Better practices in collaborative mental health care: an analysis of the evidence base.
Bibliographic record
Abstract
OBJECTIVES: To conduct a systematic review of the experimental literature in order to identify better practices in collaborative mental health care in the primary care setting. METHODS: A review of Canadian and international literature using Medline, PsycInfo, Embase, the Cochrane Library, and other databases yielded over 900 related reports, of which, 38 studies met the inclusion criteria. A systematic review and descriptive analysis is presented, with key conclusions and best practices. RESULTS: Successful collaboration requires preparation, time, and supportive structures, building on preexisting clinical relationships. Collaborative practice is likely to be most developed when clinicians are colocated and most effective when the location is familiar and nonstigmatizing for patients. Degree of collaboration does not appear to predict clinical outcome. Enhanced collaboration paired with treatment guidelines or protocols offers important benefits over either intervention alone in major depression. Systematic follow-up was a powerful predictor of positive outcome in collaborative care for depression. A clear relation between collaborative efforts to increase medication adherence and clinical outcomes was not evident. Collaboration alone has not been shown to produce skill transfer in PCP knowledge or behaviours in the treatment of depression. Service restructuring designed to support changes in practice patterns of primary health care providers is also required. Enhanced patient education was part of many studies with good outcomes. Education was generally provided by someone other than the PCP. Collaborative interventions that are part of a research protocol may be difficult to sustain long-term without ongoing funding. Consumer choice about treatment modality may be important in treatment engagement in collaborative care (for example, having the option to choose psychotherapy vs medication). CONCLUSIONS: A body of experimental literature evaluating the impact of enhanced collaboration on patient outcomes-primarily in depressive disorders-now exists. Better practices in collaborative mental health care are beginning to emerge.
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 | 0.075 | 0.212 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.017 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".