Cell phone intervention for you (CITY): A randomized, controlled trial of behavioral weight loss intervention for young adults using mobile technology

Impact of a digital employer-based weight loss program on individuals age 65 or older

Introduction

Older adults are not protected from obesity, which has been linked to frailty, cognitive impairment, and other aging-related factors. Intensive lifestyle interventions have been shown to be effective for weight loss in older adults; however, these have typically been highly intensive and less feasible for dissemination. This analysis describes weight loss in a large-scale, commercially available, digital intervention in a subset of older adults.

Methods

Older adults (N = 20,443, males = 6,238; females = 14,205) between 65 and 85 years of age with overweight (43.3%) or obesity (46.7%) participated in an online, self-directed weight loss program. Behavioral-based content was delivered through weekly video lessons within an online platform that included weight and physical activity tracking, an online community, a reference library, and access to coaching support. Self-reported measures taken at the time of entry into the program were used for this analysis (demographics, height, body weight, and health status). Weight was reported across weeks of engagement in the curriculum.

Results

The average weight loss was -3.15 kg (95% CI: [-3.20, -3.11]) at 15.5 weeks. Weight loss was significantly greater in male individuals (-3.79 kg [95% CI: -3.89, -3.71]) versus female individuals (-2.87 kg [95% CI: -2.94, -2.82]) (p < 0.001), with a similar engagement in curriculum weeks. Percent weight loss was statistically significant for all age categories (p < 0.05) and self-reported health conditions (p < 0.05).

Discussion

Short-term weight loss was observed in older adults exposed to a low-touch, self-guided, and digital behavioral-based weight loss program. Weight loss was also observed even in the presence of various chronic health conditions.

Acceptability of a Self-Guided Lifestyle Intervention Among Young Men: Mixed Methods Analysis of Pilot Findings

BACKGROUND

Young men are vastly underrepresented in lifestyle interventions, suggesting a need to develop appealing yet effective interventions for this population.

OBJECTIVE

This study aimed to determine the acceptability of a self-guided lifestyle intervention designed specifically for young men (age: 18-35 years old).

METHODS

Semistructured interviews and surveys were completed by 14 men following completion of a remotely delivered, 12-week lifestyle intervention. The intervention included 1 virtual group session, digital tools, access to self-paced web- and mobile-based content, and 12 weekly health risk text messages. We quantitatively and qualitatively examined young men's experiences with the intervention components of a remotely delivered, self-guided lifestyle intervention targeting weight loss. Data were integrated using convergent mixed methods analysis.

RESULTS

Men were a mean age of 29.9 (SD 4.9) years with a mean BMI of 31.0 (SD 4.5) kg/m2. The self-guided aspect was not acceptable, and a majority preferred more check-ins. Participants expressed a desire for a social aspect in future lifestyle interventions. All men found the focus on health risks appealing. A majority of men found the study-issued, Bluetooth-enabled scale acceptable.

CONCLUSIONS

Acceptability of the self-guided lifestyle intervention was perceived as suboptimal by young men. The findings highlight the need to add intervention components that sustain motivation and provide additional social support for young men.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04267263; https://www.clinicaltrials.gov/study/NCT04267263.

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.

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).

Effect of an mHealth weight loss intervention on Healthy Eating Index diet quality: the SMARTER randomised controlled trial

In the few weight loss studies assessing diet quality, improvements have been minimal and recommended calculation methods have not been used. This secondary analysis of a parallel group randomised trial (regsitered: https://clinicaltrials.gov/ct2/show/NCT03367936) assessed whether self-monitoring with feedback (SM + FB) v. self-monitoring alone (SM) improved diet quality. Adults with overweight/obesity (randomised: SM n 251, SM + FB n 251; analysed SM n 170, SM + FB n 186) self-monitored diet, physical activity and weight. Real-time, personalised feedback, delivered via a study-specific app up to three times daily, was based on reported energy, fat and added sugar intake. Healthy Eating Index 2015 (HEI-2015) scores were calculated from 24-hour recalls. Higher scores represent better diet quality. Data were collected August 2018 to March 2021 and analysed spring 2022. The sample was mostly female (78·9 %) and white (85·4 %). At baseline, HEI-2015 total scores and bootstrapped 95 % CI were similar by treatment group (SM + FB: 63·11 (60·41, 65·24); SM: 61·02 (58·72, 62·81)) with similar minimal improvement observed at 6 months (SM + FB: 65·42 (63·30, 67·20); SM: 63·19 (61·22, 64·97)) and 12 months (SM + FB: 63·94 (61·40, 66·29); SM: 63·56 (60·81, 65·42)). Among those who lost ≥ 5 % of baseline weight, HEI-2015 scores improved (baseline: 62·00 (58·94, 64·12); 6 months: 68·02 (65·41, 71·23); 12 months: 65·93 (63·40, 68·61)). There was no effect of the intervention on diet quality change. Clinically meaningful weight loss was related to diet quality improvement. Feedback may need to incorporate more targeted nutritional content.

Physical activity interventions have a moderate effect in increasing physical activity in university students-a meta-analysis

INTRODUCTION

The transition to college is associated with changes in physical activity. This meta-analysis aims to quantify the effect of interventions on increasing physical activity in healthy university students.

METHODS

We conducted a literature search (up to 2/3/2020) to identify randomized controlled trials with healthy undergraduate or graduate students enrolled in a college degree program. Moderator analyses were conducted to examine the effects of intervention modality delivery (delivered in-person or remotely) and the type of outcome measure (self-report or objective measures).

RESULTS

18 publications were included. Interventions had a medium effect on physical activity (Cohen's d = 0.52). Moderator analyses revealed no differences.

CONCLUSION

Suggestions of how to improve the quality of physical activity intervention studies in college students are given. The moderate effect size of physical activity interventions in college students highlights the importance of developing and testing new interventions to promote physical activity in emerging adults.

Supplemental data for this article can be accessed online at https://doi.org/10.1080/07448481.2021.1998070 .

Technology-Based Interventions to Reduce Sugar-Sweetened Beverages among Adolescents: A Scoping Review

This scoping review investigates the effectiveness of technology-based interventions in reducing sugar-sweetened beverage (SSB) consumption among adolescents. The rise in SSB consumption among young individuals has become a global public health concern due to its association with obesity, diabetes, and various other health problems. The purpose of this scoping review is to map out and examine the various technology-based interventions used in reducing sugar-sweetened beverages among children and adolescents. A systematic search of three databases using the PRISMA guideline was followed, and 474 articles were retrieved. Seven articles met the inclusion criteria and the critical appraisal using the critical appraisal skill program (CASP). The seven articles underwent both descriptive and thematic analysis. Four technology-based interventions were identified from the selected articles, which include smartphone apps, online or web-based tools, text messages, and social marketing strategies. Our findings suggest that these interventions hold promise in improving adolescents' eating patterns and health outcomes associated with SSB intake, highlighting their potential as useful strategies in resolving this urgent public health concern.

Weight Management Interventions Provided by a Dietitian for Adults with Overweight or Obesity: An Evidence Analysis Center Systematic Review and Meta-Analysis

BACKGROUND

Obesity is associated with a multitude of comorbidities and considerable health care costs.

OBJECTIVE

The objective of this review was to examine the efficacy of weight management interventions provided by a registered dietitian or international equivalent (referred to as "dietitian").

METHODS

This systematic review and meta-analysis of randomized controlled trials (RCTs) examined the effect of weight management interventions provided by a dietitian, compared with usual care or no intervention, on several cardiometabolic outcomes and quality of life in adults with overweight or obesity. MEDLINE, Embase, PsycINFO, Cochrane CENTRAL, Cochrane Database of Systematic Reviews, and CINAHL databases were searched for eligible RCTs published between January 2008 and January 2021 in the English language. Meta-analyses were conducted using a random-effects model, publication bias was assessed using funnel plots and Egger's statistics, and heterogeneity was assessed by interpreting I2 values. Efficacy of intervention components, such as telehealth or group contacts, were explored in sub-group analyses. Version 2 of the risk-of-bias tool for RCTs was used to assess risk of bias. The Grading of Recommendations Assessment, Development and Evaluation method was used to determine certainty of evidence.

RESULTS

This systematic review included 62 RCTs. Compared with control conditions, weight management interventions provided by a dietitian resulted in improved body mass index (mean difference [MD] -1.5; 95% CI -1.74 to -1.26; moderate evidence certainty); percent weight loss (MD -4.01%; 95% CI -5.26% to -2.75%; high evidence certainty); waist circumference (MD -3.45 cm; 95% CI -4.39 to -2.51 cm; high evidence certainty); blood pressure (MD -3.04 mm Hg; 95% CI -5.10 to -0.98 mm Hg and MD -1.99 mm Hg; 95% CI -3.02 to -0.96 mm Hg for systolic blood pressure and diastolic blood pressure, respectively; moderate and low evidence certainty); and quality of life using the 36-Item Short Form Survey (MD 5.84; 95% CI 2.27 to 9.41 and 2.39; 95% CI 1.55 to 3.23 for physical and mental quality of life, respectively; low and moderate evidence certainty).

CONCLUSIONS

For adults with overweight or obesity, weight management interventions provided by a dietitian are efficacious for improving several examined cardiometabolic outcomes and quality of life.

Life events and stress among young adults in weight gain prevention trial

OBJECTIVE

Young adults (YAs) are at high risk for weight gain and show high variability in treatment response. Life events and high perceived stress are common in YAs and could drive less favorable outcomes. The goal was to examine whether life events and stress were related to program engagement and weight outcomes in a weight gain prevention trial for YAs.

METHOD

Secondary analysis from the Study of Novel Approaches to Weight Gain Prevention (SNAP), a randomized clinical trial (N = 599, 18-35 years, BMI 21-30 kg/m²). Both intervention arms received 10 in-person sessions over 4 months, with long-term contact via web and SMS. Participants completed the CARDIA life events survey and Cohen Perceived Stress Scale-4 at 0 and 4 months; weight was objectively measured at 0, 4 months, and 1, 2, 3, and 4 years.

RESULTS

Participants who experienced more life events prior to study entry had lower session attendance (p < .01) and retention (p < .01), although no differences in weight outcomes were observed (p = .39). Baseline perceived stress followed a similar pattern. Participants who experienced more life events and higher perceived stress during the initial in-person program (0-4 months) appeared to experience less favorable weight outcomes long-term (p = .05 for life events, p = .04 for stress). Very few associations differed by treatment arm.

CONCLUSIONS

Experiencing more life events and stress was negatively associated with program engagement and may impair long-term weight outcomes for YAs. Future work should consider identifying YAs at highest risk and tailoring interventions to better meet their needs. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Digital Health Solutions for Weight Loss and Obesity: A Narrative Review

Personal exercise programmes have long been used and prescribed for weight loss and the improvement of quality of life in obese patients. While individualised programmes are usually the preferred option, they can be more costly and challenging to deliver in person. A move to digital programmes with a wider reach has commenced, and demand has increased due to the SARS-CoV-2 pandemic. In this review, we evaluate the current status of digital exercise programme delivery and its evolution over the past decade, with a focus on personalisation. We used specific keywords to search for articles that met our predetermined inclusion and exclusion criteria in order to provide valuable evidence and insights for future research. We identified 55 studies in total in four key areas of focus, from the more recent development of apps and personal digital assistants to web-based programmes and text or phone call interventions. In summary, we observed that apps may be useful for a low-intensity approach and can improve adherence to programmes through self-monitoring, but they are not always developed in an evidence-based manner. Engagement and adherence are important determinants of weight loss and subsequent weight maintenance. Generally, professional support is required to achieve weight loss goals.

Practical guideline on obesity care in patients with gastrointestinal and liver diseases - Joint ESPEN/UEG guideline

BACKGROUND

Patients with chronic gastrointestinal disease such as inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), celiac disease, gastroesophageal reflux disease (GERD), pancreatitis, and chronic liver disease (CLD) often suffer from obesity because of coincidence (IBD, IBS, celiac disease) or related pathophysiology (GERD, pancreatitis and CLD). It is unclear if such patients need a particular diagnostic and treatment that differs from the needs of lean gastrointestinal patients. The present guideline addresses this question according to current knowledge and evidence.

OBJECTIVE

The present practical guideline is intended for clinicians and practitioners in general medicine, gastroenterology, surgery and other obesity management, including dietitians and focuses on obesity care in patients with chronic gastrointestinal diseases.

METHODS

The present practical guideline is the shortened version of a previously published scientific guideline developed according to the standard operating procedure for ESPEN guidelines. The content has been re-structured and transformed into flow-charts that allow a quick navigation through the text.

RESULTS

In 100 recommendations (3× A, 33× B, 24 × 0, 40× GPP, all with a consensus grade of 90% or more) care of gastrointestinal patients with obesity - including sarcopenic obesity - is addressed in a multidisciplinary way. A particular emphasis is on CLD, especially metabolic associated liver disease, since such diseases are closely related to obesity, whereas liver cirrhosis is rather associated with sarcopenic obesity. A special chapter is dedicated to obesity care in patients undergoing bariatric surgery. The guideline focuses on adults, not on children, for whom data are scarce. Whether some of the recommendations apply to children must be left to the judgment of the experienced pediatrician.

CONCLUSION

The present practical guideline offers in a condensed way evidence-based advice how to care for patients with chronic gastrointestinal diseases and concomitant obesity, an increasingly frequent constellation in clinical practice.

Medical Nutrition Therapy Interventions Provided by Dietitians for Adult Overweight and Obesity Management: An Academy of Nutrition and Dietetics Evidence-Based Practice Guideline

Overweight and obesity affect most adults living in the United States and are causally linked to several adverse health outcomes. Registered dietitian nutritionists or international equivalents (dietitians) collaborate with each client and other health care professionals to meet client-centered goals, informed by the best available evidence, and translated through a lens of clinical expertise and client circumstances and preferences. Since the last iteration of the Academy of Nutrition and Dietetics guideline on adult weight management in 2014, considerable research has been conducted and circumstances confronting dietitians have evolved. Thus, updated guidance is needed. The objective of this evidence-based practice guideline is to provide recommendations for dietitians who deliver medical nutrition therapy behavioral interventions for adults (18 years and older) with overweight and obesity to improve cardiometabolic outcomes, quality of life, and weight outcomes, when appropriate for and desired by the client. Recommendations in this guideline highlight the importance of considering complex contributors to overweight and obesity and individualizing interventions to client-centered goals based on specific needs and preferences and shared decision making. The described recommendations have the potential to increase access to care and decrease costs through utilization of telehealth and group counseling as effective delivery methods, and to address other barriers to overweight and obesity management interventions. It is essential for dietitians to collaborate with clients and interprofessional health care teams to provide high-quality medical nutrition therapy interventions using the nutrition care process to promote attainment of client-centered outcomes for adults with overweight or obesity.

Is the uptake, engagement, and effectiveness of exclusively mobile interventions for the promotion of weight-related behaviors equal for all? A systematic review

Mobile health interventions are promising behavior change tools. However, there is a concern that they may benefit some populations less than others and thus widen inequalities in health. This systematic review investigated differences in uptake of, engagement with, and effectiveness of mobile interventions for weight-related behaviors (i.e., diet, physical activity, and sedentary behavior) based on a range of inequality indicators including age, gender, race/ethnicity, and socioeconomic status. The protocol was registered on PROSPERO (CRD42020192473). Six databases (CINAHL, EMBASE, ProQuest, PsycINFO, Pubmed, and Web of Science) were searched from inception to July 2021. Publications were eligible for inclusion if they reported the results of an exclusively mobile intervention and examined outcomes by at least one inequality indicator. Sixteen publications reporting on 13 studies were included with most reporting on multiple behaviors and inequality indicators. Uptake was investigated in one study with no differences reported by the inequality indicators studied. Studies investigating engagement (n = 7) reported differences by age (n = 1), gender (n = 3), ethnicity (n = 2), and education (n = 2), while those investigating effectiveness (n = 9) reported differences by age (n = 3), gender (n = 5), education (n = 2), occupation (n = 1), and geographical location (n = 1). Given the limited number of studies and their inconsistent findings, evidence of the presence of a digital divide in mobile interventions targeting weight-related behaviors is inconclusive. Therefore, we recommend that inequality indicators are specifically addressed, analyzed, and reported when evaluating mobile interventions.

The Effectiveness of a Web-Based Application for a Balanced Diet and Healthy Weight Among Indonesian Pregnant Women: Randomized Controlled Trial

BACKGROUND

Pregnant women have self-declared that they have difficulties in estimating nutrient intakes. The Nutrition Information System for Indonesian Pregnant Women (SISFORNUTRIMIL) application was created as a dietary assessment and calorie-counting tool to guide pregnant women to eat the right portion sizes for each meal.

OBJECTIVE

The study aimed to examine the effectiveness of the SISFORNUTRIMIL application in helping users achieve a balanced diet and healthy maternal weight gain in comparison to nonusers in Indonesia.

METHODS

 First-pregnancy women in the second trimester aged 19-30 years (N=112) participated in the randomized controlled trial. Recruited women who were eligible and consented to participate in the study were allocated into the intervention group, or application user (n=56), and the control group, or application nonuser (n=56). The intervention recommended that pregnant women consume at least 5 food groups and calculate a recommended average portion size for 12 weeks. Both groups were self-monitored and recorded their intake in food records for 3 days every week. The dietary diversity consumed, macro- and micronutrient intake, and maternal weight gain were assessed pre- and postintervention. Data were collected three times during the intervention. Diversity food consumption was measured by the Minimum Dietary Diversity for Women of reproductive age. Furthermore, the Indonesian recommended dietary allowances were used to refer to and validate appropriate energy and nutrient amounts. Independent sample t test was used to compare differences between the intervention and control groups.

RESULTS

The mean dietary diversity score for the application user group (7.79, SD 1.20) was significantly greater than for the application nonuser group (7.02, SD 1.39; adjusted mean difference 0.77, 95% CI 0.28-1.25; d=0.28; P=.005). Macro- and micronutrient intake was significantly more in accordance with the dietary recommendations for the user group compared to the control group, including an energy daily intake of 156.88 kcal (95% CI 114.52-199.23; d=-1.39; P=.002), 102.43 g of carbohydrates (95% CI -125.2 to -79.60; d=-1.68; P=.02), 14.33 g of protein (95% CI 11.40-17.25; d=1.86; P<.001), and 10.96 g of fat (95% CI -13.71 to -8.20; d=-1.49; P<.001). Furthermore, there was a significantly higher intake of daily vitamins and minerals in the intervention group than in the control group. Other results showed that maternal weight gain in the intervention group was in accordance with the parameters of healthy weight gain.

CONCLUSIONS

 Recording food intake using the application was significantly effective in improving the dietary diversity consumed, improving adequate energy and nutrient intake, and producing healthy maternal weight during pregnancy.

TRIAL REGISTRATION

ISRCTN Registry ISRCTN42690828; https://www.isrctn.com/ISRCTN42690828.

Healthy Eating Index Diet Quality in Randomized Weight Loss Trials: A Systematic Review

BACKGROUND

Weight loss interventions focus on dietary and physical activity changes to induce weight loss. Both through weight loss and independent of it, diet quality is important for reducing chronic disease risk. However, whether and how diet quality changes over the course of a behavioral intervention is unclear.

OBJECTIVE

To systematically review the evidence from randomized controlled trials on the effect of behavioral interventions on diet quality as defined by the Healthy Eating Index (HEI) among adults with overweight and obesity.

METHODS

PubMed, Ebscohost CINAHL, Embase, OVID APA PsycInfo, Scopus, and Web of Science were searched through May 2021. Inclusion criteria comprised randomized controlled trial design, a primary or secondary aim of weight loss, a sample of US adults with overweight or obesity, measurement using the HEI-2005, 2010, or 2015, and assessment of the time by treatment effect. Interventions must have included behavioral components and lasted at least 3 months. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool. The systematic review protocol was published on Open Science Framework.

RESULTS

Of 3,707 citations retrieved, 18 studies met inclusion criteria. A wide array of behavioral interventions were assessed, including in-person and mobile health interventions as well as those prescribing intake of specific foods. Risk of bias in the included studies primarily arose from the measurement of the outcome variable. Sample sizes ranged from 34 to 413 participants. Nine studies used multiple dietary recalls, with few using the recommended method of Healthy Eating Index calculation. Changes in diet quality ranged from no improvement to a 20-point improvement. More often, improvement was in the 4- to 7-point range.

CONCLUSIONS

The evidence for the efficacy of behavioral weight loss interventions for improving diet quality among adults with overweight and obesity is limited. Modest improvements in HEI scores were observed in the reviewed studies.

power swgee: GEE-based power calculations in stepped wedge cluster randomized trials

Stepped wedge cluster randomized trials are increasingly being used to evaluate interventions in medical, public health, educational, and social science contexts. With the longitudinal and crossover nature of a SW-CRT, complex analysis techniques are often needed which makes appropriately powering SW-CRTs challenging. In this paper, we introduce a newly-developed SW-CRT power calculator, embedded within the power command in Stata. The power calculator assumes a marginal model (i.e., generalized estimating equations [GEE]) for the primary analysis of SW-CRTs, for which other currently available SW-CRT power calculators may not be suitable. The program accommodates complete cross-sectional and closed-cohort designs, and includes multilevel correlation structures appropriate for such designs. We discuss the methods and formulae underlying our SW-CRT calculator, and provide illustrative examples of the use of power swgee. We provide suggestions about the choice of parameters in power swgee, and conclude by discussing areas of future research which may improve the program.

The effect of weight loss interventions for obesity on fertility and pregnancy outcomes: A systematic review and meta-analysis

BACKGROUND

Weight loss could improve fertility, perhaps by reducing insulin resistance.

OBJECTIVES

To assess the effect of weight loss interventions on fertility in women with obesity not recruited because of known infertility.

SEARCH STRATEGY

Three databases during 1966-2020, trial registry.

SELECTION CRITERIA

Randomized controlled trials (RCTs) with a follow-up of 1 year or more, with a mean cohort BMI of 30 kg/m² or above.

DATA COLLECTION AND ANALYSIS

A systematic review and meta-analysis was conducted. The primary outcome was pregnancy. The secondary outcome was weight change.

MAIN RESULTS

A total of 27 RCTs (5938 women) were included. Weight loss interventions showed no statistically significant increase in pregnancies compared to control interventions (24 trials, 97 women with pregnancy; risk ratio [RR] 1.43, 95% confidence interval [CI] 0.91-2.23); weight change (mean difference [MD] -2.36 kg, 21 trials, 95% CI -3.17 to -1.55). Compared with low-fat diets, very-low-carbohydrate diets showed no statistically significant effect on women with pregnancy (three trials, 14 women with pregnancy; RR 1.37, 95% CI 0.49-3.84) or weight change (MD -0.32 kg, 95% CI -3.84 to 3.21).

CONCLUSIONS

Diet-based weight loss interventions for women with obesity not recruited because of infertility were effective at producing long-term weight loss. The effects on fertility were not statistically significant, but few trials provided data. Weight loss trials should routinely collect fertility outcomes.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42017078819.

A Self-Guided Lifestyle Intervention for Young Men: Findings from the ACTIVATE Randomized Pilot Trial

Background

Young men are at high risk for developing obesity-related health complications, yet are markedly underrepresented in lifestyle interventions. This pilot study examined the feasibility and preliminary efficacy of a lifestyle intervention (self-guided + health risk messaging) targeting young men.

Methods

35 young men (Age = 29.3 ± 4.27; BMI = 30.8 ± 4.26; 34% racial/ethnic minority) were randomly assigned to the intervention or delayed treatment control. The intervention (ACTIVATE) included 1 virtual group session, digital tools (wireless scale, self-monitoring app), access to self-paced content via a secure website, and 12 weekly texts to reinforce health risk messaging. Fasted objective weight was assessed remotely at baseline and 12-weeks. Perceived risk was assessed via survey at baseline, 2-week, and 12-week. T-tests were used to compare weight outcomes between arms. Linear regressions examined the association between percent weight change and perceived risk change.

Results

Recruitment was successful as evidenced by 109% of target enrollment achieved in a 2-month period. Retention was 86% at 12 weeks, with no differences by arm (p = 0.17). Participants in the intervention arm experienced modest weight loss at 12 weeks, whereas slight gains were observed in the control arm (-1.6% ± 2.5 vs. +0.31% ± 2.8, p = 0.04). Change in perceived risk was not associated with change in percent weight (p > 0.05).

Conclusions

A self-guided lifestyle intervention showed initial promise for weight management among young men, but these findings are limited by small sample size. More research is needed to bolster weight loss outcomes while retaining the scalable self-guided approach.

Clinical Trial Registration

NCT04267263 (https://www.clinicaltrials.gov/ct2/show/NCT04267263).

Effect of a Lifestyle Intervention on Cardiometabolic Health Among Emerging Adults: A Randomized Clinical Trial

IMPORTANCE

The prevalence of obesity has increased substantially among emerging adults, yet no previous large-scale behavioral weight loss trials have been conducted among this age group.

OBJECTIVE

To test the effect of 2 theory-based motivational enhancements on weight loss within a primarily digital lifestyle intervention designed for emerging adults.

DESIGN, SETTING, AND PARTICIPANTS

In this randomized clinical trial conducted at an academic medical research center, 382 participants aged 18 to 25 years with a body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) of 25 to 45 were enrolled between February 2, 2016, and February 6, 2019. Data collection was completed February 8, 2020. Analysis was performed on an intention-to-treat basis.

INTERVENTIONS

Participants were randomized to 1 of 3 groups: developmentally adapted behavioral weight loss (aBWL), aBWL plus behavioral economics (aBWL + BE), or aBWL plus self-determination theory (aBWL + SDT). All groups received a 6-month intervention with 1 group session, 1 individual session, and a digital platform (digital tools for self-monitoring, weekly lessons, tailored feedback, text messages, and optional social media). The aBWL + BE group received modest financial incentives for self-monitoring and weight loss; the aBWL + SDT group received optional experiential classes. Coaching and message framing varied by group.

MAIN OUTCOMES AND MEASURES

The primary outcome was mean (SE) weight change (in kilograms) at 6 months. Secondary outcomes included proportion of participants achieving weight loss of 5% or more, percentage weight change, waist circumference, body composition, and blood pressure.

RESULTS

Among the 382 participants (mean [SD] age, 21.9 [2.2] years), 316 (82.7%) were female, mean (SD) BMI was 33.5 (4.9), 222 (58.1%) were of underrepresented race and/or ethnicity, and 320 (83.8%) were retained at the primary end point. There was a significant time effect for mean (SE) weight loss (-3.22 [0.55] kg in the aBWL group; -3.47 [0.55] kg in the aBWL + BE group; and -3.40 [0.53] kg in the aBWL + SDT group; all P < .001), but no between-group differences were observed (aBWL vs aBWL + BE: difference, -0.25 kg [95% CI, -1.79 to 1.29 kg]; P = .75; aBWL vs aBWL + SDT: difference, -0.18 kg [95% CI, -1.67 to 1.31 kg]; P = .81; and aBWL + SDT vs aBWL + BE: difference, 0.07 kg [95% CI, -1.45 to 1.59 kg]; P = .93). The proportion of participants achieving a weight loss of 5% or more was 40.0% in the aBWL group (50 of 125), 39.8% in the aBWL + BE group (51 of 128), and 44.2% in the aBWL + SDT group (57 of 129), which was not statistically different across groups (aBWL vs aBWL + BE, P = .89; aBWL vs aBWL + SDT, P = .45; aBWL + SDT vs aBWL + BE, P = .54). Parallel findings were observed for all secondary outcomes-clinically and statistically significant improvements with no differences between groups.

CONCLUSIONS AND RELEVANCE

In this randomized clinical trial, all interventions produced clinically significant benefit, but neither of the motivational enhancements promoted greater reductions in adiposity compared with the developmentally adapted standard group. Continued efforts are needed to optimize lifestyle interventions for this high-risk population and determine which intervention works best for specific individuals based on sociodemographic and/or psychosocial characteristics.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02736981.

European guideline on obesity care in patients with gastrointestinal and liver diseases - Joint European Society for Clinical Nutrition and Metabolism / United European Gastroenterology guideline

BACKGROUND

Patients with chronic gastrointestinal (GI) disease such as inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), celiac disease, gastroesophageal reflux disease (GERD), pancreatitis, and chronic liver disease (CLD) often suffer from obesity because of coincidence (IBD, IBS, celiac disease) or related pathophysiology (GERD, pancreatitis and CLD). It is unclear if such patients need a particular diagnostic and treatment that differs from the needs of lean GI patients. The present guideline addresses this question according to current knowledge and evidence.

OBJECTIVE

The objective of the guideline is to give advice to all professionals working in the field of gastroenterology care including physicians, surgeons, dietitians and others how to handle patients with GI disease and obesity.

METHODS

The present guideline was developed according to the standard operating procedure for European Society for Clinical Nutrition and Metabolism guidelines, following the Scottish Intercollegiate Guidelines Network grading system (A, B, 0, and good practice point [GPP]). The procedure included an online voting (Delphi) and a final consensus conference.

RESULTS

In 100 recommendations (3x A, 33x B, 24x 0, 40x GPP, all with a consensus grade of 90% or more) care of GI patients with obesity - including sarcopenic obesity - is addressed in a multidisciplinary way. A particular emphasis is on CLD, especially fatty liver disease, since such diseases are closely related to obesity, whereas liver cirrhosis is rather associated with sarcopenic obesity. A special chapter is dedicated to obesity care in patients undergoing bariatric surgery. The guideline focuses on adults, not on children, for whom data are scarce. Whether some of the recommendations apply to children must be left to the judgment of the experienced pediatrician.

CONCLUSION

The present guideline offers for the first time evidence-based advice how to care for patients with chronic GI diseases and concomitant obesity, an increasingly frequent constellation in clinical practice.

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.

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

Objective

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

Methods

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

Results

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

Conclusions

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

European guideline on obesity care in patients with gastrointestinal and liver diseases - Joint ESPEN/UEG guideline

BACKGROUND

Patients with chronic gastrointestinal (GI) disease such as inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), celiac disease, gastroesophageal reflux disease (GERD), pancreatitis, and chronic liver disease (CLD) often suffer from obesity because of coincidence (IBD, IBS, celiac disease) or related pathophysiology (GERD, pancreatitis and CLD). It is unclear if such patients need a particular diagnostic and treatment that differs from the needs of lean GI patients. The present guideline addresses this question according to current knowledge and evidence.

OBJECTIVE

The objective of the guideline is to give advice to all professionals working in the field of gastroenterology care including physicians, surgeons, dietitians and others how to handle patients with GI disease and obesity.

METHODS

The present guideline was developed according to the standard operating procedure for ESPEN guidelines, following the Scottish Intercollegiate Guidelines Network (SIGN) grading system (A, B, 0, and good practice point (GPP)). The procedure included an online voting (Delphi) and a final consensus conference.

RESULTS

In 100 recommendations (3x A, 33x B, 24x 0, 40x GPP, all with a consensus grade of 90% or more) care of GI patients with obesity - including sarcopenic obesity - is addressed in a multidisciplinary way. A particular emphasis is on CLD, especially fatty liver disease, since such diseases are closely related to obesity, whereas liver cirrhosis is rather associated with sarcopenic obesity. A special chapter is dedicated to obesity care in patients undergoing bariatric surgery. The guideline focuses on adults, not on children, for whom data are scarce. Whether some of the recommendations apply to children must be left to the judgment of the experienced pediatrician.

CONCLUSION

The present guideline offers for the first time evidence-based advice how to care for patients with chronic GI diseases and concomitant obesity, an increasingly frequent constellation in clinical practice.

A systematic review of inequalities in the uptake of, adherence to, and effectiveness of behavioral weight management interventions in adults

The extent to which behavioral weight management interventions affect health inequalities is uncertain, as is whether trials of these interventions directly consider inequalities. We conducted a systematic review, synthesizing evidence on how different aspects of inequality impact uptake, adherence, and effectiveness in trials of behavioral weight management interventions. We included (cluster-) randomized controlled trials of primary care-applicable behavioral weight management interventions in adults with overweight or obesity published prior to March 2020. Data about trial uptake, intervention adherence, attrition, and weight change by PROGRESS-Plus criteria (place of residence, race/ethnicity, occupation, gender, religion, education, socioeconomic status, social capital, plus other discriminating factors) were extracted. Data were synthesized narratively and summarized in harvest plots. We identified 91 behavioral weight loss interventions and 12 behavioral weight loss maintenance interventions. Fifty-six of the 103 trials considered inequalities in relation to at least one of intervention or trial uptake (n = 15), intervention adherence (n = 15), trial attrition (n = 32), or weight outcome (n = 34). Most trials found no inequalities gradient. If a gradient was observed for trial uptake, intervention adherence, and trial attrition, those considered "more advantaged" did best. Alternative methods of data synthesis that enable data to be pooled and increase statistical power may enhance understanding of inequalities in behavioral weight management interventions.

Factors Influencing Adherence to mHealth Apps for Prevention or Management of Noncommunicable Diseases: Systematic Review

BACKGROUND

Mobile health (mHealth) apps show vast potential in supporting patients and health care systems with the increasing prevalence and economic costs of noncommunicable diseases (NCDs) worldwide. However, despite the availability of evidence-based mHealth apps, a substantial proportion of users do not adhere to them as intended and may consequently not receive treatment. Therefore, understanding the factors that act as barriers to or facilitators of adherence is a fundamental concern in preventing intervention dropouts and increasing the effectiveness of digital health interventions.

OBJECTIVE

This review aimed to help stakeholders develop more effective digital health interventions by identifying factors influencing the continued use of mHealth apps targeting NCDs. We further derived quantified adherence scores for various health domains to validate the qualitative findings and explore adherence benchmarks.

METHODS

A comprehensive systematic literature search (January 2007 to December 2020) was conducted on MEDLINE, Embase, Web of Science, Scopus, and ACM Digital Library. Data on intended use, actual use, and factors influencing adherence were extracted. Intervention-related and patient-related factors with a positive or negative influence on adherence are presented separately for the health domains of NCD self-management, mental health, substance use, nutrition, physical activity, weight loss, multicomponent lifestyle interventions, mindfulness, and other NCDs. Quantified adherence measures, calculated as the ratio between the estimated intended use and actual use, were derived for each study and compared with the qualitative findings.

RESULTS

The literature search yielded 2862 potentially relevant articles, of which 99 (3.46%) were included as part of the inclusion criteria. A total of 4 intervention-related factors indicated positive effects on adherence across all health domains: personalization or tailoring of the content of mHealth apps to the individual needs of the user, reminders in the form of individualized push notifications, user-friendly and technically stable app design, and personal support complementary to the digital intervention. Social and gamification features were also identified as drivers of app adherence across several health domains. A wide variety of patient-related factors such as user characteristics or recruitment channels further affects adherence. The derived adherence scores of the included mHealth apps averaged 56.0% (SD 24.4%).

CONCLUSIONS

This study contributes to the scarce scientific evidence on factors that positively or negatively influence adherence to mHealth apps and is the first to quantitatively compare adherence relative to the intended use of various health domains. As underlying studies mostly have a pilot character with short study durations, research on factors influencing adherence to mHealth apps is still limited. To facilitate future research on mHealth app adherence, researchers should clearly outline and justify the app's intended use; report objective data on actual use relative to the intended use; and, ideally, provide long-term use and retention data.

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.

The effectiveness of automated digital health solutions at successfully managing obesity and obesity-associated disorders: A PICO-structured investigation

Most adults in the UK and USA are classified as overweight or obese. Recent studies suggest that the prevalence of obesity has further increased during the SARS-CoV-2 pandemic and associated lockdowns. Digital technologies may be effective at managing obesity and related comorbidities, a potential further justified by social isolation and distancing circumstances.

This review of published literature employed a Patient-Intervention-Comparison-Outcome structured approach on the use of digital solutions to determine the effectiveness of their use in the management and treatment of obesity, hypertension, and type 2 diabetes and included commercially available, automated devices and applications that did not require intervention from a clinician. Our search covered studies published between January 2004 and February 2019, and 18 papers were included in the final analysis. The digital solutions reviewed were smartphone applications, wearable activity trackers, and ‘digital medicine offerings’ (DMO), including ingestible sensors and wearable patches.

This study found that not all interventions were effective at encouraging the lifestyle changes required for the management of obesity. Smartphone applications requiring interaction from the patient appeared to be more effective at encouraging engagement with treatment interventions than more passive wearable activity trackers. Automated feedback from smartphone applications was effective at managing type 2 diabetes, while DMO were effective at reducing blood pressure.

With the advancement of new technologies alongside a rapid increase in the prevalence of obesity and associated disorders, further studies comparing the various technologies available in larger sample populations for longer periods would help determine the most cost-effective preventive and therapeutic strategies.

Effect of tailored, daily feedback with lifestyle self-monitoring on weight loss: The SMARTER randomized clinical trial

OBJECTIVE

This study aimed to test the efficacy of self-monitoring and feedback (SM+FB) versus SM without FB (SM) in a behavioral weight-loss intervention at 6 months.

METHODS

This was a randomized clinical trial. Eligibility criteria included the following: ≥18 years of age, BMI ≥ 27 and ≤43, smartphone user, and ability to engage in moderate physical activity. All participants received a 90-minute 1:1 counseling session, a Fitbit Charge 2, and a digital scale for SM. SM+FB participants were provided access to a customized smartphone application that provided three daily FB messages. The primary outcome was percentage of weight change from 0 to 6 months.

RESULTS

The sample (N = 502) was 45 (SD 14.4) years old, BMI was 33.7 (SD 4.00) kg/m2 , 79.5% of participants were female (n = 399), and 84.3% were White (n = 423). At 6 months, there was 85.86% retention and a significant percentage of weight change in both groups (SM+FB: -3.16%, 95% CI: -3.85% to -2.47%, p < 0.0001; SM: -3.20%, 95% CI: -3.86% to -2.54%, p < 0.0001) but no significant between-group mean difference (-0.04%, 95% CI: -0.99% to 0.91%, p = 0.940). A ≥5% weight loss was achieved by 31.9% of the SM+FB group and 28.3% of the SM group.

CONCLUSIONS

There was no significant between-group difference in weight loss at 6 months.

Nutrition Concepts for the Treatment of Obesity in Adults

Obesity caused by a positive energy balance is a serious health burden. Studies have shown that obesity is the major risk factor for many diseases like type 2 diabetes mellitus, coronary heart diseases, or various types of cancer. Therefore, the prevention and treatment of increased body weight are key. Different evidence-based treatment approaches considering weight history, body mass index (BMI) category, and co-morbidities are available: lifestyle intervention, formula diet, drugs, and bariatric surgery. For all treatment approaches, behaviour change techniques, reduction in energy intake, and increasing energy expenditure are required. Self-monitoring of diet and physical activity provides an effective behaviour change technique for weight management. Digital tools increase engagement rates for self-monitoring and have the potential to improve weight management. The objective of this narrative review is to summarize current available treatment approaches for obesity, to provide a selective overview of nutrition trends, and to give a scientific viewpoint for various nutrition concepts for weight loss.

Efficacy of Mobile Health for Self-management of Cardiometabolic Risk Factors: A Theory-Guided Systematic Review

BACKGROUND

Although mobile health (mHealth) technologies are burgeoning in the research arena, there is a lack of mHealth interventions focused on improving self-management of individuals with cardiometabolic risk factors (CMRFs).

OBJECTIVE

The purpose of this article was to critically and systematically review the efficacy of mHealth interventions for self-management of CMRF while evaluating quality, limitations, and issues with disparities using the technology acceptance model as a guiding framework.

METHODS

PubMed, CINAHL, EMBASE, and Lilacs were searched to identify research articles published between January 2008 and November 2018. Articles were included if they were published in English, included adults, were conducted in the United States, and used mHealth to promote self-care or self-management of CMRFs. A total of 28 articles were included in this review.

RESULTS

Studies incorporating mHealth have been linked to positive outcomes in self-management of diabetes, physical activity, diet, and weight loss. Most mHealth interventions included modalities such as text messaging, mobile applications, and wearable technologies. There was a lack of studies that are (1) in resource-poor settings, (2) theoretically driven, (3) community-engaged research, (4) measuring digital/health literacy, (5) measuring and evaluating engagement, (6) measuring outcomes related to disease self-management, and (7) focused on vulnerable populations, especially immigrants.

CONCLUSION

There is still a lack of mHealth interventions created specifically for immigrant populations, especially within the Latino community-the largest growing minority group in the United States. In an effort to meet this challenge, more culturally tailored mHealth interventions are needed.

What Works Best to Engage Participants in Mobile App Interventions and e-Health: A Scoping Review

Background:

Despite the growing popularity of mobile app interventions, specific engagement components of mobile apps have not been well studied.

Methods:

The objectives of this scoping review are to determine which components of mobile health intervention apps encouraged or hindered engagement, and examine how studies measured engagement.

Results:

A PubMed search on March 5, 2020 yielded 239 articles that featured the terms engagement, mobile app/mobile health, and adult. After applying exclusion criteria, only 54 studies were included in the final analysis.

Discussion:

Common app components associated with increased engagement included: personalized content/feedback, data visualization, reminders/push notifications, educational information/material, logging/self-monitoring functions, and goal-setting features. On the other hand, social media integration, social forums, poor app navigation, and technical difficulties appeared to contribute to lower engagement rates or decreased usage. Notably, the review revealed a great variability in how engagement with mobile health apps is measured due to lack of established processes.

Conclusion:

There is a critical need for controlled studies to provide guidelines and standards to help facilitate engagement and its measurement in research and clinical trial work using mobile health intervention apps.

Weight Stigma and Weight-Related Health: Associations of Self-Report Measures Among Adults in Weight Management

BACKGROUND

Weight stigma impairs health. Few studies have disentangled the associations of experienced versus internalized stigma with weight-related outcomes.

PURPOSE

To examine weight and health variables associated with weight stigma experiences and internalization in the largest-to-date sample of adults in weight management.

METHODS

WW (formerly Weight Watchers) members (N = 18,769, 94.6% female, 91.1% white) completed an online survey from 2017 to 2018. Participants reported whether they had experienced weight stigma and, if so, the onset, past-year frequency and distress, and interpersonal sources of stigma. Participants completed the Modified Weight Bias Internalization Scale (WBIS-M) and self-reported: past-year weight and lifetime weight cycles; current self-monitoring behaviors; eating self-efficacy; physical activity; perceived stress; eating to cope; body image; and mental and physical health-related quality-of-life (HRQOL). Participants reported their demographic characteristics, including height and weight to compute body mass index.

RESULTS

In logistic and linear regression analyses (controlling for participant characteristics), WBIS-M scores were negatively associated with weight loss, self-monitoring, eating self-efficacy, body image, and mental HRQOL and positively associated with weight gain, weight cycling, perceived stress, and eating to cope (p < .001). Experiencing weight stigma was associated with greater weight loss and less weight gain, although associations with other variables had small effect sizes (absolute β values < 0.10). WBIS-M scores remained significantly associated with all variables when including stigma onset, frequency/distress, and sources.

CONCLUSIONS

Internalized, but not experienced, weight stigma was consistently associated with adverse weight and health factors. Developing and testing interventions targeting internalized stigma in the context of weight management should be a research priority.

Use of continuous glucose monitoring in obesity research: A scoping review

BACKGROUND

This scoping review provides a timely synthesis of the use of continuous glucose monitoring in obesity research with considerations to adherence to continuous glucose monitor devices and metrics most frequently reported.

METHODS

This scoping review was conducted adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. Eligible studies (n = 31) evaluated continuous glucose monitor use in research on participants, of all ages, with overweight or obesity.

RESULTS

Reviewed studies varied in duration from one to 84 days (mean: 8.74 d, SD 15.2, range 1-84 d) with 889 participants total (range: 11-118 participants). Across all studies, the mean percent continuous glucose monitor wear time (actual/intended wear time in days) was 92% (numerator - mean: 266.1 d, SD: 452, range: 9-1596 d/denominator - mean: 271.6 d, SD: 451.5, range: 9-1596 d). Continuous glucose monitoring was utilized to provide biofeedback (n = 2, 6%), monitor dietary adherence (n = 2, 6%), and assess glycemic variability (n = 29, 93%). The most common variability metrics reported were standard deviation (n = 19, 62%), area under the curve (n = 12, 39%), and glycemic range (n = 12, 39%).

CONCLUSIONS

Available evidence suggests that continuous glucose monitoring is a well-tolerated and versatile tool for obesity research in pediatric and adult patients. Future investigation is needed to substantiate the feasibility and utility of continuous glucose monitors in obesity research and maximize comparability across studies.

A systematic review of the use of dietary self-monitoring in behavioural weight loss interventions: delivery, intensity and effectiveness

OBJECTIVE

To identify dietary self-monitoring implementation strategies in behavioural weight loss interventions.

DESIGN

We conducted a systematic review of eight databases and examined fifty-nine weight loss intervention studies targeting adults with overweight/obesity that used dietary self-monitoring.

SETTING

NA.

PARTICIPANTS

NA.

RESULTS

We identified self-monitoring implementation characteristics, effectiveness of interventions in supporting weight loss and examined weight loss outcomes among higher and lower intensity dietary self-monitoring protocols. Included studies utilised diverse self-monitoring formats (paper, website, mobile app, phone) and intensity levels (recording all intake or only certain aspects of diet). We found the majority of studies using high- and low-intensity self-monitoring strategies demonstrated statistically significant weight loss in intervention groups compared with control groups.

CONCLUSIONS

Based on our findings, lower and higher intensity dietary self-monitoring may support weight loss, but variability in adherence measures and limited analysis of weight loss relative to self-monitoring usage limits our understanding of how these methods compare with each other.

Effect of tailoring on weight loss among young adults receiving digital interventions: an 18 month randomized controlled trial

Weight loss outcomes among young adults in technology-based programs have been equivocal. The purpose of this study was to deliver digital weight loss treatments to young adults and examine the 6, 12, and 18 month effects on weight loss. Young adults with overweight/obesity (N = 459; 23.3 ± 4.4 years) were recruited from two university sites and randomly assigned to receive through Facebook and text messaging either personalized (TAILORED; n = 150) or generic (TARGETED; n = 152) weight loss information, messages, and feedback or general healthy body content (e.g., body image, sleep; CONTROL; n = 157). The study was powered to detect a 2.1-kg difference at all time points with the primary outcome being 18 months. There was no overall effect of treatment group on 6, 12, or 18 month weight loss (ps = NS). However, at 6 months, those in TAILORED who were highly engaged (completing >66%) lost more weight compared to CONTROL (-2.32 kg [95% confidence intervals: -3.90, -0.74]; p = .004), with the trend continuing at 12 months. A significant baseline body mass index (BMI) by treatment group interaction (p = .004) was observed at 6 months. Among participants in the lowest baseline BMI category (25-27.5 kg/m2), those in TAILORED lost 2.27 kg (-3.86, -0.68) more, and those in TARGETED lost 1.72 kg (-3.16, -0.29) more than CONTROL after adjusting for covariates. Among participants with a BMI between 27.5 and 30 kg/m2, those in TAILORED lost 2.20 kg (-3.90, -0.51) more than participants in TARGETED. Results did not persist over time with no treatment interaction at 12 or 18 months. Initial body weight should be considered when recommending weight loss treatments for young adults. More intensive interventions or stepped care approaches may be needed for young adults with obesity.

Feasibility of Incorporating Voice Technology and Virtual Assistants in Cardiovascular Care and Clinical Trials

PURPOSE OF REVIEW

With the rising cost of cardiovascular clinical trials, there is interest in determining whether new technologies can increase cost effectiveness. This review focuses on current and potential uses of voice-based technologies, including virtual assistants, in cardiovascular clinical trials.

RECENT FINDINGS

Numerous potential uses for voice-based technologies have begun to emerge within cardiovascular medicine. Voice biomarkers, subtle changes in speech parameters, have emerged as a potential tool to diagnose and monitor many cardiovascular conditions, including heart failure, coronary artery disease, and pulmonary hypertension. With the increasing use of virtual assistants, numerous pilot studies have examined whether these devices can supplement initiatives to promote transitional care, physical activity, smoking cessation, and medication adherence with promising initial results. Additionally, these devices have demonstrated the ability to streamline data collection by administering questionnaires accurately and reliably. With the use of these technologies, there are several challenges that must be addressed before wider implementation including respecting patient privacy, maintaining regulatory standards, acceptance by patients and healthcare providers, determining the validity of voice-based biomarkers and endpoints, and increased accessibility.

SUMMARY

Voice technology represents a novel and promising tool for cardiovascular clinical trials; however, research is still required to understand how it can be best harnessed.

Behavioral weight loss in emerging adults: Design and rationale for the Richmond Emerging Adults Choosing Health (REACH) randomized clinical trial

BACKGROUND

In the U.S., over 40% of 18-25 year olds meet criteria for overweight or obesity. Yet, no large-scale trials have targeted this age group for behavioral weight loss (BWL). Formative data revealed that existing BWL programs do not meet their unique needs and identified motivation as a fundamental barrier for weight management. The goal of the Richmond Emerging Adults Choosing Health (REACH) trial was to test the efficacy of two mHealth lifestyle interventions specifically focused on enhancing motivation, relative to adapted standard.

METHODS

Participants (N = 381, 18-25 years, body mass index 25-45 kg/m²) will be randomized to 1) adapted BWL (aBWL), 2) aBWL + self-determination theory (aBWL+SDT), or 3) aBWL + behavioral economics (aBWL+BE). All arms will receive a 6-month intervention, delivered via one group session and one individual session, followed by an mHealth platform. Assessments will occur at baseline, 3-months, 6-months (post-treatment) and 12-months (following a no-contact period). The primary aim is to compare weight loss outcomes at 6 months. Secondary aims include changes at 6-months in physical and behavioral cardiometabolic risk factors, as well as psychosocial measures. We will also explore weight loss maintenance, change in hypothesized mediators, and moderators of treatment response.

DISCUSSION

REACH is the first large-scale BWL trial designed specifically for emerging adults. Further, it will be the first trial to compare a lifestyle intervention grounded in self-determination theory to one rooted in behavioral economics. If clinically significant reductions in adiposity are achieved, findings could inform a scalable treatment model to meet the needs of this vulnerable population.

TRIAL REGISTRATION

NCT02736981.

mHealth Technology and CVD Risk Reduction

PURPOSE OF REVIEW

To review existing mHealth-based interventions and examine their efficacy in reducing cardiovascular disease (CVD) risk factors.

RECENT FINDINGS

A total of 50 articles are included in this review. The majority of the mHealth interventions targeted a specific CVD risk factor, while 4 addressed 2 or more CVD risk factors. Of the 9 mHealth-supported weight loss intervention trials, 4 resulted in significant weight loss. Four out of 7 RCTs targeting improvement in physical activity reported significant improvement, while 4 of the 8 mHealth-supported smoking cessation intervention trials resulted in smoking abstinence. Of the 10 mHealth-based diabetes intervention trials, 5 reported significant reductions in HbA1c; however, only 3 out of the 9 antihypertension interventions resulted in significant reductions in blood pressure. There is a growing body of literature focused on mHealth interventions that address CVD risk factors. Despite the immense potential of mHealth interventions, evidence of their efficacy in mitigating cardiovascular risk is heterogeneous.

The Weight of Racial Discrimination: Examining the Association Between Racial Discrimination and Change in Adiposity Among Emerging Adult Women Enrolled in a Behavioral Weight Loss Program

BACKGROUND

Non-Hispanic Black (NHB) emerging adult (EA) women are at disproportionate risk for obesity but experience limited benefit from behavioral weight loss (BWL) programs. Race-related stress could play a role; the goal of this study was to examine the association between racial discrimination (RD) and early (3 months) changes in adiposity, and to explore potential protective factors, among EA in an adapted BWL program.

METHODS

This is an ancillary study of non-Hispanic White (NHW) and NHB EA women enrolled in an adapted BWL trial (N = 49; 55.1% NHB; Age 21.2 (2.1); BMI = 33.0 + 4.3 kg/m²). At baseline, group- and personal-level RD (RD-group and RD-personal), racial identity (NHB women only), vigilant coping, and social support were assessed via validated questionnaires. Weight and waist circumference were measured objectively at 0 and 3 months.

RESULTS

NHW women manifested greater reductions in waist circumference relative to NHB women (p = .004). RD-personal did not predict change in waist circumference at 3 months (p = .402); however, the association between RD-group and change in waist circumference was statistically significant (p = .015), such that reporting greater group-level discrimination predicted a smaller decrease in waist circumference; the model explained 22% of the variance. Social support and vigilant coping were not statistically significant in the model. Among NHB women only, higher racial identity-centrality predicted greater reduction in waist circumference (p = .019).

CONCLUSION

Findings suggest racial discrimination could contribute to greater cardiometabolic risk during this developmental period. Future research should examine how experiences of racial discrimination unfold in the daily lives of NHB women to inform mechanistic interventions to enhance health and well-being.

TRIAL REGISTRATION

NCT02736981. Low Intensity Weight Loss for Young Adults.

Recruiting and retaining young adults: what can we learn from behavioural interventions targeting nutrition, physical activity and/or obesity? A systematic review of the literature

OBJECTIVE

To describe strategies used to recruit and retain young adults in nutrition, physical activity and/or obesity intervention studies, and quantify the success and efficiency of these strategies.

DESIGN

A systematic review was conducted. The search included six electronic databases to identify randomised controlled trials (RCT) published up to 6 December 2019 that evaluated nutrition, physical activity and/or obesity interventions in young adults (17-35 years). Recruitment was considered successful if the pre-determined sample size goal was met. Retention was considered acceptable if ≥80 % retained for ≤6-month follow-up or ≥70 % for >6-month follow-up.

RESULTS

From 21 582 manuscripts identified, 107 RCT were included. Universities were the most common recruitment setting used in eighty-four studies (79 %). Less than half (46 %) of the studies provided sufficient information to evaluate whether individual recruitment strategies met sample size goals, with 77 % successfully achieving recruitment targets. Reporting for retention was slightly better with 69 % of studies providing sufficient information to determine whether individual retention strategies achieved adequate retention rates. Of these, 65 % had adequate retention.

CONCLUSIONS

This review highlights poor reporting of recruitment and retention information across trials. Findings may not be applicable outside a university setting. Guidance on how to improve reporting practices to optimise recruitment and retention strategies within young adults could assist researchers in improving outcomes.

Younger Adults Are More Likely to Increase Fruit and Vegetable Consumption and Decrease Sugar Intake with the Application of Dietary Monitoring

Establishing healthy eating habits is considered to be a sustainable strategy for health maintenance, and mobile applications (apps) are expected to be highly effective among the young-aged population for healthy eating promotion. The purpose of this study was to investigate the effectiveness of a dietary monitoring app on younger adults’ nutrition knowledge and their dietary habits. A controlled-experimental study was performed with one experimental group having a three-hour nutrition seminar and 12 weeks of dietary monitoring with the app, and one control group receiving a three-hour nutrition seminar. Behavioral feedback delivered by the app was evaluated in facilitating the transfer of nutritional knowledge to nutrition behavior. A total of 305 younger adults aged from 19 to 31 were recruited. Baseline and post-intervention nutrition knowledge and dietary behavior were collected. All mean scores of post-GNKQ-R increased from baseline for both the control and the experimental groups. The mean differences of sugar intake, dietary fiber intake, and vitamin C intake for the experimental group were significantly more than those for the control group (all p < 0.001). In addition, the experimental group increased fruit and vegetable consumption significantly more than the control group (all p < 0.001). For those younger adults with a relatively large body size, they were more likely to increase fruit consumption with the application of dietary monitoring.

Use of Technology-Based Interventions in the Treatment of Patients with Overweight and Obesity: A Systematic Review

Introduction: Obesity is one of the most important health problems worldwide. The prevalence of obesity has increased dramatically in the last decades and is now recognized as a global epidemic. Given the dramatic consequences of obesity, new intervention approaches based on the potential of technologies have been developed. Methods: We conducted a systematic review of studies using PubMed, ScienceDirect, Cochrane Library, and MedLine databases to assess how different types of technologies may play an important role on weight loss in obese patients. Results: Forty-seven studies using different types of technologies including smartphones, app, websites, virtual reality and personal digital assistant were included in the review. About half of interventions (47%) found a significant effect of the technology-based interventions for weight lost in obese patients. The provision of feedback could also be effective as a complement to interventions carried out using technology to promote weight loss. Conclusions: The use of technologies can be effective to increase weight loss in patients with obesity improving treatment adherence through self-monitoring.

Weight Management Interventions for Adults With Overweight or Obesity: An Evidence Analysis Center Scoping Review

The objectives of this evidence scoping review were to identify and characterize studies investigating weight management interventions provided by a registered dietitian nutritionist or international equivalent (RDN) among adults with overweight or obesity. A medical librarian conducted an electronic literature search in 6 databases-MEDLINE (Ovid), Embase (Ovid), PyscINFO (Ovid), Cochrane CENTRAL (Ovid), Cochrane Database of Systematic Reviews (Ovid), and CINAHL (Ebsco). Except for narrative review, gray literature, and case study or report, all types of peer-reviewed articles published between January 2008 and April 26, 2019 were eligible. Two content advisors, who are experts in adult weight management, guided the process and reviewed the search plan and findings. The literature search resulted in 30,551 records with 16 additional records identified through other sources. A total of 29,756 records were excluded during the first round of screening due to duplication or irrelevancy. Of the 811 full-text articles that were screened, 139 met the criteria and were included. Approximately 51% and 43% of the studies were conducted in the community setting and in the United States or Canada, respectively. Over 97% of the studies were clinical or quasi-experimental trials. A total of 6 different intervention delivery modes were reported, which resulted in 22 combinations of the modes of delivery. RDNs delivered the weight management intervention (especially the nutrition component) in all studies, but some (61%) also involved an interdisciplinary team to deliver other components of the intervention. The average length of the intervention was about 10 months with a follow-up that ranged from 0 to 9 years. The commonly reported outcomes were anthropometrics, endocrine, and cardiovascular measures; dietary intake; and physical activity. Based on the scoping review, there were systematic reviews and evidence-based practice guidelines on weight management interventions but none of them met the a priori inclusion or exclusion criteria. Therefore, it would be beneficial to conduct a systematic review and develop an evidence-based practice guideline on adult weight management interventions provided by an RDN to guide practitioners and to evaluate their effects on health and nutrition-related outcomes.

Review of the Scientific Literature on Young Adults Related to Cardiovascular Disease Intervention

Many young adults are at risk for cardiovascular disease related to their behavioral choices. Irresponsible alcohol consumption, tobacco smoking, sedentary lifestyle, poor dietary habits, and excessive weight gain are some of the behaviors that put young adults at risk. The Centers for Disease Control and Prevention identified that 15% of young adults are diagnosed with chronic illnesses related to their behavioral choices. The purpose of this review is to identify, in the literature, interventions that are currently available to young adults and evaluate the adequacy and effectiveness of those interventions. An extensive electronic search was conducted using CINAHL, EBSCOhost, Cochrane, PubMed, and Google Scholar. A total of 130 articles were identified and 28 articles met the inclusion criteria. Three main interventions were identified for young adults: personalized interventions, technology-based interventions, and educational/behavioral interventions. The interventions were all effective to different degrees and interventions were most effective when they were combined. This review impacts in what manner nurses and health care providers deliver health promotion, prevention, and management of cardiovascular risk factors in young adults; in particular, nurses play a key role in lifestyle modifications including diet and exercise.

Effect of Behavioral Weight Management Interventions Using Lifestyle mHealth Self-Monitoring on Weight Loss: A Systematic Review and Meta-Analysis

Alongside an increase in obesity, society is experiencing the development of substantial technological advances. Interventions that are easily scalable, such as lifestyle (including diet and physical activity) mobile health (mHealth) self-monitoring, may be highly valuable in the prevention and treatment of excess weight. Thus, the aims of this systematic review and meta-analysis were to estimate the following: (i) the effect of behavioral weight management interventions using lifestyle mHealth self-monitoring on weight loss and (ii) the adherence to behavioral weight management interventions using lifestyle mHealth self-monitoring. MEDLINE via PubMed, EMBASE, the Cochrane Central Register of Controlled Trials and the Web of Science databases were systematically searched. The DerSimonian and Laird method was used to estimate the effect of and adherence to behavioral weight management interventions using lifestyle mHealth self-monitoring on weight loss. Twenty studies were included in the systematic review and meta-analysis, yielding a moderate decrease in weight and higher adherence to intervention of behavioral weight management interventions using lifestyle mHealth self-monitoring, which was greater than other interventions. Subgroup analyses showed that smartphones were the most effective mHealth approach to achieve weight management and the effect of behavioral weight management interventions using lifestyle mHealth self-monitoring was more pronounced when compared to usual care and in the short-term (less than six months). Furthermore, behavioral weight management interventions using lifestyle mHealth self-monitoring showed a higher adherence than: (i) recording on paper at any time and (ii) any other intervention at six and twelve months.

Using motivational interviewing to enhance emerging adults' engagement in weight loss: The Live Well RVA pilot randomized clinical trial

Background

Emerging adults (ages 18–25) are at high risk for overweight/obesity, yet traditional adult behavioural weight loss (BWL) interventions do not meet the needs of individuals at this developmental stage. Motivational interviewing (MI) is an evidence‐based approach to promote behaviour change but has not been tested for weight loss in this population. The study aimed to test the feasibility and preliminary efficacy of an MI‐enhanced weight loss programme to promote engagement, retention and weight loss in emerging adults.

Methods

Emerging adults with overweight/obesity (N = 47, 81% female, 47% racial/ethnic minority, body mass index [BMI] = 33.2 ± 4.6 kg/m²) were randomized to either standard BWL or MI‐enhanced BWL (MIBWL). Weight was assessed objectively at baseline and posttreatment (3 months). Engagement (in‐person session attendance [weeks 1 and 2], online self‐monitoring [weeks 3–12] and online content viewing [weeks 3–12]) was tracked throughout the program.

Results

Though results did not reach the level of statistical significance, participants in MIBWL demonstrated greater programme engagement (77% vs. 61.0%, p = .11; Cohen d = .48), retention (71% vs. 48.0%, p = .10; Cohen h = .47) and intent‐to‐treat weight loss (−3.3% vs. −2.2%, p = .37; Cohen d = .26) compared with those in BWL.

Conclusions

Effect sizes suggest that MI might be a viable approach to enhance engagement and retention in weight loss programmes targeting emerging adults. This finding is meaningful, given the documented challenges with engagement and retention in this vulnerable population and the relationship between engagement and better weight loss outcomes. The results of this small pilot study support efforts to replicate these findings within the context of a fully powered trial.

Which behaviour change techniques within interventions to prevent weight gain and/or initiate weight loss improve adiposity outcomes in young adults? A systematic review and meta-analysis of randomized controlled trials

Young adulthood is associated with the highest rate of weight gain compared with any other adult age group. This review evaluates the effectiveness of interventions with adiposity outcomes among young adults and identifies which behaviour change techniques (BCTs) are most effective. BCT utilization was assessed using Michie's 93-item BCT Taxonomy v1. Six electronic databases were searched for randomized controlled trials assessing change in adiposity in young adults (17-35 years) until December 2019; identifying 21,582 articles. Fifty-one studies were included. Meta-analyses for weight (n=19 studies), body mass index (BMI) (n=20 studies), and waist circumference (n=10 studies) demonstrated no significant between-group differences at ≤3 or >3 months. There were no differences between interventions focusing on weight loss or weight-gain prevention. Narrative synthesis showed significant between-group differences in weight change, favouring the intervention in 14/43 (33%) studies. In studies assessing BMI and waist circumference, this was 31% (11/36) and 25% (4/16). Two BCTs had a percentage effectiveness ratio >50% in weight loss interventions; social support (unspecified) and self-monitoring behaviour, and one in weight-gain prevention interventions; and goal-setting (outcome). Findings demonstrate initial potential for these types of BCTs and can help build cumulative evidence towards delivering effective, cost-efficient, and replicable interventions.