Examination of the MMPI-3 over-reporting scales in a forensic disability sample
Bibliographic record
Abstract
Objective: The aim of this investigation was to provide information about the utility of the newly revised and renormed Minnesota Multiphasic Personality Inventory-3 (MMPI-3) over-reporting scales in a forensic disability sample. Method: Participants consisted of 550 non-head injury disability-related referrals (i.e. 95.6% for worker’s compensation) and were primarily diagnosed with an adjustment disorder, depressive disorder, or posttraumatic stress disorder. Criterion measures included performance validity indicators and non-MMPI symptom validity indicators. Results: Correlation analyses showed that validity scale F was most strongly associated with non-MMPI symptom validity indicators, whereas F, Fs, FBS, and RBS were comparable to each other in their associations with performance validity indicators. Group mean comparisons between Pass versus Fail PVT groups showed that RBS consistently yielded the largest effect sizes. Using established structured criteria for Malingered Neurocognitive Dysfunction (MND), additional group mean comparisons showed that RBS, followed by Fs, F, and FBS, performed well in differentiating genuine responders from MND examinees. Classification accuracy estimates indicated that the MMPI-3 over-reporting scales performed well in the prediction of Probable/Definite MND and, as expected, to a lesser degree of Possible MND. Conclusions: Practical applications, study limitations, and directions for future research are discussed. The overall findings from this study provide empirical support for the utility of the MMPI-3 over-reporting scales in detecting negative response bias in forensic disability evaluations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.000 |
| 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".