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Updated: Oct 20, 2026

A New Technique for Quantitative Analysis of Hair Loss in Mice Using Grayscale Analysis
Published on: March 9, 2015
Cross-sectional evaluation of TikTok video quality on alopecia areata
Hilla Rosenberg1, Chaya Bracha Gordon1, Yael Hollander1
1Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva.
Abstract:
Alopecia areata (AA) is an autoimmune condition that results in hair loss, significantly impacting quality of life. As TikTok emerges as a major platform for health-related information, concerns about the spread of misinformation have arisen. This cross-sectional study aims to evaluate the quality, reliability, and understandability of "most liked" AA-related TikTok videos. Videos were categorized as healthcare providers (HP) or non-healthcare providers (NHP). Two reviewers independently assessed the videos, using validated tools - Patient Education Materials Assessment Tool for audiovisual content (PEMAT A/V), modified DISCERN (mDISCERN), Video Information and Quality Index (VIQI), Global Quality Scale (GQS), and AloCheck, a study-specific content-coverage tool. Among 93 included videos, only 26% were created by HPs, who scored significantly higher across all quality metrics: mDISCERN (3.0 vs. 1.5, p<0.01), GQS (3.5 vs. 1.5, p<0.01), VIQI (13.75 vs. 11.0, p<0.01), and PEMAT A/V (≥10: 66.7% vs. 26.1%, p<0.01). HPs focused on clinical aspects (87.5% vs. 40.6%, p<0.01), whereas NHPs emphasized psychological aspects, such as body image (37.5% vs. 63.8%, p=0.02). Findings reveal a gap between quality and user engagement, highlighting the risk that lower-quality information reaches a wide audience. Bridging this gap is essential to support the delivery of high-quality, reliable, and engaging health information to the public.