Quantifying and Examining Reserve in Symptomatic Former National Football League Players
Bibliographic record
Abstract
BACKGROUND: Repetitive head impacts (RHI) from contact sports have been associated with cognitive and neuropsychiatric disorders. However, not all individuals exposed to RHI develop such disorders. This may be explained by the reserve hypothesis. It remains unclear if the reserve hypothesis accounts for the heterogenous symptom presentation in RHI-exposed individuals. Moreover, optimal measurement of reserve in this population is unclear and likely unique from non-athlete populations. OBJECTIVE: We examined the association between metrics of reserve and cognitive and neuropsychiatric functioning in 89 symptomatic former National Football League players. METHODS: Individual-level proxies (e.g., education) defined reserve. We additionally quantified reserve as remaining residual variance in 1) episodic memory and 2) executive functioning performance, after accounting for demographics and brain pathology. Associations between reserve metrics and cognitive and neuropsychiatric functioning were examined. RESULTS: Higher reading ability was associated with better attention/information processing (β=0.25; 95% CI, 0.05-0.46), episodic memory (β=0.27; 95% CI, 0.06-0.48), semantic and phonemic fluency (β=0.24; 95% CI, 0.02-0.46; β=0.38; 95% CI, 0.17-0.59), and behavioral regulation (β=-0.26; 95% CI, -0.48, -0.03) performance. There were no effects for other individual-level proxies. Residual episodic memory variance was associated with better attention/information processing (β=0.45; 95% CI, 0.25, 0.65), executive functioning (β=0.36; 95% CI, 0.15, 0.57), and semantic fluency (β=0.38; 95% CI, 0.17, 0.59) performance. Residual executive functioning variance was associated with better attention/information processing (β=0.44; 95% CI, 0.24, 0.64) and episodic memory (β=0.37; 95% CI, 0.16, 0.58) performance. CONCLUSION: Traditional reserve proxies (e.g., years of education, occupational attainment) have limitations and may be unsuitable for use in elite athlete samples. Alternative approaches of reserve quantification may prove more suitable for this population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".