COVID-19 Pandemic: Stress, Anxiety, and Depression Levels Highest amongst Indigenous Peoples in Alberta
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study explores differences in stress, anxiety, and depression experienced by different ethnic groups during the COVID-19 pandemic. This was a cross-sectional online survey of subscribers of the COVID-19 Text4Hope text messaging program in Alberta. Stress, anxiety, and depression were measured among Caucasian, Indigenous, Asian, and other ethnic groups using the Perceived Stress Scale (PSS)-10, Generalized Anxiety Disorder (GAD)-7, and Patient Health Questionnaire (PHQ)-9 scales, respectively. The burden of depression and stress were significantly higher in Indigenous populations than in both Caucasian and Asian ethnic groups. The mean difference between Indigenous and Caucasian for PHQ-9 scores was 1.79, 95% CI of 0.74 to 2.84, p < 0.01 and for PSS-10 it was 1.92, 95% CI of 0.86 to 2.98, p < 0.01). The mean difference between Indigenous and Asian for PHQ-9 scores was 1.76, 95% CI of 0.34 to 3.19, p = 0.01 and for PSS-10 it was 2.02, 95% CI of 0.63 to 3.41, p < 0.01. However, Indigenous participant burden of anxiety was only significantly higher than Asian participants’ (mean difference for GAD-7 was 1.91, 95% CI of 0.65 to 3.18, p < 0.01). Indigenous people in Alberta have higher burden of mental illnesses during the COVID-19 pandemic. These findings are helpful for service planning and delivery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 it