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Record W2919862450 · doi:10.16884/jrr.2018.22.4.1

Effects of the Education about the Self-application of the Kinesio-Taping for the Adult Women with Chronic Low Back Pain on Pain, Satisfaction and Gait

2018· article· en· W2919862450 on OpenAlexaboutno aff
Sung-Min Son, Sung-Won Kwag, Byoung‐Jin Jeon

Bibliographic record

VenueKorean Society for Rehabilitation of Persons with Disabilities · 2018
Typearticle
Languageen
FieldMedicine
TopicHealthcare and Venom Research
Canadian institutionsnot available
Fundersnot available
KeywordsGaitPhysical medicine and rehabilitationPhysical therapyMedicinePsychology

Abstract

fetched live from OpenAlex

본 연구는 일상생활에서 스스로 자신의 통증을 관리할 수 있도록 키네시오 테이핑 자가 적용 교육을 적용하여 만성요통 여성들을 대상으로 통증과 만족도 및 보행에 미치는 영향을 분석하고자 하였으며, 키네시오 테이핑 자가적용에 대한 기초자료를 제공하고자 수행 되었다. 연구대상자는 만성요통 여성 30명이며, 키네시오 테이핑 적용을 2주간 실시한후 자가적용 교육에 따른 자가적용을 4주간 실시하였다. 대상자들의 통증 평가는 Visual Analog Scale (VAS)을 활용하였으며, 만족도의 분석은 Canadian Occupational Performance Measure (COPM)를 활용하였다. 또한, 보행의 분석은 Walkway MG-1000 보행분석기를 활용하여 Stride length, Step length, Step width and Gait time을 분석하였다. 그 결과 테이핑 적용에 따라 통계적으로 유의미한 통증의 감소와 만족도의 증가, 보행 능력의 증가가 지속적으로 나타남을 확인할 수 있었다. 또한, 대비검정 분석결과 처치 내 효과검증에서 통증, 만족도 및 보행 분석결과 에서 (처치 전과 테이핑 적용 2주 후) 통계적인 유의미한 차이가 나타났으며, Step width와 만족도 분석결과에서 (처치 전과 테이핑 적용 2주 후)와 (자가적용교육에 따른 자가적용 4주 후) 통계적으로 유의미한 차이가 나타났다. 자기관리 능력의 향상은 만성통증 환자들에게 필수적이며, 일상생활에서 스스로 관리하여 적용할수 있어야 한다. 따라서, 적극적이고 지속적인 통증관리를 위한 자기관리능력의 향상을 위해 키네시오 테이핑 자가적용 교육의 적용을 고려해야 할 것이다.We aimed to analyze the effects of Kinesio-Taping on pain, satisfaction, and gait, and to provide basic data on the self-application of this method. The participants were 30 adult women with chronic low back pain. Kinesio-Taping was applied for 2 weeks, followed by 4 weeks of self-application education and self-application. The participants pain levels were analyzed using the visual analog scale, satisfaction was analyzed using the Canadian Occupational Performance Measure, and gait was analyzed in terms of stride length, step length, step width, and gait time using the Walkway MG-1000 gait analyzer. The results of the pain showed the statistically significant decrease steadily (p<0.001) and the results of the satisfaction showed the statistically significant increase steadily (p<0.001) from the application of the Kinesio-Taping. Also, according to the In-Object verification between pre-test, taping application (after 2 weeks) and Self-application (after 4 weeks), the results of the satisfaction showed statistically significant difference (p<0.001). According to the gait analysis, the results of the stride length and step length showed the statistically significant increase steadily (p<0.001) and the results of the step width and gait time showed the statistically significant decrease steadily (p<0.001) from the application of the Kinesio-Taping. Also, according to the In-Object verification between pre-test, taping application (after 2 weeks) and Self-application (after 4 weeks), the results of the step width showed statistically significant difference (p<0.001). Thus, the self-application education about the Kinesio-Taping should be considered to reduce the pain and improve the performance level of the activities of daily life through the improvement of the self-management ability and to induce the active participation in the self-management activities and increase the satisfaction.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0030.000

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 head0.010
GPT teacher head0.295
Teacher spread0.285 · 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 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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