Evaluation of nursing students' ethical decision-making biases and attitudes toward artificial intelligence in nursing education

Abstract

Aim: This study examines nursing students' attitudes toward artificial intelligence (AI) and their association with biases in ethical decision-making processes. Background: AI technologies are central to healthcare, particularly clinical decision support systems and simulations. While AI accelerates decision-making processes, it also brings ethical responsibilities. Design: This is a descriptive cross-sectional study. Method: 265 nursing students were selected through stratified sampling from two universities in Turkey. Data were collected via an online survey using a demographic information form, the AI Attitude Scale (GAAIS) and the Ethical Decision-Making Bias Scale (EDBS). Results: Most participants were female (n = 223), with an average age of 20.45 (SD 1.67) years. The results of the GAAIS revealed that students generally had a positive attitude (3.38 SD 0.47). However, 36.2 % expressed distrust toward AI students who trusted AI more successfully to solve ethical issues and used AI tools more effectively. The average score on the EDBS was 2.48 SD 0.41. Additionally, students who encountered ethical decisions more frequently (2.30 SD 0.32) showed lower bias levels than those who experienced them less often (2.50SD0.44). Positive attitudes toward AI were positively associated with students' confidence in ethical decision-making (p < 0.05). Distrust in AI and difficulty accessing accurate information were identified as significant barriers. Conclusions: Attitudes toward AI significantly influence students' biases in ethical decision-making processes. The nursing curriculum should include AI ethics, critical thinking and decision-making skills. Integrating ethical decision-making in AI usage within nursing education can ensure that future nurses can provide patient-centered care while maintaining ethical values.