ArticleJMIR human factors2024
AI Hesitancy and Acceptability-Perceptions of AI Chatbots for Chronic Health Management and Long COVID Support: Survey Study.
Article in JMIR human factors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- "It's Not Only Attention We Need": Systematic Review of Large Language Models in Mental Health Care.JMIR mental health · 2025Pooled it
- Bridging Technology and Pretest Genetic Services: Quantitative Study of Chatbot Interaction Patterns, User Characteristics, and Genetic Testing Decisions.Journal of medical Internet research · 2025Trial
- What Resources Are Available for Parents Online? A Readability, Quality, and Source Evaluation of Website and AI-Generated Content on Inherited Pediatric Orthopaedic Conditions.Journal of the Pediatric Orthopaedic Society of North America · 2026Article
- Evaluation of the applicability of AI chatbots in addressing health management issues for living kidney donors.International urology and nephrology · 2026Article
- Behavior Change Content and Implementation of Large Language Model-Driven Conversational Agents in Cardiometabolic Care: Scoping Review.Journal of medical Internet research · 2026Article
- Trust-driven healthy engagement with conversational AI for mental health support in young adults: a mixed methods study.Scientific reports · 2026Article
- Navigating Diabetes Management in the Digital Era: Scoping Review of Online Health Information-Seeking Behavior.Journal of medical Internet research · 2026Article
- Understanding How a Digital Platform for Chronic Disease Management Can Enable and Limit Patient Self-Care: Qualitative Study.Journal of medical Internet research · 2026Article
- Clinician and patient perspectives on digital technology platforms for healthcare delivery.Frontiers in digital health · 2026Article
- "But it sounded confident": the role of accuracy, tone, and disclaimers in users' medical decision-making.Frontiers in artificial intelligence · 2026Article
- Digital health information-seeking behaviors and trust in AI-based physician chatbots among patients with hypertension: a cross-sectional survey in Saudi Arabia.Frontiers in public health · 2026Article
- Mapping applications and evaluations of LLM-enabled AI chatbots for health purposes: a scoping review.Frontiers in public health · 2026Article
- Conversational AI or a human professional for mental health advice? Exploring prevalence and public preferences in Australian adults.Australian journal of psychology · 2026Article
- Training the public health workforce for generative AI: validation of the Italian Chatbot Usability Questionnaire.Frontiers in public health · 2026Article
- Public attitudes and practices toward using AI chatbots for healthcare assistance: a multinational cross-sectional study.BMC health services research · 2025Article
- Empowering breast cancer clients through AI chatbots: transforming knowledge and attitudes for enhanced nursing care.BMC nursing · 2025Article
- Trust in large language model-based solutions in healthcare among people with and without diabetes: a cross-sectional survey from the Health in Central Denmark cohort.BMJ digital health & AI · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.