The prevalence of distress, depression, anxiety, and substance use issues among Indigenous post-secondary students in Canada
Bibliographic record
Abstract
This study aimed to estimate the prevalence of mental illness and substance use among Indigenous students attending Canadian post-secondary institutions. We obtained data from the National College Health Assessment - American College Health Association Spring 2013 survey, which includes 34,039 participants in 32 post-secondary institutions across Canada. We calculated prevalence estimates with 95% confidence intervals (CI). We compared Indigenous and non-Indigenous students using age- and sex-adjusted prevalence ratios (PR) obtained from Poisson regression models. Of the total sample, 1,110 (3.3%) post-secondary students self-identified as Indigenous. Within the past 12 months, Indigenous students had higher odds of intentionally injuring themselves (PR = 1.53, 95% CI = 1.27-1.84), seriously considering suicide (PR = 1.32, 95% CI = 1.12-1.56), attempting suicide (PR = 1.74, 95% CI = 1.16-2.62), or having been diagnosed with depression (PR = 1.26, 95% CI = 1.08-1.47) or anxiety (PR = 1.18, 95% CI = 1.02-1.35) when compared with non-Indigenous students. Indigenous students also had higher odds of having a lifetime diagnosis of depression (PR = 1.31, 95% CI = 1.17-1.47) when compared with non-Indigenous students. Indigenous students were more likely to report binging on alcohol (PR = 1.10, 95% CI = 1.02-1.19), using marijuana (PR = 1.21, 95% CI = 1.06-1.37), and using other recreational drugs (PR = 1.32, 95% CI = 1.06-1.63) compared to non-Indigenous students. This study demonstrates that Indigenous students at post-secondary institutions across Canada experience higher prevalence of mental health and related issues compared to the non-Indigenous student population. This information highlights the need to assess the utilization and ensure the appropriate provision of mental health and wellness resources to support Indigenous students attending post-secondary institutions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".