Evidence map›Paper›PMID 40991737›Full record

ArticleJMIR human factors2025

Exploratory Research With a Health Consumer Group on Social Robot Use Among Older Adults: Qualitative Study.

James Sadler, Aila Khan, Omar Mubin, Michael Lwin

Abstract read
In one paragraph

Article in JMIR human factors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

James SadlerSchool of Business, Western Sydney University, 169 Macquarie Street, Parramatta, 2150, Australia, 61 497829851.ORCID 0009-0005-4201-9679
Aila KhanSchool of Business, Western Sydney University, 169 Macquarie Street, Parramatta, 2150, Australia, 61 497829851.ORCID 0000-0001-7847-6576
Omar MubinSchool of Business, Western Sydney University, 169 Macquarie Street, Parramatta, 2150, Australia, 61 497829851.ORCID 0000-0002-6435-6407
Michael LwinSchool of Business, Western Sydney University, 169 Macquarie Street, Parramatta, 2150, Australia, 61 497829851.ORCID 0000-0002-3669-9306

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: There is an increased focus on involving members of the public in health research. These types of groups, such as "health consumer groups," bring different expertise to inform the design of a research study. There is a growing general concern about older adults' acceptance and use of technologies. This becomes critical when it involves health care services. Objective: To understand the use of social robots among older adults, it is prudent to gauge stakeholders' perspectives on optimal research design. In line with the philosophy of the "triple helix model," researchers sought the expertise and guidance of a health consumer group. Methods: Researchers recruited an expert health consumer group for this study. This included 5 participants from an 8-member panel. Semistructured interviews were conducted. Each interviewee was introduced to visual stimuli of assistive technologies, older adults, and social robots. Subsequently, they were asked for their perspectives on what they viewed and to provide guidance on how to best design upcoming research on these phenomena. Results: Key themes were derived from the interview transcripts with the health consumer group members. Findings include panel members' advice and guidance on explaining the research aims to technology-averse older adults, approaching data collection from this demographic, and, finally, their perceptions of the appearance of social robots. Conclusions: The advice and guidance of this expert health consumer, in tandem with researchers and industry partners, substantially aid in advancing research efforts toward social robot use among technology-averse older adults in Australia. This research provides vital information, including how best to approach data collection about social robots from this demographic.

Indexed as

RoboticsAgedAged, 80 and overFemaleHumansMaleMiddle AgedQualitative Researchassistive technologyhealth care stakeholdershealth consumer groupolder adultsquality of lifesocial robotstriple helix model of innovation

Identifiers

PMID40991737
PMCPMC12459739

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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.