Prevalence of Psychiatric Disorders Among Toronto Hospital Workers One to Two Years After the SARS Outbreak
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: This study aimed to determine the incidence of psychiatric disorders among health care workers in Toronto in the one- to two-year period after the 2003 outbreak of severe acute respiratory syndrome (SARS) and to test predicted risk factors. METHODS: New-onset episodes of psychiatric disorders were assessed among 139 health care workers by using the Structured Clinical Interview for DSM-IV and the Clinician-Administered PTSD Scale. Past history of psychiatric illness, years of health care experience, and the perception of adequate training and support were tested as predictors of the incidence of new-onset episodes of psychiatric disorders after the SARS outbreak. RESULTS: The lifetime prevalence of any depressive, anxiety, or substance use diagnosis was 30%. Only one health care worker who identified the SARS experience as a traumatic event was diagnosed as having PTSD. New episodes of psychiatric disorders occurred among seven health care workers (5%). New episodes of psychiatric disorders were directly associated with a history of having a psychiatric disorder before the SARS outbreak (p=.02) and inversely associated with years of health care experience (p=.03) and the perceived adequacy of training and support (p=.03). CONCLUSIONS: Incidence of new episodes of psychiatric disorders after the SARS outbreak were similar to or lower than community incidence rates, which may indicate the resilience of health care workers who continued to work in hospitals one to two years after the SARS outbreak. In preparation for future events, such as pandemic influenza, training and support may bolster the resilience of health care workers who are at higher risk by virtue of their psychiatric history and fewer years of health care experience.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it