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@article{167611,
        author = {CHAKKA VIJAY CHANDRA and ch.praneeth},
        title = {A text-based conversational agent for asthma support: Mixed-methods feasibility study},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {4},
        pages = {1642-1645},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=167611},
        abstract = {Objective-Millions of people in India have asthma, yet 70% do not access basic care, leading to a significant number of asthma-related deaths. Chatbots may extend the reach of asthma support and provide a bridge to traditional healthcare. This study evaluates ‘Brisa’, a chatbot designed to improve asthma patients’ self-assessment and self-management.
Methods-We recruited 150 adults with an asthma diagnosis to test our chatbot. Participants were recruited over three waves through social media and a research recruitment platform. Eligible participants had access to ‘Brisa’ via a WhatsApp or website version for 28 days and completed entry and exit questionnaires to evaluate user experience and asthma control. Weekly symptom tracking, user interaction metrics, satisfaction measures, and qualitative feedback were utilized to evaluate the chatbot's usability and potential effectiveness, focusing on changes in asthma control and self-reported behavioral improvements.
Results-74% of participants engaged with ‘Brisa’ at least once. High task completion rates were observed: asthma attack risk assessment (86%), voice recording submission (83%), and asthma control tracking (95.5%). Post use, an 8% improvement in asthma control was reported. User satisfaction surveys indicated positive feedback on helpfulness (80%), privacy (87%), trustworthiness (80%), and functionality (84%) but highlighted a need for improved conversational depth and personalization.
Conclusions-The study indicates that chatbots are effective for asthma support, demonstrated by the high usage of features like risk assessment and control tracking, as well as a statistically significant improvement in asthma control. However, lower satisfaction in conversational flexibility highlights rising expectations for chatbot fluency, influenced by advanced models like ChatGPT. Future health-focused chatbots must balance conversational capability with accuracy and safety to maintain engagement and effectiveness.},
        keywords = {Digital health, ehealth, chatbots, asthma, WhatsApp, conversational agents, healthcare technology},
        month = {November},
        }