RCT Evaluates ChatGPT Teaching Model for Nursing Pain Management
Summary
Shahid Beheshti University of Medical Sciences (Tehran, Iran) is conducting a two-arm parallel-group randomized controlled trial (RCT) to evaluate the effect of a ChatGPT-driven blended teaching model on nursing students' knowledge, attitudes, competence, and learning self-efficacy in pain management. Eligible nursing students will be randomly assigned 1:1 to either the intervention group (ChatGPT-assisted blended clinical nursing rounds, 8 sessions over 4 weeks, each 90 minutes) or the control group (traditional clinical nursing rounds with no AI tools). Outcomes will be measured at baseline, immediate post-test, and 3-month follow-up using validated instruments including NKASRP, NSCS, and NLSE. This is a prospective clinical trial registration; no compliance obligations or regulatory actions are associated with this document.
“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.”
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What changed
This document is a clinical trial registration entry on ClinicalTrials.gov describing a randomized controlled trial (RCT) evaluating a ChatGPT-driven blended teaching model for pain management in nursing students. The trial will enroll eligible nursing students at Shahid Beheshti University of Medical Sciences in Tehran, Iran, assigning them 1:1 to either the intervention group (8 AI-assisted sessions over 4 weeks) or the control group (traditional clinical nursing rounds). The trial's primary outcomes are knowledge and attitudes regarding pain (NKASRP), nursing competence (NSCS), and learning self-efficacy (NLSE) measured at three timepoints.
Affected parties include nursing education institutions considering AI-assisted teaching tools, healthcare educators developing curricula, and researchers studying AI integration in clinical education. This registration provides prospective notice of the study design but does not impose compliance obligations. Institutions evaluating AI-based educational interventions may use this trial's registered protocol as a reference for similar initiatives.
Archived snapshot
Apr 28, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
ChatGPT-Driven Blended Teaching for Pain Management in Nursing Students: A Randomized Controlled Trial
N/A NCT07552363 Kind: NA Apr 27, 2026
Abstract
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).
Fi...
Conditions: Pain Management, Nursing Education, Knowledge, Attitudes, Practice
Interventions: ChatGPT-Driven Blended Teaching Model for Pain Management, Traditional Clinical Nursing Rounds
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