Evidence map›Paper›PMID 41140795›Full record

ArticleInnovation in aging2025

The attitudes and acceptance of functional assistive robots among older adults with disabilities: a mixed-methods study.

Yilin Wang, Hongxiu Chen, Hong Cheng, Jing Qiu, Rui Huang, Chaobin Zou, Guangkui Song, Menghong Liu, Qian Liu, Jiali Zhang and 1 more

Abstract read
In one paragraph

Article in Innovation in aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  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

11 authors.

Yilin WangInnovation Centre of Nursing Research and Nursing Key Laboratory of Sichuan Province, West China Hospital, Sichuan University/West China School of Nursing, Sichuan University, Chengdu, China.
Hongxiu ChenInnovation Centre of Nursing Research and Nursing Key Laboratory of Sichuan Province, West China Hospital, Sichuan University/West China School of Nursing, Sichuan University, Chengdu, China.
Hong ChengSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China.
Jing QiuSchool of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China.
Rui HuangSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China.
Chaobin ZouSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China.
Guangkui SongSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China.
Menghong LiuSichuan Changhong Electric Co., Ltd, Mianyang, China.
Qian LiuInnovation Centre of Nursing Research and Nursing Key Laboratory of Sichuan Province, West China Hospital, Sichuan University/West China School of Nursing, Sichuan University, Chengdu, China.
Jiali ZhangInnovation Centre of Nursing Research and Nursing Key Laboratory of Sichuan Province, West China Hospital, Sichuan University/West China School of Nursing, Sichuan University, Chengdu, China.
Xiuying HuInnovation Centre of Nursing Research and Nursing Key Laboratory of Sichuan Province, West China Hospital, Sichuan University/West China School of Nursing, Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objectives: The growth in older adults living with disabilities and the decline in the workforce call for technology-driven nursing services to alleviate the burden. Functional assistive robots have emerged as a promising solution; however, their acceptance and attitude toward them remain underexplored. Therefore, this study aimed to investigate the attitudes and requirements of older adults living with disabilities regarding functional assistive robots. Research Design and Methods: A mixed-methods study was conducted between November 2023 and January 2024, comprising a cross-sectional survey of 85 older adults with varying levels of disability and semi-structured interviews with 10 participants. Quantitative data were analyzed descriptively, and qualitative data were thematically analyzed to enrich and contextualize the findings. Results: Fifty-three percent of participants expressed willingness to use a functional assistive robot, with safety, affordability, ease of use, and multifunctionality identified as the most influential factors. Walking assistance and toilet transfer were the most desired functions across all disability levels. Qualitative findings reinforced the quantitative findings, revealing dissatisfaction with current aids due to their limited stability and maneuverability, alongside a strong desire for increased independence and reduced strain on family caregivers. Attitudes toward robots ranged from enthusiasm to skepticism, influenced by perceived usefulness, disability level, and care context. Participants emphasized the need for compact, stable designs with simple interfaces, and some expressed interest in light social features, provided they did not compromise core functionality. Discussion and Implications: This study highlights the demand for functional assistive robots that address critical mobility-related tasks. Functional assistive robots are viewed as promising, but adoption hinges on improving safety, usability, and affordability. Multifunctional, user-friendly designs are essential for practical use. The findings offer guidance for nurses, caregivers, and developers by clarifying core functional needs and concerns, supporting the creation of acceptable technologies that enhance autonomy and quality of life.

Indexed as

DisabilityHuman–robot interactionLong-term careMixed methods

Identifiers

PMID41140795
PMCPMC12553357

What OpenQuestion holds

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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 OpenQuestion graph.