Alcohol and Violence-Related Injuries Among Emergency Room Patients in an International Perspective
Bibliographic record
Abstract
While alcohol has been found to be more closely associated with violence-related injury than with injury from other causes, little data is available which documents heterogeneity in this association across countries or cultures, taking into consideration usual drinking patterns and other socio-cultural variables. Data are reported from 15 countries comprising the Emergency Room Collaborative Alcohol Analysis Project and the WHO Collaborative Study on Alcohol and Injury. Case-crossover analysis was used to analyze the risk of injury (among current drinkers) from drinking six hours prior to the event, based on frequency of usual drinking, for violence-related injuries and separately for non-violence related injuries. Relative risk (RR) for a violence-related injury was significantly greater than for injuries from other causes across all countries (pooled RR=22.22 vs. 4.33), but the magnitude of risk varied considerably (ranging from 4.68 in Spain to 942 in Canada). Pooled effect size was found to be heterogeneous across countries, and was explained, in part, by the level of detrimental drinking pattern in a country. Risk for a violence-related injury was not significantly different by age (<30 and 30+), reporting 5 or more drinks on at least one occasion during the last year, or reporting symptoms of alcohol dependence. A number of methodological concerns suggest that risk of a violence-related injury compared to injuries from other causes may be inflated, and such variables as context of drinking should be taken into consideration in establishing relative risk and alcohol attributable fraction of violence-related injury across countries and cultures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".