JMIR Publications

ABSTRACT

Background:

Demographic shifts are increasing the global demand for long-term care services while a worldwide shortage of health care personnel persists. Service robots, designed to perform tasks in professional and personal contexts, have been proposed to alleviate health care personnel’s workload and enhance care quality. However, the evidence is fragmented and heterogeneous, with a predominant focus on residents rather than health personnel, inconsistent definitions of service robots, and limited use of implementation models and frameworks.

Objective:

This scoping review aimed to map and synthesize existing evidence on the adoption and integration of service robots in long-term care settings, focusing on their role in supporting health care personnel and informal caregivers in performing routine tasks.

Methods:

A comprehensive 3-step search was conducted in 6 databases, as well as gray literature and institutional repositories. Eligible sources included empirical studies and gray literature involving service robots, health care personnel, residents aged ≥65 years, and stakeholders such as informal caregivers in institutional long-term care. Studies on home care, medical or industrial robots, and nonrobotic technologies were excluded. Data were extracted and analyzed using the Joanna Briggs Institute methodology and charted on study characteristics, concepts and classifications of service robots, methodologies, target populations, outcomes related to workflow and workload, and use of theories, models, or frameworks. A descriptive and thematic synthesis was performed.

Results:

Screening of 4884 unique titles and abstracts yielded 64 full-text articles, of which 27 met the inclusion criteria. Most studies (20/27, 74.1%) were published in the last 4 years and conducted in Europe or Asia. Service robots varied widely in function, technical maturity, and context of use, with many described as prototypes or tested in pilot trials, and few implemented in long-term care settings. Concepts and classifications were inconsistent, and no consensus-based definition for health care and long-term care was identified. Evidence on health personnel’s workflow and workload was mixed, with reported gains in task and logistical efficiency and reduced physical burden, alongside concerns about paradoxically increased workload, integration challenges, and ethical and safety issues. The evidence base was limited by small sample sizes, short study durations, heterogeneous designs, mixed target populations, and a lack of common outcome measures; of 27 included studies, 44.4% (n=12) did not report using theories, models, or frameworks.

Conclusions:

Service robots have the potential to support health personnel in routine and logistical tasks and contribute to the digital transformation of long-term care. However, their adoption and integration remain in the early stages, and current evidence is limited by methodological heterogeneity, short-term pilot studies, and insufficient theoretical grounding. Future research should prioritize theory-informed, real-world, and longitudinal implementation studies, employ clear health personnel–focused outcomes, and advance consensus-based definitions and classifications of service robots in long-term care. Clinical Trial: Open Science Framework QWK58; https://osf.io/qwk58/