Thirty-five of the 53 subjects demonstrated differences in BBS scores between the first and second trials: 29 scored lower on the BBS while wearing the shoulder immobilizer, whereas only 6 scored lower on the BBS without the immobilizer. The Wilcoxon signed-ranks test (Table 3) indicated a significant difference between paired observations (z = −4.177, P < .0001).
Eighteen of the 53 subjects (34%) exhibited no difference in scores (ie, the use of an immobilizer did not adversely affect balance), and 9 of these 18 subjects (50%) achieved the highest possible score (56) during both test conditions. Balance may have been affected in these 9 individuals, but the BBS may have failed to detect any changes because of a ceiling effect. In examining characteristics of these 9 individuals, the mean age was 70.9 (range, 66-79) years, 6 of 9 were women, and 1 of 9 had fallen within the past 6 months. In general, this group of 9 was younger than the total group (mean age = 70.9 vs 75.4), had fewer women (67% vs 74%), and had fewer falls (11% vs 26%).
When comparing participants with history of falls (n = 14) with participants with no history of falls (n = 38), the mean (SD) change scores were similar for the 2 groups: −0.93 (1.2) for the participants with history of falls and −1.05 (1.7) for the participants with no history of falls. Of the 53 subjects, 33 wore shoulder immobilizers during the first trial and 20 wore immobilizers during the second trial. Of the 20 subjects who wore the immobilizer during the second trial, scores increased for 15% (3/20), decreased for 50% (10/20), and stayed the same for 35% (7/20). Of the 33 subjects who wore the immobilizer during the first trial, scores increased for 55% (18/33), decreased for 12% (4/33), and stayed the same for 33% (11/33).
In this study, we found a statistically significant difference in balance scores when older, community-dwelling adults wore shoulder immobilizers. Balance was impaired (significantly lower BBS scores) when subjects wore the device compared with the testing sessions without the device. Although we found statistical significance, a mean change score of −1.02 may not represent a clinically significant change because we did not determine the minimal detectable change (MDC), which is the minimal change in a test score that is not a result of measurement error.23 Steffen and Seney23 calculated MDC95 (95% confidence interval) for studies that reported reliability values for the BBS and provided the following: MDC = 2 for 26 subjects with Parkinson disease; MDC = 5 for 24 older adults (with or without cerebrovascular accident); MDC = 3 for 20 people with hemiparesis; MDC = 4 for 5 people with traumatic brain injury; and MDC = 5 for 37 community-dwelling adults with parkinsonism. Steffen and Seney23 determined these values for subjects with neurologic disorders and found variability within diagnostic categories (eg, MDC values for subjects with Parkinson disease were 2 in 1 study and 5 in another). Minimal detectable change in BBS scores has not been determined for subjects without neurologic disorders (eg, our study population) or in patients with orthopedic conditions (eg, proximal humeral fractures). However, because our change scores ranged from +1 to −7, some of these scores may represent measurement error.
We did not conduct a reliability trial prior to the study to determine reliability of our raters; however, others have found good to excellent interrater reliability for the BBS.18,20,21,24 As in our study, Holbein-Jenny et al20 also used student physical therapists as raters in a study assessing balance in older adults and reported good interrater reliability (ICC = 0.88).
We attempted to control for order of testing through random assignment, but we did not have equivalent numbers of subjects for the 2 trials: 33 wore shoulder immobilizers during the first trial and 20 wore immobilizers during the second trial. We were concerned that there might be a learning effect and that participants would perform better on the second trial regardless of the use of shoulder immobilizers. While we recommend that future researchers attempt to control for order of testing, we believe that any learning effects between the first and second trials in our study were minimal.
We did not conduct a power analysis a priori because there is limited information on power analysis for nonparametric testing.25 In fact, Portney and Watkins26 state that power analysis with nonparametric testing is not necessary when significant differences are found and the null hypothesis is rejected.
We chose to use the BBS because it requires minimal equipment (a stopwatch, step, 2 chairs, and a ruler), can be administered in less than 20 minutes, and can be performed in a clinical or nonclinical setting. It was initially tested on an older adult population with documented balance impairments18 but has been used to assess balance in patients with stroke24 and with residents of personal care homes20 to determine if functional balance is associated with falls in older persons with history of hip fracture,27 to predict falls in older persons,21 and to screen inner-city community-dwelling older adults.28 One concern with BBS testing is rater bias. We were unable to blind raters to testing condition; therefore, rater bias may have occurred because the same tester took both measurements. Raters may have been influenced to score subjects lower on the BBS when wearing the immobilizer because of a preconception that balance might be worse under this condition.
Although we did not restrict participation in our study on the basis of race and gender, our sample was limited to non-Hispanic white, predominantly female, and older adults. This group of individuals may not reflect the general characteristics of all community-dwelling, older adults. Therefore, we cannot generalize the results of our study.
Future studies examining the effects of upper extremity immobilization on balance may want to consider using different performance-based assessment tools such as the Timed Up and Go or the Four Square Step Test that provide interval-level data and do not have issues with floor and ceiling effects. Including outcome measures of postural sway under different task conditions might provide a more comprehensive assessment of balance. In addition, it might be valuable to examine the effect of shoulder immobilization on temporal and spatial aspects of gait. Other researchers may also consider using a randomized block design to control for order of testing and to minimize any potential learning effects. Finally, a prestudy reliability trial would ensure tester reliability and determine MDC values to distinguish between measurement error and clinically significant changes.
Shoulder immobilization devices are commonly used in the treatment of older adults following proximal humeral fractures. However, the results of our study suggest that immobilizing the shoulder of some older adults may have a negative effect on balance as measured by the BBS. Patients who sustain proximal humeral fractures are usually not referred for physical therapy services until the fracture site is considered stable and range-of-motion exercises are indicated. If shoulder immobilization places an individual at greater risk for falls because of its impact on balance, early balance screening by a physical therapist to determine the appropriateness of a fall prevention program may be indicated.
1. Baron JA, Karagas M, Barrett J, et al. Basic epidemiology of fractures of the upper and lower limb among Americans over 65 years of age. Epidemiology. 1996; 7:612–618.
2. Bengner U, Johnell O, Redlund-Johnell I. Changes in the incidence of fractures of the upper end of the humerus during a 30-year period. Clin Orthop. 1988; 231:179–182.
3. Rose SH, Melton LJ, Morrey BF, et al. Epidemiologic features of humeral fractures. Clin Orthop. 1982; 168:24–30.
4. Nguyen TV, Center JR, Sambrook PN, Eisman JA. Risk factors for proximal humerus, forearm, and wrist fractures in elderly men and women. Am J Epidemiol. 2001; 153:587–595.
5. Chu SP, Kelsey JL, Keegan THM, et al. Risk factors for proximal humerus fracture. Am J Epidemiol. 2004; 160:360–367.
6. Kristiansen B, Barfod G, Bredesen J, et al. Epidemiology of proximal humeral fractures. Acta Orthop Scand. 1987; 58:75–77.
7. Baron JA, Barrett JA, Karagas MR. The epidemiology of peripheral fractures. Bone. 1996; 18:209S–213S.
8. Kelsey JL, Browner WS, Seeley DG, et al. Risk factors for fractures of the distal forearm and proximal humerus. Am J Epidemiol. 1992; 135:477–489.
9. Olsson C, Nordquist A, Petersson CJ. Long-term outcome of a proximal humerus fracture predicted after 1 year. Acta Orthop. 2005; 76:397–402.
10. Center JR, Nguyen TV, Schneider D, et al. Mortality after all major types of osteoporotic fracture in men and women: an observational study. Lancet. 1999; 353:878–882.
11. Keegan THM, Kelsey JL, King AC, et al. Characteristics of fallers who fracture at the foot, distal forearm, proximal humerus, pelvis, and shaft of the tibia(fibula compared with fallers who do not fracture. Am J Epidemiol. 2004; 159:192–203.
12. Palvanen M, Kannus P, Parkkari J, et al. The injury mechanisms of osteoporotic upper extremity fractures among older adults: a controlled study of 287 consecutive patients and their 108 controls. Osteoporos Int. 2000; 11:822–831.
13. Nho SJ, Brophy RH, Barker JU, et al. Management of proximal humeral fractures based on current literature. J Bone Joint Surg Am. 2007; 89:44–58.
14. Handoll HH, Gibson JN, Madhok R. Interventions for treating proximal humeral fractures in adults. Cochrane Database Syst Rev. 2007;(3).
15. Crenshaw A, Perez E. Fractures of the shoulder, arm, and forearm. In: Canale TS, Beaty JH, eds. Campbell's Operative Orthopaedics. Vol 3. 11th ed. Philadelphia, PA: Mosby-Elsevier; 2008:3377–3379.
16. Allum JHJ, Carpenter MG, Honegger F, et al. Age-dependent variations in the directional sensitivity of balance corrections and compensatory arm movements in man. J Physiol. 2002; 542.2:643–663.
17. Maki BE, McIlroy WE. The role of limb movements in maintaining upright stance: the “change-in-support” strategy. Phys Ther. 1997; 77:488–507.
18. Berg K, Wood-Dauphinee S, Williams JI, Gayton D. Measuring balance in the elderly: preliminary development of an instrument. Physiother Can. 1989; 41:304–311.
19. Berg KO, Wood-Dauphinee SL, Williams JI, Maki B. Measuring balance in the elderly: validation of an instrument. Can J Public Health. 1992; 83:S7–S11.
20. Holbein-Jenny MA, Billek-Sawhney B, Beckman E, Smith T. Balance in personal care home residents: a comparison of the Berg Balance Scale, the Multi-Directional Reach Test, and the Activities-specific Balance Confidence Scale. J Geriatr Phys Ther. 2005; 28:48–53.
21. Thorbahn LDB, Newton RA. Use of the Berg Balance Test to predict falls in elderly persons. Phys Ther. 1996; 76:576–585.
22. Podsiadlo D, Richardson S. The Timed “Up & Go”: a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc. 1991; 39:142–148.
23. Steffen T, Seney M. Teset-retest reliability and minimal detectable change on balance and ambulation tests, the 36-Item Short-Form Health Survey, and the Unified Parkinson Disease Rating Scale in people with parkinsonism. Phys Ther. 2008; 88:733–746.
24. Blum L, Korner-Bitensky N. Usefulness of the Berg Balance Scale in stroke rehabilitation: a systematic review. Phys Ther. 2008; 88:559–566.
25. Thomas L, Juanes F. The importance of statistical power analysis. Anim Behav. 1996; 52:856–859.
26. Portney LG, Watkins MP. Foundations of Clinical Research: Applications to Practice. 3rd ed. Upper Saddle River, NJ: Pearson-Prentice Hall; 2008.
27. Kulmala J, Sihvonen S, Kallinen M, et al. Balance confidence and functional balance in relation to falls in older persons with hip fracture history. J Geriatric Phys Ther. 2007; 30:114–120.
28. Newton RA. Balance screening of an inner city older adult population. Arch Phys- Med Rehabil. 1997; 78:587–591.