Associations between periods of COVID-19 quarantine and mental health in Canada
Bibliographic record
Abstract
Since the onset of the COVID-19 pandemic, many jurisdictions, including Canada, have made use of public health measures such as COVID-19 quarantine to reduce the transmission of the virus. To examine associations between these periods of quarantine and mental health, including suicidal ideation and deliberate self-harm, we examined data from a national survey of 3000 Canadian adults distributed between May 14-29, 2020. Notably, participants provided the reason(s) for quarantine. When pooling all reasons for quarantine together, this experience was associated with higher odds of suicidal ideation and deliberate self-harm in the two weeks preceding the survey. These associations remained even after controlling for age, household income, having a pre-existing mental health condition, being unemployed due to the pandemic, and living alone. However, the associations with mental health differed across reasons for quarantine; those who were self-isolating specifically due to recent travel were not found to have higher odds of suicidal ideation or deliberate self-harm. Our research suggests the importance of accounting for the reason(s) for quarantine in the implementation of this critical public health measure to reduce the mental health impacts of this experience.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".