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Record W4319826876 · doi:10.1080/14763141.2023.2176353

Effect of incline versus block heel-raise exercise on foot muscle strength and vertical jump performance – an 11-week randomized resistance training study

2023· article· en· W4319826876 on OpenAlexaff
Torstein E. Dæhlin, Michael D. Kennedy, Hossein Rouhani, Loren Z.F. Chiu

Bibliographic record

VenueSports Biomechanics · 2023
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHeelAnkleMedicineVertical jumpPlantar flexionPhysical medicine and rehabilitationPhysical therapyJumpMuscle strengthFoot (prosody)MathematicsSurgeryAnatomyPhysics

Abstract

fetched live from OpenAlex

Strengthening the toe flexors and ankle plantar flexors may improve vertical jump performance. One exercise that may be effective for concurrently strengthening these muscles is heel-raises performed on an incline. The purpose of this study was to investigate the effects of incline versus conventional (block) heel-raise exercise on hallux and II-V digit flexor strength, vertical jump performance, and ankle plantar flexor strength. Thirty-three female volleyball players were randomly allocated to perform incline (n = 17) or block (n = 16) heel-raise exercise for 11-weeks. Participants’ toe flexor strength, countermovement jump, approach jump, and ankle plantar flexor strength were assessed before, after 7 weeks, and after 11 weeks of exercise. There were no significant time-by-group interactions for any variable (p > 0.05). However, both groups improved their hallux flexor strength (Δ0.27 ± 0.50 N·kg−1; p < 0.05), and vertical countermovement (Δ1.2 ± 2.3 cm; p < 0.05) and approach (Δ1.9 ± 2.6 cm; p < 0.05) jump height from pre- to post-test. No changes were observed in the ankle plantar flexor or II-V digit flexor strength (n > 0.05). Both incline and conventional heel-raises improve toe flexor strength. Practitioners seeking to improve individuals’ foot function may consider incorporating incline or block heel-raises.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.309
Threshold uncertainty score0.870

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.304
Teacher spread0.282 · 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 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

Citations4
Published2023
Admission routes1
Has abstractyes

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