Socioeconomic inequalities in psychological distress and suicidal behaviours among Indigenous peoples living off-reserve in Canada
Bibliographic record
Abstract
BACKGROUND: Indigenous peoples in Canada have high rates of psychological distress and suicide. We sought to assess the socioeconomic inequalities in psychological distress and suicidal behaviours, and the factors that explain them within Indigenous peoples living off-reserve. METHODS: Using the nationally representative 2012 Aboriginal Peoples Survey collected from Indigenous adults living off-reserve in Canada, we measured income-related inequalities in psychological distress (measured on the 10-item Kessler Psychological Distress Scale) and suicidal behaviours (suicidal ideation and suicide attempt) and identified factors contributing to these inequalities using the concentration index (C) approach. RESULTS: Among 14 410 individuals representing 600 750 Indigenous adults (aged ≥ 18 yr) living off-reserve in Canada, the mean score of psychological distress was 16.1; 19.4% reported lifetime suicidal ideation and 2.2% reported a lifetime suicide attempt. Women had higher psychological distress scores (mean score 16.7 v. 15.2, p < 0.001), and prevalence of suicidal ideation (21.9% v. 16.1%, p < 0.001) and suicide attempts (2.3% v. 2.0%, p = 0.002) than men. Poorer individuals disproportionately experienced higher psychological distress (C = −0.054, 95% confidence interval [CI] −0.057 to −0.050), suicidal ideation (Cn = −0.218, 95% CI −0.242 to −0.194) and suicide attempts (Cn = −0.327, 95% CI −0.391 to −0.263). Food insecurity and income, respectively, accounted for 40.2% and 13.7% of the psychological distress, 26.7% and 18.2% of the suicidal ideation and 13.4% and 7.8% of the suicide attempts concentrated among low-income Indigenous peoples. INTERPRETATION: Substantial income-related inequalities in psychological distress and suicidal behaviours exist among Indigenous peoples living off-reserve in Canada. Policies designed to address major contributing factors such as food insecurity and income may help reduce these inequalities.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".