Friends from the Future: A Scoping Review of Research into Robots and Computer Agents to Combat Loneliness in Older People.


Journal

Clinical interventions in aging
ISSN: 1178-1998
Titre abrégé: Clin Interv Aging
Pays: New Zealand
ID NLM: 101273480

Informations de publication

Date de publication:
2021
Historique:
received: 04 02 2021
accepted: 08 04 2021
entrez: 3 6 2021
pubmed: 4 6 2021
medline: 17 6 2021
Statut: epublish

Résumé

Loneliness is a common problem in older adults and contributes to poor health. This scoping review aimed to synthesize and report evidence on the effectiveness of interventions using social robots or computer agents to reduce loneliness in older adults and to explore intervention strategies. The review adhered to the Arksey and O'Malley process for conducting scoping reviews. The SCOPUS, PUBMED, Web of Science, EMBASE, CINAHL, PsycINFO, ACM Digital Library and IEEE Xplore databases were searched in November, 2020. A two-step selection process identified eligible research. Information was extracted from papers and entered into an Excel coding sheet and summarised. Quality assessments were conducted using the Mixed Methods Appraisal Tool. Twenty-nine studies were included, of which most were of moderate to high quality. Eighteen were observational and 11 were experimental. Twenty-four used robots, four used computer agents and one study used both. The majority of results showed that robots or computer agents positively impacted at least one loneliness outcome measure. Some unintended negative consequences on social outcomes were reported, such as sadness when the robot was removed. Overall, the interventions helped to combat loneliness by acting as a direct companion (69%), a catalyst for social interaction (41%), facilitating remote communication with others (10%) and reminding users of upcoming social engagements (3%). Evidence to date suggests that robots can help combat loneliness in older adults, but there is insufficient research on computer agents. Common strategies for reducing loneliness include direct companionship and enabling social interactions. Future research could investigate other strategies used in human interventions (eg, addressing maladaptive social cognition and improving social skills), and the effects of design features on efficacy. It is recommended that more robust experimental and mixed methods research be conducted, using a combination of validated self-report, observational, and interview measures of loneliness.

Sections du résumé

BACKGROUND AND AIM OBJECTIVE
Loneliness is a common problem in older adults and contributes to poor health. This scoping review aimed to synthesize and report evidence on the effectiveness of interventions using social robots or computer agents to reduce loneliness in older adults and to explore intervention strategies.
METHODS METHODS
The review adhered to the Arksey and O'Malley process for conducting scoping reviews. The SCOPUS, PUBMED, Web of Science, EMBASE, CINAHL, PsycINFO, ACM Digital Library and IEEE Xplore databases were searched in November, 2020. A two-step selection process identified eligible research. Information was extracted from papers and entered into an Excel coding sheet and summarised. Quality assessments were conducted using the Mixed Methods Appraisal Tool.
RESULTS RESULTS
Twenty-nine studies were included, of which most were of moderate to high quality. Eighteen were observational and 11 were experimental. Twenty-four used robots, four used computer agents and one study used both. The majority of results showed that robots or computer agents positively impacted at least one loneliness outcome measure. Some unintended negative consequences on social outcomes were reported, such as sadness when the robot was removed. Overall, the interventions helped to combat loneliness by acting as a direct companion (69%), a catalyst for social interaction (41%), facilitating remote communication with others (10%) and reminding users of upcoming social engagements (3%).
CONCLUSION CONCLUSIONS
Evidence to date suggests that robots can help combat loneliness in older adults, but there is insufficient research on computer agents. Common strategies for reducing loneliness include direct companionship and enabling social interactions. Future research could investigate other strategies used in human interventions (eg, addressing maladaptive social cognition and improving social skills), and the effects of design features on efficacy. It is recommended that more robust experimental and mixed methods research be conducted, using a combination of validated self-report, observational, and interview measures of loneliness.

Identifiants

pubmed: 34079242
doi: 10.2147/CIA.S282709
pii: 282709
pmc: PMC8163580
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

941-971

Informations de copyright

© 2021 Gasteiger et al.

Déclaration de conflit d'intérêts

Elizabeth Broadbent authored/co-authored five studies included in the review. However, Elizabeth did not conduct the quality assessments, so potential conflicts of interest were mitigated. Soul Machines Ltd (a company that makes digital humans) employs Kate Loveys as an intern and contracts Elizabeth Broadbent as a consultant. The authors report no other conflicts of interest in this work.

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Auteurs

Norina Gasteiger (N)

Department of Psychological Medicine, The University of Auckland, Auckland, New Zealand.
School of Health Sciences, The University of Manchester, Manchester, UK.

Kate Loveys (K)

Department of Psychological Medicine, The University of Auckland, Auckland, New Zealand.

Mikaela Law (M)

Department of Psychological Medicine, The University of Auckland, Auckland, New Zealand.

Elizabeth Broadbent (E)

Department of Psychological Medicine, The University of Auckland, Auckland, New Zealand.

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