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Record W4415727403 · doi:10.1186/s13643-025-02946-5

Should whole body vibration be used for falls prevention in older people living in the community?

2025· article· en· W4415727403 on OpenAlexaboutno aff
Suzanne M Dyer, Wing S Kwok, Rik Dawson, Ian D. Cameron, Catherine Sherrington

Bibliographic record

VenueSystematic Reviews · 2025
Typearticle
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsnot available
Fundersnot available
KeywordsOlder peopleWhole body vibrationIntervention (counseling)Health carePoison controlInjury preventionHuman factors and ergonomicsSuicide preventionSystematic reviewRandomized controlled trial

Abstract

fetched live from OpenAlex

The Canadian Task Force on Preventive Health Care has recently published a systematic review and network meta-analysis that concludes that whole-body vibration (WBV) has moderate-certainty evidence for falls prevention for older people living in the community. However, as Cochrane Collaboration falls prevention review authors and clinicians, we suggest that when the range of possible effects captured with the 95% confidence intervals, the likelihood of adverse events and the lack of evidence for effectiveness in older people living in care facilities are taken into account, that this intervention should be implemented with caution in this population. Outside of the clinical trial setting, WBV in this population should only be implemented following an individually tailored assessment and with guidance from an appropriately trained health professional.

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)0.011
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.008
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.091
GPT teacher head0.421
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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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