A collaborative primary and mental health care model with psychologist and psychiatrist working in GP practices: process evaluation of the implementation, challenges, and sustainability
Bibliographic record
Abstract
BACKGROUND: Previous studies have shown that collaboration between primary care and mental health services can enhance accessibility and improve outcomes for patients seen in general practitioners' (GPs') office. There is, however, a lack of empirical evidence regarding the benefits of collaborative care in Norway. This study, part of a larger research project, examined the adaptation and implementation of a successful Canadian collaborative care model developed in Hamilton, Ontario, in three Norwegian GP practices located in different boroughs of Oslo, Norway's largest city. AIMS: To evaluate the required adaptations, implementation, challenges, and sustainability of the Hamilton model within the Norwegian context. METHODS: The overarching study was a cluster-randomised trial testing the adapted model in three urban GP practices over an 18-month period, with three additional GP practices from the same boroughs serving as control groups. Each intervention site included a half-time clinical psychologist from the local community mental health centre and a psychiatrist who visited for two hours each week. The project also aimed to extend collaboration to other health and community services within each borough. This paper evaluates the implementation of the project's intervention arm, using inductive thematic analysis of documents from all of the project's phases and following recommendations for the process evaluation of complex interventions. RESULTS: The model's core component-collaboration between GPs and mental health specialists-was successfully implemented. Participating GPs appreciated the convenient access to mental health specialists to assist with managing mental health problems, although they faced challenges in finding time for collaboration. However, health policy restrictions on providing financial support for co-located collaborative care rendered the model unsustainable beyond the trial period and impeded its expansion to further GP practices. CONCLUSIONS: The model was successfully implemented and viewed by participants as an improvement in healthcare delivery. For such a model to be sustained, however, adjustments must be made to align it with available resources, and reimbursements are needed for collaborative activities in GP practices. It also requires a recognition by funders and planners of the benefits of co-locating mental health specialists within GP practices.
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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 | 0.060 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".