ArticleJMIR dermatology2026
Assessing Alopecia Areata Misinformation: Social Media Analysis.
Article in JMIR dermatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Background: Alopecia areata (AA) is an autoimmune, hair loss-inducing disease affecting individuals of all genders and ethnic backgrounds worldwide. As social media platforms and artificial intelligence chatbots increasingly influence patient behavior, individuals with AA may turn to these sources for treatment guidance. Objective: This study evaluated the accuracy of AA-related information on social media and assessed whether patients were exposed to misinformation that could hinder appropriate care. Influencers may recommend treatments applicable to alopecia broadly or promote therapies lacking medical benefit. Methods: YouTube and TikTok were searched using the hashtags #alopecia and #alopeciatreatment. Posts were selected based on hashtag relevance. Videos were categorized using standard AA treatment guidelines into (1) accurate and medical data-backed (aligned with guideline-supported treatments), (2) limited or anecdotal evidence (unverified treatments without clear misinformation), (3) misinformed and/or false (inaccurate or misleading claims), or (4) other (unrelated to alopecia management). Results: A total of 98 YouTube and 222 TikTok videos related to #alopecia and #alopeciatreatment were analyzed. Of the YouTube videos analyzed, 76% (n=75) were categorized as "other," 13% (n=13) as "accurate and medical data-backed," and 10% (n=10) as "limited or anecdotal evidence"; no videos were classified as "misinformed and/or false." Of the TikTok videos analyzed, 76% (n=170) were categorized as "other," 17% (n=38) as "accurate and medical data-backed," 5% (n=12) as "limited or anecdotal evidence," and 1% (n=2) as "misinformed and/or false." Among videos specifically discussing AA treatment, 56% of YouTube videos and 73%of TikTok videos were categorized as "accurate and medical data-backed." The difference in accurate vs limited or nonmedical YouTube content was statistically significant (P=.002), while misinformation prevalence between platforms was not significantly different (P=.15). Conclusions: Patients with AA are frequently exposed to generalized alopecia content on social media, which may not consistently offer disease-specific guidance. Health care professionals should help ensure that social media platforms and artificial intelligence tools are leveraged to promote accurate education and proactively combat misinformation surrounding AA treatment.
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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.