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AI evaluation of Reddit reveals public curiosity in GLP-1 medicine for weight reduction and psychological well being advantages

In a latest research revealed within the journal Communications Medication, researchers in the USA of America (US) used giant language fashions (LLMs) to research over 391,000 distinctive discussions on Reddit, a social media platform, associated to glucagon-like peptide-1 (GLP-1) receptor agonists (GLP-1 RAs). The research revealed excessive curiosity in GLP-1 RAs, with discussions specializing in weight reduction experiences, unwanted side effects, entry points, and constructive psychological advantages, with principally neutral-to-positive sentiment.

AI evaluation of Reddit reveals public curiosity in GLP-1 medicine for weight reduction and psychological well being advantagesExamine: Utilizing giant language fashions to evaluate public perceptions round glucagon-like peptide-1 receptor agonists on social media. Picture Credit score: Caroline Ruda/  Shutterstock

Background

Greater than 38% of the world’s inhabitants is chubby or overweight, projected to succeed in 51% by 2035. Weight problems is understood to extend the chance of cardiometabolic ailments and all-cause mortality considerably. GLP-1 RAs are medicine that imitate the perform of pure GLP-1, a hormone within the gut that controls glucose metabolism and emotions of fullness. Whereas this class of medicine was initially permitted for sort 2 diabetes, it has lately gained international consideration for cardiovascular danger discount and weight reduction in sufferers with weight problems, regardless of the presence of diabetes. Nonetheless, public views on GLP-1 RAs, essential for therapy uptake and adherence, haven’t been completely explored.

Social media platforms like Reddit provide anonymized public conversations on well being matters, revealing real-world experiences typically missed in medical settings or trials. Whereas manually analyzing giant volumes of this knowledge is resource-intensive, its evaluation could be expedited utilizing synthetic intelligence methods akin to LLMs. Due to this fact, researchers within the current research employed LLMs to research over 390,000 Reddit discussions on GLP-1 RAs, figuring out matters akin to weight reduction, unwanted side effects, and considerations. They aimed to observe unwanted side effects, gauge public sentiment, and information future analysis and public well being initiatives utilizing the findings.

In regards to the research

Reddit hosts consumer discussions within the type of posts and feedback. It’s organized into publicly accessible, topic-specific communities referred to as “subreddits.” GLP-1 RA-related discussions have been curated by indexing Reddit content material based mostly on the generic and model names of GLP-1 RA medicine, together with semaglutide. The dataset included 391,461 distinctive discussions (principally since 2021) from 116,216 authors, with 71,982 posts and 319,479 feedback.

A beforehand described “subject modeling” method was employed for evaluation, and numerous instruments and algorithms have been employed. Discussions are reworked into numerical representations and clustered to determine matters. Every subject was labeled and grouped based mostly on similarities in dialogue content material. This method aimed to extract key themes and insights from the intensive discussions on GLP-1 RAs out there on Reddit. Moreover, this research employed a mannequin named “RoBERTa” (quick for Robustly Optimized Bidirectional Encoder Representations from Transformers Pre-training Method) to categorise sentiment. It used three chances (starting from 0 to 1) to find out the character of the sentiment inside the textual content, categorised as “unfavorable, impartial, or constructive sentiment.”

Outcomes and dialogue

About 97.1% of the discussions centered on GLP-1 RA drugs prescribed for weight reduction, akin to semaglutide, tirzepatide, and liraglutide, with “Ozempic” being essentially the most mentioned (41.4%), regardless of not being permitted by the US Meals and Drug Administration (FDA) for weight reduction. Solely 2.9% of discussions have been about GLP-1 RAs permitted solely for diabetes. The quantity of discussions surged considerably after 2022, following the FDA approval of “Wegovy.”

The mannequin recognized 168 dialogue matters, indicating excessive public curiosity, with a deal with experiences with the medicine for weight reduction. The matters included drug efficacy, comparability to different therapies, urge for food affect, and unwanted side effects. Nausea was discovered to be essentially the most frequent facet impact, adopted by vomiting, injection web site points, constipation, pancreatitis, and gastroparesis. Additional, entry points, market shortages, insurance coverage protection, and the ethics of off-label use have been discovered to be mentioned. Constructive results on motivation and psychological well being and the worth of avoiding bariatric surgical procedure have been additionally mentioned. Subjects have been clustered into 33 teams, reflecting themes akin to comparisons with different therapies, unwanted side effects, entry considerations, and psychological advantages. Sentiment evaluation revealed that 31.8% of discussions have been unfavorable, 50.1% have been impartial, and 17.4% have been constructive. Notably, two matters have been excluded as a result of unlawful content material associated to buying illicit substances.

Scatter plot showing a 2D-projection of all discussion embeddings, where each point represents a discussion. The overlying color represents the associated group of that discussion based on the topic modeling. The x- and y-axes represent the two axes (Feature 1, Feature 2) onto which embeddings were dimensionally reduced using Uniform Manifold Approximation and Projection for visualization purposes.Scatter plot exhibiting a 2D-projection of all dialogue embeddings, the place every level represents a dialogue. The overlying colour represents the related group of that dialogue based mostly on the subject modeling. The x- and y-axes characterize the 2 axes (Function 1, Function 2) onto which embeddings have been dimensionally lowered utilizing Uniform Manifold Approximation and Projection for visualization functions.

The research is strengthened by its large-scale AI-based evaluation of social media discussions to uncover public perceptions and experiences with medicine, providing insights past conventional medical analysis. Nonetheless, the research is restricted by potential mislabeling as a result of spelling errors, incapacity to confirm reported unwanted side effects, restricted generalizability, and suboptimal basic process benchmarks for LLM.

Conclusion

In conclusion, the research analyzed large-scale GLP-1 RA-related discussions on social media utilizing LLMs. The findings reveal discussions centered on weight reduction experiences, facet impact comparisons, entry points, and constructive psychological advantages. This means excessive public curiosity in GLP-1 RAs and highlights priorities for medical and coverage communities, together with monitoring unwanted side effects, addressing entry limitations, and acknowledging each the bodily and psychological advantages of those medicine.

Journal reference:

  • Utilizing giant language fashions to evaluate public perceptions round glucagon-like peptide-1 receptor agonists on social media. Somani, S. et al. Communications Medication, 4, 137 (2024), DOI: 10.1038/s43856-024-00566-z, https://www.nature.com/articles/s43856-024-00566-z

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