PPE shortages and healthcare workers' mental health during the COVID‐19 pandemic in Canada
Bibliographic record
Abstract
Abstract Personal protective equipment (PPE) is critical among healthcare professionals, considering that it serves as the first line of defense against infectious diseases and hazards in the healthcare environment. Therefore, the shortage of PPE during the COVID‐19 pandemic exposed a unique vulnerability within the healthcare system, heightening the risk of infection among healthcare professionals. Despite this evidence, few studies have explored whether this negative impact of PPE scarcity extends to mental health among healthcare professionals in Canada. Using the Survey on Healthcare Workers' Experiences During the Pandemic conducted by Statistics Canada (n = 12,246), the current study aims to address this void by exploring the association between PPE shortages and two indicators of mental health—depression and general anxiety disorder. We found that 18% and 26% of healthcare professionals reported depression and general anxiety disorder, respectively. Results from logistic regression analyses indicate that healthcare professionals who faced at least one PPE restriction were more likely to report general anxiety disorder. Additionally, professionals who experienced four or more restrictions were more likely to report depression (OR = 1.28, p<0.01), compared to those who did not experience any restriction. Based on these findings, we discuss whether the stress and anxiety resulting from inadequate protection during the pandemic may point to the importance of understanding the broader implications of PPE shortages on the mental well‐being of healthcare professionals. The current study highlighted that it is essential to craft evidence‐based policies that not only prioritize the physical safety of healthcare professionals but also their mental well‐being, ultimately strengthening the healthcare system's response to crises.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 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) | 0.002 | 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".