Scoping review protocol: education initiatives for medical psychiatry collaborative care
Bibliographic record
Abstract
INTRODUCTION: The collaborative care model is an approach providing care to those with mental health and addictions disorders in the primary care setting. There is a robust evidence base demonstrating its clinical and cost-effectiveness in comparison with usual care; however, the transitioning to this new paradigm of care has been difficult. While there are efforts to train and prepare healthcare professionals, not much is known about the current state of collaborative care training programmes. The objective of this scoping review is to understand how widespread these collaborative care education initiatives are, how they are implemented and their impacts. METHODS AND ANALYSIS: The scoping review methodology uses the established review methodology by Arksey and O'Malley. The search strategy was developed by a medical librarian and will be applied in eight different databases spanning multiple disciplines. A two-stage screening process consisting of a title and abstract scan and a full-text review will be used to determine the eligibility of articles. To be included, articles must report on an existing collaborative care education initiative for healthcare providers. All articles will be independently assessed for eligibility by pairs of reviewers, and all eligible articles will be abstracted and charted in duplicate using a standardised form. The extracted data will undergo a 'narrative review' or a descriptive analysis of the contextual or process-oriented data and simple quantitative analysis using descriptive statistics. ETHICS AND DISSEMINATION: Research ethics approval is not required for this scoping review. The results of this scoping review will inform the development of a collaborative care training initiative emerging from the Medical Psychiatry Alliance, a four-institution philanthropic partnership in Ontario, Canada. The results will also be presented at relevant national and international conferences and published in a peer-reviewed journal.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
| grok | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| opus | Meta-epidemiology (broad) Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | medium |
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 | 0.155 | 0.169 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.018 | 0.021 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.007 | 0.010 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.175 | 0.045 |
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, unvalidatedLabeled directly by 3 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".