Mental health during the COVID-19 pandemic in a longitudinal study of Hurricane Katrina survivors
Bibliographic record
Abstract
While the COVID-19 pandemic is known to have caused widespread mental health challenges, it remains unknown how the prevalence, presentation, and predictors of mental health adversity during the pandemic compare to other mass crises. We shed light on this question using longitudinal survey data (2003-2021) from 424 low-income mothers who were affected by both the pandemic and Hurricane Katrina, which struck the U.S. Gulf Coast in 2005. The prevalence of elevated posttraumatic stress symptoms was similar 1-year into the pandemic (41.6%) as 1-year post-Katrina (41.9%), while elevated psychological distress was more prevalent 1-year into the pandemic (48.3%) than 1-year post-Katrina (37.2%). Adjusted logistic regression models showed that pandemic-related bereavement, fear or worry, lapsed medical care, and economic stressors predicted mental health adversity during the pandemic. Similar exposures were associated with mental health adversity post-Katrina. Findings underscore the continued need for pandemic-related mental health services and suggest that preventing traumatic or stressful exposures may reduce the mental health impacts of future mass crises.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".