Depressive Personality Disorder: Rates of Comorbidity with Personality Disorders and Relations to the Five-factor Model of Personality
Bibliographic record
Abstract
Depressive personality disorder (DPD) is listed in the DSM-IV as one of the "Disorders for Further Study." In this investigation we examined (1) the rates of comorbidity of DPD with the 10 personality disorders (PDs) in the main text of DSM-IV, and (2) the convergent and discriminant validity of DPD in its relation to the 30 facet traits of the Five-Factor Model of personality (FFM). One hundred and sixty-nine participants with psychiatric diagnoses were interviewed with the Structured Clinical Interview for DSM-IV Personality Disorders Questionnaire (SCID-II) and completed the Revised NEO Personality Inventory (NEO PI-R). A total of 26 (15%) of the participants met diagnostic criteria for at least one of the 10 main text PDs, and 15 (9%) met criteria for DPD. Of those who met criteria for DPD, 10 (59%) of the participants also met criteria for one or more of the 10 main text PDs. Regression analyses indicated a four-facet trait set derived from the NEO PI-R thought to be uniquely associated with DPD accounted for a significant amount of variance in DPD SCID-II PD scores and was significantly larger for DPD than it was for the 9 of the 10 main text PDs; the sole exception was for avoidant PD. Diagnostically, DPD overlaps significantly with other PDs but is distinguishable in its unique relation with traits from the FFM.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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 teacher head, 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".