Posttraumatic Stress Disorder, Gender, and Risk Factors: World Trade Center Tower Survivors 10 to 11 Years After the September 11, 2001 Attacks
Bibliographic record
Abstract
Abstract Ten to eleven years after the September 11, 2001 terrorist attacks, probable posttraumatic stress disorder (PTSD) was evaluated in 1,755 World Trade Center (WTC) evacuees based on data from the WTC Health Registry. Characteristics of men and women were compared and factors associated with PTSD symptom severity were examined using the PTSD Checklist (PCL). Compared with men (n = 1,015, 57.8%), women (n = 740, 42.2%) were younger and of lower socioeconomic status. Ten to eleven years after September 11, 2001, 13.7% of men and 24.1% of women met criteria for PTSD. Results indicated that when considered with all other variables (i.e., demographic, socioeconomic and social resources, exposure to the attacks, life events), gender was not a significant predictor of PTSD symptom severity. Being younger on September 11, 2001, unemployed, less educated, and/or having higher exposure to the attacks, unmet mental health care needs, and less social support predicted higher PCL scores for both genders (βs = .077 to .239). Demographic characteristics and socioeconomic resources (ΔR2 = .113) accounted for the largest amount of variance in PCL scores over and above exposure/evacuation, mental healthcare needs, and social support variables (ΔR2 = .093 to .102). When trends of unmet mental healthcare needs were analyzed, the most prevalent response for men was that they preferred to manage their own symptoms (15.1%), whereas the most prevalent response for women was that they could not afford to pay for mental health care (14.7%). Although the prevalence of probable PTSD in women tower survivors was approximately twice as high as it was for men, this is attributable largely to demographic and socioeconomic resource factors and not gender alone. Implications for treatment and interventions are discussed.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".