Abstract
Background:
Falls are a common challenge for people with Parkinson’s disease (PwPD), driven by balance impairments and misaligned perceptions of balance abilities.
Objective:
This study investigated the replicability and generalizability of the relationship between balance ability and perception discordance and fall risk.
Methods:
Using baseline data from 2 clinical trials involving 171 PwPD, discordance was calculated using the Activities Specific Balance Confidence Scale and Timed Up and Go (TUG) or the Mini Balance Evaluation System’s Test (MiniBEST).
Results:
Findings supported the replicability of discordance as a predictor of fall risk, with results consistent across measures. While TUG-derived discordance was statistically significant, MiniBEST-derived discordance showed generalizability without statistical inferiority.
Conclusion:
These results emphasize the relevance of balance perception and its misalignment with ability as fall risk predictors.
Introduction
Falls are common among people with Parkinson’s disease (PwPD) and become more frequent as PD progresses. 1 Beyond PD-related balance declines, perception of one’s balance abilities also contributes to falls.2-4 Recently, the interaction between balance ability and perception was described and a novel metric was proposed to quantify their degree of disagreement.4-6 This metric, termed discordance, was shown to be uniquely related to faller status among PwPD.
Our prior study offers initial evidence that discordance is related to fall risk for PwPD such that one’s odds of being a faller increased as confidence decreased. 6 This analysis was run on a heterogeneous sample of 244 PwPD, collected at several institutions across the United States. Replication of these results in a distinct sample is necessary to establish the replicability of these findings. Additionally, the previous analysis utilized the Timed Up and Go (TUG) to quantify balance performance. Although the TUG is a quick and functionally relevant outcome measure, 7 use of more balance-centric metric, such as the Mini Balance Evaluation Systems Test (MiniBEST) for the quantification of discordance would make sense conceptually. Evidence that discordance derived using the MiniBEST is related to falls would increase the generalizability and robustness of previous results concerning this relationship, showing the potential for other balance metrics being used in the quantification of discordance. To this end the purpose of this study was to further investigate the replicability and generalizability of the relationship between discordance and falls in PwPD. Specifically, the first aim of this study was to establish the replicability of previously reported results (both the size and direction of the effect). The second aim was to determine the generalizability of these results by assessing whether the utilization of a balance domain specific measure (MiniBEST) which more closely aligns with the perceptual measure (Activities Specific Balance Confidence Scale [ABC]), influences the discordance to falls relationship. Understanding the relationship between discordance and fall risk may provide novel avenues for mitigation of falls.
Methods
A secondary analysis of baseline data from 2 clinical trials8,9 led by the same investigators consisting of 171 PwPD was conducted with complete data for ABC, TUG, fall status, and MiniBEST. Baseline data utilized data from several participants who were not included in the subsequent trials. Inclusion and exclusion criteria, subsample descriptions, and sample size estimation are detailed in Supplemental Material 1. Importantly, this sample is distinct from that presented in the prior study, 6 however they share several similar qualities, such as diagnosis and disease severity. Data extracted included demographics (age and sex), PD severity (Hoehn & Yahr [HY] and disease duration), perceived balance (ABC), balance (MiniBEST), functional mobility (TUG), and reported falls from the prior 12 months. The MiniBEST was selected because it is a brief tool that assesses multiple balance constructs and was designed for individuals with PD. Participants were classified as fallers if they reported 1 or more falls in the previous 12 months. A description of sample characteristics is presented in Supplemental Material 2.
Discordance was calculated from the difference between the actual and predicted ABC value for each participant. The predicted ABC value is derived from the resulting beta coefficient for each individual’s TUG, with age, disease duration, and sex included as covariates (Supplemental Material 3). The resulting discordance value was then used as the primary independent variable in a logistic regression model with Fall status as the dependent variable and age and disease duration as covariates. The TUG beta coefficient and discordance odds ratio (OR), and their corresponding 95% confidence intervals (CI), were compared to those reported in Longhurst et al. 6 Additionally a receiver operating characteristic (ROC) curve analysis was conducted. All analyses were conducted in RStudio (R version 4.4.0 [2024-04-24]) with α set at .05 (script available on https://osf.io/ngjdh/).
Results
Between Study Participant Characteristics
Participant characteristics were similar to those presented in Longhurst 2024 by age (µ = 69.5 ± 8.1 vs µ = 70.1 ± 6.7), sex (42% female vs 44% female), and ABC (µ = 77.6 ± 19 vs µ = 68.3 ± 18). Disease severity and TUG times could not be compared due to different severity scales used (Movement Disorder Society – Unified Parkinson’s Disease Rating Scale part III vs HY and disease duration) and difference in TUG administration.
Replication of TUG Discordance to Falls
The beta coefficient between z-scored TUG and ABC in Longhurst (2024) was −7.22, CI [−9.73; −4.71] and the corresponding OR between TUG discordance to Falls was 0.98, CI [0.96; 0.99]. The beta coefficient of z-scored TUG and ABC in this sample was −1.75, CI [−2.77; −0.72] The corresponding OR between TUG discordance and falls in this sample was 0.97, 95% CI [0.95; 0.99], P = .001. These results indicate that the observed relationship between TUG and ABC and TUG discordance to falls between Longhurst et al and this sample are similar (Figure 1). The ROC curve analysis revealed that individuals with discordance values less than 0.49 were more likely to be fallers. The model had an accuracy of 68.8% and an area under the curve of 0.695 (Supplemental Material 4).

(A) Plot displaying the distribution and relationship between Activities Specific Balance Confidence Scale (ABC, y-axis) and z-score of Timed Up and Go (TUG, x-axis) with regression line adjusted for age, sex, and disease duration displayed in blue. Regression line displaying the findings from the previous study (Longhurst et al 6 ) overlayed in red. (B) The binomial relationship between probability of being a faller or a non-faller to magnitude of discordance. Density plots on the superior x-axis visualize the distribution of the fall types given the value of discordance with greater confidence (higher perceived balance confidence compared to predicted balance confidence) associated with a greater probability of being a non-faller. The relationship from the previous study (Longhurst et al 6 ) overlayed in red.
Evaluation of MiniBEST Discordance to Falls
The same procedure for calculating TUG discordance was undertaken with the MiniBEST. The relationship between MiniBEST and ABC was 2.1, CI [1.36; 2.81]. The OR between MiniBEST discordance and Falls was 0.97, CI [0.96; 1.0], P = .02 (Figure 2, Supplemental Material 5).

The binomial relationship between probability of being a faller or a non-faller to magnitude of discordance, calculated using the MiniBEST presented in green. Density plots on the superior x-axis visualize the distribution of the fall types given the value of discordance with greater confidence (higher perceived balance confidence compared to predicted balance confidence) associated with a greater probability of being a non-faller. The horizontal dashed line represents the no-information criterion which is equal to 41% given that 70 out of 171 participants in the study were classified as Fallers. The same relationship with discordance calculated using the Timed Up and Go is overlayed in blue.
Discussion
Consistent with previous work, 6 balance ability and perception discordance was uniquely and significantly related to faller status among PwPD (in the TUG derived model) such that those with lower confidence than their ability level suggests had greater odds of being a faller. The replication of previous work (both in terms of effect and direction) in a distinct group, collected in a different country demonstrates the generalizability of this finding, and suggests the importance of discordance for fall risk.5,10
The TUG is a broad and clinically relevant mobility metric. However, other outcomes, such as the MiniBEST offer additional and more balance-specific assessments of mobility. Therefore, to assess the generalizability (application to additional constructs and tools) of discordance, the TUG was replaced by the MiniBEST as a measure of balance ability in the discordance calculations. While the model using MiniBEST derived discordance did not meet the threshold for statistical significance as a predictor of faller status, it was also found to be statistically no worse than using the TUG in the discordance calculations. This indicates that discordance may be more heavily based on balance perception than ability. 5 It also indicates that the discordance-fall risk relationship is generalizable across various measures of balance ability, facilitating greater application to both research and clinical practice. Given these findings, the brevity and simplicity of the TUG make it an idea tool for assessing discordance clinically. Further investigation should be conducted to determine if this same relationship exists with other measures of balance perception and discordance. While further evidence is still needed, the identification of discordance as a fall risk factor has the potential to inform the development and implementation of interventions to reduce falls.
While this analysis revealed notable findings it has limitations that should be considered. Given the retrospective nature of this analysis several potential covariates were not available to be included in the analysis, including freezing of gait, cognition, and a more robust measures of disease severity. These could have had an influence on the relationships observed in these analyses. Additionally, falls were captured via retrospective report which is prone to potential recall bias and may be unreliable; categorization of participants as either fallers or non-fallers was utilized to mitigate this concern.
The current investigation provides evidence supporting the replicability and generalizability of the relationship between discordance and faller status indicating it may be a relevant metric for investigation. Further research should therefore be conducted to better identify potentially modifiable predictors of discordance such as physical activity levels, cognition, and anxiety, amongst others.
Supplemental Material
sj-pdf-1-nnr-10.1177_15459683251335316 – Supplemental material for Discordance Between Balance Ability and Perception and Its Relation to Falls in Parkinson’s Disease: A Replication Analysis
Supplemental material, sj-pdf-1-nnr-10.1177_15459683251335316 for Discordance Between Balance Ability and Perception and Its Relation to Falls in Parkinson’s Disease: A Replication Analysis by Jason K. Longhurst, Andrew Hooyman, Franziska Albrecht, Erika Franzén and Daniel S. Peterson in Neurorehabilitation and Neural Repair
Supplemental Material
sj-pdf-2-nnr-10.1177_15459683251335316 – Supplemental material for Discordance Between Balance Ability and Perception and Its Relation to Falls in Parkinson’s Disease: A Replication Analysis
Supplemental material, sj-pdf-2-nnr-10.1177_15459683251335316 for Discordance Between Balance Ability and Perception and Its Relation to Falls in Parkinson’s Disease: A Replication Analysis by Jason K. Longhurst, Andrew Hooyman, Franziska Albrecht, Erika Franzén and Daniel S. Peterson in Neurorehabilitation and Neural Repair
Supplemental Material
sj-pdf-3-nnr-10.1177_15459683251335316 – Supplemental material for Discordance Between Balance Ability and Perception and Its Relation to Falls in Parkinson’s Disease: A Replication Analysis
Supplemental material, sj-pdf-3-nnr-10.1177_15459683251335316 for Discordance Between Balance Ability and Perception and Its Relation to Falls in Parkinson’s Disease: A Replication Analysis by Jason K. Longhurst, Andrew Hooyman, Franziska Albrecht, Erika Franzén and Daniel S. Peterson in Neurorehabilitation and Neural Repair
Supplemental Material
sj-pdf-4-nnr-10.1177_15459683251335316 – Supplemental material for Discordance Between Balance Ability and Perception and Its Relation to Falls in Parkinson’s Disease: A Replication Analysis
Supplemental material, sj-pdf-4-nnr-10.1177_15459683251335316 for Discordance Between Balance Ability and Perception and Its Relation to Falls in Parkinson’s Disease: A Replication Analysis by Jason K. Longhurst, Andrew Hooyman, Franziska Albrecht, Erika Franzén and Daniel S. Peterson in Neurorehabilitation and Neural Repair
Supplemental Material
sj-pdf-5-nnr-10.1177_15459683251335316 – Supplemental material for Discordance Between Balance Ability and Perception and Its Relation to Falls in Parkinson’s Disease: A Replication Analysis
Supplemental material, sj-pdf-5-nnr-10.1177_15459683251335316 for Discordance Between Balance Ability and Perception and Its Relation to Falls in Parkinson’s Disease: A Replication Analysis by Jason K. Longhurst, Andrew Hooyman, Franziska Albrecht, Erika Franzén and Daniel S. Peterson in Neurorehabilitation and Neural Repair
Footnotes
Author Contributions
Jason K. Longhurst: Conceptualization; Formal analysis; Investigation; Methodology; Project administration; Validation; and Writing—original draft. Andrew Hooyman: Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Project administration; Validation; Visualization; and Writing—review & editing. Franziska Albrecht: Data curation; Formal analysis; Investigation; Methodology; Project administration; Resources; Software; Visualization; and Writing—review & editing. Erika Franzen: Funding acquisition; Methodology; Project administration; Resources; Supervision; and Writing—review & editing. Daniel S. Peterson: Conceptualization; Formal analysis; Investigation; Methodology; Project administration; Supervision; Visualization; and Writing—review & editing.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study is supported by grants from the Swedish Research Council (2022-00636, 2016-01965), the Swedish Parkinson Foundation as well as the Center for Innovative Medicine (CIMED; FoUI-975387 and FoUI-973826), the Regional Agreement on Medical Training and Clinical Research (ALF; RS2021-0855) between Karolinska Institutet and Region Stockholm, and NIH grant No. R25HD105583-03. Further funding was provided by the Augusta and Petrus Hedlunds Stiftelse and Gun und Bertil Stohnes Stiftelse.
Supplementary material for this article is available on the Neurorehabilitation & Neural Repair website along with the online version of this article.
References
Supplementary Material
Please find the following supplemental material available below.
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