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Enregistrement W4312926425 · doi:10.4085/1062-6050-1003.22

World Federation of Athletic Training and Therapy World Congress 2022 Peer-Reviewed Track Abstracts, May 5–7, 2022, Winnipeg, Manitoba, Canada

2022· article· en· W4312926425 sur OpenAlexaboutno aff

Notice bibliographique

RevueJournal of Athletic Training · 2022
Typearticle
Langueen
DomaineMedicine
ThématiqueSports injuries and prevention
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésAthletic trainingTrack (disk drive)Training (meteorology)MedicineMedical educationLibrary scienceComputer scienceGeography

Résumé

récupéré en direct d'OpenAlex

Context: Recent research has highlighted changes in neurocognitive and central nervous system function among some of the most common injuries, particularly in those with chronic ankle instability (CAI). Functional performance tests (FPT) like the side-hop test (SHT) are often used to assess physical performance, however, minimally stress a patient's neurocognitive function. On the contrary, dual-tasking is often used to assess the interplay between physical and neurocognitive performance, however, these traditional laboratory tasks are minimally challenging on higher-level athletes. Modifying and adding a reactive component to an already proven FPT may provide clinicians with increased insight into neurocognitive performance. Therefore, the purpose of this study was two-fold, to validate a choice-reaction hop test (CRHT) by assessing differences in timing versus the SHT, and to determine the CRHT's test-retest reliability. We hypothesized that the CRHT would take longer to complete than the SHT and it would demonstrate good test-retest reliability.Methods: Fourteen physically active (>90 minutes of physical activity/week) participants (5 female/9 male, 24.5±3.6 years old, 174.2±9.3 cm, 74.4±16.3 kg) with a range of ankle injury history completed the study. Participants were initially screened and completed injury history questionnaires followed by two hop tests in a randomized order. For the SHT, participants performed 20 hops on a single limb medially and laterally over a 30-cm distance as quickly as possible. For the CRHT participants similarly hopped on an instrumented mat 20 times on a single limb medially and laterally over a 30-cm distance, however, participants had to react to one of two squares on each side randomly indicated by flashing lights on a computer screen. Participants completed 3 trials of each hop test in a counterbalanced order. Participants returned one-week later to repeat the CRHT. To validate the CRHTs neurocognitive component, a paired t-test between the SHT and the CRHT was conducted. To assess the test-retest reliability of the CRHT, an ICC using a 2-way, random effects model of was between and Participants longer to complete the CRHT to the traditional SHT CRHT test-retest reliability to the SHT, the CRHT longer to complete to stress neurocognitive function an CRHT test-retest may it to a in as CRHT may an FPT to assess physical and neurocognitive function to clinicians in research to assess differences in the CRHT in those with versus participants to validate model has like to the of and the of and on the of the in chronic a to and and to are on the of the in are on the in in study using an was completed the Participants completed in and in used a of and the was using tests the between model and and the between of and the differences between and was a between and the of the model in was between and of the model in was between and in the model on of participants as with of participants were in of the was in the of model on in and the of the in of participants of 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Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Autre devis · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,912
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,046
Tête enseignante GPT0,286
Écart entre enseignants0,240 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeAutre devis
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2022
Routes d'admission1
Résumé présentoui

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