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Record W4414483027 · doi:10.21653/tjpr.1121215

THE EFFECTS OF KINESIOLOGICAL TAPING AND AEROBIC EXERCISE IN WOMEN WITH PRIMARY DYSMENORRHEA: A RANDOMİZED SINGLE-BLIND CONTROLLED TRIAL

2025· article· en· W4414483027 on OpenAlexaboutno aff
Simge Temizkan, Miray Budak

Bibliographic record

VenueTürk fizyoterapi ve rehabilitasyon dergisi · 2025
Typearticle
Languageen
FieldMedicine
TopicMenstrual Health and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsRandomized controlled trialAerobic exercisePostmenopausal womenSubacromial impingementSignificant difference

Abstract

fetched live from OpenAlex

Purpose: This study aimed to investigate the effects of kinesiological taping (KT) and aerobic exercise (AE) on pain, menstrual attitude, depression, and quality of life (QoL) in women with primary dysmenorrhea (PD).Methods: Forty-five participants diagnosed with PD were randomly assigned into three groups: KT group (n=15), AE group (n=15), and control group (n=15).The KT group received taping twice a week over 3 weeks, starting from the 14 th day of the menstrual cycle until the end of the cycle.The AE group performed moderate-intensity AE for 45 minutes twice a week for 3 weeks, following the same schedule.The control group received no intervention.Participants were evaluated on the 14 th day of the cycle and after 3 weeks using the McGill Pain Questionnaire (MPQ) for pain, the Menstrual Attitude Scale (MAS) for attitude, the Beck Depression Scale (BDS) for depression, and the short form-36 (SF-36) for QoL.Results: Within-group analyses showed significant improvements in MAS and SF-36 in the KT group, and in MPQ in the AE group (p<0.05).No significant changes were observed in the control group (p>0.05).Time*Group interaction analysis revealed a significant improvement in MPQ favoring the AE group and in MAS favoring the KT group (p<0.05). Conclusion:These findings suggest that KT may improve menstrual attitude, while AE may reduce pain in women with PD.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.869

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.260
Teacher spread0.254 · 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 designRandomized 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

Citations1
Published2025
Admission routes1
Has abstractyes

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