NursingNCT06972043
AI-Assisted Smart Interactive Healthcare Robot
A study testing Intervention Group in people with Nursing and Artificial Intelligence (AI), run by National Taiwan University Hospital at 1 site in Taiwan.
Trial summary
To address workforce shortages and increasing workloads in nursing, technological solutions and AI-powered robots for ward navigation have been introduced. However, limitations remain in their application to clinical care. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Nursing, Artificial Intelligence (AI), Deep Learning
- What is being tested?
- Intervention Group
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 160 participants
- Where
- 1 siteTaiwan
- Study dates
- 30 Apr 2025to 31 Dec 2026
- Phase
- Interventional
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
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Aged 18 years or older.
- Currently employed as a ward nurse.
- Aged 18 years or older.
- Willing to accept the "E-Nursing Assistant" intervention for care tasks that do not involve patient safety.
Who cannot join
- Nurses who do not actively participate in ward care, such as nursing unit supervisors.
- Patients/Caregivers
- Patients or caregivers who are unconscious or unable to communicate verbally or in writing to complete the research interview.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Taiwan1 site, 1 recruiting
- Recruiting
National Taiwan University Hospital
Taipei, Taiwan, 802
Yun Hsiang Lee Associate Professor, PhD, +886 978082338, yhlee338@ntu.edu.tw
About this study
Official title: Development and Testing of an AI-Assisted Smart Interactive Healthcare Robot Program
To address workforce shortages and increasing workloads in nursing, technological solutions and AI-powered robots for ward navigation have been introduced. However, limitations remain in their application to clinical care. This study aims to develop and test a programming framework for an AI-assisted nursing care robot ("E-Nursing Assistant") to reduce nurses' workload and improve the efficiency and quality of care.
Read the detailed description
In response to the challenges of workforce shortages and heavy workloads in the nursing field, clinical nursing practices are gradually integrating technological assistance, including the use of mobile phones to scan QR codes for viewing instructional videos and the introduction of robots with Artificial Intelligence (AI) technology for ward navigation. However, there are still several limitations to these technological applications in the nursing care process. Therefore, this study aims to develop and test the programming framework for an AI-assisted nursing care robot ("E-Nursing Assistant"). The goal is to reduce the workload of nursing staff and significantly improve the efficiency and quality of nursing work. The "E-Nursing Assistant" will be implemented in the ward to measure the nursing staff's workload, the time and frequency spent on specific nursing tasks, and to conduct interviews to gather their feedback.
- Conditions
- Nursing, Artificial Intelligence (AI), Deep Learning, Mechine Learning
- Being tested
- Intervention Group
- Keywords
- Nursing, Artificial Intelligence (AI), Medical Science and Technology
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Intervention GroupOther
The functions performed by the robot include guiding patients through unit-specific locations for environmental orientation and equipment usage instructions, playing educational videos related to care, reminding patients of important examination precautions, providing health education on specimen collection, and delivering responses through an expert-developed medical Q\&A system.
| Study group | Role | What they receive |
|---|---|---|
| Intervention Group | Other | The functions performed by the robot include guiding patients through unit-specific locations for environmental orientation and equipment usage instructions, playing educational videos related to care, reminding patients of important examination precautions, providing health education on specimen collection, and delivering responses through an expert-developed medical Q\&A system. Receives: Other: Intervention Group |
What is being measured
The primary outcome is the main question the study is designed to answer.
Workload-related stress in nursing staff
The investigators utilized the Nurse Stress Checklist Chinese version translated by Taiwanese scholars in 1996. The scale consists of four factors: "Personal Response," "Work Concerns," "Job Competence," and "Inability to Complete Personal Tasks." It contains a total of 43 items, each rated on a 9-point Likert scale (0 = not at all, 1 = not close, 8 = very close), with higher scores indicating greater levels of work-related stress.
Measured: It will be measured pre-intervention and immediately after the intervention.
Secondary outcomes (2)
System Usability
The investigators used the System Usability Scale (SUS) developed by scholar Brooke. The scale consists of 10 items, scored on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree). Odd-numbered items are positively worded, and the raw score for each item is subtracted by 1 to obtain the item score. Even-numbered items are reverse scored, with the item score calculated as 5 minus the raw score. The scores for all items are summed, and the total is then multiplied by 2.5 to obtain the overall SUS score, which ranges from 0 to 100. Higher scores indicate greater satisfaction with the system.
Measured: It will be measured immediately after the intervention.
Number of patients served and time spent on various nursing tasks
A self-designed table will be used to list common and repetitive nursing tasks in the ward in detail. These tasks include: ward orientation (e.g., nursing station), instructions for using ward equipment (e.g., patient beds, call bells), patient fall prevention education, reminders for various examinations (e.g., urination), health education for specimen collection (e.g., blood, urine), discharge instructions, and answering common questions from patients after viewing nursing care instructional videos. Each task will include spaces to record the number of patients served and time spent. Initially, an audio recorder will be used to measure the time, after which the researchers will calculate the start and end times, as well as any interruptions during the process, and fill in the table accordingly.
Measured: It will be measured pre-intervention and during the intervention
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted14 May 2025
- Study start30 Apr 2025
- Primary completion31 Dec 2026 (estimated)
- Study completion31 Dec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for NursingStudies of the same condition, open and under way.
- More trials run by National Taiwan University HospitalThe sponsor's other registered studies.
- 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
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- Since the robot will interact with patients or caregivers during its operation in the ward, in addition to the nursing staff completing the informed consent form, patients or caregivers will also be required to fill out a consent form.
- Masking
- None (open label)
- Enrolment
- 160 participants (estimated)
Sponsor and investigators
- Lead sponsor
- National Taiwan University Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06972043
- Sponsor's protocol ID
- 202410046RINE
- Status last verified
- Sep 2026
- First submitted
- 7 Apr 2025
- Last updated
- 14 Sep 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided