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Accuracy, reach, and content quality of information about obsessive-compulsive disorder on TikTok.

  • Published In: Bulletin of the Menninger Clinic, 2025, v. 89, n. 2. P. 154 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Cheng, Jessica Szu-Chi; Colombo, Gianna M.; Dailey, Megan M.; Pinciotti, Caitlin M.; Peng, Haoran C.; Wiese, Andrew D.; Trent, Erika S.; Townsend, Allie N.; Onyeka, Ogechi "Cynthia"; Goodman, Wayne K.; Storch, Eric A. 3 of 3

Abstract

Obsessive-compulsive disorder (OCD) is one of the most popular health-related topics on TikTok but is often misrepresented. This study analyzed the accuracy (i.e., accurate, overgeneralizing, or inaccurate), reach (i.e., views, likes, comments, and shares), and content quality (i.e., understandability and actionability) of 117 informational TikTok videos about OCD. Content creator type (health care professionals [HCPs], individuals with lived experiences, and others) was determined. Of the 117 analyzed videos, 64 (54.7%) were accurate, 31 (26.5%) overgeneralizing, and 22 (18.8%) inaccurate. HCP-created videos were significantly more accurate (82.1% accurate) than non-HCP-created ones (individuals with lived experiences: 63.6% accurate; others: 35.7%). Reach metrics did not vary significantly across accuracy levels and creator types. Videos analyzed were moderately understandable, and accurate videos were significantly more understandable. However, actionability was low overall. Results suggest that misinformation about OCD on TikTok is common and is being disseminated almost as widely as accurate information. Clinical implications are discussed. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Bulletin of the Menninger Clinic. 2025/04, Vol. 89, Issue 2, p154
  • Document Type:Article
  • Subject Area:Communication and Mass Media
  • Publication Date:2025
  • ISSN:0025-9284
  • DOI:10.1521/bumc.2025.89.2.154
  • Accession Number:186015636
  • Copyright Statement:Copyright of Bulletin of the Menninger Clinic is the property of Guilford Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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