[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100635413":3},{"organization":4,"armGroups":7,"interventions":20,"overallOfficials":32,"centralContacts":33,"locations":39,"responsibleParty":57,"collaborators":32,"id":58,"slug":59,"hasResults":60,"nctId":61,"briefTitle":62,"officialTitle":63,"acronym":32,"eligibilityCriteria":64,"healthyVolunteers":65,"sex":66,"minAge":67,"maxAge":32,"enrollmentInfo":68,"targetDuration":32,"studyType":71,"phases":72,"briefSummary":74,"conditions":75,"keywords":79,"overallStatus":86,"whyStopped":32,"lastUpdateSubmitDate":87,"lastUpdatePostDateStruct":88,"startDateStruct":91,"completionDateStruct":93,"leadSponsor":95,"locationsCount":96},{"fullName":5,"class":6},"Shahid Beheshti University of Medical Sciences","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"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.",[13],"Behavioral: ChatGPT-Driven Blended Teaching Model for Pain Management",{"label":15,"type":16,"description":17,"interventionNames":18},"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.",[19],"Behavioral: Traditional Clinical Nursing Rounds",[21,28],{"type":22,"name":23,"description":24,"armGroupLabels":25,"otherNames":26},"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 outputs were reviewed by supervising faculty for accuracy. Students used pre-designed, standardized prompts based on the WHO analgesic ladder and national clinical protocols.",[9],[27],"AI-Assisted Blended Clinical Nursing Rounds",{"type":22,"name":29,"description":30,"armGroupLabels":31,"otherNames":32},"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).",[15],null,[34],{"name":35,"role":36,"phone":37,"phoneExt":32,"email":38},"Sogand Sarmadi","CONTACT","+989198599908","sogand.sarmadi@ymail.com",[40],{"facility":41,"status":32,"city":42,"state":43,"zip":32,"country":44,"countryCode":45,"cosmosGeoPoint":46,"geoPoint":51,"contacts":52},"Faculty of Nursing and Midwifery, Shahid Beheshti University of Medical Sciences","Tehran","Tehran Province","Iran","IR",{"type":47,"coordinates":48},"Point",[49,50],51.42151,35.69439,{"lat":50,"lon":49},[53,54],{"name":35,"role":36,"phone":37,"phoneExt":32,"email":38},{"name":55,"role":56,"phone":32,"phoneExt":32,"email":32},"sogand sarmadi","PRINCIPAL_INVESTIGATOR",{"type":56,"investigatorFullName":35,"investigatorTitle":5,"investigatorAffiliation":5,"oldNameTitle":32,"oldOrganization":32},"100635413","chatgpt-driven-blended-teaching-for-pain-management-in-nursing-students-a-randomized-controlled-trial-100635413",false,"NCT07552363","ChatGPT-Driven Blended Teaching for Pain Management in Nursing Students: A Randomized Controlled Trial","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","Inclusion Criteria:\n\n1. Undergraduate nursing students in their fourth semester or higher, or master's or doctoral nursing students engaged in clinical training involving direct patient care\n2. Provision of electronic informed consent\n3. Access to the internet and a personal device (computer, tablet, or smartphone) for the asynchronous components of the blended teaching model\n4. No participation in a formal comprehensive pain management course within the previous 12 months\n\nExclusion Criteria:\n\n1. Inability to attend at least one face-to-face session or to complete online activities (e.g., due to repeated absences)\n2. Any self-reported or university-documented cognitive or mental health condition that prevented completion of questionnaires or participation in training\n3. Voluntary withdrawal at any stage of the study",true,"ALL","18 Years",{"count":69,"type":70},156,"ESTIMATED","INTERVENTIONAL",[73],"NA","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.\n\nThis 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.\n\nEligible nursing students at Shahid Beheshti University of Medical Sciences (Tehran, Iran) will be randomly assigned in a 1:1 ratio to either:\n\n* 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)\n* Control group: Traditional clinical nursing rounds (same number and duration of sessions, without any AI tools)\n\nOutcomes 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).\n\nFindings 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.",[76,77,78],"Pain Management","Nursing Education","Knowledge, Attitudes, Practice",[80,81,82,76,83,84,85],"ChatGPT","Artificial Intelligence","Blended Learning","Nursing Students","Clinical Competence","Randomized Controlled Trial","NOT_YET_RECRUITING","2026-04-20",{"date":89,"type":90},"2026-04-27","ACTUAL",{"date":92,"type":70},"2026-09-01",{"date":94,"type":70},"2027-01-01",{"name":5,"class":6},1]