Preprint · Mar 13, 2026
Care Robots as Emerging Health Technologies: A Systematic Review and Meta-Analysis (Preprint)
By Kim G, Jeon J
BACKGROUND The rapid growth of aging populations worldwide is placing mounting pressure on long-term care systems already facing critical nursing workforce shortages. Care robots—including socially assistive robots (eg, PARO, NAO, Pepper), companion robots, and therapeutic robots—have emerged as a promising category of digital health technology designed to complement professional caregiving in older adult populations. Despite increasing deployment across clinical and community care settings, a comprehensive quantitative synthesis of their clinical effectiveness across diverse patient populations and outcome domains has not been established. OBJECTIVE This systematic review and meta-analysis aimed to quantify the pooled effects of care robot interventions across key patient outcome domains, identify moderating factors including robot type and target population characteristics, appraise study methodological quality, and evaluate the overall certainty of evidence to inform clinical implementation decisions. METHODS We searched PubMed, CINAHL, Cochrane Library, and Embase from inception through December 2024 following PRISMA 2020 guidelines. Eligible studies were randomized controlled trials (RCTs) or quasi-experimental studies comparing care robot interventions with standard care, active controls, or waitlist controls in any clinical or community setting. Methodological quality was assessed using the Cochrane Risk of Bias 2 (RoB 2) tool; certainty of evidence was evaluated using the GRADE framework. Pooled standardized mean differences (SMDs; Hedges' g) with 95% CIs were calculated using random-effects models. RESULTS Thirty-four studies (N = 2,476 participants; 17 countries; 2015–2024) met inclusion criteria; 28 were included in meta-analyses. Care robot interventions yielded statistically significant effects compared with controls for neuropsychiatric symptoms (k = 8; SMD = −0.34; 95% CI −0.62 to −0.06; I² = 64%), quality of life (k = 6; SMD = 0.27; 95% CI 0.03 to 0.51; I² = 52%), agitation (k = 5; SMD = −0.31; 95% CI −0.55 to −0.07; I² = 48%), stress and pain (k = 6; SMD = −0.38; 95% CI −0.68 to −0.08; I² = 72%), and social-communicative skills (k = 6; SMD = 0.45; 95% CI 0.14 to 0.76; I² = 54%). Effects on depression and cognitive function were not statistically significant. Subgroup analyses indicated that PARO demonstrated the strongest effects in older adults with dementia, whereas humanoid robots (NAO) yielded the largest effect sizes for children with autism spectrum disorder (ASD). GRADE certainty of evidence ranged from moderate (neuropsychiatric symptoms, agitation) to very low (depression, cognitive function). CONCLUSIONS Care robots represent a viable and evidence-supported category of digital health technology with significant effects across multiple patient outcome domains relevant to aging care. These findings support integration of care robots—particularly PARO in dementia and long-term care settings—as complementary digital health interventions. Successful implementation requires attention to technology acceptance, facilitator training, and interoperability with existing health information systems. CLINICALTRIAL Not applicable