Self-Monitoring via Digital Health in Weight Loss Interventions: A Systematic Review Among Adults with Overweight or Obesity

Psychological and behavioral responses to daily weight gain during behavioral weight loss treatment

Self-weighing is consistently associated with more effective weight control. However, patterns show that participants disengage from their weight control behaviors following weight gain. Women with BMIs in the overweight/obese range (N = 50) enrolled in a long-term behavioral weight loss program completed ecological momentary assessment (EMA) surveys immediately after their daily weigh-ins. Nightly EMA surveys and self-monitoring data through Fitbit measured their weight control behavior that day. On days when participants gained weight (vs. lost or maintained), they reported more negative mood, more guilt/shame, and lower confidence in weight control. Motivation following daily weight gain depended on participants' overall satisfaction with their weight loss so far: more satisfied participants had marginally higher, but less satisfied participants had marginally lower motivation in response to daily weight gain. Greater guilt/shame and lower motivation after the weigh-in predicted less effective weight control behavior that day (e.g., lower likelihood of calorie tracking, fewer minutes of physical activity). Results demonstrate that even small weight gain is distressing and demoralizing for women in BWL programs, which can lead to goal disengagement. These findings have implications for future BWL interventions, including the potential utility of just-in-time adaptive interventions to promote more adaptive responses in the moments after weigh-ins.

Smartphone Applications to Prevent Type 2 Diabetes: A Systematic Review and Meta-Analysis

INTRODUCTION

Evidence supporting the use of apps for lifestyle behavior change and diabetes prevention in people at high risk of diabetes is lacking. The aim of this systematic review was to determine the acceptability and effectiveness of smartphone applications (apps) for the prevention of type 2 diabetes.

METHODS

PubMed, Embase, CINAHL and PsychInfo were searched from 2008 to 2023. Included studies involved adults at high risk of developing diabetes evaluating an app intervention with the aim of preventing type 2 diabetes. Random-effects meta-analyses were conducted for weight loss, body mass index (BMI), glycated hemoglobin, and waist circumference. Narrative synthesis was conducted for all studies, including qualitative studies exploring user perspectives.

RESULTS

Twenty-four studies (n=2,378) were included in this systematic review, including 9 randomized controlled trials (RCTs) with an average duration of 6 months, 10 quasi-experimental and 7 qualitative studies. Socially disadvantaged groups were poorly represented. Six RCTs were combined in meta-analyses. Apps were effective at promoting weight loss [mean difference (MD) -1.85; 95% CI -2.90 to -0.80] and decreasing BMI [MD -0.90, 95% CI -1.53 to -0.27], with no effect on glycated hemoglobin and waist circumference. No studies reported on diabetes incidence. Qualitative studies highlighted the need for app personalization.

DISCUSSION

Smartphone apps have a promising effect on preventing type 2 diabetes by supporting weight loss. Future robust trials should include diverse populations in co-design and evaluation of apps and explore the role of artificial intelligence in further personalizing interventions for higher engagement and effectiveness.

Exploring factors of adherence to weight loss interventions in population with overweight/obesity: an umbrella review

Adherence is key for achieving the optimal benefits from a weight loss intervention. Despite the number of studies on factors that promote adherence, their findings suggest inconsistent and fragmented evidence. The aim of this study was to review the existing factors of adherence to weight loss interventions and to find factors that facilitate the design of effective intervention programs. Six databases were searched for this umbrella review; after the screening process, 21 studies were included. A total of 47 factors were identified in six groups as relevant for adherence: (i) sociodemographic (n = 7), (ii) physical activity (n = 2), (iii) dietary (n = 8), (iv) behavioral (n = 4), (v) pharmacological (n = 3), and (vi) multi-intervention (n = 23). In addition, a map of adherence factors was created. The main findings are that with respect to demographic factors, the development of personalized intervention strategies based on the characteristics of specific populations is encouraged. Moreover, self-monitoring has been shown to be effective in behavioral, dietary, and multi-interventions, while technology has shown potential in dietary, behavioral, and multi-interventions. In addition, multi-interventions are adherence-promoting strategies, although more evidence is required on adherence to pharmacological interventions. Overall, the factor map can be controlled and modified by researchers and practitioners to improve adherence to weight loss interventions.

Barriers and enablers to a healthy lifestyle in people with infertility: a mixed-methods systematic review

BACKGROUND

While there is a recognized role of optimizing lifestyle (diet and physical activity) behaviours in the management of infertility, the best practice remains unknown and factors influencing the lifestyle of people with infertility are not well understood.

OBJECTIVE AND RATIONALE

This systematic review evaluated barriers and enablers to a healthy lifestyle in people with infertility, from the perspectives of people with infertility and health professionals, in order to inform optimal behavioural change strategies.

SEARCH METHODS

Ovid MEDLINE(R), PsycINFO, EMBASE, EBM Reviews, and CINAHL were searched from inception to 28 August 2023. Eligible studies were qualitative and quantitative primary studies that explored barriers and/or enablers to lifestyle for infertility management. Quality assessment was performed using the Centre for Evidence-Based Management Critical Appraisal of a Survey Tool and the Critical Appraisal Skills Programme Qualitative Checklist. Data were analysed by thematic analysis with themes mapped to the Capability, Opportunity, Motivation and Behaviour (COM-B) model and Theoretical Domains Framework (TDF).

OUTCOMES

After screening 12 326 abstracts and 99 full-texts, 27 studies were included (12 quantitative, 6 qualitative and 9 mixed-methods) with 22 studies of women with infertility (n = 2524), 11 studies of men with infertility (n = 1407), and 6 studies of health professionals (n = 372). We identified barriers and enablers relating to capability (e.g. strategies for behaviour change), opportunity (e.g. limited time, resources, and money), and motivation (e.g. interplay between lifestyle and emotional state). Based on the identified themes, suggested intervention components to integrate into lifestyle management of infertility include facilitating development of self-management skills to support lifestyle change (e.g. self-monitoring, action planning, and goal setting) and incorporating mental health strategies (e.g. providing information about the benefits of healthy lifestyle behaviours for mental health and encouraging patients to reframe healthy lifestyle behaviours as self-care strategies).

WIDER IMPLICATIONS

The findings have identified important factors that influence lifestyle management in people with infertility and have suggested relevant intervention components to consider when designing interventions. Given the paucity of qualitative studies identified, more research is needed to further understand the complex and interacting factors that shape lifestyle during the fertility journey.

Cookie cravings - Examining the impact of sugar content information on Christmas treat preferences via mobile eye-tracking

BACKGROUND

Diets high in added sugar can promote the development of overweight. Especially during the Holiday season, when high-sugar food is abundant, people overeat and gain more weight than during other times of the year. The present study with mobile eye-tracking glasses (Pupil Labs Invisible) investigated how sugar content information affects food preference (liking/wanting) and visual attention (where and how long one is looking) in a buffet-like situation.

METHODS

Fifty-eight participants who were well acquainted with the local Christmas traditions and foods (38 female, 19 male, one diverse; mean age = 25 years, SD = 6.3 years; mean body mass index = 22.2 kg/m2, SD = 3.2 kg/m2) were presented with four cookies and two non-food items (wrapped presents) in a free viewing task. Two of the displayed cookies were 'Christmas cookies' (cookies that are traditionally eaten only during the Holiday season) and two cookies had no Christmas association. The cookies were either labeled as cookies made with or without sugar, resulting in a 3 (Category: cookies with sugar, cookies without sugar, non-food) by 2 (Christmas association: yes, no) repeated-measures design.

RESULTS

Analyses of variance indicated that participants reported higher wanting and liking for cookies with sugar, particularly Christmas cookies (interaction effect for wanting: p = .047, ηp2 = .059; interaction effect for liking: p = .017, ηp2 = .084). Sugar-free cookies were fixated more often (p = .028; d = 0.35) and shorter (p < .001; d = 0.64) than sugar cookies.

CONCLUSION

Assuming that cookies are sugar-free reduced the reported preference for this product, which was associated with a more detail-oriented (critical) viewing pattern. The study's findings have potential implications for public health and can aid in developing targeted interventions to promote healthier food choices during festive periods. The new strategies should not focus on the sugar content of foods.

Weight Loss in Short-Term Interventions for Physical Activity and Nutrition Among Adults With Overweight or Obesity: A Systematic Review and Meta-Analysis

Introduction

Reaching, enrolling, and retaining participants in lengthy lifestyle change interventions for weight loss is a major challenge. The objective of our meta-analysis was to investigate whether lifestyle interventions addressing nutrition and physical activity lasting 6 months or less are effective for weight loss.

Methods

We searched for peer-reviewed studies on lifestyle change interventions of 6 months or less published from 2012 through 2023. Studies were screened based on inclusion criteria, including randomized controlled trials (RCTs) for adults with overweight or obesity. We used a random-effects model to pool the mean difference in weight loss between intervention and control groups. We also performed subgroup analyses by intervention length and control type.

Results

Fourteen RCTs were identified and included in our review. Half had interventions lasting less than 13 weeks, and half lasted from 13 to 26 weeks. Seven were delivered remotely, 4 were delivered in person, and 3 used combined methods. The pooled mean difference in weight change was -2.59 kg (95% CI, -3.47 to -1.72). The pooled mean difference measured at the end of the intervention was -2.70 kg (95% CI, -3.69 to -1.71) among interventions lasting less than 13 weeks and -2.40 kg (95% CI, -4.44 to -0.37) among interventions of 13 to 26 weeks.

Conclusion

Short-term multicomponent interventions involving physical activity and nutrition can achieve weight loss for adults with overweight or obesity. Offering short-term interventions as alternatives to long-term ones may reach people who otherwise would be unwilling or unable to enroll in or complete longer programs.

The Impact of Digital Self-Monitoring of Weight on Improving Diabetes Clinical Outcomes: Quasi-Randomized Study

BACKGROUND

The management of type 2 diabetes (T2D) and obesity, particularly in the context of self-monitoring, remains a critical challenge in health care. As nearly 80% to 90% of patients with T2D have overweight or obesity, there is a compelling need for interventions that can effectively manage both conditions simultaneously. One of the goals in managing chronic conditions is to increase awareness and generate behavioral change to improve outcomes in diabetes and related comorbidities, such as overweight or obesity. There is a lack of real-life evidence to test the impact of self-monitoring of weight on glycemic outcomes and its underlying mechanisms.

OBJECTIVE

This study aims to assess the efficacy of digital self-monitoring of weight on blood glucose (BG) levels during diabetes management, investigating whether the weight changes may drive glucose fluctuations.

METHODS

In this retrospective, real-world quasi-randomized study, 50% of the individuals who regularly used the weight monitoring (WM) feature were propensity score matched with 50% of the users who did not use the weight monitoring feature (NWM) based on demographic and clinical characteristics. All the patients were diagnosed with T2D and tracked their BG levels. We analyzed monthly aggregated data 6 months before and after starting their weight monitoring. A piecewise mixed model was used for analyzing the time trajectories of BG and weight as well as exploring the disaggregation effect of between- and within-patient lagged effects of weight on BG.

RESULTS

The WM group exhibited a significant reduction in BG levels post intervention (P<.001), whereas the nonmonitoring group showed no significant changes (P=.59), and both groups showed no differences in BG pattern before the intervention (P=.59). Furthermore, the WM group achieved a meaningful decrease in BMI (P<.001). Finally, both within-patient (P<.001) and between-patient (P=.008) weight variability was positively associated with BG levels. However, 1-month lagged back BMI was not associated with BG levels (P=.36).

CONCLUSIONS

This study highlights the substantial benefits of self-monitoring of weight in managing BG levels in patients with diabetes, facilitated by a digital health platform, and advocates for the integration of digital self-monitoring tools in chronic disease management. We also provide initial evidence of testing the underlying mechanisms associated with BG management, underscoring the potential role of patient empowerment.

Understanding Heterogeneity in Individual Responses to Digital Lifestyle Intervention Through Self-Monitoring Adherence Trajectories in Adults With Overweight or Obesity: Secondary Analysis of a 6-Month Randomized Controlled Trial

BACKGROUND

Achieving clinically significant weight loss through lifestyle interventions for obesity management is challenging for most individuals. Improving intervention effectiveness involves early identification of intervention nonresponders and providing them with timely, tailored interventions. Early and frequent self-monitoring (SM) adherence predicts later weight loss success, making it a potential indicator for identifying nonresponders in the initial phase.

OBJECTIVE

This study aims to identify clinically meaningful participant subgroups based on longitudinal adherence to SM of diet, activity, and weight over 6 months as well as psychological predictors of participant subgroups from a self-determination theory (SDT) perspective.

METHODS

This was a secondary data analysis of a 6-month digital lifestyle intervention for adults with overweight or obesity. The participants were instructed to perform daily SM on 3 targets: diet, activity, and weight. Data from 50 participants (mean age: 53.0, SD 12.6 y) were analyzed. Group-based multitrajectory modeling was performed to identify subgroups with distinct trajectories of SM adherence across the 3 SM targets. Differences between subgroups were examined for changes in clinical outcomes (ie, body weight, hemoglobin A1c) and SDT constructs (ie, eating-related autonomous motivation and perceived competence for diet) over 6 months using linear mixed models.

RESULTS

Two distinct SM trajectory subgroups emerged: the Lower SM group (21/50, 42%), characterized by all-around low and rapidly declining SM, and the Higher SM group (29/50, 58%), characterized by moderate and declining diet and weight SM with high activity SM. Since week 2, participants in the Lower SM group exhibited significantly lower levels of diet (P=.003), activity (P=.002), and weight SM (P=.02) compared with the Higher SM group. In terms of clinical outcomes, the Higher SM group achieved a significant reduction in body weight (estimate: -6.06, SD 0.87 kg; P<.001) and hemoglobin A1c (estimate: -0.38, SD 0.11%; P=.02), whereas the Lower SM group exhibited no improvements. For SDT constructs, both groups maintained high levels of autonomous motivation for over 6 months. However, the Lower SM group experienced a significant decline in perceived competence (P=.005) compared with the Higher SM group, which maintained a high level of perceived competence throughout the intervention (P=.09).

CONCLUSIONS

The presence of the Lower SM group highlights the value of using longitudinal SM adherence trajectories as an intervention response indicator. Future adaptive trials should identify nonresponders within the initial 2 weeks based on their SM adherence and integrate intervention strategies to enhance perceived competence in diet to benefit nonresponders.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05071287; https://clinicaltrials.gov/study/NCT05071287.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1016/j.cct.2022.106845.

Willingness to Use Digital Health Screening and Tracking Tools for Public Health in Sexual Minority Populations in a National Probability Sample: Quantitative Intersectional Analysis

BACKGROUND

Little is known about sexual minority adults' willingness to use digital health tools, such as pandemic-related tools for screening and tracking, outside of HIV prevention and intervention efforts for sexual minority men, specifically. Additionally, given the current cultural climate in the United States, heterosexual and sexual minority adults may differ in their willingness to use digital health tools, and there may be within-group differences among sexual minority adults.

OBJECTIVE

This study compared sexual minority and heterosexual adults' willingness to use COVID-19-related digital health tools for public health screening and tracking and tested whether sexual minority adults differed from each other by age group, gender, and race or ethnicity.

METHODS

We analyzed data from a cross-sectional, national probability survey (n=2047) implemented from May 30 to June 8, 2020, in the United States during the height of the public health response to the COVID-19 pandemic. Using latent-variable modeling, heterosexual and sexual minority adults were tested for differences in their willingness to use digital health tools for public health screening and tracking. Among sexual minority adults, specifically, associations with age, gender, and race or ethnicity were assessed.

RESULTS

On average, sexual minority adults showed greater willingness to use digital health tools for screening and tracking than heterosexual adults (latent factor mean difference 0.46, 95% CI 0.15-0.77). Among sexual minority adults, there were no differences by age group, gender, or race or ethnicity. However, African American (b=0.41, 95% CI 0.19-0.62), Hispanic or Latino (b=0.36, 95% CI 0.18-0.55), and other racial or ethnic minority (b=0.54, 95% CI 0.31-0.77) heterosexual adults showed greater willingness to use digital health tools for screening and tracking than White heterosexual adults.

CONCLUSIONS

In the United States, sexual minority adults were more willing to use digital health tools for screening and tracking than heterosexual adults. Sexual minority adults did not differ from each other by age, gender, or race or ethnicity in terms of their willingness to use these digital health tools, so no sexual orientation-based or intersectional disparities were identified. Furthermore, White heterosexual adults were less willing to use these tools than racial or ethnic minority heterosexual adults. Findings support the use of digital health tools with sexual minority adults, which could be important for other public health-related concerns (eg, the recent example of mpox). Additional studies are needed regarding the decision-making process of White heterosexual adults regarding the use of digital health tools to address public health crises, including pandemics or outbreaks that disproportionately affect minoritized populations.

Expert Opinion on the Utility of Telemedicine in Obesity Care: Recommendations on a Hybrid Multidisciplinary Integrated Care Follow-Up Algorithm

PURPOSE OF REVIEW

The proposed expert opinion was prepared by a panel of obesity and law specialists from Turkey to review the utility of telemedicine in obesity care and to provide a guidance document with recommendations on a hybrid multidisciplinary integrated care follow-up algorithm and the legislation governing telemedicine practice to assist obesity specialists in practicing the telemedicine.

RECENT FINDINGS

The efficacy and feasibility of telemedicine interventions in supporting obesity management programs even during pandemics confirm that obesity is a particularly well-suited field for telemedicine, emphasizing the strong likelihood of continued utilization of telemedicine in obesity management, beyond the pandemic period. Telemedicine has great potential to address several barriers to ongoing weight-management care, such as challenges of access to specialized care, cost, and time limitations as well as patient adherence to treatment. However, telemedicine practice should complement rather than replace the in-person visits which are unique in building rapport and offering social support. Accordingly, the participating experts recommend the use of a hybrid integrated care model in the management of obesity, with the use of telemedicine, as an adjunct to in-person visits, to enable the provision of suggested intensive obesity management via frequent visits by a multidisciplinary team of obesity specialists. Further research addressing the utility of telemedicine in terms of optimal modality and duration for successful long-term obesity management outcomes is necessary to develop specific guidelines on telemedicine practice. In addition, the legislation governing the norms and protocols on confidentiality, privacy, access, and liability needs to be improved.

Mobile health (m-health) smartphone interventions for adolescents and adults with overweight or obesity

BACKGROUND

Obesity is considered to be a risk factor for various diseases, and its incidence has tripled worldwide since 1975. In addition to potentially being at risk for adverse health outcomes, people with overweight or obesity are often stigmatised. Behaviour change interventions are increasingly delivered as mobile health (m-health) interventions, using smartphone apps and wearables. They are believed to support healthy behaviours at the individual level in a low-threshold manner.

OBJECTIVES

To assess the effects of integrated smartphone applications for adolescents and adults with overweight or obesity.

SEARCH METHODS

We searched CENTRAL, MEDLINE, PsycINFO, CINAHL, and LILACS, as well as the trials registers ClinicalTrials.gov and World Health Organization International Clinical Trials Registry Platform on 2 October 2023 (date of last search for all databases). We placed no restrictions on the language of publication.

SELECTION CRITERIA

Participants were adolescents and adults with overweight or obesity. Eligible interventions were integrated smartphone apps using at least two behaviour change techniques. The intervention could target physical activity, cardiorespiratory fitness, weight loss, healthy diet, or self-efficacy. Comparators included no or minimal intervention (NMI), a different smartphone app, personal coaching, or usual care. Eligible studies were randomised controlled trials of any duration with a follow-up of at least three months.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methodology and the RoB 2 tool. Important outcomes were physical activity, body mass index (BMI) and weight, health-related quality of life, self-efficacy, well-being, change in dietary behaviour, and adverse events. We focused on presenting studies with medium- (6 to < 12 months) and long-term (≥ 12 months) outcomes in our summary of findings table, following recommendations in the core outcome set for behavioural weight management interventions.

MAIN RESULTS

We included 18 studies with 2703 participants. Interventions lasted from 2 to 24 months. The mean BMI in adults ranged from 27 to 50, and the median BMI z-score in adolescents ranged from 2.2 to 2.5. Smartphone app versus no or minimal intervention Thirteen studies compared a smartphone app versus NMI in adults; no studies were available for adolescents. The comparator comprised minimal health advice, handouts, food diaries, smartphone apps unrelated to weight loss, and waiting list. Measures of physical activity: at 12 months' follow-up, a smartphone app compared to NMI probably reduces moderate to vigorous physical activity (MVPA) slightly (mean difference (MD) -28.9 min/week (95% confidence interval (CI) -85.9 to 28; 1 study, 650 participants; moderate-certainty evidence)). We are very uncertain about the results of estimated energy expenditure and cardiorespiratory fitness at eight months' follow-up. A smartphone app compared with NMI probably results in little to no difference in changes in total activity time at 12 months' follow-up and leisure time physical activity at 24 months' follow-up. Anthropometric measures: a smartphone app compared with NMI may reduce BMI (MD of BMI change -2.6 kg/m2, 95% CI -6 to 0.8; 2 studies, 146 participants; very low-certainty evidence) at six to eight months' follow-up, but the evidence is very uncertain. At 12 months' follow-up, a smartphone app probably resulted in little to no difference in BMI change (MD -0.1 kg/m2, 95% CI -0.4 to 0.3; 1 study; 650 participants; moderate-certainty evidence). A smartphone app compared with NMI may result in little to no difference in body weight change (MD -2.5 kg, 95% CI -6.8 to 1.7; 3 studies, 1044 participants; low-certainty evidence) at 12 months' follow-up. At 24 months' follow-up, a smartphone app probably resulted in little to no difference in body weight change (MD 0.7 kg, 95% CI -1.2 to 2.6; 1 study, 245 participants; moderate-certainty evidence). A smartphone app compared with NMI may result in little to no difference in self-efficacy for a physical activity score at eight months' follow-up, but the results are very uncertain. A smartphone app probably results in little to no difference in quality of life and well-being at 12 months (moderate-certainty evidence) and in little to no difference in various measures used to inform dietary behaviour at 12 and 24 months' follow-up. We are very uncertain about adverse events, which were only reported narratively in two studies (very low-certainty evidence). Smartphone app versus another smartphone app Two studies compared different versions of the same app in adults, showing no or minimal differences in outcomes. One study in adults compared two different apps (calorie counting versus ketogenic diet) and suggested a slight reduction in body weight at six months in favour of the ketogenic diet app. No studies were available for adolescents. Smartphone app versus personal coaching Only one study compared a smartphone app with personal coaching in adults, presenting data at three months. Two studies compared these interventions in adolescents. A smartphone app resulted in little to no difference in BMI z-score compared to personal coaching at six months' follow-up (MD 0, 95% CI -0.2 to 0.2; 1 study; 107 participants). Smartphone app versus usual care Only one study compared an app with usual care in adults but only reported data at three months on participant satisfaction. No studies were available for adolescents. We identified 34 ongoing studies.

AUTHORS' CONCLUSIONS

The available evidence is limited and does not demonstrate a clear benefit of smartphone applications as interventions for adolescents or adults with overweight or obesity. While the number of studies is growing, the evidence remains incomplete due to the high variability of the apps' features, content and components, which complicates direct comparisons and assessment of their effectiveness. Comparisons with either no or minimal intervention or personal coaching show minor effects, which are mostly not clinically significant. Minimal data for adolescents also warrants further research. Evidence is also scarce for low- and middle-income countries as well as for people with different socio-economic and cultural backgrounds. The 34 ongoing studies suggest sustained interest in the topic, with new evidence expected to emerge within the next two years. In practice, clinicians and healthcare practitioners should carefully consider the potential benefits, limitations, and evolving research when recommending smartphone apps to adolescents and adults with overweight or obesity.

A Digitally Enabled Combined Lifestyle Intervention for Weight Loss: Pilot Study in a Dutch General Population Cohort

BACKGROUND

Overweight and obesity rates among the general population of the Netherlands keep increasing. Combined lifestyle interventions (CLIs) focused on physical activity, nutrition, sleep, and stress management can be effective in reducing weight and improving health behaviors. Currently available CLIs for weight loss (CLI-WLs) in the Netherlands consist of face-to-face and community-based sessions, which face scalability challenges. A digitally enabled CLI-WL with digital and human components may provide a solution for this challenge; however, the feasibility of such an intervention has not yet been assessed in the Netherlands.

OBJECTIVE

The aim of this study was two-fold: (1) to determine how weight and other secondary cardiometabolic outcomes (lipids and blood pressure) change over time in a Dutch population with overweight or obesity and cardiometabolic risk participating in a pilot digitally enabled CLI-WL and (2) to collect feedback from participants to guide the further development of future iterations of the intervention.

METHODS

Participants followed a 16-week digitally enabled lifestyle coaching program rooted in the Fogg Behavior Model, focused on nutrition, physical activity, and other health behaviors, from January 2020 to December 2021. Participants could access the digital app to register and track health behaviors, weight, and anthropometrics data at any time. We retrospectively analyzed changes in weight, blood pressure, and lipids for remeasured users. Surveys and semistructured interviews were conducted to assess critical positive and improvement points reported by participants and health care professionals.

RESULTS

Of the 420 participants evaluated at baseline, 53 participated in the pilot. Of these, 37 (70%) were classified as overweight and 16 (30%) had obesity. Mean weight loss of 4.2% occurred at a median of 10 months postintervention. The subpopulation with obesity (n=16) showed a 5.6% weight loss on average. Total cholesterol decreased by 10.2% and low-density lipoprotein cholesterol decreased by 12.9% on average. Systolic and diastolic blood pressure decreased by 3.5% and 7.5%, respectively. Participants identified the possibility of setting clear action plans to work toward and the multiple weekly touch points with coaches as two of the most positive and distinctive components of the digitally enabled intervention. Surveys and interviews demonstrated that the digital implementation of a CLI-WL is feasible and well-received by both participants and health care professionals.

CONCLUSIONS

Albeit preliminary, these findings suggest that a behavioral lifestyle program with a digital component can achieve greater weight loss than reported for currently available offline CLI-WLs. Thus, a digitally enabled CLI-WL is feasible and may be a scalable alternative to offline CLI-WL programs. Evidence from future studies in a Dutch population may help elucidate the mechanisms behind the effectiveness of a digitally enabled CLI-WL.

Exploring the benefits and costs of a growth mindset in a digital app weight management program

We explored the potential benefits and costs of believing one can change their weight (i.e. growth mindset) in the context of a digital weight management program. We investigated mechanisms by which growth mindsets relate to weight loss achievement and body shame. Among participants seeking to lose weight (N = 1626; 74.7% female; 77.9% White; Mage = 45.7), stronger growth mindsets indirectly predicted greater weight loss achievement through positive offset expectations and subsequent increased program engagement. Additionally, stronger growth mindsets predicted less body shame through positive offset expectations but predicted more body shame through increased onset responsibility, replicating the double-edged sword model of growth mindsets. We conclude with applications that leverage growth mindsets for optimal behavior change while mitigating costs such as body shame.

Applications of digital health approaches for cardiometabolic diseases prevention and management in the Western Pacific region

Cardiometabolic diseases (CMDs) are the major types of non-communicable diseases, contributing to huge disease burdens in the Western Pacific region (WPR). The use of digital health (dHealth) technologies, such as wearable gadgets, mobile apps, and artificial intelligence (AI), facilitates interventions for CMDs prevention and treatment. Currently, most studies on dHealth and CMDs in WPR were conducted in a few high- and middle-income countries like Australia, China, Japan, the Republic of Korea, and New Zealand. Evidence indicated that dHealth services promoted early prevention by behavior interventions, and AI-based innovation brought automated diagnosis and clinical decision-support. dHealth brought facilitators for the doctor-patient interplay in the effectiveness, experience, and communication skills during healthcare services, with rapidly development during the pandemic of coronavirus disease 2019. In the future, the improvement of dHealth services in WPR needs to gain more policy support, enhance technology innovation and privacy protection, and perform cost-effectiveness research.

Decoding Heterogeneity in Data-Driven Self-Monitoring Adherence Trajectories in Digital Lifestyle Interventions for Weight Loss: A Qualitative Study

Background

Data-driven trajectory modeling is a promising approach for identifying meaningful participant subgroups with various self-monitoring (SM) responses in digital lifestyle interventions. However, there is limited research investigating factors that underlie different subgroups. This qualitative study aimed to investigate factors contributing to participant subgroups with distinct SM trajectory in a digital lifestyle intervention over 6 months.

Methods

Data were collected from a subset of participants (n = 20) in a 6-month digital lifestyle intervention. Participants were classified into Lower SM Group (n = 10) or a Higher SM (n = 10) subgroup based on their SM adherence trajectories over 6 months. Qualitative data were obtained from semi-structured interviews conducted at 3 months. Data were thematically analyzed using a constant comparative approach.

Results

Participants were middle-aged (52.9 ± 10.2 years), mostly female (65%), and of Hispanic ethnicity (55%). Four major themes with emerged from the thematic analysis: Acceptance towards SM Technologies, Perceived SM Benefits, Perceived SM Barriers, and Responses When Facing SM Barriers. Participants across both subgroups perceived SM as positive feedback, aiding in diet and physical activity behavior changes. Both groups cited individual and technical barriers to SM, including forgetfulness, the burdensome SM process, and inaccuracy. The Higher SM Group displayed positive problem-solving skills that helped them overcome the SM barriers. In contrast, some in the Lower SM Group felt discouraged from SM. Both subgroups found diet SM particularly challenging, especially due to technical issues such as the inaccurate food database, the time-consuming food entry process in the Fitbit app.

Conclusions

This study complements findings from our previous quantitative research, which used data-drive trajectory modeling approach to identify distinct participant subgroups in a digital lifestyle based on individuals' 6-month SM adherence trajectories. Our results highlight the potential of enhancing action planning problem solving skills to improve SM adherence in the Lower SM Group. Our findings also emphasize the necessity of addressing the technical issues associated with current diet SM approaches. Overall, findings from our study may inform the development of practical SM improvement strategies in future digital lifestyle interventions.

Trial registration

The study was pre-registered at ClinicalTrials.gov (NCT05071287) on April 30, 2022.

Are interactive and tailored data visualizations effective in promoting flu vaccination among the elderly? Evidence from a randomized experiment

OBJECTIVE

Although interactive data visualizations are increasingly popular for health communication, it remains to be seen what design features improve psychological and behavioral targets. This study experimentally tested how interactivity and descriptive titles may influence perceived susceptibility to the flu, intention to vaccinate, and information recall, particularly among older adults.

MATERIALS AND METHODS

We created data visualization dashboards on flu vaccinations, tested in a 2 (explanatory text vs none) × 3 (interactive + tailored, static + tailored, static + nontailored) + questionnaire-only control randomized between-participant online experiment (N   = 1378).

RESULTS

The flu dashboards significantly increased perceived susceptibility to the flu compared to the control: static+nontailored dashboard, b = 0.14, P = .049; static-tailored, b = 0.16, P = .028; and interactive+tailored, b = 0.15, P = .039. Interactive dashboards potentially decreased recall particularly among the elderly (moderation by age: b = -0.03, P = .073). The benefits of descriptive text on recall were larger among the elderly (interaction effects: b = 0.03, P = .025).

DISCUSSION

Interactive dashboards with complex statistics and limited textual information are widely used in health and public health but may be suboptimal for older individuals. We experimentally showed that adding explanatory text on visualizations can increase information recall particularly for older populations.

CONCLUSION

We did not find evidence to support the effectiveness of interactivity in data visualizations on flu vaccination intentions or on information recall. Future research should examine what types of explanatory text can best support improved health outcomes and intentions in other contexts. Practitioners should consider whether interactivity is optimal in data visualization dashboards for their populations.

Impact of feedback generation and presentation on self-monitoring behaviors, dietary intake, physical activity, and weight: a systematic review and meta-analysis

Self-monitoring of dietary intake, physical activity, and weight is a key strategy in behavioral interventions, and some interventions provide self-monitoring feedback to facilitate goal setting and promote engagement. This systematic review aimed to evaluate whether feedback increases intervention effectiveness, and which forms of feedback presentation (e.g., personalized vs. not personalized) and generation (i.e., human vs. algorithm-generated) are most effective. To achieve this aim, 5 electronic databases (PubMed/MEDLINE, Web of Science, CINAHL, PsycINFO, and Google Scholar) were searched in April 2022 and yielded 694 unique records, out of which 24 articles reporting on 19 studies were included (with a total of 3261 participants). Two reviewers independently screened titles and abstracts and then full texts and categorized articles as eligible or excluded according to the pre-registered criteria (i.e., availability of full text, peer reviewed manuscript in English; adult participants in a randomized controlled trial that included both self-monitoring and feedback; comparisons of different forms of feedback or comparisons of feedback vs. no feedback; primary outcomes of diet, physical activity, self-monitoring behavior, and/or weight). All included studies were assessed for methodological quality independently by two reviewers using the revised Cochrane risk-of-bias tool for randomized studies (version 2). Ten studies compared feedback to no feedback, 5 compared human- vs. algorithm-generated feedback, and the remaining 4 studies compared formats of feedback presentation (e.g., frequency, richness). A random effects meta-analysis indicated that physical activity interventions with feedback provision were more effective than physical activity interventions without feedback (d = 0.73, 95% CI [0.09;1.37]). No meta-analysis could be conducted for other comparisons due to heterogeneity of study designs and outcomes. There were mixed results regarding which form of feedback generation and presentation is superior. Limitations of the evidence included in this review were: lack of details about feedback provided, the brevity of most interventions, the exclusion of studies that did not isolate feedback when testing intervention packages, and the high risk of bias in many studies. This systematic review underlines the importance of including feedback in behavioral interventions; however, more research is needed to identify most effective forms of feedback generation and presentation to maximize intervention effectiveness.Trial registration (PROSPERO)CRD42022316206.

Digital Health for Oncological Care

ABSTRACT

Digital health tools extend well beyond telemedicine, holding great potential to advance oncological care. We survey digital health and provide recommendations across the health continuum, tailoring them to oncology, including prevention, detection and diagnosis, and treatment and monitoring. Within the prevention realm, we review wellness technologies, cancer screening, mental health solutions, and digital biomarkers. For detection and diagnosis, we describe existing and emerging solutions for remote patient monitoring and various means to capture digital biomarkers, the "digital exam," and "digital outcomes." Treatment and monitoring solutions include telemedicine, chatbots, and digital therapeutics, which are also explored. We also discuss a host of technology enablers that are required for successful implementation and sustainment of digital health-enabled care. Our recommendations pertain to health care systems as well as companies that work with these systems or provide care to patients directly.

Efficacy of an app-based multimodal lifestyle intervention on body weight in persons with obesity: results from a randomized controlled trial

BACKGROUND

Despite an increasing number of smartphone applications (apps) addressing weight management, data on the effect of app-based multimodal obesity treatment approaches on weight loss is limited. This study aimed to examine the effect of a digital multimodal weight loss intervention program delivered by an app on body weight in persons with obesity.

METHODS

For this single-centre randomized controlled study, 168 adults with a body mass index (BMI) between 30.0 and 40.0 kg/m2 without severe comorbidities were recruited in the region of Munich and randomized into two intervention groups. The ADHOC group received an app-based multimodal weight loss program from baseline on for 12 weeks plus 12 weeks of follow-up. The EXPECT group received the app-based intervention for 12 weeks after 12 weeks of "waiting" (no intervention). Anthropometric data, data on quality of life (EuroQol, EQ-5D-5L), and app usage data were collected.

RESULTS

64.3% of study participants were women, mean age was 46.8 ± 11.0 years, and mean BMI was 34.2 ± 2.8 kg/m2. The completers analysis resulted in a weight loss of 3.2 ± 3.2 kg (3.2 ± 3.0%) in the ADHOC group and 0.4 ± 2.6 kg (0.3 ± 2.6%) in the EXPECT group after 12 weeks, with a significant difference between the groups (β [95% CI] = -2.9 [-3.8; -1.9], p < 0.001). Completers in the ADHOC group showed weight maintenance after 24 weeks. The time spent on the app was associated with weight reduction (β [95% CI] = -0.10 [-0.18; -0.01], p = 0.03).

CONCLUSIONS

Application of a multimodal app-based weight loss program results in moderate weight loss in persons with obesity.

TRIAL REGISTRATION

This study was registered in the German Clinical Trials Register (Registration number: DRKS00025291).

Tailor Made: A Pilot Virtual Weight Loss Intervention Individually Tailored for African American Men

This study tests the acceptability and feasibility of the first virtual weight loss study individually tailored for middle-aged African American men. Tailor Made is a 3-month randomized controlled pilot of a weight loss intervention that included 58 overweight or obese African American men (mean age of 50.4; SD = 7.9). Control group participants received a Fitbit activity tracker and Bluetooth-enabled scale and copies of the self-led Tailor Made curriculum. Intervention group participants received the same Fitbit, Bluetooth-enabled scale, and curriculum and also participated in weekly, 45-minute virtual small group, professional-led education sessions using the Tailor Made curriculum and received three SMS text messages weekly: (a) a message individually tailored on African American Manhood that links men's values, goals, and motivation to health-promoting behavior; (b) a goal-tracking message to monitor physical activity, healthier eating, and lifestyle changes; and (c) a reminder 24 hours before their session. Participation rates in weekly small group sessions, randomization, and attendance at the assessments suggest that Tailor Made was feasible and acceptable. Only among intervention group participants, we found a small and significant decrease in BMI between baseline and final. In addition, active minutes of physical activity decreased for the control group while active minutes for the intervention group remained steady throughout the intervention. In sum, we demonstrated that a virtual, individually tailored weight loss intervention is feasible and acceptable to African American men. Participants valued the convenience of a virtual intervention, but there were a number of ways we may be able to enhance the potential benefits of this approach.

Racial Differences in Psychiatric Symptoms, Maladaptive Eating, and Lifestyle Behaviors After Bariatric Surgery

There are several psychological and behavioral factors associated with poorer outcomes following bariatric surgery, yet it is unknown whether and how these factors may differ by race. In this cross-sectional study, individuals who underwent bariatric surgery from 2018 to 2021 and up to 4 years post-surgery were invited to complete an online survey. Psychiatric symptoms, maladaptive eating patterns, self-monitoring behaviors, and exercise frequency were examined. Participants (N = 733) were 87% women, 63% White, with a mean age of 44 years. Analyses of covariance demonstrated that White individuals endorsed greater anxiety symptoms (p =.01) and emotional eating due to depression (p = .01), whereas Black individuals endorsed greater depression severity (p = .02). Logistic regression analyses demonstrated that White individuals were more likely to experience loss of control eating (OR= 1.7, p = .002), grazing (OR= 2.53, p <.001), and regular self-weighing (OR= 1.41, p <.001) than Black individuals, and were less likely to skip meals (OR= .61, p = .04), or partake in nighttime eating (OR= .40, p <.001). There were no racial differences in binge eating, emotional eating due to anxiety or frustration, use of a food diary, or exercise. Thus, depressive symptoms, skipping meals, and nighttime eating may be important, modifiable intervention targets to optimize the benefits of bariatric surgery and promote equitable outcomes.

Monitoring Your Weight-Loss Process Online: The Impacts of Prior Experiences and Online Social Support on Subsequent Weight-Loss Outcome

Online weight-loss communities (OWCs) have become increasingly popular for weight management; they enable individuals to monitor (i.e. self-monitoring) and discuss (i.e. social interaction) their weight-loss experiences. This study investigates the relationship between prior weight-loss experiences (success and failure), online social support, and subsequent weight-loss outcome in the context of OWCs and based on self-determination theory. We collected the data of 1465 users from one popular OWC and deployed two logit regression models to estimate the effects of prior weight-loss experiences on subsequent weight-loss success as well as the moderating role of social support. The results revealed that prior successful weight-loss experiences were positively related to subsequent weight-loss outcome, while the relationship between prior failed weight-loss experiences and subsequent weight-loss outcome was negative. Meanwhile, online social support can not only be positively related to subsequent weight-loss outcome, but also buffer the negative role of prior failed weight-loss experiences. Nevertheless, social support had no significant moderating role in the relationship between prior successful weight-loss experiences and subsequent weight-loss outcome. This study contributes to the literature on prior experiences and online social support in the context of OWCs and provides valuable insights to improve participants' engagement and their weight-loss success.

Effects of a health versus hedonic mindset on daily-life snacking behaviour

BACKGROUND

In today's obesogenic environment high-caloric palatable foods are omnipresent, making it hard for many to reach and maintain a healthy body weight. This study investigates the effects of a health versus hedonic mindset on daily-life snacking behaviour. The hypothesis is that a health mindset leads to reduced snacking behaviour compared to a hedonic mindset. This effect is expected to be most pronounced with high dietary restraint and least pronounced with high trait self-control.

METHODS

For 3 weeks, degree of craving and amount of snacks that were craved and consumed were assessed four times a day, using smartphone Ecological Momentary Assessment (EMA). A total of 111 female participants (body mass index range: 20-23.5) were randomly assigned to a 1-week health (n = 53) or hedonic (n = 58) mindset, occurring in week 2 of the EMA protocol. The mindset manipulations consisted of text messages, focusing either on the enjoyment of tasty food (hedonic) or on healthy living and eating (health).

RESULTS

contrary to our hypotheses, mindset did not affect snacking behaviour. Instead, degree of craving and intake of snacks reduced significantly over time, not moderated by mindset, dietary restraint (Restraint Scale) or trait self-control (Brief Self-Control Scale). Importantly, this was not due to reduced compliance. Possibly, the reduced craving and snacking behaviour were due to monitoring and/or socially desirable answering tendencies. Additional time point analyses showed that craving was strongest in the late afternoon (3:30-5:00 PM), and-across mindset conditions-degree of craving correlated negatively with trait self-control.

CONCLUSIONS

future studies could manipulate degree of monitoring and design individually tailored manipulations.

Smartphone Applications (Apps) for Nutrition Education: A Qualitative Analysis of Outpatient Dietitian Perspectives

OBJECTIVE

To explore how outpatient dietitians select and use applications (apps) to support nutrition education.

METHODS

Qualitative analysis of 20 dietitians who participated in semistructured interviews investigating their app use and recommendation processes. Transcripts were analyzed using thematic analysis.

RESULTS

Four themes described how dietitians perceive apps for nutrition education: (1) nutrition education goals focus on long-term lifestyle behavior change while protecting patients' relationship with food, (2) attitudes toward tracking apps influence app selection, (3) dietitians differentiate among patients who will benefit from tracking vs information apps, and (4) barriers to optimal app use result in adaptations by dietitians.

CONCLUSIONS AND IMPLICATIONS

Barriers exist to optimal app use for nutrition education. However, accessible app design, app selection guides, and research expounding the effects of apps and their use by dietitians may improve how practitioners incorporate apps into nutrition education.

Patterns and Predictors of Engagement With Digital Self-Monitoring During the Maintenance Phase of a Behavioral Weight Loss Program: Quantitative Study

BACKGROUND

Long-term self-monitoring (SM) of weight, diet, and exercise is commonly recommended by behavioral weight loss (BWL) treatments. However, sustained SM engagement is notoriously challenging; therefore, more must be learned about patterns of engagement with digital SM tools during weight loss maintenance (WLM). In addition, insight into characteristics that may influence SM engagement could inform tailored approaches for participants at risk for poor adherence.

OBJECTIVE

This study explored patterns of digital SM of weight, diet, and exercise during WLM (aim 1) and examined timing, patterns, and rates of disengagement and reengagement (aim 2). This study also assessed relationships between individual-level factors (weight-related information avoidance and weight bias internalization) and SM engagement (aim 3).

METHODS

Participants were 72 adults enrolled in a BWL program consisting of a 3-month period of weekly treatment designed to induce weight loss (phase I), followed by a 9-month period of less frequent contact to promote WLM (phase II). Participants were prescribed daily digital SM of weight, diet, and exercise. At baseline, self-report measures assessed weight-related information avoidance and weight bias internalization. SM adherence was objectively measured with the days per month that participants tracked weight, diet, and exercise. Repeated-measures ANOVA examined differences in adherence across SM targets. Multilevel modeling examined changes in adherence across phase II. Relationships between individual-level variables and SM adherence were assessed with Pearson correlations, 2-tailed independent samples t tests, and multilevel modeling.

RESULTS

During WLM, consistently high rates of SM (≥50% of the days in each month) were observed for 61% (44/72) of the participants for exercise, 40% (29/72) of the participants for weight, and 21% (15/72) of the participants for diet. Adherence for SM of exercise was higher than that for weight or diet (P<.001). Adherence decreased over time for all SM targets throughout phase II (P<.001), but SM of exercise dropped off later in WLM (mean 10.07, SD 2.83 months) than SM of weight (mean 7.92, SD 3.23 months) or diet (mean 7.58, SD 2.92 months; P<.001). Among participants with a period of low SM adherence (ie, <50% of the days in a month), only 33% (17/51 for weight, 19/57 for diet) to 46% (13/28 for exercise) subsequently had ≥1 months with high adherence. High weight-related information avoidance predicted a faster rate of decrease in dietary SM (P<.001). Participants with high weight bias internalization had the highest rates of weight SM (P=.03).

CONCLUSIONS

Participants in BWL programs have low adherence to the recommendation to sustain daily SM during WLM, particularly for SM of diet and weight. Weight-related information avoidance and weight bias internalization may be relevant indicators for SM engagement. Interventions may benefit from innovative strategies that target participants at key moments of risk for disengagement.

eHealth in obesity care

Obesity in adults is a growing health concern. Although effective, current treatment options have not been able to overcome the various factors that contribute toward rising obesity rates. eHealth might hold the capacity to improve the effectiveness, delivery and flexibility of some of these treatments. Here, we show that eHealth lifestyle change interventions delivered through smartphones (mHealth) can facilitate significant weight loss, making mHealth an attractive adjunct to clinical obesity care. However, evidence is currently limited to short-term effects, and is also lacking with regards to effectiveness based on socioeconomic status and ethnic group. This raises concerns around the potential and inadvertent widening of obesity prevalence disparities between groups as mHealth lifestyle change interventions are increasingly used in obesity care. Thus, we also describe opportunities to address these concerns and gaps in evidence.

Incorporating Consumers' Needs in Nutrition Apps to Promote and Maintain Use: Mixed Methods Study

BACKGROUND

Nutrition apps seem to be promising tools for supporting consumers toward healthier eating habits. There is a wide variety of nutrition apps available; however, users often discontinue app use at an early stage before a permanent change in dietary behavior can be achieved.

OBJECTIVE

The main objective of this study was to identify, from both a user and nonuser perspective, which functionalities should be included in nutrition apps to increase intentions to start and maintain use of these apps. A secondary objective was to gain insight into reasons to quit using nutrition apps at an early stage.

METHODS

This study used a mixed methods approach and included a qualitative and a quantitative study. The qualitative study (n=40) consisted of a home-use test with 6 commercially available nutrition apps, followed by 6 focus group discussions (FGDs) to investigate user experiences. The quantitative study was a large-scale survey (n=1420), which was performed in a representative sample of the Dutch population to quantify the FGDs' results. In the survey, several app functionalities were rated on 7-point Likert scales ranging from 1 (very unimportant) to 7 (very important).

RESULTS

A total of 3 different phases of app use, subdivided into 10 user-centric app aspects and 46 associated app functionalities, were identified as relevant nutrition app elements in the FGDs. Relevance was confirmed in the survey, as all user-centric aspects and almost all app functionalities were rated as important to include in a nutrition app. In the starting phase, a clear introduction (mean 5.45, SD 1.32), purpose (mean 5.40, SD 1.40), and flexible food tracking options (mean 5.33, SD 1.45) were the most important functionalities. In the use phase, a complete and reliable food product database (mean 5.58, SD 1.41), easy navigation (mean 5.56, SD 1.36), and limited advertisements (mean 5.53, SD 1.51) were the most important functionalities. In the end phase, the possibility of setting realistic goals (mean 5.23, SD 1.44), new personal goals (mean 5.13, SD 1.45), and continuously offering new information (mean 4.88, SD 1.44) were the most important functionalities. No large differences between users, former users, and nonusers were found. The main reason for quitting a nutrition app in the survey was the high time investment (14/38, 37%). This was also identified as a barrier in the FGDs.

CONCLUSIONS

Nutrition apps should be supportive in all 3 phases of use (start, use, and end) to increase consumers' intentions to start and maintain the use of these apps and achieve a change in dietary behavior. Each phase includes several key app functionalities that require specific attention from app developers. High time investment is an important reason to quit nutrition app use at an early stage.

Sharing digital self-monitoring data with others to enhance long-term weight loss: A randomized controlled trial

BACKGROUND

Participants in behavioral weight loss (BWL) programs increasingly use digital tools to self-monitor weight, physical activity, and dietary intake. Data collected with these tools can be systematically shared with other parties in ways that might support behavior change.

METHODS

Adults age 18 to 70 with overweight/obesity (BMI 27-50 kg/m2) will enroll in a remotely delivered, 24-month BWL program designed to produce and maintain a 10% weight loss. Participants will be asked to use a wireless body weight scale, wearable activity sensor, and dietary intake app daily. All participants will receive individual and group counseling, engage in text messaging with members of their group, and appoint a friend or family member to serve in a support role. A 2x2x2 factorial design will test the effects of three types of data sharing partnerships: 1) Coach Share: The behavioral coach will regularly view digital self-monitoring data and address data observations. 2) Group Share: Participants will view each other's self-monitoring data in small-group text messages. 3) Friend/Family Share: A friend or family member will view the participant's data via automated message. The primary outcome is weight loss at 24 months. Mediators and moderators of intervention effects will be tested.

CONCLUSION

This study will provide a clear indication of whether data sharing can improve long-term weight loss. This study will be the first to discern the mechanisms of action through which each type of data sharing may be beneficial, and elucidate conditions under which the benefits of data sharing may be maximized.

Factors influencing user acceptance of weight management apps among Chinese obese individuals during the COVID-19 pandemic

Background

During the COVID-19 epidemic, the number of obesities increased rapidly in China. Weight management apps have potential value in controlling obesity.

Objective

Explore the mechanisms behind the adoption of weight management applications by overweight and obese individuals, including psychological factors and demographic variables.

Methods

The theoretical model was extended from the technology acceptance model (TAM), and the structural equation model was used for hypothesis testing. From January 2020 to December 2021, we conducted a cross-sectional survey in six megacities in mainland China during the COVID-19 pandemic by an online questionnaire.

Results

1364 participants completed the questionnaire, and the proposed theoretical model explained 55.7% of the variance in behavioral intention. Perceived usefulness was predicted by perceived ease of use (β = 0. 290), attitude was jointly predicted by perceived usefulness (β = 0.118) and perceived ease of use (β = 0.159). Behavioral intention was predicted by perceived usefulness (β = 0. 256), perceived ease of use (β = 0. 463), attitude (β = 0. 293), and perceived risk (β = -0.136). Health awareness (β=0.016) did not significantly affect behavioral intention. Four demographic variables gender, age, education, and residence exerted significant moderating effects in theoretical model.

Conclusions

During the COVID-19 epidemic, the health awareness and behavior patterns of obese people have changed significantly. Psychological factors and demographic characteristics dynamically interact to generate user behavioral intentions of weight management applications. Weight management application developers and marketers should focus on perceived usefulness, safety, ease of use, and health awareness.

Psychological Support Strategies for Adults With Type 2 Diabetes in a Very Low-Carbohydrate Web-Based Program: Randomized Controlled Trial

BACKGROUND

A very low-carbohydrate (VLC) nutritional strategy may improve glycemic control and weight loss in adults with type 2 diabetes (T2D). However, the supplementary behavioral strategies that might be able to improve outcomes using this nutritional strategy are uncertain.

OBJECTIVE

This study aims to compare the impact of adding 3 different supplementary behavioral strategies to a web-based VLC diet intervention. To our knowledge, this is the first trial to randomize participants to different frequencies of dietary self-monitoring.

METHODS

The study included 112 overweight adults with T2D (hemoglobin A1c ≥6.5%) taking no antiglycemic medications or only metformin. They received a remotely delivered 12-month VLC diet intervention. Participants were randomly assigned through a full factorial 2×2×2 design to supplementary strategies: either daily or monthly dietary self-monitoring, either mindful eating training or not, and either positive affect skills training or not. Our research goal was to determine whether 3 different supplemental strategies had at least a medium effect size (Cohen d=0.5).

RESULTS

Overall, the VLC intervention led to statistically significant improvements in glycemic control (-0.70%, 95% CI -1.04% to -0.35%; P<.001), weight loss (-6.82%, 95% CI -8.57% to -5.08%; P<.001), and depressive symptom severity (Cohen d -0.67, 95% CI -0.92 to -0.41; P<.001). Furthermore, 30% (25/83) of the participants taking metformin at baseline reduced or discontinued their metformin. Only 1 Cohen d point estimate reached 0.5; daily (vs monthly) dietary self-monitoring had a worse impact on depressive symptoms severity (Cohen d=0.47, 95% CI -0.02 to 0.95; P=.06). None of the strategies had a statistically significant effect on outcomes. For changes in our primary outcome, hemoglobin A1c, the daily (vs monthly) dietary self-monitoring impact was 0.42% (95% CI -0.28% to 1.12%); for mindful eating, it was -0.47% (95% CI -1.15% to 0.22%); and for positive affect, it was 0.12% (95% CI -0.57% to 0.82%). Other results for daily (vs monthly) dietary self-monitoring were mixed, suggesting an increase in weight (0.98%) and depressive symptoms (Cohen d=0.47), less intervention satisfaction (Cohen d=-0.20), more sessions viewed (3.02), and greater dietary adherence (Cohen d=0.24). For mindful eating, the results suggested a benefit for dietary adherence (Cohen d=0.24) and intervention satisfaction (Cohen d=0.30). For positive affect, the results suggested a benefit for depressive symptoms (Cohen d=-0.32), the number of sessions viewed (3.68), dietary adherence (Cohen d=0.16), and intervention satisfaction (Cohen d=0.25).

CONCLUSIONS

Overall, our results support the use of a VLC diet intervention in adults with T2D. The addition of monthly (not daily) dietary self-monitoring, mindful eating, and positive affect skills training did not show a definitive benefit, but it is worth further testing.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03037528; https://clinicaltrials.gov/ct2/show/NCT03037528.

Physicians' Use of Digital Health Interventions in the Management of Nonalcoholic Fatty Liver Disease

Globally, the use of digital health interventions (DHIs) is expanding, along with growing scientific evidence of their effectiveness. Given the high and increasing prevalence of noncommunicable liver disease, we surveyed 295 physicians across Spain about their knowledge, beliefs, attitudes, practices, and access with regard to DHIs for patient care and in particular for liver diseases, including nonalcoholic fatty liver disease and nonalcoholic steatohepatitis. Physicians reported high familiarity with DHIs, although most had not recommended them in patient care. Addressing concerns, including limited available time, evidence of effectiveness, education, training, and access may contribute to an increased uptake of these technologies.

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

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

The Effects of Providing a Connected Scale in an App-Based Digital Health Program: Cross-sectional Examination

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Evaluating the effectiveness of vegetarian appeals in daily life: Comparing positive and negative imagery, and gauging differential responses

Persuasive appeals designed to reduce meat consumption often employ graphic images of the harms perpetuated by eating meat (e.g., cruel factory farming practices). However, because people are motivated to see themselves as moral, appeals that highlight omnivores' moral failings might be resisted or even backfire. Furthermore, individuals differ in ways that may influence their motivations and attitudes toward animals and meat-eating, and their responses to these appeals. Thus, in a two-week intervention study (N = 427), we compared effects of two vegetarian appeals-one employing graphic negative imagery (footage of factory farming cruelty), the other employing positive imagery (footage from farmed animal sanctuaries)-on daily meat consumption and related affects and cognitions. We also examined several personality traits and other individual differences that may confer differential effects of these appeals. Although neither appeal significantly reduced meat consumption, both the positive and negative appeal increased intentions to eat less meat, and led to more negative affect and cognition when eating meat. Moreover, several individual difference variables moderated the effects of these appeals on actual and intended meat consumption. Findings are discussed in relation to the difficulty of changing morally troublesome behaviour, and the use of graphic appeals despite their unclear impact on behaviour.

Detailed Versus Simplified Dietary Self-monitoring in a Digital Weight Loss Intervention Among Racial and Ethnic Minority Adults: Fully Remote, Randomized Pilot Study

BACKGROUND

Detailed self-monitoring (or tracking) of dietary intake is a popular and effective weight loss approach that can be delivered via digital tools, although engagement declines over time. Simplifying the experience of self-monitoring diet may counteract this decline in engagement. Testing these strategies among racial and ethnic minority groups is important as these groups are often disproportionately affected by obesity yet underrepresented in behavioral obesity treatment.

OBJECTIVE

In this 2-arm pilot study, we aimed to evaluate the feasibility and acceptability of a digital weight loss intervention with either detailed or simplified dietary self-monitoring.

METHODS

We recruited racial and ethnic minority adults aged ≥21 years with a BMI of 25 kg/m² to 45 kg/m² and living in the United States. The Pacific time zone was selected for a fully remote study. Participants received a 3-month stand-alone digital weight loss intervention and were randomized 1:1 to either the detailed arm that was instructed to self-monitor all foods and drinks consumed each day using the Fitbit mobile app or to the simplified arm that was instructed to self-monitor only red zone foods (foods that are highly caloric and of limited nutritional value) each day via a web-based checklist. All participants were instructed to self-monitor both steps and body weight daily. Each week, participants were emailed behavioral lessons, action plans, and personalized feedback. In total, 12 a priori benchmarks were set to establish feasibility, including outcomes related to reach, retention, and self-monitoring engagement (assessed objectively via digital tools). Acceptability was assessed using a questionnaire. Weight change was assessed using scales shipped to the participants' homes and reported descriptively.

RESULTS

The eligibility screen was completed by 248 individuals, of whom 38 (15.3%) were randomized, 18 to detailed and 20 to simplified. At baseline, participants had a mean age of 47.4 (SD 14.0) years and BMI of 31.2 (SD 4.8) kg/m². More than half (22/38, 58%) were identified as Hispanic of any race. The study retention rate was 92% (35/38) at 3 months. The detailed arm met 9 of 12 feasibility benchmarks, while the simplified arm met all 12. Self-monitoring engagement was moderate to high (self-monitoring diet: median of 49% of days for detailed, 97% for simplified; self-monitoring steps: 99% for detailed, 100% for simplified; self-monitoring weight: 67% for detailed, 80% for simplified). Participants in both arms reported high satisfaction, with 89% indicating that they would recommend the intervention. Weight change was -3.4 (95% CI -4.6 to -2.2) kg for detailed and -3.3 (95% CI -4.4 to -2.2) kg for simplified.

CONCLUSIONS

A digital weight loss intervention that incorporated either detailed or simplified dietary self-monitoring was feasible, with high retention and engagement, and acceptable to racial and ethnic minority adults.

TRIAL REGISTRATION

ASPREDICTED #66674; https://aspredicted.org/ka478.pdf.

Multimodal Telemonitoring for Weight Reduction in Patients With Sleep Apnea: A Randomized Controlled Trial

BACKGROUND

Telemonitoring the use of CPAP devices and remote feedback on device data effectively optimizes CPAP adherence in patients with OSA.

RESEARCH QUESTION

Can expanding the scope of telemonitoring and remote feedback to body weight (BW), BP, and physical activity enhance efforts for BW reduction in Patients with OSA receiving CPAP?

STUDY DESIGN AND METHODS

Participants were recruited from patients at 16 sleep centers in Japan with OSA and obesity who were receiving CPAP therapy. Obesity was defined as a BMI of ≥ 25 kg/m², based on Japanese obesity guidelines. Implementation of CPAP telemonitoring was enhanced with electronic scales, BP monitors, and pedometers that could transmit data from devices wirelessly. Participants were randomized to the multimodal telemonitoring group or the usual CPAP telemonitoring group and were followed up for 6 months. Attending physicians provided monthly telephone feedback calls to the usual CPAP telemonitoring group on CPAP data obtained remotely. In the multimodal telemonitoring group, physicians additionally encouraged participants to reduce their BW, after sharing the remotely obtained data on BW, BP, and step count. The primary outcome was set as ≥ 3% BW reduction from baseline.

RESULTS

One hundred sixty-eight participants (BMI, 31.7 ± 4.9 kg/m²) completed the study, and ≥ 3% BW reduction occurred in 33 of 84 participants (39.3%) and 21 of 84 participants (25.0%) in the multimodal telemonitoring and usual CPAP telemonitoring groups, respectively (P = .047). Whereas no significant differences were found between the two groups in the change in office and home BP, daily step counts during the study period were significantly higher in the multimodal telemonitoring group than in the usual CPAP telemonitoring group (4,767 steps/d [interquartile range (IQR), 2,864-6,617 steps/d] vs 3,592 steps/d [IQR, 2,117-5,383 steps/d]; P = .02) INTERPRETATION: Multimodal telemonitoring may enhance BW reduction efforts in patients with OSA and obesity.

TRIAL REGISTRY

UMIN Clinical Trials Registry; No.: UMIN000033607; URL: www.umin.ac.jp/ctr/index.htm.

Long-Term Effectiveness of a Smartphone App and a Smart Band on Arterial Stiffness and Central Hemodynamic Parameters in a Population with Overweight and Obesity (Evident 3 Study): Randomised Controlled Trial

BACKGROUND

mHealth technologies could help to improve cardiovascular health; however, their effect on arterial stiffness and hemodynamic parameters has not been explored to date.

OBJECTIVE

To evaluate the effect of a mHealth intervention, at 3 and 12 months, on arterial stiffness and central hemodynamic parameters in a sedentary population with overweight and obesity.

METHODS

Randomised controlled clinical trial (Evident 3 study). 253 subjects were included: 127 in the intervention group (IG) and 126 in the control group (CG). The IG subjects were briefed on the use of the Evident 3 app and a smart band (Mi Band 2, Xiaomi) for 3 months to promote healthy lifestyles. All measurements were recorded in the baseline visit and at 3 and 12 months. The carotid-femoral pulse wave velocity (cfPWV) and the central hemodynamic parameters were measured using a SphigmoCor System^® device, whereas the brachial-ankle pulse wave velocity (baPWV) and the Cardio Ankle Vascular Index (CAVI) were measured using a VaSera VS-2000^® device.

RESULTS

Of the 253 subjects who attended the initial visit, 237 (93.7%) completed the visit at 3 months of the intervention, and 217 (85.3%) completed the visit at 12 months of the intervention. At 12 months, IG showed a decrease in peripheral augmentation index (PAIx) (-3.60; 95% CI -7.22 to -0.00) and ejection duration (ED) (-0.82; 95% CI -1.36 to -0.27), and an increase in subendocardial viability ratio (SEVR) (5.31; 95% CI 1.18 to 9.44). In CG, cfPWV decreased at 3 months (-0.28 m/s; 95% CI -0.54 to -0.02) and at 12 months (-0.30 m/s, 95% CI -0.54 to -0.05), central diastolic pressure (cDBP) decreased at 12 months (-1.64 mm/Hg; 95% CI -3.19 to -0.10). When comparing the groups we found no differences between any variables analyzed.

CONCLUSIONS

In sedentary adults with overweight or obesity, the multicomponent intervention (Smartphone app and an activity-tracking band) for 3 months did not modify arterial stiffness or the central hemodynamic parameters, with respect to the control group. However, at 12 months, CG presented a decrease of cfPWV and cDBP, whereas IG showed a decrease of PAIx and ED and an increase of SEVR.

Do physical activity interventions combining self-monitoring with other components provide an additional benefit compared with self-monitoring alone? A systematic review and meta-analysis

Objective

To determine the net effect of different physical activity intervention components on step counts in addition to self-monitoring.

Design

A systematic review with meta-analysis and meta-regression.

Data sources

Five databases (PubMed, Scopus, Web of Science, ProQuest and Discus) were searched from inception to May 2022. The database search was complemented with backward and forward citation searches and search of the references from relevant systematic reviews.

Eligibility criteria

Randomised controlled trials comparing an intervention using self-monitoring (active control arm) with an intervention comprising the same treatment PLUS any additional component (intervention arm).

Data extraction and synthesis

The effect measures were mean differences in daily step count. Meta-analyses were performed using random-effects models, and effect moderators were explored using univariate and multivariate meta-regression models.

Results

Eighty-five studies with 12 057 participants were identified, with 75 studies included in the meta-analysis at postintervention and 24 at follow-up. At postintervention, the mean difference between the intervention and active control arms was 926 steps/day (95% CI 651 to 1201). At a follow-up, the mean difference was 413 steps/day (95% CI 210 to 615). Interventions with a prescribed goal and involving human counselling, particularly via phone/video calls, were associated with a greater mean difference in the daily step count than interventions with added print materials, websites, smartphone apps or incentives.

Conclusion

Physical activity interventions that combine self-monitoring with other components provide an additional modest yet sustained increase in step count compared with self-monitoring alone. Some forms of counselling, particularly remote phone/video counselling, outperformed other intervention components, such as websites and smartphone apps.

PROSPERO registered number

CRD42020199482.

Exercise in Obesity-the Role of Technology in Health Services: Can This Approach Work?

PURPOSE OF REVIEW

Physical activity (PA) is an important strategy to prevent and treat obesity. Electronic health (eHealth) interventions, such as wearable activity monitors and smartphone apps, may promote adherence to regular PA and successful weight loss. This review highlights the evidence for eHealth interventions in promoting PA and reducing weight.

RECENT FINDINGS

Wearables can increase PA and are associated with moderate weight loss in middle/older-aged individuals, with less convincing effects long-term (> 1 year) and in younger people. Data for interventions such as mobile phone applications, SMS, and exergaming are less robust. Investigations of all eHealth interventions are often limited by complex, multi-modality study designs, involving concomitant dietary modification, making the independent contribution of each eHealth intervention on body weight challenging to assess. eHealth interventions may promote PA, thereby contributing to weight loss/weight maintenance; however, further evaluation is required for this approach to be adopted into routine clinical practice.

Nutrition-Related Mobile Application for Daily Dietary Self-Monitoring

Nutrition apps for mobile devices such as smartphones are becoming more widely available. They can help ease the arduous chore of documenting intake for nutritional assessment and self-monitoring. This allows people to control food intake, support their participation in physical activities, and promote a healthy lifestyle. However, there remains a lack of research regarding systematic analysis mapping studies in this area. The objective of this study is to identify dietary self-monitoring implementation strategies on a mobile application. This study analyzed 205 journals from the Scopus database using the descriptive-analytic method. The records used in this exploration study were those released between 2007 and 2021 that were collected based on the keywords “dietary self-monitoring,” or “nutrition application,” or “nutrition apps,” and “calorie application.” Data analysis was conducted using the VOSviewer and NVivo software analytical tools. The results show that research studies on dietary self-monitoring increased in 2017. Results also indicated that the country that contributed the most to this topic was China. The study on mobile applications for dietary self-monitoring revealed seven clusters of dominant themes: attitude to improved dietary behaviors, parameters for disease diagnosis, noncommunicable diseases, methods, nutrition algorithms, mobile health applications, and body mass index. This study also analyzed research trends by year. The current research trends are about dietary self-monitoring using a mobile application that can upgrade people's lifestyles, enable real-time meal recording and the convenience of automatically calculating the calorie content of foods consumed, and potentially improve the delivery of health behavior modification interventions to large groups of people. The researchers summarized the recent advances in dietary self-monitoring research to shed light on their research frontier, trends, and hot topics through bibliometric analysis and network visualization. These findings may provide valuable guidance for future research and perspectives in this rapidly developing field.

Expert opinions on reducing dietary self-monitoring burden and maintaining efficacy in weight loss programs: A Delphi study

Objective

Dietary self-monitoring is consistently related to both short- and long-term weight loss, but typically declines over time. Adopting an abbreviated approach to self-monitoring might reduce burden and potentially increase engagement while maintaining efficacy.

Methods

Using a Delphi-type study, experts were queried about abbreviated self-monitoring approaches that might best balance efficacy and burden and asked to identify when these approaches might best be implemented within a behavioral weight loss program. Experts were surveyed three times until consensus was reached.

Results

Experts identified three main categories of promising strategies for abbreviated self-monitoring regardless of whether individuals have been successful with weight loss or full dietary self-monitoring: (1) self-weighing only, (2) reducing the foods/beverages self-monitored to those that are often less routine and higher in caloric density, and (3) reducing the number of days per week to engage in full dietary self-monitoring. Experts recommended transitioning to abbreviated self-monitoring after 2 weeks of no self-monitoring among individuals who were struggling and after reaching 5%-10% weight loss among successful individuals.

Conclusions

These expert opinions offer a foundation to experimentally manipulate promising strategies for reducing burden and increasing long-term engagement in self-monitoring, with a goal of enhancing long-term weight control.

What Intervention Elements Drive Weight Loss in Blended-Care Behavior Change Interventions? A Real-World Data Analysis with 25,706 Patients

Background: Blended-care behavior change interventions (BBCI) are a combination of digital care and coaching by health care professionals (HCP), which are proven effective for weight loss. However, it remains unclear what specific elements of BBCI drive weight loss. Objectives: This study aims to identify the distinct impact of HCP-elements (coaching) and digital elements (self-monitoring, self-management, and education) for weight loss in BBCI. Methods: Long-term data from 25,706 patients treated at a digital behavior change provider were analyzed retrospectively using a ridge regression model to predict weight loss at 3, 6, and 12 months. Results: Overall relative weight loss was −1.63 kg at 1 month, −3.61 kg at 3 months, −5.28 kg at 6 months, and −6.55 kg at 12 months. The four factors of BBCI analyzed here (coaching, self-monitoring, self-management, and education) predict weight loss with varying accuracy and degree. Coaching, self-monitoring, and self-management are positively correlated with weight losses at 3 and 6 months. Learn time (i.e., self-guided education) is clearly associated with a higher degree of weight loss. Number of appointments outside of app coaching with a dietitian (coach) was negatively associated with weight loss. Conclusions: The results testify to the efficacy of BBCI for weight loss-with particular positive associations per time point-and add to a growing body of research that characterizes the distinct impact of intervention elements in real-world settings, aiming to inform the design of future interventions for weight management.

Mobile health plus community health worker support for weight management among public housing residents (Path to Health): A randomized controlled trial protocol

Interventions delivered by mobile devices (mHealth interventions) have the potential to increase access to weight management treatment in low-income populations. However, little prior research has examined effects of mHealth programming plus phone-based community health worker (CHW) support for weight management among public housing residents. For our intervention, we first interacted with a community advisory board to collect feedback on proposed intervention components. Transcripts from 5 advisory board meetings were coded and qualitative data was organized into themes. We used these data to inform our ongoing trial, in which public housing residents are randomized to one of three different groups: phone text messaging and digital self-weighing (mHealth only); mHealth intervention plus CHW behavioral phone counseling (mHealth+CHW); or assessment only to evaluate their differential effects on weight loss at 6- and 12-month follow-up. We will examine changes in diet and physical activity behaviors as well as potential mediating and moderating factors. Results of this trial could provide support for technology-based weight management interventions which may have greater potential for scalability and long-term dissemination than face-to-face programming. Clinical Trial Registration Number: NCT04852042.

Effectiveness of weight management interventions for adults delivered in primary care: systematic review and meta-analysis of randomised controlled trials

OBJECTIVE

To examine the effectiveness of behavioural weight management interventions for adults with obesity delivered in primary care.

DESIGN

Systematic review and meta-analysis of randomised controlled trials.

ELIGIBILITY CRITERIA FOR SELECTION OF STUDIES

Randomised controlled trials of behavioural weight management interventions for adults with a body mass index ≥25 delivered in primary care compared with no treatment, attention control, or minimal intervention and weight change at ≥12 months follow-up.

DATA SOURCES

Trials from a previous systematic review were extracted and the search completed using the Cochrane Central Register of Controlled Trials, Medline, PubMed, and PsychINFO from 1 January 2018 to 19 August 2021.

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently identified eligible studies, extracted data, and assessed risk of bias using the Cochrane risk of bias tool. Meta-analyses were conducted with random effects models, and a pooled mean difference for both weight (kg) and waist circumference (cm) were calculated.

MAIN OUTCOME MEASURES

Primary outcome was weight change from baseline to 12 months. Secondary outcome was weight change from baseline to ≥24 months. Change in waist circumference was assessed at 12 months.

RESULTS

34 trials were included: 14 were additional, from a previous review. 27 trials (n=8000) were included in the primary outcome of weight change at 12 month follow-up. The mean difference between the intervention and comparator groups at 12 months was -2.3 kg (95% confidence interval -3.0 to -1.6 kg, I²=88%, P<0.001), favouring the intervention group. At ≥24 months (13 trials, n=5011) the mean difference in weight change was -1.8 kg (-2.8 to -0.8 kg, I²=88%, P<0.001) favouring the intervention. The mean difference in waist circumference (18 trials, n=5288) was -2.5 cm (-3.2 to -1.8 cm, I²=69%, P<0.001) in favour of the intervention at 12 months.

CONCLUSIONS

Behavioural weight management interventions for adults with obesity delivered in primary care are effective for weight loss and could be offered to members of the public.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42021275529.

Personalized Self-Monitoring of Energy Balance through Integration in a Web-Application of Dietary, Anthropometric, and Physical Activity Data

Self-monitoring of weight, diet and physical activity is a valuable component of behavioral weight loss treatment. The validation and user-friendliness of this approach is not optimal since users are selected from homogeneous pools and rely on different applications, increasing the burden and achieving partial, generic and/or unrelated information about their metabolic state. Moreover, studies establishing type, time, duration, and adherence criteria for self-monitoring are lacking. In this study, we developed a digital web-based application (ArmOnIA), which integrates dietary, anthropometric, and physical activity data and provides a personalized estimation of energy balance. Moreover, we determined type, time, duration, and adherence criteria for self-monitoring to achieve significant weight loss in a highly heterogeneous group. A single-arm, uncontrolled prospective study on self-monitored voluntary adults for 7 months was performed. Hierarchical clustering of adherence parameters yielded three behavioral approaches: high (HA), low (LA), and medium (MA) adherence. Average BMI decrease is statistically significant between LA and HA. Moreover, we defined thresholds for the minimum frequencies and duration of dietary and weight self-monitoring. This approach can provide the correct clues to empower citizens with scientific knowledge, augmenting their self-awareness with the aim of achieving long-lasting results when pursuing a healthy lifestyle.