Formative evaluation of practice changes for managing depression within a Shared Care model in primary care
Bibliographic record
Abstract
Aim To investigate the implementation and initial impact of the Physician Integrated Network (PIN) mental health indicators, which are specific to screening and managing follow-up for depression, in three primary care practices with Shared Mental Health Care in Manitoba. BACKGROUND: Manitoba Health undertook a primary care renewal initiative in 2006 called the PIN, which included the development of mental health indicators specific to screening and managing follow-up for depression. These indicators were implemented in three PIN group practice sites in Manitoba, which are also part of Shared Mental Health Care. METHODS: The design was a non-experimental longitudinal design. A formative evaluation investigated the implementation and initial impact of the mental health indicators using mixed methods (document review, survey, and interview). Quantitative data was explored using descriptive and comparative statistics and a content and theme analysis of the qualitative interviews was conducted. Survey responses were received from 32 out of 36 physicians from the three sites. Interviews were conducted with 15 providers. Findings This evaluation illustrated providers' perceived attitudes, knowledge, skills, and behaviours related to recognizing and treating depression and expanded our understanding of primary care processes related to managing depression related to the implementation of a new initiative. Depression is viewed as an important problem in primary care practice that is time consuming to diagnose, manage and treat and requires further investigation. Implementation of the PIN mental health indicators was variable across sites and providers. There was an increase in use of the indicators across time and a general sentiment that benefits of screening outweigh the costs; however, the benefit of screening for depression remains unclear. Consistent with current guidelines, a question the findings of this evaluation suggests is whether there are more effective ways of having an impact on depression within primary care than screening.
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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 | 0.138 | 0.163 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".