@Article{info:doi/10.2196/70409,
author="Lau, Cheryl W Y
and Kupiec, Klaudia
and Livermore, Polly",
title="Exploring the Acceptance and Opportunities of Using a Specific Generative AI Chatbot to Assist Parents in Managing Pediatric Rheumatological Chronic Health Conditions: Mixed Methods Study",
journal="JMIR Pediatr Parent",
year="2025",
month="Jul",
day="1",
volume="8",
pages="e70409",
keywords="pediatric health care chatbot; technology acceptance; parental attitudes; children and young people's involvement; chronic disease management; AI hesitancy; chronic health condition; artificial intelligence",
abstract="Background: Health care chatbots can be used to support patients and their families with everyday decision-making. While there is some research on integrating artificial intelligence into pediatric care, no study has focused on the opportunity of implementing a generative artificial intelligence chatbot for pediatric rheumatology. Pediatric rheumatology conditions require intense family input, which can often leave families struggling to navigate disease flares, pain, fatigue, medication side effects and adherence, and support of their child, often when pediatric rheumatology departments are shut. Understanding how we can support families better, without the need for increased personnel, will have implications for the health care systems. Objective: The study aimed to explore parental and children and young people's acceptance of chatbot use in a pediatric context, and understand how a chatbot could be specifically used for managing a child's chronic health condition. Methods: This study was a mixed methods design, using both a family workshop and a subsequent questionnaire. Results: In total, 22 participants contributed to the qualitative design using the world caf{\'e} methodology at a workshop, and 47 participants (36 parents and 11 children and young people) completed quantitative data via a questionnaire. Participants expressed their likelihood of using chatbot technology, including ChatGPT, due to its accessibility. However, participants had significantly greater intention (parents: P<.001; children and young people: P=.006) to use a specific chatbot over ChatGPT, due to increased trust, credibility, and specificity in design. Children and young people and parents should be distinguished as 2 user groups in chatbot design, reflecting their specific needs in chatbot features and personalization. Conclusions: Overall, the study reinforced the need for a specialized and trusted chatbot designed with input from health professionals to assist families in managing complex chronic health conditions to support families in between appointments and complement existing face-to-face care. Future research should evaluate users' engagement with a functional prototype to investigate its usefulness and explore its implementation into families' everyday lives. Importantly, the current findings have broader implications for the field of pediatric health care, as similarly tailored chatbot interventions could benefit families who are managing other chronic health conditions. ",
issn="2561-6722",
doi="10.2196/70409",
url="https://pediatrics.jmir.org/2025/1/e70409",
url="https://doi.org/10.2196/70409"
}