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Record W1968810163 · doi:10.1249/mss.0b013e3181cdd4e9

Effects of Ankle Power Training on Movement Time in Mobility-Impaired Older Women

2010· article· en· W1968810163 on OpenAlexafffund
Sandra C. Webber, Michelle M. Porter

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2010
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsUniversity of ManitobaResearch Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsAnklePhysical medicine and rehabilitationAnkle dorsiflexionConcentricTraining (meteorology)Flexibility (engineering)Plantar flexionPhysical therapyMedicinePsychologyMathematicsPhysicsStatisticsSurgery

Abstract

fetched live from OpenAlex

PURPOSE: Reduced abilities to generate power put older adults at risk in situations that demand rapid movements. Slower movement times are associated with greater risk of falling and of being involved in a motor vehicle crash. The purpose of this study was to determine the effects of power training on foot movement time and, secondarily, on ankle strength and power in mobility-impaired older women. METHODS: Fifty mobility-impaired women (70-88 yr) trained twice per week for 12 wk in one of three groups (weights, elastic bands, or placebo control). All groups performed seated warm-up exercises, followed by either concentric dorsiflexion (DF) and plantarflexion (PF) resistance exercises (weights and bands) performed "as fast as possible" or upper body flexibility exercises (control). Foot reaction/movement time and ankle DF and PF peak torque (30 degrees x s(-1)) and peak power (90 degrees x s(-1)) were measured before and after training. RESULTS: Participants who trained with elastic bands demonstrated improvements in movement time (decreased by 24 ms or 12%, P = 0.003). All groups demonstrated improvements in DF and PF strength and power, which were not statistically different. CONCLUSIONS: High-velocity/low-load (elastic bands) training improved movement time, which may have important implications in circumstances when rapid generation of torque is required (e.g., to avoid a fall or prevent a vehicle crash). Elastic bands are relatively inexpensive and provide a practical form of training that could be considered in programs designed for older adults with mobility limitations.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.000

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 head0.013
GPT teacher head0.322
Teacher spread0.309 · 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 designNon-randomized 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

Citations46
Published2010
Admission routes2
Has abstractyes

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