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Record W4404252499 · doi:10.1177/23259671241285075

Examining the Reliability and Validity of Coding Perceived Force Severity and Bracing in the NHL Concussion Spotter Program

2024· article· en· W4404252499 on OpenAlexaff
Kaitlin E Riegler, Ruben J. Echemendía, Willem Meeuwisse, Paul Comper, Michael G. Hutchison, J. Scott Delaney, Jared M. Bruce

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsMcGill UniversityMcGill University Health CentreToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsConcussionMedicineBracingReliability (semiconductor)Physical therapyPoison controlInjury preventionPhysical medicine and rehabilitationMedical emergencyStructural engineeringEngineeringBrace

Abstract

fetched live from OpenAlex

Background: Data obtained from the National Hockey League (NHL) have shown that a risk prediction model, including both visible signs and mechanisms of injury, improves the identification of possible concussion. However, only about half of concussions diagnosed by club medical staff in the NHL exhibit visible signs. At present, the NHL concussion spotter protocol does not include central league spotters’ subjective judgments of the severity of forces associated with a direct hit to the head (perceived force severity [PFS]) or whether players brace before a hit (bracing). Purpose: To examine the interrater reliability, preliminary validity, and association with concussion diagnosis of central league spotter determinations of PFS and bracing. Study Design: Cross-sectional study. Methods: Video footage of 1071 events after a direct or indirect blow to the head were observed from the 2020-2021 and 2021-2022 NHL seasons. These events were classified into 4 groups: concussion with visible signs; concussion without visible signs; no concussion with visible signs; and no concussion without visible signs. A total of 50 events were randomly selected from the total events in each group. Then, 2 raters (NHL central league spotters) coded PFS for each of the 200 video events as low, medium, or high. Bracing was coded as no bracing, insufficient bracing, or full bracing. Results: Interrater reliability was fair to moderate for the categorical and continuous ratings of both PFS (κ = 0.36 and 0.45, respectively) and bracing (κ = 0.40 and 0.49, respectively). There was no significant association between concussion diagnosis and either PFS ( Z = 0.00, P = .99) or bracing ( Z = 0.77, P = .44). Exploratory, post hoc analyses suggested a possible relationship between bracing and reduced concussion risk among a select subsample of events with no visible signs ( r = −0.29, P < .01). Conclusion: The interrater reliability for PFS and for bracing was fair to moderate. Neither PFS nor bracing were significantly related to concussion diagnosis, but they were significantly associated with other visible signs and mechanisms of injury.

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)0.021
metaresearch head score (Gemma)0.052
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.052
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
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 head0.068
GPT teacher head0.350
Teacher spread0.282 · 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.

Study designObservational
DomainMethods
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

Citations0
Published2024
Admission routes1
Has abstractyes

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