Migliorare la comunicazione nelle strutture per anziani: il progetto mySupport
Bibliographic record
Abstract
This article aims to explore the feasibility and impact of a quality improvement project aimed to assist nursing home staff in supporting family carers when they need to make difficult decisions about end-of-life care for their relative with advanced dementia. During the three-year pandemic period 2019-2022, Italy joined the mySupport study with 2 Piedmontese nursing homes. The mySupport study is a transnational project, which involved 6 European and extra-European countries (United Kingdom, Ireland, the Netherlands, the Czech Republic and Canada). Family carers were engaged in trained nurse-led family care conferences on care decisions at the end of life and received written resources. The project implementation required flexibility and to face unexpected events with poor resources, which were overcome by the establishment of trusting relationships with family carers and collaboration among nurses. The educational intervention appears to facilitate the transition towards a palliative-oriented approach, by promoting family understanding of dementia, knowledge of residents' and family carers' care preferences, and shared decision-making.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".