Les comportements des personnes âgées vivant avec un trouble neurocognitif : l’approche centrée sur les relations pour améliorer l’expérience de tous
Bibliographic record
Abstract
Older people living with a major neurocognitive disorder often have difficulty communicating. They may exhibit reactive behaviors, such as vocal or aggressive behaviors, which are manifestations of malaise. These behaviors have consequences for these older people, as well as for their relatives and formal caregivers. This article discusses the relationship-centered approach to improving the experience of each of these persons by stimulating a reflection on what unites us. Then, the principles of this relationship-centered approach are outlined, based on the unique needs of each person, the reciprocity of their relationship, and their common aspirations. The application of these principles to older people living with a neurocognitive disorder who exhibit reactive behaviors is reflected through the adoption of consistent language, the identification of the meanings of behaviors and personalized actions, and the establishment of a care partnership. An example of a process integrating this approach is presented, as well as its possible effects. The adoption of this approach may present several challenges in care settings. To meet these challenges, implementation strategies are described promoting the adoption of this approach and contributing to everyone’s well-being.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".