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Record W7117411476 · doi:10.17761/2025-d-24-00074

Effect of 12 Weeks of Hatha Balance Flow Yoga on Fall and Injury Risk in Postmenopausal Women

2025· article· en· W7117411476 on OpenAlexaff
Catherine M. Arnold, Brenna Bath, Shelly Prosko, Katie Crockett, Jonathan P. Farthing, Joel L. Lanovaz

Bibliographic record

VenueInternational Journal of Yoga Therapy · 2025
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsBalance (ability)Hatha yogaFall preventionIntervention (counseling)Injury preventionPoison controlPostmenopausal womenRisk factor

Abstract

fetched live from OpenAlex

Postmenopausal women are at an increased risk of falls and fractures. Upper-extremity fractures because of forward falls are common in women in their 50s and 60s, but little research has focused on the potential fall and injury risk factors within this age bracket and ways to mitigate the risks. Yoga is a promising intervention for older women to improve balance, muscle strength, and upper-body reactions for a safer fall landing. The purpose of the present study was to evaluate the effect of 12 weeks of a hatha Balance Flow Yoga class on forward fall and injury risk factors in postmenopausal women. Thirty-six women between the ages of 50 and 70 participated in an intervention study where they were tested at baseline (base), 12 weeks after a control period (pre), and again 12 weeks after participating in the group-based yoga intervention offered twice per week (post). Outcome measures included fall risk factors (balance, balance confidence, lower-body strength, and dual task) and forward fall injury risk factors (upper-body strength, range of motion, and response time). Repeated-measures multivariate analysis of variance found a significant time improvement in fall risk factors and forward fall injury risk factors (p = 0.004). Specifically, there was significant improvement in balance (one-leg stand), lower-body strength (30-second sit to stand), and upper-body response time after the intervention. Tailoring yoga classes for older women to focus on improving fall-related risk factors may help to provide effective options to improve their ability to prevent serious consequences of fall-related injury.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.652
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.339
Teacher spread0.330 · 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.

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
Published2025
Admission routes1
Has abstractyes

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