[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"clinical-decision-making\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:clinical-decision-making":64},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,6,0,[8,49,80,110,142,176],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":15,"eligibilityCriteria":16,"healthyVolunteers":17,"sex":18,"minAge":19,"maxAge":20,"enrollmentInfo":21,"targetDuration":4,"studyType":24,"phases":25,"briefSummary":27,"conditions":28,"keywords":30,"overallStatus":36,"whyStopped":4,"lastUpdateSubmitDate":37,"lastUpdatePostDateStruct":38,"startDateStruct":41,"completionDateStruct":43,"leadSponsor":45,"locationsCount":48},"100644395","effectiveness-of-virtual-reality-simulation-100644395",false,"NCT07663851","EFFECTIVENESS OF VIRTUAL REALITY SIMULATION","The Effectiveness of Virtual Reality Simulation in Psychiatric Nursing Students and Its Impact on Their Confidence and Anxiety Levels in Clinical Decision-Making: A Randomized Controlled Study","VR","Inclusion Criteria:\n\n* To be registered for the Psychiatric Nursing course in the 2024-2025 spring semester,\n* To be taking the Psychiatric Nursing course for the first time,\n* To attend the course regularly,\n* Not to have received any training with virtual reality simulation within the scope of the Psychiatric Nursing course before,\n* Not to have practiced in a Mental Health and Diseases clinic before\n\nExclusion Criteria:\n\n* Not registered for a Psychiatric Nursing course.\n* Having previously taken a Psychiatric Nursing course.\n* Not attending class regularly.\n* Having previously received training with a schizophrenia simulation.\n* Having previously practiced in a Mental Health and Diseases clinic.",true,"ALL","18 Years","23 Years",{"count":22,"type":23},32,"ESTIMATED","INTERVENTIONAL",[26],"NA","This randomized controlled trial aims to evaluate the effects of VRS on decision-making skills, self-confidence levels, and anxiety of psychiatric nursing students. Students participating in the study will be divided into two groups: intervention and control groups. VRS, which includes a scenario of a patient with schizophrenia, will be applied to the intervention group at the beginning of the academic term, before students start clinical practice, and in the middle of the term. The control group will be subjected to theoretical courses and clinical practice. Data will be collected using the Clinical Decision-Making, Self-Confidence, and Anxiety Scale, Personal Information Form, and Modified Simulation Effectiveness Tool. Measurements will be performed at three time points: before the simulation, in the middle of the academic term, and at the end of the academic term. In addition, debriefing sessions will be held with students participating in VRS in groups of 4-5 within the scope of the simulation process. It is expected that the findings obtained as a result of the study will make significant contributions to the literature in understanding the effects of VRS on psychiatric nursing education. At the same time, this study aims to demonstrate that this VRS, designed specifically for the Turkish language and culture, can be an effective tool to increase the self-confidence levels of psychiatric nursing students in their clinical decision-making processes and to reduce their anxiety levels within the scope of the psychiatric nursing course. The results of the study are intended to guide the development of new approaches to the use of technology in psychiatric nursing education and the integration of technology-based VRS into the psychiatric nursing curriculum.",[29],"Clinical Decision Making",[31,32,33,34,35],"virtual reality","simulation","clinical decision making","mental health nursing","students","RECRUITING","2026-06-17",{"date":39,"type":40},"2026-06-23","ACTUAL",{"date":42,"type":40},"2026-03-01",{"date":44,"type":23},"2026-07-01",{"name":46,"class":47},"Istanbul Arel University","OTHER",1,{"id":50,"slug":51,"hasResults":11,"nctId":52,"briefTitle":53,"officialTitle":54,"acronym":4,"eligibilityCriteria":55,"healthyVolunteers":11,"sex":18,"minAge":19,"maxAge":4,"enrollmentInfo":56,"targetDuration":4,"studyType":24,"phases":58,"briefSummary":59,"conditions":60,"keywords":65,"overallStatus":70,"whyStopped":4,"lastUpdateSubmitDate":71,"lastUpdatePostDateStruct":72,"startDateStruct":74,"completionDateStruct":76,"leadSponsor":78,"locationsCount":4},"100634349","the-utility-and-feasibility-of-accessible-diarrhea-etiology-prediction-tool-adept-in-an-informal-healthcare-setting-100634349","NCT07538531","The Utility and Feasibility of Accessible Diarrhea Etiology Prediction Tool (ADEPT) in an Informal Healthcare Setting","A Mobile Health Tool to Improve Antibiotics Stewardship Among Village Doctors in Bangladesh","Inclusion Criteria:\n\n* Village Doctor with antibiotic prescribing authority for children presenting with diarrheal illness\n* Practice in trial location subdistrict\n* Self-report treating a minimum of 5 pediatric diarrhea cases per week\n* Willing to participate in ADEPT training, use ADEPT in clinical practice with pediatric diarrhea patients, and to collect, via an electronic tool, data on patient characteristics and clinical management\n\nExclusion Criteria:\n\n\\- Planning to leave study site prior to completion of study",{"count":57,"type":23},30,[26],"Diarrheal disease remains a leading cause of morbidity and mortality for children under 5 globally. Accepted best practice for managing diarrhea in the absence of blood or suspicion of cholera is rehydration, however in resource poor areas antibiotics are still prescribed at high rates due to pressures such as financial incentives, caregiver expectations, and diagnostic uncertainty. Informal healthcare providers often serve as first point of care for pediatric diarrhea patients in low- and middle- income countries (LMICs) and commonly prescribe antibiotics for pediatric diarrhea at high frequencies.\n\nIn this pilot before-after feasibility trial informally trained healthcare providers will use a mobile phone-based application (Accessible Diarrhea Etiology Prediction Tool, ADEPT) which will allow for the exploration of the acceptability, feasibility, and utility of the tool, as well as ADEPTs ability to decrease inappropriate antibiotic prescribing practices.",[61,62,63,64],"Diarrhea Infectious","Algorithms","Decision Support Systems, Clinical","Clinical Decision-making",[66,67,68,69],"Diarrhea","Treatment Algorithm","mHealth","Antimicrobial stewardship","NOT_YET_RECRUITING","2026-04-13",{"date":73,"type":40},"2026-04-20",{"date":75,"type":23},"2026-04-12",{"date":77,"type":23},"2026-06-30",{"name":79,"class":47},"Daniel Leung",{"id":81,"slug":82,"hasResults":11,"nctId":83,"briefTitle":84,"officialTitle":85,"acronym":86,"eligibilityCriteria":87,"healthyVolunteers":17,"sex":88,"minAge":4,"maxAge":4,"enrollmentInfo":89,"targetDuration":91,"studyType":92,"phases":4,"briefSummary":93,"conditions":94,"keywords":97,"overallStatus":70,"whyStopped":4,"lastUpdateSubmitDate":101,"lastUpdatePostDateStruct":102,"startDateStruct":104,"completionDateStruct":106,"leadSponsor":108,"locationsCount":4},"100633491","operating-room-nurses-knowledge-of-medical-device-related-pressure-injuries-and-clinical-decision-making-skills-100633491","NCT07527377","Operating Room Nurses' Knowledge of Medical Device-Related Pressure Injuries and Clinical Decision-Making Skills","The Effect of Operating Room Nurses' Knowledge of Medical Device-Related Pressure Injuries on Clinical Decision-Making Skills: A Scenario-Based Multicenter Cross-Sectional Study","OR-MDRPI-KnowD","Inclusion Criteria:\n\n* Operating room nurses who have been working in operating rooms for at least one year Nurses who voluntarily agree to participate in the study Nurses who are able to understand and complete the data collection forms\n\nExclusion Criteria:\n\n* Nurses who withdraw from the study at any stage after providing consent Incomplete or missing data in the questionnaires","FEMALE",{"count":90,"type":23},165,"1 Day","OBSERVATIONAL","This multicenter, scenario-based cross-sectional study aims to examine the effect of operating room nurses' knowledge of medical device-related pressure injuries on their clinical decision-making skills. The study will be conducted with approximately 165 operating room nurses working in three different hospitals in Gaziantep, Türkiye. Data will be collected using a descriptive information form, a validated medical device-related pressure injury knowledge scale, and a scenario-based clinical decision-making assessment form. The study will evaluate the relationship between nurses' knowledge levels and their clinical decision-making performance, as well as identify factors influencing these outcomes. The findings are expected to contribute to improving patient safety, enhancing nursing education, and supporting evidence-based clinical decision-making in perioperative care.",[95,96],"Medical Device-Related Pressure Injuries","Clinical Decision-Making",[98,99,96,100],"Medical Device-Related Pressure Injurie","Operating Room Nurses","Pressure Injury Prevention","2026-04-07",{"date":103,"type":40},"2026-04-14",{"date":105,"type":23},"2026-04-25",{"date":107,"type":23},"2026-12-31",{"name":109,"class":47},"University of Gaziantep",{"id":111,"slug":112,"hasResults":11,"nctId":113,"briefTitle":114,"officialTitle":115,"acronym":4,"eligibilityCriteria":116,"healthyVolunteers":17,"sex":18,"minAge":4,"maxAge":4,"enrollmentInfo":117,"targetDuration":4,"studyType":24,"phases":119,"briefSummary":120,"conditions":121,"keywords":125,"overallStatus":70,"whyStopped":4,"lastUpdateSubmitDate":133,"lastUpdatePostDateStruct":134,"startDateStruct":136,"completionDateStruct":138,"leadSponsor":140,"locationsCount":48},"100623802","clinicians-trust-in-ai-based-fetal-growth-estimates-100623802","NCT07401368","Clinicians' Trust in AI-Based Fetal Growth Estimates","Clinicians' Trust and Decision-Making Using AI-Based Fetal Growth Estimates With and Without Uncertainty: A Randomized Questionnaire Study","Inclusion Criteria:\n\n* Clinicians working in obstetrics and gynecology departments.\n* Regular use of obstetric ultrasound in clinical practice.\n* Willingness to participate in a questionnaire-based study.\n\nExclusion Criteria:\n\n* Clinicians who do not perform obstetric ultrasound examinations.\n* Clinicians with a known conflict of interest related to the AI system being evaluated.",{"count":118,"type":23},308,[26],"This study examines how clinicians trust and use artificial intelligence (AI) when estimating fetal weight during pregnancy.\n\nAccurate assessment of fetal growth is important for identifying growth problems that may affect pregnancy management. New AI-based tools can estimate fetal weight from ultrasound images, but little is known about how clinicians trust these estimates or how uncertainty information influences their decisions.\n\nIn this study, clinicians will review anonymized ultrasound cases and compare fetal weight estimates generated by an AI model with traditional estimates. Some clinicians will also be shown information about the AI model's performance and uncertainty, while others will not.\n\nParticipants will be asked to choose which estimate they find most reliable, indicate their level of confidence, and decide whether they would recommend follow-up scans. The study aims to better understand how AI and uncertainty information affect clinical decision-making and trust among clinicians with different levels of experience.",[122,123,124,64],"Fetal Growth","Obstetric Ultrasonography","Pregnancy",[126,127,128,129,130,131,132],"Clinical decision-making","Artificial intelligence","Fetal weight estimation","Obstetric ultrasound","Trust","Human-AI interaction","Questionnaire study","2026-02-03",{"date":135,"type":40},"2026-02-10",{"date":137,"type":23},"2026-06-01",{"date":139,"type":23},"2028-12-01",{"name":141,"class":47},"Rigshospitalet, Denmark",{"id":143,"slug":144,"hasResults":11,"nctId":145,"briefTitle":146,"officialTitle":147,"acronym":148,"eligibilityCriteria":149,"healthyVolunteers":17,"sex":18,"minAge":19,"maxAge":4,"enrollmentInfo":150,"targetDuration":4,"studyType":24,"phases":152,"briefSummary":153,"conditions":154,"keywords":157,"overallStatus":36,"whyStopped":4,"lastUpdateSubmitDate":168,"lastUpdatePostDateStruct":169,"startDateStruct":171,"completionDateStruct":173,"leadSponsor":174,"locationsCount":48},"100620042","reasoning-enrichment-with-feedback-from-ia-in-nephrology-trial-100620042","NCT07352475","Reasoning Enrichment With Feedback From IA in NEphrology Trial","Reasoning Enhancement With Feedback From a Generative AI in Nephrology (REFINe): A Randomized Evaluation of Generative AI Support in Nephrology Diagnosis","REFINe","Inclusion Criteria:\n\nAdults aged 18 years or older.\n\nAble to read and answer clinical vignettes in English or French.\n\nAccess to a computer or smartphone with an internet connection.\n\nProvides informed consent online.\n\nParticipants are expected to have at least basic medical training (e.g., medical students, residents, fellows, or practicing clinicians), although no formal verification is required.\n\nExclusion Criteria:\n\nIndividuals under 18 years of age.\n\nInability to complete online study procedures.\n\nPrior involvement in the design, development, or evaluation of the AI system used in this study.",{"count":151,"type":23},100,[26],"The goal of this clinical trial is to learn how artificial intelligence (AI) may help doctors make diagnoses in kidney medicine. The researchers want to know whether an AI tool called a large language model (LLM) can help doctors choose the correct diagnosis more often and feel more confident in their answers.\n\nBefore starting the study, the research team tested several AI models and chose one of the best performers, a GPT-5-class model set to use high reasoning effort.\n\nThe main questions this study aims to answer are:\n\n1. Do doctors make more correct diagnoses when they can see AI suggestions?\n2. Does seeing AI suggestions change how confident doctors feel about their diagnosis?\n\nResearchers will compare doctors who receive AI suggestions with doctors who do not receive AI suggestions to see how the AI affects accuracy, confidence, and decision-making.\n\nParticipants will complete up to 10 online clinical cases. For each case, they will:\n\n1. Read a short medical scenario\n2. Suggest up to three possible diagnoses\n\n(If in the AI group) Review the AI's suggestions and decide whether to change their answer\n\nThe study will also look at how long participants take to answer each case and how the AI's performance compares to the human answers.",[155,64,156,63],"Diagnosis","Artificial Intelligence (AI) in Diagnosis",[158,159,160,161,162,163,164,165,166,167],"Large Language Model (LLM)","Generative AI","Diagnostic Accuracy","Clinical Vignettes","Online Study","Randomized Controlled Trial","Nephrology Diagnosis","AI Clinical Decision Support","Human-AI Collaboration","Medical Reasoning","2026-01-12",{"date":170,"type":40},"2026-01-20",{"date":172,"type":40},"2025-11-20",{"date":107,"type":23},{"name":175,"class":47},"University Hospital, Lille",{"id":177,"slug":178,"hasResults":11,"nctId":179,"briefTitle":180,"officialTitle":181,"acronym":4,"eligibilityCriteria":182,"healthyVolunteers":11,"sex":18,"minAge":19,"maxAge":4,"enrollmentInfo":183,"targetDuration":185,"studyType":92,"phases":4,"briefSummary":186,"conditions":187,"keywords":194,"overallStatus":70,"whyStopped":4,"lastUpdateSubmitDate":200,"lastUpdatePostDateStruct":201,"startDateStruct":203,"completionDateStruct":205,"leadSponsor":207,"locationsCount":209},"100573775","the-impact-of-de-implementing-urine-dipsticks-for-diagnosis-of-utis-in-hospitals-100573775","NCT06750666","The Impact of De-implementing Urine Dipsticks for Diagnosis of UTIs in Hospitals","The Impact of De-implementing Urine Dipsticks for Diagnosis of Urinary Tract Infections in the North Denmark Region: An Interrupted Time-series Analysis","Inclusion Criteria:\n\n* All patients admitted to emergency rooms (≥18 years) from 2019 and forward.\n\nExclusion Criteria:\n\n* Patients directly admitted to an inpatient unit without first visiting an emergency room are excluded from the study.\n* For the primary analysis, only the first admission will be included; subsequent admissions will be excluded.",{"count":184,"type":23},480000,"30 Days","The goal of this interrupted time-series analysis is to evaluate the impact of the de-implementation of urine dipsticks as a diagnostic tool for urinary tract infections (UTIs) in hospitalized patients in the North Denmark Region. The main question it aims to answer is:\n\nHow does de-implementation of urine dipsticks affect the diagnosis and management of UTIs and related disorders?\n\nSpecifically, does it change the following parameters:\n\n* Number and severity of UTI infections (lower and upper UTI, non-severe and severe)\n* Antibiotic prescription (overall, antibiotic classes, administration routes, duration, dosages)\n* Number of urine cultures and number of positive urine cultures\n* Risks of admission to intensive care units and 30-day mortality\n* Risk of drug toxicity\n* Length of hospital stay\n* Risk of admission to intensive care unit\n* 30-day risk of readmission after discharge\n* 6-month risks of Clostridioides difficile enterocolitis and de novo antimicrobial resistance in cultures obtained during routine clinical care.\n\nResearchers hypothesize that de-implementing urine dipsticks will lead to a reduced frequency of diagnosed cystitis, reduced antibiotic use, and fewer urine cultures without negatively affecting patient mortality or readmission risk.\n\nResearchers will compare the outcomes before and after the discontinuation of urine dipsticks across hospitals in the North Denmark Region. Furthermore, results will be compared to another Danish administrative healthcare region where dipsticks are still in use as well as urine culture data from the primary sector in the North Denmark Region.\n\nSince this is a registry-based observational study utilizing data from the electronic patient record system in the North Denmark Region, no direct contact will be made with participants.",[188,189,190,191,192,64,193],"Urinary Tract Infections","Diagnostic Techniques and Procedures","Point-of-Care Testing","Anti-Bacterial Agents","Registry","Urinalysis",[195,188,196,197,198,199],"Urine Dipstick De-implementation","Hospital","Registry-Based Study","Clinical Impact","urine dipsticks","2025-09-30",{"date":202,"type":40},"2025-10-01",{"date":204,"type":23},"2025-12",{"date":206,"type":23},"2026-12",{"name":208,"class":47},"Jacob Bodilsen",2]