The Mild Brain Injury Atypical Symptoms (mBIAS) scale in a mixed clinical sample
Bibliographic record
Abstract
INTRODUCTION: The Mild Brain Injury Atypical Symptoms (mBIAS) scale was developed as a symptom validity test (SVT) for use with patients following mild traumatic brain injury. This study was the first to examine the clinical utility of the mBIAS in a mixed clinical sample presenting to a Department of Veterans Affairs (VA) neuropsychology clinic. METHOD: Participants were 117 patients with mixed etiologies (85.5% male; age: M = 39.2 years, SD = 11.6) from a VA neuropsychology clinic. Participants were divided into pass/fail groups using two different SVT criteria, based on select validity scales from the Minnesota Multiphasic Personality Inventory-2 (MMPI-2): first, Infrequency Scale (F) scores: (a) MMPI-F-Fail (n = 21) and (b) MMPI-F-Pass (n = 96); and, second, Symptom Validity Scale (FBS) scores: (a) MMPI-FBS-Fail (n = 36) and (b) MMPI-FBS-Pass (n = 81). RESULTS: The mBIAS demonstrated good internal consistency, and each item contributed meaningfully to the total score. At a symptom exaggeration base rate of 35%, an mBIAS cutoff of ≥11 was optimal for screening symptom exaggeration when groups were classified using both F and FBS scales. This cutoff score resulted in very high specificity (.89 to .94); moderate-high positive predictive power (.71 to .75) and negative predictive power (.72 to .79); and low-moderate sensitivity (.31 to .57). At all base rates of probable somatic exaggeration, a cutoff of ≥16 resulted in perfect specificity and positive predictive power, but very low sensitivity. CONCLUSIONS: The mBIAS has potential for use in samples outside of mild traumatic brain injury. In settings where the symptom exaggeration base rate is 35%, a cutoff of ≥11 may be used as a "red flag" for further evaluation, but should not be relied on for clinical decision making. At all base rates of probable somatic exaggeration, psychologists with patients who score ≥16 can be confident that those patients were exaggerating. Importantly, however, this cutoff may fail to identify a large proportion of patients who are exaggerating.
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How this classification was reachedexpand
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".