Personalised eHealth interventions in adults with overweight and obesity: A systematic review and meta-analysis of randomised controlled trials

Effectiveness of digital health applications on the quality of life in patients with overweight or obesity: a systematic review

BACKGROUND

Globally, more than half of the adult population is overweight, including those who are obese, which increases the risk of premature death and reduces quality of life (QoL). Technologies such as digital health applications (DiHA) can potentially improve clinical outcomes (e.g., health status, illness duration, QoL) or patient-related factors (e.g., therapy monitoring, adherence, health literacy). To date, there is no systematic review addressing the effectiveness of DiHA on the QoL in patients with overweight or obesity.

OBJECTIVE

The objective was to investigate the impact of DiHA on QoL in overweight or obese patients.

METHODS

A systematic literature search was conducted in MEDLINE via PubMed, Cochrane Library, and Embase via Ovid in 2023, supplemented by additional manual searches. The eligibility criteria included patients with overweight and/or obesity who used a digital intervention independently and without interaction with a healthcare professional. The outcome of interest was QoL. As potentially eligible trials had to demonstrate effectiveness, only randomized controlled trials (RCT) were included as the minimum evidence standard. The study screening (title-abstract, full-text) was conducted independently by two researchers using pre-specified eligibility criteria. CONSORT-EHEALTH checklist was used for data extraction of qualitative and quantitative data (study characteristics and study results) and the Cochrane Risk of Bias Tool (version 2) for quality assessment independently by two researchers.

RESULTS

Seven RCT conducted in Europe and the United States were included in this systematic review with a total sample size of N = 946. Observation periods were heterogeneous and ranged from 3 to 24 months. The evaluated interventions consisted of websites or apps, all of which included nutrition and physical activity features, and functioned independently with minimal or no involvement of a healthcare professional. All studies showed a high risk of bias, no statistically significant improvement and no effects regarding QoL using different validated questionnaires.

CONCLUSIONS

This systematic review provides a comprehensive analysis of DiHA effectiveness on QoL in patients with overweight or obesity. Overall, there is heterogeneity regarding the operationalization of QoL and the examined interventions have no statistically significant impact on QoL. Comparable systematic reviews show that digital interventions have the potential to improve the QoL of these patients, but further RCT and high-quality studies are needed to assess the impact of DiHA on QoL.

TRIAL REGISTRATION

PROSPERO CRD42023408994.

Umbrella review of social inequality in digital interventions targeting dietary and physical activity behaviors

Digital interventions are increasingly utilized as a lever to promote population health, yet not everyone may equally benefit from them. This umbrella review pooled the insights from available systematic and scoping reviews regarding potential social inequalities in digital intervention uptake, engagement and effectiveness, focusing on the promotion of weight-related behaviors (diet, physical activity, sedentary behavior) and weight loss (maintenance) in adults. Six databases were searched from 1970 to October 2023. Forty-six reviews were included, of which most focused on physical activity and intervention effectiveness. Age and gender/ sex differences were most frequently studied. Most reviews found digital interventions to be effective irrespective of age, while men benefitted more from digital interventions than women. Other inequality indicators (e.g., income, education) were rarely studied, despite them being potential causes of a digital divide. A more systematic and thorough exploration of inequalities in digital health is required to promote health for all.

A narrative review of lifestyle management guidelines for metabolic dysfunction-associated steatotic liver disease

BACKGROUND AND AIMS

Metabolic dysfunction-associated steatotic liver disease management guidelines have been published worldwide; we aimed to summarize, categorize, and compare their lifestyle intervention recommendations.

APPROACH AND RESULTS

We searched metabolic dysfunction-associated steatotic liver disease/NAFLD management guidelines published between January 1, 2013, and June 31, 2024, through databases including PubMed/MEDLINE, Cochrane, and CINAHL. In total, 35 qualifying guidelines were included in the final analysis. Guideline recommendations were categorized into 5 domains (ie, weight reduction goals, physical activity, nutrition, alcohol, and tobacco smoking) and were ranked based on how frequently they appeared. A recommendation was defined as widely adopted if recommended in ≥24 (≥66.6%) of the guidelines. These included increasing physical activity; reducing body weight by 7%-10% to improve steatohepatitis and/or fibrosis; restricting caloric intake; undertaking 150-300 or 75-150 minutes/week of moderate or vigorous-intensity physical activity, respectively; and decreasing consumption of commercially produced fructose. The least mentioned topics, in ≤9 of the guidelines, evaluated environmental determinants of health, mental health, referring patients for psychological or cognitive behavioral therapy, using digital health interventions, and assessing patients' social determinants of health.

CONCLUSIONS

Most guidelines recommend weight reduction through physical activity and improving nutrition, as these have proven positive effects on health outcomes when sustained. However, gaps regarding mental health and the social and environmental determinants of metabolic dysfunction-associated steatotic liver disease were found. To optimize behavioral modifications and treatment, we recommend carrying out studies that will provide further evidence on social support, environmental factors, and mental health, as well as further exploring digital health interventions.

Assessing the accessibility and quality of mobile health applications for the treatment of obesity in the German healthcare market

Introduction

Overweight and obesity are among the most prevalent health problems worldwide leading to various diseases and having a significant impact on the healthcare system. In Germany, the prevalence of obesity among adults is 19%. Mobile health applications offer a new approach to treatment and prevention and have been proven effective in previous studies. However, it is essential to investigate the availability and quality of these digital applications. The aim of this systematic assessment is to evaluate the accessibility and quality of digital health applications in German language designed to treat obesity.

Methods

In January 2024, a systematic search for mobile health applications was conducted on both the Google Play Store and Apple App Store. Just those apps available in German for both iOS and Android were considered acceptable. The German Mobile Application Rating Scale (MARS-G) was used to assess the quality of the apps. The content of mobile health applications was evaluated using the guideline from the German Obesity Society for the treatment of obesity. The characteristics of the apps were summarized and presented, and the results were analyzed using descriptive statistics and presented in tables.

Results

After screening, ten apps were included in the review. The apps varied in terms of calorie tracking, individual workout plans, educational aspects, nutritional plans, and exercises for behavioral change. On average, 6.4 out of 12 items of the German Obesity guideline recommendations were fulfilled. The MARS score (possible range from 1-5) reached a mean of 3.39 (SD = 0.39). The section "Engagement" had the lowest quality score with a mean of 3.14 (SD = 0.57), while the section "Aesthetics" achieved the highest mean of 3.57 (SD = 0.52).

Discussion

Most German mobile health applications for managing obesity meet some guideline recommendations. They demonstrate adequate to good quality according to the MARS score. Assessing the quality of mobile health applications can be challenging for patients, despite being easily accessible and low-threshold. However, such digital health applications, reimbursed by the German SHI, offer evidence-based information, even if access can be associated with higher hurdles.

Effectiveness of an Artificial Intelligence-Assisted App for Improving Eating Behaviors: Mixed Methods Evaluation

BACKGROUND

A plethora of weight management apps are available, but many individuals, especially those living with overweight and obesity, still struggle to achieve adequate weight loss. An emerging area in weight management is the support for one's self-regulation over momentary eating impulses.

OBJECTIVE

This study aims to examine the feasibility and effectiveness of a novel artificial intelligence-assisted weight management app in improving eating behaviors in a Southeast Asian cohort.

METHODS

A single-group pretest-posttest study was conducted. Participants completed the 1-week run-in period of a 12-week app-based weight management program called the Eating Trigger-Response Inhibition Program (eTRIP). This self-monitoring system was built upon 3 main components, namely, (1) chatbot-based check-ins on eating lapse triggers, (2) food-based computer vision image recognition (system built based on local food items), and (3) automated time-based nudges and meal stopwatch. At every mealtime, participants were prompted to take a picture of their food items, which were identified by a computer vision image recognition technology, thereby triggering a set of chatbot-initiated questions on eating triggers such as who the users were eating with. Paired 2-sided t tests were used to compare the differences in the psychobehavioral constructs before and after the 7-day program, including overeating habits, snacking habits, consideration of future consequences, self-regulation of eating behaviors, anxiety, depression, and physical activity. Qualitative feedback were analyzed by content analysis according to 4 steps, namely, decontextualization, recontextualization, categorization, and compilation.

RESULTS

The mean age, self-reported BMI, and waist circumference of the participants were 31.25 (SD 9.98) years, 28.86 (SD 7.02) kg/m2, and 92.60 (SD 18.24) cm, respectively. There were significant improvements in all the 7 psychobehavioral constructs, except for anxiety. After adjusting for multiple comparisons, statistically significant improvements were found for overeating habits (mean -0.32, SD 1.16; P<.001), snacking habits (mean -0.22, SD 1.12; P<.002), self-regulation of eating behavior (mean 0.08, SD 0.49; P=.007), depression (mean -0.12, SD 0.74; P=.007), and physical activity (mean 1288.60, SD 3055.20 metabolic equivalent task-min/day; P<.001). Forty-one participants reported skipping at least 1 meal (ie, breakfast, lunch, or dinner), summing to 578 (67.1%) of the 862 meals skipped. Of the 230 participants, 80 (34.8%) provided textual feedback that indicated satisfactory user experience with eTRIP. Four themes emerged, namely, (1) becoming more mindful of self-monitoring, (2) personalized reminders with prompts and chatbot, (3) food logging with image recognition, and (4) engaging with a simple, easy, and appealing user interface. The attrition rate was 8.4% (21/251).

CONCLUSIONS

eTRIP is a feasible and effective weight management program to be tested in a larger population for its effectiveness and sustainability as a personalized weight management program for people with overweight and obesity.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04833803; https://classic.clinicaltrials.gov/ct2/show/NCT04833803.

Technology-delivered personalized nutrition intervention on dietary outcomes among adults with overweight and obesity: A systematic review, meta-analysis, and meta-regression

The prevalence of overweight and obesity has continued to increase globally, and one-size-fits-all dietary recommendations may not be suitable for different individual characteristics. A personalized nutrition intervention may be a potential solution. This review aims to evaluate the effects of the technology-delivered personalized nutrition intervention on energy, fat, vegetable, and fruit intakes among adults with overweight and obesity. A three-step comprehensive search strategy was performed from 10 databases and seven clinical registries in published and unpublished trials. A total of 46 randomized controlled trials (RCTs) involving 19,670 adults with overweight and obesity from 14 countries are included. Subgroup and meta-regression analyses were conducted. Meta-analyses showed a reduction of energy intake (-128.05, 95% CI: -197.08, -59.01) and fat intake (-1.81% energy/days, 95% CI: -3.38, -0.24, and -0.19 scores, 95% CI: -0.40, 0.02) in the intervention compared with the comparator. Significant improvements in vegetable and fruit intakes with 0.12-0.15 servings/day were observed in the intervention. Combined one- and two-way interactions had a greater effect on energy intake reduction compared with their counterparts. Meta-regression analyses revealed that no significant covariates were found. Given that the certainty of the evidence was rated as low or very low, further well-designed RCTs with long-term follow-up are warranted.

Potential role of hybrid weight management intervention: A scoping review

Background

Digital health has been widely used in delivering healthcare, presenting emerging opportunities to overcome barriers to effective obesity care. One strategy suggested for addressing obesity involves a hybrid weight management intervention that incorporates digital health. This scoping review aimed to map existing evidence regarding hybrid weight management intervention.

Methods

PubMed, Scopus, Cochrane Library, and the Web of Science electronic databases were searched for studies published between January 1, 2012 and May 16, 2023, with language restricted to English. The focus was on controlled trials in which a hybrid weight management intervention was used in the intervention among overweight or obese adults. The scoping review framework followed Arksey and O'Malley's guidelines and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISM-P).

Results

Full-text article review in the screening stage resulted in a total of 10 articles being included for narrative synthesis. Almost two-third of the articles originated from the United States (60%), followed by Europe and Australia, each accounting for 20%. The most common hybrid weight management intervention type was the combination of face-to-face and telehealth (i.e. phone call/text messaging) (40%), closely followed by a combination email intervention (30%) and mHealth apps intervention (30%). Most of the face-to-face dietary interventions were delivered as a group counseling (80%), while some were conducted as individual counseling (20%). Most studies observed a positive effect of the hybrid weight management intervention on body weight (weight lost 3.9-8.2 kg), body mass index (decreased 0.58 kg/m2), waist circumference (decreased 2.25 cm), and physical activity level compared to standard care. Findings suggest a direct association between hybrid weight management interventions and weight loss. The weight loss ranged from 3.9 to 8.2 kg, with some evidence indicating a significant weight loss of 5% from baseline. There is a need to explore stakeholders' telehealth perspective to optimize the delivery of hybrid weight management interventions, thereby maximizing greatest benefits for weight management.

Community-Based Culturally Tailored Education Programs for Black Communities with Cardiovascular Disease, Diabetes, Hypertension, and Stroke: Systematic Review Findings

BACKGROUND

Community-based culturally tailored education (CBCTE) programs for chronic diseases may reduce health disparities; however, a synthesis across chronic diseases is lacking. We explored (1) the characteristics and outcomes of CBCTE programs and (2) which strategies for culturally appropriate interventions have been used in CBCTE programs, and how they have been implemented.

METHODS

A systematic review was conducted by searching three databases to identify empirical full-text literature on CBCTE programs for Black communities with cardiovascular disease, hypertension, diabetes, or stroke. Studies were screened in duplicate, then data regarding study characteristics, participants, intervention, and outcomes were extracted and analyzed. Cultural tailoring strategies within programs were categorized using Kreuter and colleagues' framework.

RESULTS

Of the 74 studies, most were conducted in the USA (97%) and delivered in one site (53%; e.g., church/home). CBCTE programs targeted diabetes (65%), hypertension (30%), diabetes and hypertension (1%), cardiovascular disease (3%), and stroke (1%). Reported program benefits included physiological, medication-related, physical activity, and literacy. Cultural tailoring strategies included peripheral (targeted Black communities), constituent-involving (e.g., community informed), evidential (e.g., integrated community resources), linguistic (e.g., delivered in community's dialect/accent), and sociocultural (e.g., integrated community members' religious practices).

CONCLUSIONS

CBCTE programs may have beneficial outcomes, but a small sample size limited several. The strategies identified can be adopted by programs seeking to culturally tailor. Future interventions should clearly describe community members' roles/involvement and deliver programs in multiple locations to broaden reach.

TRIAL REGISTRATION

PROSPERO CRD42021245772.

Effects of an Individualized mHealth-Based Intervention on Health Behavior Change and Cardiovascular Risk Among People With Metabolic Syndrome Based on the Behavior Change Wheel: Quasi-Experimental Study

BACKGROUND

Metabolic syndrome (MetS) is a common public health challenge. Health-promoting behaviors such as diet and physical activity are central to preventing and controlling MetS. However, the adoption of diet and physical activity behaviors has always been challenging. An individualized mobile health (mHealth)-based intervention using the Behavior Change Wheel is promising in promoting health behavior change and reducing atherosclerotic cardiovascular disease (ASCVD) risk. However, the effects of this intervention are not well understood among people with MetS in mainland China.

OBJECTIVE

We aimed to evaluate the effects of the individualized mHealth-based intervention using the Behavior Change Wheel on behavior change and ASCVD risk in people with MetS.

METHODS

We conducted a quasi-experimental, nonrandomized study. Individuals with MetS were recruited from the health promotion center of a tertiary hospital in Zhejiang province, China. The study involved 138 adults with MetS, comprising a control group of 69 participants and an intervention group of 69 participants. All participants received health education regarding diet and physical activity. The intervention group additionally received a 12-week individualized intervention through a WeChat mini program and a telephone follow-up in the sixth week of the intervention. Primary outcomes included diet, physical activity behaviors, and ASCVD risk. Secondary outcomes included diet self-efficacy, physical activity self-efficacy, knowledge of MetS, quality of life, and the quality and efficiency of health management services. The Mann-Whitney U test and Wilcoxon signed rank test were primarily used for data analysis. Data analysis was conducted based on the intention-to-treat principle using SPSS (version 25.0; IBM Corp).

RESULTS

Baseline characteristics did not differ between the 2 groups. Compared with the control group, participants in the intervention group showed statistically significant improvements in diet behavior, physical activity behavior, diet self-efficacy, physical activity self-efficacy, knowledge of MetS, physical health, and mental health after a 12-week intervention (P=.04, P=.001, P=.04, P=.04, P=.001, P=.04, P=.04, and P<.05). The intervention group demonstrated a statistically significant improvement in outcomes from pre- to postintervention evaluations (P<.001, P=.03, P<.001, P=.04, P<.001, P<.001, and P<.001). The intervention also led to enhanced health management services and quality.

CONCLUSIONS

The individualized mHealth-based intervention using the Behavior Change Wheel was effective in promoting diet and physical activity behaviors in patients with MetS. Nurses and other health care professionals may incorporate the intervention into their health promotion programs.

Effectiveness of Human-Supported and Self-Help eHealth Lifestyle Interventions for Patients With Cardiometabolic Risk Factors: A Meta-Analysis

OBJECTIVE

eHealth is a useful tool to deliver lifestyle interventions for patients with cardiometabolic diseases. However, there are inconsistent findings about whether these eHealth interventions should be supported by a human professional, or whether self-help interventions are equally effective.

METHODS

Databases were searched between January 1995 and October 2021 for randomized controlled trials on cardiometabolic diseases (cardiovascular disease, chronic kidney disease, type 1 and 2 diabetes mellitus) and eHealth lifestyle interventions. A multilevel meta-analysis was used to pool clinical and behavioral health outcomes. Moderator analyses assessed the effect of intervention type (self-help versus human-supported), dose of human support (minor versus major part of intervention), and delivery mode of human support (remote versus blended). One hundred seven articles fulfilled eligibility criteria and 102 unique ( N = 20,781) studies were included.

RESULTS

The analysis showed a positive effect of eHealth lifestyle interventions on clinical and behavioral health outcomes ( p < .001). However, these effects were not moderated by intervention type ( p = .169), dose ( p = .698), or delivery mode of human support ( p = .557).

CONCLUSIONS

This shows that self-help eHealth interventions are equally effective as human-supported ones in improving health outcomes among patients with cardiometabolic disease. Future studies could investigate whether higher-quality eHealth interventions compensate for a lack of human support.Meta-analysis registration: PROSPERO CRD42021269263 .

Development of an individualized WeChat mini program-based intervention to increase adherence to dietary recommendations applying the behaviour change wheel among individuals with metabolic syndrome

BACKGROUND

Metabolic Syndrome (MetS) is a serious public health issue. Dietary changes form the core of MetS treatment. The adherence to dietary recommendations is critical for reducing the severity of MetS components and preventing complications. However, the adherence to dietary recommendations was not adequate among adults with MetS. This study utilizes the Behaviour Change Wheel (BCW) to develop an individualized WeChat mini program-based behavioural change intervention aimed at strengthening adherence to dietary recommendations in people with MetS.

METHODS

The BCW theory was used to design an individualized WeChat mini program-based behavioural change intervention. A descriptive qualitative study was conducted to identify the determinants of adherence to dietary recommendations in individuals with MetS. The study was conducted at the health promotion centre of a prominent general university hospital in Zhejiang, China. Subsequently, the intervention functions (IFs) and policy categories were selected following the identified determinants. Afterwards, behaviour change techniques (BCTs) were chosen to translate into potential intervention strategies, and the delivery mode was determined.

RESULTS

Our study identified fifteen barriers to improve the adherence to dietary recommendations in this population. These were linked with six IFs: education, training, persuasion, enablement, modelling, and environmental restructuring. Then, twelve BCTs were linked with the IFs and fifteen barriers. The delivery mode was a WeChat mini program. After these actions, an individualized WeChat mini program-based behavioural change intervention was developed to enhance adherence to dietary recommendations for individuals with MetS.

CONCLUSIONS

The BCW theory helped scientifically and systematically develop an individualized WeChat mini program-based behavioural change intervention for individuals with MetS. In the future, our research team will refine and upgrade the WeChat mini program and then test the usability and effectiveness of the individualized WeChat mini program-based behavioural change intervention program.

Are motivational and self-regulation factors associated with 12 months' weight regain prevention in the NoHoW study? An analysis of European adults

PURPOSE

Preventing weight regain can only be achieved by sustained changes in energy balance-related behaviors that are associated with weight, such as diet and physical activity. Changes in motivation and self-regulatory skills can support long-term behavioral changes in the context of weight loss maintenance. We propose that experiencing a supportive climate care is associated with enhanced satisfaction of basic psychological needs, intrinsic goals, and autonomous motivation. These factors are expected to be associate with the utilization of self-regulation skills, leading to more sustained behavior changes and ultimately preventing weight regain. This hypothesis was tested in this ancillary analysis of the NoHoW trial, where the study arms were pooled and followed for 12 months.

METHODS

The NoHoW was a three-center, large-scale weight regain prevention full factorial trial. In this longitudinal study, data were collected in adults who lost > 5% weight in the past year (N = 870, complete data only, 68.7% female, 44.10 ± 11.86 years, 84.47 ± 17.03 kg) during their participation in a 12-month digital behavior change intervention. Weight and validated measures of motivational- and self-regulatory skills-related variables were collected at baseline, six- and 12 months. Change variables were used in Mplus' path analytical models informed by NoHoW's logic model.

RESULTS

The bivariate correlations confirmed key mediators' potential effect on weight outcomes in the expected causal direction. The primary analysis showed that a quarter of the variance (r2 = 23.5%) of weight regain prevention was achieved via the mechanisms of action predicted in the logic model. Specifically, our results show that supportive climate care is associated with needs satisfaction and intrinsic goal content leading to better weight regain prevention via improvements in self-regulatory skills and exercise-controlled motivation. The secondary analysis showed that more mechanisms of action are significant in participants who regained or maintained their weight.

CONCLUSIONS

These results contribute to a better understanding of the mechanisms of action leading to behavior change in weight regain prevention. The most successful participants used only a few intrinsic motivation-related mechanisms of action, suggesting that habits may have been learned. While developing a digital behavior change intervention, researchers and practitioners should consider creating supportive climate care to improve needs satisfaction and intrinsic goal contents.

TRIAL REGISTRATION

ISRCTN, ISRCTN88405328 , registered 12/22/2016.

The Effectiveness of eHealth Interventions for Weight Loss and Weight Loss Maintenance in Adults with Overweight or Obesity: A Systematic Review of Systematic Reviews

PURPOSE OF REVIEW: The purpose of this study is to evaluate the effectiveness of eHealth interventions for weight loss and weight loss maintenance among adults with overweight or obesity through a systematic review of systematic reviews. RECENT FINDINGS: This study included 26 systematic reviews, covering a total of 338 original studies, published between 2018 and 2023. The review indicates that eHealth interventions are more effective than control interventions or no care and comparable to face-to-face interventions. The effect sizes remain relatively small when comparing eHealth interventions to any control conditions, with mean differences of weight loss results from - 0.12 kg (95% CI - 0.64 to 0.41 kg) in a review comparing eHealth interventions to face-to-face care to - 4.32 kg (- 5.08 kg to - 3.57 kg) in a review comparing eHealth interventions to no care. The methodological quality of the included studies varies considerably. However, it can be concluded that interventions with human contact work better than those that are fully automated. In conclusion, this systematic review of systematic reviews provides an updated understanding of the development of digital interventions in recent years and their effectiveness for weight loss and weight loss maintenance among adults with overweight or obesity. The findings suggest that eHealth interventions can be a valuable tool for delivering obesity care to more patients economically. Further research is needed to determine which specific types of eHealth interventions are most effective and how to best integrate them into clinical practice.

A Systematic Review of eHealth Interventions to Promote Physical Activity in Adults with Obesity or Overweight

Use of information and communication technology to improve health, known as eHealth, is an emerging concept in healthcare that may present opportunities to promote physical activity in adults with obesity. The purpose of this research was to systematically review eHealth intervention studies to promote physical activity in adults with obesity. Five electronic databases were used. Two authors screened articles, assessed risk of bias, and extracted data independently. A qualitative data synthesis for summarizing the findings was performed using harvest plots. In the search, 2276 articles were identified, and 18 studies met all inclusion criteria. Study quality ranged from poor to good. The included studies varied in intervention technology (e.g., web-based), physical activity assessment (e.g., device-based), and control group (e.g., wait-list). Behavioral change techniques used in the included studies were consistent with some techniques (e.g., self-monitoring) known as effective in face-to-face interventions, but more efficiently employed in eHealth using information and communication technology. Overall, this systematic review showed that a web-based or physical activity monitor-based eHealth intervention had the potential to effectively promote physical activity in adults with obesity. Some recommendations for future eHealth interventions to promote physical activity in adults with obesity were provided (e.g., use of theory, accelerometers).

Personalization strategies in digital mental health interventions: a systematic review and conceptual framework for depressive symptoms

Introduction

Personalization is a much-discussed approach to improve adherence and outcomes for Digital Mental Health interventions (DMHIs). Yet, major questions remain open, such as (1) what personalization is, (2) how prevalent it is in practice, and (3) what benefits it truly has.

Methods

We address this gap by performing a systematic literature review identifying all empirical studies on DMHIs targeting depressive symptoms in adults from 2015 to September 2022. The search in Pubmed, SCOPUS and Psycinfo led to the inclusion of 138 articles, describing 94 distinct DMHIs provided to an overall sample of approximately 24,300 individuals.

Results

Our investigation results in the conceptualization of personalization as purposefully designed variation between individuals in an intervention's therapeutic elements or its structure. We propose to further differentiate personalization by what is personalized (i.e., intervention content, content order, level of guidance or communication) and the underlying mechanism [i.e., user choice, provider choice, decision rules, and machine-learning (ML) based approaches]. Applying this concept, we identified personalization in 66% of the interventions for depressive symptoms, with personalized intervention content (32% of interventions) and communication with the user (30%) being particularly popular. Personalization via decision rules (48%) and user choice (36%) were the most used mechanisms, while the utilization of ML was rare (3%). Two-thirds of personalized interventions only tailored one dimension of the intervention.

Discussion

We conclude that future interventions could provide even more personalized experiences and especially benefit from using ML models. Finally, empirical evidence for personalization was scarce and inconclusive, making further evidence for the benefits of personalization highly needed.

Systematic Review Registration

Identifier: CRD42022357408.

Identifying the behavior change techniques used in obesity interventions: AN EXAMPLE FROM THE EARLY TRIALS

Objective

The dissemination of effective obesity interventions requires the documentation of key elements of the intervention. But outcome papers and other published manuscripts often lack detail that allow the replication of the intervention. The Behavior Change Technique (BCT) Taxonomy (BCTTv1) is a widely used approach to identify key elements of an intervention study. This study compares the extent to which BCTs and domains identified in studies' intervention protocol are concordant with detail from corresponding intervention design and study outcome papers.

Methods

Data come from four obesity interventions with complete intervention protocols as well as published intervention design and outcome papers. The number of domains and BCTs was calculated for each treatment arm and stratified by coding source. Emphasis of domains and BCTs was determined using an Analytical Hierarchy Process (AHP).

Results

A review of each study's intervention protocol showed the mean number of domains and BCTs used in treatment arms as 11.8 and 26.7, respectively. Primary outcome papers had a mean loss of 34% of the reported domains and 43% of BCTS as compared with intervention protocl. Design papers showed a loss of 11% and 21% of domains and BCTs, respectively.

Conclusions

The results confirm the limitations of using the BCTTv1 coding of outcome papers to describe obesity-related interventions. The results also highlight the need for mechanisms that allow for a full description of intervention content such as inclusion in a supplemental section of an online journal or the use of intervention-focused consort guidelines.

Effectiveness of mHealth/eHealth interventions on obesity treatment: a protocol for umbrella review of meta-analyses

INTRODUCTION

Mobile health (mHealth)/electronic health (eHealth) have the effect of facilitating weight loss in overweight and obese populations. However, studies have shown varied results and relatively high heterogeneity in the efficacy of mHealth/eHealth interventions. The aim of the paper was to systematically summarise published studies about the weight loss efficacy of mHealth/eHealth.

METHODS AND ANALYSIS

A comprehensive review of PubMed, Embase and Cochrane Library databases published from inception to 21 March 2021 will be conducted. The selected articles are meta-analyses that integrated the studies, which evaluated efficacy of mHealth/eHealth. Two people will select eligible articles and extract data independently. Any disputes will be resolved by discussion or the arbitration of a third person. The methodological quality of the included meta-analyses will be assessed with AMSTAR V.2 and the quality of evidence will be obtained with Grade of Recommendations Assessment, Development and Evaluation (GRADE). The study selection process will be presented using a flowchart. We will reanalyse each outcome with random effect methods. If possible, we will use funnel plot and Egger's test to evaluate if publication bias existed.

ETHICS AND DISSEMINATION

Ethical approval is not required for the study, as we collected data only from available published materials. This umbrella review will also be submitted to a peer-reviewed journal for publication after completion.

PROSPERO REGISTRATION NUMBER

CRD42021247006.

Long term Weight Loss in a Primary Care-Anchored eHealth Lifestyle Coaching Program in Denmark: Randomized Controlled Trial (Preprint)

Background

Long-term weight loss in people living with obesity can reduce the risk and progression of noncommunicable diseases. Observational studies suggest that digital coaching can lead to long-term weight loss.

Objective

We investigated whether an eHealth lifestyle coaching program for people living with obesity with or without type 2 diabetes led to significant, long-term (12-month) weight loss compared to usual care.

Methods

In a randomized controlled trial that took place in 50 municipalities in Denmark, 340 people living with obesity with or without type 2 diabetes were enrolled from April 16, 2018, to April 1, 2019, and randomized via an automated computer algorithm to an intervention (n=200) or a control (n=140) group. Patients were recruited via their general practitioners, the Danish diabetes organization, and social media. The digital coaching intervention consisted of an initial 1-hour face-to-face motivational interview followed by digital coaching using behavioral change techniques enabled by individual live monitoring. The primary outcome was change in body weight from baseline to 12 months.

Results

Data were assessed for 200 participants, including 127 from the intervention group and 73 from the control group, who completed 12 months of follow-up. After 12 months, mean body weight and BMI were significantly reduced in both groups but significantly more so in the intervention group than the control group (–4.5 kg, 95% CI –5.6 to –3.4 vs –1.5 kg, 95% CI –2.7 to –0.2, respectively; P<.001; and –1.5 kg/m², 95% CI –1.9 to –1.2 vs –0.5 kg/m², 95% CI –0.9 to –0.1, respectively; P<.001). Hemoglobin A_1c was significantly reduced in both the intervention (–6.0 mmol/mol, 95% CI –7.7 to –4.3) and control (–4.9 mmol/mol, 95% CI –7.4 to –2.4) groups, without a significant group difference (all P>.46).

Conclusions

Compared to usual care, digital lifestyle coaching can induce significant weight loss for people living with obesity, both with and without type 2 diabetes, after 12 months.

Trial Registration

ClinicalTrials.gov NCT03788915; https://clinicaltrials.gov/ct2/show/NCT03788915

mHealth Interventions to Reduce Physical Inactivity and Sedentary Behavior in Children and Adolescents: Systematic Review and Meta-analysis of Randomized Controlled Trials

Background

Children and adolescents increasingly do not meet physical activity (PA) recommendations. Hence, insufficient PA (IPA) and sedentary behavior (SB) among children and adolescents are relevant behavior change domains for using individualized mobile health (mHealth) interventions.

Objective

This review and meta-analysis investigated the effectiveness of mHealth interventions on IPA and SB, with a special focus on the age and level of individualization.

Methods

PubMed, Scopus, Web of Science, SPORTDiscus, and Cochrane Library were searched for randomized controlled trials published between January 2000 and March 2021. mHealth interventions for primary prevention in children and adolescents addressing behavior change related to IPA and SB were included. Included studies were compared for content characteristics and methodological quality and summarized narratively. In addition, a meta-analysis with a subsequent exploratory meta-regression examining the moderating effects of age and individualization on overall effectiveness was performed.

Results

On the basis of the inclusion criteria, 1.3% (11/828) of the preliminary identified studies were included in the qualitative synthesis, and 1.2% (10/828) were included in the meta-analysis. Trials included a total of 1515 participants (mean age (11.69, SD 0.788 years; 65% male and 35% female) self-reported (3/11, 27%) or device-measured (8/11, 73%) health data on the duration of SB and IPA for an average of 9.3 (SD 5.6) weeks. Studies with high levels of individualization significantly decreased insufficient PA levels (Cohen d=0.33; 95% CI 0.08-0.58; Z=2.55; P=.01), whereas those with low levels of individualization (Cohen d=−0.06; 95% CI −0.32 to 0.20; Z=0.48; P=.63) or targeting SB (Cohen d=−0.11; 95% CI −0.01 to 0.23; Z=1.73; P=.08) indicated no overall significant effect. The heterogeneity of the studies was moderate to low, and significant subgroup differences were found between trials with high and low levels of individualization (χ21=4.0; P=.04; I2=75.2%). Age as a moderator variable showed a small effect; however, the results were not significant, which might have been because of being underpowered.

Conclusions

Evidence suggests that mHealth interventions for children and adolescents can foster moderate reductions in IPA but not SB. Moreover, individualized mHealth interventions to reduce IPA seem to be more effective for adolescents than for children. Although, to date, only a few mHealth studies have addressed inactive and sedentary young people, and their quality of evidence is moderate, these findings indicate the relevance of individualization on the one hand and the difficulties in reducing SB using mHealth interventions on the other.

Trial Registration

PROSPERO CRD42020209417; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=209417

Weight Loss Trajectories in Healthy Weight Coaching: Cohort Study

Background

As global obesity prevalence continues to increase, there is a need for accessible and affordable weight management interventions, such as web-based programs.

Objective

This paper aims to assess the outcomes of healthy weight coaching (HWC), a web-based obesity management program integrated into standard Finnish clinical care.

Methods

HWC is an ongoing, structured digital 12-month program based on acceptance and commitment therapy. It includes weekly training sessions focused on lifestyle, general health, and psychological factors. Participants received remote one-on-one support from a personal coach. In this real-life, single-arm, prospective cohort study, we examined the total weight loss, weight loss profiles, and variables associated with weight loss success and program retention in 1189 adults (963 women) with a BMI >25 kg/m² among participants of the program between October 2016 and March 2019. Absolute (kg) and relative (%) weight loss from the baseline were the primary outcomes. We also examined the weight loss profiles, clustered based on the dynamic time-warping distance, and the possible variables associated with greater weight loss success and program retention. We compared different groups using the Mann-Whitney test or Kruskal-Wallis test for continuous variables and the chi-squared test for categorical variables. We analyzed changes in medication using the McNemar test.

Results

Among those having reached the 12-month time point (n=173), the mean weight loss was 4.6% (SE 0.5%), with 43% (n=75) achieving clinically relevant weight loss (≥5%). Baseline BMI ≥40 kg/m² was associated with a greater weight loss than a lower BMI (mean 6.6%, SE 0.9%, vs mean 3.2%, SE 0.6%; P=.02). In addition, more frequent weight reporting was associated with greater weight loss. No significant differences in weight loss were observed according to sex, age, baseline disease, or medication use. The total dropout rate was 29.1%. Dropouts were slightly younger than continuers (47.2, SE 0.6 years vs 49.2, SE 0.4 years; P=.01) and reported their weight less frequently (3.0, SE 0.1 entries per month vs 3.3, SE 0.1 entries per month; P<.001).

Conclusions

A comprehensive web-based program such as HWC is a potential addition to the repertoire of obesity management in a clinical setting. Heavier patients lost more weight, but weight loss success was otherwise independent of baseline characteristics.

Social Mobile Approaches to Reducing Weight (SMART) 2.0: protocol of a randomized controlled trial among young adults in university settings

Background

Excess weight gain in young adulthood is associated with future weight gain and increased risk of chronic disease. Although multimodal, technology-based weight-loss interventions have the potential to promote weight loss among young adults, many interventions have limited personalization, and few have been deployed and evaluated for longer than a year. We aim to assess the effects of a highly personalized, 2-year intervention that uses popular mobile and social technologies to promote weight loss among young adults.

Methods

The Social Mobile Approaches to Reducing Weight (SMART) 2.0 Study is a 24-month parallel-group randomized controlled trial that will include 642 overweight or obese participants, aged 18–35 years, from universities and community colleges in San Diego, CA. All participants receive a wearable activity tracker, connected scale, and corresponding app. Participants randomized to one intervention group receive evidence-based information about weight loss and behavior change techniques via personalized daily text messaging (i.e., SMS/MMS), posts on social media platforms, and online groups. Participants in a second intervention group receive the aforementioned elements in addition to brief, technology-mediated health coaching. Participants in the control group receive a wearable activity tracker, connected scale, and corresponding app alone. The primary outcome is objectively measured weight in kilograms over 24 months. Secondary outcomes include anthropometric measurements; physiological measures; physical activity, diet, sleep, and psychosocial measures; and engagement with intervention modalities. Outcomes are assessed at baseline and 6, 12, 18, and 24 months. Differences between the randomized groups will be analyzed using a mixed model of repeated measures and will be based on the intent-to-treat principle.

Discussion

We hypothesize that both SMART 2.0 intervention groups will significantly improve weight loss compared to the control group, and the group receiving health coaching will experience the greatest improvement. We further hypothesize that differences in secondary outcomes will favor the intervention groups. There is a critical need to advance understanding of the effectiveness of multimodal, technology-based weight-loss interventions that have the potential for long-term effects and widespread dissemination among young adults. Our findings should inform the implementation of low-cost and scalable interventions for weight loss and risk-reducing health behaviors.

Trial registration

ClinicalTrials.govNCT03907462. Registered on April 9, 2019

A personalized mobile app for physical activity: An experimental mixed-methods study

Objectives

To investigate the feasibility of the be.well app and its personalization approach which regularly considers users’ preferences, amongst university students.

Methods

We conducted a mixed-methods, pre-post experiment, where participants used the app for 2 months. Eligibility criteria included: age 18–34 years; owning an iPhone with Internet access; and fluency in English. Usability was assessed by a validated questionnaire; engagement metrics were reported. Changes in physical activity were assessed by comparing the difference in daily step count between baseline and 2 months. Interviews were conducted to assess acceptability; thematic analysis was conducted.

Results

Twenty-three participants were enrolled in the study (mean age = 21.9 years, 71.4% women). The mean usability score was 5.6 ± 0.8 out of 7. The median daily engagement time was 2 minutes. Eighteen out of 23 participants used the app in the last month of the study. Qualitative data revealed that people liked the personalized activity suggestion feature as it was actionable and promoted user autonomy. Some users also expressed privacy concerns if they had to provide a lot of personal data to receive highly personalized features. Daily step count increased after 2 months of the intervention (median difference = 1953 steps/day, p-value <.001, 95% CI 782 to 3112).

Conclusions

Incorporating users’ preferences in personalized advice provided by a physical activity app was considered feasible and acceptable, with preliminary support for its positive effects on daily step count. Future randomized studies with longer follow up are warranted to determine the effectiveness of personalized mobile apps in promoting physical activity.

What goes on in digital behaviour change interventions for weight loss maintenance targeting physical activity: A scoping review

Objective

To identify the core components of digital behaviour change interventions for weight loss maintenance targeting physical activity, in terms of: (i) behaviour change techniques, (ii) mechanisms of action, (iii) modes of delivery, (iv) dose and (v) tailoring/personalization. In addition, the links between these components were investigated.

Methods

A literature search was performed in five electronic databases: PubMed, Embase, CINHAL, PsycINFO and Web of Science. Two reviewers independently screened the identified articles and extracted data related with the study characteristics and behaviour change techniques, mechanism of action, mode of delivery, dose, and tailoring, using standardized classifications whenever available (e.g. behaviour change techniques taxonomy).

Results

Seventeen articles reporting 11 original studies were selected. Two studies were protocols, 9 studies presented results for weight change and all but one showed no significant differences between the intervention and control groups. Eight studies (73%) provided adequate information on behaviour change techniques. Five studies (45%) provided partial information about how the behaviour change techniques were linked to mechanisms of action, and only one study (0.9%) described these links for all the techniques. Around half of the studies reported the modes through which behaviour change techniques were delivered. Descriptions of dose were present in most studies, but with minimal information. The use of tailoring or personalization approaches was mentioned in eight studies (73%), but descriptions of what was tailored and how were minimal.

Conclusions

The compilation of information regarding intervention components was difficult due to the lack of information and systematization in reporting across papers. This is particularly true for the reporting of the links between behaviour change techniques and the other core intervention components. This information is crucial to help us understand in the context of behaviour change interventions what works or does not work, how it works and why.

Individualized mobile health interventions for cardiovascular event prevention in patients with coronary heart disease: study protocol for the iCARE randomized controlled trial

Background

Mobile health-based individualized interventions have shown potential effects in managing cardiovascular risk factors. This study aims to assess whether or not mHealth based individualized interventions delivered by an Individualized Cardiovascular Application system for Risk Elimination (iCARE) could reduce the incidence of major cardiovascular events in individuals with coronary heart disease.

Methods

This study is a large-scale, multi-center, parallel-group, open-label, randomized controlled clinical trial. This study will be conducted from September 2019 to December 2025. A total of 2820 patients with coronary heart disease will be recruited from two clinical sites and equally randomized into three groups: the intervention group and two control groups. All participants will be informed of six-time points (at 1, 3, 6, 12, 24, and 36 months after discharge) for follow-up visits. Over a course of 36 months, patients who are randomized to the intervention arm will receive individualized interventions delivered by a fully functional iCARE that using various visualization methods such as comics, videos, pictures, text to provide individualized interventions in addition to standard care. Patients randomized to control group 1 will receive interventions delivered by a modified iCARE that only presented in text in addition to routine care. Control group 2 will only receive routine care. The primary outcome is the incidence of major cardiovascular events within 3 years of discharge. Main secondary outcomes include changes in health behaviors, medication adherence, and cardiovascular health score.

Discussion

If the iCARE trial indeed demonstrates positive effects on patients with coronary heart disease, it will provide empirical evidence for supporting secondary preventive care in this population. Results will inform the design of future research focused on mHealth-based, theory-driven, intelligent, and individualized interventions for cardiovascular risk management.

Trial registration

Trial registered 24th December 2016 with the Chinese Clinical Trial Registry (ChiCTR-INR-16010242). URL: http://www.chictr.org.cn/showproj.aspx?proj=17398.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-021-02153-9.

Personalized mobile technologies for lifestyle behavior change: A systematic review, meta-analysis, and meta-regression

Given that the one-size-fits-all approach to mobile health interventions have limited effects, a personalized approach might be necessary to promote healthy behaviors and prevent chronic conditions. Our systematic review aims to evaluate the effectiveness of personalized mobile interventions on lifestyle behaviors (i.e., physical activity, diet, smoking and alcohol consumption), and identify the effective key features of such interventions. We included any experimental trials that tested a personalized mobile app or fitness tracker and reported any lifestyle behavior measures. We conducted a narrative synthesis for all studies, and a meta-analysis of randomized controlled trials. Thirty-nine articles describing 31 interventions were included (n = 77,243, 64% women). All interventions personalized content and rarely personalized other features. Source of data included system-captured (12 interventions), user-reported (11 interventions) or both (8 interventions). The meta-analysis showed a moderate positive effect on lifestyle behavior outcomes (standardized difference in means [SDM] 0.663, 95% CI 0.228 to 1.10). A meta-regression model including source of data found that interventions that used system-captured data for personalization were associated with higher effectiveness than those that used user-reported data (SDM 1.48, 95% CI 0.76 to 2.19). In summary, the field is in its infancy, with preliminary evidence of the potential efficacy of personalization in improving lifestyle behaviors. Source of data for personalization might be important in determining intervention effectiveness. To fully exploit the potential of personalization, future high-quality studies should investigate the integration of multiple data from different sources and include personalized features other than content.

eHealth interventions for reducing cardiovascular disease risk in men: A systematic review and meta-analysis

Men remain at a higher risk of developing cardiovascular disease (CVD) than women and behavioral risk factor modification is an important preventive measure. However, engaging men in behavior change interventions is challenging. Although men often indicate a preference for gender-specific information and support, this rarely occurs. eHealth interventions have the potential to address this gap, though their effectiveness for reducing CVD risk in men is unclear. Therefore, the aim of this systematic review and meta-analysis was to evaluate the effectiveness of eHealth interventions for reducing CVD risk in men. A search of published randomised controlled trials with no date restrictions up to July 2020 was conducted to identify those targeting at least two major CVD risk factors. Nine trials were identified and reviewed. Study quality ranged from low to unclear, with one trial at a high risk of bias. Compared to those in a control group or receiving printed materials, participants randomised to an eHealth intervention had statistically significant improvements in BMI (Z=-2.75, p=0.01), body weight (Z=-3.25, p=0.01), waist circumference (Z=-2.30, p=0.02) and systolic (Z=-3.57, p=0.01) and diastolic (Z=-3.56, p=0.01) blood pressure. Though less evident, there were also improvements in physical activity and diet in favour of the intervention group. This review suggests that eHealth interventions can reduce CVD risk in adult men through behavior change. However, we were unable to determine the association between intervention characteristics and outcomes. Also, overall, participant adherence to the intervention was poor. Both of these issues should be considered in future studies.

Evaluating a web- and telephone-based personalised exercise intervention for individuals living with metastatic prostate cancer (ExerciseGuide): protocol for a pilot randomised controlled trial

Introduction

Preliminary research has shown the effectiveness of supervised exercise-based interventions in alleviating sequela resulting from metastatic prostate cancer. Despite this, many individuals do not engage in sufficient exercise to gain the benefits. There are many barriers, which limit the uptake of face-to-face exercise in this population including lack of suitable facilities, remoteness, and access to experts, significant fatigue, urinary incontinence and motivation. Technology-enabled interventions offer a distance-based alternative. This protocol describes a pilot two-armed randomised controlled study that will investigate the feasibility and preliminary efficacy of an online exercise and behavioural change tool (ExerciseGuide) amongst individuals with metastatic prostate cancer.

Methods

Sixty-six participants with histologically diagnosed metastatic prostate cancer will be randomised into either the 8-week intervention or a wait-list control. The intervention arm will have access to a tailored website, remote supervision, and tele-coaching sessions to enhance support and adherence. Algorithms will individually prescribe resistance and aerobic exercise based upon factors such as metastasis location, pain, fatigue, confidence and current exercise levels. Behavioural change strategies and education on exercise benefits, safety and lifestyle are also tailored through the website. The primary outcome will be intervention feasibility (safety, usability, acceptability, and adherence). Secondary exploratory outcomes include changes in physical activity, quality of life, sleep, and physical function. Outcomes will be measured at baseline and week 9.

Discussion

The study aims to determine the potential feasibility of an online remotely monitored exercise intervention developed for individuals with metastatic prostate cancer. If feasible, this pilot intervention will inform the design and implementation of further distance-based interventions.

Trial registration

ANZCTR, ACTRN12614001268639. Registered 10 December 2018, https://anzctr.org.au/ACTRN12618001979246.aspx

Supplementary Information

The online version contains supplementary material available at 10.1186/s40814-020-00763-2.

Personalized Web-Based Weight Loss Behavior Change Program With and Without Dietitian Online Coaching for Adults With Overweight and Obesity: Randomized Controlled Trial

Background

The effect of computer- or human-delivered personalized feedback on the effectivess of web-based behavior change platforms for weight loss is unclear.

Objective

We aimed to compare the effectiveness of a web-based behavior change intervention personalized through either computerized or human-delivered feedback with a nonpersonalized intervention in promoting weight loss in community-based adults with overweight or obesity.

Methods

This pragmatic, 3-group, parallel-arm, randomized trial recruited students and staff in a Brazilian public university who were aged 18 to 60 years, had a BMI of ≥25 kg/m², and were not pregnant. Participants were allocated to one of 3 groups: platform only (24-week behavior change program delivered using a web platform with personalized computer-delivered feedback), platform plus coaching (same 24-week web-based behavior change program plus 12 weeks of personalized feedback delivered online by a dietitian), or waiting list (nonpersonalized dietary and physical activity recommendations delivered through an e-booklet and videos). Self-reported weight at 24 weeks was the primary outcome. Changes in dietary and physical activity habits within 24 weeks were secondary outcomes.

Results

Among the 1298 participants, 375 (28.89%) were lost to follow-up. In the intention-to-treat analysis, the platform-only and platform plus coaching groups had greater mean weight loss than the waiting-list group at 24 weeks (–1.08 kg, 95% CI –1.41 to –0.75 vs –1.57 kg, 95% CI –1.92 to –1.22 vs –0.66 kg, 95% CI –0.98 to –0.34, respectively). The platform-only and platform plus coaching groups, compared with the waiting list group, had a greater increase in the consumption of vegetables (3%, 95% CI 1% to 6% vs 5%, 95% CI 2% to 8% vs –3%, 95% CI –5% to 0%) and fruits (9%, 95% CI 6% to 12% vs 6%, 95% CI 2% to 9% vs 2%, 95% CI 0% to 6%) and a larger reduction in ultraprocessed food intake (–18%, 95% CI –23% to –13% vs –25%, 95% CI –30% to –20% vs –12%, 95% CI –16% to –8%). Changes in physical activity did not differ across the groups. Engagement was higher in the platform plus coaching group than in the platform-only group (7.6 vs 5.2 completed sessions; P=.007). Longer usage of the platform was associated with clinically meaningful (≥5%) weight loss (odds ratio 1.02, 95% CI 1.01 to 1.04).

Conclusions

The web-based behavior change programs with computer- and human-delivered personalized feedback led to greater, albeit small-magnitude, weight loss within 24 weeks. Improvement in multiple dietary habits, but not physical activity, were also greater in the personalized programs compared with the nonpersonalized one. The human-delivered personalized feedback by the online dietitian coach increased user engagement with the program and was associated with a significantly higher chance of clinically meaningful weight loss.

Trial Registration

ClinicalTrials.gov NCT03435445; https://clinicaltrials.gov/ct2/show/NCT03435445

International Registered Report Identifier (IRRID)

RR2-10.2196/10.1186/s12889-018-5882-y

Feasibility of Social-Network-Based eHealth Intervention on the Improvement of Healthy Habits among Children

This study shows the feasibility of an eHealth solution for tackling eating habits and physical activity in the adolescent population. The participants were children from 11 to 15 years old. An intervention was carried out on 139 students in the intervention group and 91 students in the control group, in two schools during 14 weeks. The intervention group had access to the web through a user account and a password. They were able to create friendship relationships, post comments, give likes and interact with other users, as well as receive notifications and information about nutrition and physical activity on a daily basis and get (virtual) rewards for improving their habits. The control group did not have access to any of these features. The homogeneity of the samples in terms of gender, age, body mass index and initial health-related habits was demonstrated. Pre- and post-measurements were collected through self-reports on the application website. After applying multivariate analysis of variance, a significant alteration in the age-adjusted body mass index percentile was observed in the intervention group versus the control group, as well as in the PAQ-A score and the KIDMED score. It can be concluded that eHealth interventions can help to obtain healthy habits. More research is needed to examine the effectiveness in achieving adherence to these new habits.