Prevalence and determinants of depression, anxiety, and stress symptoms among Black individuals in Canada in the context of the COVID-19 pandemic
Bibliographic record
Abstract
The COVID-19 pandemic has disproportionately affected Black communities in Canada in terms of infection, hospitalizations, and mortality rates. It exacerbated social, economic and health disparities that can impact their mental health. We investigated the prevalence and predictors of symptoms of depression, anxiety, and stress in Black individuals in Canada. A community-representative weighted sample of 2002 Black individuals (51.66% women) aged 14 to 94 years old (Mean age 29.34; SD = 10.13). Overall, 40.94%, 44.50%, and 31.36% of participants were classified as having clinically meaningful anxiety, depression, and stress levels, respectively, based on DASS scores. Men (45.92%) reported a higher prevalence of anxiety than women (36.27%), χ2 (1) = 19.24, p<.001, but similar symptoms of depression and stress. Progression of prevalence of anxiety, depression, and stress symptoms were consistent with the progression of prevalence of everyday racial discrimination. After controlling for socio-demographic variables, regression models showed that everyday discrimination (B= .14, p=.001, B= .14, p= .006, B= .18, p< .001), major experiences of racial discrimination (B= .30, p=.046, B= .34, p= .033, B= .35, p=.024), and COVID-19 traumatic stressors (B= .43, p<.001, B= .43, p< .001, B= .44, p< .001) were positively associated with anxiety, while community resilience (B= -.02, p= .039, B= -.04, p= .001, B= -.03, p= .014) was negatively associated with anxiety, depression, and stress, respectively. This study demonstrates the need to address racial discrimination in prevention and intervention programs among Black individuals and to consider intersectional factors related to age, birthplace, language spoken, and province of residence.
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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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".