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Record W7117691161 · doi:10.5535/arm.250080

Psychometric Properties of the Balance Self-Efficacy Scale in People With Stroke

2025· article· en· W7117691161 on OpenAlexaboutno aff
Peiming Chen, Shamay S.M. Ng, Yee Lam Cheung, Hin Yam Hong, Sui Hin Law, Cynthia Y.Y. Lai

Bibliographic record

VenueAnnals of Rehabilitation Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
FundersHong Kong Polytechnic University
KeywordsScale (ratio)Stroke (engine)Balance (ability)Measure (data warehouse)Outcome (game theory)Quality (philosophy)

Abstract

fetched live from OpenAlex

Objective: To investigate the psychometric properties of the balance self-efficacy (BSE) scale in people with stroke. METHODS: This is a cross-sectional study held in a university-based rehabilitation center. Sixty- three people with stroke and 30 healthy older adults were included from the community dwelling. The people with stroke underwent the following assessments in a random order: the BSE, Fugl-Meyer Assessment of Lower Extremity (FMA-LE), muscle strength of plantar flexors and dorsiflexors, Montreal Cognitive Assessment, Berg Balance Scale, Limit of Stability (LOS), Foot and Ankle Ability Measure (FAAM), 12-Item Short Form Survey (SF-12) version 2, and Oxford Participation and Activities Questionnaire (Ox-PAQ). The healthy older adults were assessed with BSE. RESULTS: The BSE scale demonstrated good test-retest reliability (intraclass correlation coefficient= 0.796) with minimal detectable change at a 95% confidence interval of 433.74 and cut-off score of 1,225, which best differentiated between people with stroke and healthy older adults. The BSE score was significantly correlated with the FMA-LE score, muscle strength of the affected side ankle dorsiflexor and plantar flexor, LOS parameter, FAAM, SF- 12, and Ox-PAQ scores. Conclusion: The BSE scale is a reliable clinical tool with good test-retest reliability. The BSE scores were significantly correlated with other outcome measures that assess motor functions, balance, and quality of life. It is a simple and easy-to-administer outcome measure for assessing BSE in people with stroke.

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)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.034
Threshold uncertainty score0.322

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
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 head0.020
GPT teacher head0.309
Teacher spread0.289 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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