Attributes of conception of relational continuity: an essential component of the integration of services for frail older people
Bibliographic record
Abstract
PURPOSE: Present the results of an exploratory study which aimed to identify the attributes of relational continuity as conceived by the actors involved in the organization of services to frail older people. THEORY: The lengthening of the duration of life with autonomy loss warrants a transformation of the response to the needs of older people. The organization of services must evolve from a hospital-centered model to a residence-centered model better adapted to long-term care. This refocus on residential care provokes a multiplication of service providers which must be coordinated to ensure continuity of care [1]. Amongst the three forms of continuity (informational, management and relational) [2], relational continuity appears as the least documented and most difficult to measure. METHODS: Twenty-seven interviews with practitioners, managers, family caregivers and users were conducted and analysed using a content analysis approach. RESULTS AND CONCLUSIONS: While the family caregivers and users stressed the psycho-affective nature of the care relationship, the practitioners viewed it as a means to ensure the adequacy of services. From the user's viewpoint, the relationship is not the responsibility of one professional, but of a collective effort that may carry his voice across the services organization.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".