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Assessing the Acceptability and Knowledge of Nurses Regarding Artificial Intelligence in Healthcare


Article Information

Title: Assessing the Acceptability and Knowledge of Nurses Regarding Artificial Intelligence in Healthcare

Authors: Najma Mukhtar, Amoon Augustin, Saima Anwar, Iram Mahmood, Saima Ashraf

Journal: Biological and Clinical Sciences Research Journal (BCSRJ)

HEC Recognition History
Category From To
Y 2024-10-01 2025-12-31
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30

Publisher: Medeye Publishers

Country: Pakistan

Year: 2025

Volume: 6

Issue: 8

Language: en

DOI: 10.54112/bcsrj.v6i8.1917

Keywords: Artificial intelligencenursingknowledgeacceptability

Categories

Abstract

The integration of artificial intelligence (AI) into healthcare offers opportunities to improve clinical efficiency and patient outcomes. However, successful adoption depends on nurses' knowledge, attitudes, and readiness to use AI tools. Objective: To assess the acceptability and knowledge of nurses regarding AI in healthcare and identify factors influencing its adoption. Methods: An analytical cross-sectional survey was conducted among 99 registered nurses in a tertiary care hospital in Pakistan from July to December. Participants were selected using stratified random sampling and completed a validated, self-administered questionnaire that covered socio-demographics, AI knowledge (a 15-item test), and attitudes (a 17-item Likert scale). Data were analyzed using descriptive statistics, bivariate analysis, and multivariable logistic regression to identify predictors of high AI acceptability. Results: The mean knowledge score was 8.7 ± 3.1, with 32.3% demonstrating good knowledge (≥11/15). Perceived usefulness (mean 3.7 ± 0.7) and intention to use (3.6 ± 0.8) scored highest among attitude domains, while job-displacement concern averaged 3.1 ± 0.9. High acceptability (composite score > 3.5) was observed in 54.5% of the nurses. Multivariable analysis identified good knowledge (AOR = 2.85, p = 0.020), prior AI training (AOR = 3.41, p = 0.038), and high computer literacy (AOR = 2.23, p = 0.047) as significant predictors, while job-displacement concerns were inversely associated (AOR = 0.71, p = 0.037). The most reported barriers were lack of training (71.7%) and inadequate infrastructure (57.6%), whereas key facilitators included hands-on workshops (68.7%) and managerial support (55.6%). Conclusion: Nurses in this study showed moderate AI knowledge and cautious optimism toward adoption. Targeted training, infrastructure investment, and addressing job security concerns are crucial to enhancing the acceptability of AI in nursing practice, particularly in resource-limited healthcare settings such as Pakistan.


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