ChatGPT-Driven Blended Teaching for Pain Management in Nursing Students: A Randomized Controlled Trial
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: ChatGPT-Driven Blended Teaching Model for Pain Management, Traditional Clinical Nursing Rounds.
- Who it may be relevant to
- Registry conditions: Pain Management, Nursing Education, Knowledge, Attitudes, Practice. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Iran
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Effect of a ChatGPT-Driven Blended Teaching Model for Pain Management on Knowledge, Attitudes, Competence, and Self-Efficacy Among Nursing Students: A Two-Arm Parallel-Group Randomized Controlled Trial
Overview
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.
Interventions
- Behavioral ChatGPT-Driven Blended Teaching Model for Pain Management
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 - Behavioral Traditional 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).
Primary outcome measures
- Knowledge and Attitudes Toward Pain [Time frame: Baseline (1 week before intervention), immediate post-test (1 week after intervention), and 3-month follow-up]
Secondary outcome measures (2)
- Nursing Competence [Time frame: Baseline (1 week before intervention), immediate post-test (1 week after intervention), and 3-month follow-up]
- Learning Self-Efficacy [Time frame: Baseline (1 week before intervention), immediate post-test (1 week after intervention), and 3-month follow-up]
Eligibility criteria
Inclusion criteria
- 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
Exclusion criteria
- 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
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Allocation
- Randomized
- Model
- Parallel assignment
- Masking
- Single blind
- Primary purpose
- Other
Study locations
Iran · 1 center
- Faculty of Nursing and Midwifery, Shahid Beheshti University of Medical Sciences — Tehran
Identifiers
NCT: NCT07552363 · IR.SBMU.PHARMACY.REC.1405.046