Post-traumatic stress disorder among persons with HIV who engage in heavy alcohol consumption in southwestern Uganda
Bibliographic record
Abstract
BACKGROUND: We aimed to describe the prevalence of PTSD symptoms and its associated factors in persons living with HIV (PLWH) in Uganda who engage in heavy alcohol use. METHODS: We analyzed baseline data from the Drinkers Intervention to Prevent Tuberculosis study which enrolls PLWH with latent tuberculosis who engage in heavy alcohol consumption. Using the primary care Post Traumatic Stress Disorder (PTSD) screening scale from the DSM-5 (PC-PTSD-5), probable PTSD was defined as reporting ≥3 of 5 assessed symptoms. We conducted the Alcohol Use Disorders Identification Test-Consumption and assessed demographics, smoking, symptoms of depression, and spirituality/religiosity. RESULTS: Of 421 participants enrolled from 2018 through 2020, the majority (68.2%) were male, median age was 40 years (interquartile range [IQR]: 32-47), and median AUDIT-C score was 6 [IQR: 4-8]. Half (50.1%) of the participants reported ever experiencing a traumatic event, and 20.7% reported ≥3 symptoms of PTSD. The most commonly reported PTSD symptoms in the past 1 month in the entire sample were avoidance (28.3%), nightmares (27.3%), and being constantly on guard (21.6%). In multivariable logistic regression analyses, level of alcohol use was not associated with probable PTSD (adjusted odds ratio [AOR] for each AUDIT-C point: (1.02; 95% CI: 0.92-1.14; p = 0.69); however, lifetime smoking (AOR 1.89; 95% CI: 1.10-3.24) and reporting symptoms of depression (AOR 1.89; 95% CI: 1.04-3.44) were independently associated with probable PTSD. CONCLUSIONS AND RECOMMENDATIONS: A history of traumatic events and probable PTSD were frequently reported among persons who engage in heavy drinking, living with HIV in Uganda. Level of alcohol use was not associated with probable PTSD in this sample of PLWH with heavy alcohol use, however other behavioral and mental health factors were associated with probable PTSD. These data highlight the high prevalence of PTSD in this group, and the need for screening and interventions for PTSD and mental health problems.
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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 | 0.001 |
| 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".