MétaCan
Menu
Back to cohort
Record W2609226356 · doi:10.3138/ptc.2016-27ep

Does Fall Arrest Strategy Training Added to a Fall Prevention Programme Improve Balance, Strength, and Agility in Older Women? A Pilot Study

2017· article· en· W2609226356 on OpenAlexaffvenue
Cathy M. Arnold, JoAnn Walker-Johnston, Joel L. Lanovaz, Lauren J. Lattimer

Bibliographic record

VenuePhysiotherapy Canada · 2017
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsUniversity of SaskatchewanSaskatchewan Health Authority
Fundersnot available
KeywordsFall preventionBalance (ability)Physical therapyPhysical medicine and rehabilitationMedicineTraining (meteorology)Injury preventionPoison controlMedical emergency

Abstract

fetched live from OpenAlex

Purpose: The purpose of this study was to determine the effect of a unique exercise programme (Fall Arrest Strategy Training, or FAST) on upper body strength, range of motion (ROM), and fall risk in older women. FAST was designed to improve upper body capacity to prevent injury when a fall cannot be avoided. Method: A quasi-randomized site design included 71 older women (aged 67–95 y, mean age 83 years), who participated either in a standard fall prevention programme (Staying on Your Feet, or SOYF; n=29) or in SOYF combined with FAST (n=42). The women were measured three times—at baseline, after the 12-week intervention, and again 12 weeks later—for upper body strength, ROM, and fall risk factors (fall risk questionnaire, balance, mobility, and leg strength). Results: No significant differences were found in age, physical activity, or cognitive or functional status between the SOYF–standard and the SOYF–FAST groups. Both groups improved their fall risk status after the intervention, with no significant differences between them; however, the SOYF–FAST group showed greater improvements in upper extremity strength and ROM (p=0.007). Conclusion: FAST can feasibly be integrated into fall prevention programming, with additional gains in upper body strength and ROM in older women.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.342
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.036
GPT teacher head0.365
Teacher spread0.329 · 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

Citations14
Published2017
Admission routes2
Has abstractyes

Explore more

Same venuePhysiotherapy CanadaSame topicBalance, Gait, and Falls PreventionFrench-language works237,207