Trial reportJournal of medical Internet research2014
Click "like" to change your behavior: a mixed methods study of college students' exposure to and engagement with Facebook content designed for weight loss.
Trial report in Journal of medical Internet research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 6 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
57 citing papers in PubMed, 6 syntheses or guidelines pooled it, 112 citations in OpenAlex.
- Elements Influencing User Engagement in Social Media Posts on Lifestyle Risk Factors: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Occupational Health Applied Infodemiological Studies of Nutritional Diseases and Disorders: Scoping Review with Meta-Analysis.Nutrients · 2023Pooled it
- The Impact of Social Media Interventions on Weight Reduction and Physical Activity Improvement Among Healthy Adults: Systematic Review.Journal of medical Internet research · 2023Pooled it
- Using Social Media to Understand Web-Based Social Factors Concerning Obesity: Systematic Review.JMIR public health and surveillance · 2022Pooled it
- Social media use for nutrition outcomes in young adults: a mixed-methods systematic review.The international journal of behavioral nutrition and physical activity · 2018Pooled it
- Peer-Based Social Media Features in Behavior Change Interventions: Systematic Review.Journal of medical Internet research · 2018Pooled it
- Trial
- Factors influencing engagement and dietary behaviour change of mothers and their children in a blog-delivered healthy eating intervention: a process evaluation of a randomised controlled trial.Public health nutrition · 2021Trial
- Social Network Analysis of the Effects of a Social Media-Based Weight Loss Intervention Targeting Adults of Low Socioeconomic Status: Single-Arm Intervention Trial.Journal of medical Internet research · 2021Trial
- Improving Calcium Knowledge and Intake in Young Adults Via Social Media and Text Messages: Randomized Controlled Trial.JMIR mHealth and uHealth · 2020Trial
- Adapting evidence-based behavioral weight loss programs for emerging adults: A pilot randomized controlled trial.Journal of health psychology · 2019Trial
- Engagement of young adult cancer survivors within a Facebook-based physical activity intervention.Translational behavioral medicine · 2017Trial
- Personalized Mobile Health Intervention for Health and Weight Loss in Postpartum Women Receiving Women, Infants, and Children Benefit: A Randomized Controlled Pilot Study.Journal of women's health (2002) · 2017Trial
- Face-to-Face and Online Networks: College Students' Experiences in a Weight-Loss Trial.Journal of health communication · 2017Trial
- Using social and mobile tools for weight loss in overweight and obese young adults (Project SMART): a 2 year, parallel-group, randomised, controlled trial.The lancet. Diabetes & endocrinology · 2016Trial
- A Technology-Mediated Behavioral Weight Gain Prevention Intervention for College Students: Controlled, Quasi-Experimental Study.Journal of medical Internet research · 2016Trial
- Process evaluation of TXT2BFiT: a multi-component mHealth randomised controlled trial to prevent weight gain in young adults.The international journal of behavioral nutrition and physical activity · 2016Trial
- Clinical trial management of participant recruitment, enrollment, engagement, and retention in the SMART study using a Marketing and Information Technology (MARKIT) model.Contemporary clinical trials · 2015Trial
- Evaluation of a Canadian social media platform for communicating perinatal health information during a pandemic.PLOS digital health · 2025Article
- "The potential of social media in health promotion beyond creating awareness: an integrative review".BMC public health · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundOverweight or obesity is prevalent among college students and many gain weight during this time. Traditional face-to-face weight loss interventions have not worked well in this population. Facebook is an attractive tool for delivering weight loss interventions for college students because of its popularity, potential to deliver strategies found in successful weight loss interventions, and ability to support ongoing adaptation of intervention content.
objectiveThe objective of this study was to describe participant exposure to a Facebook page designed to deliver content to overweight/obese college students in a weight loss randomized controlled trial (N=404) and examine participant engagement with behavior change campaigns for weight loss delivered via Facebook.
methodsThe basis of the intervention campaign model were 5 self-regulatory techniques: intention formation, action planning, feedback, goal review, and self-monitoring. Participants were encouraged to engage their existing social network to meet their weight loss goals. A health coach moderated the page and modified content based on usage patterns and user feedback. Quantitative analyses were conducted at the Facebook post- and participant-level of analysis. Participant engagement was quantified by Facebook post type (eg, status update) and interaction (eg, like) and stratified by weight loss campaign (sequenced vs nonsequenced). A subset of participants were interviewed to evaluate the presence of passive online engagement or "lurking."
resultsThe health coach posted 1816 unique messages to the study's Facebook page over 21 months, averaging 3.45 posts per day (SD 1.96, range 1-13). In all, 72.96% (1325/1816) of the posts were interacted with at least once (eg, liked). Of these, approximately 24.75% (328/1325) had 1-2 interactions, 23.39% (310/1325) had 3-5 interactions, 25.13% (333/1325) had 6-8 interactions, and 41 posts had 20 or more interactions (3.09%, 41/1325). There was significant variability among quantifiable (ie, visible) engagement. Of 199 participants in the final intervention sample, 32 (16.1%) were highly active users and 62 (31.2%) never visibly engaged with the intervention on Facebook. Polls were the most popular type of post followed by photos, with 97.5% (79/81) and 80.3% (386/481) interacted with at least once. Participants visibly engaged less with posts over time (partial r=-.33; P<.001). Approximately 40% of the participants interviewed (12/29, 41%) reported passively engaging with the Facebook posts by reading but not visibly interacting with them.
conclusionsFacebook can be used to remotely deliver weight loss intervention content to college students with the help of a health coach who can iteratively tailor content and interact with participants. However, visible engagement with the study's Facebook page was highly variable and declined over time. Whether the level of observed engagement is meaningful in terms of influencing changes in weight behaviors and outcomes will be evaluated at the completion of the overall study.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.