Symptoms of Posttraumatic Stress During the COVID-19 Pandemic in the Governmental Public Health Workforce and General Population
Bibliographic record
Abstract
We aimed to estimate the prevalence of COVID-19-related posttraumatic stress symptoms (PTSS) in the governmental public health workforce and in US adults, assess differences in reporting PTSS within subgroups, and evaluate whether frontline workers reported higher levels of PTSS than persons in other jobs. We used data from 2 nationally representative studies: the 2021 Public Health Workforce Interests and Needs Survey (PH WINS) and the COVID-19 and Life Stressors Impact on Mental Health and Well-being (CLIMB) study. Our study found that the state and local governmental public health workforce was more likely to report PTSS than the general adult population. Almost a quarter of public health agency employees (24.7%) and 21.1% of adults reported at least 3 symptoms of posttraumatic stress. Differences in levels of PTSS appeared within demographic groups for both samples. Personal care and service frontline workers had 4.3 times the odds of reporting symptoms of posttraumatic stress than non-frontline workers.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".