Personality Disorders among Alcoholic Outpatients: Prevalence and Course in Treatment
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence of concurrent personality disorders (PDs) among alcoholic men and women seeking outpatient treatment, and to examine their effect on the course of alcohol treatment. METHOD: Patients with alcohol use disorders (n = 165) were assessed by clinical and semi-structured interviews, as well as self-report scales, to measure levels of psychological distress, impulsivity, social functioning, and addiction severity at treatment intake. PD diagnoses were assessed using the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Personality Disorder (SCID-II). Course in treatment was monitored prospectively for 12 weeks. RESULTS: Using the results of the SCID-II (n = 138), the sample was divided into 3 groups-that is, no PD 41% (n = 57), Cluster B PD 32% (n = 44), and other PD 27% (n = 37). The 3 groups did not differ in their alcohol use severity at intake. However, the Cluster B PD group achieved alcohol milestones at a younger age. Subjects with a PD had more severe psychological and social problems at intake. The Cluster B PD group showed significantly higher levels of impulsivity at intake, greater likelihood of early treatment dropout, and quicker times to first slip and to relapse. CONCLUSIONS: This study supports the high prevalence of concurrent PDs, particularly Cluster B PDs, among treatment-seeking alcoholics. The relation between observed high levels of impulsivity and worse course in early alcohol treatment among people with a Cluster B PD merits further investigation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".