Psychological assessment of alcoholism in males
Bibliographic record
Abstract
BACKGROUND: Little work has been done in India on the personality factors of alcoholics. These personality factors have a significant effect on treatment outcome. AIM: To study the personality characteristics, stressful life events and diagnostic utility of the Michigan Alcoholism Screening Test (MAST) and CAGE (Cutting down, Annoyance by criticism, Guilty feeling, and Eye-opener) Questionnaire in service personnel with alcohol dependence. METHODS: Psychological assessment of 100 consecutive male inpatients meeting the DSM-IV criteria for alcohol dependence, and an equal number of controls matched for age, sex, occupation and regional background was carried out utilizing the MAST, CAGE Questionnaire, State-Trait Anxiety Inventory, Hamilton Rating Scale for Depression, Multiphasic Personality Questionnaire, Maudsley Personality Inventory, Toronto Alexithymia Scale, Self-esteem Inventory and Presumptive Stressful Life Events scale. RESULTS: The MAST and CAGE were of limited value in the diagnosis of alcohol dependence. Alcoholics obtained significantly higher scores on state and trait anxiety, depression, mania scale, paranoia scale, schizophrenia scale, psychopathic deviance, neuroticism, extroversion, and the Presumptive Stressful Life Events scale. Alcohol-dependent individuals had significantly lower self-esteem compared with control subjects, and significantly more alcoholics were identified as alexithymic. CONCLUSION: Alcohol-dependent individuals show significantly high neuroticism, extroversion, anxiety, depression, psychopathic deviation, stressful life events and significantly low self-esteem as compared with normal control subjects. Significantly more alcoholics were found to be alexithymic compared with normal controls.
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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) | 0.002 | 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".