Preventive Care in Nursing and Midwifery Journal
Volume 16, Issue 3 (7-2026)
Prev Care Nurs Midwifery J 2026, 16(3): 0-0 |
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Ethics code: PDSU20250317
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Zhao C, Wang F, Ma S. Artificial Intelligence Literacy Among Nursing Interns: Current Status and Influencing Factors. Prev Care Nurs Midwifery J 2026; 16 (3)
URL: http://nmcjournal.zums.ac.ir/article-1-1041-en.html
URL: http://nmcjournal.zums.ac.ir/article-1-1041-en.html
Pingdingshan University, Pingdingshan, China , 2716129100@qq.com
Abstract: (9 Views)
Background: With the rapid integration of artificial intelligence (AI) into healthcare and nursing, intelligent nursing has emerged as a major trend in the development of the profession.
Objective: This study aimed to assess AI literacy among nursing interns and identify its influencing factors.
Methods: A cross-sectional study was conducted between December 2025 and January 2026 using convenience sampling to recruit 250 nursing interns from five tertiary Grade A hospitals in Henan Province, China. Data were collected using a general information questionnaire and the Artificial Intelligence Literacy Survey Scale. Descriptive statistics, independent-samples t-tests, one-way ANOVA, and multiple linear regression were performed using IBM SPSS Statistics version 27.0.
Results: The mean (SD) AI literacy score among nursing interns was 40.20 (9.63). Multiple linear regression showed that willingness to participate in AI training (β = −0.193, p = 0.001) and frequency of AI use (β = −0.354, p < 0.001) were independently associated with AI literacy, explaining 19.9% of its variance (adjusted R² = 0.199).
Conclusions: Nursing interns demonstrated a moderate to high level of AI literacy. Greater AI use and willingness to participate in AI training were associated with higher AI literacy. Strengthening AI education and encouraging active engagement with AI may help improve AI literacy and better prepare nursing interns for the evolving demands of intelligent nursing practice.
Objective: This study aimed to assess AI literacy among nursing interns and identify its influencing factors.
Methods: A cross-sectional study was conducted between December 2025 and January 2026 using convenience sampling to recruit 250 nursing interns from five tertiary Grade A hospitals in Henan Province, China. Data were collected using a general information questionnaire and the Artificial Intelligence Literacy Survey Scale. Descriptive statistics, independent-samples t-tests, one-way ANOVA, and multiple linear regression were performed using IBM SPSS Statistics version 27.0.
Results: The mean (SD) AI literacy score among nursing interns was 40.20 (9.63). Multiple linear regression showed that willingness to participate in AI training (β = −0.193, p = 0.001) and frequency of AI use (β = −0.354, p < 0.001) were independently associated with AI literacy, explaining 19.9% of its variance (adjusted R² = 0.199).
Conclusions: Nursing interns demonstrated a moderate to high level of AI literacy. Greater AI use and willingness to participate in AI training were associated with higher AI literacy. Strengthening AI education and encouraging active engagement with AI may help improve AI literacy and better prepare nursing interns for the evolving demands of intelligent nursing practice.
Type of Study: Orginal research |
Subject:
Nursing
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