Volume 23, Issue 4 (Special Issue 2025)
Nursing and Midwifery Journal 2025, 23(4): 38-43 |
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Ethics code: IR.MARAGHEHPHC.REC.1403.066
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aliafsari mamaghani E, zirak M, soleimani A, membari K. Knowledge and Attitudes of Nursing Students Toward Artificial Intelligence: A Cross-Sectional Study. Nursing and Midwifery Journal 2025; 23 (4) :38-43
URL: http://unmf.umsu.ac.ir/article-1-5527-en.html
URL: http://unmf.umsu.ac.ir/article-1-5527-en.html
1- Department of Medical Surgical Nursing, Maragheh University of Medical Sciences, Maragheh, Iran
2- Department of Public Health, Maragheh University of Medical Sciences, Maragheh, Iran
3- Student research committee, Maragheh University of Medical Sciences, Maragheh, ,kosarmembari414@gmail.com
2- Department of Public Health, Maragheh University of Medical Sciences, Maragheh, Iran
3- Student research committee, Maragheh University of Medical Sciences, Maragheh, ,
Abstract: (164 Views)
Background: Artificial intelligence is expanding at a considerable pace in the fields of healthcare and nursing education. Students' knowledge and attitudes toward AI can influence various aspects of their educational quality. The aim of this study was to determine the level of knowledge and attitudes of nursing students regarding artificial intelligence.
Method: In this cross-sectional study, all second‑ to fourth‑year nursing students at the University of Medical Sciences and Islamic Azad University of Maragheh were enrolled through a census sampling method. Data were collected using a standard questionnaire on knowledge of artificial intelligence and a standard questionnaire on attitudes toward artificial intelligence. Data analysis was performed using SPSS software (version 26) with descriptive statistics (frequency, percentage, mean, and standard deviation) and inferential statistics (Mann‑Whitney U test, Kruskal‑Wallis test, and Spearman’s correlation).
Results: In this study, data from 300 eligible students were analyzed. The mean knowledge score for artificial intelligence was 8.3 ± 3.2, and the mean attitude score toward artificial intelligence was 97.6 ± 14.5. Based on the distribution table, the students' knowledge level was low in 45%, moderate in 50%, and high in 5%. Regarding attitudes, 5% showed a low level, 25% moderate, and 70% high.
Conclusion: Nursing students held positive attitudes toward artificial intelligence, but their level of knowledge was mostly moderate to weak. Given the relatively low mean knowledge score and the high percentage of students with low knowledge, there is a clear need to design and implement skill‑based, practical training courses on artificial intelligence for nursing students.
Method: In this cross-sectional study, all second‑ to fourth‑year nursing students at the University of Medical Sciences and Islamic Azad University of Maragheh were enrolled through a census sampling method. Data were collected using a standard questionnaire on knowledge of artificial intelligence and a standard questionnaire on attitudes toward artificial intelligence. Data analysis was performed using SPSS software (version 26) with descriptive statistics (frequency, percentage, mean, and standard deviation) and inferential statistics (Mann‑Whitney U test, Kruskal‑Wallis test, and Spearman’s correlation).
Results: In this study, data from 300 eligible students were analyzed. The mean knowledge score for artificial intelligence was 8.3 ± 3.2, and the mean attitude score toward artificial intelligence was 97.6 ± 14.5. Based on the distribution table, the students' knowledge level was low in 45%, moderate in 50%, and high in 5%. Regarding attitudes, 5% showed a low level, 25% moderate, and 70% high.
Conclusion: Nursing students held positive attitudes toward artificial intelligence, but their level of knowledge was mostly moderate to weak. Given the relatively low mean knowledge score and the high percentage of students with low knowledge, there is a clear need to design and implement skill‑based, practical training courses on artificial intelligence for nursing students.
Type of Study: Research |
Subject:
Digital Nursing
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