Pain management is a core competency in nursing practice, yet nursing students consistently demonstrate insufficient knowledge, unfavorable attitudes, limited competence, and low self-efficacy in this area. Artificial intelligence (AI)-based educational tools, particularly ChatGPT, have emerged as promising resources in nursing education; however, rigorous experimental evidence on their effectiveness remains scarce.
This study is a two-arm, parallel-group randomized controlled trial (RCT) that aims to evaluate the effect of a ChatGPT-driven blended teaching model for pain management on nursing students' knowledge and attitudes toward pain, nursing competence, and learning self-efficacy.
Eligible nursing students at Shahid Beheshti University of Medical Sciences (Tehran, Iran) will be randomly assigned in a 1:1 ratio to either:
* Intervention group: ChatGPT-assisted blended clinical nursing rounds (8 sessions over 4 weeks, each 90 minutes, combining bedside rounds with AI-assisted pre- and post-round activities) * Control group: Traditional clinical nursing rounds (same number and duration of sessions, without any AI tools)
Outcomes will be measured at baseline (1 week before intervention), immediate post-test (1 week after intervention), and 3-month follow-up using validated instruments: the Nurses' Knowledge and Attitudes Survey Regarding Pain (NKASRP), the Nursing Student Competence Scale (NSCS), and the Nursing Students' Learning Self-Efficacy instrument (NLSE).
Findings will provide empirical evidence to guide educational policy and curriculum design in nursing programs, with the goal of improving pain management education and patient care outcomes.
Undergraduate nursing students in their fourth semester or higher, or master's or doctoral nursing students engaged in clinical training involving direct patient care
Provision of electronic informed consent
Access to the internet and a personal device (computer, tablet, or smartphone) for the asynchronous components of the blended teaching model
No participation in a formal comprehensive pain management course within the previous 12 months
Inability to attend at least one face-to-face session or to complete online activities (e.g., due to repeated absences)
Any self-reported or university-documented cognitive or mental health condition that prevented completion of questionnaires or participation in training
Voluntary withdrawal at any stage of the study
Parallel
ChatGPT-Driven Blended Teaching Model for Pain Management
BehavioralA blended teaching model integrating ChatGPT with in-person clinical nursing rounds for pain management education. Delivered over 4 weeks (8 sessions × 90 minutes). Each session includes: (1) pre-round preparation using standardized ChatGPT prompts for case analysis and evidence retrieval; (2) bedside nursing rounds with pain assessment, patient education, and instructor feedback; and (3) post-round activities using ChatGPT to resolve clinical uncertainties and complete case reports. All ChatGPT outputs were reviewed by supervising faculty for accuracy. Students used pre-designed, standardized prompts based on the WHO analgesic ladder and national clinical protocols.
Traditional Clinical Nursing Rounds
BehavioralStandard clinical nursing rounds without AI tools. The instructor directs all activities including case introduction, bedside assessment, nursing diagnosis, intervention planning, and outcome evaluation. Students primarily observe and respond to instructor questions. Sessions match the intervention group in number, duration, and clinical setting (8 sessions × 90 minutes over 4 weeks).
Knowledge and Attitudes Toward Pain
Measured using the Nurses' Knowledge and Attitudes Survey Regarding Pain (NKASRP), a 39-item instrument comprising 22 true/false questions, 13 multiple-choice questions, and 2 case studies. Each correct answer scores 1 point (range: 0-39); results expressed as percentage of correct responses. Higher scores indicate better knowledge and attitudes toward pain management. A Persian forward-backward translation was performed, with face and content validity confirmed by a nursing faculty panel.
Nursing Competence
Measured using the Persian version of the Nursing Student Competence Scale (NSCS), a 28-item instrument across 6 subscales: medical-related knowledge, basic nursing skills, communication and cooperation, lifelong learning, global perspective, and critical thinking. Items rated on a 5-point Likert scale (range: 28-140). Higher scores indicate greater competence. The Persian version demonstrated Cronbach's α = 0.90 and ICC = 0.88.
Learning Self-Efficacy
Measured using the Persian version of the Nursing Students' Learning Self-Efficacy instrument (NLSE), a 21-item instrument across 5 dimensions: conceptual understanding, higher-order cognitive skills, practical work, everyday application, and nursing communication. Items rated on a 5-point Likert scale (range: 21-105). Higher scores indicate greater self-efficacy. The Persian version demonstrated Cronbach's α = 0.93 and ICC = 0.89.
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