ArticleJournal of the American Geriatrics Society2025
Implementing Robotic Pets in Continuing Care Settings: A Scoping Review of Barriers and Facilitators.
Article in Journal of the American Geriatrics Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Developing an implementation guide for robotic pets in continuing care settings for older adults living with dementia in Canada: findings from a modified Delphi.BMC geriatrics · 2026Article
- Evaluating a co-developed pet robot intervention and implementation for residents with dementia in long-term care.Frontiers in dementia · 2026Article
- Implementing Robotic Pets in Continuing Care Settings: A Scoping Review of Barriers and Facilitators.Journal of the American Geriatrics Society · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundRobotic pets are a unique technological innovation found among facility-based continuing care (CC) settings for older adults living with or without dementia. While researchers have reported positive outcomes for older adults who interact with robotic pets, unintended negative consequences may occur if robotic pets are not implemented properly. We examine the current evidence describing barriers and facilitators of implementing robotic pets for older adults residing in CC facilities to inform implementation practices.
methodsA scoping review was conducted following the methodological framework outlined by Arksey and O'Malley. Five databases and the CADTH Gray Matters tool were used to identify relevant articles and gray literature. Our inclusion criteria followed the Population, Concept, Context (PCC) framework: Population: older adults living with or without dementia; Concept: barriers and facilitators to implementing robotic pets to older adults; Context: CC facilities. Two reviewers independently screened all titles, abstracts, and full-text articles and extracted the data. Two reviewers also organized barriers and facilitators into the theoretical domains framework (TDF) domains, which map onto the capability, opportunity, and motivation behavioral Change Wheel (COM-B).
resultsWe identified 518 unique articles from our database and gray literature search, 42 of which met our inclusion criteria. Barriers and facilitators were identified across all 14 domains of the TDF and all six components of the COM-B. Domains mentioned in ≥ 50% of the articles include environmental context and resources, beliefs about consequences, and social influences. Common facilitators include knowledge of the benefits of robotic pets and how to use robotic pets, while common barriers include concerns over infantilization and hygiene.
conclusionsOur findings will help inform care providers of the barriers and facilitators to implementing robotic pets within CC settings with the goal of improving the quality of life of older adults.
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Registered trials
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.