ReviewCurrent diabetes reports2018
Social Media and Obesity in Adults: a Review of Recent Research and Future Directions.
Review in Current diabetes reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 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
34 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Using Social Media to Understand Web-Based Social Factors Concerning Obesity: Systematic Review.JMIR public health and surveillance · 2022Pooled it
- Use and Effectiveness of Social-Media-Delivered Weight Loss Interventions among Teenagers and Young Adults: A Systematic Review.International journal of environmental research and public health · 2021Pooled it
- 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
- Participant Preferences to Inform the Development of Theory-Driven, Digitally Delivered Cooking Interventions Using the Behavior Change Wheel.Journal of nutrition education and behavior · 2025Article
- Can Mobile Health Applications, Social Media, and Telemedicine Assist with Obesity Treatment?Current obesity reports · 2025Review
- Exploring the Acceptability of the STOP Method for Addressing Weight Loss Misinformation on Social Media: An Interview Study.Obesity science & practice · 2025Article
- The past, present, and future of behavioral obesity treatment.International journal of obesity (2005) · 2025Review
- Best Practices for Designing and Testing Behavioral and Health Communication Interventions for Delivery in Private Facebook Groups: Tutorial.JMIR formative research · 2024Article
- The Relationship Between How Participants Articulate Their Goals and Accomplishments and Weight Loss Outcomes: Secondary Analysis of a Pilot of a Web-Based Weight Loss Intervention.JMIR mHealth and uHealth · 2023Article
- Social Media Use Among Parents and Women of Childbearing Age in the US.Preventing chronic disease · 2023Article
- Article
- Factors Associated with Cancer Message Believability: a Mixed Methods Study on Simulated Facebook Posts.Journal of cancer education : the official journal of the American Association for Cancer Education · 2022Article
- Application of McGuire's Model to Weight Management Messages: Measuring Persuasion of Facebook Posts in the Healthy Body, Healthy U Trial for Young Adults Attending University in the United States.International journal of environmental research and public health · 2022Article
- Engaging primary care patients with existing online tools for weight loss: A pilot trial.Obesity science & practice · 2022Article
- Video or text? Education through a social media website in hypertension.International journal of cardiology. Cardiovascular risk and prevention · 2022Article
- Predicting Participant Engagement in a Social Media-Delivered Lifestyle Intervention Using Microlevel Conversational Data: Secondary Analysis of Data From a Pilot Randomized Controlled Trial.JMIR formative research · 2022Article
- Misinformation About the Human Gut Microbiome in YouTube Videos: Cross-sectional Study.JMIR formative research · 2022Article
- A Facebook-Delivered Weight Loss Intervention Using Open Enrollment: Randomized Pilot Feasibility Trial.JMIR formative research · 2022Article
- A Smartphone-Based Self-management Intervention for Individuals With Bipolar Disorder (LiveWell): Empirical and Theoretical Framework, Intervention Design, and Study Protocol for a Randomized Controlled Trial.JMIR research protocols · 2022Article
- A theory-based video intervention to enhance communication and engagement in online health communities: two experiments.Health psychology and behavioral medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
purpose of reviewSocial media is widely used and has potential to connect adults with obesity with information and social support for weight loss and to deliver lifestyle interventions. The purpose of this review is to summarize recent observational and intervention research on social media and obesity. RECENT
findingsOnline patient communities for weight loss abound but may include misinformation. Systematic reviews and meta-analyses suggest that social media-delivered lifestyle interventions modestly impact weight, yet how social media was used and participant engagement varies widely. The rapidly changing social media landscape poses challenges for patients, clinicians, and researchers. Research is needed on how patients can establish supportive communities for weight loss and the role of clinicians in these communities. Emerging research on meaningful engagement in, and the efficacy and cost-effectiveness of, social media-delivered lifestyle interventions should provide insights into how to leverage social media to address the obesity epidemic.
Indexed as
Identifiers
29671135What 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.