Evidence map›Paper›PMID 42378689›Full record

SynthesisJournal of medical Internet research2026

Care Robots as Emerging Health Technologies: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Gaeun Kim, Jinmi Jeon

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in Journal of medical Internet research, 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

2 authors.

Gaeun KimDepartment of Nursing, College of Nursing, Keimyung University, 1095, Dalgubeol-daero, Dalseo-gu, Daegu, 42601, Republic of South Korea, 82532587658.ORCID http://orcid.org/0000-0003-1914-8331
Jinmi JeonGraduate School, Department of Nursing, Keimyung University, Daegu, Republic of South Korea.ORCID http://orcid.org/0009-0007-2778-6495

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Global aging and health care workforce shortages are increasing demand for therapeutic support among older adult and pediatric populations. Care robots, an umbrella term for socially assistive robots, companion and pet platforms, and therapeutic humanoids sharing a social interaction component, have been proposed as embodied digital health adjuncts, but prior syntheses have remained population- or platform-specific, leaving cross-population and cross-platform effects unquantified. Objective: This review quantifies the pooled effects of care-robot interventions across 7 prespecified outcome domains, examines robot platform, target population, and intervention-duration moderators, and grades evidence certainty. Methods: Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020, we searched 5 databases (PubMed, including MEDLINE, Embase, Cochrane CENTRAL, CINAHL, APA PsycINFO) and 2 trial registries (ClinicalTrials.gov; World Health Organization International Clinical Trials Registry Platform) through April 29, 2026, with no language restriction. Eligible studies were randomized controlled trials of embodied care robots versus standard care, active controls, or waitlist. Random-effects meta-analysis used Hedges g with Hartung-Knapp-Sidik-Jonkman correction; for domains with k≥4, we report 95% CIs and prediction intervals (PIs). Risk of bias used the Cochrane Risk of Bias 2 tool; certainty used the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework. Results: A total of 34 randomized controlled studies (n=2476; 17 countries; 2015-2024) met inclusion criteria; 20 contributed to at least 1 meta-analysis, and 14 entered narrative synthesis. Under Hartung-Knapp-Sidik-Jonkman pooling, only neuropsychiatric symptoms reached significance: Hedges g=0.44 (95% CI 0.03-0.84; 95% PI -0.42 to 1.30; k=6; P=.04). The remaining 6 domains were favorable but nonsignificant: quality of life Hedges g=0.15 (95% CI -0.41 to 0.71; 95% PI -0.86 to 1.16; k=5); depression Hedges g=0.20 (95% CI -0.08 to 0.49; 95% PI -0.36 to 0.76; k=7); agitation Hedges g=0.32 (95% CI -0.07 to 0.71; 95% PI -0.26 to 0.89; k=4); stress and pain Hedges g=0.53 (95% CI -0.48 to 1.53; 95% PI -1.57 to 2.62; k=6); social-communicative skills Hedges g=0.45 (95% CI -0.52 to 1.42; 95% PI -1.66 to 2.56; k=5); and cognitive function Hedges g=0.18 (95% CI -0.62 to 0.98; 95% PI -1.11 to 1.47; k=4). All 7 PIs encompassed the null, indicating no assured effect in new settings. The neuropsychiatric symptom result was fragile: significance was lost in 5 of 6 leave-one-out iterations and on excluding Petersen 2016 (data extraction ambiguity), yielding a Hedges g of 0.40 (P=.10). GRADE certainty was low for neuropsychiatric symptoms and very low for the remaining 6 domains. Conclusions: Across cross-population, cross-platform randomized controlled trial pooling, the evidence does not yet support routine clinical adoption of care robots. Potential benefits are narrow, of low certainty, and contingent on adequately powered multicenter confirmatory trials with PI-informed sample sizes. Care robots are best framed as facilitator-supported adjuncts that augment, rather than substitute for, human-delivered care.

Indexed as

Biomedical TechnologyRoboticsDigital HealthHumansRandomized Controlled Trials as Topiccare robotsdigital healthmeta-analysisroboticssocially assistive robotssystematic review

Identifiers

PMID42378689
PMCPMC13318203

What OpenQuestion holds

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LicenceCC BY
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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.