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Record W1556509676

유선형 후방 밸런스 신발이 퇴행성 슬관절염 환자의 대퇴사두근 근력에 미치는 효과

2011· article· ko· W1556509676 on OpenAlexaboutno aff
김연정

Bibliographic record

Venue한국체육과학회지 · 2011
Typearticle
Languageko
FieldMedicine
TopicDiverse Approaches in Healthcare and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIsometric exerciseWOMACBalance (ability)OsteoarthritisPhysical therapyRandomized controlled trialPhysical medicine and rehabilitationSurgery
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study was to assess 1)the effectiveness of the curved rear balance shoes in reducing knee pain in patients with knee osteoarthritis(OA) and 2)changes in EMG signal and strength of quadriceps muscle and physical function(ability to react instantly) compared with normal shoes for 8 weeks. The research design was a randomized controlled trial(24 female, knee OA grades Ⅱ-Ⅲ of radiographic evaluation). Subjects were randomized to curved rear balance shoes(n=14) or normal shoes(n=10). The mean IEMG, WOMAC(Korean Western-Ontario & Mcmaster) index questionnaire, peak torque with isometric training system at 90°/s, 150°/s and ability to react instantly were quantified at week 0 and after week 8. Paired t-test(for IEMG) and Repeated measurement design were done for between-group comparison(a=.05). There was a significant increase in average IEMG for quadriceps muscle in the curved rear balance shoes compared with normal shoes. There was an increase of average peak torque but no significant increase in muscle strength over the 8 wks. A knee pain and stiffness in knee after 8 weeks in the curved rear balance shoes was significantly reduced(p<.05). The ability to react instantly was increased but it’s not significant statistically. This result shows that wearing the curved rear balance shoes for 8 wks can reduce pain but it doesnt make people who suffer from knee OA increase quadriceps for muscle strengthen.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.006

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 head0.325
GPT teacher head0.365
Teacher spread0.040 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2011
Admission routes1
Has abstractyes

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