Perceptions and needs regarding technologies in nursing homes: An exploratory study
Why this work is in the frame
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Bibliographic record
Abstract
Two of the most salient problems in nursing homes are the responsive behaviours and falls of older people living with Alzheimer's disease and related disorders. Intelligent videomonitoring and mobile applications are potential technologies that may help prevent and manage these problems. However, evidence for the needs for technologies in nursing homes is scarce. This study aimed to explore the perceptions and needs of care managers, and of formal and family caregivers in nursing homes regarding these potential technologies. With an exploratory qualitative design based on Rogers' diffusion of innovation theory, individual interviews and a content analysis were conducted. Results show that the potential users of these technologies consider them relevant in nursing homes. The characteristics that would make these technologies useful in nursing homes are described. These results could be used to develop useful technologies to improve the quality of clinical practice in nursing homes.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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