Substance Misuse Is Associated With Increased Psychiatric Severity Among Treatment-Seeking Individuals With Borderline Personality Disorder
Bibliographic record
Abstract
Despite high prevalence rates of concurrent borderline personality disorder (BPD) and substance use disorders (SUDs), little is known about the impact of substance misuse on the presentation of BPD. Sixty-five individuals with BPD were assessed at intake and at 3- and 6-month follow-up. Assessment included validated instruments such as the Addiction Severity Index and the Revised Symptom Checklist (SCL-90-R). Over half (58.5%) of individuals entering treatment were currently misusing substances. Substance misuse was associated with more legal and employment problems, greater mood disturbance, impulsivity, and psychiatric severity, including almost all SCL-90-R subscales. For the majority of patients (58%), there was little change in substance misuse post-treatment. The high prevalence of substance misuse and its association with psychiatric severity among individuals with BPD suggest that substance misuse should be a targeted behavior during treatment, and further specialized interventions are needed for individuals with comorbid BPD and SUD.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".