Mental health among university employees during the COVID-19 pandemic: The role of previous life trauma and current posttraumatic stress symptoms.
Bibliographic record
Abstract
OBJECTIVE: Previous studies indicated that the coronavirus disease 2019 (COVID-19) pandemic has harmed the mental health of diverse samples. Adopting a trauma lens with a sample of university faculty and staff, this study examined risk conferred by previous exposure to traumatic life events (TLE) on pandemic-related mental health harm (MHH) and stress and the mediating influence of posttraumatic stress disorder (PTSD) symptoms. METHOD: = 641) of a public university in the United States completed an online cross-sectional survey, including validated scales of TLE and PTSD and single-item measures of MHH and stress taken from published COVID-19 studies. A structural probit model was used to estimate: (a) direct effects of cumulative TLE on PTSD, MHH, and stress; and (b) indirect effects of cumulative TLE via PTSD adjusting for age. Gender was tested as a moderating influence. RESULTS: Nearly 36% of the sample reported positive PTSD screens along with high levels of MHH (22.5%) and stress (42.3%). Cumulative TLE was significantly and positively associated with MHH and stress. Both genders experienced a negative impact on mental health and stress either fully or partially through PTSD symptoms; however, the gender by trauma interaction term was not significant. As age decreased, PTSD and MHH increased. CONCLUSION: Results suggest that PTSD symptoms play a crucial role in the experience of MHH and stress during the pandemic for those who endured previous trauma. Implications for employer policies, public health messaging, and mental health services are explored. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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How this classification was reachedexpand
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 | 0.010 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".