Assessing Alopecia Areata Misinformation: Social Media Analysis

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.

Authors

Institutions

Publication Details

Journal
JMIR Dermatology
Published
2026-07-23
DOI
https://doi.org/10.2196/90088
Primary Topic
Hair Growth and Disorders
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing Alopecia Areata Misinformation: Social Media Analysis

Roxana Daneshjou, Dawn H. Siegel, Ank A Agarwal, Aaron Fanous et al.
JMIR Dermatology
Hair Growth and Disorders
article

Assessing Alopecia Areata Misinformation: Social Media Analysis

Roxana Daneshjou, Dawn H. Siegel, Ank A Agarwal, Aaron Fanous, Shanika Francis
article en

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.

JMIR DermatologyVol. 9
Meharry Medical College (US), Stanford University (US)
Gender equality
Openalex Percentile: Top 6%
Hair Growth and Disorders
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.