Neuropsychological Profiles of Athletes and Views of Parents Choosing Flag Versus Tackle Football Participation
Bibliographic record
Abstract
Background: Previous studies have found that injury rates are slightly higher in children who play flag football versus tackle football. It is unclear if this difference is due to the way each type is played or taught or whether there are intrinsic differences in attitudes or neuropsychological characteristics in children and their parents. Purpose: To determine whether children who play flag football score differently from those who play tackle football on validated neuropsychological tests. Study Design: Cross-sectional study; Level of evidence, 3. Methods: Each participating athlete (aged 8-12 years) was recruited in 2018 and 2019 by email through local youth football leagues and the local university. Each athlete was administered a 1-time multidimensional assessment battery. The battery included the Wechsler Abbreviated Scale of Intelligence-2nd Edition, the children’s version of the Trail Making Test, the Integrated Digit Span and Spatial Span subtests of the Wechsler Intelligence Scale for Children-4th Edition (WISC-IV), and the Beck Self-Concept Inventory for Youth. The parent/guardian of each athlete completed the Achenbach Child Behavior Checklist-Parent Report Form, the Behavior Rating Inventory of Executive Function (BRIEF)-Parent Form, and a custom survey. These tests were used to determine IQ estimates and standardized scores, measuring verbal comprehension, matrix reasoning, mental set-shifting, attention, cognitive processing speed, working memory, spatial processing, perception of self-concept, behavioral regulation index, metacognition index, and global executive composite. Scores were compared between flag football and tackle football groups by 2-sample t test, with the Wilcoxon rank-sum test used for nonparametric data. Results: A total of 64 athletes (41 tackle football, 23 flag football) were enrolled from youth football leagues (grades 4-6). Flag players scored significantly higher on the WISC-IV Spatial Span-Backward subtest (scaled mean, 12.0 vs 10.6; P = .046), while tackle players had significantly higher BRIEF-Inhibit subscores (mean t-score, 45 vs 42; P = .026). There were no significant differences in any of the other tests, including socioeconomic status and perceived concussion risks. Conclusion: Concerns that injury epidemiologic studies comparing flag with tackle football could be confounded by intrinsic differences in the children who choose to play each type seem to be unfounded.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".