Keselman Alla, Arnott Smith Catherine, Murcko Anita C, Kaufman David R
Division of Specialized Information Services, National Library of Medicine, National Institutes of Health, Bethesda, MD, United States.
University of Wisconsin-Madison, Madison, WI, United States.
J Med Internet Res. 2019 Feb 8;21(2):e11129. doi: 10.2196/11129.
Critical evaluation of online health information has always been central to consumer health informatics. However, with the emergence of new Web media platforms and the ubiquity of social media, the issue has taken on a new dimension and urgency. At the same time, many established existing information quality evaluation guidelines address information characteristics other than the content (eg, authority and currency), target information creators rather than users as their main audience, or do not address information presented via novel Web technologies.
The aim of this formative study was to (1) develop a methodological approach for analyzing health-related Web pages and (2) apply it to a set of relevant Web pages.
This qualitative study analyzed 25 type 2 diabetes pages, which were derived from the results of a Google search with the keywords "diabetes," "reversal," and "natural." The coding scheme, developed via a combination of theory- and data-driven approaches, includes 5 categories from existing guidelines (resource type, information authority, validity of background information sources, objectivity, and currency) and 7 novel categories (treatment or reversal method, promises and certainty, criticisms of establishment, emotional appeal, vocabulary, rhetoric and presentation, and use of science in argumentation). The coding involves both categorical judgment and in-depth narrative characterization. On establishing satisfactory level of agreement on the narrative coding, the team coded the complete dataset of 25 pages.
The results set included "traditional" static pages, videos, and digitized versions of printed newspapers or magazine articles. Treatments proposed by the pages included a mixture of conventional evidence-based treatments (eg, healthy balanced diet exercise) and unconventional treatments (eg, dietary supplements, optimizing gut flora). Most pages either promised or strongly implied high likelihood of complete recovery. Pages varied greatly with respect to the authors' stated background and credentials as well as the information sources they referenced or mentioned. The majority included criticisms of the traditional health care establishment. Many sold commercial products ranging from dietary supplements to books. The pages frequently used colloquial language. A significant number included emotional personal anecdotes, made positive mentions of the word cure, and included references to nature as a positive healing force. Most pages presented some biological explanations of their proposed treatments. Some of the explanations involved the level of complexity well beyond the level of an educated layperson.
Both traditional and data-driven categories of codes used in this work yielded insights about the resources and highlighted challenges faced by their users. This exploratory study underscores the challenges of consumer health information seeking and the importance of developing support tools that would help users seek, evaluate, and analyze information in the changing digital ecosystem.
对在线健康信息进行批判性评估一直是消费者健康信息学的核心内容。然而,随着新的网络媒体平台的出现以及社交媒体的普及,这个问题呈现出了新的维度和紧迫性。与此同时,许多现有的信息质量评估指南关注的是内容以外的信息特征(如权威性和时效性),将信息创作者而非用户作为主要受众,或者没有涉及通过新型网络技术呈现的信息。
这项形成性研究的目的是(1)开发一种分析与健康相关网页的方法,以及(2)将其应用于一组相关网页。
这项定性研究分析了25个2型糖尿病网页,这些网页来自谷歌搜索结果,关键词为“糖尿病”“逆转”和“自然”。通过理论驱动和数据驱动相结合的方法开发的编码方案,包括现有指南中的5个类别(资源类型、信息权威性、背景信息来源的有效性、客观性和时效性)以及7个新类别(治疗或逆转方法、承诺与确定性、对现有医疗机构的批评、情感诉求、词汇、修辞与表述,以及论证中科学的运用)。编码涉及分类判断和深入的叙述性描述。在就叙述性编码达成令人满意的一致性水平后,研究团队对25个网页的完整数据集进行了编码。
结果集中包括“传统”静态网页、视频以及印刷报纸或杂志文章的数字化版本。网页提出的治疗方法包括传统的循证治疗(如健康均衡饮食、运动)和非传统治疗(如膳食补充剂、优化肠道菌群)的混合。大多数网页要么承诺要么强烈暗示完全康复的可能性很大。网页在作者声明的背景和资质以及他们引用或提及的信息来源方面差异很大。大多数网页包含对传统医疗体系的批评。许多网页推销从膳食补充剂到书籍等商业产品。这些网页经常使用口语化语言。相当一部分网页包含情感化的个人轶事,积极提及“治愈”一词,并将自然视为一种积极的治愈力量。大多数网页对其提出的治疗方法给出了一些生物学解释。其中一些解释的复杂程度远远超出了受过教育的外行的理解水平。
本研究中使用的传统和数据驱动的编码类别都产生了关于这些资源的见解,并突出了用户面临的挑战。这项探索性研究强调了消费者寻求健康信息的挑战,以及开发支持工具以帮助用户在不断变化的数字生态系统中寻求、评估和分析信息的重要性。