Achieving Quality Integrated Care for Adolescent Depression: A Scoping Review
Bibliographic record
Abstract
INTRODUCTION: While primary care is often the first point of contact for adolescents with depression, more than half of depressed adolescents are either untreated or undertreated. A scoping review had been completed to summarize approaches for achieving quality integrated care in primary care focused on adolescent depression. METHODS: The scoping review followed the methodological framework for scoping studies from Arksey and O'Malley. Articles were grouped into themes and mapped to 6 quality domains for integrated care from the practice integration profile survey and 3 levels of stakeholders based on WHO's definition for health systems (patient/family, primary care team, and national/sub-national health system). RESULTS: A total of 868 records were screened resulting in 22 articles at the patient/family-level (5/22), the primary care team-level (18/22), and the national/sub-national health system-level (16/22). The results highlighted multilevel approaches to support the delivery of quality integrated care for adolescent depression in primary care: (1) population-focused using patient registries, routine screening based on standardized algorithms, and patient-centered strategies, (2) team-driven where primary care clinicians collaborate with mental health clinicians as part of a primary care team, (3) evidence-based delivery of mental health services across the integrated care pathway from screening to follow-up visits, and (4) measurement-guided by leveraging the electronic health record infrastructure to learn from patient outcomes. CONCLUSION: More research is needed on how to provide quality integrated care for adolescent depression, specifically on patient engagement and retention, grounded in the frontline experiences of patients, families, and clinicians and supported by national and/or sub-national guidelines. A learning system could help integrate mental health services in primary care in a way that is consistent across the national and/or sub-national health system.
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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 | 0.052 | 0.174 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.023 | 0.022 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".