Psychological response to the COVID-19 pandemic in Canada: main stressors and assets
Bibliographic record
Abstract
BACKGROUND: The COVID-19 crisis has unique features that increase the sense of fear, and comes with additional stressors (e.g., confusion, discrimination, quarantine), which can lead to adverse psychological responses. There is however limited understanding of differences between sociocultural contexts in psychological response to pandemics and other disasters. OBJECTIVE: To examine how Canadians in different provinces, and with different governance modes and sociocultural contexts, understand and react to the COVID-19 pandemic. METHODS: =300 elsewhere in Canada). Two psychological outcomes were assessed: probable post-traumatic stress disorder (PTSD), and probable generalized anxiety disorder (GAD). The roles of various stressors (i.e., threat perceived for oneself or family/friends, quarantine or isolation, financial losses, victims of stigma), assets (i.e., trust in authorities, information received, and compliance with directives) and sources of information used on these two outcomes were also examined. Chi-square tests were performed to examine differences in the distribution of probable PTSD and GAD according to these stressors and assets. RESULTS: Probable PTSD and GAD were observed in 25.5% and 25.4% of the respondents, respectively. These proportions were significantly lower in Quebec than elsewhere in Canada. Perceiving a high level of threat and being a victim of stigma were positively associated with probable PTSD and GAD (but not quarantine/isolation and financial losses). A high level of trust in authorities was the only asset associated with a lower risk of PTSD or GAD. Interestingly, this asset was more frequently reported in Quebec than elsewhere in Canada. CONCLUSION: The COVID-19 pandemic represents a unique opportunity to evaluate the psychosocial impacts on various sociocultural groups and contexts, providing important lessons that could help respond to future disasters.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".