Quality of bladder cancer treatment information on YouTube: May the user's profile affect the quality of results?

IF 1.3 Q3 UROLOGY & NEPHROLOGY Archivio Italiano di Urologia e Andrologia Pub Date : 2024-02-16 DOI:10.4081/aiua.2024.12179
Pier Paolo Prontera, Francesca Romana Prusciano, Marco Lattarulo, Emanuele Utano, Francesco Schiralli, Carmine Sciorio, Lorenzo Romano, Francesco Saverio Grossi
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Abstract

Background: Social media are widely used information tools, including the medical/health field. Unfortunately, the levels of misinformation on these platforms seem to be high, with a medium-low quality of the proposed content, as evidenced by previous studies. You Tube is one of the most important platforms for audio/video content. It shows content to users through a recommendation algorithm system.

Materials and methods: We have classified in two cohorts the first results obtained by researching "bladder tumor treatment" on You Tube through two different user profiles: "Cohort A" with a not logged-in session in incognito mode (46 videos enrolled) and "Cohort B" with a logged-in session with a physician profile (50 videos enrolled). The videos were evaluated using validated instruments such as DISCERN and PEMAT-AV Furthermore, we used a Likert's scale for the evaluation of levels of misinformation.

Results: Overall quality of information was moderate to poor (DISCERN 3) in 54% of Cohort A and 24% of Cohort B. Moreover, a high degree of misinformation (Likert score 3) was found in 52% of Cohort A cases and 32% of Cohort B.

Conclusions: Levels of misinformation in both cohorts are positively correlated to the number of views per month. Globally, the levels of information quality, understandability and actionability are lower for the results obtained from searches performed with anonymous user profile (Cohort A).

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YouTube 上膀胱癌治疗信息的质量:用户资料是否会影响结果的质量?
背景:社交媒体是广泛使用的信息工具,包括医疗/健康领域。不幸的是,这些平台上的错误信息水平似乎很高,而所建议内容的质量却处于中等偏下水平,这一点已被先前的研究证明。You Tube 是最重要的音频/视频内容平台之一。它通过推荐算法系统向用户展示内容:我们通过两种不同的用户特征,将在优酷上研究 "膀胱肿瘤治疗 "所获得的第一批结果分为两组:"队列 A "在隐身模式下未登录会话(注册了 46 个视频),"队列 B "在医生配置文件下登录会话(注册了 50 个视频)。我们使用 DISCERN 和 PEMAT-AV 等有效工具对视频进行了评估,并使用李克特量表对错误信息的程度进行了评估:此外,我们还发现 52% 的 A 组案例和 32% 的 B 组案例存在严重的信息错误(Likert 评分 3 分):结论:两个队列中的错误信息水平与每月浏览量呈正相关。从全球范围来看,使用匿名用户配置文件进行搜索所获得的结果(群组 A)的信息质量、可理解性和可操作性水平较低。
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来源期刊
CiteScore
2.10
自引率
35.70%
发文量
72
审稿时长
10 weeks
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