ArticleBMC public health2025
Critical discourse analysis of social media advertisements for GLP-1 receptor agonist weight loss drugs: implications for public perceptions and health communication.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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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
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Who cites it
6 citing papers in PubMed.
- Seeing Beyond GLP-1: A Systems View of Sustainable Obesity Care.Journal of human nutrition and dietetics : the official journal of the British Dietetic Association · 2026Review
- Exploring Weight Loss Medication Discourse: Mixed Methods Analysis of US-Based Facebook Posts.JMIR infodemiology · 2026Article
- Psychiatric Adverse Events and Administration Challenges Associated with GLP-1 Receptor Agonists for Weight Loss: A Real-World Analysis.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Topic and Sentiment Trends in Semaglutide Discussions on X: Subpopulation-Based Longitudinal Analysis.Online journal of public health informatics · 2026Article
- Understanding obesity treatment choices: a mixed-methods study of patient preferences and shared decision-making.Translational behavioral medicine · 2026Article
- Beyond Weight Loss: GLP-1 Usage and Appetite Regulation in the Context of Eating Disorders and Psychosocial Processes.Nutrients · 2025Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study conducts a critical discourse analysis (CDA) of social media advertisements (ads) for Glucagon-like peptide-1 receptor agonist (GLP-1 RAs) weight loss drugs to examine their linguistic features, discursive practices, and social implications, aiming to explore how advertising strategies may shape public perceptions and consumer considerations. Data collection focused on Facebook and Instagram, targeting ads related to FDA-approved GLP-1 RAs weight loss drugs from February 2023 to February 2024. Ads were collected using specific keyword searches. Inclusion criteria focused on ads explicitly related to the three GLP-1 RAs weight loss drugs, while exclusion criteria removed irrelevant, non-English, duplicate, or incomprehensible ads. Thematic analysis was conducted to identify recurring themes. Fairclough's CDA model was used to analyse the 90 ads. Thematic analysis identified four key themes including "Health and Safety", "Consultation and Support", "Ease and Affordability", and "Emotional and Psychological Impact". These themes highlight the emphasis on medical credibility, accessibility through telehealth, affordability, and emotional benefits. The ads strategically use medical authority and emotional appeals, seemingly to build trust and persuade consumers. The focus on telehealth aligns with the growing demand for remote healthcare solutions, while the emphasis on affordability and ease of use addresses common barriers to accessing weight loss treatments. This research provides new insights into the discursive strategies of pharmaceutical advertising, distinguishing it as a unique contribution to the field. The study underlines the need for balanced health communication that accurately represents the benefits and risks of weight loss drugs. It recommends stricter regulatory guidelines to ensure transparency and prevent exaggerated claims. Additionally, public health campaigns should educate consumers on comprehensive weight management, integrating medication with lifestyle changes. Moreover, stakeholders can develop better health communication strategies and regulatory policies to enhance public health outcomes by understanding the narratives in these ads.
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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.