ORGANIZATION OF WORK AND DECISION-MAKING OF PROFESSIONALS WORKING IN NURSING HOMES IN CATALONIA (SPAIN)
Bibliographic record
Abstract
Abstract The long term care environment demands specific requirements of the staff, namely that they provide a holistic approach to care. Providing holistic care leads to complex decision-making processes which go beyond just finding a solution to a specific health problem. It requires that staff are able to respond to the diverse needs expressed by the residents and which, in many cases, are only identified through the relationship that professionals have with them. However, this relationship that staff establishes with the resident often leads to burden for these professionals. The researchers sought to identify characteristics of the nursing homes that lead to positive outcomes for staff. The study involves collecting questionnaires (n=132) and conducting semi structured interviews (n=35) in 9 Catalan nursing homes with number of staff, utilizing a quantitative questionnaire and semi-structured interviews. Practices in organisations that led to positive outcomes for staff included coordinated care that includes processes of support for staff, effective communication and decision making practices, clear responsibilities for staff, and utilization of care plans. Effective long term care practices can favour both patient care and professional practice in residences for elderly.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".