Distance learning strategies for weight management utilizing online social networks versus group phone conference call

The effectiveness and usability of online, group-based interventions for people with severe obesity: a systematic review and meta-analysis

Long wait times, limited resources, and a lack of local options mean that many people with severe obesity cannot access treatment. Face-to-face group-based interventions have been found effective and can treat multiple people simultaneously, but are limited by service capacity. Digital group interventions could reduce wait times, but research on their effectiveness is limited. This systematic review aimed to examine the literature about online group-based interventions for adults with severe obesity (BMI ≥ 35 kg/m2). The review followed the PRISMA and PICOS frameworks. MEDLINE, Embase, CINAHL, Web of Science, and Cochrane Central Register of Controlled Trials were searched. Two authors independently screened articles. Data extraction, analysis, and quality assessment (using RoB2 and MMAT) was shared between two authors. A meta-analysis was conducted on eligible studies; other results were descriptively analysed. 20 papers reporting on 15 studies were included. Most studies reported some evidence of weight loss, but evidence of weight-related behaviour change was mixed. A meta-analysis on four studies indicated that online, group-based interventions had a statistically significant impact on weight loss (p = 0.001; 95% CI -0.69 to -0.17) with a small-to-moderate effect size, compared to waitlist or standard care conditions. Online interventions were considered more convenient but lack of familiarity with the group or counsellor, accessibility issues, and time constraints hindered engagement. Technical support, incentives, and interactive forums to improve group cohesion could mitigate these barriers. The findings suggested that online, group-based interventions are feasible and potentially beneficial, but barriers such as internet accessibility, digital literacy, and unfamiliarity with group members need to be mitigated. Key recommendations to improve experience and impact include providing instructions and run-throughs, building group cohesion, and providing session and additional content throughout the intervention. Future studies should focus on the influence of specific intervention characteristics and investigate the effect of these interventions compared to face-to-face interventions. Registration: National Institute for Health Research, PROSPERO CRD42021227101; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021227101 .

Remote delivery of a weight management intervention for adults with intellectual disabilities: Results from a randomized non-inferiority trial

BACKGROUND

Remote delivery of multi-component weight management interventions results in clinically meaningful weight loss in adults without intellectual disabilities (ID), but the effectiveness of remotely delivered weight management interventions in adults with ID has not previously been evaluated.

OBJECTIVE

To determine if a weight management intervention delivered remotely could achieve weight loss (kg) at 6 months that is non-inferior to in-person visits in adults with ID and overweight or obesity (BMI ≥25 kg/m2).

METHODS

Participants were randomized to a 24-mo. trial (6 mos weight loss,12 mos weight maintenance, 6 mos. no-contact follow up) to compare weight loss achieved with the same multicomponent intervention delivered to individual participants in their home either remotely (RD) or during face-to-face home visits (FTF).

RESULTS

One hundred twenty adults with ID (∼32 years of age, 53 % females) were randomized to the RD (n = 60) or the FTF arm (n = 60). Six-month weight loss in the RD arm (-4.9 ± 7.8 kg) was superior to 6-month weight loss achieved in the FTF arm (-2.1 ± 6.7 kg, p = 0.047). However, this may be partially attributed to the COVID-19 pandemic, since weight loss in the FTF arm was greater in participants who completed the intervention entirely pre-COVID (n = 33,-3.2 %) compared to post-COVID (n = 22, -0.61 %). Weight loss across did not differ significantly between intervention arms at 18 (p = 0.33) or 24 months (p = 0.34).

CONCLUSION

Our results suggest that remote delivery is a viable option for achieving clinically relevant weight loss and maintenance in adults with ID.

NCT REGISTRATION

NCT03291509.

Telehealth Technologies in Diabetes Self-management and Education

BACKGROUND

The coronavirus pandemic of 2019 (COVID-19) forced worldwide recognition and implementation of telehealth as a means of providing continuity of care by varied health care institutions. Diabetes is a global health threat with rates that continue to accelerate, thereby causing an increased need for clinicians to provide diabetes care and education to keep up with demand. Utilizing technology to provide education via phone/smartphone, video/audio, web, text message, mobile apps, or a combination of these methods can help improve patient access and clinical outcomes, cut costs, and close gaps in care.

METHODS

While numerous publications have summarized the various tools and technologies available for capturing remote clinical data and their relevance to diabetes care and self-management, this review focuses on self-educational telehealth tools available for diabetes self-management, their advantages and disadvantages, and factors that need to be considered prior to implementation. Recent relevant studies indexed by PubMed were included.

RESULTS

The widespread use and popularity of phones/smartphones, tablets, computers, and the Internet by patients of all age groups, cultures, socioeconomic and geographic areas allow for increased outreach, flexibility, and engagement with diabetes education, either in combination or as an adjunct to traditional in-person visits. Demonstrated benefits of using health technologies for diabetes self-management education include improved lifestyle habits, reduced hemoglobin A1C levels, decreased health care costs, and better medication adherence. Potential drawbacks include lack of regulation, need for staff training on methodologies used, the requirement for patients to be tech savvy, privacy concerns, lag time with technology updates/glitches, and the need for more long-term research data on efficacy.

CONCLUSIONS

Telehealth technologies for diabetes self-education improve overall clinical outcomes and have come a long way. With increasing numbers of patients with diabetes, it is expected that more optimal and user-friendly methodologies will be developed to fully engage and help patients communicate with their physicians.

Social media-based interventions for adults with obesity and overweight: a meta-analysis and meta-regression

Social isolation and loneliness are growing public health concerns in adults with obesity and overweight. Social media-based interventions may be a promising approach. This systematic review aims to (1) evaluate the effectiveness of social media-based interventions on weight, body mass index, waist circumference, fat, energy intake and physical activity among adults with obesity and overweight and (2) explore potential covariates on treatment effect. Eight databases, namely, PubMed, Cochrane Library, Embase, CINAHL, Web of Science, Scopus PsycINFO and ProQuest, were searched from inception until December 31, 2021. The Cochrane Collaboration Risk of Bias Tool and Grading of Recommendations, Assessment, Development and Evaluation criteria evaluated the evidence quality. Twenty-eight randomised controlled trials were identified. Meta-analyses found that social media-based interventions had small-to-medium significant effects on weight, BMI, waist circumference, body fat mass and daily steps. Subgroup analysis found greater effect in interventions without published protocol or not registered in trial registries than their counterparts. Meta-regression analysis showed that duration of intervention was a significant covariate. The certainty of evidence quality of all outcomes was very low or low. Social media-based interventions can be considered an adjunct intervention for weight management. Future trials with large sample sizes and follow-up assessment are needed.

The Role of Facebook® in Promoting a Physically Active Lifestyle: A Systematic Review and Meta-Analysis

BACKGROUND

it is well known in literature that sedentary lifestyle contributes to worsening people's health. This issue highlights the need for effective interventions to promote an active lifestyle. Research suggested multilevel intervention strategies to promote adherence to recommended physical activity levels, including the use of social networks that may simplify access to health notions. Being Facebook^® the most extensive worldwide social network, this document aimed to analyze the current body of evidence on the role of Facebook^® in the promotion of physical activity.

METHODS

eighteen manuscripts were considered eligible for this systematic review, and it was performed a meta-analysis (PRISMA guidelines) for overall physical activity parameters in eleven out of eighteen studies.

RESULTS

significant improvements were detected in the total amount of physical activity. In parallel, an increase in other parameters, such as cardiovascular, body composition, and social support, were found. The aerobic training, with supervised and tailored modalities, showed more considerable improvements.

CONCLUSIONS

this study showed that Facebook^® might be considered a feasible and accessible approach to promoting regular exercise practice and achieving health benefits indicators. Future research on the cross-link between physical activity and social network management could also focus on strength training to verify if a more structured intervention would show an effect.

Moving Food Assistance into the Digital Age: A Scoping Review

One of the most basic needs globally, food assistance refers to the multitude of programs, both governmental and non-governmental, to improve food access and consumption by food-insecure individuals and families. Despite the importance of digital and mobile Health (mHealth) strategies in food insecurity contexts, little is known about their specific use in food assistance programs. Therefore, the purpose of this study was to address that gap by conducting a scoping review of the literature. Keywords were defined within the concepts of food assistance and digital technology. The search included relevant peer-reviewed and grey literature from 2011 to 2021. Excluded articles related to agriculture and non-digital strategies. PRISMA guidelines were followed to perform a partnered, two-round scoping literature review. The final synthesis included 39 studies of which most (84.6%) were from the last five years and United States-based (93.2%). The top three types of articles or studies included text and opinion, qualitative research, and website, application, or model development (17.9%). The top three types of digital tools were websites (56.4%), smartphone applications (20.5%), and chatbots (5.1%). Nineteen digital features were identified as desirable. Most tools included just one or two features. The most popular feature to include was online shopping (n = 14), followed by inventory management, and client tracking. Digital tools for individual food assistance represent an opportunity for equitable and stable access to programs that can enhance or replace in-person services. While this review identified 39 tools, all are in early development and/or implementation stages. Review findings highlight an overall lack of these tools, an absence of user-centered design in their development, and a critical need for research on their effectiveness globally. Further analysis and testing of current digital tool usage and interventions examining the health and food security impacts of such tools should be explored in future studies, including in the context of pandemics, where digital tools allow for help from a distance.

Weight Loss Interventions for Adolescents With Intellectual Disabilities: An RCT

OBJECTIVES

In this randomized trial, we compared the effectiveness of 2 diets (enhanced stop light diet [eSLD] versus conventional meal plan diet [CD]) and 2 delivery strategies (face-to-face [FTF] versus remote delivery [RD]) on weight loss across 6 months in adolescents with intellectual and developmental disabilities who were overweight or obese.

METHODS

Participants were randomly assigned to 1 of 3 arms (FTF/CD, RD/CD, or RD/eSLD) and asked to attend one-on-one sessions with a health educator every 2 weeks to aid in maintaining compliance with recommendations for a reduced-energy diet and increased physical activity. The CD followed the US dietary guidelines. The eSLD used the stop light guide and was enhanced with portion-controlled meals. The FTF arm was delivered during in-person home visits. The RD arms were delivered by using video conferencing.

RESULTS

A total of 110 adolescents with intellectual and developmental disabilities (aged ∼16 years, 53% female, BMI 33) were randomly assigned to the FTF/CD (n = 36), RD/CD (n = 39), or RD/eSLD (n = 35) group. Body weight at 6 months was obtained from 97%, 100%, and 86% of participants in the FTF/CD, RD/CD, and RD/eSLD arms, respectively. The eSLD elicited significantly greater weight loss than the CD: RD/eSLD (-5.0 ± 5.9 kg; -6.4%) versus RD/CD (-1.8 ± 4.0 kg; -2.4%) (P = .01). However, weight loss did not differ by delivery strategy: FTF/CD (-0.3 ± 5.0 kg; -0.2%) versus RD/CD (-1.8 ± 4.0 kg; -2.4%) (P = .20).

CONCLUSIONS

The eSLD elicited significantly greater 6-month weight loss compared with a CD when both interventions were delivered remotely. Minimal 6-month weight loss, which did not differ significantly between FTF delivery and RD, was observed with a CD.

The effect of social media interventions on physical activity and dietary behaviours in young people and adults: a systematic review

BACKGROUND

The objectives of this systematic review were to update the evidence base on social media interventions for physical activity and diet since 2014, analyse the characteristics of interventions that resulted in changes to physical activity and diet-related behaviours, and assess differences in outcomes across different population groups.

METHODS

A systematic search of the literature was conducted across 5 databases (Medline, Embase, EBSCO Education, Wiley and Scopus) using key words related to social media, physical activity, diet, and age. The inclusion criteria were: participants age 13+ years in the general population; an intervention that used commercial social media platform(s); outcomes related to changes to diet/eating or physical activity behaviours; and quantitative, qualitative and mixed methods studies. Quality appraisal tools that aligned with the study designs were used. A mixed methods approach was used to analyse and synthesise all evidence.

RESULTS

Eighteen studies were included: randomised control trials (n = 4), non-controlled trials (n = 3), mixed methods studies (n = 3), non-randomised controlled trials (n = 5) and cross-sectional studies (n = 3). The target population of most studies was young female adults (aged 18-35) attending college/university. The interventions reported on positive changes to physical activity and diet-related behaviours through increases in physical activity levels and modifications to food intake, body composition and/or body weight. The use of Facebook, Facebook groups and the accessibility of information and interaction were the main characteristics of social media interventions. Studies also reported on Instagram, Reddit, WeChat and Twitter and the use of photo sharing and editing, groups and sub-groups and gamification.

CONCLUSIONS

Social media interventions can positively change physical activity and diet-related behaviours, via increases in physical activity levels, healthy modifications to food intake, and beneficial changes to body composition or body weight. New evidence is provided on the contemporary uses of social media (e.g. gamification, multi-model application, image sharing/editing, group chats) that can be used by policy makers, professionals, organisations and/or researchers to inform the design of future social media interventions. This study had some limitations that mainly relate to variation in study design, over-reliance of self-reported measures and sample characteristics, that prevented comparative analysis. Registration number: PROPSERO; CRD42020210806 .

Behavioural interventions delivered through interactive social media for health behaviour change, health outcomes, and health equity in the adult population

BACKGROUND

Social networking platforms offer a wide reach for public health interventions allowing communication with broad audiences using tools that are generally free and straightforward to use and may be combined with other components, such as public health policies. We define interactive social media as activities, practices, or behaviours among communities of people who have gathered online to interactively share information, knowledge, and opinions.

OBJECTIVES

We aimed to assess the effectiveness of interactive social media interventions, in which adults are able to communicate directly with each other, on changing health behaviours, body functions, psychological health, well-being, and adverse effects. Our secondary objective was to assess the effects of these interventions on the health of populations who experience health inequity as defined by PROGRESS-Plus. We assessed whether there is evidence about PROGRESS-Plus populations being included in studies and whether results are analysed across any of these characteristics.

SEARCH METHODS

We searched CENTRAL, CINAHL, Embase, MEDLINE (including trial registries) and PsycINFO. We used Google, Web of Science, and relevant web sites to identify additional studies and searched reference lists of included studies. We searched for published and unpublished studies from 2001 until June 1, 2020. We did not limit results by language.

SELECTION CRITERIA

We included randomised controlled trials (RCTs), controlled before-and-after (CBAs) and interrupted time series studies (ITSs). We included studies in which the intervention website, app, or social media platform described a goal of changing a health behaviour, or included a behaviour change technique. The social media intervention had to be delivered to adults via a commonly-used social media platform or one that mimicked a commonly-used platform. We included studies comparing an interactive social media intervention alone or as a component of a multi-component intervention with either a non-interactive social media control or an active but less-interactive social media comparator (e.g. a moderated versus an unmoderated discussion group). Our main outcomes were health behaviours (e.g. physical activity), body function outcomes (e.g. blood glucose), psychological health outcomes (e.g. depression), well-being, and adverse events. Our secondary outcomes were process outcomes important for behaviour change and included knowledge, attitudes, intention and motivation, perceived susceptibility, self-efficacy, and social support.

DATA COLLECTION AND ANALYSIS

We used a pre-tested data extraction form and collected data independently, in duplicate. Because we aimed to assess broad outcomes, we extracted only one outcome per main and secondary outcome categories prioritised by those that were the primary outcome as reported by the study authors, used in a sample size calculation, and patient-important.

MAIN RESULTS

We included 88 studies (871,378 participants), of which 84 were RCTs, three were CBAs and one was an ITS. The majority of the studies were conducted in the USA (54%). In total, 86% were conducted in high-income countries and the remaining 14% in upper middle-income countries. The most commonly used social media platform was Facebook (39%) with few studies utilising other platforms such as WeChat, Twitter, WhatsApp, and Google Hangouts. Many studies (48%) used web-based communities or apps that mimic functions of these well-known social media platforms. We compared studies assessing interactive social media interventions with non-interactive social media interventions, which included paper-based or in-person interventions or no intervention. We only reported the RCT results in our 'Summary of findings' table. We found a range of effects on health behaviours, such as breastfeeding, condom use, diet quality, medication adherence, medical screening and testing, physical activity, tobacco use, and vaccination. For example, these interventions may increase physical activity and medical screening tests but there was little to no effect for other health behaviours, such as improved diet or reduced tobacco use (20,139 participants in 54 RCTs). For body function outcomes, interactive social media interventions may result in small but important positive effects, such as a small but important positive effect on weight loss and a small but important reduction in resting heart rate (4521 participants in 30 RCTs). Interactive social media may improve overall well-being (standardised mean difference (SMD) 0.46, 95% confidence interval (CI) 0.14 to 0.79, moderate effect, low-certainty evidence) demonstrated by an increase of 3.77 points on a general well-being scale (from 1.15 to 6.48 points higher) where scores range from 14 to 70 (3792 participants in 16 studies). We found no difference in effect on psychological outcomes (depression and distress) representing a difference of 0.1 points on a standard scale in which scores range from 0 to 63 points (SMD -0.01, 95% CI -0.14 to 0.12, low-certainty evidence, 2070 participants in 12 RCTs). We also compared studies assessing interactive social media interventions with those with an active but less interactive social media control (11 studies). Four RCTs (1523 participants) that reported on physical activity found an improvement demonstrated by an increase of 28 minutes of moderate-to-vigorous physical activity per week (from 10 to 47 minutes more, SMD 0.35, 95% CI 0.12 to 0.59, small effect, very low-certainty evidence). Two studies found little to no difference in well-being for those in the intervention and control groups (SMD 0.02, 95% CI -0.08 to 0.13, small effect, low-certainty evidence), demonstrated by a mean change of 0.4 points on a scale with a range of 0 to 100. Adverse events related to the social media component of the interventions, such as privacy issues, were not reported in any of our included studies. We were unable to conduct planned subgroup analyses related to health equity as only four studies reported relevant data.

AUTHORS' CONCLUSIONS

This review combined data for a variety of outcomes and found that social media interventions that aim to increase physical activity may be effective and social media interventions may improve well-being. While we assessed many other outcomes, there were too few studies to compare or, where there were studies, the evidence was uncertain. None of our included studies reported adverse effects related to the social media component of the intervention. Future studies should assess adverse events related to the interactive social media component and should report on population characteristics to increase our understanding of the potential effect of these interventions on reducing health inequities.

Use of Fitbit Devices in Physical Activity Intervention Studies Across the Life Course: Narrative Review

BACKGROUND

Commercial off-the-shelf activity trackers (eg, Fitbit) allow users to self-monitor their daily physical activity (PA), including the number of steps, type of PA, amount of sleep, and other features. Fitbits have been used as both measurement and intervention tools. However, it is not clear how they are being incorporated into PA intervention studies, and their use in specific age groups across the life course is not well understood.

OBJECTIVE

This narrative review aims to characterize how PA intervention studies across the life course use Fitbit devices by synthesizing and summarizing information on device selection, intended use (intervention vs measurement tool), participant wear instructions, rates of adherence to device wear, strategies used to boost adherence, and the complementary use of other PA measures. This review provides intervention scientists with a synthesis of information that may inform future trials involving Fitbit devices.

METHODS

We conducted a search of the Fitabase Fitbit Research Library, a database of studies published between 2012 and 2018. Of the 682 studies available on the Fitabase research library, 60 interventions met the eligibility criteria and were included in this review. A supplemental search in PubMed resulted in the inclusion of 15 additional articles published between 2019 and 2020. A total of 75 articles were reviewed, which represented interventions conducted in childhood; adolescence; and early, middle, and older adulthood.

RESULTS

There was considerable heterogeneity in the use of Fitbit within and between developmental stages. Interventions for adults typically required longer wear periods, whereas studies on children and adolescents tended to have more limited device wear periods. Most studies used developmentally appropriate behavior change techniques and device wear instructions. Regardless of the developmental stage and intended Fitbit use (ie, measurement vs intervention tool), the most common strategies used to enhance wear time included sending participants reminders through texts or emails and asking participants to log their steps or synchronize their Fitbit data daily. The rates of adherence to the wear time criteria were reported using varying metrics. Most studies supplemented the use of Fitbit with additional objective or self-reported measures for PA.

CONCLUSIONS

Overall, the heterogeneity in Fitbit use across PA intervention studies reflects its relative novelty in the field of research. As the use of monitoring devices continues to expand in PA research, the lack of uniformity in study protocols and metrics of reported measures represents a major issue for comparability purposes. There is a need for increased transparency in the prospective registration of PA intervention studies. Researchers need to provide a clear rationale for the use of several PA measures and specify the source of their main PA outcome and how additional measures will be used in the context of Fitbit-based interventions.

Behavior Change Techniques Included in Reports of Social Media Interventions for Promoting Health Behaviors in Adults: Content Analysis Within a Systematic Review

BACKGROUND

Social media are an increasingly commonly used platform for delivering health promotion interventions. Although recent research has focused on the effectiveness of social media interventions for health promotion, very little is known about the optimal content within such interventions, and the active ingredients to promote health behavior change using social media are not clear. Identifying which behavior change techniques (BCTs) are reported may help to clarify the content of interventions using a generalizable terminology that may facilitate future intervention development.

OBJECTIVE

This study aimed to identify which BCTs are reported in social media interventions for promoting health behavior change in adults.

METHODS

We included 71 studies conducted with adult participants (aged ≥18 years) and for which social media intervention was considered interactive in a Cochrane review of the effectiveness of such interventions. We developed a coding manual informed by the Behavior Change Technique Taxonomy version 1 (BCTTv1) to identify BCTs in the included studies. We identified BCTs in all study arms (including control) and described BCTs in the group and self-directed components of studies. We characterized the dose of delivery for each BCT by low and high intensity. We used descriptive analyses to characterize the reported BCTs.

RESULTS

Our data consisted of 71 studies published from 2001 to 2017, mainly conducted in high-income countries (n=65). Most studies (n=31) used tailored, interactive websites to deliver the intervention; Facebook was the most used mainstream platform. In developing our coding manual, we adapted some BCTTv1 instructions to better capture unique nuances of how BCTs were operationalized in social media with respect to likes, retweets, smiles, congratulations, and badges. Social support (unspecified), instruction on how to perform the behavior, and credible source were most frequently identified BCTs in intervention arms of studies and group-delivery settings, whereas instruction on how to perform the behavior was most commonly applied in self-directed components of studies, control arms, and individual participant settings. Instruction on how to perform the behavior was also the most frequently reported BCT in both intervention and control arms simultaneously. Instruction on how to perform the behavior, social support (unspecified), self-monitoring of behavior, information about health consequences, and credible source were identified in the top 5 BCTs delivered with the highest intensity.

CONCLUSIONS

This study within a review provides a detailed description of the BCTs and their dose to promote behavior change in web-based, interactive social media interventions. Clarifying active ingredients in social media interventions and the intensity of their delivery may help to develop future interventions that can more clearly build upon the existing evidence.

Remotely Delivered Interventions for Obesity Treatment

PURPOSE OF REVIEW

This review synthesizes recent research on remotely delivered interventions for obesity treatment, including summarizing outcomes and challenges to implementing these treatments as well as outlining recommendations for clinical implementation and future research.

RECENT FINDINGS

There are a wide range of technologies used for delivering obesity treatment remotely. Generally, these treatments appear to be acceptable and feasible, though weight loss outcomes are mixed. Engagement in these interventions, particularly in the long term, is a significant challenge. Newer technologies are rapidly developing and enable tailored and adaptable interventions, though research in this area is in its infancy. Further research is required to optimize potential benefits of remotely delivered interventions for obesity.

Clinic Versus Online Social Network-Delivered Lifestyle Interventions: Protocol for the Get Social Noninferiority Randomized Controlled Trial

Background

Online social networks may be a promising modality to deliver lifestyle interventions by reducing cost and burden. Although online social networks have been integrated as one component of multimodality lifestyle interventions, no randomized trials to date have compared a lifestyle intervention delivered entirely via online social network with a traditional clinic-delivered intervention.

Objective

This paper describes the design and methods of a noninferiority randomized controlled trial, testing (1) whether a lifestyle intervention delivered entirely through an online social network would produce weight loss that would not be appreciably worse than that induced by a traditional clinic-based lifestyle intervention among overweight and obese adults and (2) whether the former would do so at a lower cost.

Methods

Adults with body mass index (BMI) between 27 and 45 kg/m² (N=328) will be recruited from the communities in central Massachusetts. These overweight or obese adults will be randomized to two conditions: a lifestyle intervention delivered entirely via the online social network Twitter (Get Social condition) and an in-person group-based lifestyle intervention (Traditional condition) among overweight and obese adults. Measures will be obtained at baseline, 6 months, and 12 months after randomization. The primary noninferiority outcome is percentage weight loss at 12 months. Secondary noninferiority outcomes include dietary intake and moderate intensity physical activity at 12 months. Our secondary aim is to compare the conditions on cost. Exploratory outcomes include treatment retention, acceptability, and burden. Finally, we will explore predictors of weight loss in the online social network condition.

Results

The final wave of data collection is expected to conclude in June 2019. Data analysis will take place in the months following and is expected to be complete in September 2019.

Conclusions

Findings will extend the literature by revealing whether delivering a lifestyle intervention via an online social network is an effective alternative to the traditional modality of clinic visits, given the former might be more scalable and feasible to implement in settings that cannot support clinic-based models.

Trial Registration

ClinicalTrials.gov NCT02646618; https://clinicaltrials.gov/ct2/show/NCT02646618 (Archived by WebCite at http://www.webcitation.org/6v20waTFW)

Distance learning strategies for weight management utilizing online social networks versus group phone conference call

OBJECTIVE

The increase in technology and online social networks (OSNs) may present healthcare providers with an innovative modality for delivering weight management programmes that could have an impact on health care at the population level. The objective of this study was to evaluate the feasibility and efficacy of using an OSN to deliver a weight loss programme to inform future, large-scale trials.

METHODS

Seventy individuals (age = 47 ± 12.4, minority = 24.3%) with obesity (BMI = 36.2 ± 4.0) completed a 6-month weight loss intervention and were randomized to either a conference call or OSN delivery group. Weight loss was achieved by reducing energy intake by 500-700 kcal·d-1 below estimated total daily energy expenditure and progressing physical activity to 300 min/week. Behavioural weight loss strategies were delivered weekly throughout the intervention.

RESULTS

Conference call and OSN groups produced clinically meaningful weight loss of ≥5% from baseline to 6 months (phone = -6.3 ± 6.4%, OSN = -5.8 ± 6.7%). There was no significant difference in weight change between groups (p = 0.765).

CONCLUSION

The phone and OSN groups met the American Heart Association/American College of Cardiology/The Obesity Society's Guidelines by reducing baseline weight by 5-10% within 6 months. OSNs appear to be a viable delivery platform for weight loss interventions; however, larger scale adequately powered trials are needed.