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@article{Moradbakhti:2026:10.2196/80979,
author = {Moradbakhti, L and Peters, D and Quint, JK and Schuller, B and Cook, D and Calvo, RA},
doi = {10.2196/80979},
journal = {JMIR Hum Factors},
title = {AI-Enhanced Conversational Agents for Personalized Asthma Support in People With Asthma: Factors for Engagement, Value, and Efficacy in a Cross-Sectional Survey Study.},
url = {http://dx.doi.org/10.2196/80979},
volume = {13},
year = {2026}
}
TY - JOUR
AB - BACKGROUND: Asthma-related deaths in the United Kingdom 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 to provide health education, self-management support, and better bridges to care. OBJECTIVE: This study aimed to examine patients' interest in using a chatbot for asthma and to identify factors that influence engagement. 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) developed by a team of asthma clinicians, patients, and technology developers, conducted to identify optimal factors for efficacy, value, and engagement with an asthma chatbot. RESULTS: Results indicate that most adults with asthma (53%) are interested in using a chatbot. The patients most likely to do so are those who believe their asthma is more serious and are less confident in their self-management. Results also indicate enthusiasm for 24/7 access, personalization, and for WhatsApp (Meta) as the preferred access method (compared to app, voice assistant, SMS text messaging, or website). CONCLUSIONS: Obstacles to uptake include security and privacy concerns and skepticism of technological capabilities. We present detailed findings and consolidate these into 7 recommendations for developers to optimize the efficacy of chatbot-based health support.
AU - Moradbakhti,L
AU - Peters,D
AU - Quint,JK
AU - Schuller,B
AU - Cook,D
AU - Calvo,RA
DO - 10.2196/80979
PY - 2026///
TI - AI-Enhanced Conversational Agents for Personalized Asthma Support in People With Asthma: Factors for Engagement, Value, and Efficacy in a Cross-Sectional Survey Study.
T2 - JMIR Hum Factors
UR - http://dx.doi.org/10.2196/80979
UR - https://www.ncbi.nlm.nih.gov/pubmed/41812152
VL - 13
ER -