Developing a Framework to Evaluate Collaborative Mental Health Services in Primary Care Systems in Latin America
Bibliographic record
Abstract
Mental health, including substance and concurrent disorders, is a major public health challenge worldwide. Approaches to collaborative mental health care (CMHC) are being implemented in Latin America to strengthen the accessibility and delivery of mental health services in primary health care settings. However, there are no well-defined frameworks to evaluate CMHC. Objective: To develop a feasible and meaningful evaluation framework to support the ongoing improvement and performance measurement of services and systems in Latin America regarding CMHC. Methods: Three public health networks were selected in Mexico, Nicaragua and Chile. The study included: (1) a critical review of the literature focused on relevant health services research approaches, theory and evaluation models; (2) an environmental scan at each of the three research sites, comprising document reviews, key informant interviews with decision makers, focus groups with front line clinicians, and a survey for other key stakeholders, to better understand the local context and evaluation needs, as well as to identify some implementation challenges and opportunities; (3) a Delphi group with experts to identify the main areas of consensus, as well as disagreements about the importance and feasibility of evaluation dimensions; and (4) a final consultation in the three sites aimed at discussing preliminary results and refining the evaluation framework. Quantitative and qualitative data were integrated in the analysis. Results: A comprehensive evaluation framework for CMHC in Latin America was developed. It includes 5 levels, 28 dimensions and 40 domains, as well as examples of indicators and an implementation plan. A knowledge exchange strategy was developed aimed at reaching the research sites as well as the academic community and other stakeholders. Conclusion: The evaluation framework represents an important effort to foster accountability and quality regarding CMHC in Latin America. Recommendations to build upon current capacity and to successfully address the existing implementation challenges are further discussed.
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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 | 0.250 | 0.133 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.018 | 0.011 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.019 | 0.017 |
| Open science | 0.006 | 0.018 |
| Research integrity | 0.005 | 0.004 |
| 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".