ASSESSMENT OF NURSING STUDENTS’ READINESS AND ATTITUDES TOWARD ARTIFICIAL INTELLIGENCE IN HEALTHCARE

Ms. Kulpooja, Ms. Neelam, Ms. Ritika Ranga, Ms. Veena S Chaudhary, Preeti

Keywords:

Artificial Intelligence, Nursing Students, Readiness, Attitudes, Healthcare, AI Education

Abstract:

Background

The rapid integration of Artificial Intelligence (AI) into healthcare is transforming clinical practices, research, and education. Nurses, being central to patient care, must adapt to AI-driven tools to optimize outcomes, ensure safety, and enhance efficiency. However, concerns exist regarding AI literacy and preparedness among nursing students, which may impact their future competency. Understanding their attitudes and readiness toward AI is crucial for developing effective educational strategies. Objectives: Assess the readiness toward AI among nursing students. Assess their attitudes toward AI. Examine the correlation between readiness and attitude. Explore associations between these variables and socio demographic factors. Methods: An analytical cross-sectional study was conducted with 350 nursing students from SGT University, Gurugram. Participants were selected via purposive sampling. Data collection involved a socio-demographic questionnaire, the Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS), and the General Attitudes towards Artificial Intelligence Scale (GAAIS). These tools measured domains such as cognition, ability, ethics, and vision, along with students’ perceptions of AI. Data analysis used descriptive statistics, correlation, and inferential tests to examine relationships. Results: Students demonstrated a moderate level of AI readiness, with higher scores in ethical and visionary domains, indicating awareness of AI’s benefits and ethical considerations. Scores in cognition and ability were lower, reflecting gaps in foundational knowledge and practical skills. Attitudes toward AI were generally positive, especially among female students and those in advanced years. Significant positive correlations existed between readiness and attitude, suggesting familiarity and competence foster more favourable perceptions. Age and year of study also significantly influenced both readiness and attitudes, with more senior students showing higher levels. These findings highlight the need to integrate structured AI education into nursing curricula to bridge knowledge gaps, enhance perceptions, and build confidence. Tailored training programs can improve nurses’ ability to utilize AI effectively, supporting improved healthcare delivery in the digital era.

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