AI-enhanced conversational agents for personalized asthma support Factors for engagement, value and efficacy

2025-07-22

AI Summary

The UK exhibits the highest asthma mortality rate in Europe, with only 30% of patients receiving essential care, underscoring an urgent need for scalable, innovative interventions. Method: Based on a survey of 1,257 asthma patients, we designed and evaluated an AI-powered mobile chatbot deployed via WhatsApp, delivering personalized health education, self-management support, and dynamic risk assessment. Contribution/Results: Fifty-three percent of adult patients expressed willingness to adopt the tool; uptake was significantly higher among those with greater disease severity and lower self-management confidence. Users prioritized 24/7 accessibility and high personalization, while privacy concerns and low trust in automated systems constituted primary barriers. This study pioneers the deep integration of automated conversational agents into a mainstream instant-messaging platform for asthma care and empirically identifies key patient-level determinants—such as clinical profile and psychosocial factors—and design requirements influencing digital health intervention acceptance. It establishes a generalizable, precision-oriented framework for digital support in chronic respiratory disease management.

Technology Category

• Humans and AI: AI for Accessibility
• Intelligent Robots: Embodied AI
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success

Abstract

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. 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? 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 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). 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.

Problem

• Addressing low asthma care access via AI chatbots
• Identifying engagement factors for asthma support chatbots
• Evaluating patient preferences for chatbot features and security

Innovation

• AI-enhanced chatbots for personalized asthma support
• Survey identifies key engagement and efficacy factors
• WhatsApp preferred for 24/7 access and personalization