ArticleFrontiers in psychiatry2026
Detection of depression risk among older adults using home-deployed socially assistive robots: a real-world study.
Article in Frontiers in psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Monitoring depression among older adults using socially assistive robots provides scalable and continuous health surveillance while reducing the clinical burden on therapists and minimizing delays in treatment. This study aimed to predict depression risk and identify individuals in need of specialized depression care at local healthcare centers, using response and usage log data from the socially assistive robot Methods: A total of 215 community-dwelling older adults (170 in the 2024 cohort and 45 in the 2025 cohort) who used Results: The model predicted symptomatic participants and participants requiring referral with sensitivities of 0.939 and 0.900, respectively. The model also produced considerable false positives. Features most strongly associated with depression status included engagement with quiz content, frequency of free conversations, positive responses to daily check-ins, regular meal intake, and the frequency of physical interactions with the robot. Discussion: The preliminary findings suggest that
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.