The acceptability and effectiveness of artificial intelligence-based chatbot for hypertensive patients in community: protocol for a mixed-methods study

作者：Ping Chen, Yi Li, Xuxi Zhang, Xing Lin Feng, Xinying Sun · 发表于：BMC Public Health · 年份：2024 · DOI：10.1186/s12889-024-19667-4 · 被引用次数：14 · 研究领域：Digital Mental Health Interventions、AI in Service Interactions、Artificial Intelligence in Healthcare and Education

BACKGROUND: Chatbots can provide immediate assistance tailored to patients' needs, making them suitable for sustained accompanying interventions. Nevertheless, there is currently no evidence regarding their acceptability by hypertensive patients and the factors influencing the acceptability in the real-world. Existing evaluation scales often focus solely on the technology itself, overlooking the patients' perspective. Utilizing mixed methods can offer a more comprehensive exploration of influencing factors, laying the groundwork for the future integration of artificial intelligence in chronic disease management practices. METHODS: The mixed methods will provide a holistic view to understand the effectiveness and acceptability of the intervention. Participants will either receive the standard primary health care or obtain a chatbot speaker. The speaker can provide timely reminders, on-demand consultations, personalized data recording, knowledge broadcasts, as well as entertainment features such as telling jokes. The quantitative part will be conducted as a quasi-randomized controlled trial in community in Beijing. And the convergent design will be adopted. When patients use the speaker for 1 month, scales will be used to measure patients' intention to use the speaker. At the same time, semi-structured interviews will be conducted to explore patients' feelings and influencing factors of using speakers. Data on socio-demography, physical examination, blood pressure, acceptabilit...