Fridman Ilona, Johnson Skyler, Elston Lafata Jennifer
Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, United States.
Radiation Oncology Deparment, Huntsman Cancer Hospital, University of Utah, Utah, UT, United States.
JMIR Med Educ. 2023 Jun 7;9:e38687. doi: 10.2196/38687.
When facing a health decision, people tend to seek and access web-based information and other resources. Unfortunately, this exposes them to a substantial volume of misinformation. Misinformation, when combined with growing public distrust of science and trust in alternative medicine, may motivate people to make suboptimal choices that lead to harmful health outcomes and threaten public safety. Identifying harmful misinformation is complicated. Current definitions of misinformation either have limited capacity to define harmful health misinformation inclusively or present a complex framework with information characteristics that users cannot easily evaluate. Building on previous taxonomies and definitions, we propose an information evaluation framework that focuses on defining different shapes and forms of harmful health misinformation. The framework aims to help health information users, including researchers, clinicians, policy makers, and lay individuals, to detect misinformation that threatens truly informed health decisions.
在面临健康决策时,人们倾向于搜索和获取基于网络的信息及其他资源。不幸的是,这使他们接触到大量错误信息。错误信息,再加上公众对科学的信任日益下降以及对替代医学的信任增加,可能会促使人们做出欠佳的选择,从而导致有害的健康后果并威胁公共安全。识别有害的错误信息很复杂。当前对错误信息的定义要么在全面定义有害健康错误信息方面能力有限,要么呈现出一个具有用户难以轻易评估的信息特征的复杂框架。基于先前的分类法和定义,我们提出了一个信息评估框架,该框架侧重于定义有害健康错误信息的不同形式和形态。该框架旨在帮助健康信息使用者,包括研究人员、临床医生、政策制定者和普通民众,检测那些威胁到真正明智的健康决策的错误信息。