Assessing the DSM-IV Structure of Personality Disorder With a Sample of Chinese Psychiatric Patients
Bibliographic record
Abstract
The validity of the three-cluster system of personality disorders (PDs) in the latest version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV; APA, 1994) was examined in a sample of Chinese psychiatric patients (n = 227), who completed the self-report Personality Disorders Questionnaire for DSM-IV (PDQ-4; Hyler, 1994) and who were also administered the clinician-rated Personality Disorders Interview-IV (PDI-IV; Widiger, Mangine, Corbit, Ellis, & Thomas,). Using confirmatory factor analysis, a three-factor model corresponding to the DSM-IV clusters was tested and compared statistically to a one-factor model and a set of random, three-factor models. Only the clinician-rated instrument supported the DSM-IV three-cluster model, and then only when the factors were allowed to correlate. Results from the theoretically more rigorous uncorrelated model testing did not support the DSM-IV model for either assessment modality.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".