A Psychometric Review of the Personality Inventory for DSM–5 (PID–5): Current Status and Future Directions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The paradigm of personality psychopathology is shifting from one that is purely categorical in nature to one grounded in dimensional individual differences. Section III (Emerging Measures and Models) of the Diagnostic and Statistical Manual of Mental Disorders (5th ed. [DSM-5]; American Psychiatric Association, 2013), for example, includes a hybrid categorical/dimensional model of personality disorder classification. To inform the hybrid model, the DSM-5 Personality and Personality Disorders Work Group developed a self-report instrument to assess pathological personality traits-the Personality Inventory for the DSM-5 (PID-5). Since its recent introduction, 30 papers (39 samples) have been published examining various aspects of its psychometric properties. In this article, we review the psychometric characteristics of the PID-5 using the Standards for Educational and Psychological Testing as our framework. The PID-5 demonstrates adequate psychometric properties, including a replicable factor structure, convergence with existing personality instruments, and expected associations with broadly conceptualized clinical constructs. More research is needed with specific consideration to clinical utility, additional forms of reliability and validity, relations with psychopathological personality traits using clinical samples, alternative methods of criterion validation, effective employment of cut scores, and the inclusion of validity scales to propel this movement forward.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it