Quality and engagement of cognitive behavioral therapy for insomnia videos across four chinese social media platforms

Cognitive behavioral therapy for insomnia (CBTI) is a first-line treatment, but the quality and engagement of CBTI information on short-video platforms remain uncertain. We evaluated 293 videos from Douyin, Kwai, RedNote, and Bilibili using the Global Quality Scale, modified DISCERN, Video Information Quality Instrument, Journal of the American Medical Association (JAMA) benchmarks, and a Composite Quality Index (CQI). The primary outcome was ln(1 + weighted engagement per publication day).

Multivariable models adjusted for publication days, follower count, video length, and author identity using HC3 robust inference. Bilibili had the highest mean JAMA and Global Quality Scale scores, whereas Douyin had the highest median weighted engagement per day. A 10-point CQI increase was positively associated with engagement on Douyin (β = 0.469, 95% CI [0.107,0.831], P = 0.011).

However, the global CQI-by-platform interaction was nonsignificant (P = 0.067), providing insufficient evidence that the association differed across platforms. JAMA slopes and the global interaction were nonsignificant. Alternative score weightings produced similar secondary unadjusted findings, and view-normalized CQI associations were nonsignificant in Kwai and Bilibili.

The platforms differed in information transparency, quality, and engagement, but no platform performed best across all dimensions. Popularity should not be considered a proxy for CBTI information quality. Thanks to all colleagues who supported this research.

Chengdu University of Traditional Chinese Medicine, Chengdu, China Miao-yu Ye, Yu-ting Fan, Jun-jie Chen & Xi-lai Zhang Department of Tuina, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China Yong-bing Kuang, Wen-han Li & Jin-xin Dong Department of Breast Surgery, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China The authors declare no competing interests. This study utilized publicly accessible video data from four major Chinese social media platforms: Douyin, Kwai, RedNote, and Bilibili. All analyzed content was openly available, and no sensitive personal information was retained in the analytic dataset.

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