When Machines Decide: Exploring How Trust in AI Shapes the Relationship Between Clinical Decision Support Systems and Nurses' Decision Regret: A Cross-Sectional Study.

Background: Artificial intelligence (AI)-based Clinical Decision Support Systems (AI-CDSS) are increasingly implemented in intensive care settings to support nurses in complex, time-sensitive decisions, aiming to improve accuracy, efficiency and patient outcomes. However, their use raises concerns about emotional consequences, particularly decision regret, which may arise when clinical judgement or outcomes are unfavourable. Trust in AI may play a key role in shaping nurses' responses to AI-guided decisions.

Aim: To examine the relationship between nurses' reliance on AI-CDSS, decision regret and trust in AI, with a focus on the moderating role of trust in the association between AI-CDSS reliance and decision regret.

Study design: A cross-sectional correlational design was used. A convenience sample of 250 intensive care unit (ICU) nurses completed validated instruments: the Healthcare Systems Usability Scale (HSUS) for AI-CDSS reliance, the Decision Regret Scale (DRS) and the Trust in AI Scale. Descriptive statistics, Pearson's correlations, multiple linear regression and moderation analysis were conducted.

Results: A total of 250 ICU nurses participated in the study out of 400 approached, yielding a response rate of 62.5%. Nurses reported moderate levels of AI-CDSS reliance (M = 78.6, SD = 12.4), decision regret (M = 38.5, SD = 14.8) and trust in AI (M = 13.9, SD = 3.2). AI-CDSS reliance was negatively correlated with decision regret (r = -0.42, p < 0.01) and positively with trust in AI (r = 0.51, p < 0.01). Regression analysis showed that both AI-CDSS reliance (β = -0.36) and trust in AI (β = -0.24) significantly predicted reduced regret (R² = 0.27, p < 0.001). Trust moderated the relationship, strengthening the negative association between reliance and regret.

Conclusion: Greater reliance on AI-CDSS is associated with lower decision regret among ICU nurses, especially when trust in AI is high. Trust enhances emotional acceptance and supports effective AI integration.

Relevance to clinical practice: Building trust in AI-CDSS among nurses is essential for minimising emotional burden and optimising decision-making in critical care.