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Record W2577389769 · doi:10.1177/0308022616680364

Impact of yoga on balance, balance confidence and occupational performance for adults with diabetic peripheral neuropathy: A pilot study

2017· article· en· W2577389769 on OpenAlexaboutno aff
Leslie A Willis Boslego, Chloe E Munterfering Phillips, Karen Atler, Brian Tracy, Marieke Van Puymbroeck, Arlene A. Schmid

Bibliographic record

VenueBritish Journal of Occupational Therapy · 2017
Typearticle
Languageen
FieldMedicine
TopicDiabetic Foot Ulcer Assessment and Management
Canadian institutionsnot available
FundersCollege of Education and Human Sciences, University of Nebraska–LincolnColorado CollegeColorado State University
KeywordsBalance (ability)MedicinePeripheral neuropathyPhysical therapyConfidence intervalPhysical medicine and rehabilitationDiabetes mellitusInternal medicine

Abstract

fetched live from OpenAlex

Introduction The purpose of this study was to examine the preliminary efficacy of yoga on balance, balance confidence, occupational performance, and satisfaction with performance in adults with diabetic peripheral neuropathy. Method Fifteen adults with diabetic peripheral neuropathy attended eight weeks of yoga, including positive affirmations, breathing, postures and relaxation. Balance was measured using the Berg balance scale; balance confidence, using the activities-specific balance confidence scale; and occupational performance and satisfaction, using the Canadian occupational performance measure. We used a non-controlled pretest–posttest design. Findings Significant improvements were found for all measures. Improvements remained significant after the Bonferroni correction (α = 0.05/4–0.0125) and effect sizes were large for occupational performance and satisfaction ( d Cohen = 1.13, 1.07, respectively). Conclusion Yoga may significantly improve balance, balance confidence, occupational performance, and satisfaction for adults with diabetic peripheral neuropathy. Further research utilizing a control group, a larger sample size, and randomization is required.

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)0.000
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 score0.031
Threshold uncertainty score0.545

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.046
GPT teacher head0.351
Teacher spread0.305 · 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

Citations28
Published2017
Admission routes1
Has abstractyes

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