Refugee status is associated with double the odds of psychological distress in mid-to-late life: Findings from the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
Psychological distress is associated with a range of negative outcomes including lower quality of life and an increased risk of premature all-cause mortality. The prevalence of, and factors associated with, psychological distress among middle-aged and older Canadians are understudied. Using the Canadian Longitudinal Study on Aging (CLSA) baseline data, this study examined factors associated with psychological distress among adults between 45 and 85 years, including refugee status and a wide range of sociodemographic, health-related and social support characteristics. Psychological distress was measured by Kessler's Psychological Distress Scale-K10 scores. Bivariate and multivariable binary logistic regression analyses were conducted. The prevalence of psychological distress was significantly higher among the 244 refugees (23.8%), compared to 23,149 Canadian-born Canadians (12.8%) and 4,765 non-refugee immigrants (12.6%), despite the fact that the average time the refugees had lived in Canada was more than four decades. The results of the binary logistic regression analysis indicated refugees had twice the age-sex adjusted odds of psychological distress (OR = 2.31, 95% CI: 1.74, 3.07). Even after further adjustment for 16 potential risk factors, a significant relationship remained between refugee status and psychological distress (OR = 1.56; 95% CI = 1.12, 2.17). Other significant factors associated with psychological distress included younger age, female gender, visible minority status, lower household income, not having an undergraduate degree, multimorbidities, chronic pain, and lack of social support. Policies and interventions addressing psychological distress among Canadians in mid- to later life should target refugees and other vulnerable groups.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".