医疗社交媒体伦理量表的开发及 #IRad、#CardioTwitter 和 #MedTwitter 帖子的评估:混合方法研究。

IF 3.5 Q1 HEALTH CARE SCIENCES & SERVICES
JMIR infodemiology Pub Date : 2024-03-27 DOI:10.2196/47770
Vongai Christine Mlambo, Eric Keller, Caroline Mussatto, Gloria Hwang
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引用次数: 0

摘要

背景:临床医生在社交媒体上发表的文章不受同行评议出版物相同规则的约束,从而引发了尚未广泛定性或量化的伦理问题:我们旨在开发一个量表来评估医疗社交媒体(SoMe)上的伦理问题,并用它来确定这些问题在带有 3 个不同标签的帖子中的普遍程度:#方法:根据以往对专业性的描述制定了量表,并通过对 11 名临床医生和受训人员进行半结构化认知访谈、交互同意以及对 100 篇帖子进行相关性验证。最终量表对 6 个领域的社交媒体帖子进行了评估。该量表用于分析 1500 条 Twitter 帖子,其中 500 条来自 3 个标签。帖子分析仅限于北美医疗保健专业人员在 Twitter 上发布的英文原创帖子。使用描述性统计确定了潜在问题的普遍性,并使用费舍尔精确检验和χ2检验以及耶茨校正比较了不同标签的普遍性:结果:参与者认为最终量表反映了 SoMe 潜在的伦理问题。研究者之间的一致性良好(Cohen κ=0.620, PConclusions):我们开发的 SoMe 职业化量表可靠地反映了潜在的伦理问题。SoMe上的伦理问题很少见,但却很重要,而且在不同的医学界普遍存在。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of a Medical Social Media Ethics Scale and Assessment of #IRad, #CardioTwitter, and #MedTwitter Posts: Mixed Methods Study.

Background: Social media posts by clinicians are not bound by the same rules as peer-reviewed publications, raising ethical concerns that have not been extensively characterized or quantified.

Objective: We aim to develop a scale to assess ethical issues on medical social media (SoMe) and use it to determine the prevalence of these issues among posts with 3 different hashtags: #MedTwitter, #IRad, and #CardioTwitter.

Methods: A scale was developed based on previous descriptions of professionalism and validated via semistructured cognitive interviewing with a sample of 11 clinicians and trainees, interrater agreement, and correlation of 100 posts. The final scale assessed social media posts in 6 domains. This was used to analyze 1500 Twitter posts, 500 each from the 3 hashtags. Analysis of posts was limited to original Twitter posts in English made by health care professionals in North America. The prevalence of potential issues was determined using descriptive statistics and compared across hashtags using the Fisher exact and χ2 tests with Yates correction.

Results: The final scale was considered reflective of potential ethical issues of SoMe by participants. There was good interrater agreement (Cohen κ=0.620, P<.01) and moderate to strong positive interrater correlation (=0.602, P<.001). The 6 scale domains showed minimal to no interrelation (Cronbach α=0.206). Ethical concerns across all hashtags had a prevalence of 1.5% or less except the conflict of interest concerns on #IRad, which had a prevalence of 3.6% (n=18). Compared to #MedTwitter, posts with specialty-specific hashtags had more patient privacy and conflict of interest concerns.

Conclusions: The SoMe professionalism scale we developed reliably reflects potential ethical issues. Ethical issues on SoMe are rare but important and vary in prevalence across medical communities.

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