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The prevalence, cost, and impact of stroke in the United States, focusing on the reliability and validity of two assessment tools, the Timed Up and Go Test (TUG) and the Functional Independence Measure (FIM). The document also explores the minimal detectable change (MDC) and the minimal clinically important difference (MCID) for these tests, as well as their correlation with functional outcomes.
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JEHAD ALZYOUD, PT, MSc.
DENTON, TEXAS MAY 2017
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To Almighty God, Allah, for guiding me through this project and its many phases, and for providing me with the strength, patience, and perseverance required despite challenges faced along the way.
To my loving parents, Muhammad and Nofah, whose words of inspiration and encouragement kept my motivation and enthusiasm throughout this journey.
To my wife Jomana, who has been by my side and has provided me with the unyielding support, patience, and encouragement that is so important and needed to complete a project of this magnitude and so much value to my person, I am forever grateful.
To my children, Lazaward, Adam, and Sama … the joy of my life!
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A common impairment following stroke is impaired balance. Many survivors of stroke are non-ambulatory. Using a valid, reliable, and sensitive measurement tool is essential to identifying balance impairment accurately and making informed clinical decisions. Limited studies examined qualities of available sitting balance scales. The purpose of this study was to examine the responsiveness and the predictive validity of the Sitting Balance Scale (SBS) and Function in Sitting Test (FIST), in people in sub-acute rehabilitation settings who have had a stroke. We also aimed to establish the minimal detectable change (MDC) and minimal clinically important differences (MCID) for both scales. We recruited 40 participants with stroke who were tested upon admission and shortly before discharge. The effect size (ES) and the standardized response mean (SRM) were used as indicators of internal responsiveness. Using Pearson’s correlation coefficient, the external responsiveness was tested by examining the association between the difference in scores on the SBS or FIST and the difference in scores on the Barthel Index (BI). Univariate linear regression and the receiver operating characteristic (ROC) curve were used to examine predictive validity. The MDC, 90% confident level (MDC 90 )
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was calculated from the standard error of measurement, while anchor-based and distribution-based approaches were used to establish the values of MCID. Both scales demonstrated sufficient internal (ES & SRM > 1.11) and external responsiveness (r > 0.6). The SBS demonstrated better internal responsive than the FIST. Both scales were equally useful in predicting discharge placement (area under the curve > 0.81). However, the SBS demonstrated better predictive power in predicting functional level than the FIST (SBS, R^2 = 0.53; FIST, R^2 = 0.43). Both scales failed to predict length of stay. The MDC 90 values were estimated for the SBS and the FIST to be, 2.32 and 3.9 respectively. Therefore, when a change in score between two measurement occasions exceeds 2.32 on the SBS or 3.9 on the FIST, clinicians can be 90% confident in interpreting the change as error free. We established the MCID for both scales as follows: the SBS, 5 points; the FIST, 6 points. The established MDCs and MCIDs may help clinicians to interpret the change in performance and verify treatment effects after stroke rehabilitation. The results of this study support the usefulness of two well-designed sitting balance tools in people following a stroke. Using these tools will help clinicians effectively address sitting balance during early rehabilitation phases. As supported by this study, restoring sitting balance will help to improve a patient’s functional level at discharge. Patients with sufficient functional level are likely to be discharged home, rather than to long-term care.
- Conclusion Measuring sitting balance in clinical settings. Error! Bookmark not defined. .............................. xi
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A stroke affects brain structures, the brain’s biochemical and electrical capacities, causing symptoms such as paralysis, muscle weakness, poor coordination, visual problems, and sensory impairment that may directly or indirectly affect the patient’s balance abilities. According to World Health Organization estimates, neurological disorders and their direct consequences have affected about one billion people globally (World Health Organization, 2006). Stroke, representing 55% of all neurological disorders, is a leading cause of disability and the fourth leading cause of death in the United States (Towfighi & Saver, 2011); it is a pervasive health issue in the United States, affecting 795,000 persons a year (Roger et al., 2012). By a compilation of medical bills, health care services, and time off work, stroke costs in the United States are approximately $36.5 billion every year (Roger et al., 2012). A common impairment following stroke is impaired balance. Balance is defined as the ability to maintain the position within the limits of stability or base of support (Shumway-Cook, Anson, & Haller, 1988). Balance can be maintained through coordination of three sensory input systems (vestibular, somatosensory, and visual), integration of sensory input, and a healthy motor system (musculoskeletal system) that is able to act according to the plan developed during central processing. Regardless of the
home. Restoring sitting balance following stroke is a primary goal during the early stages of rehabilitation (Nieuwboer, Feys, Weerdt, Nuyens, & Corte, 1995). Therefore, assessing patients’ sitting balance is important clinical practice. The available sitting balance scales are relatively new, and only a few studies have been conducted to investigate their psychometric properties. Two recently developed sitting balance assessments are the Sitting Balance Scale (SBS) and the Function In Sitting Scale (FIST). To date, limited studies have examined the responsiveness and predictive validity of the SBS and FIST. One study examined the responsiveness and the minimally clinically importance difference (MCID) of the FIST in inpatient rehabilitation settings across a wide variety of diagnoses (Gorman, Harro, Platko, & Greenwald, 2014). However, the predictive validity of both scales; and the responsiveness, minimal detectable change (MDC) and the MCID of the SBS have not been established. This study is the first to investigate clinically important features of two well-designed, reliable, and easy to administer sitting balance scales in individuals who have suffered a stroke. Unlike Gorman’s study, the current study focused exclusively on patients with stroke and was conducted in post-acute rehabilitation facilities where major therapy impact occurs. Tracking true changes in patients’ abilities throughout the rehabilitation program is vital for clinicians, patients, and patients’ families. Determining the responsiveness and calculating the MDC and MCID may help clinicians provide the most effective intervention and decrease patients’ risk of falling. Furthermore, all parties are interested in discussing the potential functional outcome and the level of independence a patient might reach. Such outcomes may be predicted by looking at
earlier performance on other measures. In this study, the ability of the two sitting balance scales to predict level of independence and functional mobility was examined. Purpose of the Study The primary purpose of the study was to examine responsiveness and predictive validity of scores on two sitting balance scales, the SBS and FIST, in people receiving rehabilitation in skilled nursing facilities who have had a stroke. In addition, the MDC and MCID of the two scales were estimated as a second purpose. Research Questions The following research questions were addressed in this study:
Limitations The following were limitations of this study:
these patients’ sitting balance is an important part of their rehabilitation program. Because there is no gold standard for assessing sitting balance as of this date, the available sitting balance scales have been developed only recently, and limited studies have been carried out to investigate their psychometric properties in people who have had a stroke and other neurologic diagnoses. This is the first study to compare important psychometric properties of two sitting balance scales in people with stroke in post-acute rehabilitation settings. The study’s results may guide clinicians to use the most appropriate tool when assessing sitting balance in people who have had a stroke. The results may also provide clinicians and researchers with useful information about the two sitting balance scales so these tools can be confidently used in both daily practice and research.
quantify impairment of body structure or function, methodical studies are nonexperimental in nature and utilize longitudinal (change over time) or transversal (specific point of time) approaches. An example of longitudinal approach is testing for reliability of a measure by repeating the test after a period of time to ensure consistency of that measure. In contrast, testing the agreement between a newly designed measure and the best available measure (gold standard) is an example of transversal (cross- sectional) study. Information from methodical studies is essential, allowing clinicians to choose tools that best show the effectiveness of their services. The ultimate goal of methodological studies is to determine the psychometric properties of one or more measures. Psychometric Properties Psychometric properties are quantifiable qualities that relate to data collected on a test or measurement tool to determine the statistical strength of that tool in measuring the construct of interest. Reliability and validity are the fundamental components of psychometric properties (Karanicolas et al., 2009). A tool must be valid, reliable, and sensitive to help clinicians assess and track changes over time. An assessment tool also assists clinicians in making recommendations regarding their patients’ rehabilitation program and discharge plan and may predict functional improvement. Newly developed tools are subject to statistical analysis to ensure their ability to accurately measure what they are intended to measure. A measurement tool cannot be recommended confidently without well-established psychometric properties. In this section, a description and the significance of the main psychometric properties will be provided.
Reliability Reliability refers to the ability to approximate the essential inconsistency of a condition, as well as the error attributable to the tester and the measurement tool (Portney & Watkins, 2015). For a test to be reliable, consistent results (less error) should be collected each time the test is administered by one rater (intra-rater reliability), different raters (inter-rater reliability), or over multiple instances of testing (test-retest reliability). In reality, it is rare to find absolute consistency in testing measures. Therefore, the focus of reliability testing is to evaluate the effects of inconsistency on the accuracy of a test. In fact, a wide variety of factors lead to inconsistency (source of errors). These factors include but are not limited to; the characteristics of the individual being tested (e.g., emotional status), testing environment and circumstances (e.g., instructions clarity, race of examiner), and chance influence (e.g., luck in guessing an answer). These factors are also known as errors in measurement. On the other hand, the true score involves the elements of the construct repeatedly being measured. The observed score contains both the true score and the measurement error, whereas the true score is the feature that persists over numerous measurement occasions in the absence of error. The intention in calculating the reliability of a measurement tool is to examine how much of the scores’ variability can be attributed to errors in measurement and, as a result, the variability in the true scores (Davidshofer & Murphy, 2005). Reliability is often assessed using the intraclass correlation coefficient (ICC). Typically, an ICC of 0.75 or more is considered excellent reliability in rehabilitation research. A tool must be valid to be used confidently across clinical setting. However, reliability is a “prerequisite” for validity, which means a