Gihan Mohamed Mohamed Salem, Heba Emad El-Gazar, Abeer Yahia Mahdy, Talal Ali F. Alharbi, Mohamed Ali Zoromba
{"title":"护理专业学生的人格特质及其对人工智能的态度:多中心横断面研究","authors":"Gihan Mohamed Mohamed Salem, Heba Emad El-Gazar, Abeer Yahia Mahdy, Talal Ali F. Alharbi, Mohamed Ali Zoromba","doi":"10.1155/2024/6992824","DOIUrl":null,"url":null,"abstract":"<div>\n <p><i>Background</i>. 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. <i>Aim</i>. This study aimed to unveil whether nursing students’ personality traits are related to their attitude toward AI. <i>Methods</i>. 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. <i>Results</i>. 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. <i>Conclusion</i>. Except for extraversion, personality traits appear to predict attitudes toward artificial intelligence. <i>Implications for Nursing Management</i>. 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.</p>\n </div>","PeriodicalId":49297,"journal":{"name":"Journal of Nursing Management","volume":"2024 1","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/6992824","citationCount":"0","resultStr":"{\"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\",\"doi\":\"10.1155/2024/6992824\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n <p><i>Background</i>. 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. <i>Aim</i>. This study aimed to unveil whether nursing students’ personality traits are related to their attitude toward AI. <i>Methods</i>. 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. <i>Results</i>. 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. <i>Conclusion</i>. Except for extraversion, personality traits appear to predict attitudes toward artificial intelligence. <i>Implications for Nursing Management</i>. 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.</p>\\n </div>\",\"PeriodicalId\":49297,\"journal\":{\"name\":\"Journal of Nursing Management\",\"volume\":\"2024 1\",\"pages\":\"\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-08-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/6992824\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Nursing Management\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1155/2024/6992824\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Nursing Management","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/2024/6992824","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MANAGEMENT","Score":null,"Total":0}
Nursing Students’ Personality Traits and Their Attitude toward Artificial Intelligence: A Multicenter Cross-Sectional Study
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.
期刊介绍:
The Journal of Nursing Management is an international forum which informs and advances the discipline of nursing management and leadership. The Journal encourages scholarly debate and critical analysis resulting in a rich source of evidence which underpins and illuminates the practice of management, innovation and leadership in nursing and health care. It publishes current issues and developments in practice in the form of research papers, in-depth commentaries and analyses.
The complex and rapidly changing nature of global health care is constantly generating new challenges and questions. The Journal of Nursing Management welcomes papers from researchers, academics, practitioners, managers, and policy makers from a range of countries and backgrounds which examine these issues and contribute to the body of knowledge in international nursing management and leadership worldwide.
The Journal of Nursing Management aims to:
-Inform practitioners and researchers in nursing management and leadership
-Explore and debate current issues in nursing management and leadership
-Assess the evidence for current practice
-Develop best practice in nursing management and leadership
-Examine the impact of policy developments
-Address issues in governance, quality and safety