Accepted for/Published in: JMIR Pediatrics and Parenting
Date Submitted: Dec 20, 2024
Open Peer Review Period: Jan 7, 2025 - Mar 4, 2025
Date Accepted: May 20, 2025
(closed for review but you can still tweet)
Exploring the Acceptance and Opportunities of Using a Specific Generative AI Chatbot to Assist Parents in Managing Paediatric Rheumatological Chronic Health Conditions: A Mixed-Methods Study
ABSTRACT
Background:
Healthcare chatbots can be used to support patients with everyday decision-making. While there is some research on integrating artificial intelligence (AI) into paediatric care, no study has focused on the opportunity of implementing a generative AI (genAI) chatbot for paediatric rheumatology. Paediatric 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 paediatric rheumatology departments are shut. Understanding how we can support families better, without the need for increased personnel, will have implications for the healthcare systems.
Objective:
The study aimed to explore children and young peoples (CYP) and parental acceptance of chatbot use in a paediatric context and understand how a chatbot can be specifically utilised for managing a child’s chronic health condition.
Methods:
This study was a mixed-methods design, utilising both a family workshop and subsequent questionnaire.
Results:
In total, 22 participants contributed to the table at the world care methodology workshop and 47 participants (36 parents and 11 children and young people) completed the questionnaire. Participants expressed their likelihood of using chatbot technology, including ChatGPT, due to its accessibility. However, participants had significantly greater intention (CYP: p=.006; Parents: p <.001) to use a specific chatbot over ChatGPT, due to increased trust, credibility, and specificity in design. CYP and parents should be distinguished as two user groups in chatbot design, reflecting their specific needs in chatbot features and personalisation.
Conclusions:
Overall, the study reinforced the need for a specialised and trusted chatbot designed with input from health professionals to assist families in managing complex chronic health conditions. Future research should evaluate users’ engagement with a functional prototype to investigate its usefulness and explore its implementation into families’ everyday life. Importantly, the current findings have broader implications for the field of paediatric healthcare, as similarly tailored chatbot interventions could benefit families who are managing other chronic health conditions.
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Copyright
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