Influence of poor effort on neuropsychological test performance in U.S. military personnel following mild traumatic brain injury
Bibliographic record
Abstract
The purpose of this study was to examine the influence of poor effort on neuropsychological test performance in military personnel following mild traumatic brain injury (MTBI). Participants were 143 U.S. service members who sustained a TBI, divided into three groups based on injury severity and performance on the Word Memory Test and four embedded markers of poor effort: MTBI-pass (n = 87), MTBI-fail (n = 21), and STBI-pass (n = 35; where STBI denotes severe TBI). Patients were evaluated at the Walter Reed Army Medical Center on average 3.9 months (SD = 3.4) post injury. The majority of the sample was Caucasian (84.6%), was male (93.0%), and had 12+ years of education (96.5%). Measures included the Personality Assessment Inventory (PAI) and 13 common neurocognitive measures. Patients in the MTBI-fail group performed worse on the majority of neurocognitive measures, followed by the Severe TBI-Pass group and the MTBI-pass group. Using a criterion of three or more low scores <10th percentile, the MTBI-fail group had the greatest rate of impairment (76.2%), followed by the Severe TBI-Pass group (34.3%) and MTBI-pass group (16.1%). On the PAI, the MTBI-fail group had higher scores on the majority of clinical scales (p < .05). There were a greater number of elevated scales (e.g., 5 or more elevated mild or higher) in the MTBI-fail group (71.4%) than in the MTBI-pass group (32.2%) and Severe TBI-Pass group (17.1%). Effort testing is an important component of postacute neuropsychological evaluations following combat-related MTBI. Those who fail effort testing are likely to be misdiagnosed as having severe cognitive impairment, and their symptom reporting is likely to be inaccurate.
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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 | 0.002 | 0.002 |
| 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 | 0.001 |
| 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".