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Accepted for/Published in: JMIR Infodemiology

Date Submitted: Jan 20, 2026
Date Accepted: Oct 3, 2026

The final, peer-reviewed published version of this preprint can be found here:

Quality Assessment of and User Engagement With Short Videos About Breast Cancer Screening on Douyin, Kuaishou, and TikTok: Cross-Sectional Content Analysis Study

Li A, Lin X, Shi F, Chang J

Quality Assessment of and User Engagement With Short Videos About Breast Cancer Screening on Douyin, Kuaishou, and TikTok: Cross-Sectional Content Analysis Study

JMIR Infodemiology 2026;6:e91852

DOI: 10.2196/91852

A Comparative Study of Quality Assessment and User Engagement on Douyin, Kuaishou, and TikTok Short Videos on Breast Cancer Screening: A Cross-sectional Content Analysis

  • Anqi Li; 
  • Xiaohua Lin; 
  • Fujun Shi; 
  • Jinghui Chang

ABSTRACT

Background:

Breast cancer screening plays a critical role in reducing its mortality. Nowadays, short video platforms have emerged as important channels for disseminating health education regarding breast cancer screening.

Objective:

The study aims to explore and compare the source, content characteristics, and quality of short videos on "breast cancer screening" across major Chinese-language platforms (Douyin and Kuaishou) and the English-language platform (TikTok).

Methods:

Using the keyword "breast cancer screening," this study retrieved and screened the top 100 short videos from each of three platforms—Douyin, Kuaishou, and TikTok—resulting in a final sample of 258 eligible videos. Basic video information, user engagement metrics, and uploader characteristics were collected. Three breast disease specialists independently evaluated the content using four tools: the Patient Education Materials Assessment Tool for Audiovisual Materials (PEMAT-A/V), modified DISCERN (mDISCERN), Global Quality Score (GQS), and the Journal of the American Medical Association Benchmark Criteria (JAMA-BC), respectively assessing understandability and actionability, overall quality, educational value, and reliability. Statistical analyses included Kruskal-Wallis tests, Dunn-Bonferroni tests, chi-square tests, and Spearman correlation analysis.

Results:

Videos on TikTok demonstrated significantly lower scores in the mDISCERN, GQS, and JAMA-BC compared to those on Douyin and Kuaishou (P-values < 0.05), indicating poorer overall quality and reliability. The median mDISCERN score for TikTok was 6.50 (8.00 for both Douyin and Kuaishou; P-values<0.05), the GQS median was 2.00 (3.00 for both Douyin and Kuaishou; P-values<0.05), and the JAMA-BC median was 10.00 (12.00 for both Douyin and Kuaishou; P-values<0.05). The PEMAT-A/V scores were also significantly lower on TikTok (P<0.01). Healthcare professionals were the main content creators on Douyin (74.24%) and Kuaishou (81.20%), while individual content creators dominated TikTok (45.83%). Authentication rates were significantly lower on TikTok (12.50%) compared to Kuaishou (50.72%) and Douyin (87.88%). Viewer engagement metrics—including likes, comments, and shares—were non-significant or negatively correlated with video quality. For example, mDISCERN scores were negatively correlated with the number of likes (P<0.05).

Conclusions:

This study reveals that high-quality videos on breast cancer screening tend to attract lower viewer engagement, highlighting platform-specific disparities and challenges in dissemination. It is recommended that short video platforms implement stricter reviews for health-related videos or uploaders. Additionally, governmental or related agencies should provide media training for healthcare professionals in public science communication to enhance the impact and effectiveness of health education via short videos.


 Citation

Please cite as:

Li A, Lin X, Shi F, Chang J

Quality Assessment of and User Engagement With Short Videos About Breast Cancer Screening on Douyin, Kuaishou, and TikTok: Cross-Sectional Content Analysis Study

JMIR Infodemiology 2026;6:e91852

DOI: 10.2196/91852

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© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.