We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
Nursing Students' Personality Traits and Their Attitude toward Artificial Intelligence: A Multicenter Cross‐Sectional Study.
- Authors
Salem, Gihan Mohamed Mohamed; El-Gazar, Heba Emad; Mahdy, Abeer Yahia; Alharbi, Talal Ali F.; Zoromba, Mohamed Ali; Alamri, Majed
- 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.
- Subjects
SAUDI Arabia; CROSS-sectional method; SCALE analysis (Psychology); PEARSON correlation (Statistics); STATISTICAL correlation; RESEARCH funding; CRONBACH'S alpha; T-test (Statistics); ARTIFICIAL intelligence; ATTITUDES toward computers; UNIVERSITIES &; colleges; PUBLIC sector; STATISTICAL sampling; RESEARCH evaluation; DESCRIPTIVE statistics; NURSING education; TEACHING methods; EDUCATIONAL technology; CHI-squared test; SURVEYS; PERSONALITY; RESEARCH; ONE-way analysis of variance; STUDENT attitudes; COMPARATIVE studies; DATA analysis software; FACTOR analysis; NURSING students; REGRESSION analysis; NEUROSES
- Publication
Journal of Nursing Management, 2024, Vol 2024, p1
- ISSN
0966-0429
- Publication type
Article
- DOI
10.1155/2024/6992824