Psychological mediators of the associations between pandemic-related stressors and suicidal ideation across three periods of the COVID-19 pandemic in Canada
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic's mental health impact is well-established. While early evidence suggested suicide deaths remained stable or declined, suicidal ideation (SI) became more prevalent than before the pandemic. Our study: (1) examined the prevalence and distribution of SI among Canadian adults, (2) compared SI among those with and without pre-existing mental illnesses, and (3) evaluated associations between pandemic-related stressors (i.e., unemployment, insecure employment, loss of income, medical vulnerability, COVID-19 exposure) with SI, and whether such associations were mediated by depression, thwarted belongingness, perceived burdensomeness, or perceived discrimination. METHODS: The sample was comprised of data gathered at three timepoints (Wave 1 08/18/2020-10/01/2020, n = 6629; Wave 2 12/21/2020-03/31/2021, n = 5920; Wave 3 09/07/2021-12/07/2021, n = 7354). Quota-based responses from survey research panels which matched the geographic, age, and sex distribution of the Canadian population were supplemented with convenience-sampled responses. RESULTS: The prevalence of SI was 4.1 % (Wave 1), 5.3 % (Wave 2), and 5.8 % (Wave 3). Odds of SI were higher for respondents under the age of 35 years and with pre-existing mental illnesses. SI was associated with quarantining due to suspected or confirmed COVID-19 exposure, potential COVID-19 exposure at work, medical vulnerability toward COVID-19, insecure employment or unemployment, and income loss. These associations were mediated by psychological experiences, particularly depression and thwarted belongingness. LIMITATIONS: This cross-sectional, observational study cannot establish temporality or causality. CONCLUSION: Results highlight groups who may benefit from enhanced screening for depression and suicide risk. Reducing depression and increasing sense of belonging should be prioritized.
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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 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".