PSYCHIATRY * P61 * DIMENSIONS AND CATEGORIES OF DSM V CRITERIA IN AN INTERNATIONAL SAMPLE OF DRINKING SUBJECTS AND INPATIENT ALCOHOL-DEPENDENT INDIVIDUALS
Bibliographic record
Abstract
DSM V-criteria of the diagnostic category alcohol use disorder have been proposed. Eleven criteria have been proposed which try to overcome some of the limitations of the DSM IV distinction between alcohol abuse and alcohol dependence. The aims of the analyses of two samples are: to confirm the dimensionality of DSM V criteria and to determine a potential diagnostic threshold and severity of an alcohol use disorder. This analysis takes advantage of the WHO/ISBRA Study on State and Trait Markers of Alcohol Use and Dependence data set. Subjects included into the analyses (n = 1424) were aged 18 and over were recruited in five countries: Australia (Sydney), Brazil (São Paulo), Canada (Montreal), Finland (Helsinki) and Japan (Sapporo). All DSM V criteria were determined in this sample by a structured interview. The CIGAR (Collaborative Initiative on Genetics in Alcoholism in CentRal Europe) sample of inpatient alcohol-dependent individuals from Germany was used to determine DSM V symptom severity (n = 635). Again, DSM V criteria were obtained using structured interviews (SSAGA, CIDI/DIA-X). The results indicate that dimensionality of DSM V alcohol use disorder criteria can be confirmed by IRT (Item Response Theory) statistics. However, using the criteria, a diagnostic threshold to distinguish between the presence or absence of the disorder is difficult to determine. Furthermore, a proposal is made, how alcohol use disorder severity can be defined by DSM V clinical symptoms and this proposal can be confirmed using a number of external validitors (e.g. comorbidity with mental disorders, alcohol consumption markers, suicidal behavior and rate of genetic risk variants).
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".