Pain ManagementNCT07552363
ChatGPT-Driven Blended Teaching for Pain Management in Nursing Students: A Randomized Controlled Trial
A study testing ChatGPT-Driven Blended Teaching Model for Pain Management and Traditional Clinical Nursing Rounds in people with Pain Management and Nursing Education, run by Shahid Beheshti University of Medical Sciences at 1 site in Iran.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Pain Management, Nursing Education, Knowledge, Attitudes, Practice
- What is being tested?
- ChatGPT-Driven Blended Teaching Model for Pain Management and Traditional Clinical Nursing Rounds
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 156 participants
- Where
- 1 siteIran
- Study dates
- 1 Sep 2026to 1 Jan 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- 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
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Iran1 site
Faculty of Nursing and Midwifery, Shahid Beheshti University of Medical Sciences
Tehran, Tehran Province
Sogand Sarmadi, +989198599908, sogand.sarmadi@ymail.com
sogand sarmadi
About this study
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
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.
Read more
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.
- Being tested
- ChatGPT-Driven Blended Teaching Model for Pain Management, Traditional Clinical Nursing Rounds
- Keywords
- ChatGPT, Artificial Intelligence, Blended Learning, Pain Management, Nursing Students, Clinical Competence, Randomized Controlled Trial
- Medical subject headings
- Agnosia, Behavior
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
ChatGPT-Driven Blended Teaching Model for Pain ManagementBehavioural
Also called AI-Assisted Blended 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.
Traditional Clinical Nursing RoundsBehavioural
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).
| Study group | Role | What they receive |
|---|---|---|
| ChatGPT-Driven Blended Teaching Group | Experimental | 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. Receives: Behavioral: ChatGPT-Driven Blended Teaching Model for Pain Management |
| Traditional Clinical Nursing Rounds Group | Active comparator | 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. Receives: Behavioral: Traditional Clinical Nursing Rounds |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: Baseline (1 week before intervention), immediate post-test (1 week after intervention), and 3-month follow-up
Secondary outcomes (2)
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.
Measured: 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.
Measured: Baseline (1 week before intervention), immediate post-test (1 week after intervention), and 3-month follow-up
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Apr 2026
- Study start1 Sep 2026 (estimated)
- Primary completion1 Dec 2026 (estimated)
- Study completion1 Jan 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Pain ManagementStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- Two-arm parallel-group design with 1:1 allocation ratio. Participants are randomly assigned to either a ChatGPT-driven blended teaching group or a traditional clinical nursing rounds group. Both groups receive the same number and duration of sessions (8 sessions over 4 weeks, each approximately 90 minutes) in the same clinical departments.
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 156 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Shahid Beheshti University of Medical Sciences
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Sogand Sarmadi, Shahid Beheshti University of Medical Sciences
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07552363
- Sponsor's protocol ID
- IR.SBMU.PHARMACY.REC.1405.046
- Status last verified
- Apr 2026
- First submitted
- 20 Apr 2026
- Last updated
- 27 Apr 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided: Due to privacy considerations, a final decision has not been made at this time.
Study at a glance
From the registry record, last updated by the sponsor on 27 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- 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
- ClinicalTrials.gov ID
- NCT07552363
- Acronym / sponsor ID
- IR.SBMU.PHARMACY.REC.1405.046
- Keywords
- ChatGPT, Artificial Intelligence, Blended Learning, Pain Management, Nursing Students, Clinical Competence, Randomized Controlled Trial
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 156 participants (estimated)
- Lead sponsor
- Shahid Beheshti University of Medical SciencesUniversity, hospital or other
- Study start
- 1 Sep 2026 (estimated)
- Primary completion
- 1 Dec 2026 (estimated)
- Study completion
- 1 Jan 2027 (estimated)
- First posted
- 27 Apr 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
- Model description
- Two-arm parallel-group design with 1:1 allocation ratio. Participants are randomly assigned to either a ChatGPT-driven blended teaching group or a traditional clinical nursing rounds group. Both groups receive the same number and duration of sessions (8 sessions over 4 weeks, each approximately 90 minutes) in the same clinical departments.
| Arm | Type | Receives |
|---|---|---|
| ChatGPT-Driven Blended Teaching Group | Experimental | Behavioral: ChatGPT-Driven Blended Teaching Model for Pain ManagementParticipants 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. |
| Traditional Clinical Nursing Rounds Group | Active comparator | Behavioral: Traditional Clinical Nursing RoundsParticipants 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- 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
Key exclusion criteria (3 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| ChatGPT-Driven Blended Teaching Model for Pain ManagementAlso: AI-Assisted Blended Clinical Nursing RoundsA 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. | Behavioural | ChatGPT-Driven Blended Teaching Group |
| Traditional Clinical Nursing RoundsStandard 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). | Behavioural | Traditional Clinical Nursing Rounds Group |
Primary outcome
Knowledge and Attitudes Toward Pain
Time frame: Baseline (1 week before intervention), immediate post-test (1 week after intervention), and 3-month follow-up
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.
2 secondary outcomes
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
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 27 Apr 2026.
- Individual participant dataSharing planned: Undecided. Due to privacy considerations, a final decision has not been made at this time.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing ChatGPT-Driven Blended Teaching Model for Pain Management and Traditional Clinical Nursing Rounds in people with Pain Management and Nursing Education, run by Shahid Beheshti University of Medical Sciences at 1 site in Iran.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 27 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Iran. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Sogand Sarmadi (+989198599908, sogand.sarmadi@ymail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Knowledge and Attitudes Toward Pain (time frame: Baseline (1 week before intervention), immediate post-test (1 week after intervention), and 3-month follow-up). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 27 Apr 2026; AzTrials last refreshed its copy on 26 Oct 2026.