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Factors Influencing Caregivers' Intention to Use Transfer-care Robots: A Sequential Explanatory Mixed-methods Study.

Kyungja Kang¹, Young Ae Song², Ji Yeon Park²

¹College of Nursing, Health and Nursing Research Institute, Jeju National University, Jeju, Republic of Korea.

Computers, Informatics, Nursing : CIN

|June 16, 2026

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This summary is machine-generated.

Caregiver acceptance of transfer-care robots (TCRs) is crucial for adoption. Job relevance, usefulness, and self-efficacy significantly predict TCR intention to use, highlighting the need for user-centered design.

Area of Science:

Robotics in Healthcare
Human-Computer Interaction
Caregiver Technology Adoption

Background:

Limited research exists on transfer-care robot (TCR) acceptance across diverse caregiver roles and settings.
Existing studies often focus on single professional groups or institutional environments.
A holistic perspective across the continuum of care is needed to understand technology adoption.

Purpose of the Study:

To examine the acceptance of transfer-care robots (TCRs) among nurses, personal care assistants, and family caregivers.
To identify key predictors of intention to use TCRs across various care settings (hospitals, long-term care, home care).
To explore caregiver perspectives on the benefits and requirements for successful TCR implementation.

Main Methods:

Keywords:

care assistant caregivers intention patient transfer robotics

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A sequential explanatory mixed-methods design was employed.

Quantitative survey (n=224) assessing Technology Acceptance Model constructs.

Qualitative focus group interviews (n=15) to contextualize quantitative findings.

Main Results:

Job relevance was the strongest predictor of intention to use TCRs (β=0.50, P<.001).
Perceived usefulness and self-efficacy also significantly predicted intention to use (adj. R²=.81).
Qualitative themes revealed the physical burden of transfers, need for assistance, and desire for safe, efficient, transformative robotic technology.

Conclusions:

User-centered design and workflow alignment are essential for successful TCR implementation.
Addressing caregiver needs and highlighting job relevance can enhance technology adoption.
Findings support developing informatics strategies for diverse healthcare settings to integrate robotic assistance effectively.