Evidence map›Paper›PMID 34308262›Full record

ArticleProceedings of the ACM on human-computer interaction2021

Dignity, Autonomy, and Style of Company: Dimensions Older Adults Consider for Robot Companions.

Simon Coghlan, Jenny Waycott, Amanda Lazar, Barbara Barbosa Neves

Open access · greenAbstract read
In one paragraph

Article in Proceedings of the ACM on human-computer interaction, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
10.3field-weighted citation impact, top 1% of its field
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

20 citing papers in PubMed, 65 citations in OpenAlex.

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  7. HCI and Older Adults: The Critical Turn and What Comes Next.Foundations and trends in human computer interaction · 2025
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  10. Patient Perspectives on AI-Driven Predictions of Schizophrenia Relapses: Understanding Concerns and Opportunities for Self-Care and Treatment.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2024
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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 at 3 institutions in 2 countries.

Simon CoghlanThe University of Melbourne, Australia.
Jenny WaycottThe University of Melbourne, Australia.
Amanda LazarUniversity of Maryland, USA.
Barbara Barbosa NevesMonash University, Australia.
University of Melbourne · AUMonash University · AUUniversity of Maryland, College Park · US

Funding

ACL HHS 90REGE0008
6 · The paper itself

Abstract

Research into companion robots for older adults, including those who are socially isolated and lonely, continues to grow. Although some insight into older adults' preferences for various robotic types and functionality is emerging, we lack research examining how these robots fulfil or challenge a range of values and aspirations individuals have in later life. This study examines the attitudes and perspectives of 16 older adults (aged 65+) living independently but alone in their own homes, who were interviewed and shown videos depicting three distinctive companion robots: a talking assistant; a roving toylike vehicle; and a robotic dog. This approach illuminated values, preferences, and needs amongst older people that are vital for understanding the potential of companion robots. In comparing the robots, participants expressed concerns about the impact of different companion robots on their abilities and skills, their sense of autonomy and control over their lives, and the maintenance of several kinds of dignity. These results inform user-centered design and use of companion robots for older people living alone and independently.

Indexed as

autonomyCompanion robotsdignityethicsolder adultssocial isolationsocial robots

Identifiers

PMID34308262
PMCPMC8297987
OpenAlexW3159541715

What OpenQuestion holds

Textmetadata
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.