Physical therapists (PTs) continually compare tests and measures to choose those most appropriate for each patient. The term outcome measure (OM) is often used to describe these tests since they are frequently used to determine whether there has been a change in patient status or outcome. Physical therapists also use measurement tools to diagnose or formulate a prognosis about a patient's future status. In this article, the term outcome measure will be used broadly—to describe those tools that are used to assess patient status, as well as tools that serve diagnostic or predictive purposes. Outcome measures help to guide the selection of appropriate interventions. For example, if a patient scores low on the Berg Balance Scale (BBS), interventions that target postural control would be important to include in the plan of care. The complexity and variability of patients seen in neurological physical therapy practice make selection of OMs challenging. In addition, time constraints in the clinical setting limit the number of OMs that one can reasonably administer.
Part I of this article series, “Outcome Measures in Neurological Clinical Practice: Part I. Making Sound Decisions,”1 also in this journal issue, explores multiple factors involved in OM selection, including measurement psychometrics, measurement purpose, and clinical utility. The steps in selecting OMs are introduced in that article (see Figure 1, Potter et al1).
This article further explores the process for OM selection, and illustrates the application of that process for a patient with a diagnosis of stroke. A fully developed OM selection process is schematically represented in Figure 1. At the core of the process and represented in the center of the figure are the psychometric properties of the measure(s) under consideration. The key psychometric characteristics to examine before selecting an OM are that it:
* is appropriate to examine the desired constructs → Validity
* can be administered with minimal error → Reliability
* will help to determine if intervention produces a change in the patient's status → Responsiveness
Health Condition/Referral Question
The first step in the process (illustrated in Figure 1) is to gather information about a patient's health condition or reason for referral. This information prompts the therapist to consider the body structure/function issues common in that health condition. Knowledge of the health condition, combined with experience treating patients with that condition, allows a therapist to anticipate possible activity limitations and participation restrictions. A review of the medical record provides valuable preliminary information to help guide selection of OMs. In inpatient settings, nursing notes about the patient's activity level and assistance required for bed positioning and transfers may prompt the inclusion of specific activity-level measures. Combining information on the patient's health condition, medical record, and nursing notes allows the therapist to develop a tentative list of OMs prior to the therapist's initial evaluation of the patient. The list often includes measures that are specific to the patient's medical diagnosis or condition. Disease-specific measures may be particularly appropriate because they contain items designed to capture issues unique to individuals with that health condition. For example, stroke-specific OMs may include items about selective movement. Items about rigidity and tremor may be included in a Parkinson's disease–specific measure. Referral information may prompt the therapist to include measures, such as measures of balance for a patient who has been referred because of falls, that capture other constructs of interest. Each subsequent step of the examination process serves to tailor the list of OMs to a patient's unique circumstances and concerns.
Clinical Utility and Facility-Specific Issues
The next step in the process involves consideration of the clinical setting and facility-specific requirements and resources. Factors unique to each setting, including equipment and space available, as well as the time allotted for patient examination, affect the choice of measures. Facilities may require the use of specific OMs, like the Functional Independence Measure (FIM)3 in inpatient rehabilitation, or the Minimum Data Set4 in skilled nursing facilities. The choice of OMs occurs within the context of these resources and requirements.
An initial observation of the patient is the next step in the process. The therapist observes the patient performing spontaneous movements and considers whether the movement is consistent with expectations given the health condition or reason for referral. Observations of posture and movement quality, excursion, and speed help the therapist generate hypotheses about the underlying causes of the activity limitations and participation restrictions. Comparing these hypotheses with the initial list of OMs leads the therapist to include additional OMs and/or reaffirm the appropriateness of the initial list. The potential list is further narrowed because OMs that may have either a ceiling or floor effect are ruled out. Floor and ceiling effects are indicative of failures of responsiveness at the 2 ends of the measurement scale: floor, minimum end, and ceiling, maximum end. For example, if the patient is having difficulty moving in bed, an OM that captures advanced balance activities, such as the HiMat,2 may be associated with a floor effect, and therefore would be inappropriate for this patient.
Patient History and Goals
The therapist then explores the patient's history and identifies his or her concerns and goals. This provides information about the patient's past and current health situation, including medical and social history, and environment. Knowing the context in which the patient wishes to function, and his or her available resources and limitations, further helps to refine the potential list of OMs.
The systems review follows and leads to the final OM selection. The systems review begins when the therapist first observes a patient, noting posture, movement, function, and so on. It continues with a more detailed review of the body systems. The Guide to Physical Therapist Practice5 provides a comprehensive outline of this process. Anticipating the focus of treatment allows the therapist to choose OMs that will evaluate the success of those interventions. Following the examination, during evaluation, the therapist considers the OM findings and confirms or modifies initial hypotheses, leading to the development of the PT diagnosis, prognosis, and plan of care.
Consider how this process helps guide the selection of OMs for J.W., a 73-year-old man having a diagnosis of a left cerebral vascular accident 1 week before being admitted to an inpatient rehabilitation unit. The first step in selecting OMs begins when the referral is received (Figure 1). Knowledge that J.W. had a stroke prompts the hypothesis of potential limitations at several levels of the International Classification of Functioning, Disability, and Health (ICF).6 At the activity level, J.W. may have difficulty with bed mobility, transitions, arm function, and/or locomotion. At the body function/structure level, he may have limitations in the areas of cognition, communication, movement selectivity, muscle tone, and/or sensation. Therefore, OMs that capture these activity and body function/structure constructs should be considered. J.W. may also experience participation-level challenges such as limitations in being able to fully carry outfamily and employment roles. A participation measure, such as the Stroke Impact Scale,7 might be appropriate if the patient has had the opportunity to experience the impact of the health condition in community living. Participation measures typically ask a patient for a “self-report” of their perceptions, for example, fear of falling or satisfaction with life roles. Because J.W. has been in the hospital since his stroke, this type of measure may not be appropriate at this point in the rehabilitation process.
J.W.'s diagnosis of stroke prompts the therapist to consider stroke-specific OMs. Stroke-specific measures are available to examine the patient's function at each level of the ICF.6 An advantage of these measures is that they include items that examine many of the symptoms common with stroke, such as abnormal selectivity, spasticity, sensory loss, and cognitive change. Generic measures that target areas of interest such as balance and walking ability may also be included. Preliminary OM considerations for J.W. at this point in the process are illustrated in Figure 2.
The resources and requirements specific to the facility in which J.W. is being treated, including time available for the initial examination, equipment and space resources, and facility-specific OM requirements, are illustrated in Figure 3.
Armed with an awareness of the resources and requirements and a preliminary list of OMs, the therapist meets J.W. in his hospital room. J.W. responds to a knock on the door by saying, “Come in.” Using his left hand, he uses the bed controls to move to a sitting position. When he reaches his left hand to greet the therapist, J.W. falls slightly to the right. He is able to state his name, the name of the facility, and the reason he was hospitalized. The initial observation and therapist's underlying hypotheses regarding the patient's movement problems are illustrated in Figure 4.
During the history, J.W. reports that he lives with his daughter in a second floor walk-up apartment. He works part-time driving a boat. Prior to his stroke, J.W. was independent in all functional mobility and activities of daily living. He describes his health as “pretty good” before his stroke. J.W.'s medical history is significant for atrial fibrillation, hypertension, and hypercholesterolemia. His goals are to return home and to resume his premorbid life roles.
The systems review follows the history (Table 1). Each of the positive findings obtained during the systems review is compared with the initial hypotheses regarding body structure/function impairments, activity limitations, and participation restrictions resulting in a final list of constructs to examine. The findings also help to narrow the focus of the examination and eliminate those OMs that would result in ceiling or floor effects.
OUTCOME MEASURE SELECTION
The proposed process of selecting OMs can result in numerous possible OMs at each of the ICF levels.6 It is inefficient and impractical to administer multiple OMs that examine the same construct. To illustrate how a therapist might choose between different measurement tools, 2 motor function measures, the Stroke Rehabilitation Assessment of Movement (STREAM)8 and the FMA of sensorimotor function,9and 2 balance measures, the Berg Balance Scale (BBS)10 and the Activities-specific Balance Confidence Scale (ABC)11 will be considered. Comparing and contrasting these measures in the context of J.W.'s needs and goals helps to identify the best OM to select to examine each construct.
Information about the psychometrics of the FMA and STREAM is presented in Tables 2 to 4. The concepts of reliability, validity, and responsiveness are addressed at the center of the OM selection process. An OM's responsiveness and predictive validity are arguably the2 most important characteristics to be considered when selecting among different tools. An OM that is responsive will allow the therapist to monitor change in a patient's status. Predictive validity will help the therapist to formulate a prognosis and make discharge recommendations. Numerous studies indicate that both the STREAM and FMA can be reliably administered to J.W.8,9,12–16 The validity of these measures is similarly supported. Concurrent validity for the STREAM and FMA has been established by comparisons with other measures of the same construct. Predictive validity information may help the therapist set goals related to motor capacity and functional activities, such as locomotion, as well as shape discharge recommendations.
J.W. is being seen in an inpatient rehabilitation setting. A primary role of the PT in this setting is to make discharge placement recommendations. The STREAM score is predictive of discharge destination (e.g., patients scoring < 63/100 on the total STREAM have 0% probability of being discharged to home). This information can assist the PT in making appropriate, evidence-based recommendations. The STREAM and FMA have been shown to be responsive to changes in motor function following stroke. While the FMA can be used to classify patients according to motor function severity, this information may be less useful in assisting with clinical decision making pertaining to discharge destination. Rather, this classification may be more useful to researchers wishing to stratify their subjects according to severity. Both the STREAM20–22 and FMA20–25 have published minimal detectable change (MDC) values, but only the STREAM has published minimal clinically important difference (MCID) values.22 The MDC and MCID represent 2 different aspects of responsiveness, both of which are important in clinical practice.
Another element of responsiveness is the consideration of floor and ceiling effects. Choosing OMs in which J.W. scores at neither the minimum nor the maximum of the scale allows for optimal monitoring of his progress. Studies suggest that both floor and ceiling effects may be seen with the STREAM12,17,20 and FMA24,27 with someone like J.W., who has an acute stroke. However, initial observation of J.W. will allow the therapist to make a general prediction about where his scores might fall on these measures.12–28 Although there is evidence of excellent psychometric date on both measures, the availability of MCID data offers an advantage in selecting the STREAM to provide more complete information about J.W.'s change or response to intervention.
As disease-specific OMs, both the FMA and the STREAM capture body function/structure constructs of interest following stroke, such as selective extremity movement. Both OMs have fairly good clinical utility. The equipment needed to perform the tests can be found in most clinics and is available in the facility where J.W. is being seen. Scoring for these OMs is on a 3-point ordinal scale. There are, however, differences between the measures. While the STREAM scoring system captures the concepts of movement excursion and quality (1a-c scores), total scores do not reflect this concept since all scores of 1 (a, b, or c) are tabulated as “1.” The FMA items examine selective extremity movements; it also includes items on range of motion, pain, sensation, balance, and reflexes. The STREAM includes a gross mobility subscale composed of 10 mobility items assessing various aspects of bed mobility, transitions, and gait. The FIM,3 a tool that is required in inpatient rehabilitation facilities, includes only3 items pertaining to mobility. The FIM does not include items specific to bed mobility, which is an important skill for patients following stroke. In addition, the FIM is used to rate the burden of care, whereas the STREAM rates the patient's degree of independence and the degree to which the patient demonstrates a normal movement pattern during tasks. Hence, the information garnered from the STREAM and the FIM are complementary, rather than duplicative. Both provide useful information when determining the plan of care for patients following stroke. Finally, administration time for the tools differs; the STREAM takes 15 to 20 minutes to complete all 3 scales, while the FMA requires 20 to 30 minutes.
As described earlier, both FMA and the STREAM capture the construct of selective limb movement and have acceptable psychometrics that should allow the therapist to develop prognoses and measure change. Because of the greater clinical utility of the STREAM with its inclusion of gross mobility items, shorter administration time, ability to predict discharge destination, and published MCID values,20,22 we believe that the STREAM is the more appropriate OM to use in this case.
The psychometric properties of the 2 balance measures, the ABC and BBS, are presented in Tables 6 to 8. The ABC is a self-report measure, where the BBS is a performance-based tool. Both the BBS and the ABC were developed as generic measures; however, excellent reliability has been reported for each measure when used following stroke.10,28,29 The validity of both measures is similarly supported.24,29,31–39 Concurrent validity for the BBS has been established by comparisons with other measures of balance.24,28,30–38 Information on predictive validity is extremely helpful as it may contribute to the development of a prognosis about J.W.'s functional activities as well as discharge status.32–38 The BBS has been studied in stroke across acuity levels,30,32,35,36 while most studies of the ABC have involved stroke subjects in the chronic stage of recovery. Finally, the BBS has been shown to be responsive following stroke.18,24,40–43
Another element of responsiveness is the consideration of floor and ceiling effects. One study suggests that both floor and ceiling effects may be seen with the BBS in acute stroke.24 No studies have examined the ABC in acute stroke and therefore the presence of floor or ceiling effects is unknown. However, after initial observation of J.W., the therapist may be able to generally predict where he might score on these OMs.
Clinical utility is good for both the BBS and the ABC, including reasonable equipment requirements, administration time, and ease of scoring. While the BBS and the ABC each address the construct of balance, the ABC specifically focuses on balance in community settings; for this reason the ABC can be eliminated from the list of potential OMs during J.W.'s short-term hospitalization. At a later point in his rehabilitation, in an outpatient or home care setting, the ABC may be very appropriate. The clinical utility for the BBS and the ABC is summarized in Table 9.
In summary, the therapist's initial observations of J.W. led to hypotheses about underlying issues with motor function, balance, and difficulty with basic and instrumental activities of daily living. These hypotheses supported initial inclusion of the STREAM and BBS. The psychometrics and clinical utility of both OMs support their selection. However, given the absence of observable movement in J.W.'s right arm and loss of balance in sitting, there may be concerns about floor effects on both the BBS and the upper extremity subscale of the STREAM. Yet, J.W. has several positive indicators including his relatively healthy premorbid status, recent onset of stroke, the ability to communicate his needs and goals, as well as some active movement of his right extremities that suggest that he will improve with rehabilitation. Thus, the selection of these measures seems appropriate. Furthermore, since both the STREAM and BBS are organized by position (supine, sitting, standing, and walking), the tests can be efficiently administered.
J.W. is anxious to return to his premorbid status as independent in daily activities. Right-sided movement and balance will contribute to achieving these goals. In the final step of the selection process, the systems review confirmed that J.W. has hemiparesis and requires assistance with transitions from supine to sitting to standing as well as gait. The choice of the STREAM and BBS will provide quantitative information on these issues that can be used to plan and evaluate the success of intervention strategies. Responsiveness data on these measures allow the therapist to conclude that these measures will capture meaningful changes during intervention.
The process presented in this article expands on the steps for OM selection outlined in “Outcome Measures in Neurological Physical Therapy Practice: Part I. Making Sound Decisions,”1 and describes a comprehensive method for optimal OM choice. A step-by-step guide considering the critical elements related to the patient, therapist, facility, and available OMs is included. The challenge is to reconcile OM choice with the realities of the clinical environment.
One response to this challenge is the concept of “core sets” of OMs, which are batteries of OMs recommended for specific health conditions. Typically, core sets are developed by panels of experts using a process similar to that described in this article. An example of core set development is the recent effort by the American Physical Therapy Association—Neurology Section StrokEDGE Taskforce, which developed recommendations for the use of OMs following stroke. Consistent use of these core sets of recommended test batteries has multiple advantages including the ability to make comparison of treatment outcomes across facilities, clinicians, and patient characteristics. Perhaps most importantly, routine data collection using common metrics will facilitate the creation of a larger data set upon which to base clinical decisions and contribute to the evidence for best clinical practices. The use of these core sets of OMs does not preclude the use of additional measures that the therapist may find desirable, but will facilitate the collection of a uniform set of data.
Unfortunately, expert panel development of core sets is in its infancy. Using the process described in this article, individual therapists and clinical facilities have the opportunity to tailor test batteries for their settings and help to move forward the effort to develop core sets. Starting with patient populations most frequently treated in their settings, therapists can use resources such as in-services, journal clubs, and student projects to build their OM batteries. Numerous excellent Web sites are available with information about the psychometric properties and clinical utility of OMs used with several neurological populations (see Appendix, Supplemental Digital Content 1, for a list of these Web sites, http://links.lww.com/JNPT/A10).
However, until such time as there are core sets of OMs that are appropriate for the majority of patients seen in neurological PT practice, the process described in thisarticle is designed to equip therapists to make optimal OM choices on a patient-specific basis.
Physical therapists have made strides in using standardized OMs to assess body structure/function, activity, and participation from the days where examination was documented primarily with subjective, narrative descriptors such as “poor balance, slow gait speed, and synergistic movement.” The use of objective OMs allows therapists to quantify what was previously described only in subjective terms. This allows PTs to track progress and compare effectiveness and costs across interventions, settings, and providers, while considering patient characteristics such as severity, acuity, and lesion type or location. Comprehensive assessment across all components of the ICF model, including personal factors, the environment, and the patient's participation in life roles, enhances the focus on the patient's perspectives. Considerable information is available about what constructs are captured by specific measures, how the measures perform over time, and how scores can be used to predict change and plan care. In the future, consistent use of standardized OMs by therapists and collection of data across patients and settings can inform best clinical practice and the development of clinical prediction rules. Ultimately, consistent use of a core set of standardized OMs will allow therapists to determine, on a patient/situation basis, the optimal interventions needed to achieve the best possible outcomes.
1. Potter K, Fulk GD, Salem Y, Sullivan J. Outcome measures in neurological physical therapy practice: Part I. Making sound decisions. J Neurol Physic Ther. 2011;35(2):57–64.
2. Tyson S, Connell L. The psychometric properties and clinical utility of measures of walking and mobility in neurological conditions: a systematic review. Clin Rehabil. 2009;23(11):1018–1033.
3. Keith RA, Granger CV, Hamilton BB, Sherwin FS. The functional independence measure: a new tool for rehabilitation. Adv Clin Rehabil. 1987;(1):6–18.
4. Hawes C, Morris JN, Phillips CD, Mor V, Fries BE, Nonemaker S. Reliability estimates for the minimum data set for nursing home resident assessment and care screening (MDS). Gerontologist. 1995;35(2):172–178.
5. Guide to Physical Therapist Practice. Phys Ther. 2001;81(1):12–746.
6. Schepers VP, Ketelaar M, van de Port IG, Visser-Meily JM, Lindeman E. Comparing contents of functional outcome measures in stroke rehabilitation using the International Classification of Functioning, Disability and Health. Disabil Rehabil. 2007;29(3):221–230.
7. Duncan PW, Propst M, Nelson SG. Reliability of the Fugl-Meyer Assessment of sensorimotor recovery following cerebrovascular accident. Phys Ther. 1983;63(10):1606–1610.
8. Daley K, Mayo N, Wood-Dauphinee S. Reliability of scores on the Stroke Rehabilitation Assessment of Movement (STREAM) measure. Phys Ther. 1999;79(1):8–19; quiz 20–13.
9. Duncan PW, Propst M, Nelson SG. Reliability of the Fugl-Meyer assessment of sensorimotor recovery following cerebrovascular accident. Phys. Ther. 1983;63(10):1606–1610.
10. Berg K, Wood-Dauphinee S, Williams JI. The Balance Scale: reliability assessment with elderly residents and patients with an acute stroke. Scand J Rehabil Med. 1995;27(1):27–36.
11. Powell LE, Myers AM. The Activities-specific Balance Confidence (ABC) Scale. J Gerontol A Biol Sci Med Sci. 1995;50A(1):M28–M34.
12. Hsueh I-P, Hsu M-J, Sheu C-F, Lee S, Hsieh CL, Lin JH. Psychometric comparisons of 2 versions of the Fugl-Meyer Motor Scale and 2 versions of the Stroke Rehabilitation Assessment of Movement. Neurorehabil Neural Repair. 2008;22(6):737–744.
13. Wang CH, Hsieh CL, Dai MH, Chen CH, Lai YF. Inter-rater reliability and validity of the Stroke Rehabilitation Assessment of Movement (STREAM) instrument. J Rehabil Med. 2002;34(1):20–24.
14. Sanford J, Moreland J, Swanson LR, Stratford PW, Gowland C. Reliability of the Fugl-Meyer Assessment for testing motor performance in patients following stroke. Phys Ther. 1993;73(7):447–454.
15. Platz T, Pinkowski C, van Wijck F, Kim IH, di Bella P, Johnson G. Reliability and validity of arm function assessment with standardized guidelines for the Fugl-Meyer Test, Action Research Arm Test and Box and Block Test: a multicentre study. Clin Rehabil. 2005;19(4):404–411.
16. Lin JH, Hsueh IP, Sheu CF, Hsieh CL. Psychometric properties of the sensory scale of the Fugl-Meyer Assessment in stroke patients. Clin Rehabil. 2004;18(4):391–397.
17. Ahmed S, Mayo NE, Higgins J, Salbach NM, Finch L, Wood-Dauphinée SL. The Stroke Rehabilitation Assessment of Movement (STREAM): a comparison with other measures used to evaluate effects of stroke and rehabilitation. Phys Ther. 2003;83(7):617–630.
18. Salbach NM, Mayo NE, Higgins J, Ahmed S, Finch LE, Richards CL. Responsiveness and predictability of gait speed and other disability measures in acute stroke. Arch Phys Med Rehabil. 2001;82(9):1204–1212.
19. Hsueh IP, Wang CH, Sheu CF, Hsieh CL. Comparison of psychometric properties of three mobility measures for patients with stroke. Stroke. 2003;34:1741–1745.
20. Lin J-H, Hsu M-J, Sheu C-F, et al. Psychometric comparisons of 4 measures for assessing upper-extremity function in people with stroke. Phys Ther. 2009;89(8):840–850.
21. Lu WS, Wang CH, Lin JH, Sheu CF, Hsieh CL. The minimal detectable change of the simplified stroke rehabilitation assessment of movement measure. J Rehabil Med. 2008;40(8):615–619.
22. Hsieh YW, Wang CH, Sheu CF, Hsueh IP, Hsieh CL. Estimating the minimal clinically important difference of the Stroke Rehabilitation Assessment of Movement measure. Neurorehabil Neural Repair. 2008;22(6):723–727.
23. Rabadi MH, Rabadi FM. Comparison of the Action Research Arm Test and the Fugl-Meyer Assessment as measures of upper-extremity motor weakness after stroke. Arch Phys Med Rehabil. 2006; 87:962–966.
24. Mao H, Hsueh I, Tang P, Sheu CF, Hsieh CL. Analysis and comparison of the psychometric properties of three balance measures for stroke patients. Stroke. 2002;33(4):1022–1027.
25. Beckerman, Vogelaar TW, Lankhorst GJ, Verbeek AL. A criterion for stability of the motor function of the lower extremity in stroke patients using the Fugl-Meyer Assessment Scale. Scand J Rehabil Med. 1996;28(1):3–7.
26. van der Lee JH, Beckerman H, Lankhorst GJ, Bouter LM. The responsiveness of the Action Research Arm test and the Fugl-Meyer Assessment scale in chronic stroke patients. J Rehabil Med 2001;33(3):110–113.
27. Gladstone DJ, Danells CJ, Black SE. The Fugl-Meyer Assessment of motor recovery after stroke: a critical review of its measurement properties. Neurorehabil Neural Repair. 2002;16(3):232–240.
28. Liston RA, Brouwer BJ. Reliability and validity of measures obtained from stroke patients using the Balance Master. Arch Phys Med Rehabil. 1996;77(5):425–430.
29. Botner EM, Miller WC, Eng JJ. Measurement properties of the Activities-specific Balance Confidence Scale among individuals with stroke. Disabil Rehabil. 2005;27(4):156–163.
30. Smith PS, Hembree JA, Thompson ME. Berg Balance Scale and Functional Reach: determining the best clinical tool for individuals post acute stroke. Clin Rehabil. 2004;18(7):811–818.
31. Tyson SF, DeSouza LH. Reliability and validity of functional balance tests post stroke. Clin Rehabil. 2004;18(8):916–923.
32. Wee JY, Bagg SD, Palepu A. The Berg Balance Scale as a predictor of length of stay and discharge destination in an acute stroke rehabilitation setting. Arch Phys Med Rehabil. 1999;80(4):448–452.
33. Wee JY, Wong H, Palepu A. Validation of the Berg Balance Scale as a predictor of length of stay and discharge destination in stroke rehabilitation. Arch Phys Med Rehabil. 2003;84(5):731–735.
34. Patterson SL, Forrester LW, Rodgers MM, et al. Determinants of walking function after stroke: differences by deficit severity. Arch Phys Med Rehabil. 2007;88(1):115–119.
35. Belgen B, Beninato M, Sullivan PE, Narielwalla K. The association of balance capacity and falls self-efficacy with history of falling in community-dwelling people with chronic stroke. Arch Phys Med Rehabil. 2006;87(4):554–561.
36. Mackintosh SF, Hill KD, Dodd KJ, Goldie PA, Culham EG. Balance score and a history of falls in hospital predict recurrent falls in the 6 months following stroke rehabilitation. Arch Phys Med Rehabil. 2006;87(12):1583–1589.
37. Andersson AG, Kamwendo K, Seiger A, Appelros P. How to identify potential fallers in a stroke unit: validity indexes of 4 test methods. J Rehabil Med. 2006;38(3):186–191.
38. Ashburn A, Hyndman D, Pickering R, Yardley L, Harris S. Predicting people with stroke at risk of falls. Age Ageing. 2008;37(3):270–276.
39. Salbach NM, Mayo NE, Robichaud-Ekstrand S, Hanley JA, Richards CL, Wood-Dauphinee S. Balance self-efficacy and its relevance to physical function and perceived health status after stroke. Arch Phys Med Rehabil. 2006;87(3):364–370.
40. Wood-Dauphinee S, Berg KO, Bravo G, Williams JL. The Balance Scale: responsiveness to clinically meaningful changes. Can J Rehabil. 1997;10:35–50.
41. English CK, Hillier SL, Stiller K, Warden-Flood A. The sensitivity of three commonly used outcome measures to detect change amongst patients receiving inpatient rehabilitation following stroke. Clin Rehabil. 2006;20(1):52–55.
42. Stevenson TJ, Garland SJ. Standing balance during internally produced perturbations in subjects with hemiplegia: validation of the Balance Scale. Arch Phys Med Rehabil. 1996;77:656–662.
43. Stevenson TJ. Detecting change in patients with stroke using the Berg Balance Scale. Aust J Physiother. 2001;47(1):29–38.
44. Beninato M, Portney LG, Sullivan PE. Using the international classification of functioning, disability and health as a framework to examine the association between falls and clinical assessment tools in people with stroke. Phys Ther. 2009;89(8):816–825.
45. Myers AM, Fletcher PC, Myers AH, Sherk W. Discriminative and evaluative properties of the activities-specific balance confidence (ABC) scale. J Gerontol A Biol Sci Med Sci. 1998;53(4):M287–M294.
46. Lajoie Y, Gallagher SP. Predicting falls within the elderly community: comparison of postural sway, reaction time, the Berg Balance Scale and the Activities-specific Balance Confidence (ABC) Scale for comparing fallers and non-fallers. Arch Gerontol Geriatr. 2004;38(1):11–26.
examination; outcome measures therapy; stroke
Supplemental Digital Content
© 2011 Neurology Section, APTA