A dimensional model of personality disorder: Incorporating DSM Cluster A characteristics.
Bibliographic record
Abstract
The authors articulate an expanded dimensional model of personality pathology to better account for symptoms of DSM-defined Cluster A personality disorders. Two hundred forty participants (98 first-degree relatives of probands with schizophrenia or schizoaffective disorder, 92 community control participants, and 50 first-degree relatives of probands with bipolar disorder) completed a dimensional personality pathology questionnaire, a measure of schizotypal characteristics, and Chapman measures of psychosis proneness. Scales from all questionnaires were subjected to an exploratory factor analysis with varimax rotation. A 5-factor structure of personality pathology emerged from the analyses, with Peculiarity forming an additional factor to the common 4-factor structure of personality pathology (consisting of Introversion, Emotional Dysregulation, Antagonism, and Compulsivity). These results support a 5-factor dimensional model of personality pathology that better accounts for phenomena encompassed by the Cluster A personality disorders in DSM-IV-TR (4th ed., text revised; American Psychiatric Association, 2000). This study has implications for the consideration of a dimensional model of personality disorder in DSM-V by offering a more comprehensive structural model that builds on previous work in this area.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".