Systematic Evidence Review Oconnor Behavioral Treatment Pediatric Obesity
Review
Abstract
Background: Recent meta-analyses suggest the utilise of technology-based interventions equally a treatment choice for obesity in adulthood. Like 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 full, nine 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 subsequently intervention were considered equally main outcomes. In seven of eight studies, a technology-based intervention was practical in addition to conventional care. Of the 8 studies, 6 studies were conducted in the Us, 1 in Australia, and i in northwestern Europe. In full, 5 studies included adolescents, whereas the residuum addressed children anile 9 to 12 years. Intervention duration ranged from iii to 24 months. Significant differences betwixt groups in BMI metric changes were reported by 5 of the viii 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 divergence –0.36, 95% CI –0.83 to 0.eleven; P=.fourteen). 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 adequate technology-based approaches, in addition to conventional treatments, to enhance weight loss in young populations.
doi:ten.2196/30675
Keywords
Introduction
Groundwork
Excess weight in childhood and boyhood has remained one of the about important global public health challenges since emerging as a business several decades ago []. The urgent demand to reverse the class of childhood obesity has led to meaning growth in enquiry regarding the efficacy of babyhood obesity interventions []. Various interventions have been tested so far, from school-based interventions to comprehensive behavioral programs with multiple components, delivered past a multidisciplinary team [,]. Such models of handling—even when effective—are frequently inconvenient, burdensome, and inaccessible in some cases. New estimator- or mobile-assisted information and communication tools can provide useful ways to develop smart digital health interventions that could tackle babyhood obesity [,]. Data nerveless through internet-linked systems, electronic health records capturing clinical or demographic information, and sensors or smartphones tracking dietary behaviors provide the opportunity to generate useful knowledge regarding users' health, behavior, and progress [].
A previous meta-analysis with 83 randomized clinical trials (RCTs) has suggested the apply of technology-based interventions as a treatment option for obesity in adulthood with potential benefits in weight loss []. For children and adolescents, there is only 1 meta-analysis on eHealth overweight and obesity interventions, where parents or caregivers were the agents of change []. The meta-analysis included interventions, such equally behavioral websites with nutrition information, interactive vox response sessions, or telemedicine via videoconferencing. The fact that most of the eligible technological facilities lacked an interaction with users and the self-monitoring component is considered a limitation. Other meta-analyses examined the effect of web-based or mobile-based interventions on children commenting on modifications in obesogenic behaviors, such as sedentary lifestyle or unhealthy nutritional habits and not on core outcomes such as BMI [,]. Therefore, this systematic review and meta-assay examines the effect of technology-based interventions on overweight and obesity treatment in childhood and adolescence.
Objectives
The objective of this meta-analysis is to determine whether such interventions, delivered mostly on top of conventional care, could be more effective in improving the weight condition of children or adolescents with overweight or obesity compared with conventional care or no care. The research hypothesis in this written report is that technology-based interventions are effective in weight direction and in case of direct comparison with conventional intendance, at to the lowest degree equivalent to conventional intendance.
Methods
Search Strategy
Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2009 guidelines, a computer-assisted systematic literature search (not a registered protocol) was performed by 2 independent researchers (M Kouvari and M Karipidou) using MEDLINE (PubMed), Scopus, and the Cochrane Library for RCTs examining the effect of technology-based versus conventional interventions on weight direction of children and adolescents with excess weight. The search strategy was mainly based on Medical Subject Headings terms every bit follows: (obesity OR overweight OR body mass index OR weight OR diet OR diet) AND (mobile health OR ehealth OR mhealth OR mobile applied science OR Net OR cellular phone OR cellular phones OR smartphone OR telecommunications OR mobile applications OR web-based OR mobile apps OR portable electronic app OR portable software app OR text message OR SMS OR short bulletin service OR portable game OR computers, handheld OR PDA OR personal digital assistant OR social media OR social media health OR Twitter OR tweets OR Facebook OR Instagram OR mobile fitness apps OR online social networking OR virtual reality OR avatars OR online gaming OR video games) AND (pediatric OR child OR adolescent OR youth) AND (clinical trial OR pilot study OR randomized controlled clinical trial). The search was express to publications in English from January 1, 2000, to February 1, 2021. Reference lists of retrieved manufactures were also considered when these were relevant to the consequence examined yet not allocated in the basic search. The relevance of the studies was assessed using a hierarchical approach based on the title, abstract, and full manuscript.
Titles and abstracts of the identified studies were independently screened by ii researchers (M Kouvari and M Karipidou), and duplicates were removed. Full-text copies of papers were assessed for eligibility (Grand Kouvari and M Karipidou), with any disagreements resolved by a third researcher (EB). Information for each included study were extracted by 1 researcher (M Kouvari) and cleaned and checked by some other (Thou Karipidou). The ii researchers (Grand Kouvari and One thousand Karipidou) extracted data using a standardized extraction form to ensure that it adequately captured trial data. For papers in which additional information was required, the corresponding authors were contacted via e-mail.
Selection Criteria
Studies were selected based on the inclusion and exclusion criteria presented in .
Quality Assessment of Selected Studies
The quality assessment of the selected validation studies was independently implemented by 2 researchers (Thou Kouvari and 1000 Karipidou) using the Consolidated Standards of Reporting Trials statement []. Whatsoever differences were discussed, and a determination was fabricated past consensus.
Inclusion and exclusion criteria.
Inclusion criteria
- Study design: controlled clinical trials with at least one arm with a applied science-based intervention controlled by a second arm with a conventional intendance intervention or without any intervention
- Sample: children and adolescents with overweight or obesity (defined through BMI or validated growth charts) anile ≤eighteen years
- Intervention: engineering science-based intervention for children or adolescents with or without parents' or families' back up
- Effect: BMI, BMI z-score, and other BMI-related metrics (eg, BMI-SD score) at baseline, during the intervention, and at the postintervention phase were considered equally the main measurements for this meta-analysis
Exclusion criteria
- Review articles
- Letters to editors
- Editorials
- Manufactures based on studies with adults
- Manufactures providing only feasibility or acceptance level of the practical technology-based interventions or outcomes related simply to obesogenic behaviors
- Articles in which the technology-based intervention was practical only to parents
- Articles in which the control group included the use of technology
- Manufactures in which the technology-based intervention was non interactive with the user, for instance, telemedicine or it had only an informative grapheme, for example, a website
- Articles with inadequate statistical information
Outcome Size Measurements
The result of interest in this meta-assay was the deviation betwixt the web-based intervention and the control grouping with regard to the potential changes from cumulative frequency distribution in BMI or BMI z-score or BMI-SD score. Studies that reported BMI-related metric results equally change scores or baseline and final values; SD, SE, or CIs; and number of participants in each intervention group were included in the meta-analysis. The hateful alter was calculated where required, and SDs were calculated from SE or 95% CI where SD was non reported []. Finally, missing SDs of the changes from baseline were calculated using an imputed correlation coefficient [].
Data Analysis
Standardized mean departure (SMD) was used to enable the inclusion of BMI-related metrics in the same meta-analysis. In a written report that reported >i BMI metric, BMI was used. Pooled values of SMDs between the engineering science-based intervention and the control group and 95% CIs equally the recommended summary statistics of the effect size were calculated using either a fixed or random effects model. The stock-still effects model was used when sample heterogeneity was <50%, and the random effects model was used when heterogeneity was >50%. Heterogeneity assessed the null hypothesis that all studies evaluated the aforementioned consequence and was evaluated using the chi-square examination. Inconsistency (I two) was calculated to quantify the total variation consistent with interstudy heterogeneity, ranging from 0% to 100%. A P value of <.10 for the chi-square test and I 2 >fifty% reflected a significant heterogeneity []. Estimates of the effect size measures were weighted by the inverse of their variances. The random effects model (DerSimonian and Laid method) was used in the presence of heterogeneity. In contrast, fixed effects models were used to calculate effect size estimates for studies that lacked heterogeneity. Subgroup analysis of prespecified groupings was performed for the following study characteristics: duration of follow-up (3-24 months), parental involvement, and type of intervention (spider web based vs mobile based and others). In subgroup analyses, only the last follow-up values were considered. In studies with multiple follow-ups, only the concluding follow-up fourth dimension was considered for the estimation of the overall effect size. Possible publication bias was assessed using a contour-enhanced funnel plot of each trial's issue size confronting the SE. Funnel plot asymmetry was evaluated using the Begg and Egger tests []. Stata software, version 14 (StataCorp LLC) was used for all statistical analyses.
Results
Flow of Included Studies
A literature search catamenia diagram is presented in . Initially, 7245 papers were retrieved and selected for evaluation. Then, 6713 manuscripts were removed based on their titles and abstracts as they were irrelevant to the telescopic of this piece of work, accompanied past 340 duplicate records from multiple databases and searches that were also excluded. Amidst the rest (n=192), 9 manuscripts from 8 studies (ie, 2 separate articles were published based on 1 study regarding ii follow-up periods) were considered relevant; 183 manuscripts were excluded, equally they did not meet the inclusion criteria of this systematic review.
General Characteristics of the Selected Clinical Trials
The characteristics of the eligible clinical trials for this meta-analysis are presented in [-]. In total, 582 children and adolescents participated in the selected 8 studies with a range of cultural or ethnic groups, including African American, Chinese American, White, and others. Of the eight studies, half-dozen (75%) studies were conducted in the United States [-], ane (thirteen%) in Australia [], and ane (13%) in northwestern Europe (Netherlands) []. Moreover, 75% (6/8) of studies were conducted within the last decade [-,,], whereas the remaining 25% (2/viii) of studies were conducted earlier [-]. Nearly of the selected studies addressed adolescents [,,-], whereas the rest had children aged 9-12 years as the target group [,,]. The length of interventions ranged from 3 months [,,] to four months [], 6 months [,], and 24 months [-]. All studies were two-arm controlled clinical trials, in which technology-based interventions were controlled for ane conventional care intervention, except for two studies in which no intervention was implemented in the control group [,,].
Description of the Technology-Based Interventions
Of the 8 studies, four (50%) examined the effect of a mobile health (mHealth) intervention with or without sensors [,,,], 3 (38%) studies used a web-based intervention [,-], and i (13%) study used an SMS text messaging intervention accompanied by telemedicine []. Focusing on mobile-based interventions, they also addressed nutrition-related issues and unhealthy dietary behaviors [,,,], whereas in 38% (3/eight) of studies, physical activity and screen time were likewise taken into business relationship [,,]. In one study with web-based interventions, participants were enhanced to increment their physical activity level via a gamification method []. The other two web-based interventions, following a family-oriented approach, provided diet education accompanied past concrete action tips and counseling regarding salubrious trunk image [-]. The SMS text messaging intervention along with telemedicine and group sessions focused on weight loss and weight loss maintenance, covering bug from diet and physical activity to body paradigm and psychological well-being []. The level of parental interest varied among the selected studies. In 6 (75%) of the viii studies, there was participation of parents in the intervention group [-] accompanied by a similar participation of parents in the command group, with the exception of two (25%) studies [,]. In vii (88%) out of 8 interventions, a hybrid arroyo was followed, which means that the technological tools—of any kind—were examined as supportive of conventional intendance treatment [,-]. In vii (88%) of the 8 studies, in that location was support from health care practitioners, such as dietitians, physicians, pediatricians, and psychologists [-]. Participants in the intervention grouping (children or adolescents lonely or with their parents) attended weekly, biweekly, or monthly face up-to-face sessions with wellness professionals [,-] or videoconferences []. These sessions included goal setting, motivation techniques, individualized feedback based on the technology-based dietary or physical activity records, and enhancement to use the digital tools provided.
Primary and Secondary Outcomes of the Selected Clinical Trials
Different measures of weight status and adiposity were used in the selected studies, with most of them using multiple measures. In total, of the 8 studies, five (63%) used BMI z-score [-,], three (38%) used BMI [,,,], iii (38%) used BMI percentiles [,,,], 2 (25%) used trunk fat [,,], 1 (13%) used waist-to-hip ratio [], and 1 (13%) used BMI-SD score []. Other metrics included modifications in obesogenic behaviors, such as dietary habits [,-,-], concrete activity habits and/or screen time [,,,,], and physical examination or biochemical metrics [,]. All studies included psychological and cocky-efficacy metrics related to diet, physical activity, well-being, or good for you body paradigm. With the exception of 25% (two/viii) of studies [,], the remaining studies provided information on participants' satisfaction and compliance with the technology-based intervention.
Risk of Bias Within Selected Studies
The results of the risk of bias assessment for all included studies are summarized in . The selected eligible studies were of moderate quality, meeting on average, approximately half-dozen out of the 9 quality criteria. In particular, all studies except 1 had a well-documented randomization process []. In all studies, except for 1 study [], the baseline characteristics were presented. All studies used a valid method to assess the main outcome of interest, that is, BMI, whereas merely iv (44%) out of 9 studies reported blinded cess of the result of involvement [,,,]. All studies except one [] met the dropout rate cutting-off points (ie, ≤20% for <half-dozen months and ≤xxx% for ≥half dozen months). Regarding the quality of statistical analysis, on average, the selected studies met 2 out of 9 criteria. Specifically, all studies except 3 used intention-to-treat assay [,,]; all studies except 2 reported acceptable statistical ability [,], whereas merely 4 studies provided adjusted differences betwixt groups [-,].
| Characteristics | Study | ||||||||||||||||||
| | Chen et al [] | Vidmar et al [] | Staiano et al [] | Wright et al [] | Nguyen et al [] | de Niet et al [] | Doyle et al [] | Williamson et al [] | Williamson et al [] | ||||||||||
| Study blueprint | |||||||||||||||||||
| | Randomization described and conducted | ✓ | | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||
| | Baseline characteristics by grouping | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | | ✓ | |||||||||
| Result assessment | |||||||||||||||||||
| | Valid measurement of BMI | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |||||||||
| | Blinded outcome assessment | ✓ | | ✓ | | ✓ | | ✓ | | | |||||||||
| Dropout rate | |||||||||||||||||||
| | ≤xx% for <six months and ≤30% for ≥6 months | ✓ | ✓ | ✓ | ✓ | | ✓ | ✓ | ✓ | ✓ | |||||||||
| Statistical analysis | |||||||||||||||||||
| | Intention to treat for BMI outcomes | ✓ | | ✓ | ✓ | ✓ | | | ✓ | ✓ | |||||||||
| | Covariates accounted for in assay | ✓ | | ✓ | | ✓ | | | ✓ | ✓ | |||||||||
| | Power calculation reported and power adequate | ✓ | | ✓ | | ✓ | ✓ | ✓ | ✓ | | |||||||||
| | Summary results, adjusted difference between groups, and CI | ✓ | ✓ | ✓ | | ✓ | | | | | |||||||||
| Scoring | |||||||||||||||||||
| | Score in study design (range 0-2) | 2 | i | 2 | 2 | two | two | 2 | 1 | 2 | |||||||||
| | Score in effect assessment (range 0-2) | 2 | 1 | 2 | 1 | 2 | 1 | two | 1 | i | |||||||||
| | Score in dropout rate (range 0-i) | 1 | one | i | i | 0 | 1 | 1 | 1 | 1 | |||||||||
| | Score in statistical analysis (range 0-4) | 4 | i | iv | 1 | 4 | i | 1 | iii | 2 | |||||||||
| | Total score (range 0-9) | 9 | four | 9 | five | viii | 5 | 6 | 6 | 6 | |||||||||
aQuality assessment was performed based on the Consolidated Standards of Reporting Trials argument.
Separate Outcomes of Selected Studies
Overview
The separate outcomes of the eligible clinical trials are summarized in [-].
Weight and Adiposity Outcomes
Of the viii, 5 (63%) studies reported significant differences between groups in BMI metrics from baseline to the end of intervention [,,,,]. The intervention duration of these studies was >6 months, and all of them addressed non just children or adolescents simply also their parents. Significant reductions in trunk fat [] and waist-to-hip ratio [] were observed in interventions with a 2-year elapsing.
Diet-Related Outcomes
The 7 studies reporting modifications on dietary intake and behaviors revealed a pregnant divergence between groups with regard to improvement in at least one dietary consequence. In particular, a decrease in consumption of carbohydrate-sweetened beverages [], lower sugar intake [], increased fruit consumption [], decreased meat and fruit juice intake [], ameliorate adherence to a healthier dietary pattern [,], and lower consumption of food products with loftier-fat content [,] were observed.
Physical Activity–Related Outcomes
Among the five studies that provided input on changes in participants' physical activity level, 1 (20%) written report revealed a meaning decrease in screen time [], whereas the remaining 4 (fourscore%) studies highlighted increases in physical activity level in terms of hours per solar day or the intensity of exercise [,,,].
Physical Test and Biochemical Metrics
In 1 (50%) of the two studies with physical examination and biochemical measurements, meaning reductions in blood pressure and cholesterol levels were observed [].
Psychological Wellness–Related Outcomes
All studies provided input on the effect of technology-based intervention over the control group on participants' psychological wellness. Of the 8 studies, vii (88%) studies observed that participants in the intervention group increased their self-efficacy in relation to diet [,,] and physical activity [,,], decreased unhealthy eating behaviors related to dieting or weight or body prototype [,], and ameliorated their self-esteem [,].
Usability and Acceptability of the Technology-Based Intervention
Of the half-dozen studies providing data on the level of compliance of participants with the technology-based intervention, 5 (83%) reported moderate to high levels of usability and acceptability of the engineering science-based intervention [-,]. Even so, the added value of the engineering-based intervention over typical intendance was not articulate because the similar dropout rates between the ii groups (dropout rate in the intervention group: 12.9%, range 0%-41%, vs dropout rate in the control group: 12.half-dozen%, range 0%-36%; P=.96), excluding studies in which the control group had no intervention [,]. Among the 6 studies, 1 (17%) revealed that children assigned to the technology-based intervention receiving SMS text messages were less likely to withdraw from the study than children who did not receive this service [].
Synthesis of BMI-Related Outcomes
Overview
A meta-assay was conducted on pooled data from 9 manuscripts (8 studies in full), which compared applied science-based intervention groups with control groups. The meta-assay results are presented in -.
As presented in , a significantly higher decrease in the BMI-related metric was observed (SMD –0.61, 95% CI –1.x to –0.thirteen; P=.01). Compared with the other follow-ups, this was more evident later a 6-month follow-up in the technology-based intervention group when compared with the control group (SMD –0.37, 95% CI –0.72 to –0.03; P=.03), whereas a favorable effect of the technology-based interventions was also found after 24 months; however, statistical significance was not reached (SMD –0.31, 95% CI –0.63 to 0.02; P=.07).
Sensitivity Analysis
Of the 8 studies, 2 (25%) had a control group without whatsoever intervention. Hence, nosotros repeated the same analysis, excluding these two studies. The overall consequence remained significant (SMD –0.65, 95% CI –1.20 to –0.ten; P=.02), whereas the six-calendar month outcome remained marginally significant (SMD –0.32, 95% CI –0.71 to 0.07; P=.10).
A subgroup analysis was conducted based on parental involvement, and the results are shown in . The meta-analysis revealed a significantly higher decrease in the BMI-related metric in the technology-based intervention grouping than in the control group but in example of parental interest (SMD –0.39, 95% CI –0.59 to –0.18; P<.001). In the example of no parental interest, no significant difference between groups was observed (SMD –0.36, 95% CI –0.83 to 0.11; P=.14).
Some other subgroup analysis performed in this study was related to the blazon of technology-based intervention used. The results are shown in . Interventions were grouped equally web-based, mobile-based, and others. A statistically pregnant subtract in the BMI-related metric in the intervention group compared with that in the control group was observed both in the case of mobile-based and other interventions (SMD –0.89, 95% CI –1.15 to –0.64; P<.001) equally well equally in the instance of the web-based interventions (SMD –0.45, 95% CI –0.72 to –0.18; P=.001).
Discussion
Principal Findings
This meta-assay revealed that an intervention that combines conventional intendance with technological facilities could be an effective method for weight management of children and adolescents with overweight or obesity and is probably more than effective than conventional care alone. These observations were more evident in the example of interventions lasting at to the lowest degree six months. The selected studies included eHealth and mHealth technologies, such as interactive spider web platforms, mobile apps, gaming, and SMS text messaging with or without sensors and were accompanied or not accompanied past other contact forms such as telemedicine, emails, and informative websites. The focus of these technologies was more or less related either exclusively or in combination with improvement in dietary habits, enhancement of physical activity, or the increasing of users' self-monitoring potential. The type of technological means used in each intervention, that is, mobile-based or web-based, did not seem to change the final outcome. Parental involvement was related to greater outcomes of the intervention, particularly in children; however, it was not possible to isolate the split up contribution of parents to the final outcome.
Strengths and Limitations
To the best of our knowledge, this is the first meta-analysis to examine the effect of technology-based interventions on weight management in childhood and adolescence using strict eligibility criteria, such as the existence of a control—without any kind of applied science—group, the exclusion of technology-based interventions without an interactive—with the user—character, and the exclusion of studies providing the effect on weight-related metrics of normal-weight children or adolescents (obesity prevention spectrum). Nonetheless, several limitations exist, including the restriction to articles published only in English, the small number of clinical trials found with varying report quality, heterogeneity of the studies, inadequacy of the power to find an outcome in some studies because of the small number of participants, varying aims between studies, and all but 2 studies being conducted in the Us. Finally, no definite conclusion can be drawn on whether the actual difference in weight management was caused by the different techniques used or by the differences in other intervention characteristics (eg, number of sessions).
Comparison With Prior Piece of work
To date, technology-based health interventions for weight management in young people have been reported every bit a apace developing research area; although promising results have been produced, more research is definitely in lodge []. Hitherto, studies accept described technologies with the potential to promote good for you behaviors related to nutrition or physical activity in children and adolescents [,]. The pooled higher reduction in adiposity metrics observed in this study in favor of technology-based intervention groups were observed with improvements in users' dietary habits, physical activity level, and screen time and with improve psychological health regarding body paradigm, cocky-esteem, or weight- and dieting-related stress. Examining the bodily efficiency and added value of technology-based methods over conventional interventions in childhood obesity direction remains a challenging research field for many reasons. Most interventional studies combine eHealth or mHealth interventions with other mostly conventional treatments (hybrid arroyo), thus making the efficacy of technology-only approaches to affect adiposity outcomes difficult to ascertain [,]. In most studies selected for this meta-assay, the digital behavior change intervention was examined on top of conventional care and matched for conventional-only care, revealing an advantage of the old in weight loss. On the other hand, digital behavior change interventions accept non been generated to replace the role of health professionals and the multifaceted treatments required for direction of backlog weight in childhood and adolescence but rather to support them, showing potential every bit an additional tool for patient monitoring and designing tailor-made interventions through the selection of more than valid data and plausibly weight loss maintenance in the postintervention stage [,].
Another outcome examined in this study was related to parental involvement in engineering science-based interventions. Active enrollment of parents was reported in half dozen (75%) out of 8 studies [-], accompanied by a like participation in the control group, with the exception of ii studies [,]. Interestingly, ii-8 studies without parental involvement did not accomplish meaning modifications in adiposity metrics. Although many reasons could be responsible for this nonsignificance, such as the fact that lower combined sample size in the 2 studies could lead to greater CIs and college P values, this finding may imply that the participation of families in childhood obesity management programs remains of loftier importance fifty-fifty in or especially in interventions with advanced technological means. Currently, interventions that target parents to tackle obesity in early life stages are presented as effective, particularly when it comes to preschoolers, that is, children <5 years [-]. On the other paw, the studies in this meta-analysis were designed for children >9 years and principally adolescents, which may challenge the level of parental involvement. Preschool-aged children are rarely targeted in such technology-based interventions. The MINISTOP RCT is probably the very first study to apply a 6-month technology-based weight loss intervention to children <5 years, using their parents as the master target group. Although no pregnant differences in adiposity metrics between the command and intervention groups were observed, children and parents assigned to the technology-based group seemed to significantly ameliorate their nutrition and physical activeness habits []. Considering the fact that technological approaches and parental involvement are usually presented as constructive practices to tackle excess weight in babyhood, their combination into ane tailor-made weight loss intervention may issue in multiple positive outcomes.
The studies in this meta-analysis provided input on the usability and acceptability of technology-based interventions. Most of them reported a moderate to high level of adherence to the intervention using dissimilar criteria and metrics, such as the level of user enjoyment, the frequency of app use, or the number of SMS text messages received [-,]. Nevertheless, based on the dropout rates, no significant differences were observed between the intervention and control groups in most cases. This evidence regarding the usability of technology-based interventions is based largely on the employ of SMS text messaging using a mobile- or spider web-based approach. Nevertheless, the latest technological advances include the emergence of smartphone apps [], interactive platforms [], and exergaming []. Such facilities take increased in popularity, offering a unique opportunity to implement big-scale obesity treatment interventions in youth []. The current orientation for improving adherence to treatments in pediatrics focuses on motivation, problem-solving skills, and reduction of posttreatment influence, resorting to several novel youth-friendly technological approaches []. For instance, studies accept described the best placement and accuracy of mobile devices and sensors to record dietary intake or physical activity and ways to lessen user burden []. Reward-type incentives, provision of social connections and multiplayer capabilities, short- and long-term motivational techniques, and personalized feedback are also suggested equally ways to enhance user acceptability, efficiency of the intervention, and probably maintenance of positive outcomes even in the postintervention phase []. Focusing on gamification, many video games have been created with the aim to modify children'southward or adolescents' dietary habits or physical activeness status, such every bit Allow'due south Motion! (To move!), Counting Carbohydrates with Lenny, LeapBand, or Zamzee, where users interact with virtual characters that—creating a fascinating environment—enhance them to consummate a series of relevant activities and challenges []. Finally, early interest of key stakeholders in the intervention development stage seems to exist detrimental for the commitment of a technological tool that will be well-accepted by the target group—even more than when it comes to younger ages [].
Conclusions
Studies reported herein describe functional and acceptable technology-based approaches, on pinnacle of conventional care, to enhance weight loss in overweight or obese children and adolescents through the promotion of a healthy lifestyle and improvement of users' well-being. Still, the big heterogeneity in study designs, settings, intervention components, and outcomes probably eliminates the strength of this determination. Finally, this field is advancing so quickly that the technology used is ofttimes no longer country of the fine art; interventions that employ the total range of novel technologies, such as ubiquitous sensing and existent-time feedback, are currently beingness developed and pilot tested. Therefore, like meta-analytic approaches should be repeated on a regular ground.
Acknowledgments
This work has received funding from the Eu's Horizon 2020 Research and Innovation Plan through the NUTRISHIELD projection under grant understanding 818110. This paper reflects merely the authors' views; the European Union is not liable for any use that may be made of the data contained therein.
Conflicts of Involvement
None declared.
Multimedia Appendix 1
Characteristics of the eligible clinical trials of the meta-analysis (9 manuscripts and 8 studies).
DOCX File , 26 KB
Multimedia Appendix two
Primary and secondary outcomes of the eligible clinical trials of the meta-analysis (nine manuscripts and eight studies).
DOCX File , 24 KB
Abbreviations
| mHealth: mobile health |
| PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses |
| RCT: randomized clinical trial |
| SMD: standardized mean difference |
Edited by R Kukafka; submitted 24.05.21; peer-reviewed by P Henriksson, J Alvarez Pitti, J Lee; comments to author 30.07.21; revised version received x.09.21; accepted 22.09.21; published 14.02.22
Copyright©Matina Kouvari, Melina Karipidou, Thomas Tsiampalis, Eirini Mamalaki, Dimitrios Poulimeneas, Eirini Bathrellou, Demosthenes Panagiotakos, Mary Yannakoulia. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 14.02.2022.
This is an open-access article distributed nether the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/iv.0/), which permits unrestricted utilize, distribution, and reproduction in any medium, provided the original piece of work, commencement published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well equally this copyright and license information must be included.
Source: https://www.jmir.org/2022/2/e30675/
Post a Comment for "Systematic Evidence Review Oconnor Behavioral Treatment Pediatric Obesity"