CLINICAL_TRIALS ClinicalTrials.gov record update

EFFECT OF GENERATİVE ARTİFİCİAL INTELLİGENCE-SUPPORTED NURSİNG PROCESS EDUCATİON ON NURSİNG STUDENTS' LEARNİNG OUTCOMES: A RANDOMİZED CONTROLLED TRİAL

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Record identity and dates

Source: ClinicalTrials.gov
Source record ID: NCT07905040
Title field or adapter rule: {'original_value': "EFFECT OF GENERATİVE ARTİFİCİAL INTELLİGENCE-SUPPORTED NURSİNG PROCESS EDUCATİON ON NURSİNG STUDENTS' LEARNİNG OUTCOMES: A RANDOMİZED CONTROLLED TRİAL", 'source_field': 'protocolSection.identificationModule.officialTitle'}
Ingested At: 2026-10-31T23:27:37.028019+00:00
Published At: 2026-10-29T00:00:00+00:00
Record Updated At: 2026-10-29
Source Retrieved At: 2026-10-31T22:19:03.988133+00:00
Timestamp Basis: ClinicalTrials.gov API/RSS response retrieval timestamp recorded by Dossier adapter
Date limitation: ClinicalTrials.gov API/RSS response retrieval timestamp recorded by Dossier adapter

protocolSection.conditionsModule.conditions: ["Nursing Education", "Nursing Process", "Learning Outcome", "Generative Artificial Intelligence"]
protocolSection.statusModule.lastUpdatePostDateStruct: {"date": "2026-10-29", "type": "ACTUAL"}
protocolSection.identificationModule.nctId: "NCT07905040"
protocolSection.identificationModule.officialTitle: "EFFECT OF GENERAT\u0130VE ART\u0130F\u0130C\u0130AL INTELL\u0130GENCE-SUPPORTED NURS\u0130NG PROCESS EDUCAT\u0130ON ON NURS\u0130NG STUDENTS\u0027 LEARN\u0130NG OUTCOMES: A RANDOM\u0130ZED CONTROLLED TR\u0130AL"
protocolSection.statusModule.overallStatus: "COMPLETED"
protocolSection.designModule.phases: ["NA"]
protocolSection.statusModule.resultsFirstPostDateStruct: null

{'armGroupLabels': ['Generative AI-Supported Nursing Process Education'], 'description': 'Students used a generative AI platform for three consecutive weeks, working on one patient case per week (diabetic foot, hyponatremia, primiparous cesarean birth). Each case was analyzed through pre-defined themes and guiding prompts that covered the nursing process steps: data classification and interpretation, nursing diagnosis formulation and justification, prioritization, planning, and implementation. Students were expected to use only the prepared prompts and to report their analyses. AI-generated responses were then discussed in class for accuracy, consistency, and alignment with the nursing process steps. The intervention followed a 7-week instructor-centered theoretical course.', 'name': 'Generative AI-Supported Nursing Process Education', 'type': 'BEHAVIORAL'} (protocolSection.armsInterventionsModule.interventions[])
{'armGroupLabels': ['Case Study-Based Nursing Process Education'], 'description': 'Students completed three different patient case studies over three consecutive weeks, one per week, as part of routine instruction. Each case study was completed using concept mapping, without the use of generative AI. The intervention followed the same 7-week instructor-centered theoretical course as the intervention group.', 'name': 'Case Study-Based Nursing Process Education', 'type': 'BEHAVIORAL'} (protocolSection.armsInterventionsModule.interventions[])

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