Patient Perspectives and Expectations on the Use of Artificial Intelligence to Guide Treatment Decision‐Making in Juvenile Idiopathic Arthritis: A Qualitative Study

Abstract

Objective Artificial intelligence (AI) is rapidly transforming clinical decision‐making. However, patient perspectives on these technologies remain understudied in pediatric care. We investigated patient and parent perspectives on AI use in juvenile idiopathic arthritis (JIA) care among a highly engaged cohort. Methods We conducted four focus groups with patients with JIA and parents of children with JIA to explore: (1) perceived utility of AI, (2) anticipated benefits and risks of its implementation, (3) information needs for fostering understanding and trust in AI tools, and (4) preferences for model calibration, including acceptable performance thresholds and trade‐offs between sensitivity and specificity. Transcripts were analyzed using reflexive thematic analysis. Results Participants included 8 patients with JIA (3 children and 5 adults) and 10 parents (n = 18 total). Participants expressed enthusiasm for AI's potential to support personalized treatment, but acceptance was universally contingent on AI serving as decision support rather than replacing physician judgment. Primary concerns were physician over‐reliance undermining clinical reasoning, privacy vulnerability for pediatric populations, and potential algorithmic bias. Participants emphasized that successful implementation must preserve the patient–provider relationship and accommodate individual circumstances, including disease severity, patient preferences, and lifestyle factors. Acceptable sensitivity–specificity trade‐offs varied widely, shaped by each participant's disease experience. Some participants emphasized that trust required disclosing AI use, training data sources, model performance, model provenance and conflicts of interest, and cohort characteristics. Conclusion Patients expect AI technologies to augment rather than replace clinical judgment, operate transparently, and accommodate individual circumstances. These priorities should guide AI implementation to ensure trust and meaningful adoption.