Playing a memory game with a socially assistive robot: A case study at a long-term care facility
Bibliographic record
Abstract
Studies have shown that cognitive and social stimulation is crucial to the overall health of older adults including psychological, cognitive and physical well-being. However, activities to promote such stimulation are often lacking in long-term care facilities. Our work focuses on the use of social robotic technologies to provide person-centered cognitive interventions. Namely, this paper presents an HRI study with the unique human-like socially assistive robot Brian 2.1, in order to investigate the use and acceptability of the expressive human-like robot by older adults living in a longterm care center. Current studies with social robots for the elderly have been mainly directed towards collecting data on the acceptance and use of animal-like robots. Herein, we aim to determine if the robot's human-like assistive and social characteristics result in the elderly having positive attitudes towards the robot as well as accepting it as an interactive cognitive training tool.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".