Accepted for/Published in: JMIR Human Factors
Date Submitted: Jul 26, 2025
Open Peer Review Period: Jul 26, 2025 - Sep 20, 2025
Date Accepted: Jan 22, 2026
(closed for review but you can still tweet)
AI-enhanced conversational agents for personalized asthma support: Factors for engagement, value and efficacy
ABSTRACT
Background:
Asthma-related deaths in the UK are the highest in Europe, and only 30% of patients access basic care. There is a need for alternative approaches to reaching people with asthma in order to provide health education, self-management support and bridges to care.
Objective:
Automated conversational agents (specifically, mobile chatbots) present opportunities for providing alternative and individually tailored access to health education, self-management support and risk self-assessment. But would patients engage with a chatbot, and what factors influence engagement?
Methods:
We present results from a patient survey (N=1257) devised by a team of asthma clinicians, patients, and technology developers, conducted to identify optimal factors for efficacy, value and engagement for a chatbot.
Results:
Results indicate that most adults with asthma (53%) are interested in using a chatbot and the patients most likely to do so are those who believe their asthma is more serious and who are less confident about self-management. Results also indicate enthusiasm for 24/7 access, personalisation, and for WhatsApp as the preferred access method (compared to app, voice assistant, SMS or website).
Conclusions:
Obstacles to uptake include security/privacy concerns and skepticism of technological capabilities. We present detailed findings and consolidate these into 7 recommendations for developers for optimising efficacy of chatbot-based health support.
Citation
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Copyright
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