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Record W2762469609 · doi:10.7575/aiac.ijkss.v.5n.4p.1

The Effect of an Isometric Hip Muscle Strength Training Protocol on Valgus Angle During a Drop Vertical Jump in Competitive Female Volleyball Players

2017· article· en· W2762469609 on OpenAlexaff
Kaitlin Jackson, Tyson A.C. Beach, David M. Andrews

Bibliographic record

VenueInternational Journal of Kinesiology and Sports Science · 2017
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsUniversity of TorontoUniversity of Windsor
Fundersnot available
KeywordsIsometric exerciseHamstringMedicineVertical jumpPhysical therapyValgusPhysical medicine and rehabilitationACL injuryRepeated measures designRotator cuffMuscle strengthAnterior cruciate ligamentJumpOrthodonticsMathematicsSurgery

Abstract

fetched live from OpenAlex

Background: Hip muscle weakness is associated with higher peak knee valgus angles (VA) during drop vertical jumps (DVJ) and linked to ACL injury risk. Objective: To determine if isometric strengthening (IST) of the hip extensor, abductor, and external rotator muscle groups would reduce VA exhibited during a DVJ. Methodology: Fourteen female volleyball players (7 training (TG), 7 control (CG), VA≥9˚ during DVJ) participated. Pre- and post-test gluteal, quadriceps and hamstring strength were measured with a digital force gauge. Three-dimensional kinematics were collected during 15 DVJ trials. TG participated in a 6-week IST program that targeted the hip extensor, abductor, and external rotator muscle groups. Two-way mixed ANOVAs compared mean differences of VA and strength. Single-participant analyses examined if athlete-specific adaptations went undetected in the analyses of aggregated data. Results: TG hip extension, abduction, and knee flexion strength increased, respectively, by 20.5%, 27.5% and 23.5% (P<0.05). No group-level changes in VA were detected. Unilateral VA decreased for 5 TG participants, and bilateral VA decreased in 2 TG participants. Conclusions: IST increased isometric hip muscle strength, but its effect on VA is inconclusive based on group-level analyses. Using single-participant designs, future studies should assess IST and/or dynamic resistance/neuromuscular training in a larger sample to determine its effect on ACL injury risk factors.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.213

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.016
GPT teacher head0.348
Teacher spread0.332 · 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.

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

Citations9
Published2017
Admission routes1
Has abstractyes

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