Evidence map›Paper›PMID 42231881›Full record

ArticleFrontiers in dementia2026

Social robot design preferences as reported by stakeholders.

Matthew Green, Dzung Dao, Sam Canning, Wendy Moyle

Abstract read
In one paragraph

Article in Frontiers in dementia, 2026. 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
–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

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.

Matthew GreenMechanical and Mechatronic Engineering, Griffith University, Gold Coast, QLD, Australia.
Dzung DaoMechanical and Mechatronic Engineering, Griffith University, Gold Coast, QLD, Australia.
Sam CanningSchool of Engineering and Built Environment, Griffith University, Gold Coast, QLD, Australia.
Wendy MoyleSchool of Nursing and Midwifery, Nathan, QLD, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Social robots have the potential to support older adults and their carers; but to be effective in dementia care, they must be designed in ways that align with the specific needs, preferences, and capabilities of people living with dementia. Objective: This descriptive exploratory study investigated design preferences for social robots among people with dementia and key stakeholders involved in their care. Methods: An online survey was conducted using a multi-method design involving people with dementia ( Results: Animal-like robots were positively received across all stakeholder groups. Telepresence robots were viewed as valuable tools for communication and information exchange, although some participants expressed concerns regarding their potential technical complexity. Both formal and informal carers reported that humanoid robots could provoke anxiety among people with dementia. Participants consistently emphasized that a robot's capabilities and audio outputs should be congruent with its appearance, adjustable to user preferences and appropriate for the robot type. Data capture and storage of personal preferences, along with face recognition, and camera-based monitoring (infrared or skeletal tracking) were considered acceptable when they enhanced safety or supported personalized interactions. Conclusion: The findings highlight the importance of designing customizable social robots tailored to the diverse preferences and needs that shape human-robot interaction in dementia care through a co-design approach. Support for personalization, appropriate aesthetic-function alignment, and safety-enhancing data use emerged as key considerations for future social robot development.

Indexed as

dementiadesignmulti-methodssocial robotstechnology

Identifiers

PMID42231881
PMCPMC13222834

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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.