Evaluating the quality of TikTok videos on alopecia areata: A cross-sectional study

Evaluating the quality of TikTok videos on alopecia areata: A cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Evaluating the quality of TikTok videos on alopecia areata: A cross-sectional study Hilla Rosenberg, Chaya Bracha Gordon, Yael Hollander, Reut Rotem, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7022768/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction Alopecia areata (AA) is an autoimmune condition that results in hair loss and affects quality of life. With TikTok emerging as a major platform for health-related information, concerns about the spread of misinformation have arisen. This study evaluates the quality of AA content on TikTok, aiming to promote accurate, evidence-based content. Methods A cross-sectional study was conducted to evaluate the quality and accuracy of “most liked” AA-related content on TikTok. Videos were categorized as healthcare providers (HP) or non-healthcare providers (NHP). Two reviewers independently assessed the videos, using validated tools - PEMAT, mDISCERN, VIQI, GQS, and a novel tool developed for this study, 'AloCheck'. Results Of 179 videos reviewed, 93 met the inclusion criteria and only 26% were created by HPs. These videos scored 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 more on clinical aspects (87.5% vs. 40.6%, p<0.01), while NHPs emphasized body image (37.5% vs 63.8%, P=0.02). Conclusion Findings reveal a gap between quality and user engagement, highlighting the risk of disseminating misleading information. Bridging this gap is essential to support the delivery of accurate and engaging health information to the public. Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Alopecia Areata adolescents social media health education Figures Figure 1 INTRODUCTION Alopecia areata (AA) is an inflammatory, nonscarring type of hair loss in which cytotoxic CD8 + NKG2D + and Th17 T cells target exposed follicle autoantigens in bulge and hair bulb matrix stem cells 1 . Up to 2% of the world’s population experience AA in their lifetime with higher prevalence in children than adults 2 , 3 It is estimated that up to nearly half of patients experience their first episode of hair loss by the age of 20, and 20% of all cases occurred during infancy 4 . The etiology of the specific trigger remains unclear, and the disease has a spectrum of clinical presentations, including AA, alopecia totalis (total scalp hair loss) and alopecia universalis (total body hair loss, including eyebrows and eyelashes 5 . Quality of life can be affected in individuals with AA, who often face increased bullying, social isolation, higher rates of depression and anxiety, which can improve with appropriate treatment 3 , 6 – 9 Given the significant burden associated with AA and the fact that many patients fall within TikTok’s primary demographic, individuals with AA often turn to social media for information and support. TikTok is a platform with over 1.1 billion users, with a primary user base of adolescents, and has evolved beyond its original focus on entertainment to include a growing body of health-related content 10 – 14 . However, the quality and accuracy of the content varies widely, posing a risk of misinformation with associated public health implications. In comparison to other platforms, such as BiliBili and YouTube, TikTok has been seen to score lower across multiple evaluation tools in assessments of video quality, for example, in related to gastrointestinal bleeding education 15 .There has been minimal research on the quality of AA content on social media, although there is substantial research focusing on the treatment, epidemiology, and pathophysiology of AA 16 , 17 . In this analysis, we aim to evaluate the quality and accuracy of TikTok videos related to AA with the goal of determining the reliability of this content for patient education. MATERIALS and METHODS A descriptive cross-sectional study was conducted to evaluate the quality and accuracy of AA-related content on TikTok. To minimize algorithmic bias, a new account was created for the purpose of the study. Videos were retrieved according to predefined hashtags: #AlopeciaAreata and #AlopeciaAreata Dermatology and filtered by the “most liked” criterion, and a total of 179 videos were reviewed. From these, the first 93 videos that matched with the inclusion criteria were selected (Fig 1). Exclusion criteria included non-English languages, lack of audio, content not related to AA, or duplication. Videos were categorized by 1. content type- educational, promotional or storytelling, and 2. by creator type- healthcare provider (HP), including certified dermatologists and other medical professionals, or non-healthcare provider (NHP), such as patients and influencers. Two independent reviewers assessed the videos using standardized, validated and novel assessment tool. The requirement for informed consent was waived by the local Ethics Committee of SUMC, Israel since the data were publicly accessible on social media and no identifiable information is included in the report. All independent reviewers who participated in the study provided informed verbal consent via videochat prior to their involvement. This study adhered to the Terms & Conditions for data access and use of TikTok. Only publicly available content was analyzed. Video Characteristics For each video, we recorded key metrics including follower count, duration, upload date, tone (positive, negative or neutral), purpose and engagement metrics such as comments, likes, and shares. Assessment Tools We utilized the Patient Education Materials Assessment Tool for Audiovisual Content (PEMAT A/V) which contains seventeen sections to evaluate understandability and actionability of the content by rating it on a binary scale. A higher total score indicates high understandability, with a score below 75% (sum < 10) considered poorly understandable or actionable. The Modified DISCERN (mDISCERN) tool was used to assess the quality and comprehensiveness of the information presented in the video. The tool comprises five sections, each assessed on a binary scale (yes/no), with 1 point awarded for a 'yes' response and 0 points for a 'no' response. The sections assessed include: (1) The video is clear; (2) Sourced of information used are reliable; (3) Information is balanced and unbiased; (4) Additional sources of information are listed; (5) Areas of uncertainty are mentioned. A score above three indicates greater reliability. The Global Quality Scale (GQS) was used to evaluate overall quality, flow, and utility of the video. GQS rates videos on a scale ranging from one to five, when higher scores indicate higher quality of content. The Video Information and Quality Index (VIQI) tool was used to evaluate specific metrics such as flow, accuracy, and depth of content. For this study, we developed a unique tool, which we named “AloCheck”, to comprehensively evaluate key aspects of AA in video content. The parameters we focused on fell into two main categories: (1) clinical aspects, including pathophysiology, clinical presentation and treatment; and (2) psychological aspects, including body image. The tool uses a binary score, “1” is given if a criterion is mentioned in the video, and a score of “0” if not. Statistical Analysis Categorical data were expressed as percentages, while continuous data were described using either mean and standard deviation (SD) or median and interquartile range (IQR), depending on the data distribution. The Chi-square test or Fisher’s exact test was applied to compare categorical variables. For continuous variables, comparisons were made using either the student’s T-test or the Mann-Whitney U test, as appropriate. A p-value of less than 0.05 was considered statistically significant. Data analysis was conducted using IBM SPSS Statistics, version 28 (IBM Corp., Armonk, NY). RESULTS Of 179 videos reviewed, 93 videos met the inclusion criteria and were selected for analysis (Fig. 1 ). Videographic Characteristics and Engagement Metrics From the videos that met the inclusion criteria, 26% (n = 24) were created by HPs and 74% (n = 69), were created by NHPs. The median duration of NHP videos was significantly longer than HP videos (52 sec vs 32 sec, P < 0.01). NHP videos demonstrated higher median numbers of comments and likes (P < 0.01, P = 0.05). In terms of content, all HP videos were educational with a neutral tone, whereas NHP videos contained more personal anecdotes and a positive tone (P < 0.001 and P < 0.01 respectively) (Table I). Table I - Videographic characteristics and engagement metrics Criteria Descriptive Statistics Total videos (N = 93) Healthcare providers (HP), (N = 24) Nonhealthcare providers (NHP), (N = 69) P Value Length (S) Median, IQR 44.30 (24.45–82.45) 32.00 (20.00–44.00) 53.00 (27.00 -113.00) < 0.01 Comments Median, IQR 0.05 (0.02–0.29) 0.02 (0.00-0.16) 0.08 (0.02–0.28) < 0.01 Likes (K) Median, IQR 1.30 (0.27–14.70) 0.45 (0.14–6.28) 2.40 (0.40–16.80) 0.05 Shares Median, IQR 0.10 (0.01–0.59) 0.08 (0.02–0.91) 0.10 (0.01–0.52) 0.98 Followers (K) Median, IQR 56.10 (5.80–226.00) 144.60 (15.9–47.6) 47.6 (3.30-150.50) 0.02 Purpose Educational 24 (100.0%) 28 (40.6%) < .001 Other (promotional, storytelling) 0 (0.0%) 41 (59.4%) Tone of video Positive 0 (0.0%) 28 (43.1%) < 0.01 Negative 0 (0.0%) 7 (10.8%) Natural 24 (100.0%) 30 (46.2%) Quality Assessment Metrics Healthcare professional videos scored significantly higher on all quality metrics. The median mDISCERN score (3.0 vs. 1.5, p < 0.01), with 70.8% of healthcare videos receiving a score ≥ 3 compared to 7.2% of non-healthcare videos (p < 0.01). Similarly, GQS score (3.5 [IQR3.00-4.00] vs. 1.5 [IQR0.5-2.25], p < 0.01) with 79.2% of healthcare videos scoring ≥ 3 vs. 14.5% (p < 0.01).VIQI scores were markedly higher across all subcategories, with a total VIQI score of 13.75 [IQR13.0-15.0] vs 11.0 [IQR9.00-12.00], (p < 0.01). PEMAT A/V tool also exposed greater understandability and actionability in the HP group and the number of videos achieving an overall PMAT ≥ 10 was significantly higher in the HP videos (66.7% vs. 26.1%, p < 0.01). (Table II) Table II – Quality assessment tools; mDISCERN, GQS, VIQI, and PEMAT A/V Quality assessment tool Descriptive Statistics Total videos (N = 93) Healthcare providers (HP), (N = 24) Nonhealthcare providers (NHP), (N = 69) P Value mDISCERN Score Median, IQR 2.0 (1.0-2.5) 3.0 (2.5-3.0) 1.5 (1.0–2.0) = 3 N(%) 22 (23.7%) 17 (70.8%) 5 (7.2%) < 0.01 GQS Score Median, IQR 2.0 (0.5-3.0) 3.5 (3.0–4.0) 1.5 (0.5–2.25) = 3 N (%) 29 (31.2%) 19 (79.2%) 10 (14.5%) < 0.01 VIQI1 Median, IQR 3.0 (2.5-4.0) 5.0 (4.0–5.0) 3.0 (2.0–4.0) < 0.01 VIQI2 Median, IQR 3.0 (2.0–4.0) 5.0 (4.0–5.0) 3.0 (2.0–3.0) < 0.01 VIQI3 Median, IQR 1.0 (1.0–2.0) 2.0 (1.0–2.0) 1.0 (1.0–2.0) < 0.01 VIQI4 Median, IQR 3.0 (2.0–4.0) 4.0 (4.0–5.0) 3.0 (2.0–3.0) < 0.01 SUMVIQI Median, IQR 11.5 (9.5–13.5) 13.75 (13.0–15.0) 11.0 (9.0–12.0) < 0.01 PEMAT A/V Understandability Median, IQR 8.0 (6.0–9.0) 9.0 (7.25-10.0) 7.0 (5.0–8.0) = 10.0 (75% PERCENTILE) N (%) 34 (36.6%) 16 (66.7%) 18 (26.1%) < 0.01 Novel tool Score Analysis HPs were significantly more likely to address pathophysiology or mechanisms of disease compared to non–health professional (NHP) videos (87.5% vs. 40.6%, p < 0.01).NHP videos were more likely to address subjects concerning body image (63.8% vs. 37.5%, p = 0.02). No significant differences were observed regarding addressing clinical presentation (P = 0.35) or treatment (P = 0.25). (Table III). Table III - Novel Alopecia Areata Assessment Score System (AloCheck) Criteria Descriptive Statistics Total videos (N = 93) Healthcare providers (HP), (N = 24) Nonhealthcare providers (NHP), (N = 69) P Value Pathophysiology and Mechanism of the disease N (%) 49 (52.7%) 21 (87.5%) 28 (40.6%) < 0.01 Clinical Presentation N (%) 80 (86.0%) 22 (91.7%) 58 (84.1%) 0.35 Treatment N (%) 65 (69.9%) 19 (79.2%) 46 (66.7%) 0.25 Body image N (%) 53 (57.0%) 9 (37.5%) 44 (63.8%) 0.02 SUMPTPAT Median, IQR 3 (2.0–3.0) 17 (70.8%) 39 (56.5%) 0.22 DISCUSSION Originally designed for entertainment, TikTok quickly evolved into a platform for information exchange, including health-related topics 13 . However, the lack of regulations raises concerns about the reliability and accuracy of content. NHP users or “skinfluencers” can disseminate inaccurate information and potentially mislead viewers seeking guidance about the causes and management of AA. In today’s digital era, being aware of the quality of information on social media platforms such as TikTok is crucial. The platform has the power to shape public perceptions of disease. This is especially relevant for conditions like AA, which can have a profound and lasting psychosocial impact, particularly in younger individuals, highlighting the need for accurate, and evidence-based content 7 . To assess AA content on TikTok, we utilized several validated assessment tools, including PEMAT A\V, mDISCERN, VIQI, GQS and a novel evaluation tool “AloCheck”. Across all evaluation tools, HP videos consistently outperformed those by NHPs, with higher mDISCERN and GQS scores indicating greater reliability and content quality, and higher PEMAT A/V and VIQI scores reflecting improved flow, accuracy, and visual presentation. However, HP videos fell behind in engagement metrics compared to NHP videos, receiving less likes and comments while content created by NHPs tended to be more popular among users. This gap suggests that while evidence-based content exists on the platform, it may not be effectively reaching users. This pattern is not unique to alopecia areata and has been observed across a range of medical conditions. Studies on acne-related content have demonstrated that TikTok content frequently lacks reliability and rarely incorporates evidence-based information 13 . Similarly, more than half of TikTok videos related to psoriasis were rated as low quality yet often received higher engagement than higher-quality content produced by HPs 18 . Comparably, in the context of type 1 diabetes, content generated by non–health professionals were found to be of low reliability and quality, while approximately 50% of TikTok videos on attention-deficit/hyperactivity disorder (ADHD) were identified as misleading or inaccurate, particularly those created by NHPs 19 , 20 . This discrepancy, where content produced by HPs is consistently of higher quality but receives significantly less engagement than that from NHPs, raises important questions about the accessibility of quality medical content on TikTok. Our analysis showed that HP content focused on clinical concepts and pathophysiology of AA while NHP content focused on psychosocial topics such as body image or personal narratives. The average user on TikTok is typically not seeking in-depth medical explanations, but rather gravitates to emotionally compelling, humorous, or relatable content, factors that encourage viewer engagement 21 . This highlights the need for collaboration between HP and NHP content creators. By enhancing the appeal of evidence-based content we could bridge the current gap and potentially reduce the spread of misinformation ultimately guiding people to access care that is effective and safe. To our knowledge, this is the first comprehensive study with multiple assessment tools utilized to evaluate AA-related content on TikTok. Moreover, we developed a novel tool to assess the quality and accuracy of the videos. However, this study presents certain limitations. We selected videos using the hashtags #AlopeciaAreata and #AlopeciaAreataDermatology, filtered by the “most liked” criterion to capture the most widely engaged content. It is possible that other relevant hashtags were not included in our analysis. Furthermore, although video evaluation was conducted independently by two reviewers to reduce bias, the assessment remains subject to reviewer interpretation. Of note, our analysis focused on the “most liked” videos at a single point in time to better understand the quality of content that users are actively viewing and engaging with. However, this approach may not fully capture the entire spectrum of available content, as it excludes less popular videos and does not account for changes over time, leaving room for temporal bias in our results. It is important to recognize that TikTok is a rapidly evolving platform with a dynamic interface, where new content is uploaded daily and trending topics and creators shift frequently. Longitudinal research that tracks changes in content quality over time could provide deeper insights into digital health communication in dermatology and other fields. Moreover, we had an English language-only cohort, which limited the geographic and linguistic diversity of the sample and may have introduced geographic and cultural bias. Additionally, the ALO-TRACE tool developed for this study has not yet undergone formal psychometric validation or pilot testing. While it was constructed through expert consensus to address both clinical and social dimensions of vitiligo content, further research is needed to establish its validity and reliability. Future studies should aim to refine and validate the tool across broader samples and dermatological conditions. In today’s digital era TikTok plays a major role in shaping public health knowledge due to its simple and accessible interface. However, due to the platforms’ unregulated nature, concerns about misinformation emerge. Promoting collaboration between clinicians and NHPs in content creation may help address this issue by encouraging the dissemination of evidence-based information. Such partnerships have the potential to reduce misinformation, enhance the quality of online health content, and ultimately influence clinical outcomes by making accurate, high-quality information more accessible to the public. Declarations Declaration of interest: The authors declare that they have nothing to disclose and that they have no financial or non-financial conflict of interest. Disclosure of interests The authors report no conflict of interest. Author Contribution Writing (original draft), Writing (review and editing), Formal analysis [H.R]Visualization, Writing (review and editing) [C.B.G]Investigation, Visualization [Y.H] Data curation, Formal analysis [R.T]Project administration, Writing (review and editing), Supervision, Methodology, Validation, Visualization [A.H] Data Availability All data is available upon request from the authorsCorresponding author: Prof. Amir HorevEmail address: [email protected] References Fukuyama, M., Ito, T. & Ohyama, M. Alopecia areata: Current understanding of the pathophysiology and update on therapeutic approaches, featuring the Japanese Dermatological Association guidelines. J Dermatol 49 , 19–36 (2022). Barton, V. R., Toussi, A., Awasthi, S. & Kiuru, M. Treatment of pediatric alopecia areata: A systematic review. J Am Acad Dermatol 86 , 1318–1334 (2022). Prendke, M. et al. Quality of life in children and adolescents with alopecia areata—A systematic review. Journal of the European Academy of Dermatology and Venereology 37 , 1521–1534 (2023). Waśkiel‐Burnat, A. et al. Therapeutic management in paediatric alopecia areata: A systematic review. Journal of the European Academy of Dermatology and Venereology 35 , 1299–1308 (2021). What is alopecia areata? Pediatr Dermatol 42 , 43–44 (2025). Piraccini, B. M. et al. Scalp hair regrowth is associated with improvements in health-related quality of life and psychological symptoms in patients with severe alopecia areata: results from two randomized controlled trials. Journal of Dermatological Treatment 34 , (2023). Cruz, S., Lei, D. K., Carr, H. & Rosenblatt, A. The psychosocial impacts of vitiligo, psoriasis, and alopecia areata on pediatric patients. Dermatol Online J 29 , (2023). Tan, I. J. & Jafferany, M. Psychosocial impact of alopecia areata in paediatric and adolescent populations: A systematic review. J Paediatr Child Health 60 , 778–782 (2024). van Dalen, M., Muller, K. S., Kasperkovitz-Oosterloo, J. M., Okkerse, J. M. E. & Pasmans, S. G. M. A. Anxiety, depression, and quality of life in children and adults with alopecia areata: A systematic review and meta-analysis. Front Med (Lausanne) 9 , (2022). Hyperconnected: children and adolescents on social media. The TikTok phenomenon. Arch Argent Pediatr 121 , (2023). Suarez-Lledo, V. & Alvarez-Galvez, J. Prevalence of Health Misinformation on Social Media: Systematic Review. J Med Internet Res 23 , e17187 (2021). O’Sullivan, N. J., Nason, G., Manecksha, R. P. & O’Kelly, F. The unintentional spread of misinformation on ‘TikTok’; A paediatric urological perspective. J Pediatr Urol 18 , 371–375 (2022). Iyengar, L., Saldanha, S. & Chong, A. H. #Acne: A Thematic Qualitative Analysis of Acne Content on TikTok. Australasian Journal of Dermatology (2025) doi:10.1111/ajd.14433. Zheng, D. X., Mulligan, K. M. & Scott, J. F. TikTok and dermatology: An opportunity for public health engagement. J Am Acad Dermatol 85 , e25–e26 (2021). Wang, J. et al. Assessing the content and quality of GI bleeding information on Bilibili, TikTok, and YouTube: a cross-sectional study. Sci Rep 15 , 14856 (2025). Gabay, S. I., Zlakishvili, B. & Horev, A. A Bibliometric Analysis of Alopecia Areata Literature over the Past 50 Years. Acta Dermatovenerol Croat 32 , 17–25 (2024). Andre, N. et al. Hematological ratios as an indicator of severity in alopecia areata: A retrospective nationwide study. PLoS One 19 , e0314600 (2024). Aghajani, M. J. & Aghajani, R. TikTok and #psoriasis: A cross‐sectional study of content quality. Australasian Journal of Dermatology 64 , (2023). Vasistha, S., Kanchibhatla, A., Blanchette, J. E., Rieke, J. & Hughes, A. S. The Sugar-Coated Truth: The Quality of Diabetes Health Information on TikTok. Clinical Diabetes 43 , 53–58 (2025). Yeung, A., Ng, E. & Abi-Jaoude, E. TikTok and Attention-Deficit/Hyperactivity Disorder: A Cross-Sectional Study of Social Media Content Quality. The Canadian Journal of Psychiatry 67 , 899–906 (2022). Anderer, S. Patients Are Turning to TikTok for Health Information—Here’s What Clinicians Need to Know. JAMA 331 , 1262 (2024). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7022768","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":484742899,"identity":"0f208318-0cfe-456b-9c4c-e10dbaff148a","order_by":0,"name":"Hilla Rosenberg","email":"","orcid":"","institution":"Ben-Gurion University of the Negev","correspondingAuthor":false,"prefix":"","firstName":"Hilla","middleName":"","lastName":"Rosenberg","suffix":""},{"id":484742900,"identity":"51166f34-1f0b-4e88-955f-bc76b6cfa81d","order_by":1,"name":"Chaya Bracha Gordon","email":"","orcid":"","institution":"Ben-Gurion University of the Negev","correspondingAuthor":false,"prefix":"","firstName":"Chaya","middleName":"Bracha","lastName":"Gordon","suffix":""},{"id":484742901,"identity":"51daa64e-defb-4b25-80f0-c1a8b9762247","order_by":2,"name":"Yael Hollander","email":"","orcid":"","institution":"Ben-Gurion University of the Negev","correspondingAuthor":false,"prefix":"","firstName":"Yael","middleName":"","lastName":"Hollander","suffix":""},{"id":484742902,"identity":"77dd60c5-c8ee-4883-a541-88e19352f258","order_by":3,"name":"Reut Rotem","email":"","orcid":"","institution":"Cork University Maternity Hospital","correspondingAuthor":false,"prefix":"","firstName":"Reut","middleName":"","lastName":"Rotem","suffix":""},{"id":484742903,"identity":"9bf74c89-13fa-43e6-824d-51dacbf3f6c4","order_by":4,"name":"Amir Horev","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtUlEQVRIiWNgGAWjYBACAzBZYQMkGBsPkKDlTBpISwMJWhjbDoM5xGkxZ+99+JjnzHm7te2HgbbU2EQT1GLZc9zYmKfidvK2M4lALcfSchsIOuxGGpvkjDO3k80OALUwNhwmSgv7z5lt55LNzj8kXgsbw8e2A3ZmN4i25cwxZokPZ5ITzG4AbUkgyi/H2xg/JFTY2ZudT3/44EONDWEtMJAIVplArHIQsCdF8SgYBaNgFIwwAAATUEmQqr7kPQAAAABJRU5ErkJggg==","orcid":"","institution":"Pediatric Dermatology Service, Soroka University Medical Center","correspondingAuthor":true,"prefix":"","firstName":"Amir","middleName":"","lastName":"Horev","suffix":""}],"badges":[],"createdAt":"2025-07-01 17:53:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7022768/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7022768/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87033124,"identity":"66f44ee9-691c-4852-ad83-be64e0d21c12","added_by":"auto","created_at":"2025-07-18 13:03:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":33682,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eFlowchart of study design and video analysis process\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\u003cbr\u003e\n\u003c/strong\u003e\u003cem\u003eFlowchart displaying the methodology of video selection and evaluation in this cross-sectional analysis\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7022768/v1/2a981fa4a6f2f554e0c67a23.png"},{"id":109761905,"identity":"563d55ef-bce7-437c-b558-f0a78ba1267b","added_by":"auto","created_at":"2026-05-22 07:30:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":263014,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7022768/v1/4f217140-96ba-4a7e-b67e-becb36f673d4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eEvaluating the quality of TikTok videos on alopecia areata: A cross-sectional study\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAlopecia areata (AA) is an inflammatory, nonscarring type of hair loss in which cytotoxic CD8\u0026thinsp;+\u0026thinsp;NKG2D\u0026thinsp;+\u0026thinsp;and Th17 T cells target exposed follicle autoantigens in bulge and hair bulb matrix stem cells \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Up to 2% of the world\u0026rsquo;s population experience AA in their lifetime with higher prevalence in children than adults \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003eIt is estimated that up to nearly half of patients experience their first episode of hair loss by the age of 20, and 20% of all cases occurred during infancy \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. The etiology of the specific trigger remains unclear, and the disease has a spectrum of clinical presentations, including AA, alopecia totalis (total scalp hair loss) and alopecia universalis (total body hair loss, including eyebrows and eyelashes \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Quality of life can be affected in individuals with AA, who often face increased bullying, social isolation, higher rates of depression and anxiety, which can improve with appropriate treatment\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Given the significant burden associated with AA and the fact that many patients fall within TikTok\u0026rsquo;s primary demographic, individuals with AA often turn to social media for information and support. TikTok is a platform with over 1.1\u0026nbsp;billion users, with a primary user base of adolescents, and has evolved beyond its original focus on entertainment to include a growing body of health-related content \u003csup\u003e\u003cspan additionalcitationids=\"CR11 CR12 CR13\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eHowever, the quality and accuracy of the content varies widely, posing a risk of misinformation with associated public health implications. In comparison to other platforms, such as BiliBili and YouTube, TikTok has been seen to score lower across multiple evaluation tools in assessments of video quality, for example, in related to gastrointestinal bleeding education \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.There has been minimal research on the quality of AA content on social media, although there is substantial research focusing on the treatment, epidemiology, and pathophysiology of AA \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. In this analysis, we aim to evaluate the quality and accuracy of TikTok videos related to AA with the goal of determining the reliability of this content for patient education.\u003c/p\u003e"},{"header":"MATERIALS and METHODS","content":"\u003cp\u003eA descriptive cross-sectional study was conducted to evaluate the quality and accuracy of AA-related content on TikTok. To minimize algorithmic bias, a new account was created for the purpose of the study. Videos were retrieved according to predefined hashtags: #AlopeciaAreata and #AlopeciaAreata Dermatology and filtered by the \u0026ldquo;most liked\u0026rdquo; criterion, and a total of 179 videos were reviewed. From these, the first 93 videos that matched with the inclusion criteria were selected (Fig 1). Exclusion criteria included non-English languages, lack of audio, content not related to AA, or duplication. Videos were categorized by 1. content type- educational, promotional or storytelling, and 2. by creator type- healthcare provider (HP), including certified dermatologists and other medical professionals, or non-healthcare provider (NHP), such as patients and influencers. Two independent reviewers assessed the videos using standardized, validated and novel assessment tool. The requirement for informed consent was waived by the local Ethics Committee of SUMC, Israel since the data were publicly accessible on social media and no identifiable information is included in the report. All independent reviewers who participated in the study provided informed verbal consent via videochat prior to their involvement. This study adhered to the Terms \u0026amp; Conditions for data access and use of TikTok. Only publicly available content was analyzed.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eVideo Characteristics\u003c/h2\u003e\n\u003cp\u003eFor each video, we recorded key metrics including follower count, duration, upload date, tone (positive, negative or neutral), purpose and engagement metrics such as comments, likes, and shares.\u003c/p\u003e\n\u003cp\u003eAssessment Tools\u003cbr\u003eWe utilized the Patient Education Materials Assessment Tool for Audiovisual Content (PEMAT A/V) which contains seventeen sections to evaluate understandability and actionability of the content by rating it on a binary scale. A higher total score indicates high understandability, with a score below 75% (sum \u0026lt; 10) considered poorly understandable or actionable.\u003cbr\u003e\u0026nbsp;The Modified DISCERN (mDISCERN) tool was used to assess the quality and comprehensiveness of the information presented in the video. The tool comprises five sections, each assessed on a binary scale (yes/no), with 1 point awarded for a \u0026apos;yes\u0026apos; response and 0 points for a \u0026apos;no\u0026apos; response. The sections assessed include: (1) The video is clear; (2) Sourced of information used are reliable; (3) Information is balanced and unbiased; (4) Additional sources of information are listed; (5) Areas of uncertainty are mentioned. A score above three indicates greater reliability. The Global Quality Scale (GQS) was used to evaluate overall quality, flow, and utility of the video. GQS rates videos on a scale ranging from one to five, when higher scores indicate higher quality of content.\u003cbr\u003e\u0026nbsp;The Video Information and Quality Index (VIQI) tool was used to evaluate specific metrics such as flow, accuracy, and depth of content.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor this study, we developed a unique tool, which we named \u0026ldquo;AloCheck\u0026rdquo;, to comprehensively evaluate key aspects of AA in video content. The parameters we focused on fell into two main categories: (1) clinical aspects, including pathophysiology, clinical presentation and treatment; and (2) psychological aspects, including body image. \u0026nbsp;The tool uses a binary score, \u0026ldquo;1\u0026rdquo; is given if a criterion is mentioned in the video, and a score of \u0026ldquo;0\u0026rdquo; if not.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n\u003cp\u003eCategorical data were expressed as percentages, while continuous data were described using either mean and standard deviation (SD) or median and interquartile range (IQR), depending on the data distribution. The Chi-square test or Fisher\u0026rsquo;s exact test was applied to compare categorical variables. For continuous variables, comparisons were made using either the student\u0026rsquo;s T-test or the Mann-Whitney U test, as appropriate. A p-value of less than 0.05 was considered statistically significant. Data analysis was conducted using IBM SPSS Statistics, version 28 (IBM Corp., Armonk, NY).\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eOf 179 videos reviewed, 93 videos met the inclusion criteria and were selected for analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eVideographic Characteristics and Engagement Metrics\u003c/p\u003e\u003cp\u003eFrom the videos that met the inclusion criteria, 26% (n\u0026thinsp;=\u0026thinsp;24) were created by HPs and 74% (n\u0026thinsp;=\u0026thinsp;69), were created by NHPs. The median duration of NHP videos was significantly longer than HP videos (52 sec vs 32 sec, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). NHP videos demonstrated higher median numbers of comments and likes (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, P\u0026thinsp;=\u0026thinsp;0.05). In terms of content, all HP videos were educational with a neutral tone, whereas NHP videos contained more personal anecdotes and a positive tone (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and P\u0026thinsp;\u0026lt;\u0026thinsp;0.01 respectively) (Table I).\u003c/p\u003e\u003cp\u003eTable I - Videographic characteristics and engagement metrics\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCriteria\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDescriptive Statistics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal videos (N\u0026thinsp;=\u0026thinsp;93)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHealthcare providers (HP), (N\u0026thinsp;=\u0026thinsp;24)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNonhealthcare providers (NHP), (N\u0026thinsp;=\u0026thinsp;69)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eP Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLength (S)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian, IQR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e44.30 (24.45\u0026ndash;82.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32.00 (20.00\u0026ndash;44.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e53.00 (27.00 -113.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComments\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian, IQR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.05 (0.02\u0026ndash;0.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.02 (0.00-0.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.08 (0.02\u0026ndash;0.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLikes (K)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian, IQR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.30 (0.27\u0026ndash;14.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.45 (0.14\u0026ndash;6.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.40 (0.40\u0026ndash;16.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.05\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eShares\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian, IQR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.10 (0.01\u0026ndash;0.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.08 (0.02\u0026ndash;0.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.10 (0.01\u0026ndash;0.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFollowers (K)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian, IQR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e56.10 (5.80\u0026ndash;226.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e144.60 (15.9\u0026ndash;47.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e47.6 (3.30-150.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePurpose\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEducational\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24 (100.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28 (40.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOther (promotional, storytelling)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e41 (59.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eTone of video\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePositive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28 (43.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7 (10.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNatural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24 (100.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e30 (46.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eQuality Assessment Metrics\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eHealthcare professional videos scored significantly higher on all quality metrics.\u003c/p\u003e\u003cp\u003eThe median mDISCERN score (3.0 vs. 1.5, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with 70.8% of healthcare videos receiving a score\u0026thinsp;\u0026ge;\u0026thinsp;3 compared to 7.2% of non-healthcare videos (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003cp\u003eSimilarly, GQS score (3.5 [IQR3.00-4.00] vs. 1.5 [IQR0.5-2.25], p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) with 79.2% of healthcare videos scoring\u0026thinsp;\u0026ge;\u0026thinsp;3 vs. 14.5% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).VIQI scores were markedly higher across all subcategories, with a total VIQI score of 13.75 [IQR13.0-15.0] vs 11.0 [IQR9.00-12.00], (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). PEMAT A/V tool also exposed greater understandability and actionability in the HP group and the number of videos achieving an overall PMAT\u0026thinsp;\u0026ge;\u0026thinsp;10 was significantly higher in the HP videos (66.7% vs. 26.1%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). (Table II)\u003c/p\u003e\u003cp\u003eTable II \u0026ndash; Quality assessment tools; mDISCERN, GQS, VIQI, and PEMAT A/V\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQuality assessment tool\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDescriptive Statistics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal videos (N\u0026thinsp;=\u0026thinsp;93)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHealthcare providers (HP), (N\u0026thinsp;=\u0026thinsp;24)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNonhealthcare providers (NHP), (N\u0026thinsp;=\u0026thinsp;69)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eP Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emDISCERN Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian, IQR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.0 (1.0-2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.0 (2.5-3.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.5 (1.0\u0026ndash;2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emDISCERN Score\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22 (23.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17 (70.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5 (7.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGQS Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian, IQR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.0 (0.5-3.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.5 (3.0\u0026ndash;4.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.5 (0.5\u0026ndash;2.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGQS Score\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29 (31.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19 (79.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10 (14.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVIQI1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian, IQR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.0 (2.5-4.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.0 (4.0\u0026ndash;5.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.0 (2.0\u0026ndash;4.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVIQI2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian, IQR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.0 (2.0\u0026ndash;4.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.0 (4.0\u0026ndash;5.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.0 (2.0\u0026ndash;3.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVIQI3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian, IQR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.0 (1.0\u0026ndash;2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.0 (1.0\u0026ndash;2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.0 (1.0\u0026ndash;2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVIQI4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian, IQR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.0 (2.0\u0026ndash;4.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.0 (4.0\u0026ndash;5.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.0 (2.0\u0026ndash;3.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSUMVIQI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian, IQR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.5 (9.5\u0026ndash;13.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.75 (13.0\u0026ndash;15.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e11.0 (9.0\u0026ndash;12.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePEMAT A/V Understandability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian, IQR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.0 (6.0\u0026ndash;9.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.0 (7.25-10.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.0 (5.0\u0026ndash;8.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePEMAT A/V Actionability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian, IQR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.0 (1.0\u0026ndash;2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.0 (0.0\u0026ndash;2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0 (0.0\u0026ndash;2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePEMAT SUM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian, IQR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.0 (6.5\u0026ndash;10.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.0 (8.25\u0026ndash;10.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e8.0 (6.0\u0026ndash;10.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePMAT\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;10.0 (75% PERCENTILE)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34 (36.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16 (66.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e18 (26.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eNovel tool Score Analysis\u003c/p\u003e\u003cp\u003eHPs were significantly more likely to address pathophysiology or mechanisms of disease compared to non\u0026ndash;health professional (NHP) videos (87.5% vs. 40.6%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).NHP videos were more likely to address subjects concerning body image (63.8% vs. 37.5%, p\u0026thinsp;=\u0026thinsp;0.02). No significant differences were observed regarding addressing clinical presentation (P\u0026thinsp;=\u0026thinsp;0.35) or treatment (P\u0026thinsp;=\u0026thinsp;0.25). (Table III).\u003c/p\u003e\u003cp\u003eTable III - Novel Alopecia Areata Assessment Score System (AloCheck)\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabc\" border=\"1\"\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCriteria\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDescriptive Statistics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal videos (N\u0026thinsp;=\u0026thinsp;93)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHealthcare providers (HP), (N\u0026thinsp;=\u0026thinsp;24)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNonhealthcare providers (NHP), (N\u0026thinsp;=\u0026thinsp;69)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eP Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePathophysiology and Mechanism of the disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e49 (52.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21 (87.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e28 (40.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical Presentation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e80 (86.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22 (91.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e58 (84.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e65 (69.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19 (79.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e46 (66.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBody image\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e53 (57.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9 (37.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e44 (63.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSUMPTPAT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian, IQR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3 (2.0\u0026ndash;3.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17 (70.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e39 (56.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOriginally designed for entertainment, TikTok quickly evolved into a platform for information exchange, including health-related topics \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. However, the lack of regulations raises concerns about the reliability and accuracy of content. NHP users or \u0026ldquo;skinfluencers\u0026rdquo; can disseminate inaccurate information and potentially mislead viewers seeking guidance about the causes and management of AA. In today\u0026rsquo;s digital era, being aware of the quality of information on social media platforms such as TikTok is crucial.\u003c/p\u003e\u003cp\u003eThe platform has the power to shape public perceptions of disease. This is especially relevant for conditions like AA, which can have a profound and lasting psychosocial impact, particularly in younger individuals, highlighting the need for accurate, and evidence-based content \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eTo assess AA content on TikTok, we utilized several validated assessment tools, including PEMAT A\\V, mDISCERN, VIQI, GQS and a novel evaluation tool \u0026ldquo;AloCheck\u0026rdquo;. Across all evaluation tools, HP videos consistently outperformed those by NHPs, with higher mDISCERN and GQS scores indicating greater reliability and content quality, and higher PEMAT A/V and VIQI scores reflecting improved flow, accuracy, and visual presentation. However, HP videos fell behind in engagement metrics compared to NHP videos, receiving less likes and comments while content created by NHPs tended to be more popular among users. This gap suggests that while evidence-based content exists on the platform, it may not be effectively reaching users. This pattern is not unique to alopecia areata and has been observed across a range of medical conditions. Studies on acne-related content have demonstrated that TikTok content frequently lacks reliability and rarely incorporates evidence-based information \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Similarly, more than half of TikTok videos related to psoriasis were rated as low quality yet often received higher engagement than higher-quality content produced by HPs \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Comparably, in the context of type 1 diabetes, content generated by non\u0026ndash;health professionals were found to be of low reliability and quality, while approximately 50% of TikTok videos on attention-deficit/hyperactivity disorder (ADHD) were identified as misleading or inaccurate, particularly those created by NHPs \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThis discrepancy, where content produced by HPs is consistently of higher quality but receives significantly less engagement than that from NHPs, raises important questions about the accessibility of quality medical content on TikTok. Our analysis showed that HP content focused on clinical concepts and pathophysiology of AA while NHP content focused on psychosocial topics such as body image or personal narratives. The average user on TikTok is typically not seeking in-depth medical explanations, but rather gravitates to emotionally compelling, humorous, or relatable content, factors that encourage viewer engagement \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThis highlights the need for collaboration between HP and NHP content creators. By enhancing the appeal of evidence-based content we could bridge the current gap and potentially reduce the spread of misinformation ultimately guiding people to access care that is effective and safe. To our knowledge, this is the first comprehensive study with multiple assessment tools utilized to evaluate AA-related content on TikTok. Moreover, we developed a novel tool to assess the quality and accuracy of the videos. However, this study presents certain limitations. We selected videos using the hashtags #AlopeciaAreata and #AlopeciaAreataDermatology, filtered by the \u0026ldquo;most liked\u0026rdquo; criterion to capture the most widely engaged content. It is possible that other relevant hashtags were not included in our analysis. Furthermore, although video evaluation was conducted independently by two reviewers to reduce bias, the assessment remains subject to reviewer interpretation. Of note, our analysis focused on the \u0026ldquo;most liked\u0026rdquo; videos at a single point in time to better understand the quality of content that users are actively viewing and engaging with. However, this approach may not fully capture the entire spectrum of available content, as it excludes less popular videos and does not account for changes over time, leaving room for temporal bias in our results. It is important to recognize that TikTok is a rapidly evolving platform with a dynamic interface, where new content is uploaded daily and trending topics and creators shift frequently. Longitudinal research that tracks changes in content quality over time could provide deeper insights into digital health communication in dermatology and other fields.\u003c/p\u003e\u003cp\u003eMoreover, we had an English language-only cohort, which limited the geographic and linguistic diversity of the sample and may have introduced geographic and cultural bias. Additionally, the ALO-TRACE tool developed for this study has not yet undergone formal psychometric validation or pilot testing. While it was constructed through expert consensus to address both clinical and social dimensions of vitiligo content, further research is needed to establish its validity and reliability. Future studies should aim to refine and validate the tool across broader samples and dermatological conditions. In today\u0026rsquo;s digital era TikTok plays a major role in shaping public health knowledge due to its simple and accessible interface. However, due to the platforms\u0026rsquo; unregulated nature, concerns about misinformation emerge. Promoting collaboration between clinicians and NHPs in content creation may help address this issue by encouraging the dissemination of evidence-based information. Such partnerships have the potential to reduce misinformation, enhance the quality of online health content, and ultimately influence clinical outcomes by making accurate, high-quality information more accessible to the public.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eDeclaration of interest:\u003c/h2\u003e\u003cp\u003eThe authors declare that they have nothing to disclose and that they have no financial or non-financial conflict of interest.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDisclosure of interests\u003c/strong\u003e\u003cp\u003e\u003cb\u003e\u003c/b\u003eThe authors report no conflict of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eWriting (original draft), Writing (review and editing), Formal analysis [H.R]Visualization, Writing (review and editing) [C.B.G]Investigation, Visualization [Y.H] Data curation, Formal analysis [R.T]Project administration, Writing (review and editing), Supervision, Methodology, Validation, Visualization [A.H]\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data is available upon request from the authorsCorresponding author: Prof. Amir HorevEmail address: [email protected]\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFukuyama, M., Ito, T. \u0026amp; Ohyama, M. Alopecia areata: Current understanding of the pathophysiology and update on therapeutic approaches, featuring the Japanese Dermatological Association guidelines. \u003cem\u003eJ Dermatol\u003c/em\u003e \u003cstrong\u003e49\u003c/strong\u003e, 19\u0026ndash;36 (2022).\u003c/li\u003e\n\u003cli\u003eBarton, V. R., Toussi, A., Awasthi, S. \u0026amp; Kiuru, M. Treatment of pediatric alopecia areata: A systematic review. \u003cem\u003eJ Am Acad Dermatol\u003c/em\u003e \u003cstrong\u003e86\u003c/strong\u003e, 1318\u0026ndash;1334 (2022).\u003c/li\u003e\n\u003cli\u003ePrendke, M. \u003cem\u003eet al.\u003c/em\u003e Quality of life in children and adolescents with alopecia areata\u0026mdash;A systematic review. \u003cem\u003eJournal of the European Academy of Dermatology and Venereology\u003c/em\u003e \u003cstrong\u003e37\u003c/strong\u003e, 1521\u0026ndash;1534 (2023).\u003c/li\u003e\n\u003cli\u003eWaśkiel‐Burnat, A. \u003cem\u003eet al.\u003c/em\u003e Therapeutic management in paediatric alopecia areata: A systematic review. \u003cem\u003eJournal of the European Academy of Dermatology and Venereology\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, 1299\u0026ndash;1308 (2021).\u003c/li\u003e\n\u003cli\u003eWhat is alopecia areata? \u003cem\u003ePediatr Dermatol\u003c/em\u003e \u003cstrong\u003e42\u003c/strong\u003e, 43\u0026ndash;44 (2025).\u003c/li\u003e\n\u003cli\u003ePiraccini, B. M. \u003cem\u003eet al.\u003c/em\u003e Scalp hair regrowth is associated with improvements in health-related quality of life and psychological symptoms in patients with severe alopecia areata: results from two randomized controlled trials. \u003cem\u003eJournal of Dermatological Treatment\u003c/em\u003e \u003cstrong\u003e34\u003c/strong\u003e, (2023).\u003c/li\u003e\n\u003cli\u003eCruz, S., Lei, D. K., Carr, H. \u0026amp; Rosenblatt, A. The psychosocial impacts of vitiligo, psoriasis, and alopecia areata on pediatric patients. \u003cem\u003eDermatol Online J\u003c/em\u003e \u003cstrong\u003e29\u003c/strong\u003e, (2023).\u003c/li\u003e\n\u003cli\u003eTan, I. J. \u0026amp; Jafferany, M. Psychosocial impact of alopecia areata in paediatric and adolescent populations: A systematic review. \u003cem\u003eJ Paediatr Child Health\u003c/em\u003e \u003cstrong\u003e60\u003c/strong\u003e, 778\u0026ndash;782 (2024).\u003c/li\u003e\n\u003cli\u003evan Dalen, M., Muller, K. S., Kasperkovitz-Oosterloo, J. M., Okkerse, J. M. E. \u0026amp; Pasmans, S. G. M. A. Anxiety, depression, and quality of life in children and adults with alopecia areata: A systematic review and meta-analysis. \u003cem\u003eFront Med (Lausanne)\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, (2022).\u003c/li\u003e\n\u003cli\u003eHyperconnected: children and adolescents on social media. The TikTok phenomenon. \u003cem\u003eArch Argent Pediatr\u003c/em\u003e \u003cstrong\u003e121\u003c/strong\u003e, (2023).\u003c/li\u003e\n\u003cli\u003eSuarez-Lledo, V. \u0026amp; Alvarez-Galvez, J. Prevalence of Health Misinformation on Social Media: Systematic Review. \u003cem\u003eJ Med Internet Res\u003c/em\u003e \u003cstrong\u003e23\u003c/strong\u003e, e17187 (2021).\u003c/li\u003e\n\u003cli\u003eO\u0026rsquo;Sullivan, N. J., Nason, G., Manecksha, R. P. \u0026amp; O\u0026rsquo;Kelly, F. The unintentional spread of misinformation on \u0026lsquo;TikTok\u0026rsquo;; A paediatric urological perspective. \u003cem\u003eJ Pediatr Urol\u003c/em\u003e \u003cstrong\u003e18\u003c/strong\u003e, 371\u0026ndash;375 (2022).\u003c/li\u003e\n\u003cli\u003eIyengar, L., Saldanha, S. \u0026amp; Chong, A. H. #Acne: A Thematic Qualitative Analysis of Acne Content on \u0026lt;scp\u0026gt;TikTok\u0026lt;/scp\u0026gt;. \u003cem\u003eAustralasian Journal of Dermatology\u003c/em\u003e (2025) doi:10.1111/ajd.14433.\u003c/li\u003e\n\u003cli\u003eZheng, D. X., Mulligan, K. M. \u0026amp; Scott, J. F. TikTok and dermatology: An opportunity for public health engagement. \u003cem\u003eJ Am Acad Dermatol\u003c/em\u003e \u003cstrong\u003e85\u003c/strong\u003e, e25\u0026ndash;e26 (2021).\u003c/li\u003e\n\u003cli\u003eWang, J. \u003cem\u003eet al.\u003c/em\u003e Assessing the content and quality of GI bleeding information on Bilibili, TikTok, and YouTube: a cross-sectional study. \u003cem\u003eSci Rep\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 14856 (2025).\u003c/li\u003e\n\u003cli\u003eGabay, S. I., Zlakishvili, B. \u0026amp; Horev, A. A Bibliometric Analysis of Alopecia Areata Literature over the Past 50 Years. \u003cem\u003eActa Dermatovenerol Croat\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 17\u0026ndash;25 (2024).\u003c/li\u003e\n\u003cli\u003eAndre, N. \u003cem\u003eet al.\u003c/em\u003e Hematological ratios as an indicator of severity in alopecia areata: A retrospective nationwide study. \u003cem\u003ePLoS One\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, e0314600 (2024).\u003c/li\u003e\n\u003cli\u003eAghajani, M. J. \u0026amp; Aghajani, R. \u0026lt;scp\u0026gt;TikTok\u0026lt;/scp\u0026gt; and #psoriasis: A cross‐sectional study of content quality. \u003cem\u003eAustralasian Journal of Dermatology\u003c/em\u003e \u003cstrong\u003e64\u003c/strong\u003e, (2023).\u003c/li\u003e\n\u003cli\u003eVasistha, S., Kanchibhatla, A., Blanchette, J. E., Rieke, J. \u0026amp; Hughes, A. S. The Sugar-Coated Truth: The Quality of Diabetes Health Information on TikTok. \u003cem\u003eClinical Diabetes\u003c/em\u003e \u003cstrong\u003e43\u003c/strong\u003e, 53\u0026ndash;58 (2025).\u003c/li\u003e\n\u003cli\u003eYeung, A., Ng, E. \u0026amp; Abi-Jaoude, E. TikTok and Attention-Deficit/Hyperactivity Disorder: A Cross-Sectional Study of Social Media Content Quality. \u003cem\u003eThe Canadian Journal of Psychiatry\u003c/em\u003e \u003cstrong\u003e67\u003c/strong\u003e, 899\u0026ndash;906 (2022).\u003c/li\u003e\n\u003cli\u003eAnderer, S. Patients Are Turning to TikTok for Health Information\u0026mdash;Here\u0026rsquo;s What Clinicians Need to Know. \u003cem\u003eJAMA\u003c/em\u003e \u003cstrong\u003e331\u003c/strong\u003e, 1262 (2024).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Alopecia Areata, adolescents, social media, health education","lastPublishedDoi":"10.21203/rs.3.rs-7022768/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7022768/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlopecia areata (AA) is an autoimmune condition that results in hair loss and affects quality of life. With TikTok emerging as a major platform for health-related information, concerns about the spread of misinformation have arisen. This study evaluates the quality of AA content on TikTok, aiming to promote accurate, evidence-based content.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA cross-sectional study was conducted to evaluate the quality and accuracy of “most liked” AA-related content on TikTok. Videos were categorized as healthcare providers (HP) or non-healthcare providers (NHP). Two reviewers independently assessed the videos, using validated tools - PEMAT, mDISCERN, VIQI, GQS, and a novel tool developed for this study, 'AloCheck'.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOf 179 videos reviewed, 93 met the inclusion criteria and only 26% were created by HPs. These videos scored higher across all quality metrics; mDISCERN (3.0 vs. 1.5, p\u0026lt;0.01), GQS (3.5 vs. 1.5, p\u0026lt;0.01), VIQI (13.75 vs. 11.0, p\u0026lt;0.01), and PEMAT A/V (≥10: 66.7% vs. 26.1%, p\u0026lt;0.01). HPs focused more on clinical aspects (87.5% vs. 40.6%, p\u0026lt;0.01), while NHPs emphasized body image (37.5% vs 63.8%, P=0.02).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFindings reveal a gap between quality and user engagement, highlighting the risk of disseminating misleading information. Bridging this gap is essential to support the delivery of accurate and engaging health information to the public.\u003c/p\u003e","manuscriptTitle":"Evaluating the quality of TikTok videos on alopecia areata: A cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-18 13:03:41","doi":"10.21203/rs.3.rs-7022768/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7c92a82d-0645-4c67-a610-4914771a38bc","owner":[],"postedDate":"July 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":51584815,"name":"Health sciences/Diseases"},{"id":51584816,"name":"Health sciences/Health care"},{"id":51584817,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2026-05-22T06:11:02+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-18 13:03:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7022768","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7022768","identity":"rs-7022768","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}