Independent Living for Older Adults with Cognitive Impairment: A Narrative Review of Stakeholder Perceptions and Experiences with Assistive and Socially Assistive Robots
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: (1)Alzheimer's disease and related dementias (ADRD) are a major cause of mortality among older adults globally. The cognitive decline associated with ADRD often reduces individuals' ability to live independently over time, increasing reliance on caregivers. Assistive and socially assistive robots offer a promising means of supporting independent living. This narrative review examined how older adults with ADRD, their caregivers, and healthcare providers perceive and experience interactions with robots. Methods: (2)Guided by the Population, Phenomenon of Interest, and Context (PICo) framework, five databases were searched. Sixteen studies met the inclusion criteria. Extracted data were summarized, and a convergent synthesis integrated qualitative and quantitative findings. Results: (3)Drawing on content analysis, the qualitative findings were organized into three domains: user perceptions and experiences, barriers to adoption, and suggestions for improvement. Quantitative results emphasized usability, usefulness, acceptance, satisfaction, feature preferences, and barriers. While most stakeholders viewed robots as beneficial, acceptance was shaped by factors such as design features, timing of introduction, familiarity with technology, and perceived need. Conclusions: (4)This review highlights priorities for future research and development, including personalization, ethical safeguards, and caregiver integration, to improve the acceptance and effectiveness of robot-assisted support for individuals with cognitive impairment.
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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 | 0.001 |
| 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 it