P-19STUDY OF INSIGHT IN SCHIZOPHRENIC PATIENTS WITH ALCOHOL ABUSE OR DEPENDENCE
Bibliographic record
Abstract
Objectives. The aim of this study is to investigate the relationship between insight and treatment adherence and to analyze the influence of other clinical and socio-demographic factors. Methods. Subjects included in the study were diagnosed of Acohol Abuse or Dependence comorbid with Schizophrenic Disorder, following DSM-IVTR criteria and received treatment in a Mental Health Outpatient Clinic. Medical records were reviewed and a socio-demographic questionnaire was developed for this purpose (sex, age, marital status, educational level, occupational status, level of family support). Patients were evaluated over a period of 2 years. Instruments used were Scale of Unawareness of Mental Disorders (SUMD), Drug Attitude Inventory (DAI), and Calgary Depression Scale (CDSS) with a cut-off point 4/5. Results. A total of 17 patients were included in the study. Mean age 38.7 years (SD:7.4). 26% of the subjects had at least had one prior hospital admission and 72% reported having occasionally discontinued their medication. Men presented higher score in SUMD (lower global awareness of disease). Patients with poor insight have the highest drop-out rates of treatment and follow-up care, highest readmission rates and emergency department utilization, and lower scores on the DAI scale, (p <0.05).
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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 | 0.002 |
| 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) | 0.003 | 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".