Abstract
Purpose
Since fear of falling may be one of the main problems in people with Parkinson's disease (PD), its assessment with valid tools is necessary in both drug phases. This study was carried out to investigate the psychometric attributes of the Fall Efficacy Scale-International (FES-I) in people with PD, both in On and Off phases.
Methods
One hundred twenty-four patients with PD (mean age ± standard deviation, 60.33 ± 12.59 years) were assessed with the FES-I, both in On- and Off-drug phases. Dimensionality, internal consistency, and test-retest reliability were, respectively, explored by means of factor analysis, Cronbach's alpha, and Intraclass Correlation Coefficient. Convergent validity of FES-I was established with Visual Analog Scale-Fear of Falling, Berg Balance Scale, and Functional Reach Test. Parkinson's Disease Questionnaire-39 and Unified Parkinson Disease Rating Scale-Activities of Daily Living were also applied. Discriminative validity was tested between patients with and without a history of falling.
Results
Factor analysis showed two factors for On- and one factor for Off-drug phase. Internal consistency (α = 0.96, On phase; 0.98, Off phase) and test-retest reliability (0.94; 0.91) were satisfactory in both drug phases. There was a moderate/high correlation (rS = |0.50–0.70|) between FES-I and Visual Analog Scale-Fear of Falling, Berg Balance Scale, and Functional Reach Test. Parkinson's Disease Questionnaire-39 and Unified Parkinson Disease Rating Scale-Activities of Daily Living were achieved in both drug phases too. The sensitivity of FES-I to discriminate Parkinson's disease with and without falls showed moderate effect size in both phases.
Conclusion
This study verified that FES-I is unidimensional, reliable, and valid to measure the Fear of Falling during On- and Off-drug phases in people with PD.
1. Introduction
Fear of falling (FOF) in Parkinson's disease (PD) is known to be a common problem affecting about 45 to 68 percent in this population [1]. FOF is defined as a reduction in certainty in doing activities without falling (loss of self-efficacy) [2]. It may not cause disorder in daily-life by itself, but the avoidance of doing daily activities, reduction in the amount of physical activities, and increase in the risk of falling are among its serious consequences [3, 4]. In addition, the psychological impact of FOF can increase the patients' social isolation [5]. The detrimental effect of FOF on the quality of life of individuals prompts to consider this disorder an important problem requiring monitoring and treatment [6, 7].
Levodopa is the main gold standard treatment of PD and can be beneficial for almost all people with PD. However, as the disease progresses, continuous use of the drug can lead to a series of motor complications (motor fluctuations and dyskinesia). Motor fluctuations refer to oscillations between two drug phases called “On” (when the motor symptoms are controlled by the medication) and “Off” (when the motor symptoms reemerge uncontrolled by the medication) [8, 9]. Various studies have examined the effects of motor fluctuations in both drug phases on various performances such as balance and falling in patients who develop this complication. It has been shown that reducing the amount of levodopa (reaching to Off-drug phase) may cause stride time variability and increase the intensity of fear of falling and subsequent falling, which could influence results in Off state [10–12].
Several instruments have been designed to assess the fear of falling while doing daily activities [13–15]. Among these scales, Activity Balance Confidence (ABC), Fall Efficacy Scale (FES), Survey of Activities and Fear of Falling in the Elderly (SAFE), and Fall Efficacy Scale-International (FES-I) can be mentioned valid and reliable in PD during On-drug phase. The ABC scale measures the level of balance confidence while doing 16 activities without falling. ABC scale has been used widely although it contains items (such as icy pavements) that can be culturally not applicable in all populations. The FES is a well-validated and short scale that contains 10 items and measures the level of concern for falling during specific daily activities. Unfortunately, this scale does not consider social activities [16]. The SAFE scale consists of 17 items that measure the individual's avoidance of a series of activities. The main weakness of this scale is the length that may turn it impractical in some sitting [17]. One of other tools is the Fall Efficacy Scale-International (FES-I), an instrument designed by Yardley et al. in 2005. This 16-item scale has appropriate psychometric properties in elder population to measure the extent of concern caused by falling at the time of doing daily activities [18]. This scale has also been studied in people with stroke, MS, osteoporosis, and dizziness and postmenopausal women [19–22]. It was hypothesized that FES-I would be strongly correlated with scales estimating balance and would show moderate to high association with disability measures. Previous studies for dimensionality of FES-I have reported two factors (indoor and outdoor activities) in other populations [18, 22–24]. Also, with a cut-off point of 21 in FES-I total score, subjects could be divided to two groups of high and low level of fear of falling [25].
Recent studies investigated the test-retest reliability and the ability of the FES-I (and other tools for measuring FOF) for detecting PD patients with falling records during the “On” phase [26, 27]. Nevertheless, a reliable and valid instrument is required to show the extent of changes in rehabilitation and drug treatments in both drug phases [12]. While most studies in PD population have been conducted to investigate the psychometric properties of the assessment tools in “On” phase, it is unknown whether changes in the motor symptoms of patients during the “Off” phase alter the psychometric properties of the tools. Therefore, we aimed to investigate the psychometric properties (such as acceptability, dimensionality, internal consistency, test-retest reliability, and convergent and discriminative validity) of the FES-I in people with PD during both “On-” and “Off-”drug phases.
2. Methods
2.1. Subjects
One hundred twenty-four people with PD referred to movement disorder clinic in Rasoul Akram Hospital were included. Inclusion criteria were diagnosis of PD based on the UK brain bank criteria [28], fluency in Persian language, absence of evident cognitive problem (Minimal Mental Status Examination >21) [29], lack of other neurologic and orthopedic diseases (such as stroke, severe arthritis, lower limb fracture, etc.), and fixed dose of medication use (Levodopa and other dopamine agonists) until the time of retest.
All subjects signed the informed consent to take part in the project. The study protocol was approved by the ethics committee of the Student Research Committee in Iran University of Medical Sciences.
2.2. Assessments
The Persian version of the FES-I has been previously shown to have adequate reliability and validity in Iranian elder population [30, 31]. FES-I has 16 items that assess persons concern about falling during daily activities. Every item is scored from 0 to 4 and the maximum total score of the scale is 64, a figure representing person's fear of falling while doing activity [18].
In order to assess the convergent validity of the FES-I in both “On-” and “Off-”drug phases, we also assessed other PD disturbances relevant to falling, namely, balance, quality of life, and activities of daily living. For this purpose, the following assessments with random order were applied: Visual Analog Scale-Fear of Falling (VAS-FOF), Berg Balance Scale (BBS), Functional Reach Test (FRT), Parkinson's Disease Questionnaire-39 (PDQ-39), and Unified Parkinson Disease Rating Scale-Activities of Daily Living (UPDRS-ADL).
The VAS-FOF is a numerical scale on which elder individuals score their fear of falling in the range 0 to 10. In this scale 10 represents extreme fear of falling [32].
The BBS has proper reliability and validity in PD. This 14-item tool is designed to measure functional balance. The total score of BBS ranges from 0 to 56, and greater scores indicate better balance [33].
The FRT is used to screen persons for falling risk and to measure anteroposterior stability in PD [34]. Each subject performed 3 test trials and the average of these trials is calculated as FRT score. The persons with better functional balance receive higher score [35].
The PDQ-39 was designed to measure Parkinson's patient's quality of life. PDQ-39 consists of 8 domains (movement, daily-living activities, well-being, motivation, social support, cognition, communication, and physical discomfort). Items are scored in the range 0–4, and total scores for domains are calculated as percentage on the maximum possible score of their corresponding items, whereas the PDQ-39 summary index is the mean score of the eight domains. The lower the score, the better the quality of life [36].
The UPDRS-ADL section is commonly used to evaluate the ability of patients for doing daily-living activities. This UPDRS subscale consists of 13 items, with a total score of 0 to 52. Higher scores indicate higher disability [37].
Hoehn and Yahr (HY) scale was designed to determine the level of disease progression in people with Parkinson's. Based on this scale, the severity of disease is divided into 5 levels. At the first level, the condition is normal, and at the last level, people are wheelchair bound [38].
2.3. Procedures
Patients were assessed by an experienced occupational therapist through face to face interview using Persian version of the FES-I, in Off-drug phase (12 hours after taking the last dose of Levodopa and before taking the first morning dose [12]) and in On-drug phase (1 hour after taking Levodopa at first morning dose [12]). All assessments were applied during On- and Off-drug phases.
The history of falling in the last 6 months was recorded by interviewing with people with PD. Accordingly, individuals were categorized into two groups with and without history of falling. To evaluate reliability of test-retest, subjects were studied in second session (average interval, 10 days) by the same occupational therapist at the same conditions of first session.
2.4. Data Analysis
Normal distribution of data was tested using Shapiro–Francia test [39]. Apart descriptive statistics (mean, standard deviation, and percentage) the following statistics were used.
Acceptability was determined by floor and ceiling effects (percentages), with ≤15% values considered acceptable [40]. The range of skewness deemed acceptable was +1 to −1 [41].
Exploratory factor analysis (EFA) with varimax rotation was used to investigate the construct validity and dimensionality of FES-I. Explained variance of dimension with Eigenvalues of greater 1 was considered [42].
Internal consistency was determined through Cronbach's alpha, with a value >0.70 considered the minimum acceptable value [43]. Interitem and corrected item-total correlations were also calculated, with minimal threshold values 0.20 [44] and 0.30 [45] deemed acceptable, respectively.
Test-retest reliability of the FES-I total score was estimated by Intraclass Correlation Coefficient (ICC), two-way, and single measure, with 95% confidence interval. ICC values higher than 0.70 represent acceptable reliability [46]. FES-I precision was estimated through its Standard Error of Measurement (SEM = SDpooled ∗ ). SEM values <1/2 SDpooled are considered acceptable [47].
FES-I convergent validity was explored by correlation with other measures (VAS-FOF, BBS, FRT, PDQ-39 (Domain “Mobility”), and UPDRS-ADL), using Spearman rank correlation coefficient. Correlation values higher than 0.50, between 0.35 and 0.50 and less than 0.35 were considered strong, moderate, and weak correlations, respectively [48]. It was hypothesized that FES-I would be strongly correlated with scales for estimating balance, and would show moderate to high association with disability measures.
Discriminative validity between two different groups (PD patients with and without history of falling during previous 6 months) was determined by Mann–Whitney test and Cohen's d effect size (differences of means divided by baseline pooled standard deviation). Magnitudes of effect size 0.2, 0.5, and 0.8 reflect small, moderate, and high separation power, respectively [49]. It was expected a moderate to highly significant difference of the FES-I total score between fallers and nonfallers.
Wilcoxon signed-rank test was applied to compare the scale scores between the two drug phases (significant level, p < 0.05) [50].
3. Results
The mean (±SD) age was 60.33 ± 12.59 years and disease duration was 6.66 ± 5.51 (Table 1). Thirty-four out of the 124 patients (27%) were Hoehn and Yahr (HY) stage 1; 51 patients (40.5%) in stage 2; 39 (31%) in stage 3.
Table 1.
Variables | Mean (±SD) |
---|---|
Age (year) | 60.33 (±12.59) |
Time since diagnosis (year) | 6.66 (±5.51) |
Mini mental status examination (score) | 23.90 (±2.75) |
Variables | Frequency (%) |
Sex (male) | 90 (72.58%) |
Current medications | |
Levodopa | 101 (81.45%) |
Dopamine agonists | 22 (17.74%) |
MAOB (monoamine oxidase enzyme-B) inhibitor | 4 (3.22%) |
Anticholinergics | 15 (12.09%) |
COMT (catechol-O-methyltransferase enzyme) inhibitor | 10 (8.06%) |
Affected side | |
Right | 65 (52.41%) |
Left | 59 (47.58%) |
History of falling (past six months) | |
No | 71 (57.3%) |
Yes | 53 (42.7%) |
Shapiro–Francia test showed nonnormal distribution of data, including the total score of the FES-I. Total FES-I scores were 27.34 and 33.38 for On- and Off-drug phases, respectively (Table 2). Fifty-three patients (42.7%) had record of falling (had history of falling during previous six months), with mean ± SD FES-I scores of 31.56 ± 10.80 and 37.81 ± 15.29 for On- and Off-drug phases, respectively, for this group.
Table 2.
Drug phase | Mean (±SD) | Range | Floor effect | Ceiling effect | Skewness | SEM | Cronbach's α | ICC (test-retest) (95% IC) |
---|---|---|---|---|---|---|---|---|
On | 27.34 (11.32) | 16–64 | 34.67% | 1.61% | 1.00 | 2.77 | 0.96 | 0.94 (0.90–0.96) |
Off | 33.38 (15.41) | 16–64 | 21.77% | 7.25% | 0.64 | 4.62 | 0.98 | 0.91 (0.86–0.94) |
SEM: standard error of measurement. 95% IC: 95% lower and upper confidence bounds for the ICC statistics are given in parentheses.
3.1. Acceptability
The ceiling effect of the FES-I for both drug phases was ≥15%, but floor effect was mildly higher than this threshold (Table 2). The skewness values were in the range −1 to +1 for both On- and Off-drug phases.
3.2. Dimensionality
Exploratory factor analysis showed two factors for On phase and just one factor for Off phase (Kaiser–Meyer–Olkin = 0.91 and 0.95; Bartlett's test of sphericity both p < 0.001) (Table 3). We named the first factor as “Balance and social activities (outdoor)” which is including 8 items (7, 8, 9, 11, 13, 14, 15, and 16) and the second factor as “Basic personal activities (indoor)” which is including the remaining items (1, 2, 3, 4, 5, 6, 10, and 12).
Table 3.
On-drug phase | Off-drug phase | |||
---|---|---|---|---|
Item of FES-I | Component (factor) | Item of FES-I | Component (factor) | |
1 | 2 | 1 | ||
14 | 0.87 | 8 | 0.90 | |
15 | 0.85 | 4 | 0.89 | |
11 | 0.84 | 5 | 0.89 | |
9 | 0.69 | 12 | 0.88 | |
13 | 0.68 | 15 | 0.88 | |
7 | 0.67 | 16 | 0.88 | |
8 | 0.66 | 3 | 0.87 | |
16 | 0.65 | 13 | 0.87 | |
3 | 0.81 | 14 | 0.87 | |
1 | 0.75 | 1 | 0.86 | |
10 | 0.74 | 6 | 0.84 | |
2 | 0.70 | 7 | 0.84 | |
4 | 0.64 | 9 | 0.83 | |
6 | 0.62 | 10 | 0.82 | |
5 | 0.60 | 11 | 0.82 | |
12 | 0.59 | 2 | 0.80 |
1: cleaning the house. 2: getting dressed or undressed. 3: preparing simple meals. 4: taking a bath or shower. 5: going to the shop. 6: getting in or out of a chair. 7: going up or down stair. 8: walking around in the neighborhood. 9: reaching for something above your head or on the ground. 10: going to answer the telephone before it stops ringing. 11: walking on a slippery surface. 12: visiting a friend or relative. 13: walking in a place with crowds. 14: walking on an uneven surface. 15: walking up or down a slope. 16: going out to a social event.
3.3. Internal Consistency
Cronbach's alpha index of the FES-I was 0.96 for On- and 0.98 for Off-drug phases. Interitem correlations ranged in On state from 0.40 (Item 10 with items 14, 15, and 16) to 0.97 (Item 1 with item 7) and, in Off state, from 0.58 (Item 10 with 11) to 0.87 (Item 12 with item 16). Item homogeneity index was 0.59 for the On and 0.72 for the Off phase.
3.4. Reliability
In regard to the test-retest reliability for total FES-I scores, ICC values were 0.94 (CI 95% = 0.90–0.96), and 0.91 (CI 95% = 0.86–0.94) for On- and Off-drug phases, respectively. SEM calculation on these ICCs was 2.77 and 4.62, respectively, values clearly lower than 1/2 SD at first application (5.66 in On state and 7.71 in Off state).
3.5. Convergent Validity
This study revealed strong relationship between total FES-I score and VAS-FOF (r = 0.50–0.54, p < 0.001), tests for functional movement and its quality (BBS, FRT, PDQ-39 (Mobility) (r = 0.51–0.76, p < 0.001), and independency in daily activities (UPDRS-ADL) (r = 0.67, p < 0.001) in both On- and Off-drug phases (Table 4).
Table 4.
Drug phase | Scales | VAS-FOF | BBS | FRT | PDQ-39 (mobility) | UPDRS-ADL |
---|---|---|---|---|---|---|
On | FES-I | 0.54 | −0.71 | −0.51 | 0.65 | 0.59 |
Off | 0.50 | −0.70 | −0.56 | 0.71 | 0.67 |
FES-I: Fall Efficacy Scale-International. VAS-FOF: Visual Analog Scale-Fear of Fall. BBS: Berg Balance Scale. FRT: Functional Reach Test. PDQ-39: Parkinson Disease Questionnaire-39-Domain “Mobility”. UPDRS-ADL: Unified Parkinson's disease Rating Scale-Activities of Daily Living. All coefficients, p < 0.001.
3.6. Discriminative Validity
The difference in FES-I scores for Fallers vs Nonfallers in On ((meanF ± SD) 31.56 ± 10.80 vs 4.19 ± 10.72) and in Off, Fallers vs Nonfallers (37.81 ± 15.29 vs 30.43 ± 14.86) were statistically significant (Mann–Whithney test, p < 0.001 and p ≤ 0.005, respectively). Effect size for the FES-I in discriminating between Fallers and Nonfallers was 0.68 (On drug phase) and 0.48 (Off-drug phase).
For the complete sample of patients in the study, FES-I total score was (mean ± SD) 27.34 ± 11.32 in On and 33.38 ± 15.41 in Off state (Wilcoxon test, p ≤ 0.001).
4. Discussion
This study was carried out to assess the main clinimetric properties of FES-I for both drug phases, On and Off, in subjects with PD. Our findings revealed that FES-I has high reliability and acceptable convergent (convergent and discriminant) validity to measure fear of falling in PD during both On- and Off-drug phases.
In the FES-I (both On- and Off-drug phases), item 11 (Walking on a slippery surface) and item 14 (Walking on an uneven surface) got the highest mean score, indicating a greater degree of difficulty, according to past studies [51, 52].
Based on our test-retest results, FES-I total score was very stable in both drug phases and similar to previous report in PD populations in which is done only in On-drug phase (ICC = 0.92) [27]. Regarding the ICC obtained in the mentioned previous report, the samples were the same in size and PD duration, but in our data were included “On-” and “Off-”drug phases separately.
SEM values obtained for FES-I were ≤30% of the standard deviation at the first application. SEM value in On-drug phase is close to that obtained in Jonasson's study (2017) (SEM = 3.4) [27].
In factor analysis of FES-I total score for the drug on-phase, similar to previous studies, two dimensions have been shown (the first factor dominated by basic and instrumental activities of daily living and the second factor dominated by physically demanding outdoor activities) [18, 53]. The results factor analysis in the Off-drug phase showed unidimensionality of this scale. Possibly, patients with PD and mobility or stability problems are concerned about falling during daily activities (home or outdoor), a fact that should be considered for optimizing the management of those PD patients.
A strong correlation between total FES-I score and VAS-FOF revealed that it is reasonable to use either of these tools to measure fear of falling in both drug phases. In VAS-FOF, fear of falling is generally evaluated and can be faster. In contrast, with FES-I, fear of falling in 16 activities can be estimated with more detail by spending more time. Although both scales are used to assess the fear of falling and have a strong relationship, they also have advantages and disadvantages. FES-I score showed strong-association with other scales measuring balance (BBS, FRT, PDQ-39 (Mobility)) in both drug phases (Table 4). This finding indicates the close relationships between fear of falling and disorders of global mobility in people with Parkinson's disease that can be due to the similarities between the evaluated activities on these scales, such as up and down steps and reaching. Strong correlation between FES-I total score and scores of scales measuring independency in daily-living activities (UPDRS-ADL) showed that fear of falling is associated with restriction for performing daily activities in individuals with PD and how this factor can contribute to their functional disability and quality of life deterioration.
Findings from a previous study [27] revealed that FES-I score in On-drug phase was able to distinguish PD subjects with and without history of falling, which is aligned with our results for both drug phases. In addition, we showed that FES-I can discriminate the two drug phases, the ability with potential application for future studies to assess treatment response in PD.
Since most of the participants in our study were in early stage based on the modified Hoehn and Yahr staging, results showed a low score of the FES-I and mild floor effect of this score in both drug phases, which is in contrast to Jonasson's study (2014) in this population (in this study, PD patients were older and at higher level on modified Hoehn and Yahr.) [26]. Assessment in Off-drug phase is one of the major issues that have always been used to provide more accurate medication and evaluation clinical interventions in Parkinson's disease [10]. Examination of psychometric properties of this scale in the Off-drug phase for use in research and clinics is another strength of this study. Limitations of this study are the lack of evaluation of Levodopa dose equivalence and identification of patients with motor fluctuations. Also, using more appropriate tools for PD (e.g., the Fullerton Advanced Balance Scale or the Mini-BESTest) to analyze the FES-I convergent validity, carrying out confirmatory factor analysis (CFA) for dimensionality, and higher size of the samples are suggested for future studies addressing the properties of the FES-I in PD patients with fluctuations.
5. Conclusion
In conclusion, our study suggests that the FES-I is a reliable and valid scale for measuring fear of falling in individuals with PD. Also, it is an appropriate scale for clinicians and researchers to use during the On- and Off-drug phases.
Acknowledgments
The authors thank the patients and their families for making this study possible through their participation.
Data Availability
The data used to support the findings of this study are included within the article.
Conflicts of Interest
The authors declare that there are no conflicts of interest.
References
- 1.Paul S. S., Thackeray A., Duncan R. P., et al. Two-year trajectory of fall risk in people with parkinson disease: a latent class analysis. Archives of Physical Medicine and Rehabilitation. 2016;97(3):372–379. doi: 10.1016/j.apmr.2015.10.105. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Rahman S., Griffin H. J., Quinn N. P., Jahanshahi M. On the nature of fear of falling in parkinson’s disease. Behavioural Neurology. 2011;24(3):219–228. doi: 10.1155/2011/274539. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Bryant M. S., Rintala D. H., Hou J.-G., Protas E. J. Relationship of falls and fear of falling to activity limitations and physical inactivity in parkinson’s disease. Journal of Aging and Physical Activity. 2015;23(2):187–193. doi: 10.1123/japa.2013-0244. [DOI] [PubMed] [Google Scholar]
- 4.Kader M., Iwarsson S., Odin P., Nilsson M. H. Fall-related activity avoidance in relation to a history of falls or near falls, fear of falling and disease severity in people with parkinson’s disease. BMC Neurology. 2016;16(1):p. 84. doi: 10.1186/s12883-016-0612-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Franzén E., Conradsson D., Hagströmer M., Nilsson M. H. Depressive symptoms associated with concerns about falling in parkinson’s disease. Brain and Behavior. 2016;6(10) doi: 10.1002/brb3.524.e00524 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Canning C. G., Sherrington C., Lord S. R., et al. Exercise for falls prevention in Parkinson disease: a randomized controlled trial. Neurology. 2014;84(3):304–312. doi: 10.1212/wnl.0000000000001155. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Bloem B. R., de Vries N. M., Ebersbach G. Nonpharmacological treatments for patients with parkinson’s disease. Movement Disorders. 2015;30(11):1504–1520. doi: 10.1002/mds.26363. [DOI] [PubMed] [Google Scholar]
- 8.Rodríguez-Molinero A., Samà A., Pérez-López C., et al. Analysis of correlation between an accelerometer-based algorithm for detecting parkinsonian gait and UPDrs subscales. Frontiers in Neurology. 2017;8:p. 431. doi: 10.3389/fneur.2017.00604. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Ahlskog J. E., Muenter M. D. Frequency of levodopa-related dyskinesias and motor fluctuations as estimated from the cumulative literature. Movement Disorders. 2001;16(3):448–458. doi: 10.1002/mds.1090. [DOI] [PubMed] [Google Scholar]
- 10.Foreman K. B., Addison O., Kim H. S., Dibble L. E. Testing balance and fall risk in persons with parkinson disease, an argument for ecologically valid testing. Parkinsonism and Related Disorders. 2011;17(3):166–171. doi: 10.1016/j.parkreldis.2010.12.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Galli M., Kleiner A., Gaglione M., et al. Timed up and go test and wearable inertial sensor: a new combining tool to assess change in subject with parkinson’s disease after automated mechanical peripheral stimulation treatment. International Journal of Engineering and Innovative Technology. 2015;4:155–163. [Google Scholar]
- 12.Morris S., Morris M. E., Iansek R. Reliability of measurements obtained with the timed “up and go” test in people with parkinson disease. Physical Therapy. 2001;81(2):810–818. doi: 10.1093/ptj/81.2.810. [DOI] [PubMed] [Google Scholar]
- 13.Almeida L. R. S., Valenca G. T., Negreiros N. N., Pinto E. B., Oliveira-Filho J. Comparison of self-report and performance-based balance measures for predicting recurrent falls in people with parkinson disease: cohort study. Physical Therapy. 2016;96(7):1074–1084. doi: 10.2522/ptj.20150168. [DOI] [PubMed] [Google Scholar]
- 14.Perell K. L., Nelson A., Goldman R. L., Luther S. L., Prieto-Lewis N., Rubenstein L. Z. Fall risk assessment measures: an analytic review. Journals of Gerontology Series A: Biological Sciences and Medical Sciences. 2001;56(12):761–766. doi: 10.1093/gerona/56.12.m761. [DOI] [PubMed] [Google Scholar]
- 15.da Costa-Dias M. J. M., Lopes Ferreira P. Fall risk assessment tools. Revista de Enfermagem Referência. 2014;4(2) [Google Scholar]
- 16.Bloem B. R., Marinus J., Almeida Q., et al. Measurement instruments to assess posture, gait, and balance in parkinson’s disease: critique and recommendations. Movement Disorders. 2016;31(9):1342–1355. doi: 10.1002/mds.26572. [DOI] [PubMed] [Google Scholar]
- 17.Schrag E. S., Wetherell J. L., Merz C. C., Petkus A. J., Malcarne V. L., Lenze E. J. A new measure of fear of falling: psychometric properties of the fear of falling questionnaire revised (FFQ-R) International Psychogeriatrics. 2014;27(7):1121–1133. doi: 10.1017/s1041610214001434. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Yardley L., Beyer N., Hauer K., Kempen G., Piot-Ziegler C., Todd C. Development and initial validation of the falls efficacy scale-international (FES-I) Age and Ageing. 2005;34(6):614–619. doi: 10.1093/ageing/afi196. [DOI] [PubMed] [Google Scholar]
- 19.Morgan M. T., Friscia L. A., Whitney S. L., Furman J. M., Sparto P. J. Reliability and validity of the falls efficacy scale-international (FES-I) in individuals with dizziness and imbalance. Otology and Neurotology. 2013;34(6):1104–1108. doi: 10.1097/mao.0b013e318281df5d. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.van Vliet R., Hoang P., Lord S., Gandevia S., Delbaere K. Falls efficacy scale-international: a cross-sectional validation in people with multiple sclerosis. Archives of Physical Medicine and Rehabilitation. 2013;94(5):883–889. doi: 10.1016/j.apmr.2012.10.034. [DOI] [PubMed] [Google Scholar]
- 21.Lomas-Vega R., Hita-Contreras F., Mendoza N., Martínez-Amat A. Cross-cultural adaptation and validation of the falls efficacy scale international in Spanish postmenopausal women. Menopause: The Journal of North American Menopause Society. 2012;19(8):904–908. doi: 10.1097/gme.0b013e3182475f6e. [DOI] [PubMed] [Google Scholar]
- 22.Azad A., Mehraban A. H., Mehrpour M., Mohammadi B. Clinical assessment of fear of falling after stroke: validity, reliability and responsiveness of the persian version of the fall efficacy scale-international. Medical Journal of Islamic Republic of Iran. 2014;28:p. 131. [PMC free article] [PubMed] [Google Scholar]
- 23.Hill H., McMeekin P., Parry S. W. Does the falls efficacy scale international version measure fear of falling: a reassessment of internal validity using a factor analytic approach. Age and Ageing. 2014;43(4):559–562. doi: 10.1093/ageing/afu059. [DOI] [PubMed] [Google Scholar]
- 24.Nordell E., Andreasson M., Gall K., Thorngren K.-G. Evaluating the Swedish version of the falls efficacy scale-international (FES-I) Advances in Physiotherapy. 2009;11(2):81–87. doi: 10.1080/14038190802318986. [DOI] [Google Scholar]
- 25.Delbaere K., Close J. C. T., Mikolaizak A. S., Sachdev P. S., Brodaty H., Lord S. R. The falls efficacy scale international (FES-I). A comprehensive longitudinal validation study. Age and Ageing. 2010;39(2):210–216. doi: 10.1093/ageing/afp225. [DOI] [PubMed] [Google Scholar]
- 26.Jonasson S., Nilsson M. H., Lexell J. Reliability of the original and short versions of the falls efficacy scale-international (FES-I) in people with parkinson’s disease. Proceedings of ISOQOL 21st Annual Conference; October 2014; Berlin, Germany. Springer; pp. 74–75. [Google Scholar]
- 27.Jonasson S. B., Nilsson M. H., Lexell J. Psychometric properties of the original and short versions of the falls efficacy scale-international (FES-I) in people with parkinson’s disease. Health and Quality of Life Outcomes. 2017;15(1):p. 116. doi: 10.1186/s12955-017-0689-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Hughes A. J., Daniel S. E., Kilford L., Lees A. J. Accuracy of clinical diagnosis of idiopathic parkinson’s disease: a clinico-pathological study of 100 cases. Journal of Neurology, Neurosurgery and Psychiatry. 1992;55(3):181–184. doi: 10.1136/jnnp.55.3.181. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Godefroy O., Fickl A., Roussel M., et al. Is the montreal cognitive assessment superior to the mini-mental state examination to detect poststroke cognitive impairment? Stroke. 2011;42(6):1712–1716. doi: 10.1161/strokeaha.110.606277. [DOI] [PubMed] [Google Scholar]
- 30.Baharlouei H., Salavati M., Akhbari B., Mosallanezhad Z., Mazaheri M., Negahban H. Cross-cultural validation of the falls efficacy scale international (FES-I) using self-report and interview-based questionnaires among persian-speaking elderly adults. Archives of Gerontology and Geriatrics. 2013;57(3):339–344. doi: 10.1016/j.archger.2013.06.005. [DOI] [PubMed] [Google Scholar]
- 31.Khajavi D. Validation and reliability of persian version of fall efficacy scale-international (FES-I) in community-dwelling older adults. Iranian Journal of Ageing. 2013;8(2):39–47. [Google Scholar]
- 32.Scheffer A. C., Schuurmans M. J., van Dijk N., van der Hooft T., de Rooij S. E. Psychometric properties of the VAS-FOF, a visual analogue scale for fear of falling in older persons. International Journal Geriatric Psychiatry. 2011;26(3):284–291. doi: 10.1002/gps.2526. [DOI] [PubMed] [Google Scholar]
- 33.Babaei-Ghazani A., Mohammadi H., Shahidi G. A., et al. Reliability and validity of the persian translation of berg balance scale in parkinson disease. Aging Clinical and Experimental Research. 2016;29(5):857–862. doi: 10.1007/s40520-016-0682-7. [DOI] [PubMed] [Google Scholar]
- 34.Behrman A. L., Light K. E., Flynn S. M., Thigpen M. T. Is the functional reach test useful for identifying falls risk among individuals with parkinson’s disease? Archives of Physical Medicine and Rehabilitation. 2002;83(4):538–542. doi: 10.1053/apmr.2002.30934. [DOI] [PubMed] [Google Scholar]
- 35.Duncan P. W., Studenski S., Chandler J., Prescott B. Functional reach: predictive validity in a sample of elderly male veterans. Journal of Gerontology. 1992;47(3):93–98. doi: 10.1093/geronj/47.3.m93. [DOI] [PubMed] [Google Scholar]
- 36.Jenkinson C., Fitzpatrick R., Peto V., Greenhall R., Hyman N. The parkinson’s disease questionnaire (PDQ-39): development and validation of a parkinson’s disease summary index score. Age and Ageing. 1997;26(5):353–357. doi: 10.1093/ageing/26.5.353. [DOI] [PubMed] [Google Scholar]
- 37.Martínez‐Martín P., Gil‐Nagel A., Gracia L. M., Gómez J. B., Martínez‐Sarriés J., Bermejo F. Unified parkinson’s disease rating scale characteristics and structure. Movement Disorders. 1994;9(1):76–83. doi: 10.1002/mds.870090112. [DOI] [PubMed] [Google Scholar]
- 38.Goetz C. G., Poewe W., Rascol O., et al. Movement disorder society task force report on the Hoehn and Yahr staging scale: status and recommendations the movement disorder society task force on rating scales for parkinson’s disease. Movement Disorders. 2004;19(9):1020–1028. doi: 10.1002/mds.20213. [DOI] [PubMed] [Google Scholar]
- 39.Yahr S. S., Wilk M. B. An analysis of variance test for normality (complete samples) Biometrika. 1965;52(3-4):591–611. doi: 10.2307/2333709. [DOI] [Google Scholar]
- 40.McHorney C. A., Tarlov A. R. Individual-patient monitoring in clinical practice: are available health status surveys adequate? Quality of Life Research. 1995;4(4):293–307. doi: 10.1007/bf01593882. [DOI] [PubMed] [Google Scholar]
- 41.Hobart J., Riazi A., Lamping D., Fitzpatrick R., Thompson A. Improving the evaluation of therapeutic interventions in multiple sclerosis: development of a patient-based measure of outcome. Health Technology Assessment (Winchester, England) 2004;8(9) doi: 10.3310/hta8090. [DOI] [PubMed] [Google Scholar]
- 42.Gorsuch R. L. Exploratory factor analysis: its role in item analysis. Journal of Personality Assessment. 1997;68(3):532–560. doi: 10.1207/s15327752jpa6803_5. [DOI] [PubMed] [Google Scholar]
- 43.Lohr K. N. Assessing health status and quality-of-life instruments: attributes and review criteria. Quality of Life Research. 2002;11(3):193–205. doi: 10.1023/a:1015291021312. [DOI] [PubMed] [Google Scholar]
- 44.Piedmont R. L. Encyclopedia of Quality of Life and Well-Being Research. Berlin, Germany: Springer; 2014. Inter-item correlations; pp. 3303–3304. [Google Scholar]
- 45.van der Linden F. A. H., Kragt J., Klein M., Van der Ploeg H., Polman C. Psychometric evaluation of the multiple sclerosis impact scale (MSIS-29) for proxy use. Journal of Neurology, Neurosurgery and Psychiatry. 2005;76(12):1677–1681. doi: 10.1136/jnnp.2005.065227. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Terwee C. B., Bot S. D. M., de Boer M. R., et al. Quality criteria were proposed for measurement properties of health status questionnaires. Journal of Clinical Epidemiology. 2007;60(1):34–42. doi: 10.1016/j.jclinepi.2006.03.012. [DOI] [PubMed] [Google Scholar]
- 47.Norman G., Sloan J., Wyrwich K. Interpretation of changes in health-related quality of life: the remarkable universality of half a standard deviation. Medical Care. 2003;41(5):582–592. doi: 10.1097/00005650-200305000-00004. [DOI] [PubMed] [Google Scholar]
- 48.Feeny D., Farris K., Côté I., Johnson J. A., Tsuyuki R. T., Eng K. A cohort study found the RAND-12 and health utilities index mark 3 demonstrated construct validity in high-risk primary care patients. Journal of Clinical Epidemiology. 2005;58(2):138–141. doi: 10.1016/j.jclinepi.2004.08.005. [DOI] [PubMed] [Google Scholar]
- 49.Cohen J. A power primer. Psychological Bulletin. 1992;112(1):155–159. doi: 10.1037/0033-2909.112.1.155. [DOI] [PubMed] [Google Scholar]
- 50.Gibbons J. D., Chakraborti S. International Encyclopedia of Statistical Science. Berlin, Germany: Springer; 2011. Nonparametric statistical inference; pp. 977–979. [Google Scholar]
- 51.Oates A. R., Van Ooteghem K., Frank J. S., Patla A. E., Horak F. B. Adaptation of gait termination on a slippery surface in parkinson’s disease. Gait and Posture. 2013;37(4):516–520. doi: 10.1016/j.gaitpost.2012.09.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Oates A. R., Frank J. S., Patla A. E., VanOoteghem K., Horak F. B. Control of dynamic stability during gait termination on a slippery surface in parkinson’s disease. Movement Disorders. 2008;23(14):1977–1983. doi: 10.1002/mds.22091. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Camargos F. F. O., Dias R. C., Dias J. M. D., Freire M. T. F. Adaptação transcultural e avaliação das propriedades psicométricas da falls efficacy scale-international em idosos Brasileiros (FES-I-BRASIL) Revista Brasileira de Fisioterapia. 2010;14(3):237–243. doi: 10.1590/s1413-35552010000300010. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data used to support the findings of this study are included within the article.