Can the MMPI-2 Validity Scales Detect Depression Feigned by Experts?
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
Major depression is one of the most frequently presented disorders for claims of psychiatric disability. Evidence also suggests that many individuals making claims of disability exaggerate or even fabricate mental illness. These facts suggest that the detection of feigned depression is an important task in psychiatric disability claim assessments. In this study, the capacity of a number of MMPI-2 validity scales and indicators to detect feigned depression was examined. Twenty-three mental health professionals with specific expertise and significant experience in assessing and treating major depression were asked to complete the MMPI-2 as if they were suffering from major depression. The MMPI-2 protocols of this sample were compared to those of a sample of patients diagnosed with major depression. Results indicated that the validity scales F, back F (FB), and the Dissimulation scale (Ds) were highly successful at distinguishing MMPI-2 protocols of feigned depression from bona fide depression. Replicating results from previous studies, however, FB proved most effective, outperforming all other validity scales and indicators, including F and Ds. These findings suggest that even experts are unable to feign major depression successfully on the MMPI-2, and that the FB scale might be the most effective indicator for detecting feigned depression.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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