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Dr. Gihan Mohamed Mohamed Salem :: Publications:

Title:
Nursing Students’ Personality Traits and Their Attitude toward Artificial Intelligence: A Multicenter Cross-Sectional Study
Authors: Gihan Mohamed Mohamed Salem, Heba Emad El-Gazar, Abeer Yahia Mahdy, Talal Ali F. Alharbi, Mohamed Ali Zoromba
Year: 2024
Keywords: Not Available
Journal: Journal of nursing management
Volume: 2024
Issue: Not Available
Pages: 10
Publisher: Wiley
Local/International: International
Paper Link:
Full paper Not Available
Supplementary materials Not Available
Abstract:

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.

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