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Record W4414995130 · doi:10.1016/j.jts.2025.09.005

Caractéristiques et facteurs prédictifs des blessures au Kin-Ball au Québec : une étude rétrospective

2025· article· fr· W4414995130 on OpenAlexafffundabout
Emile Marineau, Guillaume Vadez, Allyssa-James Plaisance, Martin Descarreaux, Jacques Abboud

Bibliographic record

VenueJournal de Traumatologie du Sport · 2025
Typearticle
Languagefr
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersMitacs
KeywordsPoison controlTraffic accidentUnfair dismissalAnterior Cruciate Ligament Injuries

Abstract

fetched live from OpenAlex

L’objectif principal de cette étude était d’identifier les régions anatomiques les plus fréquemment blessées et d’estimer l’incidence des blessures lors de la pratique compétitive du Kin-Ball. L’objectif secondaire était d’identifier des déterminants associés à ces blessures chez les joueurs de Kin-Ball. Une série de questionnaires en ligne auto-administrés a été remplie par des athlètes compétitifs de la Fédération québécoise de Kin-Ball. Ces questionnaires comprenaient un questionnaire sur les données anthropométriques et sociodémographiques, un questionnaire sur la pratique du Kin-Ball, et une version française adaptée du Nordic Musculoskeletal Questionnaire. Un modèle de régression logistique binaire a été généré pour identifier les déterminants associés à ces blessures. Sur un total de 134 répondants, 105 athlètes (78 %) ont subi une blessure au cours de l’année, pour un total de 214 blessures (moyenne de 2,04 blessures par athlète). Les blessures les plus fréquentes touchaient le genou (16 %), le coude (15 %) et la cheville/pied (14 %). Une augmentation du nombre d’heures d’entraînement hebdomadaires était associée à un risque accru de blessures ( p = 0,046 ; Exp(B) = 0,716). Cette étude a permis de quantifier l’incidence des blessures chez un groupe de joueurs de Kin-Ball et d’identifier les déterminants associés à ces blessures. Les genoux et coudes étaient les plus touchés. Une fréquence d’entraînement élevée était associée à un risque plus élevé de blessures, probablement en raison d’une plus grande exposition à des facteurs de risque et à des événements déclencheurs. The primary objective of this study was to identify the anatomical regions most frequently injured and to estimate the incidence of injuries during competitive Kin-Ball practice. The secondary objective was to identify determinants of these injuries in Kin-Ball players. A series of self-administered online questionnaires were completed by competitive athletes from the Fédération Québécoise de Kin-Ball. These questionnaires included an anthropometric and sociodemographic questionnaire, a Kin-Ball practice questionnaire, and a French version adapted from the Nordic Musculoskeletal Questionnaire. A binary logistic regression model was used to identify injury determinants. From a total of 134 respondents, 105 athletes (78%) suffered an injury during the year, for a total of 214 injuries (average of 2.04 injuries per athlete). The most frequent injuries were to the knee (16%), elbow (15%) and ankle/foot (14%). An increase in weekly training hours was associated with an increased risk of injury ( P = 0.046; Exp(B) = 0.716). This study quantified the incidence of injury in a group of Kin-Ball players and identified the determinants of injury. Knees and elbows are most affected. High training frequency was associated with increased injury risk, probably due to greater exposure to risk factors and trigger events.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.018
GPT teacher head0.330
Teacher spread0.312 · 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.

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

Citations0
Published2025
Admission routes3
Has abstractyes

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