AI Hesitancy and Acceptability—Perceptions of AI Chatbots for Chronic Health Management and Long COVID Support: Survey Study

Abstract Background Artificial intelligence (AI) chatbots have the potential to assist individuals with chronic health conditions by providing tailored information, monitoring symptoms, and offering mental health support. Despite their potential benefits, research on public attitudes toward health care chatbots is still limited. To effectively support individuals with long-term health conditions like long COVID (or post–COVID-19 condition), it is crucial to understand their perspectives and preferences regarding the use of AI chatbots. Objective This study has two main objectives: (1) provide insights into AI chatbot acceptance among people with chronic health conditions, particularly adults older than 55 years and (2) explore the perceptions of using AI chatbots for health self-management and long COVID support. Methods A web-based survey study was conducted between January and March 2023, specifically targeting individuals with diabetes and other chronic conditions. This particular population was chosen due to their potential awareness and ability to self-manage their condition. The survey aimed to capture data at multiple intervals, taking into consideration the public launch of ChatGPT, which could have potentially impacted public opinions during the project timeline. The survey received 1310 clicks and garnered 900 responses, resulting in a total of 888 usable data points. Results Although past experience with chatbots ( P <.001, 95% CI .110-.302) and online information seeking ( P <.001, 95% CI .039-.084) are strong indicators of respondents’ future adoption of health chatbots, they are in general skeptical or unsure about the use of AI chatbots for health care purposes. Less than one-third of the respondents (n=203, 30.1%) indicated that they were likely to use a health chatbot in the next 12 months if available. Most were uncertain about a chatbot’s capability to provide accurate medical advice. However, people seemed more receptive to using voice-based chatbots for mental well-being, health data collection, and analysis. Half of the respondents with long COVID showed interest in using emotionally intelligent chatbots. Conclusions AI hesitancy is not uniform across all health domains and user groups. Despite persistent AI hesitancy, there are promising opportunities for chatbots to offer support for chronic conditions in areas of lifestyle enhancement and mental well-being, potentially through voice-based user interfaces.