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Record W2491752289 · doi:10.1089/neu.2016.4412

Consistency of Self-Reported Concussion History in Adolescent Athletes

2016· article· en· W2491752289 on OpenAlexaff
Magdalena Wójtowicz, Grant L. Iverson, Noah D. Silverberg, Rebekah Mannix, Ross Zafonte, Bruce Maxwell, Paul D. Berkner

Bibliographic record

VenueJournal of Neurotrauma · 2016
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsGF Strong Rehabilitation CentreUniversity of British Columbia
FundersNational Center for Research ResourcesNational Football League Players AssociationEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentColby CollegeAssociation of Academic Physiatrists
KeywordsConcussionAthletesConsistency (knowledge bases)PsychologyInjury preventionPhysical medicine and rehabilitationPoison controlHuman factors and ergonomicsPhysical therapyMedicineClinical psychologyMedical emergencyComputer science

Abstract

fetched live from OpenAlex

Relying on self-reported concussion injury history is common in both clinical care and research. However, young athletes may not provide consistent medical information. To date, little is known about the reliability of self-reported concussion history in high school students. This study examined whether student athletes reported their lifetime history of concussions consistently over time. Self-reported concussion history was examined in 4792 student athletes (ages 13–18) from Maine who completed a preseason health survey on two occasions (median re-test interval = 23.7 months; standard deviation = 7.3; interquartile range = 12.4–24.5). Consistency of self-reported concussion history was determined by differences in the number of concussions reported during the second survey. Inconsistent concussion history was defined primarily by a decrease in the number of lifetime concussions reported at the second testing, compared with at the first testing. The majority of the sample (80.3%) reported no change in the number of concussions between the two baseline assessments. A minority (15.9%; n = 763) reported more concussions during the second assessment. Only 3.8% ( n = 181) of student athletes provided inconsistent concussion histories, defined as fewer concussions at the second assessment. Boys provided inconsistent concussion histories a little more frequently, compared with girls (5.3% and 2.0%, respectively; p < 0.001). Similarly, athletes with self-reported attention-deficit hyperactivity disorder (ADHD) provided inconsistent concussion histories somewhat more frequently, compared with those without ADHD (7.8% and 3.5%, respectively; p < 0.001). Of the athletes with inconsistent concussion histories, greater degree of inconsistency was associated with a greater number of concussions initially reported at baseline ( r s = 0.54; p < 0.001). Only a small proportion of student athletes provided inconsistent concussion histories. Male gender, ADHD, and greater number of baseline concussions were significantly associated with inconsistency in reporting. Overall, these findings suggest that student athletes are quite consistent when reporting their concussion history when surveyed twice during high school.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.184
GPT teacher head0.365
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations64
Published2016
Admission routes1
Has abstractyes

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