Exergaming for Health: A Randomized Study of Community-Based Exergaming Curriculum in Pediatric Weight Management

Christison, Amy L.; Evans, Tyler A.; Bleess, Brandon B.; Wang, Huaping; Aldag, Jean C.; Binns, Helen J.

doi:10.1089/g4h.2015.0097

Cited by 26 publications

(51 citation statements)

References 34 publications

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“…Three interventions showed no promise; 2 of these were targeting overweight and obesity, 1 was the exergaming plus classroom curriculum, and the other was motivational interviewing delivered via one-way text messaging [ 68 , 69 ]. Neither lead to improvements in behavioral outcomes (screen time, physical activity, and diet) or the primary outcome (BMI Z-scores) at 6 and 3 months, respectively.…”

Section: Resultsmentioning

confidence: 99%

Digital Behavior Change Interventions for Younger Children With Chronic Health Conditions: Systematic Review

Brigden¹,

Anderson²,

Linney³

et al. 2020

J Med Internet Res

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Background The prevalence of chronic health conditions in childhood is increasing, and behavioral interventions can support the management of these conditions. Compared with face-to-face treatment, the use of digital interventions may be more cost-effective, appealing, and accessible, but there has been inadequate attention to their use with younger populations (children aged 5-12 years). Objective This systematic review aims to (1) identify effective digital interventions, (2) report the characteristics of promising interventions, and (3) describe the user’s experience of the digital intervention. Methods A total of 4 databases were searched (Excerpta Medica Database [EMBASE], PsycINFO, Medical Literature Analysis and Retrieval System Online [MEDLINE], and the Cochrane Library) between January 2014 and January 2019. The inclusion criteria for studies were as follows: (1) children aged between 5 and 12 years, (2) interventions for behavior change, (3) randomized controlled trials, (4) digital interventions, and (5) chronic health conditions. Two researchers independently double reviewed papers to assess eligibility, extract data, and assess quality. Results Searches run in the databases identified 2643 papers. We identified 17 eligible interventions. The most promising interventions (having a beneficial effect and low risk of bias) were 3 targeting overweight or obesity, using exergaming or social media, and 2 for anxiety, using web-based cognitive behavioral therapy (CBT). Characteristics of promising interventions included gaming features, therapist support, and parental involvement. Most were purely behavioral interventions (rather than CBT or third wave), typically using the behavior change techniques (BCTs) feedback and monitoring, shaping knowledge, repetition and substitution, and reward. Three papers included qualitative data on the user’s experience. We developed the following themes: parental involvement, connection with a health professional is important for engagement, technological affordances and barriers, and child-centered design. Conclusions Of the 17 eligible interventions, digital interventions for anxiety and overweight or obesity had the greatest promise. Using qualitative methods during digital intervention development and evaluation may lead to more meaningful, usable, feasible, and engaging interventions, especially for this underresearched younger population. The following characteristics could be considered when developing digital interventions for younger children: involvement of parents, gaming features, additional therapist support, behavioral (rather than cognitive) approaches, and particular BCTs (feedback and monitoring, shaping knowledge, repetition and substitution, and reward). This review suggests a model for improving the conceptualization and reporting of behavioral interventions involving children and parents.

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Section: Resultsmentioning

confidence: 99%

Digital Behavior Change Interventions for Younger Children With Chronic Health Conditions: Systematic Review

Brigden¹,

Anderson²,

Linney³

et al. 2020

J Med Internet Res

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“…We reviewed 38 distinct interventions across 69 published articles for the childhood developmental stage . We classified 37% of these as universal prevention, 26% as selective, and the remaining 37% as indicated.…”

Section: Resultsmentioning

confidence: 99%

A developmental cascade perspective of paediatric obesity: A systematic review of preventive interventions from infancy through late adolescence

et al. 2019

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The goals of this systematic review were to identify and describe paediatric obesity prevention interventions from infancy to late adolescence and to provide recommendations for future intervention research in light of a recently proposed developmental cascade (DC) model of paediatric obesity. We conducted an electronic search of randomized controlled trials with a minimum 6-month postintervention follow-up published between 1995 and 2019. We included 74 interventions: prenatal/infancy (n = 4), early childhood (n = 11), childhood (n = 38), early to mid-adolescence (n = 18), and late adolescence (n = 3). Infancy and early childhood trials targeted early feeding and positive parenting skills. Half of the childhood and adolescence trials were school based and used universal prevention strategies; those classified as selective or indicated prevention tended to involve the family for more intensive lifestyle modification. Less than 10% of studies followed participants over long periods of time (greater than or equal to 5 years), and only 16% and 31% of studies assessed intervention mediators and moderators, respectively. We recommend that future interventions focus on early prevention, assess long-term intervention effects, use a standardized taxonomy for defining intervention behavioural strategies, assess underlying mechanisms of action and intervention moderators, target parent and family management strategies across development, and increase scientific equity. We also provide specific recommendations regarding intervention targets for each developmental stage. K E Y W O R D Scascade, development, paediatric obesity, prevention

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“…There was variability in the overall quality scores of the different studies, with a range between 1 (Fernández-Rosado, 2013) [65] and 10 (Staiano, 2017) [61] between the lowest and highest scoring studies. Eleven studies [21,31,36,38,39,42,59,60,[63][64][65] scored below 8, and five studies [37,40,58,61,62] scored greater than or equal to 8 points.…”

Section: Resultsmentioning

confidence: 99%

“…Only three discrepancies between the reviewers occurred. In the case of the assessment of the studies by Maddison et al (2011) [37] and Christison et al (2016), the discrepancies between the two reviewers in the dimension "withdrawals and dropouts" affected the score, so that it was agreed to use the numerical mean between the two quantitative scores and the qualitative rate for each rate was reported. In the case of the last discrepancy regarding Trost et al study (2013) study in the dimension "confounding", it did not affect the score or the qualitative rate of the dimension.…”

Section: Assessment Of Methodological Qualitymentioning

confidence: 99%

Impact of active video games on body mass index in children and adolescents: Systematic review and meta-analysis evaluating the quality of primary studies

Hernandez

Paz-Zulueta

Parás‐Bravo

et al. 2018

Revue d'Épidémiologie et de Santé Publique

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Objective: To study the impact of active video games on Body Mass Index (BMI) in children and adolescents. Design and Methods: A systematic review and meta-analysis. Data were pooled in meta-analysis using the method of random effects or fixed effects, as appropriate, after examination of statistical heterogeneity. Data sources and eligibility criteria for selecting studies. A comprehensive literature research was conducted in Medline (PubMed), ISI web of Knowledge, and SCOPUS up to April 2018, in relation to clinical trials (both controlled and non-controlled) in children and adolescents, whose intervention was based on active video games. Results: The overall intragroup effect of the intervention based on active video games was in favor of the intervention, reaching statistical significance using the fixed effects model: (standardized mean difference (SMD) = −0.138; 95% CI (−0.237 to −0.038), p = 0.007 and was of borderline statistical significance in the random effects model: SMD= −0.191; 95% CI (−0.386 to 0.003), p = 0.053. The individual results of the determinations of the 15 included studies for this analysis showed a high heterogeneity among them (I 2 = 82.91%). When the intervention was applied to children and adolescents with greater than or equal to 85 (overweight or obese) BMI percentile showed a greater effect in favor of the active video games: SMD= −0.483, p = 0.012. The overall intra-group effect in the control group was close to zero (SMD = 0.087). With respect to the non-standardized mean difference (MD) between groups, it was also in favor of active video games for both BMI (Kg/m 2 ): DM = −0.317, 95% CI (−0.442 to −0.193), p = < 0.001 and BMI z-score: DM = −0.077, 95% CI (−0.139 to −0.016), p = 0.013. Conclusions: Our meta-analysis show a statistically significant effect in favor of using active video games on BMI in children and adolescents. The clinical relevance of this positive effect must be evaluated.has undergone a radical change with the arrival of a new generation of video games, active video games, which involve physical activity since they allow players to interact physically, through their body movements (arms, legs, or the whole body), with the virtual reality that appears on screen through different devices.Individual primary studies and subsequent meta-analyses have focused on the effects of active video games on the promotion of physical activity [3][4][5][6][7][8], energy expenditure , oxygen volume consumption [9,12,15,16,[27][28][29], and heart rate [9,14,15,17,18,[27][28][29][30][31][32]. These studies have shown an increase in heart rate and an increase in oxygen consumption. This energy consumption is statistically significantly higher compared to non-active video games and sedentary activities, despite the variability of the types of active video games, as well as the time spent playing them [5,7,19,[22][23][24][25][26]33].Regarding the effect of active video games on body mass index (BMI), various primary studies [21,31,[33][34][35][36][37][38][39][40][41] have analyzed...

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Exergaming for Health: A Randomized Study of Community-Based Exergaming Curriculum in Pediatric Weight Management

Cited by 26 publications

References 34 publications

Digital Behavior Change Interventions for Younger Children With Chronic Health Conditions: Systematic Review

Digital Behavior Change Interventions for Younger Children With Chronic Health Conditions: Systematic Review

A developmental cascade perspective of paediatric obesity: A systematic review of preventive interventions from infancy through late adolescence

Impact of active video games on body mass index in children and adolescents: Systematic review and meta-analysis evaluating the quality of primary studies

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