Griffin Ashley C, Khairat Saif, Bailey Stacy C, Chung Arlene E
VA Palo Alto Health Care System, Palo Alto, CA 94025, United States.
Department of Health Policy, Stanford University School of Medicine, Stanford, CA 94305, United States.
JAMIA Open. 2023 Sep 8;6(3):ooad073. doi: 10.1093/jamiaopen/ooad073. eCollection 2023 Oct.
Health-related chatbots have demonstrated early promise for improving self-management behaviors but have seldomly been utilized for hypertension. This research focused on the design, development, and usability evaluation of a chatbot for hypertension self-management, called "Medicagent."
A user-centered design process was used to iteratively design and develop a text-based chatbot using Google Cloud's Dialogflow natural language understanding platform. Then, usability testing sessions were conducted among patients with hypertension. Each session was comprised of: (1) background questionnaires, (2) 10 representative tasks within Medicagent, (3) System Usability Scale (SUS) questionnaire, and (4) a brief semi-structured interview. Sessions were video and audio recorded using Zoom. Qualitative and quantitative analyses were used to assess effectiveness, efficiency, and satisfaction of the chatbot.
Participants ( = 10) completed nearly all tasks (98%, 98/100) and spent an average of 18 min (SD = 10 min) interacting with Medicagent. Only 11 (8.6%) utterances were not successfully mapped to an intent. Medicagent achieved a mean SUS score of 78.8/100, which demonstrated acceptable usability. Several participants had difficulties navigating the conversational interface without menu and back buttons, felt additional information would be useful for redirection when utterances were not recognized, and desired a health professional persona within the chatbot.
The text-based chatbot was viewed favorably for assisting with blood pressure and medication-related tasks and had good usability.
Flexibility of interaction styles, handling unrecognized utterances gracefully, and having a credible persona were highlighted as design components that may further enrich the user experience of chatbots for hypertension self-management.
与健康相关的聊天机器人已展现出改善自我管理行为的早期前景,但很少用于高血压管理。本研究聚焦于一款名为“Medicagent”的用于高血压自我管理的聊天机器人的设计、开发及可用性评估。
采用以用户为中心的设计流程,使用谷歌云的Dialogflow自然语言理解平台迭代设计和开发基于文本的聊天机器人。然后,对高血压患者进行可用性测试。每个测试环节包括:(1)背景调查问卷;(2)Medicagent中的10项代表性任务;(3)系统可用性量表(SUS)问卷;(4)简短的半结构化访谈。测试环节使用Zoom进行视频和音频录制。采用定性和定量分析来评估聊天机器人的有效性、效率和满意度。
参与者(n = 10)几乎完成了所有任务(98%,98/100),与Medicagent交互平均花费18分钟(标准差 = 10分钟)。只有11条(8.6%)话语未成功映射到意图。Medicagent的SUS平均得分为78.8/100,表明其可用性可接受。一些参与者在没有菜单和返回按钮的情况下难以操作对话界面,认为在话语未被识别时额外的信息有助于重定向,并且希望聊天机器人中有一个健康专业人员的角色形象。
基于文本的聊天机器人在协助血压和药物相关任务方面受到好评,并且具有良好的可用性。
交互方式的灵活性、优雅地处理未识别的话语以及拥有可信的角色形象被强调为可能进一步丰富高血压自我管理聊天机器人用户体验的设计要素。