O-12 Knowledge and attitudes of registered nurses towards artificial intelligence at a national hospital in Antigua

Methods: A cross-sectional survey was conducted among registered nurses at a public hospital in Antigua using a structured questionnaire comprising Likert-scale items. A convenience sample of 179 eligible nurses was invited to participate. Ordinal logistic regression was used to identify predictors of selected attitudes. Differences in perceived AI competency needs between student, practicing and academic nurses were examined using Cochran’s Q and McNemar tests.

Results: Eighty-six nurses responded (response rate 48.1%) mean age 37.6 years. Only (34.9%) nurses reported awareness of AI applications in nursing practice. Television/radio (81.4%) and social media (80.2%) were more common sources of information, on speech to text applications, when compared to educational institutions (27.9%) or the workplace (16.3%). Only 13.9% believed that AI would replace human nurses. Nurses with diploma/associate’s degrees were less likely than those with bachelor’s/master’s degree to perceive automated identification of care interventions as a useful application of AI (OR = 0.27, 95% CI 0.11, 0.64). Nurses with 21 years’ experience to believe AI will replace members of the interprofessional healthcare team (OR = 0.28, 95% CI 0.09, 0.82), and nurses with 11–15 years’ experience were more likely to agree that AI will replace them compared to nurses with >21 years’ experience (OR 4.66, 95% CI 1.08, 19.90). Practicing and academic nurses were perceived to require greater AI competencies than student nurses (p<0.05).

Conclusion: Surveyed nurses in Antigua demonstrated limited awareness of AI in nursing practice but generally supported its integration and expressed low concern about workforce replacement. Targeted AI education and competency development is needed.