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Record W14496049 · doi:10.21091/mppa.2012.4037

The Relationship Between Postural Stability and Dancer’s Past and Future Lower-Limb Injuries

2012· article· en· W14496049 on OpenAlexaff
Terry Clark, Emma Redding

Bibliographic record

VenueMedical Problems of Performing Artists · 2012
Typearticle
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBalance (ability)DancePhysical medicine and rehabilitationPhysical therapyLower limbRehabilitationInjury preventionForce platformMedicinePsychologyCenter of pressure (fluid mechanics)Poison controlSurgery

Abstract

fetched live from OpenAlex

In an effort to address dance-related injuries, screening programs are typically employed to assess injury susceptibility. The aim of this study was to explore for potential links between postural stability and dancers' previous lower-limb injuries and susceptibility to future lower-limb injuries. Eighty-five contemporary dance students were recruited at a UK dance conservatoire. Information concerning previous injuries was collected by self-report survey. The participants completed two balance tasks, one static and one dynamic, performed on a RS Scan Footscan pressure pad to calculate postural sway. Injuries in the participant cohort were then tracked for a 10-month period to assess injury susceptibility. The participants exhibited significantly less postural sway when balancing on the left leg than their right, and the women exhibited less postural sway than the men. A one-way ANOVA revealed that participants who had experienced a lower-limb injury in the 12 months prior to testing exhibited more postural sway than participants who had not experienced a lower-limb injury, with some of the differences attaining significance (p <0.05). No significant links were found between either postural sway or previous injury and future injury susceptibility. The results suggest that assessments of postural stability via centre of pressure measurements are a reliable method for assessing dancers' balance ability. While reaffirming the importance of comprehensive, multidisciplinary screening programs, the results also highlight the necessity of developing a greater understanding of both dancers and the environments in which they dance and work to fully ascertain injury susceptibility.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.040
GPT teacher head0.308
Teacher spread0.269 · 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

Citations13
Published2012
Admission routes1
Has abstractyes

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