An interventional study of ChatGPT-Driven Blended Teaching Model for Pain Management and Traditional Clinical Nursing Rounds in Pain Management, Nursing Education and Knowledge, Attitudes, Practice, sponsored by Shahid Beheshti University of Medical Sciences. Not yet recruiting at 1 site in Iran. Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-04-27.
Sponsored by Shahid Beheshti University of Medical Sciences · Not applicable, Interventional, and Other
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:
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.
1,573 studies on the registry are indexed under Behavior; 313 are open to participants now.
This study's planned enrollment of 156 is above the median of 120 across 1,197 interventional studies indexed under Behavior.
Browse Behavior studies →Shahid Beheshti University of Medical Sciences is the lead sponsor of 229 studies on the registry; 19 are open to participants now.
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Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Informed consent
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Participants receive a blended teaching intervention integrating ChatGPT-assisted instruction with traditional in-person clinical nursing rounds focused on pain management. The intervention consists of 8 sessions over 4 weeks (2 sessions per week), each approximately 90 minutes, comprising three phases: pre-round preparation (30 min) using standardized ChatGPT prompts and case-based learning; bedside nursing round (30 min) with patient assessment and instructor feedback; and post-round activities (30 min) using ChatGPT to resolve uncertainties and complete case reports. Students are organized in groups of 4-6 and rotate through medical, surgical, and chronic pain clinical departments.
Behavioral: ChatGPT-Driven Blended Teaching Model for Pain Management
Participants receive traditional clinical nursing rounds without any ChatGPT or AI components. The instructor selects and introduces clinical cases; students review resources and prepare reports. During rounds, the instructor directs all activities, including case presentation, assessment, nursing diagnosis, intervention, and outcome evaluation. The control group receives an identical number and duration of sessions (8 sessions over 4 weeks, each approximately 90 minutes) in the same clinical departments to ensure exposure consistency.
Behavioral: Traditional Clinical Nursing Rounds
A 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.
Also known as: AI-Assisted Blended Clinical Nursing Rounds
Standard 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.
Time frame: Baseline (1 week before intervention), immediate post-test (1 week after intervention), and 3-month follow-up
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.
Time frame: Baseline (1 week before intervention), immediate post-test (1 week after intervention), and 3-month follow-up
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.
Time frame: Baseline (1 week before intervention), immediate post-test (1 week after intervention), and 3-month follow-up
Plan to share: Undecided — Due to privacy considerations, a final decision has not been made at this time.
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