[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100622964":3},{"organization":4,"armGroups":7,"interventions":20,"overallOfficials":25,"centralContacts":30,"locations":25,"responsibleParty":36,"collaborators":25,"id":40,"slug":41,"hasResults":42,"nctId":43,"briefTitle":44,"officialTitle":44,"acronym":45,"eligibilityCriteria":46,"healthyVolunteers":47,"sex":48,"minAge":25,"maxAge":25,"enrollmentInfo":49,"targetDuration":25,"studyType":52,"phases":53,"briefSummary":55,"conditions":56,"keywords":58,"overallStatus":64,"whyStopped":25,"lastUpdateSubmitDate":65,"lastUpdatePostDateStruct":66,"startDateStruct":69,"completionDateStruct":71,"leadSponsor":73,"locationsCount":25},{"fullName":5,"class":6},"Chonnam National University Hospital","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"Arm 1","EXPERIMENTAL","Participants receive a Artificial Intelligence integrated Mixed Reality-based High-Alert Medications Management Simulation Program",[13],"Other: Artificial Intelligence integrated Mixed Reality-based Simulation Program",{"label":15,"type":16,"description":17,"interventionNames":18},"Arm 2","ACTIVE_COMPARATOR","Participants receive the hospital's standard medication-management education",[19],"Other: Standard medication-management education",[21,26],{"type":6,"name":22,"description":23,"armGroupLabels":24,"otherNames":25},"Artificial Intelligence integrated Mixed Reality-based Simulation Program","Participants in the intervention arm receive Artificial Intelligence integrated Mixed Reality-based High-Alert Medications Management Simulation Program",[9],null,{"type":6,"name":27,"description":28,"armGroupLabels":29,"otherNames":25},"Standard medication-management education","Participants receive the hospital's standard medication-management education (didactic lectures, case discussions, and workshops)",[15],[31],{"name":32,"role":33,"phone":34,"phoneExt":25,"email":35},"Hwigon Jeon, Ph.D. student","CONTACT","+82-10-5121-0700","tjdans779@gmail.com",{"type":37,"investigatorFullName":38,"investigatorTitle":39,"investigatorAffiliation":5,"oldNameTitle":25,"oldOrganization":25},"PRINCIPAL_INVESTIGATOR","Jinkyung Park","professor","100622964","effectiveness-of-artificial-intelligence-integrated-mixed-reality-based-high-alert-medications-management-simulation-program-100622964",false,"NCT07390461","Effectiveness of Artificial Intelligence Integrated Mixed Reality-based High-Alert Medications Management Simulation Program","AIMR-HAM","Inclusion Criteria:\n\n* Nurses with at least one to six years of clinical experience.\n\n  * Those who understand the purpose and procedures of this study and have given written consent to participate.\n\n    * Those who have no physical or cognitive limitations in using mixed reality devices.\n\n      ④ Those who are able to communicate in Korean and understand and respond to questions.\n\nExclusion Criteria:\n\n* Those who do not wish to participate in the study. ② Those who have participated in education related to high-alert medications within the past six months.\n\n  * Those who are unable or have difficulty participating in the mixed reality education program due to visual, hearing, or neurological impairments, or adverse effects such as dizziness or motion sickness.\n\n    * Those who voluntarily withdraw from the study midway through.",true,"ALL",{"count":50,"type":51},60,"ESTIMATED","INTERVENTIONAL",[54],"NA","The goal of this clinical trial is to learn if a Artificial Intelligence integrated Mixed Reality-based High-Alert Medications Management Simulation Program (AIMR-HAM) helps hospital nurses manage high-alert medicines (HAMs) more safely. MR mixes real and virtual elements to let nurses practice in realistic scenarios.\n\nThe main questions are:\n\nDoes the AIMR-HAM improve nurses' medication safety skills? Does the AIMR-HAM lower medication errors and improve clinical performance?\n\nResearchers will compare two groups to answer these questions:\n\nIntervention group: AIMR-HAM Control group: standard education only\n\nWho can take part:\n\nNurses who work at large hospitals and have 1 to 6 years of clinical experience.\n\nAbout 60 nurses will join the study.\n\nWhat participants will do:\n\nAttend the assigned training (AIMR-HAM or standard education only). Complete short tests and surveys before and after training to measure skills, communication, and clinical reasoning.\n\nReport any medication errors that occur during the study. Why this matters: The study will show whether AIMR-HAM training can improve how nurses handle HAMs and make patient care safer.",[57],"Healhty",[59,60,61,62,63],"High-alert medications","nurse","mixed reality","artificial intelligence","medication safety","NOT_YET_RECRUITING","2026-01-28",{"date":67,"type":68},"2026-02-05","ACTUAL",{"date":70,"type":51},"2026-03-04",{"date":72,"type":51},"2026-03-06",{"name":5,"class":6}]