Quarantine and Mental Health During COVID-19: Exploring the Impact on Depressive Symptoms and Suicidal Ideation Among Adults in Canada
Bibliographic record
Abstract
Background: The COVID-19 pandemic led to significant public health measures, including mandatory quarantine, which had potential mental health implications. This thesis investigated the association between mandatory quarantine and mental health outcomes, specifically depressive symptoms and suicidal ideation, among adults in Canada. Objectives: The primary objective was to assess whether mandatory quarantine due to close contact with a COVID-19 case was associated with increased odds of depressive symptoms and suicidal ideation. Secondary objectives included identifying key demographic, socioeconomic, and psychosocial factors that may act as effect modifiers or confounders to these associations. Methods: A cross-sectional analysis was conducted using data from a national survey by Mental Health Research Canada. The study sample included 3012 Canadian adults who participated in the sixth poll conducted in April 2021. Logistic regression models were used to examine the associations between quarantine and the mental health outcomes, adjusting for potential confounders such as age, prior mood disorders, and resilience. Results: Quarantine was not significantly associated with depressive symptoms after adjusting for confounders (AOR = 1.25, 95% CI: 0.90 to 1.73). Similarly, no significant association was found between quarantine and suicidal ideation (AOR = 1.07, 95% CI: 0.69 to 1.65). However, strong associations were observed for other factors. Having a history of a prior mood disorder was significantly associated with both depressive symptoms (AOR = 5.02, 95% CI: 4.07 to 6.20) and suicidal ideation (AOR = 5.97, 95% CI: 4.05 to 7.92). Older age was consistently protective against both outcomes, with the 65+ age group showing the lowest odds of depressive symptoms (AOR = 0.27, 95% CI: 0.19 to 0.39) and suicidal ideation (AOR = 0.25, 95% CI: 0.14 to 0.42). Conclusions: While quarantine itself was not a significant predictor of depressive symptoms or suicidal ideation after adjusting for confounders, the findings underscored the importance of considering pre-existing mood disorders and demographic factors in understanding mental health risks during public health crises. Targeted interventions for high-risk populations, particularly those with a history of mood disorders, remain crucial in mitigating the mental health impacts of such crises in the future.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".