Determinants of ChatGPT Utilization Among Banda Aceh Nurses: A UTAUT Analysis

Abstract

ChatGPT and nursing practice intersect as interactive language models offer real?time support for clinical documentation and decision making. This study examines performance expectancy, effort expectancy, social influence and facilitating conditions as predictors of ChatGPT adoption among nurses. A cross?sectional design was conducted in April 2025 with 186 registered nurses at a regional hospital in Banda Aceh, Indonesia. A modified Unified Theory of Acceptance and Use of Technology questionnaire measured key constructs on five?point Likert scales. Data were analyzed descriptively and inferentially using chi-square tests and logistic regression. Performance expectancy (p = .044), effort expectancy (p = .000), and facilitating conditions (p = .000) were all significantly associated with ChatGPT utilization. Social influence (p = .650) was excluded due to nonsignificance in preliminary tests. The facilitating conditions variable was the most significantly associated with ChatGPT utilization (p = .000), with nurses who had strong facilitating conditions being 14.27 times more likely to use ChatGPT. These findings highlight that nurses’ expectations of benefits, ease of use, and available support drive the integration of artificial intelligence in nursing. Strengthening infrastructure, providing AI utilization training, and clarifying performance benefits are recommended to promote the adoption of AI tools such as ChatGPT in nursing practice.