The Effect of AI-Assisted Nursing Process Training on Nursing Process Competence, Perception and Attitudes Towards Artificial Intelligence in Nurses: A Randomized Controlled Study

Overview

This study aims to determine how applied artificial intelligence (AI) training affects nurses' ability to manage the nursing process and their perceptions and attitudes toward AI technology * The nursing process is a scientific, six-stage approach used by nurses to identify patient needs and provide holistic care The research is a randomized controlled trial involving 78 nurses at Yalova Education and Research Hospital . Participants will be split into two groups: Both groups will receive standard theoretical training on the nursing process . The intervention group will receive additional specialized training on using AI tools (such as ChatGPT and Deepseek) to help create nursing care plans through practical case studies . Nurses' skills and views will be measured using specific scales before the training and one month after the intervention to evaluate the training's effectiveness * This study is expected to provide valuable insights into how AI can support clinical decision-making and help healthcare providers adapt to new technologies * The research has been approved by the Yalova University Ethics Committee (Protocol 2026/183) and will be conducted between May and December 2026

This randomized controlled, quasi-experimental study is designed to evaluate the impact of an applied artificial intelligence (AI)-supported nursing process training program on nurses' professional competence and their attitudes toward AI technology. The primary objective is to determine how the integration of AI tools into clinical decision-making affects nursing process efficiency and perception among healthcare professionals . Methodology and Randomization: The study population consists of 414 nurses working at Yalova Education and Research Hospital * Based on power analysis (power=0.95, alpha=0.05), a total of 78 nurses will be recruited and randomized into two groups: an intervention group (n=39) and a control group (n=39) * Randomization will be conducted following the collection of baseline (pre-test) data Intervention Protocol: Phase 1 (Common Foundation): Both the intervention and control groups will receive a "Theoretical Training on the Nursing Process" to ensure baseline knowledge standardization . Phase 2 (AI Training - Intervention Group only): The intervention group will receive "AI-Supported Nursing Process Theoretical Training," which includes technical guidance on using AI tools (such as ChatGPT and Deepseek) for clinical care , . Phase 3 (Practical Application - Intervention Group only): Participants will engage in hands-on workshops using structured clinical cases. They will apply AI tools to generate care plans based on NANDA-I, NIC, and NOC taxonomies * This phase includes structured debriefing and feedback sessions led by the researcher The control group will only receive the standard theoretical nursing process education and will not have access to the AI training modules until the study is completed . Data Collection and Assessment: Data will be collected using three instruments: The Nurse Information Form (demographics and AI usage habits) . The Nursing Process Competence Scale (to measure clinical workflow skills) . The Artificial Intelligence Perception and Attitude Scale (YAZAT-24) (to measure attitudes toward AI integration) , . Measurements will be conducted at two time points: baseline (pre-test) and one month following the intervention (post-test) to assess long-term retention and impact , . Statistical Analysis: Data analysis will be performed using SPSS 22.0. Normality will be assessed via the Kolmogorov-Smirnov test. Analysis will include descriptive statistics, independent samples t-test or Mann-Whitney U for group comparisons, and Repeated Measures ANOVA or Friedman tests for within-group changes over time