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Record W2609673875 · doi:10.3138/ptc.2016-47

Balance Assessment Practices of Saskatchewan Physiotherapists: A Brief Report of Survey Findings

2017· article· en· W2609673875 on OpenAlexaffvenueabout
Alison Oates, Catherine M. Arnold, JoAnn Walker-Johnston, Karen Van Ooteghem, Ainsley Oliver, Jennifer Yausie, Nicole Loucks, Kelly Bailey, Justin Lemieux, Kathryn M. Sibley

Bibliographic record

VenuePhysiotherapy Canada · 2017
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsManitoba HealthUniversity of WaterlooSaskatchewan Health AuthorityUniversity of Saskatchewan
Fundersnot available
KeywordsBalance (ability)Physical therapyPhysical medicine and rehabilitationMedicine

Abstract

fetched live from OpenAlex

Purpose: This study was conducted to determine the balance assessment practices of physiotherapists in Saskatchewan. Methods: Practising physiotherapists who assess and treat adults with balance and mobility impairments were eligible to participate in this cross-sectional, online survey. The questions investigated the use of balance assessment measures, the balance components assessed, and practice area. Results: Of the 72 respondents, most reported regularly assessing five or more of the nine balance components listed. Movement observation was the most commonly reported measure used, followed by the Berg Balance Scale, single-leg stance test, and tandem standing/walking. Conclusions: Most physiotherapists in Saskatchewan use a variety of tools to assess balance. Gaps in practices related to fall prevention were noted in the mismatch between the tools used and the components reportedly assessed.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.200
Threshold uncertainty score0.403

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.038
GPT teacher head0.419
Teacher spread0.380 · 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 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

Citations13
Published2017
Admission routes3
Has abstractyes

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