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Record W2023261238 · doi:10.1589/jpts.25.1137

Effects of the MWM Technique Accompanied by Trunk Stabilization Exercises on Pain and Physical Dysfunctions Caused by Degenerative Osteoarthritis

2013· article· en· W2023261238 on OpenAlexaboutno aff
Chan-Woo Nam, Sang‐In Park, Min-Sik Yong, Young-Min Kim

Bibliographic record

VenueJournal of Physical Therapy Science · 2013
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOsteoarthritisVisual analogue scaleTrunkPhysical therapyJoint mobilizationPhysical medicine and rehabilitationRange of motionAlternative medicinePathology

Abstract

fetched live from OpenAlex

[Purpose] This study aimed to identify how treatment with the Mulligan technique of mobilization with movement (MWM) influences pain and physical function of patients with degenerative osteoarthritis. [Subjects] Thirty patients diagnosed with degenerative osteoarthritis were divided into an experimental group (n=15), and a control group (n=15). [Methods] The experimental group was treated with general physical therapy, trunk stabilization exercises, and performed the MWM using the Mulligan technique. The control group was treated with general physical therapy, and then performed trunk stabilization exercises. [Results] Statistically significant differences were found after the intervention in the experimental group in the visual analog scale and Western Ontario and McMaster Universities osteoarthritis index pain, stiffening, and physical function scores. [Conclusion] We consider the treatment of degenerative osteoarthritis patients using the MWM technique is effective for reducing pain and improving physical functions.

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)0.000
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.006
GPT teacher head0.258
Teacher spread0.252 · 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

Citations18
Published2013
Admission routes1
Has abstractyes

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