EXPOSURE AND INTENTION OF NURSING STUDENTS TO INTEGRATE ARTIFICIAL INTELLIGENCE (AI) INTO HEALTHCARE

Abstract

The integration of Artificial Intelligence (AI) into healthcare is transforming clinical practice globally. However, a significant gap exists in understanding the preparedness of nursing students in low- and middle-income countries, like Nigeria, for this digital revolution. This study assessed the exposure to AI technologies and the intention to adopt AI in clinical practice among nursing students in Akwa Ibom State, Nigeria. Two research questions were raised to guide the study and two research hypotheses were formulated and tested. A cross-sectional survey design was employed, recruiting 400 nursing students from two accredited colleges via a multi-stage sampling technique. Data were collected using a structured, self-administered questionnaire that assessed sociodemographic characteristics, exposure to 13 AI applications, and intention to adopt AI using an 8-item scale. Data were analyzed using descriptive statistics and one-way Analysis of Variance (ANOVA) with SPSS version 26.0. Findings revealed a generally low level of exposure to AI technologies (Mean score = 8.2/13), with exposure primarily limited to basic digital tools like electronic record keeping (62.5%). Exposure to advanced AI applications, such as robot-assisted procedures (6.3%) and predictive analytics (13.8%), was minimal. However, students demonstrated a high level of intention to adopt AI, with the majority willing to undertake AI training (87.5%) and confident in their ability to adapt (83.0%). ANOVA results showed a statistically significant difference in exposure levels by year of study (p < 0.001), but no significant difference in intention to adopt AI across academic levels (p = 0.458). Despite limited practical exposure, Nigerian nursing students exhibit strong positive intentions toward adopting AI. There is an urgent need to bridge the gap between intention and competency by integrating AI education into nursing curricula and investing in the digital infrastructure of clinical training environments to prepare a future-ready nursing workforce.