摘要
【ABSTRACT】【Background】Patient‐facing chatbots can be used for administrative tasks, personalized care reminders, and overcoming transportation or geographic barriers in healthcare. Although some data suggest older adults see privacy as an ethical barrier to adopting digital technologies, little is known about privacy concerns regarding information shared with novel patient‐facing chatbots. We sought to examine attitudes toward privacy based on age or other sociodemographic characteristics.【Methods】We conducted a sequential mixed methods study among patient users of a large healthcare system chatbot. We purposively oversampled by race and ethnicity to survey 3089 patient chatbot users online using de novo and validated items. Next, we conducted semi‐structured interviews with users (n = 46) purposively sampled based on diversity or select survey responses. We used multivariable logistic regression to analyze survey data and modified grounded theory to analyze interviews. We integrated data using simultaneous visualization and triangulation.【Results】We received 617/3089 surveys (response rate, 20.0%). Overall, 370/597 (63.9%) expressed worry about the privacy of information shared with the chatbot. Logistic regression found that users ≥ 65 years were 26% points less likely to be worried about information privacy compared to those 18–34 years old (p < 0.001). We found less worry among Black, non‐Hispanic users and among those with more than a four‐year college degree. By integrating our survey and interview data, we observed that older adult users experienced a halo effect: they worried less because they saw the chatbot as associated with a trusted health system and experienced lower medical mistrust.【Conclusion】Contrary to some prior research, adults aged 65 and older expressed less concern about chatbot privacy than younger adults because of their trust in health care. To maintain this trust and build it among all users, health systems using patient‐facing chatbots need to take active steps to maintain and communicate patient privacy protections.
摘要译文
【摘要】【背景】 -facking -facking -facking face chatbot可用于管理任务，个性化的护理提醒以及克服医疗保健中的运输或地理障碍。尽管一些数据表明，老年人将隐私视为采用数字技术的道德障碍，但对与新型患者聊天机器人共享的信息的隐私问题知之甚少。我们试图根据年龄或其他社会人口统计学特征来检查对隐私的态度。【方法】我们对大型医疗保健系统聊天机器人的患者使用者进行了顺序混合方法研究。我们有目的地对种族和种族进行了过采样，以调查3089名患者聊天机器人用户在线使用从头和经过验证的项目。接下来，我们对用户进行了半结构化访谈（n = 46），是根据多样性或选择调查响应进行采样的。我们使用多变量逻辑回归分析调查数据并修改了扎根理论来分析访谈。我们使用同时可视化和三角剖分整合了数据。结果】我们收到了617/3089的调查（响应率为20.0％）。总体而言，370/597（63.9％）表示担心与聊天机器人共享信息的隐私。逻辑回归发现，与18-34岁的年龄相比，≥65岁的用户对信息隐私的担忧低26％（p <0.001）。我们发现黑人，非西班牙裔用户以及具有超过四年大学学位的人的担忧较少。通过整合我们的调查和访谈数据，我们观察到老年人用户经历了光晕效应：他们担心的是，他们看到聊天机器人与可信赖的卫生系统相关，并且经历了较低的医疗不信任性。【结论】与一些先前的研究相反，与65岁及65岁的成年人相反，对聊天机器人的关注较少，因为他们对卫生保健的信任，他们对聊天机器人的关注较少。为了维持这种信任并在所有用户中建立它，使用患者面向聊天机器人的卫生系统需要采取积极的步骤来维护和传达患者隐私保护。
Jessica R. Ellis (https://orcid.org/0009-0009-2936-7862) [1];Natalia S. Dellavalle [2];Mika K. Hamer [3];Marlee Akerson [4];Matt Andazola [5];Annie A. Moore [6];Eric G. Campbell [7];Matthew DeCamp [8];. The Halo Effect: Perceptions of Information Privacy Among Healthcare Chatbot Users[J]. Journal of the American Geriatrics Society, 2025,73(5): 1472-1483