RNSurveyNursing open2023

Nurse preferences of caring robots: A conjoint experiment to explore most valued robot features.

Miklós Zrínyi, Annamária Pakai, Kinga Lampek and 4 others

PMID 35762116

WHAT IT FOUND

Hungarian nurses and students preferred a caring robot that follows commands, looks like a machine, operates with precision, runs a set programme without self-learning, and behaves friendly.

They strongly rejected self-learning capabilities, prioritizing human control over nursing tasks.

Key findings

01Participants ranked the robot's ability to learn as the most important feature, followed by behaviour, look, safety, and communication.

02The most preferred robot profile was one that responds only to commands, looks like a machine, is always on target, runs a fixed programme, and behaves friendly.

03Self-learning capability was the least favoured function, indicating nurses are not ready to hand over cognitive skills or decision-making to robots.

STILL TO COME

How it was doneWhat they foundWhat it means for RNs

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What it does not show

The sample consisted of Hungarian nurses and students, which may not reflect preferences in other cultural or healthcare contexts. Most participants (86.5%) had no prior experience with healthcare robots, so their preferences were based on hypothetical scenarios rather than actual use. Data collection occurred via email during the pandemic, which may have influenced response rates or engagement compared to face-to-face methods. The study did not remove extreme responses to preserve representativeness, which could affect the stability of the utility scores.

Declared interests

Authors report no conflict of interest. The study was funded by the Ministry for Innovation and Technology in Hungary.

The easy way to misread this

Do not interpret these preferences as a universal standard for robot design or a rejection of all autonomous technologies. The findings reflect the views of Hungarian nurses with little prior robot experience, and preferences may shift significantly as clinicians gain familiarity with these tools.

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