Previously submitted to: JMIR Human Factors (no longer under consideration since Sep 18, 2025)
Date Submitted: Jul 14, 2025
Open Peer Review Period: Jul 16, 2025 - Sep 10, 2025
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Beyond Specialty and Experience: Attitudinal Profiles as Key Predictors of Physician Satisfaction with Clinical AI
ABSTRACT
This study investigates physician satisfaction with artificial intelligence (AI) decision-support systems in radiology and pathology. This mixed-methods pilot study analyzed quantitative questionnaire data from 29 Israeli radiologists and pathologists, alongside qualitative interview data. Statistical comparisons based on professional roles (specialty, experience) revealed few significant differences in attitudes. However, exploratory cluster analysis demonstrated that satisfaction is driven by underlying attitudinal profiles, segmenting physicians into "optimistic" and "skeptical" subgroups, which showed significant differences in perceived utility and future adoption. Qualitative findings confirmed physicians value AI for workflow triage but have concerns regarding accuracy and false positives, viewing it as a support tool rather than a replacement. The study concludes that understanding AI adoption requires moving beyond demographic labels to analyze data-driven attitudinal profiles, which are more predictive of physician satisfaction and acceptance.
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