Prevalence of the alternative model of personality disorders diagnoses in populational and at-risk samples, gender and age groups comparisons, and normative data for the LPFS-SR and PID-5.
Bibliographic record
Abstract
The Alternative Model of Personality Disorders (AMPD), introduced in Section III of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association, 2013), was proposed as a new operationalization of personality disorders (PDs) aiming to overcome the several limitations of the traditional symptom-based model (Waugh et al., 2017; Zimmerman et al., 2019). In the AMPD, PDs are defined by two-dimensional criteria (the level of personality functioning and maladaptive personality traits), but as a hybrid model, it also allows for categorical assessment of PDs (i.e., "hybrid types") to facilitate continuity with clinical practice. The present study aimed to provide normative data for two widely used instruments assessing Criterion A (Level of Personality Functioning Scale-Self-Report; Morey, 2017) and B (Personality Inventory for DSM-5; Krueger et al., 2012) in a large populational French-Canadian sample. Regarding the categorical assessment, Gamache et al. (2022) recently tested scoring approaches for extracting the PD hybrid types from dimensional measures of the AMPD. In the present study, these approaches were used to estimate prevalence rates for these PD hybrid types in two samples. In the populational sample, results showed that prevalence rates varied from 0.2% (antisocial PDs) to 3.0% (trait-specified PDs), with an overall prevalence of 5.9% to 6.1% for any PD hybrid type. Prevalence was higher in men than in women in the populational sample, but the contrary was observed in the at-risk sample. Prevalence was higher in younger adults than in middle-aged and older adults. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".