The Mediating and Moderating Roles of Innovation Climate in the Relationship Between Nurses' Attitudes Toward Artificial Intelligence, Creative Self-Efficacy, and Clinical Competence.

backgroundArtificial intelligence (AI) is increasingly integrated into health care; however, how nurses' attitudes toward AI and creative self-efficacy are associated with perceived clinical competence within different organizational contexts remains unclear.

aimTo examine whether perceived climate for innovation statistically mediates the association between nurses' attitudes toward AI and perceived clinical competence and moderates the association between creative self-efficacy and perceived clinical competence.

methodsThis cross-sectional study included 233 nurses recruited online by convenience sampling from hospitals in Türkiye between January and March 2026. Self-report measures assessed attitudes toward AI, creative self-efficacy, perceived climate for innovation, and perceived clinical competence. Pearson correlations and PROCESS Models 4 and 1 with 5000 bootstrap samples tested statistical mediation and moderation. Adjusted analyses included age, gender, previous AI-related training and AI use, educational level, professional experience, and institution type.

resultsAttitudes toward AI were indirectly associated with perceived clinical competence through perceived climate for innovation; the adjusted indirect association remained significant (B = 0.0700, SE = 0.0333, 95% CI [0.0173, 0.1453]), consistent with partial statistical mediation. Perceived climate for innovation also moderated the association between creative self-efficacy and perceived clinical competence after adjustment (interaction B = -0.1672, SE = 0.0447, 95% CI [-0.2552, -0.0792]). This positive association became weaker as perceived climate for innovation increased.

conclusionAttitudes toward AI, creative self-efficacy, perceived climate for innovation, and perceived clinical competence were significantly associated, and the statistical mediation and moderation patterns remained after adjustment. The cross-sectional, self-report data do not establish temporal or causal mechanisms or effects on objectively measured clinical performance or patient outcomes. IMPLICATIONS FOR NURSING MANAGEMENT: Nurse managers may consider supporting AI literacy, safe AI use, team-based learning, and innovation-supportive work environments. These strategies should be evaluated prospectively using objective clinical and patient outcomes before their effectiveness is inferred.