Delivering a Post-Partum Weight Loss Intervention via Facebook or In-Person Groups: Protocol for a Randomized Feasibility Pilot Trial

Feedback on Instagram posts for a gestational weight gain intervention

Lifestyle interventions can facilitate healthy gestational weight gain but attending in-person meetings can be challenging. High rates of use and the popularity of pregnancy content suggests Instagram as a possible platform for delivering gestational weight gain interventions. We assessed the logistics and acceptability of creating a private Instagram group and to obtain feedback on intervention posts. We conducted a 2-week study with pregnant women with pre-pregnancy overweight or obesity who use Instagram daily. Participants created a private Instagram account and followed other participants and a moderator who shared twice-daily posts about physical activity and healthy eating during pregnancy. Participants provided feedback through a follow-up survey and focus group/interviews. Engagement data was abstracted from Instagram. Participants (N = 11) were on average 26.3 (SD: 7.4) weeks gestation and 54% had obesity pre-pregnancy. All participants followed the moderator's account, 73% followed all other participants, participants engaged with 100% of study posts, 82% felt comfortable sharing in the group, and 73% would participate in a similar group if pregnant in the future. While participants felt the posts were visually attractive and included helpful information, they wanted more personalized content and felt reluctant to post photos they felt were not "Instagram worthy." Moderators should foster an environment in which participants feel comfortable posting unedited, authentic photos of their lives, perhaps by sharing personal photos that are relatable and represent their own imperfect lives. Results will inform further development and testing of an Instagram-delivered gestational weight gain intervention.

A Proposed Approach for Conducting Studies That Use Data From Social Media Platforms

The prominence of social media in contemporary society has extended significantly into the health care arena, where both patients and health care providers have used social media platforms to gather, communicate, learn, and share medical content and personal experience in real time. The medical literature has also seen an exponential increase in the number of studies that use data derived from social media coverage of various medical issues and topics. In this guide, we present a step-by-step framework for health care professionals and researchers to conduct studies that use data from social media platforms. We present 6 overarching steps: focus on framing a question that is appropriate for social media evaluation, identification of social media outlet and selection criteria of content, systematic data extraction, assessment of quality of content and sources of bias, analysis of data, and interpretation of study findings. Each step is illustrated with published examples.

Facebook usage, participation patterns, and social support from Facebook activity among smokers with mobility impairments

People with mobility impairments (MIs; use assistive devices to ambulate) have twice the smoking prevalence versus the general population. A Facebook intervention could improve reach to smokers with MIs, but use and patterns of use are unknown. The study examined: (a) Facebook use and relationship with Facebook-based social support and (b) whether Facebook use differs by motivation to quit smoking. Participants (N = 510; 56.3% female, mean age = 42.4 years) were recruited via a recruitment company to complete a one-time online survey assessing motivation to quit within 30 days, Facebook use (Facebook Activities Scale), reasons for use (Facebook Motives Scale), attitudes (Facebook Intensity Scale), and social support (Facebook Measure of Social Support). The vast majority said that Facebook is part of their daily routine (92.9%), 83% checked Facebook >once a day, and 69% spent >30 min/day on Facebook. Facebook was used to connect with similar others (68.4%), participate in groups (72.9%), decrease loneliness (69.2%), and obtain health information (62.5%); 88% said that they would join a Facebook program to help them quit smoking. A greater number of Facebook friends (rs = .18-.22, p < .001) and greater Facebook use (rs = .20 to rs = .59; p < .001) were correlated with greater perceived social and emotional support. Those motivated to quit posted more frequently (odds ratio [OR] = 1.56, 95% confidence interval [CI] = 1.10, 2.22) and were more likely to indicate that they would join a Facebook group for smoking cessation (OR = 4.15, 95% CI = 2.05, 8.38) than those not motivated. Facebook could circumvent disability and environmental barriers to accessing cessation among this health disparity population.

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.

Feasibility of a Digital Intervention to Promote Healthy Weight Management among Postpartum African American/Black Women

The study aim was to implement and evaluate the feasibility of a culturally informed (“BeFAB”) app for African American/Black women to address postpartum weight. Women (n = 136; mean age = 27.8 ± 5.4; mean BMI = 32.5 ± 4.3) were recruited from postpartum units, and randomly assigned to receive BeFAB (n = 65) or usual care (n = 71) for 12 weeks. App content included didactic lessons delivered via a virtual coach, app-based messages, goal setting and tracking, and edutainment videos. Feasibility outcomes included recruitment, retention and engagement, and self-reported acceptability. Behavioral (i.e., diet, physical activity), psychosocial (i.e., stress, coping, support, self-efficacy) and weight outcomes were also examined. Recruitment goals were met, but attrition was high, with 56% retention at 12 weeks. Approximately half of participants accessed the app and set a goal ≥one time, but <10% reported achieving a nutrition or activity goal. Among study completers, ≥60% found the app content at least somewhat helpful. Within-group changes for BeFAB among completers were found for increased moderate-to-vigorous physical activity and decreased fruit/vegetable intake and weight. Findings indicate initial feasibility of recruiting postpartum women to participate in a digital healthy body weight program but limited use, reflecting low acceptability and challenges in engagement and retention. Future research is needed on strategies to engage and retain participants in postpartum interventions.

What are Ophthalmology Patients Asking Online? An Analysis of the Eye Triage Subreddit

Importance

Ophthalmology patients are seeking medical advice on social media websites like Reddit, where users are able to post comments and discuss issues pertaining to different topics that are organized in ‘subreddits’. Understanding which issues are most pertinent will guide ophthalmic providers in delivering more effective patient education.

Methods

This cross-sectional study assessed a systematic sample of the first 22 posts and their top 3 comments from each month since January 27th, 2019, the subreddit’s creation. Information was gathered from reddit.com/r/eyetriage in October 2019 and analyzed in November 2019.

Main Outcomes

The posts were characterized by date and time, inclusion of an image, type, content, emotional tone, and number of upvotes and comments. The comments were categorized based on content, emotional tone, time of comment, and user background. Post and comment content codes were categorized in an iterative manner with differences resolved by author consensus. Categorical statistics were compiled.

Results

Two hundred posts and 456 comments were analyzed since the creation of r/eyetriage, a forum created exclusively for patients to seek advice from health-care professionals. Twenty-six (13%) of the total posts included an image. On average, comments received 1.76 ± 2.17 upvotes along with 4.50 ± 4.47 replies. The most common content codes among the posts were 42 (21.0%) seeking diagnoses, 23 (11.5%) surgical complications, and 13 (6.50%) alternative medication options. Eighty-two (41%) posts conveyed a clear emotional tone, most notably 11 (13.4%) with anxiety and 10 (12.2%) with worry. The top comments came from 165 (36.2%) self-identified patients, 151 (33.1%) optometrists, and 49 (10.8%) ophthalmologists. The top comment codes for replies included 158 (34.7%) with treatment advice, 70 (15.4%) with advice deferred to follow-up appointment with other health-care specialists, and 60 (13.2%) with sharing information.

Conclusions

Patients are asking ophthalmology-related questions on the Eye Triage subreddit, and they are more likely to receive information from other patients or optometrists than from self-identified ophthalmologists. When emotions were revealed, patients were often anxious and worried. Opportunities exist for ophthalmologists to take a more active role on this subreddit and help educate patients.