Background. Despite the importance of studying factors contributing to nursing students’ attitudes toward artificial intelligence, yet according to our knowledge, no study has addressed the relationship between personality traits and the attitude of nursing students toward artificial intelligence. Aim. This study aimed to unveil whether nursing students’ personality traits are related to their attitude toward AI. Methods. This multicenter cross‐sectional study included 218 nursing students from three governmental universities across various regions of the Kingdom of Saudi Arabia. Data were gathered online, utilizing the Big Five Inventory, the General Attitudes toward Artificial Intelligence Scale, and a demographic questionnaire. Descriptive statistics, Pearson’s correlation, and regression analysis were employed. The research complied with the STROBE checklist. Results. Findings indicated that nursing students with a high score in the openness trait displayed positive attitudes toward artificial intelligence. Conversely, those who scored high in neuroticism and agreeableness exhibited fewer positive attitudes toward artificial intelligence and more negative attitudes toward artificial intelligence. Additionally, nursing students who ranked high in conscientiousness showed a negative attitude toward artificial intelligence. Conclusion. Except for extraversion, personality traits appear to predict attitudes toward artificial intelligence. Implications for Nursing Management. The current study provides a foundation for understanding how generative AI can be integrated into nursing education and practice in a manner that is both effective and considerate of the diverse psychological profiles of students.

Introduction: The nursing literature is silent about the relationship between ethical leadership, nurses’ flourishing, and extra-role behavior. This study was carried out to contribute to the relevant field research. Objective: The aim of the present study was to investigate the relationship between nurses’ perceptions of their nursing managers’ ethical leadership behavior, nurses’ flourishing, and their extra-role behavior. Methods: This was a cross-sectional study involving 302 nurses from six hospitals in Damietta City, Egypt. Data were collected using the following three self-report scales: Ethical Leadership at Work questionnaire, Flourishing Scale, and extra-role behavior scale. The data were analyzed using descriptive statistical, Pearson correlation, regression analysis and the structure equation model. Results: There was a significant positive relationship between nursing managers’ ethical leadership, nurses’ flourishing, and extra-role behavior. The regression analysis showed that the ethical leadership of nursing managers and nurses’ flourishing predict extra-role behavior. Conclusion: Nurses with a high level of flourishing and who work with a manager exhibiting ethical leadership behavior are more likely to activate extra-role behavior. Hence, it is recommended that nursing managers embrace an ethical approach in their leadership practices and promote flourishing among nurses to encourage them to go the extra the mile in their jobs.