Alcohol Abuse/Dependence Symptoms Among Hospital Employees Exposed to a SARS Outbreak: Table 1
Bibliographic record
Abstract
AIMS: The aim of this study was to examine alcohol abuse/dependence symptoms among hospital employees exposed to a severe acute respiratory syndrome (SARS) outbreak, and the relationship between types of exposure to the SARS outbreak and subsequent alcohol abuse/dependence symptoms. METHODS: A survey was conducted among 549 randomly selected hospital employees in Beijing, China, concerning the psychological impact of the 2003 SARS outbreak. Subjects were assessed on sociodemographic factors and types of exposure to the outbreak, and on symptoms of post-traumatic stress (PTS), alcohol abuse/dependence and depression. RESULTS: Current alcohol abuse/dependence symptom counts 3 years after the outbreak were positively associated with having been quarantined, or worked in high-risk locations such as SARS wards, during the outbreak. However, having had family members or friends contract, SARS was not related to alcohol abuse/dependence symptom count. Symptoms of PTS and of depression, and having used drinking as a coping method, were also significantly associated with increased alcohol abuse/dependence symptoms. The relationship between outbreak exposure and alcohol abuse/dependence symptom count remained significant even when sociodemographic and other factors were controlled for. When the intrusion, avoidance and hyperarousal PTS symptom clusters were entered into the model, hyperarousal was found to be significantly associated with alcohol abuse/dependence symptoms. CONCLUSIONS: Exposure to an outbreak of a severe infectious disease can, like other disaster exposures, lead not only to PTSD but also to other psychiatric conditions, such as alcohol abuse/dependence. The findings will help policy makers and health professionals to better prepare for potential outbreaks of diseases such as SARS or avian flu.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".