Griffin Ashley C, Xing Zhaopeng, Mikles Sean P, Bailey Stacy, Khairat Saif, Arguello Jaime, Wang Yue, Chung Arlene E
Carolina Health Informatics Program, University of North Carolina at Chapel Hill (UNC), Chapel Hill, North Carolina, USA.
Lineberger Comprehensive Cancer Outcomes Program, UNC, Chapel Hill, North Carolina, USA.
JAMIA Open. 2021 Apr 19;4(2):ooab021. doi: 10.1093/jamiaopen/ooab021. eCollection 2021 Apr.
Chatbots have potential to deliver interactive self-management interventions but have rarely been studied in the context of hypertension or medication adherence. The objective of this study was to better understand patient information needs and perceptions of chatbots to support hypertension medication self-management.
Mixed methods were used to assess self-management needs and preferences for using chatbots. We purposively sampled adults with hypertension who were prescribed at least one medication. Participants completed questionnaires on sociodemographics, health literacy, self-efficacy, and technology use. Semi-structured interviews were conducted, audio-recorded, and transcribed verbatim. Quantitative data were analyzed using descriptive statistics, and qualitative data were analyzed using applied thematic analysis.
Thematic saturation was met after interviewing 15 participants. Analysis revealed curiosity toward chatbots, and most perceived them as humanlike. The majority were interested in using a chatbot to help manage medications, refills, communicate with care teams, and for accountability toward self-care tasks. Despite general enthusiasm, there were concerns with chatbots providing too much information, making demands for lifestyle changes, invading privacy, and usability issues with deployment on smartphones. Those with overall positive perceptions toward chatbots were younger and taking fewer medications.
Chatbot-related informational needs were consistent with existing self-management research, and many felt chatbots would be valuable if customizable and compatible with patient portals, pharmacies, or health apps.
Although most were not familiar with chatbots, patients were interested in interacting with them, but this varied. This research informs future design and functionalities of conversational interfaces to support hypertension self-management.
聊天机器人有潜力提供交互式自我管理干预措施，但在高血压或药物依从性背景下的研究很少。本研究的目的是更好地了解患者的信息需求以及对聊天机器人的看法，以支持高血压药物自我管理。
采用混合方法评估自我管理需求以及使用聊天机器人的偏好。我们有目的地抽取了至少开具了一种药物处方的成年高血压患者。参与者完成了关于社会人口统计学、健康素养、自我效能感和技术使用的问卷调查。进行了半结构化访谈，进行了录音并逐字转录。定量数据采用描述性统计进行分析，定性数据采用应用主题分析进行分析。
在采访了15名参与者后达到了主题饱和。分析显示对聊天机器人有好奇心，并且大多数人认为它们像人类。大多数人有兴趣使用聊天机器人来帮助管理药物、续方、与护理团队沟通以及对自我护理任务负责。尽管总体上热情高涨，但人们担心聊天机器人提供过多信息、要求改变生活方式、侵犯隐私以及在智能手机上部署时的可用性问题。对聊天机器人总体看法积极的人更年轻且服用的药物较少。
与聊天机器人相关的信息需求与现有的自我管理研究一致，许多人认为如果聊天机器人可定制并与患者门户、药房或健康应用程序兼容，将会很有价值。
尽管大多数人不熟悉聊天机器人，但患者有兴趣与它们互动，但情况各不相同。这项研究为支持高血压自我管理的对话界面的未来设计和功能提供了信息。
