Evidence map›Paper›PMID 39726915›Full record

ArticleFrontiers in psychiatry2024

Evaluation of the quality of depression-related information on Chinese websites and video platforms: a cross-sectional comparative analysis.

YueDong Chen, Jia Yin, YuKe Ding, ChangYu Wang, JiaXin Zhu, Lu Niu

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

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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

6 authors.

YueDong ChenDepartment of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, China.
Jia YinDepartment of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, China.
YuKe DingDepartment of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, China.
ChangYu WangDepartment of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, China.
JiaXin ZhuDepartment of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, China.
Lu NiuDepartment of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: We aimed to assess the quality of information regarding depression on Chinese websites and popular video platforms. Methods: We conducted searches on website platforms (Baidu, Bing) and video platforms (Bilibili, Douyin) using search terms "depression", "depressive disorder", "depression treatment", "depressive anxiety", "depressed patient", and "depressive symptoms". We collected the first 50 results with each search term in each platform. Each website and video included in this study was assessed using The DISCERN instrument (DISCERN), Journal of American Medical Association benchmark criteria (JAMA), Hexagonal Radar Schema (HRS), and Global Quality Scores (GQS). Results: A total of 177 websites, 216 Bilibili videos, and 244 Douyin videos were included. Among all the platforms, websites had the highest median scores on DISCERN and HRS, at 33 and 2 respectively, but were still classified as "poor" and "very poor" according to the classification. Bilibili, Douyin, and websites had median scores of 3, 2, and 2 respectively in JAMA, indicating a moderate level of quality. Bilibili, Douyin, and websites all had a median score of 2 for GQS, and were of poor quality. Only the percentage score for JAMA was more than half of the weighted score, while none of the other scales reached half of the score. The median percentage scores of the websites in DISCERN, HRS, and GQS were higher than those of Bilibili and Douyin ( Conclusions: The findings of the study indicated an overall low quality of online depression information. Collaborative efforts between platforms and professionals are necessary to improve the comprehensiveness and quality of depression-related information available online. In addition, the platform needs to prioritize optimizing the algorithm of recommendations and present real high-quality health information to the audience.

Indexed as

Chinese videosChinese websitesdepressioninformation qualityinternet

Identifiers

PMID39726915
PMCPMC11669601

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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.