Development and validation of an Overreporting Scale for the Personality Inventory for DSM–5 (PID-5).
Bibliographic record
Abstract
(PID-5) to detect noncredible overreported responding. To this end, we used a rare symptoms approach and identified extreme response options on PID-5 items that were infrequently endorsed by students in 3 different university samples (N = 1,370) and in a psychiatric patient sample (N = 194). The resulting 10-item scale (the PID-5-ORS) produced adequate-to-good estimates of internal reliability and was significantly correlated with the Minnesota Multiphasic Personality Inventory-2 Restructued Form (MMPI-2-RF) overreporting validity scales, providing evidence of concurrent validity. The criterion validity of the PID-5-ORS was demonstrated in an analog simulation design study. More specifically, university students instructed to overreport (n = 80) scored substantially higher on the PID-5-ORS relative to both a group of genuine psychiatric patients and students instructed to complete the PID-5 under standard (honest) instructions (n = 161); the effect size magnitudes associated with these differences were large. Classification accuracy analyses further revealed that high scores on the PID-5-ORS were associated with high specificity (and thus, low rates of false positive classifications) in differentiating overreporters from genuine patients, with sensitivity being somewhat weaker. (PsycINFO Database Record
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".