Evidence map›Paper›PMID 40986789›Full record

ArticleJMIR cancer2025

Quality Assessment of Radiotherapy Health Information on Short-Form Video Platforms of TikTok and Bilibili: Cross-Sectional Study.

Feihang Guo, Guangcheng Ding, Yanzheng Zhang, Xinru Liu

Abstract read
In one paragraph

Article in JMIR cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed.

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  18. Content Quality, Reliability, and Factors Associated With Likes of Venous Thromboembolism-Related Short Videos on TikTok and Bilibili: A Cross-Platform Analysis.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Feihang Guo *The Fifth Affiliated Hospital of Zhengzhou University, 3 Kangfuqian Street, Erqi District, Zhengzhou, China, 86 13623861790.ORCID 0009-0000-2072-6739
Guangcheng Ding *The Fifth Affiliated Hospital of Zhengzhou University, 3 Kangfuqian Street, Erqi District, Zhengzhou, China, 86 13623861790.ORCID 0000-0002-4371-0147
Yanzheng Zhang *The Fifth Affiliated Hospital of Zhengzhou University, 3 Kangfuqian Street, Erqi District, Zhengzhou, China, 86 13623861790.ORCID 0009-0006-1139-0798
Xinru Liu *The Fifth Affiliated Hospital of Zhengzhou University, 3 Kangfuqian Street, Erqi District, Zhengzhou, China, 86 13623861790.ORCID 0009-0002-5895-3923

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Radiotherapy (RT) is a crucial modality in cancer treatment. In recent years, the rise of short-form video platforms has transformed how the public accesses medical information. TikTok and Bilibili, as leading short-video platforms, have emerged as significant channels for disseminating health information. However, there is an urgent need to evaluate the quality and reliability of the information related to RT available on these platforms. Objective: This study aims to systematically assess the information quality and reliability of RT-related short-form videos on TikTok and Bilibili platforms using the Global Quality Score (GQS) and a modified DISCERN (mDISCERN) evaluation tool, thereby elucidating the current landscape and challenges of digital health communication. Methods: This study systematically retrieved the top 100 RT-related videos on TikTok and Bilibili as of February 25, 2025. The quality of the videos was assessed using the GQS (1-5 points) and an mDISCERN scoring system (1-5 points). Statistical analyses were conducted using the Mann-Whitney U test, as well as Spearman and Pearson correlation analyses, to ensure the reliability and validity of the results. Results: A total of 200 short-form videos related to RT were analyzed, revealing that the overall quality of videos on TikTok and Bilibili is unsatisfactory. Specifically, the median GQS for TikTok was 4 (IQR 3-4), while for Bilibili, it was 3 (IQR 3-4). The median mDISCERN scores for both platforms were 3 (IQR 2-4 and 3-4, respectively), and no significant differences were observed between the 2 platforms regarding the GQS (P=.12) and mDISCERN score (P=.10). On TikTok, 53% (53/100) of videos had a GQS of 4 or higher ("good" quality or better). On Bilibili, 45% (45/100) of videos had an mDISCERN score of 4 or higher, indicating "relatively reliable" quality. Videos produced by professionals, institutions, and nonprofessional institutions had significantly higher mDISCERN scores than those made by patients, with statistical significance (P<.001, P<.001, and P<.01, respectively). Furthermore, the correlations between the number of bookmarks and video duration, with mDISCERN scores, were 0.172 (P=.02) and 0.192 (P=.007), respectively. However, no video variables were found to predict the overall quality and reliability of the videos effectively. Conclusions: This study revealed that the overall quality of RT-related videos on TikTok and Bilibili is generally low. However, videos uploaded by professionals demonstrate higher information quality and reliability, providing valuable support for patients seeking guidance on health care management and treatment options for cancers. Therefore, improving the quality and reliability of video content, particularly that produced by patients, is crucial for ensuring that the public has access to accurate medical information.

Indexed as

Information DisseminationNeoplasmsRadiotherapyVideo RecordingCross-Sectional StudiesHumansReproducibility of ResultsBilibiliDISCERN scoreGlobal Quality Scoreinformation qualityradiotherapyRTshort-form videossocial mediaTikTok

Identifiers

PMID40986789
PMCPMC12456845

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.