Clinical Correlates of Alcohol Abuse among Adolescent Psychiatric Inpatients in Israel.
Bibliographic record
Abstract
BACKGROUND: Recent epidemiological studies have reported a world-wide increase in the rates of alcohol use among adolescents. Research has shown a strong link between alcohol abuse and psychiatric disorders. This study explored the clinical and demographic correlates of adolescents with a history of alcohol abuse (AA) compared to adolescents with no history of alcohol abuse (NAA) among a group of adolescent psychiatric inpatients in Israel. METHOD: Two hundred and thirty-eight subjects were screened, all were patients consecutively admitted to an adolescent inpatient unit at a university-affiliated mental health center in Israel during a 4-year period RESULT: Patients in the AA group were more prone to have a history of suicide attempts and self-injury compared to patients in the NAA group. Prevalence of attentiondeficit disruptive behavior disorders was more common in the AA group, and these patients were more prone to have a history of criminal activity and drug use. Median length of hospitalization was greater in the NAA group. LIMITATIONS: Limitations concerning attribution of causality due to the cross-sectional nature of this study. CONCLUSION: Higher prevalence of criminal behavior, selfinjury and suicide attempts associated with alcohol abuse may be related to higher levels of impulsivity, indicated by higher prevalence of attention-deficit disruptive behavior disorders. Alcohol-related disorders should be carefully screened and addressed in adolescent psychiatric units and in consequent ambulatory treatment settings.
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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 | 0.000 |
| 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) | 0.001 | 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".