African American acculturation and neuropsychological test performance following traumatic brain injury
Bibliographic record
Abstract
The present study examined the influence of African American acculturation on the performance of neuropsychological tests following traumatic brain injury (TBI). Seventy one participants already enrolled in a larger-scale study assessing the impact of TBI (i.e., the South Eastern Michigan Traumatic Brain Injury Model Systems project) completed a self-report measure of African American acculturation (African American Acculturation Scale-Short Form; Landrine & Klonoff, 1995) in addition to a standardized battery of neuropsychological tests. Hierarchical regression analyses were conducted to evaluate the relationship between level of acculturation and test performance after controlling for injury-related (initial Glasgow Coma Scale score, time since injury) and demographic variables (age, sex, years of education, and socioeconomic status). Lower levels of acculturation were associated with significantly poorer performances on the Galveston Orientation & Amnesia Test, MAE Tokens test, WAIS-R Block Design, Rey Auditory Verbal Learning Test, and Symbol Digit Modalities Test. Decreased levels of acculturation were also significantly related to lower scores on a composite indicator of overall neuropsychological test performance. In addition, the examiner's ethnicity (Black or White) was related with scores on a few of the tests (i.e., Block Design, Trail Making Test), but was not significantly associated with the overall neuropsychological test performance. Overall, these findings suggest that differences in cultural experience may be an important factor in the neuropsychological assessment of African Americans following TBI, and provide additional support for the hypothesis that cultural factors may partially account for the differences among ethnic/cultural groups on neuropsychological tests.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".