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Record W2951936356 · doi:10.3389/fneur.2019.00712

Comprehensive Neuropsychiatric and Cognitive Characterization of Former Professional Football Players: Implications for Neurorehabilitation

2019· article· en· W2951936356 on OpenAlexafffund
Alex R. Terpstra, Brandon P. Vasquez, Brenda Colella, Maria Carmela Tartaglia, Charles H. Tator, David J. Mikulis, Karen D. Davis, Richard Wennberg, Robin Green

Bibliographic record

VenueFrontiers in Neurology · 2019
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of TorontoUniversity Health NetworkOccupational Cancer Research CentreToronto Western HospitalBaycrest HospitalToronto Rehabilitation InstituteUniversity of British Columbia
FundersCanada Research Chairs
KeywordsConcussionNeurorehabilitationPsychologyPopulationClinical psychologyCognitionNeuropsychologyRehabilitationPsychiatryPhysical medicine and rehabilitationPoison controlMedicineInjury prevention

Abstract

fetched live from OpenAlex

Objectives: With the overarching aim of identifying novel targets for neurorehabilitation, our objectives were to: (1) comprehensively characterize neuropsychiatric and cognitive functioning in high-functioning former professional football players with a focus on executive functioning; (2) distinguish concussion-related impairments from cohort characteristics unique to elite professional football players; and, (3) explore the relationship between executive function and neuropsychiatric impairments in this population. Participants: 61 high-functioning former professional football players and 31 age- and sex-matched control participants without history of concussion or participation in contact sports. Design: Between-groups analysis. Main measures: Neuropsychiatric. Personality Assessment Inventory (PAI) clinical scales plus the Aggression treatment consideration scale; the Mini International Neuropsychiatric Interview (MINI). Cognitive. Comprehensive clinical neuropsychological battery assessing domains of verbal and visuospatial attention, speed of processing and memory; current and estimated pre-morbid IQ; and, executive functioning, including two novel measures for this population (i.e., response inhibition and intra-individual variability [IIV], a measure of consistency in responding). Results: (1) Compared to control participants, former professional football players scored significantly higher on the PAI’s Depression, Mania, and Aggression scales, and significantly lower on response inhibition. (2) Retired players with a higher concussion history (4 or more concussions; x̅=6.1), but not retired players with a lower concussion history (3 or fewer concussions; x̅=2.0), showed (i) significantly higher scores on the Depression scale, (ii) more MINI diagnoses overall and manic/hypomanic episodes specifically, and (iii) poorer executive function than control participants. (3) The relationships between concussion exposure and, (i) the PAI Mania scale and (ii) the PAI Aggression scale, respectively, were fully mediated by IIV; Depression on the PAI was partially mediated by IIV. Conclusions: In high-functioning former professional football players, impairments were observed in several neuropsychiatric domains and on experimental measures of executive function. Many findings were attributable to concussion history rather than to cohort characteristics. As inconsistency of responding) mediated relationships between concussion exposure and Mania, Aggression, and Depression (partially), it warrants further investigation; if it does increase vulnerability to expression of neuropsychiatric symptoms in individuals with a history of multiple concussions, this would constitute a novel and important treatment target.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.028
GPT teacher head0.325
Teacher spread0.297 · 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

Citations19
Published2019
Admission routes2
Has abstractyes

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