The General Assessment of Personality Disorder (GAPD): Factor Structure, Incremental Validity of Self-Pathology, and Relations to<i>DSM–IV</i>Personality Disorders
Bibliographic record
Abstract
Recent developments in the classification of personality disorder, especially moves toward more dimensional systems, create the need to assess general personality disorder apart from individual differences in personality pathology. The General Assessment of Personality Disorder (GAPD) is a self-report questionnaire designed to evaluate general personality disorder. The measure evaluates 2 major components of disordered personality: self or identity problems and interpersonal dysfunction. This study explores whether there is a single factor reflecting general personality pathology as proposed by the Diagnostic and Statistical Manual of Mental Disorders (5th ed.), whether self-pathology has incremental validity over interpersonal pathology as measured by GAPD, and whether GAPD scales relate significantly to Diagnostic and Statistical Manual of Mental Disorders (4th ed. [DSM-IV]) personality disorders. Based on responses from a German psychiatric sample of 149 participants, parallel analysis yielded a 1-factor model. Self Pathology scales of the GAPD increased the predictive validity of the Interpersonal Pathology scales of the GAPD. The GAPD scales showed a moderate to high correlation for 9 of 12 DSM-IV personality disorders.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".