Perceptions des aidant(e)s de la qualité des soins et des services en unités de courte durée gériatriques: Développement et validation d'un outil de mesure
Bibliographic record
Abstract
ABSTRACT The goal of this study is to develop and validate a tool for measuring perceptions of caregivers of the quality of care and services in Geriatric Assessment Units. It has been designed so as to reproduce the notion of quality for caregivers. The validation of the tool is based on analyses of responses provided by caregivers (n = 274) to questions of perceived quality and to a certain number of questions necessary for the evaluation of its metric qualities. The measurement scale developed includes 25 items and it demonstrates good internal consistency. The Alpha Cronbach coefficients are 0.95 for the global index and they range from 0.88 to 0.91 on the sub-scales. The various analyses support a three-dimensional structure of the notion of quality for caregivers, explaining 66 per cent of the total variance. These dimensions are: “exchanges with professionals on the relative's condition,” “care given to a loved one,” and “planning the discharge”. It is hoped that this tool will promote the inclusion of the points of view of caregivers in the process of the improvement and assessment of quality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".