Evidence map›Paper›PMID 39586076›Full record

ArticleJMIR aging2024

Social Robots and Sensors for Enhanced Aging at Home: Mixed Methods Study With a Focus on Mobility and Socioeconomic Factors.

Roberto Vagnetti, Nicola Camp, Matthew Story, Khaoula Ait-Belaid, Suvobrata Mitra, Sally Fowler Davis, Helen Meese, Massimiliano Zecca, Alessandro Di Nuovo, Daniele Magistro

Abstract read
In one paragraph

Article in JMIR aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

10 authors.

Roberto VagnettiDepartment of Sport Science, School of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom.ORCID 0000-0001-5192-1756
Nicola CampDepartment of Sport Science, School of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom.ORCID 0000-0003-0972-9722
Matthew StoryDepartment of Computing & Advanced Wellbeing Research Centre, Sheffield Hallam University, Sheffield, United Kingdom.ORCID 0000-0001-7976-6786
Khaoula Ait-BelaidWolfson School of Mechanical, Electrical, and Manufacturing Engineering, Loughborough University, Loughborough, United Kingdom.ORCID 0000-0003-4699-9668
Suvobrata MitraDepartment of Psychology, Nottingham Trent University, Nottingham, United Kingdom.ORCID 0000-0001-7620-4809
Sally Fowler DavisFaculty of Allied Health and Social Care, Anglia Ruskin University, Chelmsford, United Kingdom.ORCID 0000-0002-3870-9272
Helen MeeseThe Care Machine Ltd, Potterhanworth, United Kingdom.ORCID 0000-0002-9528-4442
Massimiliano ZeccaWolfson School of Mechanical, Electrical, and Manufacturing Engineering, Loughborough University, Loughborough, United Kingdom.ORCID 0000-0003-4741-4334
Alessandro Di NuovoDepartment of Computing & Advanced Wellbeing Research Centre, Sheffield Hallam University, Sheffield, United Kingdom.ORCID 0000-0003-2677-2650
Daniele MagistroDepartment of Sport Science, School of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom.ORCID 0000-0002-2554-3701

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPopulation aging affects society, with a profound impact on daily activities for those of a low socioeconomic status and with motor impairments. Social assistive robots (SARs) and monitoring technologies can improve older adults' well-being by assisting with and monitoring home activities.

objectiveThis study explored the opinions and needs of older adults, including those with motor difficulties and of a low socioeconomic status, regarding SARs and monitoring technologies at home to promote daily activities and reduce sedentary behaviors.

methodsA mixed methods approach was used, with 31 older adults divided into 3 groups: those of a low socioeconomic status, those with motor difficulties, and healthy individuals. Focus groups were conducted, and they were analyzed using thematic analysis. Perceived mental and physical well-being were assessed using the 12-Item Short Form Health Survey, and attitudes toward robots were evaluated using the Multidimensional Robot Attitude Scale.

resultsThe results identified 14 themes in four key areas: (1) technology use for supporting daily activities and reducing sedentary behaviors, (2) perceived barriers, (3) suggestions and preferences, and (4) actual home technology use. Lower perceived physical well-being was associated with higher levels of familiarity, interest, perceived utility, and control related to SARs. Lower perceived psychological well-being was linked to a more negative attitude, increased concerns about environmental fit, and a preference for less variety. Notably, older adults from the low-socioeconomic status group perceived less control over SARs, whereas older adults with motor difficulties expressed higher perceived utility compared to other groups, as well as higher familiarity and interest compared to the low-socioeconomic status group.

conclusionsParticipants indicated that SARs and monitoring technologies could help reduce sedentary behaviors by assisting in the management of daily activities. The results are discussed in the context of these outcomes and the implementation of SARs and monitoring technologies at home. This study highlights the importance of considering the functional and socioeconomic characteristics of older adults as future users of SARs and monitoring technologies to promote widespread adoption and improve well-being within this population.

Indexed as

Activities of Daily LivingRoboticsSocioeconomic FactorsAgedAged, 80 and overAgingFemaleFocus GroupsHumansMaleMiddle AgedSedentary BehaviorSelf-Help Devicesmixed methodsmonitoring technologiesmotor difficultiesolder adultssocial assistive robotssocioeconomic status

Identifiers

PMID39586076
PMCPMC11629043

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.