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Record W1973957859 · doi:10.3138/ptc.2009-51

Rasch Analysis of the Fullerton Advanced Balance (FAB) Scale

2010· article· en· W1973957859 on OpenAlexvenueno aff
Penelope J. Klein, Roger C. Fiedler, Debra J. Rose

Bibliographic record

VenuePhysiotherapy Canada · 2010
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsRasch modelCronbach's alphaPolytomous Rasch modelBalance (ability)Scale (ratio)Reliability (semiconductor)PsychologyTest (biology)PsychometricsItem response theoryPhysical therapyClinical psychologyMedicineDevelopmental psychology

Abstract

fetched live from OpenAlex

PURPOSE: This cross-sectional study explores the psychometric properties and dimensionality of the Fullerton Advanced Balance (FAB) Scale, a multi-item balance test for higher-functioning older adults. METHODS: Participants (n=480) were community-dwelling adults able to ambulate independently. Data gathering consisted of survey and balance performance assessment. Psychometric properties were assessed using Rasch analysis. RESULTS: Mean age of participants was 76.4 (SD=7.1) years. Mean FAB Scale scores were 24.7/40 (SD=7.5). Analyses for scale dimensionality showed that 9 of the 10 items fit a unidimensional measure of balance. Item 10 (Reactive Postural Control) did not fit the model. The reliability of the scale to separate persons was 0.81 out of 1.00; the reliability of the scale to separate items in terms of their difficulty was 0.99 out of 1.00. Cronbach's alpha for a 10-item model was 0.805. Items of differing difficulties formed a useful ordinal hierarchy for scaling patterns of expected balance ability scoring for a normative population. CONCLUSION: The FAB Scale appears to be a reliable and valid tool to assess balance function in higher-functioning older adults. The test was found to discriminate among participants of varying balance abilities. Further exploration of concurrent validity of Rasch-generated expected item scoring patterns should be undertaken to determine the test's diagnostic and prescriptive utility.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.850
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.322
Teacher spread0.315 · 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

Citations56
Published2010
Admission routes1
Has abstractyes

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