Humanoid Robot–Assisted Support for Health Care in Older Adults: Systematic Scoping Review

TL;DR

This review explores how humanoid robots can support healthcare for older adults, finding promise but also significant challenges in their use.

Contribution

The study provides a systematic synthesis of humanoid robot applications in elder care, identifying key patterns and research gaps.

Findings

Most studies were real-world but had small sample sizes and mixed methods.

Key challenges include technical limitations, user acceptance, and systemic adoption barriers.

Four patterns emerged: effects of robots, user preferences, implementation barriers, and outcome determinants.

Abstract

Humanoid robots offer a promising solution to the growing burden of care for older adults. However, existing evidence on their applications for general aging populations remains fragmented and lacks systematic synthesis.

This scoping review aimed to examine the literature on humanoid robot–assisted support for health care in older adults and identify gaps in the literature to guide future research.

The methodological framework by Arksey and O’Malley was used to conduct this scoping review. We conducted a comprehensive search in 8 databases, including IEEE Xplore Digital Library, CINAHL, Cochrane Library, EMBASE, PubMed, Scopus, Web of Science, and OpenGrey Repository, covering literature published up to April 30, 2025. The reference lists of key texts were examined, and citation chaining was conducted. Two independent reviewers examined all full articles for fitness with the eligibility criteria and extracted data elements. The study findings were then summarized, coded, and analyzed using the PAGER (Patterns, Advances, Gaps, Evidence for practice, and Research recommendations) framework.

A total of 32,477 articles were retrieved, 59 of which were included in this review. The majority (49/59, 83%) were conducted in real-world settings. Methodologically, 34 studies (34/59, 58%) had small sample sizes (n≤25), with study designs comprising 26 quantitative (26/59, 44%), 22 mixed method (22/59, 37%), and 11 qualitative (11/59, 19%) approaches. Participant characteristics revealed female predominance (>50%) in 32 studies (32/59, 54%), while 27 studies (27/59, 46%) included participants with cognitive impairment. Through PAGER framework analysis, we identified 4 key patterns: (1) effects, perceptions, and experiences of humanoid robots; (2) preferences, expectations, and facilitators for humanoid robots; (3) implementation barriers and challenges; and (4) determinants of user experiences and outcomes.

This scoping review demonstrates the promising yet methodologically constrained potential of humanoid robots in health care for older adults while highlighting key challenges in their practical implementation. Successful integration will require addressing technical limitations, user acceptance barriers, and systemic adoption challenges.

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