Student‐Athletes’ Views on <i>APOE</i> Genotyping for Increased Risk of Poor Recovery after a Traumatic Brain Injury
Bibliographic record
Abstract
Use of apolipoprotein E genotyping to personalize the risk of a poor recovery after traumatic brain injury is complicated by the potential for genetic discrimination and the potential to reveal an increased risk for late onset Alzheimer's disease. We developed a survey to gauge interest in testing among athletes participating in National Collegiate Athletic Association programs. Eight hundred and forty seven student-athletes were surveyed to determine their interest in genetic testing, their willingness to share the results of testing with parents, coaches and physicians, their concerns about privacy and/or discrimination, and their interest in genetic counseling. Nearly three quarters of respondents expressed some level of interest in testing, with the largest number describing themselves as 'possibly interested' (54.9 %, n = 463) and a smaller number describing themselves as 'very interested' (18.9 %, n = 159). Most student-athletes said that receiving secondary information about their risk for late-onset Alzheimer's disease made them more likely to test (50.6 %, n = 426) rather than less likely to test (12.4 %, n = 104). Student-athletes were open to apolipoprotein E genotyping and willing to share test results with their parents, coaches and physicians. They did not anticipate that test results would impact their behavior or ability to play. Testing programs may be welcome but should provide clear information as to risks and benefits.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".