The General Assessment of Personality Disorder (GAPD) as an Instrument for Assessing the Core Features of Personality Disorders
Bibliographic record
Abstract
UNLABELLED: This study presents a psychometric evaluation of the General Assessment of Personality Disorder (GAPD), a self-report questionnaire for assessing the core components of personality dysfunction on the basis of Livesley's (2003) adaptive failure model. Analysis of samples from a general (n = 196) and a clinical population (n = 280) from Canada and the Netherlands, respectively, found a very similar two-component structure consistent with the two core components of personality dysfunction proposed by the model, namely, self-pathology and interpersonal dysfunction. Moreover, the GAPD discriminated between patients diagnosed with and without Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV-TR) personality disorder(s) and demonstrated discriminative power in detecting the severity of personality pathology. Correlations with a DSM-IV symptom measure and a pathological traits model suggest partial conceptual overlap. Although further testing is indicated, the present findings suggest the GAPD is suitable for assessing the core components of personality dysfunction. It may contribute to a two-step integrated assessment of personality pathology that assesses both personality dysfunction and personality traits. KEY PRACTITIONER MESSAGE: The core features of personality disorder can be defined as disorders in the self and in the capacity for interpersonal functioning. A clinically useful operationalization of disordered functioning of personality is needed to determine the maladaptivity of personality traits. An integrated assessment of personality (dys)functioning and personality traits provides a more comprehensive clinical picture of the patient, which may aid treatment planning.
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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 | 0.003 | 0.007 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".