MétaCan
Menu
Back to cohort
Record W2338596816 · doi:10.3109/02703181.2015.1128510

Impact of the Number of Steps on the Fukuda Stepping Test in Older Adults

2016· article· en· W2338596816 on OpenAlexaff
Nicole Paquet, Deborah A. Jehu, Yves Lajoie

Bibliographic record

VenuePhysical & Occupational Therapy In Geriatrics · 2016
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsIntraclass correlationTest (biology)Reliability (semiconductor)Step testStandard errorMedicineStatisticsPsychologyPhysical therapyMathematicsReproducibilitySignificant difference

Abstract

fetched live from OpenAlex

Aims: This study aimed to compare performance, within-subject variability and test–retest reliability between the 50-step and 100-step Fukuda test in healthy older adults. Methods: Fifty participants aged between 65 and 75 years performed three trials of both the 50- and 100-step tests on two separate sessions seven days apart. Their final foot position was measured relative to the starting line. Results: Absolute values of body rotation and lateral and longitudinal displacements were significantly larger on the 100-step than on the 50-step test. The mean standard deviations of these measures on the three trials were significantly larger on the 100- compared to the 50-step test, indicating larger within-subject variability. Intraclass correlation coefficients were similar for both tests, suggesting comparable test–retest reliability. Conclusion: The 50-step test is recommended over the 100-step as it may have reduced measurement error.

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)0.008
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.402
Teacher spread0.366 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

Explore more

Same venuePhysical & Occupational Therapy In GeriatricsSame topicBalance, Gait, and Falls PreventionFrench-language works237,207