Evidence map›Paper›PMID 41181568›Full record

ArticleDigital health

Quality assessment of Chinese robot-assisted rehabilitation shorts.

Xinrui Li, Chuanmei Zhu, Yujie Xie, Li Wang, Xi Luo, Shengjian Wu, Chi Zhang

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

7 authors.

Xinrui LiSchool of Nursing, Southwest Medical University, Luzhou, Sichuan, China.
Chuanmei ZhuOutpatient Department, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Yujie XieDepartment of Rehabilitation, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Li WangDepartment of Rehabilitation, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Xi LuoDepartment of Rehabilitation, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Shengjian WuDepartment of Rehabilitation, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Chi ZhangDepartment of Rehabilitation, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.ORCID https://orcid.org/0009-0006-6544-3269

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The growing rehabilitation demands driven by global aging and the increasing prevalence of chronic diseases underscore the limitations of conventional therapies, highlighting robot-assisted training as a promising alternative. However, public awareness remains limited, and the quality of health information on short-video platforms is highly variable. This study aimed to evaluate the quality and reliability of Chinese-language videos pertaining to robot-assisted rehabilitation on Douyin and BiliBili. Methods: A cross-sectional analysis was conducted on 5 February 2025, involving the selection of the top 100 videos related to "robotic rehabilitation" from each of two platforms: Douyin and BiliBili. The Global Quality Score (GQS) and modified DISCERN tool (mDISCERN) were employed to assess the quality and reliability of the video content. Videos were categorized by their source and content type. Meanwhile, their interaction metrics (including likes, comments, shares, and favorites) as well as basic characteristics (such as upload time and duration) were extracted. Cohen'sκtest was used to evaluate inter-rater reliability. Spearman correlation analysis was performed to explore the relationships between variables. Additionally, multiple linear regression analysis was conducted to identify factors influencing the quality and reliability of the videos. Results: A total of 200 videos were included in the study (100 from each platform). Videos on Douyin were shorter in duration but garnered significantly higher user engagement (all p < 0.001 for likes, comments, shares, and favorites), whereas videos on BiliBili were longer and featured more academic resource citations. Median scores for video quality and reliability on both platforms were moderate (GQS = 2, mDISCERN = 2), yet BiliBili had a higher proportion of high-quality videos. Content created by experts exhibited greater informational value, while commercially promoted videos demonstrated lower credibility. Multiple regression analysis revealed that sources from academic and medical institutions, content types focused on science communication/education and expert explanations, video duration, and daily share rate were significant positive predictors of both GQS and mDISCERN scores. Conclusion: Short-video platforms serve as valuable channels for disseminating information on robot-assisted rehabilitation; however, significant variability in content quality necessitates critical evaluation by users. Individuals should verify the scientific validity of such information before applying it in health-related decision making.

Indexed as

information qualityrehabilitationRoboticsshort videos

Identifiers

PMID41181568
PMCPMC12576090

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.