A Prospective Post-disaster Longitudinal Follow-up Study of Emotional and Psychosocial Outcomes of the Oklahoma City Bombing Rescue and Recovery Workers During the First Quarter Century Afterward
Bibliographic record
Abstract
OBJECTIVE: Little prospectively assessed post-disaster longitudinal research has been done on mental health (MH) outcomes of disaster rescue and recovery workers. This longitudinal prospective study, which is examining first responders to a terrorist bombing in Oklahoma City after nearly a quarter century, was conducted to investigate their long-term MH outcomes using full diagnostic assessments. This will most accurately inform planning for longitudinal MH care needs. METHODS: Longitudinal follow-up interviews of 124 rescue and recovery workers, from an original volunteer sample of 181 volunteer workers, were completed 3 years after the bombing, and reassessed 23 years after using consistent research methods. Structured diagnostic interviews were conducted at both assessments, but these were limited to posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) with additional questions about alcohol use, problems, and major psychosocial problems of life at follow up. RESULTS: Initially, the rescue and recovery workers had a lower prevalence of post-disaster PTSD and MDD than directly exposed survivors. They also showed higher rates of PTSD than MDD. However, over time, PTSD increased a little while MDD increased 4-fold though fewer than 50% of the cases were remitted. CONCLUSION: Low remission and increasing MDD provide incentives for surveillance and availability of treatment for decades after disaster, regardless of whether they were pre-existing conditions or disaster related.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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".