Mobile Health for Pediatric Weight Management: Systematic Scoping Review

Usability of the BigO system in pediatric obesity treatment: A mixed-methods evaluation of clinical end-users

Objective

To assess technical usability of the BigO app and clinical portal among diverse participants and explore the overall user experiences of both.

Methods

Methods included technical usability testing by measuring the relative user efficiency score (RUS) for the app and measuring Relative User Efficiency (RUE) using the 'think aloud' method with the clinical portal. Qualitative approaches involved focus groups with adolescent app users and semi-structured one-to-one interviews with clinician participants. Thematic analysis was applied to analyze qualitative data.

Participants

Clinical participants consisted of adolescents seeking treatment for severe obesity and were invited via telephone/face to face to attend technical usability testing and a focus group. Healthcare professionals (HCPs) and researchers using the BigO clinical portal interface were invited to participate in usability testing and semi-structured interviews.

Results

From 14 families invited to attend, seven consented to join the study and four adolescents (mean age=13.8 (SD 0.8) years) participated. Additionally, six HCPs and one pediatric obesity researcher took part. RUS for adolescents indicated that the tasks required of them via myBigO app were feasible, and technically efficient. No user-related errors were observed during tasks. Technical barriers reported by adolescents included notifications of battery optimization, misunderstanding image annotation language, and compatibility challenges with certain phone models. RUS for the HCPs and researcher indicated that basic technical skills are a potential barrier for clinical portal use and qualitative findings revealed that clinical users wanted a logging option for monitoring goals and providing feedback on the portal.

Conclusion

Our study provided valuable formative findings from clinical end-users in Ireland indicating that adolescents being treated for obesity rated myBigO app as usable, acceptable and that it may assist other key stakeholders to understand food marketing and to monitor dietary and physical activity behaviors. Several key suggestions for future iterations of the clinical portal were provided to enhance its value in pediatric obesity treatment.

Lifestyle intervention and support preferences to maximize health outcomes in adolescent bariatric surgery patients

Introduction

Metabolic and bariatric surgery (MBS) is safe and efficacious for adolescents with severe obesity. Pairing MBS with behavioral lifestyle interventions may be effective for optimizing treatment outcomes. However, no standardized program exists. Adolescent perspectives are critical to understanding how to design interventions to enhance engagement, sustain motivation, and meet informational needs for pre- and post-MBS self-management behaviors. The aim of this study was to develop an MBS lifestyle support intervention built on evidence-based content with input from adolescents and their families.

Methods

A mixed-methods design identified adolescent preferences for MBS lifestyle support. Data were collected from a racially and ethnically diverse sample of adolescents (N = 17, 76% females, 24% males 41.2% non-Hispanic Black, 41.2% Hispanic/Latino, 11.8% non-Hispanic White, 5.8% Other) and their mothers (N = 13, 38.4% Hispanic) recruited from an MBS clinic. Quantitative surveys and qualitative interviews assessed preferred types of pre-post MBS content, modality, frequency, and delivery platforms to inform the design of the intervention. Mixed methods data were triangulated to provide a comprehensive understanding of adolescent/parent preferences.

Results

Adolescents prioritized eating well, managing stress, and maintaining motivation as desired support strategies. Parents identified parental support groups and nutrition guidance as priorities. Peer support and social media platforms were identified as key approaches for boosting motivation and engagement.

Conclusions

The patient voice is an important first step in understanding how, and whether behavioral lifestyle programs combined with MBS for weight management can be optimized. Adolescent preferences may enhance program fit and identify health behavior supports needed to sustain behavior change.

Effectiveness of a nurse-led mHealth approach in preventing obesity in adolescents: an intervention study

Background

Obesity prevention in adolescents is a public health priority given its increasing prevalence and health impact of obesity.

Aim

To evaluate the effectiveness of an educational intervention in overweight and obesity using a mHealth app in improving nutritional and sports knowledge, adherence to the Mediterranean diet, physical activity and anthropometric measurements in adolescents.

Methods

A randomised controlled trial with parallel groups that included 305 adolescents. The app includes the use of effective behavioural strategies to achieve habit change. Primary outcome variables were nutritional and sports knowledge score (GeSNK), adherence to a Mediterranean diet (KidMed) and level of physical activity (PAQ-A).

Results

The study included 154 participants in the mHealth group and 151 in the control group. The level of nutritional and sports knowledge was significantly higher in the mHealth group, 47 points versus 42 points. Adherence to the Mediterranean diet improved in both groups, 9 points in the mHealth group versus 8 points in the control group. Physical activity was statistically higher in the intervention group, 160 minutes/week versus 120 minutes/week.

Conclusions

The mHealth intervention showed a significant improvement in the level of nutritional and sports knowledge, adherence to the Mediterranean diet and time spent on physical activity.

Effectiveness of mHealth App-Based Interventions for Increasing Physical Activity and Improving Physical Fitness in Children and Adolescents: Systematic Review and Meta-Analysis

BACKGROUND

The COVID-19 pandemic has significantly reduced physical activity (PA) levels and increased sedentary behavior (SB), which can lead to worsening physical fitness (PF). Children and adolescents may benefit from mobile health (mHealth) apps to increase PA and improve PF. However, the effectiveness of mHealth app-based interventions and potential moderators in this population are not yet fully understood.

OBJECTIVE

This study aims to review and analyze the effectiveness of mHealth app-based interventions in promoting PA and improving PF and identify potential moderators of the efficacy of mHealth app-based interventions in children and adolescents.

METHODS

We searched for randomized controlled trials (RCTs) published in the PubMed, Web of Science, EBSCO, and Cochrane Library databases until December 25, 2023, to conduct this meta-analysis. We included articles with intervention groups that investigated the effects of mHealth-based apps on PA and PF among children and adolescents. Due to high heterogeneity, a meta-analysis was conducted using a random effects model. The Cochrane Risk of Bias Assessment Tool was used to evaluate the risk of bias. Subgroup analysis and meta-regression analyses were performed to identify potential influences impacting effect sizes.

RESULTS

We included 28 RCTs with a total of 5643 participants. In general, the risk of bias of included studies was low. Our findings showed that mHealth app-based interventions significantly increased total PA (TPA; standardized mean difference [SMD] 0.29, 95% CI 0.13-0.45; P<.001), reduced SB (SMD -0.97, 95% CI -1.67 to -0.28; P=.006) and BMI (weighted mean difference -0.31 kg/m2, 95% CI -0.60 to -0.01 kg/m2; P=.12), and improved muscle strength (SMD 1.97, 95% CI 0.09-3.86; P=.04) and agility (SMD -0.35, 95% CI -0.61 to -0.10; P=.006). However, mHealth app-based interventions insignificantly affected moderate to vigorous PA (MVPA; SMD 0.11, 95% CI -0.04 to 0.25; P<.001), waist circumference (weighted mean difference 0.38 cm, 95% CI -1.28 to 2.04 cm; P=.65), muscular power (SMD 0.01, 95% CI -0.08 to 0.10; P=.81), cardiorespiratory fitness (SMD -0.20, 95% CI -0.45 to 0.05; P=.11), muscular endurance (SMD 0.47, 95% CI -0.08 to 1.02; P=.10), and flexibility (SMD 0.09, 95% CI -0.23 to 0.41; P=.58). Subgroup analyses and meta-regression showed that intervention duration was associated with TPA and MVPA, and age and types of intervention was associated with BMI.

CONCLUSIONS

Our meta-analysis suggests that mHealth app-based interventions may yield small-to-large beneficial effects on TPA, SB, BMI, agility, and muscle strength in children and adolescents. Furthermore, age and intervention duration may correlate with the higher effectiveness of mHealth app-based interventions. However, due to the limited number and quality of included studies, the aforementioned conclusions require validation through additional high-quality research.

TRIAL REGISTRATION

PROSPERO CRD42023426532; https://tinyurl.com/25jm4kmf.

Significant effects of childhood obesity treatment with a web-based component in a randomised controlled study (Web-COP)

AIM

We evaluated the effect on body mass index standard deviation score (BMI-SDS) of a combined treatment (Web-COP) for children with obesity, including a web-based component targeting their parents.

METHODS

This randomised controlled trial recruited children 5-12 years of age with obesity (International Obesity Task Force BMI [IOTF-BMI] ≥30 kg/m2 ) from school health care and outpatient paediatric clinics in in Northern Sweden from 1 June 2019 to 21 June 2020. The children were randomised to Web-COP, an intervention with group sessions and a 12-week web-based component, or standard care. The primary outcome was the change in IOTF BMI-SDS after 6 months.

RESULTS

In total, 75 children (33 girls), mean age 9.5 years, were randomised, and 65/75 (87%) children and their parents completed the study, 35/39 (90%) in the Web-COP intervention and 30/36 (83%) in the standard care group. BMI-SDS at 6 months was changed from 3.08 to 2.81 in the intervention group compared to an increase from 3.07 to 3.16 in the standard care group, representing a significant difference between groups (p < 0.001). In the intervention group, 14/30 (47%) reduced their BMI-SDS ≥0.25, compared to none in the standard care group.

CONCLUSION

The parent-focused intervention significantly improved BMI-SDS in children with obesity as compared to children in standard care.

Effectiveness of utilizing step-monitoring devices to prevent and treat obesity in children and adolescents: A systematic review and meta-analysis

Background

Children and adolescents who are overweight and obese represent a growing public health issue. The use of step-monitoring devices as an intervention tool may be a simple, cost-effective, and easily replicable solution for addressing obesity in children and adolescents. No prior systematic reviews have evaluated the effectiveness of utilizing step-monitoring devices as an intervention method for obesity in children and adolescents.

Methods

Previous studies on using step-monitoring devices to prevent and treat obesity in children and adolescents were identified in the following databases: Web of Science, EMBASE, PubMed, Cochrane Library, SPORTDiscus, and SCOPUS. The search period for each database ranged from the year of their inception to 8 March 2023 (updated in June 2024). Meta-analyses were performed for mean differences (MDs) in body mass index (BMI), BMI z-score (BMI-Z), body fat, waist circumference, and body weight.

Results

From 12,907 relevant records, 23 studies were included in this meta-analysis. The included studies were mainly at low risk of bias, except for blinding. Step-monitoring device-based interventions had significant effects in reducing BMI-Z (MD -0.06; 95% CI -0.10 to -0.02), body fat (MD -0.95%; 95% CI -1.35 to -0.54), and body weight (MD -1.23 kg; 95% CI -2.36 to -0.10). However, there was no significant effect on BMI (MD -0.16 kg/m2; 95% CI -0.55 to 0.22) and waist circumference (MD -0.33 cm; 95% CI -1.23 to 0.58). Subgroup analyses indicated that participants who were overweight or obese showed greater intervention effects on BMI and BMI-Z compared to participants with normal weight. The programs with an intervention duration of ≤6 months presented a greater intervention effect on BMI-Z than those with an intervention duration of more than 6 months. The programs that established goals had a greater intervention effect on body fat than those that did not.

Conclusions

Step-monitoring devices may be an effective and generalizable intervention tool for the prevention and treatment of obesity in children and adolescents. Future studies should further explore how to set step goals and the duration of interventions to achieve better intervention effects.

Effectiveness of a Scalable mHealth Intervention for Children With Overweight and Obesity

Background: Multicomponent interventions are the first line of treatment for pediatric obesity, but are challenging to access. Mobile health (mHealth) interventions hold promise as they address commonly cited barriers for attending in person programs and have potential for wide scale dissemination. Methods: This retrospective cohort study examined data from youth who enrolled in the Kurbo program, which includes personal health coaching and a mobile app. Hierarchical linear regression was used to examine the impact of baseline percentage of the 95th% percentile for body mass index (%BMIp95), number of coaching sessions, and length of time enrolled in the program on change in %BMIp95, controlling for baseline age and sex. Results: A total of 3500 youth (mean age of 12.79 years, 71.3% female) were included. Youth experienced a 0.70 U decrease in BMI [standard deviation (SD) = 2.19] and a 4.45% decrease (SD = 8.5) in %BMIp95 over a mean of 31.5 weeks. The overall regression model was significant, R2 = 0.066, F(3,3494) = 77.18, and p < 0.001. Predictors of decrease in weight status included being female (b = -1.11, p < 0.001), higher baseline %BMIp95, (b = -0.58, p < 0.001), and greater number of coaching sessions (b = -0.12, p < 0.001), while greater time enrolled in the program (b = 0.02, p < 0.001) was associated with less change. Conclusion: Findings suggest a scalable coaching program with integrated digital tools for monitoring diet and activity can lead to significant reductions in weight status. Findings need to be replicated with more rigorous study designs, including a comparison condition and verified assessment of height and weight.

Collection and Analysis of Adherence Information for Software as a Medical Device Clinical Trials: Systematic Review

BACKGROUND

The rapid growth of digital health apps has necessitated new regulatory approaches to ensure compliance with safety and effectiveness standards. Nonadherence and heterogeneous user engagement with digital health apps can lead to trial estimates that overestimate or underestimate an app's effectiveness. However, there are no current standards for how researchers should measure adherence or address the risk of bias imposed by nonadherence through efficacy analyses.

OBJECTIVE

This systematic review aims to address 2 critical questions regarding clinical trials of software as a medical device (SaMD) apps: How well do researchers report adherence and engagement metrics for studies of effectiveness and efficacy? and What efficacy analyses do researchers use to account for nonadherence and how appropriate are their methods?

METHODS

We searched the Food and Drug Administration's registration database for registrations of repeated-use, patient-facing SaMD therapeutics. For each such registration, we searched ClinicalTrials.gov, company websites, and MEDLINE for the corresponding clinical trial and study articles through March 2022. Adherence and engagement data were summarized for each of the 24 identified articles, corresponding to 10 SaMD therapeutics. Each article was analyzed with a framework developed using the Cochrane risk-of-bias questions to estimate the potential effects of imperfect adherence on SaMD effectiveness. This review, funded by the Richard King Mellon Foundation, is registered on the Open Science Framework.

RESULTS

We found that although most articles (23/24, 96%) reported collecting information about SaMD therapeutic engagement, of the 20 articles for apps with prescribed use, only 9 (45%) reported adherence information across all aspects of prescribed use: 15 (75%) reported metrics for the initiation of therapeutic use, 16 (80%) reported metrics reporting adherence between the initiation and discontinuation of the therapeutic (implementation), and 4 (20%) reported the discontinuation of the therapeutic (persistence). The articles varied in the reported metrics. For trials that reported adherence or engagement, there were 4 definitions of initiation, 8 definitions of implementation, and 4 definitions of persistence. All articles studying a therapeutic with a prescribed use reported effectiveness estimates that might have been affected by nonadherence; only a few (2/20, 10%) used methods appropriate to evaluate efficacy.

CONCLUSIONS

This review identifies 5 areas for improving future SaMD trials and studies: use consistent metrics for reporting adherence, use reliable adherence metrics, preregister analyses for observational studies, use less biased efficacy analysis methods, and fully report statistical methods and assumptions.

A systematic review of economic evaluations of interventions targeting childhood overweight and obesity

This systematic review critically appraised and synthesized evidence from economic evaluations of interventions targeting childhood excess weight. We conducted systematic searches in 11 databases from inception to April 19, 2023. Studies were eligible if they evaluated interventions targeting children up to 18 years and the study intervention(s) targeted childhood excess weight or sought to improve diet or physical activity, regardless of the type of economic evaluation or the underpinning study design. We synthesized evidence using narrative synthesis methods. One-hundred fifty-one studies met the eligibility criteria and were classified into three groups based on the intervention approach: prevention-only (13 studies), prevention and treatment (100 studies), and treatment-only (38 studies). The predominant setting and study design differed considerably between the three groups of studies. However, compared with usual care, most interventions were deemed cost-effective. The study participants' ages, sex, and socioeconomic status were crucial to intervention cost-effectiveness. Interventions whose effects were projected beyond childhood, such as bariatric surgery, lower protein infant formula, and home-based general practitioner consultations, tended to be cost-effective. However, cost-effectiveness was sensitive to the assumptions underlying the persistence and intensity of such effects. Our findings can inform future recommendations on the conduct of economic evaluations of interventions targeting childhood overweight and obesity, as well as practice and policy recommendations.

The Impact of the ENDORSE Digital Weight Management Program on the Metabolic Profile of Children and Adolescents with Overweight and Obesity and on Food Parenting Practices

Childhood obesity is a serious public health problem worldwide. The ENDORSE platform is an innovative software ecosystem based on Artificial Intelligence which consists of mobile applications for parents and health professionals, activity trackers, and mobile games for children. This study explores the impact of the ENDORSE platform on metabolic parameters associated with pediatric obesity and on the food parenting practices of the participating mothers. Therefore, the metabolic parameters of the 45 children (mean age: 10.42 years, 53% girls, 58% pubertal, mean baseline BMI z-score 2.83) who completed the ENDORSE study were evaluated. The Comprehensive Feeding Practices Questionnaire was used for the assessment of food parenting practices. Furthermore, regression analysis was used to investigate possible associations between BMI z-score changes and changes in metabolic parameters and food parenting practices. Overall, there was a statistically significant reduction in glycated hemoglobin (mean change = −0.10, p = 0.013), SGOT (mean change = −1.84, p = 0.011), and SGPT (mean change = −2.95, p = 0.022). Emotional feeding/food as reward decreased (mean change −0.21, p = 0.007) and healthy eating guidance increased (mean change = 0.11, p = 0.051). Linear regression analysis revealed that BMI z-score change had a robust and significant correlation with important metabolic parameters: HOMA-IR change (beta coefficient = 3.60, p-value = 0.046), SGPT change (beta coefficient = 11.90, p-value = 0.037), and cortisol change (beta coefficient = 9.96, p-value = 0.008). Furthermore, healthy eating guidance change had a robust negative relationship with BMI z-score change (beta coefficient = −0.29, p-value = 0.007). Conclusions: The Endorse digital weight management program improved several metabolic parameters and food parenting practices.

The ENDORSE Feasibility Study: Exploring the Use of M-Health, Artificial Intelligence and Serious Games for the Management of Childhood Obesity

Childhood obesity constitutes a major risk factor for future adverse health conditions. Multicomponent parent-child interventions are considered effective in controlling weight. Τhe ENDORSE platform utilizes m-health technologies, Artificial Intelligence (AI), and serious games (SG) toward the creation of an innovative software ecosystem connecting healthcare professionals, children, and their parents in order to deliver coordinated services to combat childhood obesity. It consists of activity trackers, a mobile SG for children, and mobile apps for parents and healthcare professionals. The heterogeneous dataset gathered through the interaction of the end-users with the platform composes the unique user profile. Part of it feeds an AI-based model that enables personalized messages. A feasibility pilot trial was conducted involving 50 overweight and obese children (mean age 10.5 years, 52% girls, 58% pubertal, median baseline BMI z-score 2.85) in a 3-month intervention. Adherence was measured by means of frequency of usage based on the data records. Overall, a clinically and statistically significant BMI z-score reduction was achieved (mean BMI z-score reduction -0.21 ± 0.26, p-value < 0.001). A statistically significant correlation was revealed between the level of activity tracker usage and the improvement of BMI z-score (-0.355, p = 0.017), highlighting the potential of the ENDORSE platform.

Parents' Experiences Using Digital Health Technologies in Paediatric Overweight and Obesity Support: An Integrative Review

This study aimed to explore parents' perspectives regarding the use of digital health technologies in paediatric overweight and obesity weight support. A systematic search in 'Academic Search Premier', 'British Nursing Index', 'Cumulative Index to Nursing and Allied Health', and 'Health Research Premium Collection' was conducted in November 2021. Inclusion criteria were English or Nordic peer-reviewed articles published after 2010, overweight and obese children aged 2-10, weight support using digital health technologies, and parental experiences examined. An integrative review was conducted using Joanna Briggs Institute quality appraisal checklists and a constant comparison analysis method. In total, 14 articles were analysed that included SMS, telephone, apps, websites, and social media as the main technology groups. A limitation of this review was the heterogenicity of the studies. The results indicate that parents, mostly mothers, had a positive experience, finding technologies helpful and easy to use, and expressed optimism toward future use. An option for interacting with others and the possibility of personalising support were enjoyed or requested. In conclusion, digital health technologies can be a suitable tool to empower the parents of children with overweight and obesity concerns, whose perspective should be considered during the design and support phases.

Adolescents' and professionals' experiences of metabolic and bariatric surgery and requirements for preoperative and postoperative support through mHealth: a qualitative study

OBJECTIVES

This study aimed to explore adolescents' and professionals' incentives and experiences of metabolic and bariatric surgery (MBS) and to explore perceived needs and requirements for preoperative and postoperative support through an mHealth intervention to improve long-term healthy lifestyle behaviour and health outcomes.

DESIGN

An inductive qualitative study using in-depth semistructured interviews.

SETTING

Three hospital-based specialist paediatric obesity treatment units in Sweden.

PARTICIPANTS

A total of 18 participants (14 women and 4 men). Nine adolescents aged between 17 and 22 years who had undergone or were about to undergo surgery, and nine professionals, including researchers and clinicians working in various professional roles such as physiotherapist, dietician, nurse, psychologist, physician and pedagogue.

RESULTS

Both informant groups of participants highlighted that undergoing MBS is a complex process, and hence actions are required on several levels to optimise the positive, long-term effects of surgery. Efficient communication between the healthcare professionals and adolescents was considered crucial and a key success factor. Informants acknowledged the need for additional support that relates to psychosocial well-being and mental health in order to understand, form and accept new behaviours and identity. An mHealth intervention should be seen as complementary to physical appointments, and informants acknowledged that an app could be a way of improving access to healthcare, and a useful tool to allow for individually tailored and easily available support.

CONCLUSIONS

The findings address the importance of a personal encounter and a need for additional support that relates to psychosocial well-being, mental health and healthy lifestyle behaviour. These findings should be incorporated into future research concerning mHealth interventions in MBS during adolescence.

Technology-Based Obesity Prevention Interventions Among Hispanic Adolescents in the United States: Scoping Review

BACKGROUND

Given that today's adolescents are digital front-runners, technology-based obesity prevention strategies are age-appropriate for this population. The use of remote and wireless technologies may be suitable for extending the reach and engagement of obesity prevention efforts among high-risk Hispanic youths, as this subgroup is disproportionately affected by barriers that limit participation in traditional, in-person interventions.

OBJECTIVE

The purpose of this scoping review was to examine the intervention and sample characteristics of technology-based obesity prevention interventions among Hispanic adolescents. We also examined feasibility criteria to assess the acceptability and appropriateness of technology-based strategies among Hispanic youths.

METHODS

A comprehensive search of Embase and PubMed identified 7 studies that met the inclusion criteria. Data were extracted by 2 independent reviewers.

RESULTS

Of the 7 included studies, half (n=4, 57%) used a randomized control trial design, with equal implementation in school (n=3, 43%) and clinic (n=4, 57%) settings. Studies commonly targeted improvements in diet (n=4, 57%) and physical activity (n=7, 100%), with only 1 (14%) study focused on sedentary behaviors. Just 2 (29%) studies reported the use of behavioral theories or models. Studies focused primarily on youths in early (n=5, 71%) or middle (n=6, 86%) adolescence, and there was limited information reported on socioeconomic status. Only 3 (43%) study conducted formative work, and few (n=3, 43%) reported on acceptability. Only 1 (14%) study reported that materials were available in Spanish and English, and only 1 (14%) study used culturally tailored content. Additionally, 3 (43%) studies used strategies that considered social determinants of health.

CONCLUSIONS

To increase our understanding of the feasibility and effectiveness of technology-based obesity prevention strategies among Hispanic adolescents, there is a need for more feasibility studies that are theoretically grounded and comprehensively report on feasibility-related outcomes. Future studies should also leverage technology to simultaneously address multiple health behaviors beyond diet and physical activity. The result of this review can be used to guide the development of future technology-based obesity prevention strategies among Hispanic adolescents.

TRIAL REGISTRATION

CliniclaTrials.gov NCT04953442; https://clinicaltrials.gov/ct2/show/NCT04953442.

Guidelines for treating child and adolescent obesity: A systematic review

Obesity is a chronic disease that compromises the physical and mental health of an increasing proportion of children globally. In high-income countries, prevalence of paediatric obesity is increasing faster in those from marginalised populations such as low-income households, suggesting the disease as one that is largely systemic. Appropriate treatment should be prioritised in these settings to prevent the development of complications and co-morbidities and manage those that already exist. An array of clinical practice guidelines are available for managing overweight and obesity in children and adolescents, but no systematic review has yet compared their quality or synthesised their recommendations. We aimed to narratively review clinical practice guidelines published in English for treating child and adolescent obesity, to identify the highest quality guidelines, and assess similarities, conflicts, and gaps in recommendations. We systematically searched academic databases and grey literature for guidelines published. We used the AGREE II tool to assess the quality, and identified nine high quality guidelines for inclusion in a narrative review of recommendations. Guidelines predominantly recommended the delivery of multi-component behaviour-change interventions aimed at improving nutrition and physical activity. Treatment outcomes were generally focussed on weight, with less emphasis on managing complications or improving quality-of-life. There was no evidence-based consensus on the best mode of delivery, setting, or treatment format. The guidelines rarely included recommendations for addressing the practical or social barriers to behaviour change, such as cooking skills or supervised physical activity. There is insufficient evidence to evaluate pharmaceutical and surgical interventions in children, and these were generally not recommended. It should be noted that this review addressed documents published in English only, and therefore the included guidelines were applicable predominantly to high-resource settings.

Toward Systems Models for Obesity Prevention: A Big Role for Big Data

The relation among the various causal factors of obesity is not well understood, and there remains a lack of viable data to advance integrated, systems models of its etiology. The collection of big data has begun to allow the exploration of causal associations between behavior, built environment, and obesity-relevant health outcomes. Here, the traditional epidemiologic and emerging big data approaches used in obesity research are compared, describing the research questions, needs, and outcomes of 3 broad research domains: eating behavior, social food environments, and the built environment. Taking tangible steps at the intersection of these domains, the recent European Union project "BigO: Big data against childhood obesity" used a mobile health tool to link objective measurements of health, physical activity, and the built environment. BigO provided learning on the limitations of big data, such as privacy concerns, study sampling, and the balancing of epidemiologic domain expertise with the required technical expertise. Adopting big data approaches will facilitate the exploitation of data concerning obesity-relevant behaviors of a greater variety, which are also processed at speed, facilitated by mobile-based data collection and monitoring systems, citizen science, and artificial intelligence. These approaches will allow the field to expand from causal inference to more complex, systems-level predictive models, stimulating ambitious and effective policy interventions.

Automated growth monitoring app (GROWIN): a mobile Health (mHealth) tool to improve the diagnosis and early management of growth and nutritional disorders in childhood

OBJECTIVE

To assess the functionality and feasibility of the GROWIN app for promoting early detection of growth disorders in childhood, supporting early interventions, and improving children's lifestyle by analyzing data collected over 3 years (2018-2020).

METHODS

We retrospectively assessed the growth parameters (height, weight, body mass index [BMI], abdominal circumference) entered by users (caregivers/parents) in the GROWIN app. We also analyzed the potential health problems detected and the messages/recommendations the app showed. Finally, we assessed the possible impact/benefit of the app on the growth of the children.

RESULTS

A total of 21 633 users (Spanish [65%], Latin American [30%], and others [5%]) entered 10.5 ± 8.3 measurements (0-15 y old). 1200 recommendations were for low height and 550 for low weight. 1250 improved their measurements. A specialist review was recommended in 500 patients due to low height. 2567 nutrition tests were run. All children with obesity (n = 855, BMI: 27.8 kg/m2 [2.25 SD]) completed the initial test with a follow-up of ≥1 year. Initial results (score: 8.1) showed poor eating habits (fast food, commercially baked goods, candy, etc.), with >90% not having breakfast. After 3-6 months, BMI decreased ≥1 point, and test scores increased ≥2 points. This benefit was maintained beyond 1 year and was correlated with an improvement in BMI (r = -.65, P = .01).

DISCUSSION/CONCLUSIONS

The GROWIN app represents an innovative automated solution for families to monitor growth. It allows the early detection of abnormal growth indicators during childhood and adolescence, promoting early interventions. Additionally, in children with obesity, an improvement in healthy nutritional habits and a decrease in BMI were observed.

The Aim2Be mHealth Intervention for Children With Overweight or Obesity and Their Parents: Person-Centered Analyses to Uncover Digital Phenotypes

Background

Despite the growing number of mobile health (mHealth) interventions targeting childhood obesity, few studies have characterized user typologies derived from individuals’ patterns of interactions with specific app features (digital phenotypes).

Objective

This study aims to identify digital phenotypes among 214 parent-child dyads who used the Aim2Be mHealth app as part of a randomized controlled trial conducted between 2019 and 2020, and explores whether participants’ characteristics and health outcomes differed across phenotypes.

Methods

Latent class analysis was used to identify distinct parent and child phenotypes based on their use of the app’s behavioral, gamified, and social features over 3 months. Multinomial logistic regression models were used to assess whether the phenotypes differed by demographic characteristics. Covariate-adjusted mixed-effect models evaluated changes in BMI z scores (zBMI), diet, physical activity, and screen time across phenotypes.

Results

Among parents, 5 digital phenotypes were identified: socially engaged (35/214, 16.3%), independently engaged (18/214, 8.4%) (socially and independently engaged parents are those who used mainly the social or the behavioral features of the app, respectively), fully engaged (26/214, 12.1%), partially engaged (32/214, 15%), and unengaged (103/214, 48.1%) users. Married parents were more likely to be fully engaged than independently engaged (P=.02) or unengaged (P=.01) users. Socially engaged parents were older than fully engaged (P=.02) and unengaged (P=.01) parents. The latent class analysis revealed 4 phenotypes among children: fully engaged (32/214, 15%), partially engaged (61/214, 28.5%), dabblers (42/214, 19.6%), and unengaged (79/214, 36.9%) users. Fully engaged children were younger than dabblers (P=.04) and unengaged (P=.003) children. Dabblers lived in higher-income households than fully and partially engaged children (P=.03 and P=.047, respectively). Fully engaged children were more likely to have fully engaged (P<.001) and partially engaged (P<.001) parents than unengaged children. Compared with unengaged children, fully and partially engaged children had decreased total sugar (P=.006 and P=.004, respectively) and energy intake (P=.03 and P=.04, respectively) after 3 months of app use. Partially engaged children also had decreased sugary beverage intake compared with unengaged children (P=.03). Similarly, children with fully engaged parents had decreased zBMI, whereas children with unengaged parents had increased zBMI over time (P=.005). Finally, children with independently engaged parents had decreased caloric intake, whereas children with unengaged parents had increased caloric intake over time (P=.02).

Conclusions

Full parent-child engagement is critical for the success of mHealth interventions. Further research is needed to understand program design elements that can affect participants’ engagement in supporting behavior change.

Trial Registration

ClinicalTrials.gov NCT03651284; https://clinicaltrials.gov/ct2/show/NCT03651284

International Registered Report Identifier (IRRID)

RR2-10.1186/s13063-020-4080-2

Obesity in children and adolescents: epidemiology, causes, assessment, and management

This Review describes current knowledge on the epidemiology and causes of child and adolescent obesity, considerations for assessment, and current management approaches. Before the COVID-19 pandemic, obesity prevalence in children and adolescents had plateaued in many high-income countries despite levels of severe obesity having increased. However, in low-income and middle-income countries, obesity prevalence had risen. During the pandemic, weight gain among children and adolescents has increased in several jurisdictions. Obesity is associated with cardiometabolic and psychosocial comorbidity as well as premature adult mortality. The development and perpetuation of obesity is largely explained by a bio-socioecological framework, whereby biological predisposition, socioeconomic, and environmental factors interact together to promote deposition and proliferation of adipose tissue. First-line treatment approaches include family-based behavioural obesity interventions addressing diet, physical activity, sedentary behaviours, and sleep quality, underpinned by behaviour change strategies. Evidence for intensive dietary approaches, pharmacotherapy, and metabolic and bariatric surgery as supplemental therapies are emerging; however, access to these therapies is scarce in most jurisdictions. Research is still needed to inform the personalisation of treatment approaches of obesity in children and adolescents and their translation to clinical practice.

The Effectiveness of Wearable Devices as Physical Activity Interventions for Preventing and Treating Obesity in Children and Adolescents: Systematic Review and Meta-analysis

Background

The prevalence of obesity in children and adolescents remains a global public health issue. Wearable devices may offer new opportunities for prevention and intervention in obesity. Previous systematic reviews have only examined the effect of the wearable device interventions on preventing and treating obesity in adults. However, no systematic review has provided an evaluation of wearable devices as physical activity interventions for preventing and treating obesity in children and adolescents.

Objective

The purpose of this review and meta-analysis was to evaluate the effectiveness of wearable devices as physical activity interventions on obesity-related anthropometric outcomes in children and adolescents.

Methods

Research articles retrieved from PubMed, EMBASE, Cochrane Library, Scopus, and EBSCO from inception to February 1, 2021, were reviewed. The search was designed to identify studies utilizing wearable devices for preventing and treating obesity in children and adolescents. The included studies were evaluated for risk of bias following the Cochrane recommendation. Meta-analyses were conducted to evaluate the effectiveness of wearable devices as physical activity interventions on body weight, body fat, BMI z-score (BMI-Z), BMI, and waist circumference. Subgroup analyses were performed to determine whether the characteristics of the interventions had an impact on the effect size.

Results

A total of 12 randomized controlled trials (3227 participants) were selected for meta-analysis. Compared with the control group, wearable device interventions had statistically significant beneficial effects on BMI (mean difference [MD] –0.23; 95% CI –0.43 to –0.03; P=.03; I²=2%), BMI-Z (MD –0.07; 95% CI –0.13 to –0.01; P=.01; I²=81%), body weight (MD –1.08; 95% CI –2.16 to –0.00; P=.05; I²=58%), and body fat (MD –0.72; 95% CI –1.19 to –0.25; P=.003; I²=5%). However, no statistically significant effect was found on waist circumference (MD 0.55; 95% CI –0.21 to 1.32; P=.16; I²=0%). The subgroup analysis showed that for participants with overweight or obesity (MD –0.75; 95% CI –1.18 to –0.31; P<.01; I²=0%), in the short-term (MD –0.62; 95% CI –1.03 to –0.21; P<.01; I²=0%), wearable-based interventions (MD –0.56; 95% CI –0.95 to –0.18; P<.01; I²=0%) generally resulted in greater intervention effect size on BMI.

Conclusions

Evidence from this meta-analysis shows that wearable devices as physical activity interventions may be useful for preventing and treating obesity in children and adolescents. Future research is needed to identify the most effective physical activity indicators of wearable devices to prevent and treat obesity in children and adolescents.

Effectiveness of Mobile Apps in Promoting Healthy Behavior Changes and Preventing Obesity in Children: Systematic Review

BACKGROUND

Mobile apps have been increasingly incorporated into healthy behavior promotion interventions targeting childhood obesity. However, their effectiveness remains unclear.

OBJECTIVE

This paper aims to conduct a systematic review examining the effectiveness of mobile apps aimed at preventing childhood obesity by promoting health behavior changes in diet, physical activity, or sedentary behavior in children aged 8 to 12 years.

METHODS

MEDLINE, Embase, PsycINFO, CINAHL, and ERIC were systematically searched for peer-reviewed primary studies from January 2008 to July 2021, which included children aged 8 to 12 years; involved mobile app use; and targeted at least one obesity-related factor, including diet, physical activity, or sedentary behavior. Data extraction and risk of bias assessments were conducted by 2 authors.

RESULTS

Of the 13 studies identified, most used a quasi-experimental design (n=8, 62%). Significant improvements in physical activity (4/8, 50% studies), dietary outcomes (5/6, 83% studies), and BMI (2/6, 33% studies) were reported. All 6 multicomponent interventions and 57% (4/7) of standalone interventions reported significant outcomes in ≥1 behavioral change outcome measured (anthropometric, physical activity, dietary, and screen time outcomes). Gamification, behavioral monitoring, and goal setting were common features of the mobile apps used in these studies.

CONCLUSIONS

Apps for health behavior promotion interventions have the potential to increase the adoption of healthy behaviors among children; however, their effectiveness in improving anthropometric measures remains unclear. Further investigation of studies that use more rigorous study designs, as well as mobile apps as a standalone intervention, is needed.

An mHealth Intervention to Reduce the Packing of Discretionary Foods in Children's Lunch Boxes in Early Childhood Education and Care Services: Cluster Randomized Controlled Trial

Background

Interventions in early childhood education and care (ECEC) services have the potential to improve children’s diet at the population level.

Objective

This study aims to test the efficacy of a mobile health intervention in ECEC services to reduce parent packing of foods high in saturated fat, sugar, and sodium (discretionary foods) in children’s (aged 3-6 years) lunch boxes.

Methods

A cluster randomized controlled trial was undertaken with 355 parent and child dyads recruited by phone and in person from 17 ECEC services (8 [47%] intervention and 9 [53%] control services). Parents in the intervention group received a 10-week fully automated program targeting barriers to packing healthy lunch boxes delivered via an existing service communication app. The program included weekly push notifications, within-app messages, and links to further resources, including websites and videos. The control group did not receive any intervention. The primary outcomes were kilojoules from discretionary foods and associated nutrients (saturated fat, free sugars, and sodium) packed in children’s lunch boxes. Secondary outcomes included consumption of kilojoules from discretionary foods and related nutrients and the packing and consumption of serves of discretionary foods and core food groups. Photography and weights of foods in children’s lunch boxes were recorded by trained researchers before and after the trial to assess primary and secondary outcomes. Outcome assessors were blinded to service allocation. Feasibility, appropriateness, and acceptability were assessed via an ECEC service manager survey and a parent web-based survey. Use of the app was assessed via app analytics.

Results

Data on packed lunch box contents were collected for 88.8% (355/400) of consenting children at baseline and 84.3% (337/400) of children after the intervention. There was no significant difference between groups in kilojoule from discretionary foods packed (77.84 kJ, 95% CI −163.49 to 319.18; P=.53) or the other primary or secondary outcomes. The per-protocol analysis, including only data from children of parents who downloaded the app, also did not find any statistically significant change in primary (−1.98 kJ, 95% CI −343.87 to 339.90; P=.86) or secondary outcomes. Approximately 61.8% (102/165) of parents in the intervention group downloaded the app, and the mean service viewing rate of weekly within-app messages was 26% (SD 14.9). Parents who responded to the survey and participating services agreed that it was appropriate to receive lunch box information via the app (40/50, 80% and 6/8, 75%, respectively).

Conclusions

The intervention was unable to demonstrate an impact on kilojoules or associated nutrients from discretionary foods packed in children’s lunch boxes. Low app downloads and program message views indicate a need to explore how to improve factors related to implementation before further testing similar mobile health interventions in this setting.

Trial Registration

Australian New Zealand Clinical Trials Registry ACTRN12618000133235; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374379

George SM, Prinz R, Resnicow K. The Results of the Families Improving Together (FIT) for Weight Loss Randomized Trial in Overweight African American Adolescents

BACKGROUND

Few intervention studies have integrated cultural tailoring, parenting, behavioral, and motivational strategies to address African American adolescent weight loss.

PURPOSE

The Families Improving Together (FIT) for Weight Loss trial was a randomized group cohort study testing the efficacy of a cultural tailoring, positive parenting, and motivational intervention for weight loss in overweight African American adolescents (N = 241 adolescent/caregiver dyads).

METHODS

The trial tested an 8-week face-to-face group motivational plus family weight loss program (M + FWL) compared with a comprehensive health education control program. Participants were then rerandomized to an 8-week tailored or control online program to test the added effects of the online intervention on reducing body mass index and improving physical activity (moderate-to-vigorous physical activity [MVPA], light physical activity [LPA]), and diet.

RESULTS

There were no significant intervention effects for body mass index or diet. There was a significant effect of the group M + FWL intervention on parent LPA at 16 weeks (B = 33.017, SE = 13.115, p = .012). Parents in the group M + FWL intervention showed an increase in LPA, whereas parents in the comprehensive health education group showed a decrease in LPA. Secondary analyses using complier average causal effects showed a significant intervention effect at 16 weeks for parents on MVPA and a similar trend for adolescents.

CONCLUSIONS

While the intervention showed some impact on physical activity, additional strategies are needed to impact weight loss among overweight African American adolescents.

Digital Health Interventions for Weight Management in Children and Adolescents: Systematic Review and Meta-analysis

Background

Recent meta-analyses suggest the use of technology-based interventions as a treatment option for obesity in adulthood. Similar meta-analytic approaches for children are scarce.

Objective

The aim of this meta-analysis is to examine the effect of technology-based interventions on overweight and obesity treatment in children and adolescents.

Methods

A systematic literature search was performed using MEDLINE (PubMed), Scopus, and Cochrane Library for randomized clinical trials to identify interventional studies published between January 2000 and February 2021.

Results

In total, 9 manuscripts from 8 clinical trials of 582 children or adolescents were considered eligible. BMI, BMI z-score, and other BMI-related baseline metrics during and after intervention were considered as primary outcomes. In 7 of 8 studies, a technology-based intervention was applied in addition to conventional care. Of the 8 studies, 6 studies were conducted in the United States, 1 in Australia, and 1 in northwestern Europe. In total, 5 studies included adolescents, whereas the rest addressed children aged 9 to 12 years. Intervention duration ranged from 3 to 24 months. Significant differences between groups in BMI metric changes were reported by 5 of the 8 studies. Pooled analysis revealed an overall significant decrease in BMI metrics in the intervention group (standardized mean difference –0.61, 95% CI –1.10 to –0.13; P=.01). Subgroup analysis revealed that significance was lost in case of no parental involvement (standardized mean difference –0.36, 95% CI –0.83 to 0.11; P=.14). The small number of clinical trials found, the varying study quality, and the study heterogeneity are some limitations of this review.

Conclusions

The studies reported herein describe functional and acceptable technology-based approaches, in addition to conventional treatments, to enhance weight loss in young populations.

A Systematic Review of the Scope of Study of mHealth Interventions for Wellness and Related Challenges in Pediatric and Young Adult Populations

Background

Despite the purported advantages and potential efficacy of mHealth interventions to promote wellness in children, adolescents, and young adults, it is not clear what areas have been explored and the challenges reported in the biomedical literature.

Methods

We conducted a scoping review of publications between 2015 and 2019.

Results

We identified 54 papers that met our inclusion criteria. Studies were conducted in 21 countries and ranged in size from six to 9851 participants (median: 184). A total of 41% of studies enrolled adolescents only (n = 19). Of the seven types of mHealth interventions identified, apps were the most common intervention (59%; n = 32) evaluated and 44% of the studies evaluated two or more interventions. The most common topic of the studies reviewed was sexual and reproductive health (24%; n = 13).

Conclusion

Most pediatric mHealth intervention studies are conducted in adolescents in large part, and sexual and reproductive health is the most commonly studied topic. With the easy and widespread accessibility to smartphone technology, the use of mobile apps for wellness interventions will likely continue to expand to other wellness topics.

Usability and Engagement Testing of mHealth Apps in Paediatric Obesity: A Narrative Review of Current Literature

Mobile health (mHealth) platforms have become increasingly popular for delivering health interventions in recent years and particularly in light of the COVID-19 pandemic. Childhood obesity treatment is an area where mHealth interventions may be useful due to the multidisciplinary nature of interventions and the need for long-term care. Many mHealth apps targeting youth exist but the evidence base underpinning the methods for assessing technical usability, user engagement and user satisfaction of such apps with target end-users or among clinical populations is unclear, including for those aimed at paediatric overweight and obesity management. This review aims to examine the current literature and provide an overview of the scientific methods employed to test usability and engagement with mHealth apps in children and adolescents with obesity. A narrative literature review was undertaken following a systematic search. Four academic databases were searched. Inclusion criteria were studies describing the usability of mHealth interventions for childhood obesity treatment. Following the application of inclusion and exclusion criteria, fifty-nine articles were included for full-text review, and seven studies met the criteria for usability and engagement in a clinical paediatric population with obesity. Six apps were tested for usability and one for engagement in childhood obesity treatment. Sample sizes ranged from 6-1120 participants. The included studies reported several heterogenous measurement instruments, data collection approaches, and outcomes. Recommendations for future research include the standardization and validation of instruments to measure usability and engagement within mHealth studies in this population.

Digital health for quality healthcare: A systematic mapping of review studies

Objective

To systematically catalogue review studies on digital health to establish extent of evidence on quality healthcare and illuminate gaps for new understanding, perspectives and insights for evidence-informed policies and practices.

Methods

We systematically searched PubMed database using sensitive search strings. Two reviewers independently conducted two-phase selection via title and abstract, followed by full-text appraisal. Consensuses were derived for any discrepancies. A standardized data extraction tool was used for reliable data mining.

Results

A total of 54 reviews from year 2014 to 2021 were included with notable increase in trend of publications. Systematic reviews constituted the majority (61.1%, (37.0% with meta-analyses)) followed by scoping reviews (38.9%). Domains of quality being reviewed include effectiveness (75.9%), accessibility (33.3%), patient safety (31.5%), efficiency (25.9%), patient-centred care (20.4%) and equity (16.7%). Mobile apps and computer-based were the commonest (79.6%) modalities. Strategies for effective intervention via digital health included engineering improved health behaviour (50.0%), better clinical assessment (35.1%), treatment compliance (33.3%) and enhanced coordination of care (24.1%). Psychiatry was the discipline with the most topics being reviewed for digital health (20.3%).

Conclusion

Digital health reviews reported findings that were skewed towards improving the effectiveness of intervention via mHealth applications, and predominantly related to mental health and behavioural therapies. There were considerable gaps on review of evidence on digital health for cost efficiency, equitable healthcare and patient-centred care. Future empirical and review studies may investigate the association between fields of practice and tendency to adopt and research the use of digital health to improve care.

The Potential Role of Digital Health in Obesity Care

Obesity is a complex, multi-factorial, chronic condition which increases the risk of a wide range of diseases including type 2 diabetes mellitus, cardiovascular disease and certain cancers. The prevalence of obesity continues to rise and this places a huge economic burden on the healthcare system. Existing approaches to obesity treatment tend to focus on individual responsibility and diet and exercise, failing to recognise the complexity of the condition and the need for a whole-system approach. A new approach is needed that recognises the complexity of obesity and provides patient-centred, multidisciplinary care which more closely meets the needs of each individual with obesity. This review will discuss the role that digital health could play in this new approach and the challenges of ensuring equitable access to digital health for obesity care. Existing technologies, such as telehealth and mobile health apps and wearable devices, offer emerging opportunities to improve access to obesity care and enhance the quality, efficiency and cost-effectiveness of weight management interventions and long-term patient support. Future application of machine learning and artificial intelligence to obesity care could see interventions become increasingly automated and personalised.

E-&mHealth interventions targeting nutrition, physical activity, sedentary behavior, and/or obesity among children: A scoping review of systematic reviews and meta-analyses

Childhood obesity is a public health concern. Electronic and mobile health (e-&mHealth) approaches can facilitate the delivery of interventions for obesity prevention and treatment. Synthesizing reviews of e-&mHealth interventions to improve weight and weight-related behaviors (physical activity, sedentary behavior, and diet) is useful to characterize the current scope of the literature and identify opportunities for future reviews and studies. Using a scoping review methodology, we aimed to evaluate the breadth and methodological quality of systematic reviews and meta-analyses of e-&mHealth interventions targeting weight and weight-related behaviors in children and adolescents aged <19 years. A systematic search of seven databases was conducted, including reviews published between 2000 and 2019. Review characteristics were extracted, and methodological quality was assessed using the AMSTAR 2 tool. Forty-five systematic reviews and meta-analyses were included. All reviews evaluated intervention efficacy (100%), but few assessed other aspects (20% in total) such as cost-effectiveness. Smartphone applications (47%), text messages (44%), and websites (35%) were the main modalities. Weight (60%), physical activity (51%), and diet (44%) were frequently assessed, unlike sedentary behavior (8%). Most reviews were rated as having critically low or low methodological quality (97%). Reviews that identify the effective active ingredients of interventions and explore metrics beyond efficacy are recommended.

Mobile Health and Telehealth Interventions to Increase Physical Activity in Adolescents with Obesity: a Promising Approach to Engaging a Hard-to-Reach Population

PURPOSE OF REVIEW

Adolescence represents a critical time to set habits for long-term health, yet adequate rates of physical activity are uncommon in this age group. Mobile technology use, however, is ubiquitous. We review advantages and challenges posed by mobile health (mHealth) and telehealth-based physical activity interventions aimed at adolescents.

RECENT FINDINGS

Mobile Health (mHealth) and telehealth interventions to increase physical activity in adolescents include use of wearable activity trackers, text messages or apps, and video visits with exercise specialists. Definitions and goals for physical activity differ across interventions, and methods of activity measurement also vary. User engagement is often poor, if tracked at all. No identified studies included use of behavioral economics-informed engagement strategies. Intervention designers must plan for ways to maximize engagement and to reliably measure the intended outcome. Although mHealth and telehealth interventions have advantages such as scalability and acceptability, potential pitfalls must be addressed before widespread implementation.

Telehealth: A Useful Tool for the Management of Nutrition and Exercise Programs in Pediatric Obesity in the COVID-19 Era

The COVID-19 pandemic has led to the implementation of policies that mandate various restrictions on daily life, including social distancing, the closure of public services and schools, and movement limitations. Even though these restrictive measures decreased the COVID-19 spread, they may have detrimental effects on various lifestyle components such as physical inactivity, sedentary behavior, and dietary habits, influencing the maintenance of weight and contributing to obesity among children and adolescents. The coexistence of childhood obesity and COVID-19 and changes in the bioecological environment have put children and adolescents at increased risk for developing obesity and exacerbating the severity of this disorder. The use of telehealth technology is a modern approach useful for the delivery of health care services by health care professionals, where distance is a critical factor. Telehealth is effective in promoting increased self-monitoring and behavioral change, and provides the opportunity to perform online nutritional support and exercise training programs to promote a healthy lifestyle and reduce sedentary behaviors in children and adolescents. Telehealth, including tele-exercise and tele-nutrition, has the potential to address many of the key challenges in providing health services, including in patients with obesity during the COVID-19 outbreak. This narrative review aims to describe the role of telehealth as an opportunity in the management of pediatric obesity in the COVID-19 era, and to deliver nutrition and exercise programs for the maintenance of health.

Pediatric Weight Management Through mHealth Compared to Face-to-Face Care: Cost Analysis of a Randomized Control Trial

BACKGROUND

Mobile health (mHealth) may improve pediatric weight management capacity and the geographical reach of services, and overcome barriers to attending physical appointments using ubiquitous devices such as smartphones and tablets. This field remains an emerging research area with some evidence of its effectiveness; however, there is a scarcity of literature describing economic evaluations of mHealth interventions.

OBJECTIVE

We aimed to assess the economic viability of using an mHealth approach as an alternative to standard multidisciplinary care by evaluating the direct costs incurred within treatment arms during a noninferiority randomized controlled trial (RCT).

METHODS

A digitally delivered (via a smartphone app) maintenance phase of a pediatric weight management program was developed iteratively with patients and families using evidence-based approaches. We undertook a microcosting exercise and budget impact analysis to assess the costs of delivery from the perspective of the publicly funded health care system. Resource use was analyzed alongside the RCT, and we estimated the costs associated with the staff time and resources for service delivery per participant.

RESULTS

In total, 109 adolescents participated in the trial, and 84 participants completed the trial (25 withdrew from the trial). We estimated the mean direct cost per adolescent attending usual care at €142 (SD 23.7), whereas the cost per adolescent in the mHealth group was €722 (SD 221.1), with variations depending on the number of weeks of treatment completion. The conversion rate for the reference year 2013 was $1=€0.7525. The costs incurred for those who withdrew from the study ranged from €35 to €681, depending on the point of dropout and study arm. The main driver of the costs in the mHealth arm was the need for health professional monitoring and support for patients on a weekly basis. The budget impact for offering the mHealth intervention to all newly referred patients in a 1-year period was estimated at €59,046 using the assessed approach.

CONCLUSIONS

This mHealth approach was substantially more expensive than usual care, although modifications to the intervention may offer opportunities to reduce the mHealth costs. The need for monitoring and support from health care professionals (HCPs) was not eliminated using this delivery model. Further research is needed to explore the cost-effectiveness and economic impact on families and from a wider societal perspective.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01804855; https://clinicaltrials.gov/ct2/show/NCT01804855.

Pediatric Obesity Treatment via Telehealth: Current Evidence and Future Directions

PURPOSE OF REVIEW

Telehealth delivery of pediatric weight management interventions may address time, travel, and cost barriers to in-person interventions, thus improving accessibility. This narrative review highlights findings from the past 5 years of pediatric lifestyle interventions for weight management that utilize telehealth for treatment delivery. We describe impressions and future directions.

RECENT FINDINGS

We identified and included 20 studies that described unique interventions from the past 5 years. The majority of reviewed studies indicated statistically significant reductions in BMI z-scores, high retention and attendance, and high satisfaction. However, mean decreases in BMI z-scores were marginal (approximately 0.10) in all but two studies. Studies did not often report effect sizes. Pediatric telehealth weight management interventions demonstrate good feasibility and acceptability. Improvement in reporting results and more rigorous research, including use of randomized designs, recruitment of larger samples, and incorporation of extended follow-up is needed to determine clinical impact and magnitude of effects.

Variability in How Canadian Pediatric Weight Management Clinics Deliver Care: Evidence from the CANadian Pediatric Weight Management Registry

Background: Clinical practice guidelines for pediatric weight management highlight the importance of family-based behavioral strategies to enhance health behaviors. Little is known, however, of how clinics implement these programs. The study objectives were to (1) describe how Canadian pediatric weight management clinics deliver care and (2) evaluate change in services over time. Methods: The CANadian Pediatric Weight management Registry (CANPWR) is a multisite prospective cohort study of participants enrolled in a Canadian pediatric weight management clinic. Clinical program characteristics (e.g., referral process, inclusion criteria, funding, program characteristics, patient interaction methods, and follow-up) were collected at the start and end of the CANPWR recruitment period (2015-2019). Results: Entrance into the nine clinics varied with limiting criteria based on geographic proximity, age, weight status, and presence of health conditions. The clinics varied in size (50-220 new patients/year). The planned length of intervention varied widely, from 10 weeks to open-ended (median 2 years). Behavior modification strategies were delivered with a mix of individual and group-based sessions and most were delivered in person, complemented by use of virtual care. Over time, more clinics saw patients under the age of 5 years and all clinics defined a program length. Conclusion: Although all clinics offered family-based behavioral weight management services, these varied considerably, especially in program entrance criteria, size of clinic, and the length of intervention. The influence of the variability in delivery of services on health outcomes will be addressed in future studies.

Exploring Associations Between Children's Obesogenic Behaviors and the Local Environment Using Big Data: Development and Evaluation of the Obesity Prevention Dashboard

BACKGROUND

Obesity is a major public health problem globally and in Europe. The prevalence of childhood obesity is also soaring. Several parameters of the living environment are contributing to this increase, such as the density of fast food retailers, and thus, preventive health policies against childhood obesity must focus on the environment to which children are exposed. Currently, there are no systems in place to objectively measure the effect of living environment parameters on obesogenic behaviors and obesity. The H2020 project "BigO: Big Data Against Childhood Obesity" aims to tackle childhood obesity by creating new sources of evidence based on big data.

OBJECTIVE

This paper introduces the Obesity Prevention dashboard (OPdashboard), implemented in the context of BigO, which offers an interactive data platform for the exploration of objective obesity-related behaviors and local environments based on the data recorded using the BigO mHealth (mobile health) app.

METHODS

The OPdashboard, which can be accessed on the web, allows for (1) the real-time monitoring of children's obesogenic behaviors in a city area, (2) the extraction of associations between these behaviors and the local environment, and (3) the evaluation of interventions over time. More than 3700 children from 33 schools and 2 clinics in 5 European cities have been monitored using a custom-made mobile app created to extract behavioral patterns by capturing accelerometer and geolocation data. Online databases were assessed in order to obtain a description of the environment. The dashboard's functionality was evaluated during a focus group discussion with public health experts.

RESULTS

The preliminary association outcomes in 2 European cities, namely Thessaloniki, Greece, and Stockholm, Sweden, indicated a correlation between children's eating and physical activity behaviors and the availability of food-related places or sports facilities close to schools. In addition, the OPdashboard was used to assess changes to children's physical activity levels as a result of the health policies implemented to decelerate the COVID-19 outbreak. The preliminary outcomes of the analysis revealed that in urban areas the decrease in physical activity was statistically significant, while a slight increase was observed in the suburbs. These findings indicate the importance of the availability of open spaces for behavioral change in children. Discussions with public health experts outlined the dashboard's potential to aid in a better understanding of the interplay between children's obesogenic behaviors and the environment, and improvements were suggested.

CONCLUSIONS

Our analyses serve as an initial investigation using the OPdashboard. Additional factors must be incorporated in order to optimize its use and obtain a clearer understanding of the results. The unique big data that are available through the OPdashboard can lead to the implementation of models that are able to predict population behavior. The OPdashboard can be considered as a tool that will increase our understanding of the underlying factors in childhood obesity and inform the design of regional interventions both for prevention and treatment.

Evaluating Asthma Mobile Apps to Improve Asthma Self-Management: User Ratings and Sentiment Analysis of Publicly Available Apps

BACKGROUND

The development and use of mobile health (mHealth) apps for asthma management have risen dramatically over the past two decades. Asthma apps vary widely in their content and features; however, prior research has rarely examined preferences of users of publicly available apps.

OBJECTIVE

The goals of this study were to provide a descriptive overview of asthma mobile apps that are publicly available and to assess the usability of asthma apps currently available on the market to identify content and features of apps associated with positive and negative user ratings.

METHODS

Reviews were collected on June 23, 2020, and included publicly posted reviews until June 21, 2020. To characterize features associated with high or low app ratings, we first dichotomized the average user rating of the asthma app into 2 categories: a high average rating and a low average rating. Asthma apps with average ratings of 4 and above were categorized as having a high average rating. Asthma apps with average ratings of less than 4 were categorized as having a low average rating. For the sentiment analysis, we modeled both 2-word (bi-gram) and 3-word (tri-gram) phrases which commonly appeared across highly rated and lowly rated apps.

RESULTS

Of the 10 apps that met the inclusion criteria, a total of 373 reviews were examined across all apps. Among apps reviewed, 53.4% (199/373) received high ratings (average ratings of 4 or 5) and 47.2% (176/373) received low ratings (average ratings of 3 or less). The number of ratings across all apps ranged from 188 (AsthmaMD) to 10 (My Asthma App); 30% (3/10) of apps were available on both Android and iOS. From the sentiment analysis, key features of asthma management that were common among highly rated apps included the tracking of peak flow readings (n=48), asthma symptom monitoring (n=11), and action plans (n=10). Key features related to functionality that were common among highly rated apps included ease of use (n=5). Users most commonly reported loss of data (n=14) and crashing of app (n=12) as functionality issues among poorly rated asthma apps.

CONCLUSIONS

Our study results demonstrate that asthma app quality, maintenance, and updates vary widely across apps and platforms. These findings may call into question the long-term engagement with asthma apps, a crucial factor for determining their potential to improve asthma self-management and asthma clinical outcomes.