[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"generative-artificial-intelligence\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:generative-artificial-intelligence":31},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,3,0,[8,48,79],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":15,"eligibilityCriteria":16,"healthyVolunteers":11,"sex":17,"minAge":18,"maxAge":19,"enrollmentInfo":20,"targetDuration":4,"studyType":23,"phases":24,"briefSummary":26,"conditions":27,"keywords":32,"overallStatus":36,"whyStopped":4,"lastUpdateSubmitDate":37,"lastUpdatePostDateStruct":38,"startDateStruct":41,"completionDateStruct":43,"leadSponsor":45,"locationsCount":4},"100651560","impact-of-generative-ai-on-university-students-learning-processes-and-critical-thinking-100651560",false,"NCT07762261","Impact of Generative AI on University Students' Learning Processes and Critical Thinking","An Experimental Investigation of the Effects of Generative Artificial Intelligence-Supported Learning on University Students' Academic Success, Learning Efficiency, and Critical Thinking Skills","AI-Critical","Inclusion Criteria:\n\n* Being an active undergraduate student enrolled in the university program\u002Fcourse during the study period\n* Willingness to voluntarily participate in the study and providing written informed consent\n* Having regular access to a digital device (e.g., smartphone, laptop, tablet) and an internet connection\n* Basic digital literacy to use educational software and AI tools\n* Agreeing to complete all course activities, pre-tests, and post-test\n\nExclusion Criteria:\n\n* Prior formal or advanced training in generative AI tools (e.g., prompt engineering certification)\n* Transfer students or students repeating the course who have prior experience with the course material\n* Having cognitive, visual, or physical impairments that prevent participation in online learning or completing evaluation surveys\n* Unwillingness to participate in the study or withdrawing consent at any stage\n* Missing more than 20% of the course sessions or failing to complete the outcome assessment tools (pre-test\u002Fpost-test)","ALL","18 Months","25 Months",{"count":21,"type":22},100,"ESTIMATED","INTERVENTIONAL",[25],"NA","This study is a randomized, controlled trial with a pre-test\u002Fpost-test design, conducted to determine the effects of Generative AI (GenAI)-supported learning on academic achievement, learning efficiency, and critical thinking within a university setting. The study population consists of students from the Dialysis Program at Bingöl University's Vocational School of Health Services; the sample comprises 100 volunteer students who met the inclusion criteria and were randomly assigned to either an experimental group (n=50) or a control group (n=50). The experimental group will participate in a \"Generative AI-Supported Learning Program\" over the course of one month-meeting two days a week for a total of eight 60-minute sessions-covering topics ranging from effective prompting techniques to case analysis and academic ethics; meanwhile, the control group will continue with their routine educational activities. Data will be collected using a Demographic Information Form, the Academic Achievement Inventory, the Critical Thinking Disposition Scale, and the Artificial Intelligence Dependency Scale, and will be analyzed using biostatistical methods (t-tests, ANCOVA, and effect size calculations).",[28,29,30,31],"Education","Academic Performance","Learning Efficiency","Generative Artificial Intelligence",[31,33,34,30,35],"Artificial Intelligence in Education","Academic Success","Critical Thinking","NOT_YET_RECRUITING","2026-08-08",{"date":39,"type":40},"2026-08-13","ACTUAL",{"date":42,"type":22},"2026-09-01",{"date":44,"type":22},"2027-01-01",{"name":46,"class":47},"Ataturk University","OTHER",{"id":49,"slug":50,"hasResults":11,"nctId":51,"briefTitle":52,"officialTitle":52,"acronym":4,"eligibilityCriteria":53,"healthyVolunteers":54,"sex":17,"minAge":55,"maxAge":4,"enrollmentInfo":56,"targetDuration":4,"studyType":23,"phases":58,"briefSummary":59,"conditions":60,"keywords":63,"overallStatus":36,"whyStopped":4,"lastUpdateSubmitDate":69,"lastUpdatePostDateStruct":70,"startDateStruct":72,"completionDateStruct":74,"leadSponsor":76,"locationsCount":78},"100645426","patient-aid-for-theory-driven-health-communication-path-translating-goal-power-theory-into-an-instrument-and-generative-ai-support-for-palliative-care-communication-100645426","NCT07692711","Patient Aid for Theory-Driven Health Communication (PATH): Translating Goal-Power Theory Into an Instrument and Generative AI Support for Palliative Care Communication","Patients (Self-responding)\n\nInclusion Criteria:\n\n* Age 18 years or older.\n* Diagnosed with an advanced disease requiring consultation with outpatient palliative care clinics or home care services.\n* Able to self-complete the study questionnaires.\n\nExclusion Criteria:\n\n-None\n\nGroup 2: Caregivers (Proxy-responding) (Invited only when the patient meets the clinical criteria but is unable to self-complete the questionnaires)\n\nInclusion Criteria:\n\n* Age 18 years or older.\n* Identified as the primary family caregiver of a patient with an advanced disease requiring palliative care.\n\nExclusion Criteria:\n\n* Professional or paid caregivers.\n* Unable to complete the study questionnaires.",true,"18 Years",{"count":57,"type":22},240,[25],"The goal of this clinical trial is to learn whether an artificial intelligence (AI)-supported communication tool can help improve communication between people receiving palliative care and their healthcare providers. The study will also evaluate a new questionnaire designed to measure the quality of healthcare communication.\n\nThe main questions this study aims to answer are:\n\n1. Can the new questionnaire accurately measure the quality of communication between participants and healthcare providers?\n2. Does using the AI-supported communication tool, called NurseChat+, help participants feel more confident and prepared before meeting with their healthcare team?\n3. Does NurseChat+ improve the quality of communication during palliative care visits?\n\nResearchers will compare participants who use NurseChat+ together with their usual care to participants who receive usual care alone to see whether the tool improves communication outcomes.\n\nThe study will be conducted in three stages. First, researchers will develop and test a questionnaire that measures healthcare communication. Next, they will develop and refine the NurseChat+ tool. Finally, they will test the tool in adults receiving palliative care at National Taiwan University Hospital.\n\nParticipants in the final stage of the study will be randomly assigned to one of two groups. One group will use NurseChat+ before their scheduled medical visits in addition to receiving usual care, while the other group will receive usual care only. Participants will complete questionnaires about their communication experiences during the study.",[61,31,62],"Palliative Care","Natural Language Processing (NLP)",[64,65,66,67,68],"Randomized Controlled Trial","Health Communication","Psychometrics","Theoretical Models","Mixed Methods Research","2026-07-12",{"date":71,"type":40},"2026-07-14",{"date":73,"type":22},"2026-08-01",{"date":75,"type":22},"2030-12-31",{"name":77,"class":47},"National Taiwan University Hospital",1,{"id":80,"slug":81,"hasResults":11,"nctId":82,"briefTitle":83,"officialTitle":84,"acronym":4,"eligibilityCriteria":85,"healthyVolunteers":54,"sex":17,"minAge":55,"maxAge":86,"enrollmentInfo":87,"targetDuration":4,"studyType":23,"phases":89,"briefSummary":90,"conditions":91,"keywords":92,"overallStatus":36,"whyStopped":4,"lastUpdateSubmitDate":97,"lastUpdatePostDateStruct":98,"startDateStruct":100,"completionDateStruct":102,"leadSponsor":104,"locationsCount":4},"100607519","implementation-of-a-blended-online-and-offline-teaching-model-100607519","NCT07189611","Implementation of a Blended Online and Offline Teaching Model","A Study Protocol for Implementing a Blended Online and Offline Teaching Model Based on Generative Artificial Intelligence in the Practical Teaching of Internal Medicine Nursing: a Mixed-methods Study","Inclusion Criteria:\n\n* Nursing major students;\n* Four-year undergraduate students.\n\nExclusion Criteria:\n\n* Students who drop out midway;\n* Students whose absences accumulate to exceed 30% of the total class hours.","25 Years",{"count":88,"type":22},600,[25],"This study aims to design, implement, and evaluate a blended online and offline teaching model for Internal Medicine Nursing, integrating generative artificial intelligence (GAI), a virtual simulation platform, card-based exercises, and scenario simulation. The objective is to address key limitations of traditional teaching, including low student engagement, insufficient cultivation of clinical thinking, limited personalized learning, and a disconnect between theory and practice.\n\nA mixed-methods approach will be used. All undergraduate nursing students from the 2024 cohort at Changsha Medical University will be enrolled via convenience sampling as the experimental group to receive the new blended model. The 2023 cohort will serve as the control group, receiving traditional teaching. Quantitative data (course grades, satisfaction questionnaires) and qualitative data (semi-structured interviews) will be collected to comprehensively evaluate the model's effectiveness.\n\nExpected outcomes include improved student mastery of theoretical knowledge, enhanced practical skills and clinical thinking, increased learning interest, and higher teaching satisfaction. The study intends to provide a replicable, scalable innovative solution for nursing education reform, ultimately contributing to the training of high-quality applied nursing talents.\n\nKey problems addressed:\n\nOvercoming single-method teaching and poor interaction through GAI and gamification.\n\nEnhancing clinical thinking and decision-making via dynamic GAI cases and card-based exercises.\n\nProviding personalized learning paths and instant feedback using GAI technology.\n\nBridging the theory-practice gap with high-fidelity virtual and scenario simulations.\n\nImplementing a multi-dimensional evaluation system beyond final exams to assess comprehensive student abilities.",[31],[93,94,95,96],"generative artificial intelligence","practical teaching","Internal Medicine Nursing","blended online and offline teaching model","2025-09-19",{"date":99,"type":40},"2025-09-24",{"date":101,"type":22},"2026-01-01",{"date":103,"type":22},"2028-06-01",{"name":105,"class":47},"Hengxu Wang"]