The experience of the 2003 SARS outbreak as a traumatic stress among frontline healthcare workers in Toronto: lessons learned
Bibliographic record
Abstract
The outbreak of severe acute respiratory syndrome (SARS) in the first half of 2003 in Canada was unprecedented in several respects. Understanding the psychological impact of the outbreak on healthcare workers, especially those in hospitals, is important in planning for future outbreaks of emerging infectious diseases. This review draws upon qualitative and quantitative studies of the SARS outbreak in Toronto to outline the factors that contributed to healthcare workers' experiencing the outbreak as a psychological trauma. Overall, it is estimated that a high degree of distress was experienced by 29-35% of hospital workers. Three categories of contributory factors were identified. Relevant contextual factors were being a nurse, having contact with SARS patients and having children. Contributing attitudinal factors and processes were experiencing job stress, perceiving stigmatization, coping by avoiding crowds and colleagues, and feeling scrutinized. Pre-existing trait factors also contributed to vulnerability. Lessons learned from the outbreak include: (i) that effort is required to mitigate the psychological impact of infection control procedures, especially the interpersonal isolation that these procedures promote; (ii) that effective risk communication is a priority early in an outbreak; (iii) that healthcare workers may have a role in influencing patterns of media coverage that increase or decrease morale; (iv) that healthcare workers benefit from resources that facilitate reflection on the effects of extraordinary stressors; and (v) that healthcare workers benefit from practical interventions that demonstrate tangible support from institutions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".