Evidence map›Paper›PMID 41783288›Full record

ArticleDigital health

N-UNRAQ: Psychometric testing of the modified nursing Users' Needs, Requirements, and Abilities Questionnaire for care robots in long-term care.

Katie Trainum, Karen Johnson, Bo Xie, Elizabeth Heitkemper, Elliott Hauser

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Katie TrainumSchool of Nursing, University of Texas at Austin, Austin, TX, USA.ORCID https://orcid.org/0000-0002-0996-1006
Karen JohnsonSchool of Nursing, University of Texas at Austin, Austin, TX, USA.
Bo XieSchool of Nursing, University of Texas at Austin, Austin, TX, USA.ORCID https://orcid.org/0000-0002-6016-6008
Elizabeth HeitkemperSchool of Nursing, University of Texas at Austin, Austin, TX, USA.
Elliott HauserSchool of Information, University of Texas at Austin, Austin, TX, USA.ORCID https://orcid.org/0000-0002-2547-0952

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: As care robots become increasingly common in long-term care (LTC), understanding the perceptions of those who provide patient care is critical to ensure technology aligns with workforce needs and enhances care. Methods: This cross-sectional study aimed to modify the Users' Needs, Requirements, and Abilities Questionnaire (UNRAQ) for LTC nursing staff in the United States and conduct initial psychometric testing. The modified instrument (N-UNRAQ) expands the original assistive role and social aspects domains into three subdomains (facility, staff, robot) and adds three LTC-specific assistive tasks (transferring/lifting, administering medications, and assisting with activities of daily living). Electronic surveys were distributed to nursing staff across a random sample of LTC facilities in Central Texas. Results: Responses from 122 staff across 28 LTC facilities were analyzed to assess reliability and validity. Results demonstrated excellent internal consistency across domains and the full questionnaire, with partial support for construct validity. Findings suggest that technological experience, rather than prior robot familiarity, influenced perceptions. Limited response variability in facility and staff domains suggested a ceiling effect that may constrain discrimination. Participants rated assistive and social tasks as important to their roles and facilities but expressed neutral attitudes toward robots performing them. Environmental monitoring and reminders were rated most favorably, while physical assistance tasks were rated less positively, suggesting staff are more comfortable with indirect rather than hands-on robot support. Conclusions: The N-UNRAQ offers a reliable tool for assessing nursing staff perceptions of care robots. Future work should refine the instrument and validate it across broader contexts.

Indexed as

assisted livinglong-term carenursingnursing homeolder adultspsychometric propertiesRobots

Identifiers

PMID41783288
PMCPMC12953973

What Socratic holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.