by participants’ interaction with study tools and technology [ 13 , 15 , 24 ].…”

“…mHealth tools provide adjunctive options to standard treatment approaches and can be beneficial for patients at home and their clinical team. However, engagement with devices and apps can act as a barrier to treatment [ 13 , 15 , 22 ].…”