Perez Susan L, Paterniti Debora A, Wilson Machelle, Bell Robert A, Chan Man Shan, Villareal Chloe C, Nguyen Hien Huy, Kravitz Richard L
Betty Irene Moore School of Nursing, University of California, Davis, Sacramento, CA, United States.
J Med Internet Res. 2015 Jul 20;17(7):e173. doi: 10.2196/jmir.3945.
Little is known about the processes people use to find health-related information on the Internet or the individual characteristics that shape selection of information-seeking approaches.
Our aim was to describe the processes by which users navigate the Internet for information about a hypothetical acute illness and to identify individual characteristics predictive of their information-seeking strategies.
Study participants were recruited from public settings and agencies. Interested individuals were screened for eligibility using an online questionnaire. Participants listened to one of two clinical scenarios—consistent with influenza or bacterial meningitis—and then conducted an Internet search. Screen-capture video software captured Internet search mouse clicks and keystrokes. Each step of the search was coded as hypothesis testing (etiology), evidence gathering (symptoms), or action/treatment seeking (behavior). The coded steps were used to form a step-by-step pattern of each participant's information-seeking process. A total of 78 Internet health information seekers ranging from 21-35 years of age and who experienced barriers to accessing health care services participated.
We identified 27 unique patterns of information seeking, which were grouped into four overarching classifications based on the number of steps taken during the search, whether a pattern consisted of developing a hypothesis and exploring symptoms before ending the search or searching an action/treatment, and whether a pattern ended with action/treatment seeking. Applying dual-processing theory, we categorized the four overarching pattern classifications as either System 1 (41%, 32/78), unconscious, rapid, automatic, and high capacity processing; or System 2 (59%, 46/78), conscious, slow, and deliberative processing. Using multivariate regression, we found that System 2 processing was associated with higher education and younger age.
We identified and classified two approaches to processing Internet health information. System 2 processing, a methodical approach, most resembles the strategies for information processing that have been found in other studies to be associated with higher-quality decisions. We conclude that the quality of Internet health-information seeking could be improved through consumer education on methodical Internet navigation strategies and the incorporation of decision aids into health information websites.
人们在互联网上查找健康相关信息所采用的过程,以及影响信息寻求方式选择的个体特征,目前鲜为人知。
我们的目标是描述用户在互联网上查找关于一种假设的急性疾病信息的过程,并识别能够预测其信息寻求策略的个体特征。
研究参与者从公共场所和机构招募。通过在线问卷对感兴趣的个体进行资格筛选。参与者听取两种临床情景之一(与流感或细菌性脑膜炎相符),然后进行互联网搜索。屏幕截图视频软件记录互联网搜索的鼠标点击和按键操作。搜索的每一步被编码为假设检验(病因)、证据收集(症状)或行动/治疗寻求(行为)。编码步骤用于形成每个参与者信息寻求过程的逐步模式。共有78名年龄在21至35岁之间且在获取医疗服务方面存在障碍的互联网健康信息寻求者参与。
我们识别出27种独特的信息寻求模式,根据搜索过程中采取的步骤数量、一种模式是否在结束搜索前包括提出假设和探索症状或搜索行动/治疗,以及一种模式是否以寻求行动/治疗结束,将其分为四个总体类别。应用双加工理论,我们将这四个总体模式类别归类为系统1(41%,32/78),即无意识、快速、自动且处理能力强的加工;或系统2(59%,46/78),即有意识、缓慢且审慎的加工。使用多元回归分析,我们发现系统2加工与更高的教育程度和更年轻的年龄相关。
我们识别并分类了两种处理互联网健康信息的方法。系统2加工是一种有条理的方法,与其他研究中发现的与更高质量决策相关的信息处理策略最为相似。我们得出结论,通过对消费者进行有条理的互联网导航策略教育,并在健康信息网站中纳入决策辅助工具,可以提高互联网健康信息寻求的质量。