Experiences of immigrants when accessing mental health services and psychosocial supports in Canada: Protocol for a scoping review
Bibliographic record
Abstract
In Canada, the mental health needs of immigrants from diverse ethnic backgrounds are a growing concern, as they are at a higher risk for adverse mental health outcomes compared to native-born Canadians. These challenges are often driven by stressors experienced both before and after their settlement. The limited research on immigrant experiences in accessing mental health and psychosocial support highlights the need for our study. Compounding this gap, existing data reveal significant challenges immigrants face in accessing mental health services. Therefore, to better understand and address the needs of Canada's immigrant population, we are conducting a scoping review to identify and synthesize the existing literature on immigrants' experiences when accessing mental health services and psychosocial support. This scoping review will follow the methodological framework outlined by Arksey and O'Malley and complimented by Joanna Briggs Institute guidelines, as well as the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for scoping review. To ensure intercoder reliability (ICR), the team will conduct a calibration exercise before initiating the screening process. This will involve an independent screening by all reviewers followed by a team discussion to resolve any discrepancies and clarify the application of inclusion/exclusion criteria. All stages of the selection process will be conducted using Covidence, a web-based software platform designed to support systematic reviews. Our analysis will involve both quantitative and qualitative approaches to align with the nature of the included articles and address our research questions. By synthesizing the current state of knowledge, identifying gaps, and highlighting potential solutions, this protocol aims to contribute to the ongoing crucial efforts to improve mental health outcomes for Canada's immigrant population.
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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 | 0.089 | 0.068 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.011 | 0.013 |
| Bibliometrics | 0.018 | 0.015 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.055 | 0.009 |
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".