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Record W2164454063 · doi:10.3109/09593980802664851

Intertrial and test-retest reliabilities of Timed Bridge tests among frail older adults

2009· article· en· W2164454063 on OpenAlexaff
Manon Pilon, Sylvie Nadeau, France Piotte

Bibliographic record

VenuePhysiotherapy Theory and Practice · 2009
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversité de MontréalCentre for Interdisciplinary Research in RehabilitationCentre Intégré de Santé et de Services Sociaux des Laurentides
Fundersnot available
KeywordsGeneralizability theoryTest (biology)Reliability (semiconductor)MedicineBridge (graph theory)PopulationPhysical therapyPsychologyAudiologyDevelopmental psychologySurgery

Abstract

fetched live from OpenAlex

The objective of this study was to assess the reliability of three versions of the Timed Bridge test (TB test) using the generalizability theory. A convenience sample of 30 frail older adults, from 65 to 94 years of age, performed three different TB Tests: 1) hold test (TB-Static); 2) five-repetitions dynamic test (TB-5rep); and 3) 60-second dynamic test (TB-60s). The tests were repeated twice on two occasions separated by a 48-hour interval. For each trial, the height of the bridge, the time of execution or the number of repetitions, the pain, and perceived effort were recorded. The intertrial and test-retest reliability for bridge heights were excellent. For the duration and the number of repetitions, a good intertrial reliability was found (0.83 <Phi< 0.94; SEMs 11.1 s, 2.9 s, and 4.2 rep), and the test-retest reliability was good for the TB-60 s and moderate for TB-Static and for the TB-5rep. The different tests were generally well tolerated by the subjects. The level of exertion perceived by the participants was light for the TB-5rep and moderate for the TB-Static and TB-60 s. The TB tests were simple to execute, showed good clinical applicability, and provided reliable measurements in a geriatric population.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.959
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.317
Teacher spread0.310 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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