DeliriumAINURSE-OPNCT07171944
Effects of Artificial Intelligence Nurse Orientation Program on Psychological Outcomes and Length of Hospital Stay in Intensive Care Unit
A study testing Structured orientation program and Human Nurse in people with Delirium and Anxiety and Depression, run by Koç University at 1 site in Turkey (Türkiye).
Trial summary
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… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Delirium, Anxiety and Depression, Intensive Care Units (ICUs)
- What is being tested?
- Structured orientation program and Human Nurse
- Type of treatment
- Pill or oral medicine, Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 10 participants
- Where
- 1 siteTurkey (Türkiye)
- Study dates
- 1 Nov 2025to 1 Nov 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Intensive care unit confusion assessment scale (CAM-ICU scale) score of 0-2
- Age 18 years or older
- Hospitalized in the intensive care unit for at least 24 hours
- Glasgow coma scale score of 13-14-15 points
- Richmond Agitation Sedation Scale (RASS) score between -1 and +1
- No hearing problems
Who cannot join
- Intensive care unit confusion assessment scale (CAM-ICU scale) score of 6-7
- Any psychiatric illness or impaired brain function
- Defined hearing loss
- Advanced dementia
- Younger than 18 years of age
- Richmond Agitation Sedation Scale (RASS) score outside the range of -1 to +1
- Who use sedative medication
- History of surgery or disease around the ear
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Turkey (Türkiye)1 site
Koç University
Istanbul, 34010
Pelin Karaçay, Associate Professor
Elif Aylin Basüt, RN,BSN
About this study
Official title: Effects of AINurse Orientation Program on Psychological Outcomes and Length of Hospital Stay: A Randomized Controlled Trial
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.
The 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:
Read more
H1: Patients who receive the structured AINurse patient orientation training program will have longer delirium-free days than patients who receive Human Nurse orientation training.
H2: 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.
H3: 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.
Researchers 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.
- Those in the intervention group will receive the AINurse orientation training program twice daily for 3 days.
- Participants in the control group will receive face-to-face structured orientation training from researchers twice daily for 3 days.
- Delirium-free day assessment, anxiety and depression will be evaluated for patients in both groups over 3 days.
- The length of stay in the intensive care unit will be monitored for patients in both groups.
Read the detailed description
The study is planned to be conducted in the adult intensive care unit of University Hospital, a tertiary care hospital in Türkiye. The general intensive care unit (GICU) of University Hospital has 16 beds and the cardiovascular surgery intensive care unit (CVSICU) has eight beds. The hospital where the study will be conducted has a total of 1950 patient admissions annually, 1500 in the GICU, and 450 adult patients in the CVSICU.
This study is designed as a single-center, randomized controlled experimental study. Although there are no similar studies available for calculating the sample size for this study, a pilot study with 10 patients will be conducted. Following the pilot study, the sample size will be calculated using G-Power analysis.
Recruitment, randomisation and blinding:
A computer-assisted simple randomization method will be used to assign eligible participants to study groups. The randomization process will be performed by a statistician independent of the researcher and communicated to the researcher. The website "https://www.random.org/integer-sets" will be used for this purpose.
Study Intervention:
The study consists of four stages;
Phase 1: Development of the Structured Orientation Program:
Structured orientation training programs will be developed by the researchers for both AI Nurse and Human Nurse interventions based on the literature. While the AINurse training program will be implemented in the experimental group, the Human Nurse training program will be implemented in the control group. The content of the structured training program for both groups will be the same. The training content will be sent to the opinion of 10 experts who are experts in intensive care and AI, and changes will be made in the training program.
In the AINurse training program, the training text will be written in a patient-friendly language to enhance comprehensibility. The Narrative Orientation Experience model will be used not only to deliver information but also to support the patient's psychosocial adaptation to the intensive care environment. Within this method, key information such as time, place, care environment, relatives, and daily routine will be presented in the form of a scenario format in a "starting the day story" in which the patient is addressed by name to foster a sense of personal connection and orientation.
Phase 2: Development of AI-Nurse orientation program/software:
The AI-Nurse orientation program to be implemented in the intervention group will be developed by a researcher with expertise in AI and engineering, who is also part of the study team. During the development phase, the content of the program will be structured by the researchers to be compatible with individual patient information. Voice-based orientation training will be delivered using the Google Cloud Text-to-Speech (TTS) API, which enables the conversion of written text into natural-sounding speech. The TTS engine allows for customization of voice parameters, including gender (female and male), speech tempo (slowed), and tone (calm). For Turkish language output, the use of 'tr-TR-Wavenet-A' or 'tr-TR-Standard-B' voice models is recommended. The training content can be personalized, with relevant information about the patient, weather, and family-related data will be automatically retrieved from the database. 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.
The training program will include approximately 10 minutes of audio narration and will be administered twice daily over a period of three days. Existing orientation practices in the hospital will be observed and documented. During this observation, all elements of nurse-patient interaction, such as whether the nurse introduces herself/himself, whether she/he gives day information, and whether she/he provides information about the environment, will be detailed. The control group will receive a researcher-designed orientation training program of similar duration and frequency, comprising 10-minute sessions delivered over three consecutive days.
Phase 3: Piloting the AI-Nurse orientation training program: The developed AI-Nurse training program will be conducted as a pilot study with 10 patients hospitalized in the ICU. A sample calculation will be made as a result of the pilot study. Patients included in the pilot study will not be included in the sample.
Phase 4: Implementation of structured orientation training to intervention and experimental group:
In the experimental group, the structured AI-Nurse orientation program will be listened to twice daily (10:00 and 14:00) through a headset connected to a structured audio recording application. The content will include orientation to time and environment, but will exclude any personally identifiable information such as the patient's name. Following each orientation session, the daily news will be played with the help of the television in the patient's room (at 10:30-14:30), aiming to enhance environmental awareness and perception of real-time audio streaming. The TTS engines to be used will be able to provide real-time audio streaming. This intervention will be implemented by the same researcher over a three-day period. Anxiety and depression levels, as well as the CAM-ICU score, will be assessed both before and after the intervention. After three days of structured AI-Nurse training, the patient's discharge time from the ICU will be followed and recorded. In the control group, the structured orientation training will be given face-to-face by the Human-Nurse researcher. The patient in this group will also be monitored for signs and symptoms of delirium for three days. Anxiety and depression levels will be measured prior to the intervention, while post-intervention evaluations will include the number of delirium-free days, anxiety and depression scores, and length of stay in the ICU.
Data Collection Instruments: Data will be collected using the sociodemographic characteristics form, a clinical patient information form, the Confusion Assessment Method-Intensive Care Unit (CAM-ICU), and the Hospital Anxiety and Depression Scale (HADS). In the initial stage, patients will be screened for the presence of delirium using the CAM-ICU.
- Conditions
- Delirium, Anxiety and Depression, Intensive Care Units (ICUs), Artificial Intelligence (AI), Nurse, Critical Care
- Being tested
- Structured orientation program, Human Nurse
- Keywords
- Delirium, Artificial intelligence, Anxiety and depression, Intensive care unit, critical care, Orientation Training, Nurse
- Medical subject headings
- Delirium, Anxiety Disorders, Depression, Orientation, Spatial
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Structured orientation programBehavioural
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.
Human NurseBehavioural
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.
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: Behavioral: Structured orientation program |
| 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. Receives: Behavioral: Human Nurse |
What is being measured
The primary outcome is the main question the study is designed to answer.
Delirium-free days
The Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) scale will be used to assess delirium-free days. CAM-ICU is utilized to assess the presence of delirium in critically ill patients. The CAM-ICU evaluates four key features in critically ill patients: (1) acute onset or fluctuating course of mental status, (2) inattention, (3) altered level of consciousness, and (4) disorganized thinking. A positive diagnosis of delirium is made when the first two criteria are present, along with either the third or fourth. The scale yields a total score ranging from 0 to 7, with interpretive cut-off points as follows: 0-2 indicating no delirium, 3-5 suggesting mild to moderate delirium, and 6-7 indicating severe delirium.
Measured: Before randomization, patients will be screened for delirium before being selected for the study.Patients scoring between 0 and 2 points will be included in the study. Subsequently, patients will be monitored for 3 days, with delirium assessed twice day.
Secondary outcomes (2)
Level of anxiety and depression
Anxiety and depression, which can trigger delirium in patients, are assessed using the Hospital Anxiety and Depression Scale (HADS). HADS assesses the severity and risk of anxiety and depression in hospitalized patients. The scale consists of 14 items in a 4-point Likert format.Items 1, 3, 5, 6, 8, 10, 11, and 13 are reverse scored (3, 2, 1, 0), while items 2, 4, 7, 9, 12, and 14 are scored progressively (0, 1, 2, 3). Subscale scores are obtained by summing the relevant items: questions 1, 3, 5, 7, 9, 11, and 13 for the anxiety subscale (HAD-A), and questions 2, 4, 6, 8, 10, 12, and 14 for the depression subscale (HAD-D). In the Turkish adaptation, the cut-off scores were identified as 10/11 for the anxiety subscale and 7/8 for the depression subscale. Scores exceeding these thresholds indicate a risk of clinically significant anxiety or depression.
Measured: It will be evaluated before and after the training for three days.
Length of stay in the intensive care unit
Patients will be followed up until discharge after the application to examine the effect of the planned Human Nurse and AINurse training on the length of stay in the intensive care unit.
Measured: From the date of first randomization until discharge from the ICU , assessed up to 60 days or date of death from any cause (whichever came first)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted15 Sep 2025
- Study start1 Nov 2025 (estimated)
- Primary completion1 Nov 2026 (estimated)
- Study completion1 Nov 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (4)Papers the sponsor has linked to this study.
- Other trials for DeliriumStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- In the experimental group, the structured AI-Nurse orientation program will be listened to twice daily (10:00 and 14:00) through a headset connected to a structured audio recording application. The content will include orientation to time and environment but will exclude any personally identifiable information such as the patient's name. Following each orientation session, the daily news will be played with the help of the television in the patient's room (at 10:30-14:30), aiming to enhance environmental awareness and perception of real-time audio streaming. In the control group, the structured orientation training will be given face-to-face by the Human-Nurse researcher. The patient in this group will also be monitored for signs and symptoms of delirium for three days.
- Masking
- Single blind
- Who is masked
- Participant
- Enrolment
- 10 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Koç University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Pelin Karacay, Koç University
- Investigators
- Pelin Karaçay, Associate Professor, Study director, Koç University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07171944
- Sponsor's protocol ID
- 2025.258.IRB2.124
- Acronym
- AINURSE-OP
- Status last verified
- Sep 2025
- First submitted
- 2 Sep 2025
- Last updated
- 15 Sep 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Sadeh-Sharvit S, Camp TD, Horton SE, Hefner JD, Berry JM, Grossman E, Hollon SD. Effects of an Artificial Intelligence Platform for Behavioral Interventions on Depression and Anxiety Symptoms: Randomized Clinical Trial. J Med Internet Res. 2023 Jul 10;25:e46781. doi: 10.2196/46781.
PubMed 37428547Zhang S, Ding S, Cui W, Li X, Wei J, Wu Y. Evaluating the effectiveness of a clinical decision support system (AI-Antidelirium) to improve Nurses' adherence to delirium guidelines in the intensive care unit. Intensive Crit Care Nurs. 2025 Apr;87:103933. doi: 10.1016/j.iccn.2024.103933. Epub 2025 Jan 8.
PubMed 39787945Khalifa, M., Albadawy, M., & Iqbal, U. (2024). Advancing clinical decision support: The role of artificial intelligence across six domains. Computer Methods and Programs in Biomedicine Update, 5, 100142. Doi: doi.org/10.1016/j.cmpbup.2024.100142
Wubineh BZ, Deriba FG, Woldeyohannis MM. Exploring the opportunities and challenges of implementing artificial intelligence in healthcare: A systematic literature review. Urol Oncol. 2024 Mar;42(3):48-56. doi: 10.1016/j.urolonc.2023.11.019. Epub 2023 Dec 14.
PubMed 38101991
Study at a glance
From the registry record, last updated by the sponsor on 15 Sep 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Effects of AINurse Orientation Program on Psychological Outcomes and Length of Hospital Stay: A Randomized Controlled Trial
- ClinicalTrials.gov ID
- NCT07171944
- Acronym / sponsor ID
- AINURSE-OP / 2025.258.IRB2.124
- Conditions
- Delirium, Anxiety and Depression, Intensive Care Units (ICUs), Artificial Intelligence (AI), Nurse, Critical Care
- Keywords
- Delirium, Artificial intelligence, Anxiety and depression, Intensive care unit, critical care, Orientation Training, Nurse
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 10 participants (estimated)
- Lead sponsor
- Koç UniversityUniversity, hospital or other
- Study start
- 1 Nov 2025 (estimated)
- Primary completion
- 1 Nov 2026 (estimated)
- Study completion
- 1 Nov 2026 (estimated)
- First posted
- 15 Sep 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
The 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:
H1: Patients who receive the structured AINurse patient orientation training program will have longer delirium-free days than patients who receive Human Nurse orientation training.
H2: 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.
H3: 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.
Researchers 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.
- Those in the intervention group will receive the AINurse orientation training program twice daily for 3 days.
- Participants in the control group will receive face-to-face structured orientation training from researchers twice daily for 3 days.
- Delirium-free day assessment, anxiety and depression will be evaluated for patients in both groups over 3 days.
- The length of stay in the intensive care unit will be monitored for patients in both groups.
Detailed description
The study is planned to be conducted in the adult intensive care unit of University Hospital, a tertiary care hospital in Türkiye. The general intensive care unit (GICU) of University Hospital has 16 beds and the cardiovascular surgery intensive care unit (CVSICU) has eight beds. The hospital where the study will be conducted has a total of 1950 patient admissions annually, 1500 in the GICU, and 450 adult patients in the CVSICU.
This study is designed as a single-center, randomized controlled experimental study. Although there are no similar studies available for calculating the sample size for this study, a pilot study with 10 patients will be conducted. Following the pilot study, the sample size will be calculated using G-Power analysis.
Recruitment, randomisation and blinding:
A computer-assisted simple randomization method will be used to assign eligible participants to study groups. The randomization process will be performed by a statistician independent of the researcher and communicated to the researcher. The website "https://www.random.org/integer-sets" will be used for this purpose.
Study Intervention:
The study consists of four stages;
Phase 1: Development of the Structured Orientation Program:
Structured orientation training programs will be developed by the researchers for both AI Nurse and Human Nurse interventions based on the literature. While the AINurse training program will be implemented in the experimental group, the Human Nurse training program will be implemented in the control group. The content of the structured training program for both groups will be the same. The training content will be sent to the opinion of 10 experts who are experts in intensive care and AI, and changes will be made in the training program.
In the AINurse training program, the training text will be written in a patient-friendly language to enhance comprehensibility. The Narrative Orientation Experience model will be used not only to deliver information but also to support the patient's psychosocial adaptation to the intensive care environment. Within this method, key information such as time, place, care environment, relatives, and daily routine will be presented in the form of a scenario format in a "starting the day story" in which the patient is addressed by name to foster a sense of personal connection and orientation.
Phase 2: Development of AI-Nurse orientation program/software:
The AI-Nurse orientation program to be implemented in the intervention group will be developed by a researcher with expertise in AI and engineering, who is also part of the study team. During the development phase, the content of the program will be structured by the researchers to be compatible with individual patient information. Voice-based orientation training will be delivered using the Google Cloud Text-to-Speech (TTS) API, which enables the conversion of written text into natural-sounding speech. The TTS engine allows for customization of voice parameters, including gender (female and male), speech tempo (slowed), and tone (calm). For Turkish language output, the use of 'tr-TR-Wavenet-A' or 'tr-TR-Standard-B' voice models is recommended. The training content can be personalized, with relevant information about the patient, weather, and family-related data will be automatically retrieved from the database. 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.
The training program will include approximately 10 minutes of audio narration and will be administered twice daily over a period of three days. Existing orientation practices in the hospital will be observed and documented. During this observation, all elements of nurse-patient interaction, such as whether the nurse introduces herself/himself, whether she/he gives day information, and whether she/he provides information about the environment, will be detailed. The control group will receive a researcher-designed orientation training program of similar duration and frequency, comprising 10-minute sessions delivered over three consecutive days.
Phase 3: Piloting the AI-Nurse orientation training program: The developed AI-Nurse training program will be conducted as a pilot study with 10 patients hospitalized in the ICU. A sample calculation will be made as a result of the pilot study. Patients included in the pilot study will not be included in the sample.
Phase 4: Implementation of structured orientation training to intervention and experimental group:
In the experimental group, the structured AI-Nurse orientation program will be listened to twice daily (10:00 and 14:00) through a headset connected to a structured audio recording application. The content will include orientation to time and environment, but will exclude any personally identifiable information such as the patient's name. Following each orientation session, the daily news will be played with the help of the television in the patient's room (at 10:30-14:30), aiming to enhance environmental awareness and perception of real-time audio streaming. The TTS engines to be used will be able to provide real-time audio streaming. This intervention will be implemented by the same researcher over a three-day period. Anxiety and depression levels, as well as the CAM-ICU score, will be assessed both before and after the intervention. After three days of structured AI-Nurse training, the patient's discharge time from the ICU will be followed and recorded. In the control group, the structured orientation training will be given face-to-face by the Human-Nurse researcher. The patient in this group will also be monitored for signs and symptoms of delirium for three days. Anxiety and depression levels will be measured prior to the intervention, while post-intervention evaluations will include the number of delirium-free days, anxiety and depression scores, and length of stay in the ICU.
Data Collection Instruments: Data will be collected using the sociodemographic characteristics form, a clinical patient information form, the Confusion Assessment Method-Intensive Care Unit (CAM-ICU), and the Hospital Anxiety and Depression Scale (HADS). In the initial stage, patients will be screened for the presence of delirium using the CAM-ICU.
Study design
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (participant)
- Number of arms
- 2
- Model description
- In the experimental group, the structured AI-Nurse orientation program will be listened to twice daily (10:00 and 14:00) through a headset connected to a structured audio recording application. The content will include orientation to time and environment but will exclude any personally identifiable information such as the patient's name. Following each orientation session, the daily news will be played with the help of the television in the patient's room (at 10:30-14:30), aiming to enhance environmental awareness and perception of real-time audio streaming. In the control group, the structured orientation training will be given face-to-face by the Human-Nurse researcher. The patient in this group will also be monitored for signs and symptoms of delirium for three days.
| Arm | Type | Receives |
|---|---|---|
| Artificial Intelligence Nurse (AINurse) | Experimental | Behavioral: Structured orientation programThe 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. |
| Human Nurse | Active comparator | Behavioral: Human NurseIn 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (6 listed)
- Intensive care unit confusion assessment scale (CAM-ICU scale) score of 0-2
- Age 18 years or older
- Hospitalized in the intensive care unit for at least 24 hours
- Glasgow coma scale score of 13-14-15 points
- Richmond Agitation Sedation Scale (RASS) score between -1 and +1
Key exclusion criteria (8 listed)
- Intensive care unit confusion assessment scale (CAM-ICU scale) score of 6-7
- Any psychiatric illness or impaired brain function
- Defined hearing loss
- Advanced dementia
- Younger than 18 years of age
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Structured orientation programArtificial 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. | Behavioural | Artificial Intelligence Nurse (AINurse) |
| Human NurseResearchers 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. | Behavioural | Human Nurse |
Primary outcome
Delirium-free days
Time frame: Before randomization, patients will be screened for delirium before being selected for the study.Patients scoring between 0 and 2 points will be included in the study. Subsequently, patients will be monitored for 3 days, with delirium assessed twice day.
The Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) scale will be used to assess delirium-free days. CAM-ICU is utilized to assess the presence of delirium in critically ill patients. The CAM-ICU evaluates four key features in critically ill patients: (1) acute onset or fluctuating course of mental status, (2) inattention, (3) altered level of consciousness, and (4) disorganized thinking. A positive diagnosis of delirium is made when the first two criteria are present, along with either the third or fourth. The scale yields a total score ranging from 0 to 7, with interpretive cut-off points as follows: 0-2 indicating no delirium, 3-5 suggesting mild to moderate delirium, and 6-7 indicating severe delirium.
2 secondary outcomes
Level of anxiety and depression
Time frame: It will be evaluated before and after the training for three days.
Length of stay in the intensive care unit
Time frame: From the date of first randomization until discharge from the ICU , assessed up to 60 days or date of death from any cause (whichever came first)
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 Sep 2025.
- Results publication: PubMed 37428547Sadeh-Sharvit S, Camp TD, Horton SE, Hefner JD, Berry JM, Grossman E, Hollon SD. Effects of an Artificial Intelligence Platform for Behavioral Interventions on Depression and Anxiety Symptoms: Randomized Clinical Trial. J Med Internet Res. 2023 Jul 10;25:e46781. doi: 10.2196/46781.
- Results publication: PubMed 39787945Zhang S, Ding S, Cui W, Li X, Wei J, Wu Y. Evaluating the effectiveness of a clinical decision support system (AI-Antidelirium) to improve Nurses' adherence to delirium guidelines in the intensive care unit. Intensive Crit Care Nurs. 2025 Apr;87:103933. doi: 10.1016/j.iccn.2024.103933. Epub 2025 Jan 8.
- Results publicationKhalifa, M., Albadawy, M., & Iqbal, U. (2024). Advancing clinical decision support: The role of artificial intelligence across six domains. Computer Methods and Programs in Biomedicine Update, 5, 100142. Doi: doi.org/10.1016/j.cmpbup.2024.100142
- Results publication: PubMed 38101991Wubineh BZ, Deriba FG, Woldeyohannis MM. Exploring the opportunities and challenges of implementing artificial intelligence in healthcare: A systematic literature review. Urol Oncol. 2024 Mar;42(3):48-56. doi: 10.1016/j.urolonc.2023.11.019. Epub 2023 Dec 14.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Pelin Karaçay, Associate Professor study director
Koç University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Structured orientation program and Human Nurse in people with Delirium and Anxiety and Depression, run by Koç University at 1 site in Turkey (Türkiye).
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 8 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 15 Sep 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Turkey (Türkiye). Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Pelin Karaçay, Associate Professor (+90 05325475674, pkaracay@ku.edu.tr), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Delirium-free days (time frame: Before randomization, patients will be screened for delirium before being selected for the study.Patients scoring between 0 and 2 points will be included in the study. Subsequently, patients will be monitored for 3 days, with delirium assessed twice day.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07171944, which also lists 4 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 15 Sep 2025.