Addressing the mental health impacts of COVID-19 on Canada’s frontline workers
Bibliographic record
Abstract
On June 21, 2018, the Federal Framework on Post-Traumatic Stress Disorder Act became law, after receiving all-party support in the Parliament of Canada.This ground-breaking Act acknowledges that those in certain occupations, including public safety personnel (PSP) such as police, firefighters, paramedics, search and rescue personnel, Indigenous emergency managers, correctional employees, operational and intelligence personnel, border services personnel, and public safety communicators, along with healthcare professionals (HCPs) and military personnel, are at greater risk of exposure to potentially traumatic events, and therefore are more likely to develop posttraumatic stress disorder (PTSD) than the general population, just by doing their jobs (Public Health Agency of Canada [PHAC], 2019).The Act mandated PHAC to lead a coordinated, national approach to recognize PTSD among those within these occupational groups and, through this recognition, to help lay the groundwork for more timely access to mental health and well-being supports for those affected.As such, the Federal Framework on PTSD was created by PHAC in collaboration with multiple stakeholders.Through research, promotion, and implementation of best practices, education, awareness, and evidence-based treatments, this framework seeks to ensure the creation of solutions for those affected by occupation-related PTSD.The Federal Framework on PTSD Act was passed in 2018, and its relevance has only increased in significance during the COVID-19 pandemic.According to preliminary data from a study on the mental health effects of working the frontlines of the COVID-19 pandemic, 35% of Canadian PSP scored above 33 on the PCL-5, a self-report psychological instrument that assesses for the diagnostic symptoms of PTSD.Scores above 33 on the PCL-5 are compatible with the presence of symptoms severe enough to require formal treatment for PTSD.Furthermore, when screened for symptoms of depression, anxiety, and stress using the Depression, Anxiety, and Stress Scale 21 (DASS-21), an alarming percentage of PSP scored within the moderate to extremely severe range for depression (41%), for anxiety (over
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".