Mobile Application Interventions and Weight Loss in Type 2 Diabetes: A Meta-Analysis

The effectiveness of mobile app usage in facilitating weight loss: An observational study

Aim

With increasing rates of global obesity and associated health issues, there is an ever-increasing need for weight management solutions to be more accessible. Mobile applications offer accessible support systems and have the potential to offer a viable and effective weight management solution as an alternative to traditional healthcare models.

Objective

To evaluate the effectiveness of the SIMPLE mobile application for time-restricted eating in achieving weight loss (WL).

Methods

User data were analyzed between January 2021 and January 2023. In-app activity was calculated as the proportion of active days over 12, 26 and 52 weeks. A day is considered active if it contains at least one in-app action (e.g., logging weight, food, fasting, or physical activity). Users were categorized into four in-app activity levels: inactive (in-app activity <33%), medium activity (33%-66%), high activity (66%-99%), and maximal activity (100%). Weight change among in-app activity groups was assessed at 12, 26, and 52 weeks.

Results

Out of 53,482 users, a positive association was found between the use of the SIMPLE app and WL. Active app users lost more weight than their less active counterparts. Active users had a median WL of 4.20%, 5.04%, and 3.86% at 12, 26, and 52 weeks, respectively. A larger percentage of active users-up to 50.26%-achieved clinically significant WL (≥5%) when compared to inactive users. A dose-response relationship between WL and app usage was found after adjusting for gender, age, and initial Body Mass Index; a 10% increase in app activity correlated with increased WL by 0.43, 0.66 and 0.69 kg at 12, 26, and 52 weeks, respectively.

Conclusions

The study demonstrates that the SIMPLE app enables effective WL directly associated with the level of app engagement. Mobile health applications offer an accessible and effective weight management solution and should be considered when supporting adults to lose weight.

Efficacy of information and communication technology interventions for the management of diabetes mellitus: An umbrella review and evidence map

INTRODUCTION

We validated the quality of evidence and potential benefits of information and communication technology interventions on diabetes-related health outcomes.

METHODS

We systematically searched PubMed/MEDLINE, Embase, Google Scholar, and CINAHL and manually searched the reference lists of the retrieved review articles from each database's inception to October 2022. Randomized controlled trials were included to determine the benefits of information and communication technology interventions on diabetes outcomes.

RESULTS

Ten meta-analyses of randomized controlled trials were included, with 37 unique outcomes encompassing 379 studies and >70,000 participants across 47 countries and six continents. Information and communication technology intervention was associated with reduced HbA1c levels in patients with type 1 (moderate certainty), type 2 (moderate certainty), and gestational diabetes (low certainty) and showed potential benefits for type 2 diabetes, demonstrating a reduction in systolic blood pressure (high certainty), low-density lipoprotein cholesterol (low certainty), and body weight (low certainty), whereas those for gestational diabetes demonstrated a reduction in fasting (low certainty) and 2-h postprandial blood glucose levels (low certainty).

CONCLUSION

This umbrella review and evidence map revealed varying evidence on the potential benefits of information and communication technology interventions for diabetes-related outcomes. Our results demonstrate these interventions to be novel treatment options for policymakers and physicians to establish personalized health strategies.

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.

Development of a crowdsourcing- and gamification-based mobile application to collect epidemiological information and promote healthy lifestyles in Mexico

We developed a mobile application to promote healthy lifestyles and collect non-communicable disease (NCD) data in Mexico. Its theoretical foundations are supported by a framework-guided literature review. With design sprints, Scrum, Model-View-Controller, and Representational State Transfer architecture, we operationalized evidence-based nutrition/physical activity information into a crowdsourcing- and gamification-based application. The application was piloted for three months to monitor the response of 520 adults. Potential improvements were characterized, considering benchmarking, expert guidance, and standards. Salud Activa (English: Active Health) has two crowdsourcing modules: Nutritional scanner, scanning products' bar codes, providing nutritional data, and allowing new product registry feeding our databases; Surveys, comprising gradually-released NCD questions. Three intervention modules were generated: Drinks diary, a beverage assessment component to receive hydration recommendations; Step counter, monitoring users' steps via Google Fit/Health-iOS; Metabolic Avatar, interconnecting modules and changing as a function of beverage and step records. The 3-month median of Salud Activa use was seven days (IQR = 3-12), up to 35% of participants completed a Survey section, and 157 food products were registered through Nutritional scanner. Better customization might benefit usability and user engagement. Quantitative and qualitative data will enhance Salud Activa's design, user uptake, and efficacy in interventions delivered through this platform.

Barriers and Enablers to the Adoption of a Healthier Diet Using an App: Qualitative Interview Study With Patients With Type 2 Diabetes Mellitus

BACKGROUND

Adopting a healthy diet is one of the cornerstones of type 2 diabetes (T2D) management. Apps are increasingly used in diabetes self-management, but most studies to date have focused on assessing their impact in terms of weight loss or glycemic control, with limited evidence on the behavioral factors that influence app use to change dietary habits.

OBJECTIVE

The main objectives of this study were to assess the enablers and barriers to adopting a healthier diet using the Gro Health app in 2 patient groups with T2D (patients with recently diagnosed and long-standing T2D) and to identify behavior change techniques (BCTs) to enhance enablers and overcome barriers.

METHODS

Two semistructured qualitative interview studies were conducted; the first study took place between June and July 2021, with a sample of 8 patients with recently diagnosed (<12 mo) T2D, whereas the second study was conducted between May and June 2022 and included 15 patients with long-standing (>18 mo) T2D. In both studies, topic guides were informed by the Capability, Opportunity, Motivation, and Behavior model and the Theoretical Domains Framework. Transcripts were analyzed using a combined deductive framework and inductive thematic analysis approach. The Behavior Change Wheel framework was applied to identify appropriate BCTs that could be used in future iterations of apps for patients with diabetes. Themes were compared between the patient groups.

RESULTS

This study identified similarities and differences between patient groups in terms of enablers and barriers to adopting a healthier diet using the app. The main enablers for recently diagnosed patients included the acquired knowledge about T2D diets and skills to implement these, whereas the main barriers were the difficulty in deciding which app features to use and limited cooking skills. By contrast, for patients with long-standing T2D, the main enablers included knowledge validation provided by the app, along with app elements to help self-regulate food intake; the main barriers were the limited interest paid to the content provided or limited skills engaging with apps in general. Both groups reported more enablers than barriers to performing the target behavior when using the app. Consequently, BCTs were selected to address key barriers in both groups, such as simplifying the information hierarchy in the app interface, including tutorials demonstrating how to use the app features, and redesigning the landing page of the app to guide users toward these tutorials.

CONCLUSIONS

Patients with recently diagnosed and long-standing T2D encountered similar enablers but slightly different barriers when using an app to adopting a healthier diet. Consequently, the development of app-based approaches to adopt a healthier diet should account for these similarities and differences within patient segments to reduce barriers to performing the target behavior.

An umbrella review of effectiveness and efficacy trials for app-based health interventions

Health interventions based on mobile phone or tablet applications (apps) are promising tools to help patients manage their conditions more effectively. Evidence from randomized controlled trials (RCTs) on efficacy and effectiveness of such interventions is increasingly available. This umbrella review aimed at mapping and narratively summarizing published systematic reviews on efficacy and effectiveness of mobile app-based health interventions within patient populations. We followed a pre-specified publicly available protocol. Systematic reviews were searched in two databases from inception until August 28, 2023. Reviews that included RCTs evaluating integrated or stand-alone health app interventions in patient populations with regard to efficacy/effectiveness were considered eligible. Information on indications, outcomes, app characteristics, efficacy/effectiveness results and authors' conclusions was extracted. Methodological quality was assessed using the AMSTAR2 tool. We identified 48 systematic reviews published between 2013 and 2023 (35 with meta-analyses) that met our inclusion criteria. Eleven reviews included a broad spectrum of conditions, thirteen focused on diabetes, five on anxiety and/or depression, and others on various other indications. Reported outcomes ranged from medication adherence to laboratory, anthropometric and functional parameters, symptom scores and quality of life. Fourty-one reviews concluded that health apps may be effective in improving health outcomes. We rated one review as moderate quality. Here we report that the synthesized evidence on health app effectiveness varies largely between indications. Future RCTs should consider reporting behavioral (process) outcomes and measures of healthcare resource utilization to provide deeper insights on mechanisms that make health apps effective, and further elucidate their impact on healthcare systems.

An Explainable Artificial Intelligence Software Tool for Weight Management Experts (PRIMO): Mixed Methods Study

BACKGROUND

Predicting the likelihood of success of weight loss interventions using machine learning (ML) models may enhance intervention effectiveness by enabling timely and dynamic modification of intervention components for nonresponders to treatment. However, a lack of understanding and trust in these ML models impacts adoption among weight management experts. Recent advances in the field of explainable artificial intelligence enable the interpretation of ML models, yet it is unknown whether they enhance model understanding, trust, and adoption among weight management experts.

OBJECTIVE

This study aimed to build and evaluate an ML model that can predict 6-month weight loss success (ie, ≥7% weight loss) from 5 engagement and diet-related features collected over the initial 2 weeks of an intervention, to assess whether providing ML-based explanations increases weight management experts' agreement with ML model predictions, and to inform factors that influence the understanding and trust of ML models to advance explainability in early prediction of weight loss among weight management experts.

METHODS

We trained an ML model using the random forest (RF) algorithm and data from a 6-month weight loss intervention (N=419). We leveraged findings from existing explainability metrics to develop Prime Implicant Maintenance of Outcome (PRIMO), an interactive tool to understand predictions made by the RF model. We asked 14 weight management experts to predict hypothetical participants' weight loss success before and after using PRIMO. We compared PRIMO with 2 other explainability methods, one based on feature ranking and the other based on conditional probability. We used generalized linear mixed-effects models to evaluate participants' agreement with ML predictions and conducted likelihood ratio tests to examine the relationship between explainability methods and outcomes for nested models. We conducted guided interviews and thematic analysis to study the impact of our tool on experts' understanding and trust in the model.

RESULTS

Our RF model had 81% accuracy in the early prediction of weight loss success. Weight management experts were significantly more likely to agree with the model when using PRIMO (χ2=7.9; P=.02) compared with the other 2 methods with odds ratios of 2.52 (95% CI 0.91-7.69) and 3.95 (95% CI 1.50-11.76). From our study, we inferred that our software not only influenced experts' understanding and trust but also impacted decision-making. Several themes were identified through interviews: preference for multiple explanation types, need to visualize uncertainty in explanations provided by PRIMO, and need for model performance metrics on similar participant test instances.

CONCLUSIONS

Our results show the potential for weight management experts to agree with the ML-based early prediction of success in weight loss treatment programs, enabling timely and dynamic modification of intervention components to enhance intervention effectiveness. Our findings provide methods for advancing the understandability and trust of ML models among weight management experts.

The Efficacy of Mobile Applications for Weight Loss

Purpose of Review

A variety of mobile-based applications aimed at weight loss have become popular in recent years. This review describes the features and effectiveness of mobile weight loss apps.

Recent Findings

Overall, mobile apps can help patients lose weight either as well as or better than traditional paper-and-pencil weight loss interventions and often better than minimal intervention control groups. Mobile apps promote multiple strategies, including self-monitoring of diet, exercise, and weight, as well as social support and educational content. Significant variation exists in app types, which makes it difficult to conclude which features drive program effectiveness. Intervention success varies based on patients’ level of engagement with the app. There is a deficit of apps and app-based studies of older, less tech-savvy adults, ethnic/racial minorities, and low-income individuals, as well as longer-term studies.

Summary

Mobile apps can successfully help patients lose weight and represent a cost-effective, accessible alternative to intensive in-person weight loss programs. More research is needed into their long-term potential, especially for hard-to-reach populations.

Cognitive Benefits of Physical Exercise, Physical-Cognitive Training, and Technology-Based Intervention in Obese Individuals with and without Postmenopausal Condition: A Narrative Review

Obesity and estrogen deprivation have been identified as significant risk factors for cognitive impairment. Thus, postmenopausal conditions when paired with obesity may amplify the risks of developing dementia. Physical exercise has been recommended as a primary treatment for preventing obesity-related comorbidities and alleviating menopausal symptoms. This narrative review aimed to summarize the effects of exercise on cognition in obese individuals with and without menopausal condition, along with potential physiological mechanisms linking these interventions to cognitive improvement. Research evidence has demonstrated that exercise benefits not only physical but also cognitive and brain health. Among various types of exercise, recent studies have suggested that combined physical-cognitive exercise may exert larger gains in cognitive benefits than physical or cognitive exercise alone. Despite the scarcity of studies investigating the effects of physical and combined physical-cognitive exercise in obese individuals, especially those with menopausal condition, existing evidence has shown promising findings. Applying these exercises through technology-based interventions may be a viable approach to increase accessibility and adherence to the intervention. More evidence from randomized clinical trials with large samples and rigorous methodology is required. Further, investigations of biochemical and physiological outcomes along with behavioral changes will provide insight into underlying mechanisms linking these interventions to cognitive improvement.

American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan-2022 Update

OBJECTIVE

The objective of this clinical practice guideline is to provide updated and new evidence-based recommendations for the comprehensive care of persons with diabetes mellitus to clinicians, diabetes-care teams, other health care professionals and stakeholders, and individuals with diabetes and their caregivers.

METHODS

The American Association of Clinical Endocrinology selected a task force of medical experts and staff who updated and assessed clinical questions and recommendations from the prior 2015 version of this guideline and conducted literature searches for relevant scientific papers published from January 1, 2015, through May 15, 2022. Selected studies from results of literature searches composed the evidence base to update 2015 recommendations as well as to develop new recommendations based on review of clinical evidence, current practice, expertise, and consensus, according to established American Association of Clinical Endocrinology protocol for guideline development.

RESULTS

This guideline includes 170 updated and new evidence-based clinical practice recommendations for the comprehensive care of persons with diabetes. Recommendations are divided into four sections: (1) screening, diagnosis, glycemic targets, and glycemic monitoring; (2) comorbidities and complications, including obesity and management with lifestyle, nutrition, and bariatric surgery, hypertension, dyslipidemia, retinopathy, neuropathy, diabetic kidney disease, and cardiovascular disease; (3) management of prediabetes, type 2 diabetes with antihyperglycemic pharmacotherapy and glycemic targets, type 1 diabetes with insulin therapy, hypoglycemia, hospitalized persons, and women with diabetes in pregnancy; (4) education and new topics regarding diabetes and infertility, nutritional supplements, secondary diabetes, social determinants of health, and virtual care, as well as updated recommendations on cancer risk, nonpharmacologic components of pediatric care plans, depression, education and team approach, occupational risk, role of sleep medicine, and vaccinations in persons with diabetes.

CONCLUSIONS

This updated clinical practice guideline provides evidence-based recommendations to assist with person-centered, team-based clinical decision-making to improve the care of persons with diabetes mellitus.

Association Between Mobile Health App Engagement and Weight Loss and Glycemic Control in Adults With Type 2 Diabetes and Prediabetes (D'LITE Study): Prospective Cohort Study

Background

Mobile health apps are increasingly used as early intervention to support behavior change for diabetes prevention and control, with the overarching goal of lowering the overall disease burden.

Objective

This prospective cohort study conducted in Singapore aimed to investigate app engagement features and their association with weight loss and improved glycemic control among adults with diabetes and prediabetes from the intervention arm of the Diabetes Lifestyle Intervention using Technology Empowerment randomized controlled trial.

Methods

Diabetes and prediabetes participants (N=171) with a median age of 52 years, BMI of 29.3 kg/m², and glycated hemoglobin (HbA_1c) level of 6.5% and who were being assigned the Nutritionist Buddy Diabetes app were included. Body weight and HbA_1c were measured at baseline, 3 months, and 6 months. A total of 476,300 data points on daily app engagement were tracked via the backend dashboard and developer’s report. The app engagement data were analyzed by quartiles and weekly means expressed in days per week. Linear mixed model analysis was used to determine the associations between the app engagements with percentage weight and HbA_1c change.

Results

The median overall app engagement rate was maintained above 90% at 6 months. Participants who were actively engaged in ≥5 app features were associated with the greatest overall weight reduction of 10.6% from baseline (mean difference −6, 95% CI −8.9 to −3.2; P<.001) at 6 months. Adhering to the carbohydrate limit of >5.9 days per week and choosing healthier food options for >4.3 days per week had the most impact, eliciting weight loss of 9.1% (mean difference −5.2, 95% CI −8.2 to −2.2; P=.001) and 8.8% (mean difference −4.2, 95% CI −7.1 to −1.3; P=.005), respectively. Among the participants with diabetes, those who had a complete meal log for >5.1 days per week or kept within their carbohydrate limit for >5.9 days per week each achieved greater HbA_1c reductions of 1.2% (SD 1.3%; SD 1.5%), as compared with 0.2% (SD 1%; SD 0.6%). in the reference groups who used the features <1.1 or ≤2.5 days per week, respectively.

Conclusions

Higher app engagement led to greater weight loss and HbA_1c reduction among adults with overweight or obesity with type 2 diabetes or prediabetes.

Trial Registration

Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12617001112358; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12617001112358

Effects of peer support and mobile application-based walking programme on physical activity and physical function in rural older adults: a cluster randomized controlled trial

PURPOSE

Increased physical activity maintains functional fitness and prevents aging-related declines in muscle mass for older adults. However, physical inactivity is prevalent in aging population, particularly in those living in rural areas. In this study we assessed the effectiveness of a 3-month peer support and mobile application-based walking programme on physical activity and physical function in rural older Chinese adults.

METHODS

This was a cluster randomized control trial recruiting adults aged  ≥ 60 years. Participants were randomized into intervention and control groups (4 clusters with 36 participants for each group). The intervention included face-to-face physical activity group sessions, peer-led walking, and mobile application-based feedback. Primary outcome was pedometer-measured daily walking steps, and secondary outcomes mainly included physical function and body composition. Both intention-to-treat and per-protocol analyses were performed.

RESULTS

Of the included 72 participants (mean age 66.9 years, male 36.1%), 64 completed the study. Intention-to-treat analysis showed that after 3-month walking programme, physical activity was increased by 408 steps/day and grip strength by 1.25 kg in the intervention group compared with the control group. However, no significant outcomes were observed on gait speed, chair-rising time, or body composition. Per-protocol analysis showed similar results. Linear regression analyses showed that changes in daily steps were associated with changes in gait speed (ß = 0.63, P < 0.001) and chair-rising time (ß = - 0.31, P = 0.01).

CONCLUSIONS

The 3-month peer support and mobile application-based walking programme could improve physical activity and physical function in rural older adults.

TRIAL REGISTRATION

ChiCTR2000034842, registered on 2020/07/21.

Reversing Type 2 Diabetes in a Primary Care-Anchored eHealth Lifestyle Coaching Programme in Denmark: A Randomised Controlled Trial

The goal of this trial was to investigate whether an eHealth lifestyle coaching programme led to significant weight loss and decreased Haemoglobin A1c (HbA1c) in patients with type 2 diabetes. In an RCT, 170 patients were enrolled from 2018 to 2019 for intervention or control. Inclusion criteria were diagnosed with type 2 diabetes, BMI 30−45 kg/m2, and aged 18−70 years. Exclusion criteria were lacks internet access, pregnant or planning a pregnancy, or has a serious disease. Primary and secondary outcomes were a reduction in body weight and HbA1c. At six months, 75 (75%) patients in the intervention group and 53 (76%) patients in the control group remained in the trial. The mean body weight loss was 4.2 kg (95% CI, −5.49; −2.98) in the intervention group and 1.5 kg (95% CI, −2.57; −0.48) in the control group (p = 0.005). In the intervention group, 24 out of 62 patients with elevated HbA1c at baseline (39%) had a normalized HbA1c < 6.5% at six months, compared to 8 out of 40 patients with elevated HbA1c at baseline (20%) in the control group (p = 0.047). The eHealth lifestyle coaching programme can lead to significant weight loss and decreased HbA1c among patients with type 2 diabetes, compared to standard care.

A New Taxonomy for Technology-Enabled Diabetes Self-Management Interventions: Results of an Umbrella Review

BACKGROUND

A 2017 umbrella review defined the technology-enabled self-management (TES) feedback loop associated with a significant reduction in A1C. The purpose of this 2021 review was to develop a taxonomy of intervention attributes in technology-enabled interventions; review recent, high-quality systematic reviews and meta-analyses to determine if the TES framework was described and if elements contribute to improved diabetes outcomes; and to identify gaps in the literature.

METHODS

We identified key technology attributes needed to describe the active ingredients of TES interventions. We searched multiple databases for English language reviews published between April 2017 and April 2020, focused on PwD (population) receiving diabetes care and education (intervention) using technology-enabled self-management (comparator) in a randomized controlled trial, that impact glycemic, behavioral/psychosocial, and other diabetes self-management outcomes. AMSTAR-2 guidelines were used to assess 50 studies for methodological quality including risk of bias.

RESULTS

The TES Taxonomy was developed to standardize the description of technology-enabled interventions; and ensure research uses the taxonomy for replication and evaluation. Of the 26 included reviews, most evaluated smartphones, mobile applications, texting, internet, and telehealth. Twenty-one meta-analyses with the TES feedback loop significantly lowered A1C.

CONCLUSIONS

Technology-enabled diabetes self-management interventions continue to be associated with improved clinical outcomes. The ongoing rapid adoption and engagement of technology makes it important to focus on uniform measures for behavioral/psychosocial outcomes to highlight healthy coping. Using the TES Taxonomy as a standard approach to describe technology-enabled interventions will support understanding of the impact technology has on diabetes outcomes.

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

Background

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

Objective

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

Methods

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

Results

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

Conclusions

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

Trial Registration

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

The Effectiveness of Combining Nonmobile Interventions With the Use of Smartphone Apps With Various Features for Weight Loss: Systematic Review and Meta-analysis

Background

The effectiveness of smartphone apps for weight loss is limited by the diversity of interventions that accompany such apps. This research extends the scope of previous systematic reviews by including 2 subgroup analyses based on nonmobile interventions that accompanied smartphone use and human-based versus passive behavioral interventions.

Objective

The primary objective of this study is to systematically review and perform a meta-analysis of studies that evaluated the effectiveness of smartphone apps on weight loss in the context of other interventions combined with app use. The secondary objective is to measure the impact of different mobile app features on weight loss and mobile app adherence.

Methods

We conducted a systematic review and meta-analysis of relevant studies after an extensive search of the PubMed, MEDLINE, and EBSCO databases from inception to January 31, 2022. Gray literature, such as abstracts and conference proceedings, was included. Working independently, 2 investigators extracted the data from the articles, resolving disagreements by consensus. All randomized controlled trials that used smartphone apps in at least 1 arm for weight loss were included. The weight loss outcome was the change in weight from baseline to the 3- and 6-month periods for each arm. Net change estimates were pooled across the studies using random-effects models to compare the intervention group with the control group. The risk of bias was assessed independently by 2 authors using the Cochrane Collaboration tool for assessing the risk of bias in randomized trials.

Results

Overall, 34 studies were included that evaluated the use of a smartphone app in at least 1 arm. Compared with controls, the use of a smartphone app–based intervention showed a significant weight loss of –1.99 kg (95% CI –2.19 to –1.79 kg; I²=81%) at 3 months and –2.80 kg (95% CI –3.03 to –2.56 kg; I²=91%) at 6 months. In the subgroup analysis, based on the various intervention components that were added to the mobile app, the combination of the mobile app, tracker, and behavioral interventions showed a statistically significant weight loss of –2.09 kg (95% CI –2.32 to –1.86 kg; I²=91%) and –3.77 kg (95% CI –4.05 to –3.49 kg; I²=90%) at 3 and 6 months, respectively. When a behavioral intervention was present, only the combination of the mobile app with intensive behavior coaching or feedback by a human coach showed a statistically significant weight loss of –2.03 kg (95% CI –2.80 to –1.26 kg; I²=83%) and –2.63 kg (95% CI –2.97 to –2.29 kg; I²=91%) at 3 and 6 months, respectively. Neither the type nor the number of mobile app features was associated with weight loss.

Conclusions

Smartphone apps have a role in weight loss management. Nevertheless, the human-based behavioral component remained key to higher weight loss results.

Effects of Short-term Mobile Application Use on Weight Reduction for Patients with Type 2 Diabetes

Background

The increasing prevalence of type 2 diabetes mellitus (T2DM) has led to a significant health burden. Technological advancements have highlighted the benefits of digital therapeutics for chronic diseases. In this study, we aimed to investigate the effects of a mobile application on weight reduction in patients with T2DM.

Methods

A total of 48 patients with T2DM was included in this single-center, randomized, controlled trial. In addition to conventional treatment, participants in the intervention group used a mobile application-based self-management system for diet, exercise, and medication adherence. The primary outcome of this study was weight change after 3 months of intervention, and secondary outcomes were metabolic parameters.

Results

After 12 weeks, no significant differences in body weight change were observed between the intervention and control groups (P=0.229). However, a significant difference was found in waist circumference (WC) between the two groups, wherein the control group showed an increase in WC (from 95.00±8.89 cm to 95.76±9.72 cm), while the intervention group showed a reduction (from 91.93±6.25 cm to 90.75±6.01 cm) with a significant time by group interaction (P=0.016). Additionally, participants with good compliance exhibited a more evident reduction in WC (P=0.037). However, no significant differences were found in other metabolic parameters between the two groups.

Conclusion

Lifestyle modification using short-term mobile applications effectively reduced WC, especially in patients with good adherence to the application. However, weight reduction was not achieved.

Identifying modifiable factors that could arrest progression to type 2 diabetes: A cluster analysis of Australian adults

Lifestyle-based disease prevention and self-management strategies play an important role in the mitigation of health, social, and economic burdens associated with type 2 diabetes mellitus (T2DM) and other chronic diseases. However, there are significant implementation and translational challenges associated with the design and delivery of effective interventions. In this study, data-driven techniques for the identification of optimal target audiences and intervention targets for T2DM prevention interventions were applied. Australian adults (N = 3159) with differing T2DM status (no diabetes diagnosis, pre-diabetes, or T2DM) completed self-report assessments of diet quality, physical activity, psychological distress, future orientation, health literacy, and socio-demographic characteristics. K-medoids cluster analysis was conducted to identify homogenous groups within the research sample and proportional odds ordinal logistic regressions conducted to identify signficant predictors of T2DM status within each cluster. Results identified a two-factor optimal solution that stratified participants based on sex (male/female). Within each cluster, psychosocial variables explained approximately 25% of the variance in T2DM status, with future orientation identified as a significant modifiable predictor of T2DM. For the male cluster, health literacy was also significant (p ≤0.01). Findings indicate that men and women should be targeted separately in T2DM prevention or management programs and that future interventional research targeting future orientation is warranted.

The nudge strategies for weight loss in adults with obesity and overweight: A systematic review and meta-analysis

Obesity and overweight conditions have become major health challenges worldwide. The exploration of effective weight loss strategies is essential. Nudges are currently advancing approaches that represent a new and better method for changing the behaviors of people. However, the effectiveness of nudge interventions on weight loss in overweight people who may be obese has not been synthesized in a systematic manner. In this study, a systematic literature search was performed. Only randomized controlled trials (RCTs) were considered. Weighted mean differences (WMDs) and 95% confidence intervals (CIs) were calculated as summary statistics. In total, 25 RCTs involving a population of 5,929 individuals were included. Significant effects of the nudge strategy on weight loss (WMD: -0.96 kg, 95% CI: -1.49 to -0.43), body mass index (WMD: -0.3 kg/m², 95% CI: -0.41 to -0.19) and waist circumference (WMD: -0.75 cm, 95% CI: -1.23 to -0.27) were observed. The subgroup analysis showed that the reduction in body weight associated with nudge interventions was significant in younger and more obese people. Moreover, the effect of nudge intervention on weight loss weakened over time. Overall, the nudge strategy can promote changes in weight loss, body mass index and waist circumference of adults, albeit at a mild magnitude and in particular types of individuals. Nudge strategies can be recommended to clinical practitioners and policy-makers to promote obesity management.

Patient Use of Cardiovascular Devices and Apps: Are We Getting Our Money's Worth?

The evolution of technology makes it likely that a large number of people will invest in and use health-related mobile applications and wearable devices. Yet the question remains: Do these technology-based interventions modify health behavior and improve health…and are we getting our money's worth? The vast majority of studies concerning health-related apps and wearable devices have small sample sizes and short time spans of 6 months or less, so it is not clear if these durations were determined by lack of consistent use over time. Furthermore, many of the most popular applications have not been subjected to randomized trials. Overall, the small demonstrated improvements in outcomes are often associated with professional involvement from clinicians, coaches, or diabetes educators provided in conjunction with use of mobile health (mHealth) platforms. This paper explores the use of mHealth technologies that address cardiovascular disease/prevention (eg, diabetes, diet, physical activity, and associated weight loss) and discusses the lack of adequate evidence to support even minimal patient investment in mobile applications or wearable devices at this time.

Identifying Persuasive Design Principles and Behavior Change Techniques Supporting End User Values and Needs in eHealth Interventions for Long-Term Weight Loss Maintenance: Qualitative Study

BACKGROUND

An increasing number of eHealth interventions aim to support healthy behaviors that facilitate weight loss. However, there is limited evidence of the effectiveness of the interventions and little focus on weight loss maintenance. Knowledge about end user values and needs is essential to create meaningful and effective eHealth interventions, and to identify persuasive system design (PSD) principles and behavior change techniques (BCTs) that may contribute to the behavior change required for successful long-term weight loss maintenance.

OBJECTIVE

This study aimed to provide insight into the design of eHealth interventions supporting behavior change for long-term weight maintenance. The study sought to identify the values and needs of people with obesity aiming to maintain weight after weight loss, and to identify PSD principles, BCTs, and design requirements that potentially enable an eHealth intervention to meet end user values and needs.

METHODS

This study presents the concept of integrating PSD principles and BCTs into the design process of eHealth interventions to meet user values and needs. In this study, individual interviews and focus groups were conducted with people with obesity (n=23) and other key stakeholders (n=27) to explore end user values and needs related to weight loss maintenance. Design thinking methods were applied during the focus group sessions to identify design elements and to explore how eHealth solutions can support the needs to achieve sustainable weight loss maintenance. The PSD model and behavior change taxonomy by Michie were used to identify PSD principles and BCT clusters to meet end user values and needs.

RESULTS

A total of 8 key end user values were identified, reflecting user needs for weight loss maintenance support: self-management, personalized care, autonomy, feel supported, positive self-image, motivation, happiness, and health. Goals and planning, feedback and monitoring, repetition and substitution, shaping knowledge, social support, identity, and self-belief were some of the BCT clusters identified to address these concepts, together with PSD principles such as personalization, tailoring, self-monitoring, praise, and suggestions.

CONCLUSIONS

The process of translating end user values and needs into design elements or features of eHealth technologies is an important part of the design process. To our knowledge, this is the first study to explore how PSD principles and BCTs can be integrated when designing eHealth self-management interventions for long-term weight loss maintenance. End users and other key stakeholders highlighted important factors to be considered in the design of eHealth interventions supporting sustained behavior change. The PSD principles and BCTs identified provide insights and suggestions about design elements and features to include for supporting weight loss maintenance. The findings indicate that a combination of BCTs and PSD principles may be needed in evidence-based eHealth interventions to stimulate motivation and adherence to support healthy behaviors and sustained weight loss maintenance.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04537988; https://clinicaltrials.gov/ct2/show/NCT04537988.

Can you see me? Participant experience of accessing a weight management programme via group videoconference to overcome barriers to engagement

Background

Engagement with conventional weight management group programmes is low.

Objective

To understand participant experience of accessing an adapted programme via videoconference.

Participants

Adults with obesity (BMI ≥ 35kg/m²), referred to an NHS Dietetics service in Wales, were offered a group videoconference weight management programme as an optional alternative to in‐person groups. Thirteen participants (mean age 48.5 ± 20.2 years, 8 female) recruited to two videoconference groups were interviewed.

Study design

A Registered Dietitian delivered a behavioural programme using Skype for Business in 10 sessions over 6 months. Participants joined the groups from any Internet‐connected device with a webcam. Participant perspectives were audiorecorded in one‐to‐one, semi‐structured interviews. Interviews were transcribed verbatim and thematically analysed using self‐determination theory as a theoretical framework.

Results

Ten themes were identified, three relating to service engagement and seven relating to behaviour change facilitation. Key themes in engagement included ‘reduced burden’, described as saving time and travel and ‘reduced threat’ as participants perceived joining a group from home as less daunting compared to attending in‐person. Despite reporting some initial technical difficulties with establishing video and audio connection, participants described beneficial peer support although not physically with other group members.

Conclusion

Accessing a group weight management programme via videoconference may be the preferred option for some participants, overcoming some of the barriers to access to standard in‐person programmes, particularly in rural areas. Participants are able to experience peer support via videoconference. During the COVID‐19 pandemic, weight management programmes could utilize videoconference groups to continue to provide support.