Collaboration médecine-psychologie : évolution des mentalités en Belgique et évolution du système de soins de santé au Canada
Bibliographic record
Abstract
Objectives 1) To give a portrait of the evolving mentalities prevailing in Belgium on the collaboration between psychologists and general practitioners, and identify the barriers to the development of the collaboration between those two health professionals 2) To report on the primary care reform in Canada, its role in fostering collaborative practice in primary mental health and on the strategies needed to improve collaboration.Methods Literature search using PubMed and Google Scholar.Results Because of the unmet need of psychologists in primary care, general practitioners and psychologists have a propensity to work together. However to facilitate the collaborative process there needs to be system changes and clear definition of scopes of practices. Both countries are at different levels of implementing change. In Belgium for example it is only very recently that the autonomous practice of clinical psychology has been acknowledged. In Canada although the primary care reform has put forward and supported collaborative care, focus on mental health is insufficient. Early reports on collaborative care in the new models of care inconsistently report improved health outcomes. Strategies to improve collaborative care are looking at teaching future health professionals on how to work together by integrating inter-professional education.Conclusion Both the health care system and graduate training need to support foster and teach collaborative care.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".