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Record W6977484604 · doi:10.6084/m9.figshare.29859909

Physiotherapists’ understanding and assessment of gait stability: a qualitative study

2025· dataset· en· W6977484604 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2025
Typedataset
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsGaitGait analysisTrunkQualitative researchRehabilitationCognitionClinical Practice

Abstract

fetched live from OpenAlex

Maintaining a stable gait is required to safely navigate our environments, however, little is known about what physiotherapists consider when determining an older adult’s gait stability. Thus, the objective of this study was to describe how physiotherapists understand and assess gait stability. Twenty-six Canadian registered physiotherapists with clinical experience in gerontology participated in a semi-structured interview. Physiotherapists were asked about their understanding of gait stability and shared their approach to assessment using videos of older adults walking. Physiotherapists then used a standardized definition of gait stability and re-assessed gait stability. Interviews were analyzed using conventional and summative content analysis. There was no common understanding of gait stability amongst participants, and their assessments included these features: managing disturbances to balance, movement of the trunk and arms, gait mechanics, level of independence, confidence, cognition and insight and medical conditions. Upon receiving a standardized definition of gait stability, participants more consistently discussed how gait impairments impacted resilience to perturbations. It is important for physiotherapists to gain familiarity with how to assess gait stability. This study highlights the need for translating gait stability knowledge into practice. Addressing gait stability in clinical practice may help physiotherapists better support patients in being able to safely navigate home and community environments.Some physiotherapists are unfamiliar with the term gait stability and there was variability in their gait stability assessments.Physiotherapists should consider using the six features identified in this study as a basis for understanding and assessing gait stability in their clinical practice. Addressing gait stability in clinical practice may help physiotherapists better support patients in being able to safely navigate home and community environments. Some physiotherapists are unfamiliar with the term gait stability and there was variability in their gait stability assessments. Physiotherapists should consider using the six features identified in this study as a basis for understanding and assessing gait stability in their clinical practice.

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)0.014
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0080.007
Scholarly communication0.0040.003
Open science0.0020.004
Research integrity0.0020.003
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 head0.181
GPT teacher head0.504
Teacher spread0.323 · 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 designQualitative
Domainnot available
GenreDataset

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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