Socially Assistive Robots in Elderly Care: A Mixed-Method Systematic Literature Review

TLDR

The aging global population is prompting a shift toward new care paradigms, with socially assistive robots being considered to support caregiving and enable older adults to remain at home longer. The review aims to assess the impact of socially assistive robots on elderly well‑being and to identify methodological gaps and recommendations for future research. The authors conducted a Cochrane‑handbook–guided systematic review of 86 studies across 37 groups, classifying SAR interventions, measures, and outcomes. The review finds that socially assistive robots positively affect elderly well‑being, can reduce caregiver workload, and offers ten recommendations to address current research limitations.

Abstract

The world’s population is aging, and developed countries are engaged in developing a new aged-care paradigm to reduce spiraling healthcare costs. Assistive technologies like Socially Assistive Robots (SAR) are being considered as enablers to support the process of care giving or keep elderly at home longer. This article reports a mixed-method systematic review of SAR in elderly care and recognizes its impact on elderly well-being, integrating evidence from qualitative and quantitative studies. It follows the principles explained in Cochrane Handbook for Systematic Reviews of Interventions and classifies interventions, measures, and outcomes of field trials of SAR in elderly care. Eighty-six studies in 37 study groups have been included. The findings imply positive effects of SAR on elderly well-being. Ten significant recommendations are made to help avoid the current limitations of existing research and to improve future research and its applicability. This review revealed that SAR can potentially enhance elderly well-being and decrease the workload on caregivers. There is a need for rigorous research methodology, person-centered care, caregiver expectation model, multimodal interaction, multimodal data collection, and modeling of culturally diverse groups to facilitate acceptability of SAR.