Major Depression in Patients with Borderline Personality Disorder: A Clinical Investigation
Bibliographic record
Abstract
OBJECTIVE: Borderline personality disorder (BPD) is characterized by a high frequency of comorbidity with major depressive disorder (MDD). This study aimed to compare the clinical characteristics of 2 groups of patients with MDD: those with concomitant BPD and those with other concomitant personality disorders. METHODS: We assessed 119 outpatients, using a semistructured interview for demographic and clinical features, the Structured Clinical Interview for DSM-IV, Hamilton anxiety and depression scales, the Zung Self-Rating Depression Scale (ZSDS), the Social and Occupational Functioning Assessment Scale (SOFAS), the Sheehan Disability Scale, and the Revised Childhood Experiences Questionnaire. We performed a regression analysis, using the number of criteria for BPD as the dependent variable. RESULTS: Severity of BPD was positively related to the ZSDS score, to self-mutilating behaviours, and to the occurrence of mood disorders in first-degree relatives; it was negatively related to the SOFAS score and age at onset of MDD. CONCLUSIONS: Patients with comorbid MDD and BPD present differential characteristics that indicate a more serious and impairing condition with a stronger familial link with mood disorders than is shown by depression patients with other Axis II codiagnoses.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".