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

Background: Artificial 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. Aim: To 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. Methods: This 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. Results: Attitudes 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. Conclusion: Attitudes 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.