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Using psychometric techniques to improve the Balance Evaluation Systems Test: the mini-BESTest
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OBJECTIVE: To improve, with the aid of psychometric analysis, the Balance Evaluation Systems Test (BESTest), a tool designed to analyse several postural control systems that may contribute to poor functional balance in adults. METHODS: Performance of the BESTest was examined in a convenience sample of 115 consecutive adult patients with diverse neurological diagnoses and disease severity, referred to rehabilitation for balance disorders. Factor (both explorative and confirmatory) and Rasch analysis were used to process the data in order to produce a new, reduced and coherent balance measurement tool. RESULTS: Factor analysis selected 24 out of the 36 original BESTest items likely to represent the unidimensional construct of "dynamic balance". Rasch analysis was then used to: (i) improve the rating categories, and (ii) delete 10 items (misfitting or showing local dependency). The model consisting of the remaining 14 tasks was verified with confirmatory factor analysis to meet the stringent requirements of modern measurement. CONCLUSION: The new 14-item scale (dubbed mini-BESTest) focuses on dynamic balance, can be conducted in 10-15 min, and contains items belonging evenly to 4 of the 6 sections from the original BESTest. Further studies are needed to confirm the usefulness of the mini-BESTest in clinical settings.
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“the recently described Balance Evaluation Systems Test (BESTest) 27 or the miniBESTest, 78 which were developed to differentiate the six postural control elements of the systems control approach.”
From Exercise interventions improve postural control in children with cerebral palsy: a systematic review (2015) · cites this paper as [78]
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Self-citation
Metadata
- Authors
- Franchignoni, F., Horak, F., Godi, M., Nardone, A., & Giordano, A.
- Affiliations
- Fondazione Salvatore Maugeri (IT)
- Oregon Health & Science University (US)
- Università degli Studi del Piemonte Orientale “Amedeo Avogadro” (IT)
- Venue
- Journal of Rehabilitation Medicine
- Published
- 2010
- Volume
- 42
- Issue
- 4
- Pages
- 323-331
- ISSN
- 1650-1977 (ISSN-L)
- PMC
- PMC3228839
- OpenAlex
- W2156121997
- Cited by
- 1,081
- References
- 42
- Citations by year
- 2026: 86 · 2025: 112 · 2024: 109 · 2023: 95 · 2022: 97 · 2021: 114 · 2020: 93 · 2019: 82 · 2018: 55 · 2017: 51 · 2016: 46 · 2015: 37 · 2014: 31 · 2013: 29 · 2012: 27
- FWCI
- 58.89
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Journal of Rehabilitation Medicine (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (5r37ag006457-28)
- National Institute on Aging (R37-AG006457, R01AG006457, AG 06457)
- Topics
- Health Sciences › Health Professions › Physical Therapy, Sports Therapy and Rehabilitation › Balance, Gait, and Falls Prevention
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
- Keywords
- Balance Evaluation Systems Test, Mini-BESTest, dynamic balance, postural control, balance disorders, neurorehabilitation, psychometric validation, Rasch analysis, factor analysis, item reduction, local dependence
- MeSH terms
- Adult, Aged, Postural Balance, Factor Analysis, Statistical, Female, Humans, Male, Middle Aged, Psychometrics, Vestibular Diseases, Gait Disorders, Neurologic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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