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NCT Number: NCT06972043

AI-Assisted Smart Interactive Healthcare Robot

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.

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Key information

Conditions

Nursing Artificial Intelligence (AI) Deep Learning Mechine Learning

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

National Taiwan University Hospital

Taipei, Taiwan, 802

Location status: Recruiting

Location contact

Yun Hsiang Lee Associate Professor, PhD

CONTACT

[email protected]

+886 978082338

About this study

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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

  • Nurse

Inclusion criteria

  • Aged 18 years or older.
  • Currently employed as a ward nurse.

Exclusion criteria

  • Nurses who do not actively participate in ward care, such as nursing unit supervisors.
  • Patients/Caregivers

Inclusion criteria

  • Aged 18 years or older.
  • Willing to accept the "E-Nursing Assistant" intervention for care tasks that do not involve patient safety.

Exclusion criteria

  • Patients or caregivers who are unconscious or unable to communicate verbally or in writing to complete the research interview.

Treatment and study plan

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.

Primary outcomes

  1. Workload-related stress in nursing staff

    Time frame: It will be measured pre-intervention and immediately after the intervention.

    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.

Secondary outcomes

  1. System Usability

    Time frame: It will be measured immediately after the intervention.

    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.

  2. Number of patients served and time spent on various nursing tasks

    Time frame: It will be measured pre-intervention and during the intervention

    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.

Study contacts

Contact information is provided by the study sponsor or research team.

Yun-Hsiang Lee Associate Professor, PhD

CONTACT

[email protected]

+886 978082338 ext. 288424

Sponsors and collaborators

Lead sponsor

National Taiwan University Hospital

Other

Registry information

Official study title

Development and Testing of an AI-Assisted Smart Interactive Healthcare Robot Program

Important dates

Study start
2025
Primary completion
2025
Study completion
2026
First posted
May 14, 2025
Registry last updated
May 14, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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