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Record W2994632852 · doi:10.1136/bjsports-2019-101117

Implementing a junior high school-based programme to reduce sports injuries through neuromuscular training (iSPRINT): a cluster randomised controlled trial (RCT)

2019· article· en· W2994632852 on OpenAlexafffundabout
Carolyn A. Emery, Carla van den Berg, Sarah A. Richmond, Luz Palacios‐Derflingher, Carly McKay, Patricia K. Doyle–Baker, Megan McKinlay, Clodagh Toomey, Alberto Nettel‐Aguirre, Evert Verhagen, Kathy Belton, Alison Macpherson, Brent Hagel

Bibliographic record

VenueBritish Journal of Sports Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsYork UniversityPublic Health OntarioUniversity of TorontoUniversity of AlbertaUniversity of Calgary
FundersAlberta InnovatesInternational Olympic CommitteeAlberta Children's Hospital FoundationUniversity of AlbertaAlberta Innovates - Health SolutionsChildren's Hospital Foundation
KeywordsRandomized controlled trialPhysical therapyCluster randomised controlled trialMedicinePhysical medicine and rehabilitationCluster (spacecraft)Computer scienceSurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the effectiveness of a junior high school-based sports injury prevention programme to reduce injuries through neuromuscular training (NMT). METHODS: This was a cluster randomised controlled trial. Students were recruited from 12 Calgary junior high schools (2014-2017). iSPRINT is a 15 min NMT warm-up including aerobic, agility, strength and balance exercises. Following a workshop, teachers delivered a 12-week iSPRINT NMT (six schools) or a standard-of-practice warm-up (six schools) in physical education classes. The definition of all recorded injuries included injuries that resulted in participants being unable to complete a sport and recreation (S&R) session, lost time from sport and/or seek medical attention. Incidence rate ratios (IRRs) were estimated based on multiple multilevel Poisson regression analyses (adjusting for sex (considering effect modification) and previous injury, offset by S&R participation hours, and school-level and class-level random effects were examined) for intent-to-treat analyses. RESULTS: 1067 students (aged 11-16) were recruited across 12 schools (6 intervention schools (22 classes), 6 control schools (27 classes); 53.7% female, 46.3% male). The iSPRINT programme was protective of all recorded S&R injuries for girls (IRR=0.543, 95% CI 0.295 to 0.998), but not for boys (IRR=0.866, 95% CI 0.425 to 1.766). The iSPRINT programme was also protective of each of lower extremity injuries (IRR=0.357, 95% CI 0.159 to 0.799) and medical attention injuries (IRR=0.289, 95% CI 0.135 to 0.619) for girls, but not for boys (IRR=1.055, 95% CI 0.404 to 2.753 and IRR=0.639, 95% CI 0.266 to 1.532, respectively). CONCLUSION: The iSPRINT NMT warm-up was effective in preventing each of all recorded injuries, lower extremity injuries and medically treated S&R injuries in female junior high school students. TRIAL REGISTRATION NUMBER: NCT03312504.

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.017
GPT teacher head0.295
Teacher spread0.278 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations51
Published2019
Admission routes3
Has abstractyes

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