Effects of Concussion on Attention and Executive Function in Adolescents
Bibliographic record
Abstract
BACKGROUND: Head trauma in adolescents has been linked with deficits in attention and executive function that can compromise the performance of everyday tasks. Although previous research has examined this issue using computerized neuropsychological testing, little work has been done using laboratory-based measurements of attention and executive function in this population. A longitudinal analysis of recovery patterns of these measures among adolescents is central to understanding the effects of concussions across the age spectrum. PURPOSE: This study prospectively and longitudinally examined laboratory-based measures of attention and executive function in concussed adolescents sequentially during a 2-month period after injury. METHODS: Two measures of attention and executive function, the Attentional Network Test and the Task-Switching Test, were administered to 20 concussed adolescents within 72 h postinjury as well as at 1 wk, 2 wk, 1 month, and 2 months postinjury. Twenty healthy, matched control subjects were similarly assessed at the same time intervals. Data were analyzed by two-way, mixed-effects ANOVA to determine the effect of group and time on the dependent variables. RESULTS: Compared with control subjects, the concussed group exhibited a significantly greater switch cost on the Task-Switching Test (P = 0.038, mean difference value = 38 ms) and a significantly greater reaction time for the Attentional Network Test conflict effect component (P = 0.015, mean difference value = 34 ms) for up to 2 months after injury. CONCLUSIONS: Concussed adolescents have difficulty recovering executive function after injury and may require extended recuperation time before full recovery is achieved. Evaluations focusing on attention and executive function can be useful additions in the assessment and follow-up after head injury.
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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 | 0.001 |
| 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) | 0.001 | 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".