[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100606160":3},{"organization":4,"armGroups":7,"interventions":20,"overallOfficials":30,"centralContacts":34,"locations":43,"responsibleParty":63,"collaborators":26,"id":66,"slug":67,"hasResults":68,"nctId":69,"briefTitle":70,"officialTitle":71,"acronym":72,"eligibilityCriteria":73,"healthyVolunteers":68,"sex":74,"minAge":75,"maxAge":26,"enrollmentInfo":76,"targetDuration":26,"studyType":79,"phases":80,"briefSummary":82,"conditions":83,"keywords":91,"overallStatus":97,"whyStopped":26,"lastUpdateSubmitDate":98,"lastUpdatePostDateStruct":99,"startDateStruct":102,"completionDateStruct":104,"leadSponsor":106,"locationsCount":107},{"fullName":5,"class":6},"Koç University","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"Artificial Intelligence Nurse (AINurse)","EXPERIMENTAL","The AI-Nurse orientation program to be implemented in the intervention group will be developed by a researcher who is part of the research team and has expertise in AI and engineering. During the development phase, the content of the program will be structured by researchers to be compatible with individual patient information. Voice-based orientation training will be provided using Google Cloud Text-to-Speech (TTS) API, which converts written text into natural-sounding speech. The training program will include approximately 10 minutes of audio narration and will be administered twice daily over a period of three days. The TTS engine allows for customization of voice parameters, including gender (female and male), speech tempo (slowed), and tone (calm). The AI Nurse system will be developed to work via mobile devices (e.g., an Android tablet). The patient will listen to the audio training through headphones and, if necessary, will be able to read the text on the screen.",[13],"Behavioral: Structured orientation program",{"label":15,"type":16,"description":17,"interventionNames":18},"Human Nurse","ACTIVE_COMPARATOR","In this arm, participants will receive a structured orientation training program designed by the researcher, consisting of 10-minute sessions over three days at similar times and frequencies. This structured orientation training will be delivered face-to-face by the Human-Nurse researcher. Patients in this group will also be monitored for signs and symptoms of delirium over three days. The content of this training program will be developed by the researchers and subsequently reviewed by experts.",[19],"Behavioral: Human Nurse",[21,27],{"type":22,"name":23,"description":24,"armGroupLabels":25,"otherNames":26},"BEHAVIORAL","Structured orientation program","Artificial intelligence technology will be incorporated into the orientation training program developed for patients in the intensive care unit who are assigned to the intervention group. The program will be administered twice daily over a three-day period. In this group, delirium-free days will be tracked, changes in anxiety and depression levels will be evaluated, and the length of intensive care unit stay among patients who remain free of delirium through this intervention will be examined.",[9],null,{"type":22,"name":15,"description":28,"armGroupLabels":29,"otherNames":26},"Researchers will administer a structured orientation training program lasting approximately 10 minutes face-to-face to participants in the control group. This training program will be administered twice daily for 3 days. Following the training program, delirium-free days, anxiety and depression scores, and length of stay in the intensive care unit will be evaluated.",[15],[31],{"name":32,"affiliation":5,"role":33},"Pelin Karaçay, Associate Professor","STUDY_DIRECTOR",[35,39],{"name":32,"role":36,"phone":37,"phoneExt":26,"email":38},"CONTACT","+90 05325475674","pkaracay@ku.edu.tr",{"name":40,"role":36,"phone":41,"phoneExt":26,"email":42},"Elif Aylin Basüt, RN,BSN","+90 5346793555","edagli17@ku.edu.tr",[44],{"facility":5,"status":26,"city":45,"state":26,"zip":46,"country":47,"countryCode":26,"cosmosGeoPoint":48,"geoPoint":53,"contacts":54},"Istanbul","34010","Turkey (Türkiye)",{"type":49,"coordinates":50},"Point",[51,52],28.94966,41.01384,{"lat":52,"lon":51},[55,57,59,61],{"name":32,"role":56,"phone":26,"phoneExt":26,"email":26},"PRINCIPAL_INVESTIGATOR",{"name":40,"role":58,"phone":26,"phoneExt":26,"email":26},"SUB_INVESTIGATOR",{"name":60,"role":58,"phone":26,"phoneExt":26,"email":26},"Polat Göktaş, Associate professor",{"name":62,"role":58,"phone":26,"phoneExt":26,"email":26},"Furkan Subaş, RN,BSN",{"type":56,"investigatorFullName":64,"investigatorTitle":65,"investigatorAffiliation":5,"oldNameTitle":26,"oldOrganization":26},"Pelin Karacay","Associate Professor","100606160","effects-of-artificial-intelligence-nurse-orientation-program-on-psychological-outcomes-and-length-of-hospital-stay-in-intensive-care-unit-100606160",false,"NCT07171944","Effects of Artificial Intelligence Nurse Orientation Program on Psychological Outcomes and Length of Hospital Stay in Intensive Care Unit","Effects of AINurse Orientation Program on Psychological Outcomes and Length of Hospital Stay: A Randomized Controlled Trial","AINURSE-OP","Inclusion Criteria:\n\n* Intensive care unit confusion assessment scale (CAM-ICU scale) score of 0-2\n* Age 18 years or older\n* Hospitalized in the intensive care unit for at least 24 hours\n* Glasgow coma scale score of 13-14-15 points\n* Richmond Agitation Sedation Scale (RASS) score between -1 and +1\n* No hearing problems\n\nExclusion Criteria:\n\n* Intensive care unit confusion assessment scale (CAM-ICU scale) score of 6-7\n* Any psychiatric illness or impaired brain function\n* Defined hearing loss\n* Advanced dementia\n* Younger than 18 years of age\n* Richmond Agitation Sedation Scale (RASS) score outside the range of -1 to +1\n* Who use sedative medication\n* History of surgery or disease around the ear","ALL","18 Years",{"count":77,"type":78},10,"ESTIMATED","INTERVENTIONAL",[81],"NA","Artificial intelligence (AI), now an integral part of healthcare services and presents numerous opportunities. Customized treatment plans, clinical decision support systems, predictive analysis for disease prevention, patient engagement and education, quality improvement, and error reduction are some of these opportunities. In the context of delirium prevention, risk assessment, and treatment planning, the AI-supported system AI-AntiDelirium is designed to standardize the approach to delirium management in alignment with the PADIS guidelines. A randomized controlled trial evaluating the effectiveness of this system found that the workload of nurses decreased, facilitated early diagnosis and prevention of delirium, and recommended evidence-based and individualized delirium interventions. A systematic review concluded that AI applications did not significantly impact the length of hospital stay and emphasized the need for further research. Also, AI platforms contributed to positive results in reducing anxiety and depression in patients. Furthermore, systematic reviews have demonstrated that AI-based chatbots are effective in alleviating symptoms of depression and anxiety. However, the literature includes a limited number of patient education programs specifically designed to prevent or manage delirium through AI-based approaches. Notably, there is a lack of studies comparing the effectiveness of AI-supported educational interventions with those delivered directly by nurses.\n\nThe goal of this clinical trial is to develop a structured AINurse and Human Nurse orientation training program for intensive care unit (ICU) patients and compare the effects of these training programs on ICU patients' delirium-free days, level of anxiety and depression, and length of stay in the ICU. Hypotheses of the study:\n\nH1: Patients who receive the structured AINurse patient orientation training program will have longer delirium-free days than patients who receive Human Nurse orientation training.\n\nH2: Patients who receive the structured AINurse patient orientation training program will have lower levels of anxiety and depression than patients who receive the Human Nurse orientation training.\n\nH3: Patients who receive the structured AINurse patient orientation training program will have shorter lengths of stay in the intensive care unit than patients who receive the Human Nurse orientation training.\n\nResearchers will compare the AINurse patient orientation training program and the orientation training program provided by human nurses in terms of patients' delirium-free days, level of anxiety and depression, and length of stay in the ICU.\n\n* Those in the intervention group will receive the AINurse orientation training program twice daily for 3 days.\n* Participants in the control group will receive face-to-face structured orientation training from researchers twice daily for 3 days.\n* Delirium-free day assessment, anxiety and depression will be evaluated for patients in both groups over 3 days.\n* The length of stay in the intensive care unit will be monitored for patients in both groups.",[84,85,86,87,88,89,90],"Delirium","Anxiety and Depression","Intensive Care Units (ICUs)","Artificial Intelligence (AI)","Nurse","Critical Care","Orientation",[84,92,93,94,95,96,88],"Artificial intelligence","Anxiety and depression","Intensive care unit","critical care","Orientation Training","NOT_YET_RECRUITING","2025-09-10",{"date":100,"type":101},"2025-09-15","ACTUAL",{"date":103,"type":78},"2025-11-01",{"date":105,"type":78},"2026-11-01",{"name":5,"class":6},1]