Posttraumatic Stress Disorder Is a Risk Factor for Multiple Addictions in Police Officers Hospitalized for Alcohol
Bibliographic record
Abstract
BACKGROUND: In police officers, posttraumatic stress disorder (PTSD) is associated with alcohol use disorder (AUD), but we lack data on the association between PTSD and other substance-related and addictive disorders. OBJECTIVES: We assessed whether PTSD could be a risk factor for different substance-related and addictive disorders in police officers, including alcohol, tobacco, cannabis, and gambling. METHOD: This cross-sectional study included all police officers admitted consecutively for alcohol to an inpatient ward dedicated to police officers (Le Courbat rehabilitation center, France; n= 133). Each patient completed self-administered questionnaires that assessed lifetime exposure to potentially traumatic events (Life Event Checklist for DSM-5), PTSD severity and diagnosis (PTSD Checklist for DSM-5), AUD severity (Alcohol Use Disorder Identification Test [AUDIT]), tobacco dependence (Fagerström test for Nicotine Dependence), cannabis dependence (Cannabis Abuse Screening test), and gambling disorder (Canadian Problem Gambling Index). RESULTS: Mean AUDIT score was 23.7 ± 8.0; 66.2% had an AUDIT score ≥20. Our sample comprised a high prevalence for PTSD (38.3%) and for substance-related and addictive disorders: tobacco dependence (68.4%), cannabis dependence (3.8%), and pathological gambling (3%). Patients with PTSD experienced higher lifetime exposure to traumatic experiences: physical assault, severe human suffering, sudden accidental death of another person, and other types of stressful events/experiences. In multiple linear regressions adjusted for age, sex, and marital status, PTSD was a significant predictor of the severity of AUD and tobacco use disorder, but not of the severity of cannabis use disorder nor gambling disorder. CONCLUSIONS: PTSD is common in police officers hospitalized for alcohol and associated with a higher severity of some addictive disorders (alcohol/tobacco). PTSD and its comorbid addictive disorders should be systematically screened and treated in this population.
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".