Evidence map›Paper›PMID 40098594›Full record

ArticleJournal of advanced nursing2025

A Scoping Review on Long-Term Care Workers' Perceptions of Robot-Assisted Care for Older Adults in Long-Term Care Facilities.

Yong-Xin Ruan, Run-Ping Che, Naonori Kodate, Sarah Donnelly, Yiwen Shi, Xiaoting Liu, Sayuri Suwa, Wenwei Yu, Dexia Kong, Mei-Chun Cheung

Abstract readScoping Review
In one paragraph

Article in Journal of advanced nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Effectiveness of Group Interventions With Socially-Assistive Robots for Older Adults: A Systematic Review.Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2025
    Pooled it
  2. Article
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

10 authors.

Yong-Xin RuanDepartment of Social Work, The Chinese University of Hong Kong, Hong Kong SAR, China.ORCID https://orcid.org/0000-0002-2895-4338
Run-Ping CheDepartment of Social Work, The Chinese University of Hong Kong, Hong Kong SAR, China.
Naonori KodateSchool of Social Policy, Social Work and Social Justice, University College Dublin, Dublin, Ireland.
Sarah DonnellySchool of Social Policy, Social Work and Social Justice, University College Dublin, Dublin, Ireland.
Yiwen ShiSchool of Government, Shanghai University of Political Science and Law, Shanghai, China.
Xiaoting LiuSchool of Public Affairs, Zhejiang University, Zhejiang, China.
Sayuri SuwaGraduate School of Nursing, Chiba University, Chiba, Japan.ORCID https://orcid.org/0000-0003-3693-7455
Wenwei YuCenter for Frontier Medical Engineering, Chiba University, Chiba, Japan.
Dexia KongDepartment of Social Work, The Chinese University of Hong Kong, Hong Kong SAR, China.
Mei-Chun CheungDepartment of Social Work, The Chinese University of Hong Kong, Hong Kong SAR, China.

Funding

Department of Social Work, The Chinese University of Hong Kong 19231108National Natural Science Foundation of China 72474194
6 · The paper itself

Abstract

aimsTo synthesise the current research on long-term care workers' perceptions (i.e., attitudes, concerns, and expected functions) of robot-assisted care and their perceived effects of different types of robot-assisted care for older adults in long-term care facilities.

designScoping review. DATA SOURCES: A search was conducted in July 2024 using five databases. Articles published between 2010 and 2024 on the perceptions and/or perceived effects of robot-assisted care for older adults among frontline long-term care workers in long-term care facilities were identified. Additionally, the reference lists of the included articles were manually searched.

methodsA five-step framework that guided the development of research questions, screening of studies, and synthesis and presentation of data was adopted. Two authors independently screened and analysed the identified articles. Conflicts were resolved through joint-discussions.

resultsForty-one articles were included in the review. Data were narratively synthesised into three categories: expected function of care robots, perceived effects of robot-assisted care, and attitudes and concerns regarding robot-assisted care. Subcategories were identified and presented in tabular form.

conclusionThis review shows the physical, psychological, social, and practical benefits and limitations of different types of robot-assisted care. It also contributes to understanding long-term care workers' attitudes, concerns, and expectations regarding the function of robot-assisted care. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Having a priori discussion with long-term care workers about their expectations regarding using robot-assisted care is needed. Improvements in the design and in the digital literacy of the workers are also necessary. IMPACT: This review provides an overview of the perceptions and perceived effects of different types of robot-assisted care among care workers in long-term care facilities. The findings provide practical implications and highlight areas in need of further studies. REPORTING

methodScoping Review (PRISMA-ScR) checklist. PATIENT OR PUBLIC CONTRIBUTION: No Patient or Public Contribution.

Indexed as

Attitude of Health PersonnelHealth PersonnelLong-Term CareNursing HomesRoboticsAdultAgedAged, 80 and overFemaleHumansMaleMiddle Agedcare workerslong‐term carenursingperceived effectsperceptionsrobot‐assisted care

Identifiers

PMID40098594
PMCPMC12623707

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.