Comparability of Neuropsychological Test Profiles in Patients with Chronic Substance Abuse and Mild Traumatic Brain Injury
Bibliographic record
Abstract
The purpose of this study was to compare 104 patients with acute uncomplicated mild traumatic brain injury (MTBI) to a sample of 104 patients from an inpatient substance abuse program to determine whether these patients could be differentiated by their pattern of relative cognitive strengths and weaknesses. Patients were matched on age, education, and gender. Eight cognitive measures were used that included tests of attention, memory, and processing speed. There were no statistically significant differences between the two groups on any of the cognitive measures. Using a two-step cluster analysis procedure (i.e., hierarchical and k-means analyses), seven common profiles were identified. There was no significant difference in the proportions of patients from the MTBI or substance abuse group in each of the seven profiles. These results show that patients with uncomplicated MTBIs could not be reliably differentiated from patients with substance abuse problems on these cognitive measures. This is of particular concern for clinicians evaluating the neuropsychological effects of MTBI in individuals with a comorbid history of substance abuse.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".