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Record W4320039111 · doi:10.1007/s12144-023-04316-7

Predictors of concussion reporting intentions in adolescent hockey players

2023· article· en· W4320039111 on OpenAlexaboutno aff
Natalie D. Macdonald, Oliver Baumann

Bibliographic record

VenueCurrent Psychology · 2023
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsConcussionPsychologyIce hockeyClinical psychologyApplied psychologyInjury preventionPhysical medicine and rehabilitationPoison controlMedical emergencyMedicine

Abstract

fetched live from OpenAlex

Young athletes who do not report a concussion injury are at greater risk for a prolonged recovery time and further neurocognitive impairments. Despite the seriousness of the issue and the scale of the problem, not enough is known about the behavioural underpinnings of concussion underreporting in minor athletes. This paper aims to apply the Knowledge, Attitude, and Behaviour (KAB) framework to the issue of injury reporting in adolescents, with the specific purpose of exploring to which degree concussion knowledge, concussion attitudes, and gender affect concussion reporting intentions of both male and female athletes. We recruited 97 young athletes between the ages of 14 and 19 (M = 16.22, SD = 11.06) from the Okanagan Hockey Academy (Canada) and employed a self-administered supervised survey approach to measuring the target variables. A hierarchical multiple regression was conducted, and consistent with the prior literature, females were more likely to report a sport-related concussion than males. It was further found that attitudes around concussions (i.e., taking concussions seriously) were significant predictors of concussion reporting intention. At the same time, there was no significant relationship between concussion knowledge and concussion reporting intention. These results highlight that knowledge about concussion symptoms is insufficient to warrant proper injury reporting. It will therefore be essential to work on changing the attitudes of young athletes regarding the significance of concussions to achieve meaningful behavioural change.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.108
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

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

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 head0.282
GPT teacher head0.499
Teacher spread0.217 · 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 teacher head, 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

Citations5
Published2023
Admission routes1
Has abstractyes

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