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Record W2046946864 · doi:10.1177/0363546505279576

Evaluation of Risk Factors for Injury in Adolescent Soccer

2005· article· en· W2046946864 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe American Journal of Sports Medicine · 2005
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: There are limited data on the epidemiology of adolescent soccer injury across all levels of play. HYPOTHESIS: Through implementation and validation of an injury surveillance system in adolescent soccer, risk factors for injury will be identified. STUDY DESIGN: Descriptive epidemiology study. METHODS: The study population was a random sample of 21 adolescent soccer teams (ages 12-18). A certified athletic therapist completed preseason baseline measurements and did weekly assessments of any identified soccer injury. The injury definition included any injury occurring in soccer that resulted in 1 or more of the following: medical attention, the inability to complete a session, or missing a subsequent session. RESULTS: Based on completeness of data in addition to validity of time loss, this method of surveillance has proven to be effective. The overall injury rate during the regular season was 5.59 injuries per 1,000 player hours (95% confidence interval, 4.42-6.97). Soccer injury resulted in time loss from soccer for 86.9% of the injured players. Ankle and knee injuries were the most common injuries reported. Direct contact was reported to be involved in 46.2% of all injuries. There was an increased risk of injury associated with games versus practices (relative risk = 2.89; 95% confidence interval, 1.69-5.21). The risk of injury in the under 14 age group was greatest in the most elite division. Having had a previous injury in the past 1 year increased the risk of injury (relative risk = 1.74; 95% confidence interval, 1.0-3.1). CONCLUSION: There were significant differences in injury rates found by division, previous injury, and session type (practice vs game). Future research should include the use of such a surveillance system to examine prevention strategies for injury in adolescent soccer.

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.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.839
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.031
GPT teacher head0.360
Teacher spread0.329 · 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