A Proposed Classification of ICD-11 Severity Degrees of Personality Pathology Using the Self and Interpersonal Functioning Scale
Bibliographic record
Abstract
Background: The 11th version of the World Health Organization's International Classification of Diseases (ICD-11) has adopted a dimensional approach to personality disorder (PD) nosology. Notably, it includes an assessment of PD degree of severity, which can be classified according to five categories. To date, there is no gold standard measure for assessing degree of PD severity based on the ICD-11 model, and there are no empirically-based anchor points to delineate the proposed categories. With the operationalization of PD degrees of severity in the ICD-11 PD model now being closely aligned with Criterion A of the DSM-5 Alternative Model for Personality Disorders (AMPD), sharing a focus on self and interpersonal dysfunction, self-report instruments developed for the latter model might prove useful as screening tools to determine degrees of severity in the former. Methods: The Self and Interpersonal Functioning Scale, a brief validated self-report questionnaire originally designed to assess level of personality pathology according to the AMPD framework, was used to derive anchor points to delineate the five severity degrees from the ICD-11 PD model. Data from five clinical and non-clinical samples (total N = 2,240) allowed identifying anchor points for classification, based on Receiver Operating Characteristic curve analysis, Latent Class Analysis, and data distribution statistics. Categories were validated using multiple indices pertaining to externalizing and internalizing symptoms relevant to PD. Results: Analyses yielded the following anchor points for PD degrees of severity: No PD = 0–1.04; Personality Difficulty = 1.05–1.29; Mild PD = 1.30–1.89; Moderate PD = 1.90–2.49; and Severe PD = 2.50 and above. A clear gradient of severity across the five categories was observed in all samples. A high number of significant contrasts among PD categories were also observed on external variables, consistent with the ICD-11 PD degree of severity operationalization. Conclusions: The present study provides potentially useful guidelines to determine severity of personality pathology based on the ICD-11 model. The use of a brief self-report questionnaire as a screening tool for assessing PD degrees of severity should be seen as a time-efficient support for clinical decision and 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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".