Robots for Older Adults: A Scoping Review
Samuel A. Olatunji, Yao-Lin Tsai, Saathveek A. Gowrishankar, Megan A. Bayles, Wendy A. Rogers · 2026 · ACM Transactions on Human-Robot Interaction · doi:10.1145/3799977
Summary
This mixed-method scoping review in the ACM Journal of Human-Robot Interaction establishes the state of the science for robots supporting older adults, covering 205 empirical studies published from 2010 through 2022. The review follows PRISMA reporting guidelines and the Budgen and Brereton systematic-review process. The authors used Google Scholar as their primary search engine with 35 robot-term × aging-term combinations, screened 2,359 records, assessed 563 full reports for eligibility, and included the remaining 205 after consensus coding. Three researchers coded roughly 80 articles each using a shared codebook; intercoder reliability averaged 93.2%. The coding scheme classifies studies along five axes: who participated (age, health conditions), what type of robot (social, assistive, telepresence, and their overlaps — notably socially-assistive robots), what tasks the robot supported (framed through the gerontological ADL / IADL / EADL hierarchy of everyday activities), how the study was conducted, and where (laboratory, facility such as a care home, home, or other). The paper is explicitly positioned to produce a comprehensive, multi-dimensional view that previous narrower reviews have not provided, and to ground recommendations in the Rogers and Mitzner HRI framework, which spans human, robot, interaction, and environment considerations. The review is registered on OSF and the coding dataset is publicly available.
Key findings
Research output grew steadily across the review period, from four articles in 2010 to a peak of 34 in 2022, with a COVID-related dip in 2021. Over 6,305 older adults participated across the studies; mean age sat around 74, and 60% of studies recruited generally healthy older adults while 28% focused on cognitive impairments, 7% mobility, 2% hearing, and 2% vision. Social robots dominated the robot category mix (48.4%), followed by assistive (16.4%) and a large social-assistive overlap (23%); telepresence robots were rare (5%). By task, EADLs — companionship, entertainment, video communication — accounted for 52% of studies, IADLs (medication reminders, housekeeping, shopping) 28%, and ADLs (bathing, feeding, dressing, sit-to-stand) only 8%. Most studies took place in laboratories (37%) or care facilities (30%), with home-based studies rising over time (17%). The authors flag major gaps: very few robots targeted perceptual impairments (hearing, vision), ADL support for high-need older adults is underdeveloped, sample demographics are often poorly reported, and common usage of “elderly”/“seniors” language reinforces ageist framings.
Relevance
For accessibility practitioners, the paper is a practical map of where robot support for older adults currently sits and where design effort is still missing. The ADL / IADL / EADL framing is useful for specifying accessibility requirements in any aging-in-place or elder-care technology, not only robotics. The paper’s reporting-quality critique is applicable beyond HRI: if participant demographics, health conditions, robot capabilities, tasks, and contexts are not reported in sufficient detail, synthesis and meta-analysis — and therefore evidence-based policy and procurement decisions — are impossible. Practitioners should also note the paper’s sustained argument against deficit framings of aging and its recommended language shift from “elderly” to “older adults” or “people over age X.” Limitations include reliance on Google Scholar as the single primary database, exclusion of studies without explicit older-adult user evaluation, and the 2022 cut-off which predates the wave of LLM- and agent-enabled robot work.
Tags: human-robot interaction · robots · older adults · aging · assistive technology · scoping review · ADL · IADL · EADL · social robots · telepresence · user-centered design
Standards referenced: PRISMA