Clinical Trial

ChatGPT-Driven Blended Teaching for Pain Management in Nursing Students: A Randomized Controlled Trial

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Summary
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.
Trial Details
NCT Number NCT07552363
Lead Sponsor Shahid Beheshti University of Medical Sciences
Conditions Pain Management, Nursing Education, Knowledge, Attitudes, Practice
Enrollment 156 participants
Start Date 2026-09-01
Primary Completion 2026-12-01 (estimated)
Study Completion 2027-01-01 (estimated)
Updated on ClinicalTrials.gov 2026-04-27