A Rapid Review of the Impact of Family-Based Digital Interventions for Obesity Prevention and Treatment on Obesity-Related Outcomes in Primary School-Aged Children

Virtual delivery of obesity prevention and treatment programs may be effective for supporting children and families to adopt healthy lifestyle changes while enhancing program accessibility. This rapid review aimed to summarize the impact of family-based digital interventions for childhood obesity prevention and treatment. Four databases were searched up to February 2021 for trials of interactive digital programs aimed to prevent and/or treat obesity in children aged 5–12 years and reported diet, physical activity, sedentary behavior, sleep, or weight-related outcomes in children. A total of 23 publications (from 18 interventions) were included. Behavior change theories were used in 13 interventions with “Social Cognitive Theory” applied most frequently (n = 9). Interventions included websites (n = 11), text messaging (n = 5), video gaming (n = 2), Facebook (n = 3), and/or mobile applications (n = 2). Studies reported changes in body mass index (BMI; n = 11 studies), diet (n = 11), physical activity (n = 10), screen time (n = 6), and/or sleep (n = 1). Significant improvements were reported for diet (n = 5) or physical activity (n = 4). Two of the six interventions were effective in reducing screen time. Digital interventions have shown modest improvements in child BMI and significant effectiveness in diet and physical activity, with emerging evidence supporting the use of social media and video gaming to enhance program delivery.


Introduction
Childhood obesity is a global public health challenge of the 21st century and has been designated as one of the five key policy priorities of the World Obesity Federation. Evidence suggests that obesity is linked with an increased risk of complications and mortality from coronavirus disease 2019 (COVID- 19), which further adds to global health concerns [1]. Moreover, the need for self-isolation and/or quarantine during the COVID-19 pandemic is prompting many to rely on processed food with a longer shelf life (instead of fresh produce). Considering this, the ongoing burden of the pandemic threatens the risk of excessive weight gain. A report published by the Centers for Disease Control and Prevention [2] indicated that the body mass index (BMI) increment rates almost doubled between pre-pandemic and pandemic periods in children aged 2-19 years across all BMI categories, except those who were underweight. These findings highlighted the importance of preventing excess weight gain in children during and following the pandemic, as well as in the events of future public health emergencies, by increasing access to programs that promote healthy behaviors [2].
Conventional family-based obesity interventions are effective in promoting health behavior changes for children. These programs usually engage at least one parent and the child to encourage healthy behavior change by coaching parents in weekly, group-based sessions which focused on goal-setting, problem-solving, monitoring, and role-modelling healthy behaviors. However, the common barriers faced by participants include geographical distance, ease of access, time constraints, and weight-related stigma. Research suggests that web-based programs may be effective in supporting children and families to adopt healthy lifestyle changes while enhancing program accessibility [3]. COVID-19 has led to an increase in using online digital platforms for remote work, education, and healthcare [4]. Globally, there is a commitment to the development and implementation of digital health technologies for the detection, prevention, and treatment of disease, and the promotion of health and wellbeing. These technologies often include computers, websites, mobile applications (apps), short message services (SMS), digital games, telehealth, and wearables/monitoring devices. The potential scalable reach of these technologies provides a unique opportunity for the implementation of population-wide behavioral interventions.
The current literature has broadly investigated the acceptability and efficacy of technology-based interventions to improve clinical outcomes for children and adolescents [5] and its impact to facilitate communication between caregivers and health professionals in the clinical setting [6]. However, limited reviews of the literature to date have investigated the effectiveness of family-based digital interventions across various health outcomes in the context of obesity prevention or treatment for children. Due to the heterogeneity and differing methodologies employed by studies investigating the effectiveness of digital interventions to improve health outcomes [7], as well as the dynamic development and evolvement of digital technologies and their various applications, a rapid review methodology would be more appropriate than a thorough systematic literature review or meta-analysis [8]. Rapid reviews are useful in fields where change is ongoing, such as the development and advancement of digital technologies. This review utilized a simplified methodology based on a systematic literature review process to produce synthesized knowledge in a time-efficient manner [9]. The aim of this rapid review is to summarize the impact of family-based digital interventions for obesity prevention and treatment in children, with a specific focus on diet, physical activity, sedentary behavior, sleep, and weight-related outcomes in primary school-aged children.

Search Strategy
Peer-reviewed journal articles were searched in February 2021 in four electronic databases, including MEDLINE (1946 to present), CINAHL (1981 to present), PsycINFO (1806 to present), and Cochrane Library (including Cochrane Reviews, the Database of Abstracts of Reviews of Effectiveness, the Health Technology Assessment database). Handsearching of relevant outcome papers of eligible published protocols and the reference lists of relevant systematic reviews were performed to identify other potentially eligible studies. No language or geographical region restrictions were imposed. Unpublished studies or grey literature publications (conference proceedings, blogs, theses, and dissertations) were excluded from this review.
A list of search terms was developed based on previous reviews [10,11], presented in Supplementary Table S1 (see supplementary materials). In brief, the search terms and combinations used were as follows: Family (family OR parent OR carer OR mother OR father) AND child (child OR children OR young person NOT infant) AND digital intervention (online program OR digital tool OR multimedia OR app OR website OR eHealth OR mHealth) AND interactive component (gaming OR music OR animation OR interactive) AND obesityrelated outcomes (body mass index OR waist circumference OR nutrition OR physical activity OR sleep).
Web searching was performed in February 2021 to identify digital interventions for obesity prevention and treatment in children, which may not have been indexed or published in the databases searched. The Cochrane Handbook for Systematic Reviews of Interventions [12] recommended that web searching should use a combination of search engines and websites to ensure a wide range of sources are identified and searched in depth. Google Search and Google Scholar were used to search for websites of digital interventions, online programs that were known to the researchers, and associated publications that may be relevant to this review. Due to the basic search interfaces of the search engines, a combination of simplified and natural language key terms, based on the search terms used for searching bibliographic databases (child obesity online prevention program, an online healthy lifestyle program for families), were used. The search was limited to the first 30 hits sorted by relevance.

Study Design
The review included studies with a parallel control group, including randomized controlled trials (RCTs) and cluster RCTs; quasi-RCTs and cluster quasi-RCTs; controlled before and after studies (CBAs) and cluster CBAs; controlled time series designs. Observational studies, such as longitudinal cohort studies and cross-sectional studies were excluded. Studies could be published in any language or geographic region. Only studies that: (1) compare an online/digital intervention with no intervention or "usual practice" control group, or (2) compare two or more online/digital interventions which aim to improve obesity-related outcomes in children were included. Studies without a comparison arm were excluded.

Participants
Eligible studies involved children who were aged 5-12 years and generally healthy, and/or their parent(s) (i.e., carers, caregivers, guardians). Participants could be grouped as follows: children and parents, whole family, parents only, or child only. Studies that involved children aged below five years, pre-natal or ante-natal, infants, those aged above 12 years (adolescents), or those with chronic health conditions, were excluded.

Interventions
The conditions of interest were interactive digital programs for obesity prevention and treatment interventions in children targeting diet, physical activity, sedentary behavior, sleep, or weight-related measures. Any prevention and/or treatment intervention that aimed to improve obesity-related outcomes in children and was delivered to participants using a digital and/or an online platform as a standalone intervention or in combination with a non-digital/online component was included. The platform may include websites, mobile apps, SMS, and other online mediums. Interventions were excluded if they were telephone-based or included phone coaching or in-person face-to-face interventions without a digital/online component. The digital component of interest was the use of interactive multimedia content in the interventions for visual storytelling and/or play-based learning. Examples include the use of games, gamification, music, and/or animation. Given the novelty of this research area, studies were included where authors reported the use of a digital and/or online platform, and a standard data extraction template was used to collect information related to the use of interactive multimedia content included in the interventions.

Outcomes
The main outcomes were any measure of the change in a child's weight, BMI, waist circumference, diet, physical activity, sedentary behavior, screen time, and/or sleep from baseline to the last available follow-up, to assess intervention impact on child obesityrelated anthropometric and/or behavioral health outcomes. Most of the outcome variables were continuous data, such as BMI and waist circumference, and were expressed as mean difference and standard deviation, and/or confidence intervals. Where categorical outcome data were reported, for example, whether participants improved dietary habits by eating breakfast every day, the effect measures were expressed as the proportion of participants who ate breakfast every day in the intervention group vs the control group.

Settings
Studies undertaken in family-based or home-based settings were included. Schoolbased and hospital-based studies and experiments in a controlled environment were excluded.

Study Selection
Two review authors (Leila Fathi and either Rebecca Farletti or Li Kheng Chai) screened abstracts and titles independently for eligible studies. Review authors were not blinded to author or journal information. The screening was performed using a standardized screening tool developed by the author team experienced in conducting systematic reviews based on the Cochrane Handbook for Systematic Reviews of Interventions [12], with reference to the Rapid Reviews to Strengthen Health Policy and Systems: a Practical Guide published by World Health Organization (WHO) [13]. The full texts of potentially eligible studies were retrieved for further screening. Conflicts between review authors regarding study eligibility were resolved by a third review author.

Data Extraction
Data from the included trials were extracted and checked by two review authors (Leila Fathi and Rebecca Farletti). Conflicts between review authors regarding extracted data were resolved by consensus and via a third review author where required. Extracted data included study characteristics (aims and objectives, study design, number of experimental conditions, targeted participants demographic characteristics, country, intervention description and duration, behavior change theory/techniques used, and overall conclusion); study outcomes, including the data collection method, the validity of instruments/measures used, effect size and measures of outcome variability; and source(s) of research funding and potential conflicts of interest.

Quality Appraisal
Critical appraisal was performed by two review authors (Li Kheng Chai and Robyn Littlewood) independently using the Joanna Briggs Institute Critical Appraisal Tools, including Checklist for Randomized Controlled Trials [14]. The critical appraisal tool that has previously been used by the author team in other systematic reviews, was adapted for use in this review and was piloted before use. A risk of bias classification ("high", "low" or "unclear") was assigned for each of the following study characteristics: sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessors, incomplete outcome data, selective outcome reporting, outcome measure reliability, trial design, and "other" potential sources of bias. Additionally, a criterion for "potential confounding" was included for the assessment of the risk of bias in non-randomized trial designs. An overall risk of bias classification was assigned to each study, giving consideration to all such study characteristics. Conflicts between review authors regarding the methodological quality of studies were resolved by consensus and via a third review author where required.

Data Synthesis
It was anticipated that differences in measures and study outcomes reported in the included studies may preclude the use of summary statistics to describe treatment effects and also necessitate a narrative synthesis. However, whenever possible, the relevant outcomes were synthesized and the effect measures were summarized including the child's weight, BMI, waist circumference, and other anthropometry outcomes; diet, physical activity, sedentary behavior, sleep, and other obesity-related behavioral outcomes.

Study Selection
The study selection process is presented in an adapted Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram [15] presented in Figure 1. The database searches identified 362 records for the title and abstract screening against the inclusion criteria, followed by 40 full texts retrieved for further screening, which resulted in the final inclusion of 23 publications (from 18 interventions) in this review. The majority of the 17 excluded publications were primary studies with irrelevant study designs (n = 11). A list of excluded studies and reasons for exclusion are presented in Supplementary Table S2 (see supplementary materials). and also necessitate a narrative synthesis. However, whenever possible, the relevant outcomes were synthesized and the effect measures were summarized including the child's weight, BMI, waist circumference, and other anthropometry outcomes; diet, physical activity, sedentary behavior, sleep, and other obesity-related behavioral outcomes.

Study Selection
The study selection process is presented in an adapted Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram [15] presented in Figure  1. The database searches identified 362 records for the title and abstract screening against the inclusion criteria, followed by 40 full texts retrieved for further screening, which resulted in the final inclusion of 23 publications (from 18 interventions) in this review. The majority of the 17 excluded publications were primary studies with irrelevant study designs (n = 11). A list of excluded studies and reasons for exclusion are presented in Supplementary Table S2 (see supplementary materials). Web searching identified five additional digital interventions for obesity prevention and treatment in Australian children. Brief descriptions and characteristics of these interventions are presented in Supplementary Table S3 (see supplementary materials). The interventions predominantly used websites, telehealth coaching, and mobile apps as digital Web searching identified five additional digital interventions for obesity prevention and treatment in Australian children. Brief descriptions and characteristics of these interventions are presented in Supplementary Table S3 (see supplementary materials). The interventions predominantly used websites, telehealth coaching, and mobile apps as digital delivery methods. Only one of these interventions, i.e., the Kurbo app by WW International (formerly known as Weight Watchers International) has published evaluation findings; however, the study was a retrospective cohort study without a comparison arm [16]. The searches did not retrieve any other peer-reviewed publications which reported the acceptability, usability, or effectiveness of these interventions on obesity-related outcomes. As such, these interventions were excluded from the synthesis. Table 1 presents the results of the quality appraisal for the 18 interventions [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34] included in the review. Overall, the majority of the studies were of moderate to high quality (i.e., meeting at least nine of the thirteen criteria). The studies have reported an adequate randomization procedure (n = 13) and concealment of group allocation (n = 11), while the two studies did not describe the randomization procedure, nor the allocation concealment. Blinding of participants was not reported in eight studies and deemed not possible in four studies due to the nature of the intervention study design (e.g., waitlist control). Only six studies were rated low in risk of bias related to blinding of participants to treatment assignment.

Quality Appraisal
Yes, N: No, U: Unclear, NA: Not Applicable. Q1. Was true randomization used for the assignment of participants to treatment groups? Q2. Was allocation to treatment groups concealed? Q3. Were treatment groups similar at the baseline? Q4. Were participants blind to the treatment assignment? Q5. Were those delivering treatment blind to treatment assignment? Q6. Were outcome assessors blind to the treatment assignment? Q7. Were treatment groups treated identically other than the intervention of interest? Q8. Was the follow-up complete and if not, were differences between groups in terms of their follow-up adequately described and analyzed? Q9. Were participants analyzed in the groups to which they were randomized? Q10. Were outcomes measured in the same way for treatment groups? Q11. Were outcomes measured in a reliable way? Q12. Was appropriate statistical analysis used? Q13. Was the trial design appropriate, and was any deviation from the standard RCT design (individual randomization, parallel groups) accounted for in the conduct and analysis of the trial?
Blinding of intervention providers was not applicable to three studies where the interventions were web-based modules accessible by participants independently without needing an intervention provider. Additionally, blinding of intervention providers was not possible in six studies due to the nature of the study design (e.g., waitlist control commenced intervention at a later time). The blinding of outcome assessors was mixed in the included studies, where five studies were rated a high risk of bias and six studies were rated as unclear. In studies where BMI was reported, actual height and weight measurements were recorded by research staff using standardized protocols. However, one included study, conducted by Rangelov et al., used parent-reported child height and weight and presented outcomes as a percentage of weight categories (e.g., % healthy weight, % overweight/obesity) instead of BMI changes. All studies used a validated instrument tool when measuring weight, physical activity, diet, sedentary behavior, and/or sleep. The intention-to-treat statistical approach was applied in 11 studies using the last observation carried forward or multiple imputation method, including two studies that had 22% and 59% drop out rates, respectively.

Study Characteristics
All studies included parent-child dyads with the majority of children (n = 1693 of 2053) aged between 9-11 years. One study specifically focused on mothers [25], while another focused on fathers [27]. Among the included interventions, 10 were "treatment focused" that targeted children who were overweight or have obesity, and the remaining eight were "prevention focused" that targeted children in all weight categories, including one intervention that targeted children in the healthy weight category. Most of the studies (n = 13) were published in the last five years. The studies were conducted in eight countries including Belgium, Malaysia, Sweden, the USA, New Zealand, Australia, Canada, and Switzerland. Overall, the study period ranged between 4 and 20 weeks in duration, with the longest follow-up being between two months and two years from baseline. A total of 14 studies reported ≤ 20% dropout rate at follow-up, and the remaining four studies had a dropout rate that ranged between 22% to 59%. Demographic characteristics of families included in the studies and a summary of interventions are presented in Table 2. Further details on study aims, participant characteristics, attrition rates, intervention use, and theoretical framework are presented in Supplementary Table S4 (see supplementary materials).  Most significant intervention effects were found for more complex parenting practices (e.g., an increase in motivating the child to eat fruit). Subgroup analyses showed that the intervention had more effect on the actual parenting practices related to PA, screen-time, and healthy diet in parents of older children (10-12 years old), whereas intervention effects on parental self-efficacy related to those behaviors were stronger in parents of younger children (6-9 years).  10 weekly face-to-face 90 min sessions, four community-based activities (i.e., family grocery store tour), and an interactive web-portal. Children's BMI z-scores were not significantly changed. The intervention group significantly improved their days of moderate-to-vigorous physical activity relative to control; however, child dietary behaviors were not significantly changed. Relative to control, intervention group showed significant improvements in physical activity. Prevention RCT 608 parent-child dyads. Children (mean age of 8.5 years) were in the first two years of secondary school and about equal proportion of boys and girls.
8 weeks access to website (parents) and a personalized and tailored letter by post (children). The emails (INT 1) and mobile text messages (INT 2) were used as weekly reminders to prompt parents to visit the Website. The email also provided a short summary of the weekly theme.
I Website (weekly nutrition content and a forum for participants discussion together and with a dietitian) I Emails and mobile text messages were sent as weekly reminders to prompt parents to visit the website.
Overall, the intervention effects were not significantly different across groups. Children increased their daily consumption of fruit and decreased that of sweets regardless of the group they were assigned.

Theoretical Framework
Behavior change theories (BCT) were used in 13 interventions with "Social Cognitive Theory" (SCT) applied most frequently (n = 9) [17][18][19]22,23,[25][26][27]30]. The SCT theorizes behavioral outcomes (e.g., child behavior change) as a reciprocal interaction between the person (e.g., child) and environmental factors (e.g., home and family unit) [17]. Interventions focused on elements of behavior capability in parents, such as self-monitoring, goal setting, self-efficacy, problem-solving, relapse prevention, and stimulus control [17,18,23]. Similarly, a study by Knowlden et al. focused on the environment, emotional coping, expectations, self-control, and self-efficacy of parents [25]. Other interventions also focused on creating a shift in attitudes toward healthy behavior among parents [22] or the family unit [23]. Ahmad et al. encouraged parents to practice authoritative parenting skills, consistent with Wald et al., and focus on self-efficacy of the child's healthy behaviors in addition to the elements of behavior capability in parents [17,33].
Nine studies incorporated one or more other behavior change theories, some in conjunction with SCT, when designing the intervention [22,23,26,27,30]. For example, Jake et al. incorporated elements of Family Systems Theory with SCT and conceptualized parent-child relationships in the context of reciprocal interactions [23]. Morgan et al. and Wald et al. incorporated Self-Determination Theory, which suggests that three basic psychological needs (autonomy, competency, and relatedness) must be satisfied to foster well-being [27,33]. Chai et al. and Perdew et al. used a different behavior change framework underpinned by constructs similar to SCT: attitude, motivation, self-efficacy, opportunity, behavioral regulation, identity, and habit [20]. Rangelov et al. used the Social Marketing Framework incorporating all six elements of the marketing mix: product, place, price, promotion, policy, and partnership.
The use of BCT was not reported in five studies [21,24,31,32,34]; however, two of the studies [32,34] described intervention strategies that were aligned with SCT, including goal setting, reinforcement, modeling, changing the home environment, problem-solving, and/or behavioral contracting.

Intervention Components and Usage
Interventions included in this rapid review facilitated delivery via websites (n = 11) [18,20,21,23,24,26,[28][29][30]33,34], text messaging (n = 5) [18,20,24,29,31], Facebook (n = 3) [17,18,20], mobile apps (n = 2) [24,31] and/or video gaming (n = 2) [30,32]. Websites were used for providing additional resources to complement the in-person group sessions on topics, such as healthy living, physical activity, and recipe ideas [28,34]. Some intervention websites included an online discussion forum [25,28,29,33] to engage parents in sharing their challenges and successes while offering a forum for parents to ask questions [33]. Websites were also used for goal setting and self-monitoring, where families may log activities and track progress with an interactive graph [23,34]. Jake et al. reported high adherence to self-monitoring protocols with parents and children using the website for step and food logs [23]. A study by Williamson et al. provided instant feedback after parents completed online worksheets and quizzes involving self-reported health behavior [34].
Intervention websites provided content in the form of short videos [22], audiovisual presentations [25], or narrated graphic stories [21]. Studies reported moderate to high utilization of websites, ranging from around 86% to 93% of participants accessing the content [21][22][23], except for Rangelov et al. who reported 39% to 46% of participants visiting the website despite weekly email and SMS reminders. Evidence suggests that websites with interactive features have higher engagement rates compared to those with non-interactive content (e.g., texts and pictures) [34], which may explain the lower website usage rates in Rangelov et al.
An emerging number of studies have used apps and/or social media platforms to boost participant engagement with the intervention content. Two interventions used a combination of website, social media platforms, and text messaging which achieved high utilization rates with 77% to 86% of families accessing the website regularly [18,20]. Tuesdays had the highest number of website visits and 16:00 was the most popular time on most days [20]. Many parents also preferred a weekly text message on earlier days of the week, such as Monday (40%) and Tuesday (36%) [18]. To encourage long-term behavior maintenance, a study provided families with access to an app at the conclusion of the in-person group program, which included a variety of fun physical activities for families to complete and track together weekly. The app was used by 83% of families [27]. Another study [31] reported that 71% of families used the app at least two times per week, including 35% who used it at least three times a week. Studies reported higher rates of participation in WhatsApp and/or Facebook sessions compared to in-person sessions and websites [18]; indicating that a social media approach may enhance participation. Some parents also noted interaction among Facebook participants as an important feature [18].
Other interventions have used technological devices including a screentime monitoring device to help budget family media use (but 46% of parents reported never using the device to budget their child's television or computer use) [26], and a Bluetooth weighing scale with no displays to indicate weight readings together, with a wrist-worn activity monitor that was connected to a gamified app that encourages physical activity (in which 80% of children participated) [24]. Two other interventions incorporated gamification in the form of video games and reported 76% to 91% participation rates [32].

Anthropometry
Studies predominantly reported anthropometric outcomes in BMI, BMI z-scores (zBMI), waist circumference, and body fat percentage. Intervention effects on child anthropometry reported in the included studies were mixed. Eight studies (n = 587 families) [18][19][20][26][27][28]33,34] reported that the changes in BMI, zBMI, and/or waist circumference were not significant. Only three studies (n = 207) [17,24,32] reported that BMI z-scores were significantly reduced in the intervention group compared to the control group and all these three studies were 'treatment focused' with one of these studies (n = 122) [17] also reported significant decreases in waist circumference percentile and body fat percentage in the intervention group.

Dietary Intakes
Overall, 11 studies have reported dietary outcome measures via food group consumption and total energy intake. Fruit and/or vegetable intakes were the most frequently reported in the studies [18][19][20][21][22][23]25,[28][29][30], followed by sugar-sweetened beverages (SSB) [19,[21][22][23]25,28,29]. Studies reported food and/or drink intakes in varying units, including frequency per day, frequency per week, portions per week, or standard serves per week. Mixed findings were reported on child dietary behavior where six studies (n = 313) [19,[21][22][23]28,34] reported that the changes in fruit, vegetable, and/or SSB intakes were not significant compared to five studies that reported significant improvements. Intervention groups in four studies (n = 533) [18,20,25,30] showed a significant increase in healthy foods/food group consumption post-intervention with a decrease in SSB or discretionary food (e.g., fast food) intake. One study (n = 608) [29] found that families who received an SMS intervention had reported improved dietary intake for vegetables, but not for fruit, sweets, SSB, and water.

Physical Activity
Among the 10 studies which measured physical activity, the six studies (n = 433) [19,20,22,23,26,31] reporting intervention effects were not significant when com-paring the physical activity scores, step counts, or minutes of active transportation between groups. Four studies (n = 297) [25,27,28,32] reported a significant increase in physical activity levels or step counts post-intervention.

Screen Time/Sedentary Behavior
Two of the six studies [22,[25][26][27][28]33] that reported child screen time showed a significant intervention effect [25,27] on decreasing screen time at post-intervention and follow-up. The two studies (n = 175) [25,27] were delivered as a knowledge-based healthy lifestyle intervention focusing on one or more changed behaviors and they each included a weekly group session and web-based materials. While two other studies (n = 92) [28,33] used similar intervention modalities (i.e., weekly group sessions and websites), the changes in screen time were not significant.

Sleep
Sleep outcome was reported in only one study [26] that focused on reducing leisure time screen-based sedentary behavior in children (n = 238) aged nine to 12 years, delivered over 20 weeks. A key focus was to train the primary caregivers to initiate change in the home environment, implementing behavior change strategies with an aim of facilitating behavioral change in the child. However, the changes in sleep duration (minutes/day) between groups from baseline to six months follow-up were not significant. This lack of effect may be explained by the bias associated with self-report measures and/or poor compliance, where 46% of parents reported never using the screen time monitoring device to budget their child's television or computer use [26].

Discussion
The COVID-19 pandemic has impelled the potential of using online platforms for day-to-day tasks, such as remote work, videoconferencing, telehealth, and food ordering services. Online platforms and digital solutions are no longer unfamiliar to many and have increasingly demonstrated the potential for use in health promotion and prevention. This rapid review aimed to summarize the impact of family-based digital interventions for obesity prevention and treatment, with a focus on diet, physical activity, sedentary behavior, sleep, and/or weight-related outcomes in primary school-aged children.
Digital intervention for family-based childhood obesity prevention and treatment is an emerging research area with increased publications over the last five years. The interventions have shown promising preliminary results with modest improvement in child BMI, diet, and physical activity. Similar findings were reported in a systematic review [35] that examined the effectiveness of mobile apps aimed at obesity prevention in children aged eight to 12 years and suggested that apps for health behavior promotion interventions may potentially improve health behaviors among children, but their effectiveness in improving anthropometric measures remains unclear. When comparing the results between studies, it is important to consider the various quantifying units used in measuring dietary intake and physical activity. The lack of consistency in measuring and reporting approaches in behavioral studies such as these has hindered further analysis to be conducted to make a comprehensive review.
A scoping review [36] of E&M Health interventions (defined as the use of information and communications technology, especially Internet (web), text messages with SMS, smartphone apps, and social media to monitor, improve or enable health behavior or health care) for childhood obesity reported that weight, physical activity, and diet were frequently assessed, while limited reviews have focused on sedentary behavior. The current rapid review included sedentary behavior and found six studies that reported child screen time, in which two of the studies showed significant screen time reduction after the intervention. However, the evidence around screen time and sleep remains scarce. Only one study [26] included in the current review has reported sleep outcomes but the between-group differences were not significant. Similarly, a systematic review identified that only eight trials included a sleep component in obesity prevention interventions and that evidence on sleep intervention research is limited. Thus, the potential impact of sleep on childhood obesity remains unclear [11].
Interventions included in this review used websites, text messaging, Facebook, mobile apps, and/or video games, incorporating digital interactive elements and/or gamification. Research suggests that virtual delivery utilizing gamification can be effective in increasing the acceptability and accessibility of health interventions, thus, more readily supporting children and families to adopt healthy lifestyle changes [5]. A systematic review found that gamification, behavioral monitoring, and goal setting were common features of mobile apps aimed at childhood obesity prevention [35]. However, the reporting of process indicators, such as attendance tracking, participation, and retention rates were limited [35]. This rapid review found digital approaches are acceptable and positively received by families, with high participation rates.
There was emerging evidence of the use of social media and gamification to support program delivery. In line with established theories of intrinsic motivation [37], interactive digital components can employ motivational features such as goal setting, and real-time feedback through interface elements such as point scores, badges, levels, challenges, social support through leaderboards, teams and communication functions, and autonomy through customizable profiles and user choice in goals and activities [38,39]. Another study found that interventions using gamification to target nutrition behaviors among children and adolescents increased program adherence, knowledge, self-efficacy, and nutrition-related health behavior in the short term [39]. Similarly, interactive social media interventions reported improvements in overall wellbeing and were effective in improving physical activity among adults [40]. However, the effectiveness, dose of meaningful engagement (e.g., click-through rates, posts, comments), and sustainability of these novel approaches require further studies, given the limited existing evidence [41].
Despite several digital interventions for childhood obesity that were accessible in online marketplaces to the wider public in Australia, only one program targeted prevention while the remaining four programs focused on weight loss treatment or weight management. It is unclear whether the market programs have peer-reviewed evidence or rigorous evaluation to support their usability, acceptability, or effectiveness. This raises concerns regarding the quality and credibility of readily accessible programs on the internet. The limited evaluation findings of existing programs present a missed opportunity to advance the evidence base around digital interventions for childhood obesity, exchange learnings between peers, and inform future interventions. Thus, there is a research-practice gap that limits the availability of evidence-based childhood obesity prevention and treatment programs in the public domain, and more support is needed to enhance the translation of effective interventions into population health benefits.
A limitation of the current rapid review was the inclusion of just four electronic databases in the search strategy, unlike systematic reviews which usually search more databases. The search terms around digital and interactive interventions used in this rapid review were broad and less exhaustive, however, the lack of standard definition in this emerging field has contributed to the complication. Despite the rapid review design, the methodological rigor was upheld by including the quality appraisal of the included studies and the use of two independent reviewers across the screening phases, while applying the WHO practical guide for rapid reviews [13]. A strength of the current rapid review was the web searching of marketplace digital interventions for obesity prevention and treatment in children which may not have been indexed or published in the databases searched. The current rapid review also included sedentary behavior and sleep which were rarely included or reported in reviews. The rapid review also reported on the digital components of interventions and process indicators, such as intervention usage and engagement rates where available, instead of focusing solely on the efficacy results regarding behavior change which were commonly reported in other reviews.
Australia has committed to the WHO global target to halt the rise in obesity and being overweight, and recently released the National Obesity Strategy-a 10-year framework for action to prevent, reduce, and treat obesity and being overweight in Australia. The strategy has been agreed upon by Australian State and Territory Governments and has advocated for early intervention services to consider various delivery modes, including telehealth and other digital technology, that are affordable and accessible for all. For example, the Queensland Government has established a dedicated prevention agency, Health and Wellbeing Queensland, which will lead the statewide implementation of the National Obesity Strategy and drive innovative solutions to combat obesity. Evidence presented in the current rapid review supported the recommendations for virtual intervention delivery utilizing digital approaches, interactive elements, and/or gamification. However, more research is warranted to better understand how virtual delivery may impact screen time and sedentary behavior, the optimal dose and engagement for health behavior change, and whether educational screen time and discretionary screen time contribute to health and behavior outcomes differently. Future research assessing the effectiveness of digital interventions on improving sleep is needed, considering the limited research despite evidence suggesting sleep is associated with overweight and obesity in children [11].

Conclusions
In conclusion, family-based digital interventions for childhood obesity prevention and treatment were acceptable and well-received by families. The findings of the review suggest that digital interventions have shown some improvements in child BMI, diet, and physical activity, however, statistically significant results were mixed. The evidence around screen time and sleep remains scarce due to limited studies available. There is emerging evidence of the use of social media and gamification in digital interventions. However, further research is warranted to understand its long-term effectiveness and sustainability, and whether a blend of virtual and in-person approaches could be the recommended best practice for the future. Such approaches must consider the need for prevention and treatment interventions to be adaptable in response to unforeseen crises, such as a global pandemic.
Supplementary Materials: The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/nu14224837/s1: Table S1: Search terms; Table S2: List of excluded studies and reasons for exclusion; Table S3: Interventions available on marketplace (identified from web searching); Table S4: Characteristics of included studies; Table S5: Intervention effects on child outcomes.
Author Contributions: Conceptualization, L.K.C. and R.F.; methodology, L.K.C. and R.F.; data collection and extraction, L.K.C., R.F., and L.F.; data analysis, L.K.C. and R.L.; writing-original draft preparation, L.K.C.; writing-review and editing, R.F., L.F., R.L. All authors have read and agreed to the published version of the manuscript.