COVID-19 Pandemic: Influence of Gender Identity on Stress, Anxiety, and Depression Levels in Canada
Bibliographic record
Abstract
Background: This cross-sectional study explored variation of the prevalence of perceived stress, depression and anxiety among different self-identified gender identity groups in the Canadian population during the early stages of the COVID-19 pandemic. Methods: Anxiety, depression, and stress were assessed using the Generalized Anxiety Disorder 7-item (GAD-7) scale, Patient Health Questionnaire-9 (PHQ-9), and Perceived Stress Scale (PSS) respectively. Data were analyzed using one-way analysis of variance. Results: There were 8267 respondents to the online survey; 982 (12.0%) were male-identified, 7120 (86.9%) female-identified, and 92 (1.1%) identified as a diverse gender group. Prevalence rates for clinically meaningful anxiety (333 (41.7%), 2882 (47.6%), 47 (61.0%)), depression (330 (40.2%), 2736 (44.3%), 46 (59.7%)), and stress (702 (79.6%), 5711 (86.4%), 74 (90.2%)) were highest among respondents who self-identified as “other gender” followed by female-identified and then male-identified, respectively. There were statistically significant differences between gender groups for mean scores on GAD-7 (F (2, 6929) = 18.02, p < 0.001), PHQ-9 (F (2, 191.4) = 11.17, p < 0.001), and PSS (F (2, 204.6) = 21.13, p < 0.001). Conclusions: Gender identity differences exist in terms of the prevalence and severity of anxiety, depressive, and stress symptoms during the COVID-19 pandemic. This finding highlights the importance of incorporating self-identified gender identity in medical research, clinical practice, and policy.
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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) | 0.001 | 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".