Immigrant Mental Health, A Public Health Issue: Looking Back and Moving Forward
Bibliographic record
Abstract
The Mental Health Commission of Canada's (MHCC) strategy calls for promoting the health and wellbeing of all Canadians and to improve mental health outcomes. Each year, one in every five Canadians experiences one or more mental health problems, creating a significant cost to the health system. Mental health is pivotal to holistic health and wellbeing. This paper presents the key findings of a comprehensive literature review of Canadian research on the relationship between settlement experiences and the mental health and well-being of immigrants and refugees. A scoping review was conducted following a framework provided by Arskey and O'Malley (Int J Soc Res Methodol 8:19-32, 2005). Over two decades of relevant literature on immigrants' health in Canada was searched. These included English language peer-reviewed publications from relevant online databases Medline, Embase, PsycInfo, Healthstar, ERIC and CINAHL between 1990 and 2015. The findings revealed three important ways in which settlement affects the mental health of immigrants and refugees: through acculturation related stressors, economic uncertainty and ethnic discrimination. The recommendations for public health practice and policy are discussed.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".