Establishing Levels of Personality Functioning Using the Structured Interview of Personality Organization (STIPO-R): A Latent Profile Analysis
Bibliographic record
Abstract
Both the new ICD-11 and the latest Alternative DSM-5 Model for Personality Disorders focus on self and interpersonal functioning as the central feature of personality pathology, also acknowledging that personality disorders are organized along a dimensional continuum of severity. This revised understanding is in line with long-standing psychodynamic conceptualisations of personality pathology, in particular Kernberg’s object relations model of personality organization. Despite existing evidence for the clinical utility of the derived Structured Interview of Personality Organization (STIPO-R), empirical support for the identification of clear cut-points between the different levels of personality functioning is missing. For this purpose, a total of 764 adult participants were recruited across two clinical (outpatient and inpatient) settings (n = 250) and two non-clinical (university students and general community) samples (n = 514). Results from the mixture modeling suggested the existence of five groups across the clinical and non-clinical samples that covered: healthy personality functioning, maladaptive personality rigidity, and mild, moderate, and severe levels of personality pathology. All five indicators of personality organization were found to be reliable predictors of personality pathology. Of the five STIPO-R indicators, Aggression and Moral Values had the most discriminative power for differentiating between the Mild, Moderate, and Severe personality disorder groups. Implications of these findings are discussed.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| 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".