Which Tools Better Predict Fall Risk in Parkinson's Disease: A Comparative Study of Objective, Self-Reported, and Functional Balance Assessment
NCT ID: NCT07148700
Last Updated: 2025-08-29
Study Results
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Basic Information
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RECRUITING
40 participants
OBSERVATIONAL
2025-05-01
2025-08-30
Brief Summary
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Methods: Patients with PD at Hoehn and Yahr stages 1-3 will be included in the study. Fall data will be collected using a fall diary, while objective balance will be assessed with the Biodex Balance System, functional performance will be evaluated with the Mini-BESTest, and self-reported balance confidence will be measured with the FES-I.
Detailed Description
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Falls in individuals with PD are associated with severe complications, including hospitalization, fear of falling, impairments in body structure and function, activity limitations, increased dependence in activities of daily living, social restrictions, and diminished quality of life. Preventing falls in PD, a problem with significant consequences and multiple risk factors, has been shown to reduce morbidity, mortality, and healthcare costs.
The fundamental strategy for preventing falls involves accurately identifying individuals at risk and initiating appropriate interventions early. Although the etiology of falls in PD appears complex, the literature suggests that balance impairments are the primary cause and that interventions should focus on improving balance. Therefore, it is crucial to identify tools that can effectively detect balance deficits. Determining the ideal balance assessment method for clinical practice requires consideration of test sensitivity, simplicity and feasibility, minimal equipment and cost requirements, ease of patient comprehension, and time efficiency. In addition, the ability of an assessment tool to accurately predict falls is a crucial criterion when selecting the most appropriate test.
Several assessments exist to assess fall risk and balance deficits in PD, including objective measures such as the Biodex Balance System, self-reported tools like the Falls Efficacy Scale-International (FES-I) and Morse Fall Scale, and functional balance tests such as the Mini-Balance Evaluation Systems Test (Mini-BESTest), Timed Up and Go Test, and Berg Balance Scale. Each of these tools has distinct advantages and disadvantages. For example, devices like the Biodex Balance System provide objective and sensitive data, but they may not reflect balance abilities during functional positions and activities of daily living, limiting their validity. Additionally, these devices require specialized equipment and can be costly.
Self-reported scales such as the FES-I are valuable as they assess an individual's perceived balance confidence during activities of daily living, including eating, personal hygiene, dressing, and transfers. However, because these assessments rely on individuals recalling their fear of falling during specific activities, responses may be influenced by memory bias or inaccurate self-perception.
Functional tests like the Mini-BESTest have the advantage of assessing task-based performance across multiple dimensions of postural control (e.g., static/dynamic balance, sensory integration, anticipatory and reactive postural adjustments) and can guide individualized treatment strategies. Nevertheless, factors such as patient motivation during testing and misunderstanding of test instructions can influence results. Functional balance tests are also time-consuming due to their multi-step structure.
Although the validity and reliability of many of these assessment tools have been established, there is insufficient evidence to determine which method best reflects actual fall risk and frequency in daily life. Furthermore, no studies have compared the predictive ability of objective, self-reported, and functional tests for future falls in patients with PD. The aim of this study is to investigate the relationship between fall frequency and three different tools for balance assessment: the Biodex Balance System, which provides objective measurements; the FES-I, which relies on self-reported data; and the Mini-BESTest, which evaluates functional balance performance.
Conditions
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Keywords
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Study Design
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COHORT
CROSS_SECTIONAL
Study Groups
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Parkinson Disease Group
Participants diagnosed with Parkinson Disease by a neurologist
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
* Receiving stable dopaminergic treatment
* No other neurological disorders besides PD
* A Standardized Mini-Mental State Examination (MMSE) score \>24
* Hoehn and Yahr stage between 1-3
* Voluntarily agreed to participate in the study after receiving detailed information
Exclusion Criteria
* Having mental or physical impairments severe enough to hinder communication
* Clinically unstable condition within the past month
* Participation in a rehabilitation program within the last six months
40 Years
80 Years
ALL
No
Sponsors
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Bezmialem Vakif University
OTHER
Responsible Party
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Ayça Arslantürk Yıldırım
Research Assistant
Locations
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Bezmialem Vakif University
Istanbul, Eyup, Turkey (Türkiye)
Countries
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Central Contacts
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References
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Winser SJ, Kannan P, Bello UM, Whitney SL. Measures of balance and falls risk prediction in people with Parkinson's disease: a systematic review of psychometric properties. Clin Rehabil. 2019 Dec;33(12):1949-1962. doi: 10.1177/0269215519877498. Epub 2019 Oct 1.
Meekes WM, Korevaar JC, Leemrijse CJ, van de Goor IA. Practical and validated tool to assess falls risk in the primary care setting: a systematic review. BMJ Open. 2021 Sep 29;11(9):e045431. doi: 10.1136/bmjopen-2020-045431.
Lopes LKR, Scianni AA, Lima LO, de Carvalho Lana R, Rodrigues-De-Paula F. The Mini-BESTest is an independent predictor of falls in Parkinson Disease. Braz J Phys Ther. 2020 Sep-Oct;24(5):433-440. doi: 10.1016/j.bjpt.2019.07.006. Epub 2019 Jul 25.
Schlenstedt C, Brombacher S, Hartwigsen G, Weisser B, Moller B, Deuschl G. Comparison of the Fullerton Advanced Balance Scale, Mini-BESTest, and Berg Balance Scale to Predict Falls in Parkinson Disease. Phys Ther. 2016 Apr;96(4):494-501. doi: 10.2522/ptj.20150249. Epub 2015 Sep 17.
Liu WY, Tung TH, Zhang C, Shi L. Systematic review for the prevention and management of falls and fear of falling in patients with Parkinson's disease. Brain Behav. 2022 Aug;12(8):e2690. doi: 10.1002/brb3.2690. Epub 2022 Jul 14.
Camicioli R, Morris ME, Pieruccini-Faria F, Montero-Odasso M, Son S, Buzaglo D, Hausdorff JM, Nieuwboer A. Prevention of Falls in Parkinson's Disease: Guidelines and Gaps. Mov Disord Clin Pract. 2023 Sep 2;10(10):1459-1469. doi: 10.1002/mdc3.13860. eCollection 2023 Oct.
Schrag A, Choudhury M, Kaski D, Gallagher DA. Why do patients with Parkinson's disease fall? A cross-sectional analysis of possible causes of falls. NPJ Parkinsons Dis. 2015 Jun 11;1:15011. doi: 10.1038/npjparkd.2015.11.
Kerr GK, Worringham CJ, Cole MH, Lacherez PF, Wood JM, Silburn PA. Predictors of future falls in Parkinson disease. Neurology. 2010 Jul 13;75(2):116-24. doi: 10.1212/WNL.0b013e3181e7b688. Epub 2010 Jun 23.
Ou Z, Pan J, Tang S, Duan D, Yu D, Nong H, Wang Z. Global Trends in the Incidence, Prevalence, and Years Lived With Disability of Parkinson's Disease in 204 Countries/Territories From 1990 to 2019. Front Public Health. 2021 Dec 7;9:776847. doi: 10.3389/fpubh.2021.776847. eCollection 2021.
Dorsey ER, Bloem BR. The Parkinson Pandemic-A Call to Action. JAMA Neurol. 2018 Jan 1;75(1):9-10. doi: 10.1001/jamaneurol.2017.3299. No abstract available.
Other Identifiers
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E-54022451-050.04-19466
Identifier Type: -
Identifier Source: org_study_id