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Record W4390078717 · doi:10.1017/s1355617723007944

19 Preseason Neurocognitive Test Performance and Symptom Reporting Among Student Athletes with Autism Spectrum Disorders

2023· article· en· W4390078717 on OpenAlexaff
Nathan E. Cook, Ila A. Iverson, Bruce Maxwell, Ross Zafonte, Paul D. Berkner, Grant L. Iverson

Bibliographic record

VenueJournal of the International Neuropsychological Society · 2023
Typearticle
Languageen
FieldMedicine
TopicDiverse Approaches in Healthcare and Education Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNeurocognitiveAutism spectrum disorderConcussionAthletesMedicinePopulationAutismClinical psychologyAttention deficit hyperactivity disorderCognitionPsychiatryPhysical therapyPoison controlInjury prevention

Abstract

fetched live from OpenAlex

Objective: Participation in sports likely confers multiple benefits for children and adolescents with autism spectrum disorder (ASD). Adolescent student athletes often undergo preseason testing as part of a broader concussion management program for schools. This study compares preseason neurocognitive functioning and symptom reporting between high school athletes with and without ASD. Participants and Methods: Participants were derived from a database of 60,751 adolescent student athletes from Maine (aged 13-18) who completed preseason testing between 2009 and 2019 and did not have missing data on the history question relating to ASD. There were 425 students (0.7%) who self-reported having been diagnosed with ASD in their health history. Cognitive functioning was measured by ImPACT, and the Post-Concussion Symptom Scale (PCSS) was used to obtain symptom ratings. Group differences between the ASD and the population control group on the five ImPACT cognitive test composite raw scores and the total symptom score from the PCSS were examined using Mann-Whitney U tests. Results: Compared to the population control sample, those with ASD reported much greater rates of comorbid conditions: attention deficit/hyperactivity disorder (50.1% vs. 10.3%), special education (39.2% vs. 4.4%), learning disabilities (43.8% vs. 4.4%), and prior treatment for a psychiatric condition (23.4% vs. 7.5%). Groups differed significantly across all neurocognitive composites (p values <.002). However, all differences were negligible in terms of the magnitude of the effects (r values range from 0.01-0.03). The groups also differed significantly on the PCSS total symptom score (p<.001), but the magnitude of the difference was negligible (r=.031). Among boys, the ASD group endorsed 21 of the 22 symptoms at a greater rate. Among girls, the ASD group endorsed 11 of the 22 individual baseline symptoms at a greater rate than the control group. Examples of symptoms that were endorsed at a higher rate among both boys and girls with ASD: sensitivity to noise (girls: odds ratio, OR=4.38; boys: OR=4.99), numbness or tingling (girls: OR=3.67; boys: OR=3.25), difficulty remembering (girls: OR=2.01; boys: OR=2.49), difficulty concentrating (girls: OR=1.82; boys: OR=2.40), sleeping more than usual (girls: OR=1.94; boys: OR=1.97), sensitivity to light (girls: OR=1.82; boys: OR=1.76), sadness (girls: OR=1.72; boys: OR=2.56), nervousness (girls: OR=1.80; boys: OR=2.27), and feeling more emotional (girls: OR=1.79; boys: OR=2.84). Conclusions: Students with ASD participating in organized sports are likely high functioning, on average. There were small differences in their cognitive test scores compared to the population control sample. They endorsed more symptoms, however, during baseline preseason testing. If they sustain a concussion, their clinical management should be more intensive to maximize the likelihood of swift and favorable recovery.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.058
GPT teacher head0.356
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".

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Citations1
Published2023
Admission routes1
Has abstractyes

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