Validation of the Multidimensional Outcome Expectations for Exercise Scale in Ambulatory, Symptom-Free Persons With Multiple Sclerosis

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ORIGINAL ARTICLE

Validation of the Multidimensional Outcome Expectations for Exercise Scale in Ambulatory, Symptom-Free Persons With Multiple Sclerosis Edward McAuley, PhD, Robert W. Motl, PhD, Siobhan M. White, BS, Thomas R. Wójcicki, BS ABSTRACT. McAuley E, Motl RW, White SM, Wójcicki TR. Validation of the Multidimensional Outcome Expectations for Exercise Scale in ambulatory, symptom-free persons with multiple sclerosis. Arch Phys Med Rehabil 2010;91:100-5. Objective: To determine the psychometric properties of the 3-factor Multidimensional Outcome Expectations for Exercise Scale in a sample of ambulatory, symptom-free persons with multiple sclerosis (MS). Design: Cross-sectional validation study. Setting: Midwestern university. Participants: Community-dwelling adults (N⫽242) with an established definite diagnosis of MS, as corroborated by the participant’s neurologist, who were relapse free for the last 30 days and ambulatory with minimal assistance. Interventions: Not applicable. Main Outcome Measures: Multidimensional Outcome Expectations for Exercise Scale, physical activity, self-efficacy, and physical health status. Confirmatory factor analyses using covariance modeling and correlational analyses were used to establish factorial and construct validity. Results: Analyses showed excellent factorial validity for the hypothesized factor structure reflecting physical, social, and self-evaluative outcome expectations. All 3 subscales were internally consistent. Theoretically, relevant correlations between outcome expectations and self-efficacy, physical activity, and physical health status were all supported. Conclusions: The Multidimensional Outcome Expectations for Exercise Scale appears to be a reliable and valid measure of outcome expectations for exercise in this limited sample of community-dwelling adults with MS. Further validation in clinical samples is warranted. Key Words: Exercise; Multiple sclerosis; Rehabilitation; Self-efficacy. © 2010 by the American Congress of Rehabilitation Medicine HERE IS INCREASING EVIDENCE to suggest that perT sons with MS are less active than those persons without neurologic disease. Being more active is associated with less 1,2

ity of life.3,4 As with all sedentary populations, understanding those factors that have implications for the adoption and maintenance of physical activity in MS is an important public health issue. Social Cognitive Theory5,6 specifies a core set of psychosocial determinants (ie, self-efficacy, outcome expectations, goals, impediments) for a range of health behaviors, including physical activity. Of these core determinants, self-efficacy has been consistently identified as an important, malleable construct associated with greater levels of structured physical activity.7 More efficacious persons engage in more challenging activities, expend more effort, and show persistence in the face of aversive stimuli or setbacks.8 For persons with MS, physical activity is undoubtedly challenging, certainly requires effort expenditure, and can be fraught with setbacks brought about by the often progressive and unpredictable nature of the disease. Several recent studies9,10 have suggested self-efficacy is just as important a determinant of physical activity behavior in MS as in those persons without neurologic disease. Unfortunately, other key constructs within the social cognitive model have been examined less frequently in this literature. Outcome expectations, for example, reflect beliefs that a given behavior will produce a specific outcome and are thought to be particularly important for motivating persons to engage in a particular behavior. Although outcome expectations have been shown to be predictive of structured physical activity behaviors in some studies,11,12 it has been argued that the approach taken to measure this construct has been suspect.13 Specifically, researchers have considered all outcome expectations to be equal and have failed to assess expectations that reflect the conceptually distinct areas of the physical, social, and self-evaluative domains.5,8 We believe that this is particularly important in the context of physical activity in persons with MS, a population that may well have limited awareness and understanding of the benefits of physical activity for the management of disease symptoms and outcomes. For example, physical outcome expectations are characterized by beliefs about pleasant and aversive physical experiences that might result from being physically active, such as improving strength and cardiovascular fitness and being able to conduct daily activities without difficulty. Social expectations reflect beliefs

fatigue, possibly fewer functional limitations, and improved qualList of Abbreviations From the Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL. Supported by a Shahid and Ann Carlson Khan Professorship in Applied Health Science and the National Institute for Neurological Disorders and Stroke (grant no. NS054050). No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit on the authors or on any organization with which the authors are associated. Reprint requests to Edward McAuley, PhD, Dept of Kinesiology and Community Health, University of Illinois, 906 S Goodwin Ave, Urbana, IL 61801, e-mail: [email protected]. 0003-9993/10/9101-00439$36.00/0 doi:10.1016/j.apmr.2009.09.011

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CFI CI EXSE GLTEQ LL-FDI MS MSSE PDDS RMSEA SF-12

Comparative Fit Index confidence interval Exercise Self-Efficacy Scale Godin Leisure-Time Exercise Questionnaire Late Life Function and Disability Instrument multiple sclerosis Multiple Sclerosis Self-Efficacy Scale Patient Determined Disease Steps root mean square error of approximation 12-Item Short Form Health Survey

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about having more opportunities to be with other persons or potentially improving what others think of you through being physically active. Self-evaluative outcome expectations are concerned with the degree to which engaging in structured physical activities might enhance one’s self-worth and personal well-being. As noted, until recently, measures of outcome expectations have overlooked the importance of examining these dimensions as related but conceptually different elements.14,15 Wójcicki et al13 developed a multidimensional measure of outcome expectations for exercise that reflects the dimensions theorized by Bandura8 and provide factorial and construct validity for the scale in a sample of middle- and older-aged adults. The 3-factor structure was superior to a 1- and 2-factor model, and the outcome expectation dimensions were significantly correlated with physical activity patterns, self-efficacy, and health status. The development of this measure is an important step in attempting to unravel the role different types of outcome expectations may play in physical activity behavior and establishing a more comprehensive social cognitive model of health behavior. In the present study, we further examined the psychometric evidence for the validity of the Multidimensional Outcome Expectations for Exercise Scale13 in a sample of adults with MS. This sample was drawn from an ongoing study examining physical activity and quality of life in symptom-free ambulatory persons. Specifically, we examined the 3-dimensional factor structure for the Multidimensional Outcome Expectations for Exercise Scale proposed in the original study and its relationship with physical activity, demographic factors, health status, and functional limitations. METHODS Participants and Procedures We recruited 242 persons for this study. Details of recruitment of the original sample and data-collection methods have been published elsewhere.4 For this study, we contacted the 292 enrolled participants by mail to describe the research project and determine their interest in participating in this aspect of the project. Initial screening criteria required all participants to have an established definite diagnosis of MS, as corroborated by the participant’s neurologist, and be relapse free for the last 30 days and ambulatory with minimal assistance. As noted, 242 persons agreed to participate, with the remainder failing to return study materials for unknown reasons. All participants completed a university institutional review board–approved informed consent and returned it by mail along with the questionnaire packet and accelerometer. Measures Demographics. A brief questionnaire assessed basic demographic information including sex, education, employment status, income, and marital status. Additionally, we asked participants to report the type of MS with which they had been diagnosed, and this was verified by the participant’s neurologist. Outcome expectations. We measured outcome expectation with the Multidimensional Outcome Expectations for Exercise Scale,13 a 15-item scale with 6 items reflecting physical outcome expectations (eg, “Exercise will increase my muscular strength,” “Exercise will improve my overall functioning”), 4 items assessing social outcome expectations (“Exercise will improve my companionship,” “Exercise will increase my acceptability by others”), and 5 items measuring self-evaluative outcome expectations (eg, “Exercise will give me a sense of accomplishment,” “Exercise

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will help me manage my stress”). Participants were asked to rate how strongly they agreed with each of these 15 items on a 5-point scale (1 ⫽ strongly disagree, 2 ⫽ disagree, 3 ⫽ neutral, 4 ⫽ agree, 5 ⫽ strongly agree). Physical activity. We used 2 methods of assessing physical activity in our sample, and both the self-report and objective measure have evidence of validity in samples of ambulatory adults with MS.16,17 The inclusion of self-report and objective measures allows for a clearer assessment of relationships between social-cognitive constructs and physical activity. The observation of a similar pattern of correlations across selfreport and objective measures of physical activity reduces the concern of self-report biases inflating correlations between self-report measures of physical activity and social-cognitive constructs. The first assessment was the GLTEQ.18 The GLTEQ is a self-administered 2-part measure of usual physical activity; in this study, we only included responses from the first portion of this questionnaire, consistent with previous research.16,17 The first part has 3 items that measure the frequency of strenuous (eg, jogging), moderate (eg, fast walking), and mild (eg, easy walking) exercise for periods of more than 15 minutes during one’s free time in a typical week. The weekly frequencies of strenuous, moderate, and mild activities are multiplied by 9, 5, and 3 metabolic equivalents, respectively, and summed to form a measure of total leisure activity. Reported activity was based on the previous week as a timeframe for the GLTEQ, and participants completed the GLTEQ after wearing an accelerometer for the 7-day period. We also used the ActiGraph single-axis accelerometer,a the criterion standard for the objective assessment of physical activity. We collected data in 1-minute epochs over a preprogrammed 7-day period, and accelerometers were worn during the waking hours, except while showering, bathing, and swimming. Waking hours were defined as the moment upon getting out of bed in the morning through the moment of getting into bed in the evening. The accelerometers were not worn during the night while the participants slept. The participants recorded the time the accelerometer was worn on a log, and this was verified by inspection of the minute-by-minute accelerometer data. We summed the minute-by-minute counts across each of the 7 days and then averaged the total daily movement counts. This yielded accelerometer data in total movement counts per day, with higher scores representing more physical activity. These procedures and both physical activity measures have been used in previous research among persons with MS.16,17 Self-efficacy. We used 2 measures of self-efficacy: the MSSE19 and the EXSE.20 The MSSE is an 18-item scale assessing both confidence in functional abilities and confidence in the management of symptoms and being able to cope with the demands of the illness. The EXSE scale has 6 items that assess a person’s beliefs in his/her ability to engage in 20⫹ minutes of moderate physical activity 3 times per week in 1-month increments across the next 6 months. Both scales are internally consistent and have shown validity.19,20 Coefficient alpha for MSSE and EXSE were .92 and .98, respectively, in the present study. Physical health status. Three self-report measures were used to assess physical health status. First, we used the physical health status subscale of the SF-12,21 a shortened version of the Medical Outcomes Study 36-Item Short-Form Health Survey. This is a well-validated measure of health status and healthrelated quality of life, with higher scores reflecting better health status. Our second measure was the Functional Limitations subscale of the abbreviated LL-FDI.22 The measure is scored on a 1 to 5 scale (1 ⫽ completely limited, 5 ⫽ not at all limited). Items were reverse scored and summed to provide Arch Phys Med Rehabil Vol 91, January 2010

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measures of limitations with respect to upper-extremity function and basic and advanced lower-extremity function. In addition, we summed all items to provide a composite measure of functional limitation, with higher scores representing better functioning. The LL-FDI has been shown to have good psychometric properties in persons with MS.23 Finally, we used the PDDS24 scale, a single-item scale for measuring selfreported disability by using an 8-level ordinal scale. Data Analysis Factorial validity. To determine the tenability of the 3-factor structure proposed by Wójcicki et al,13 we conducted a confirmatory factor analysis to examine the strength of 15 individual item loadings on the 3 hypothesized categories of outcome expectations. All data were analyzed by using covariance modeling with the full-information maximum likelihood estimator in Mplus V5.0.25,b Full-information maximum likelihood is an optimal method for the treatment of missing data in structural equation modeling and has yielded accurate parameter estimates and fit indices with simulated missing data.26-28 Missing data comprised 3.7% of physical outcome expectations data (n⫽9), 4.6% of social outcome expectations data (n⫽11), 3.3% of self-evaluative outcome expectations data (n⫽8), 0.8% (n⫽2) of GLTEQ and the self-efficacy and health status measures, and 4.6% of the accelerometer data (n⫽11). Evaluation of model fit. Several indices of model fit were used. The chi-square statistic assessed absolute fit of the model to the data.29 Values for the RMSEA of 0.06 or less were also used and are indicative of good model fit.30,31 The RMSEA can range from 0 to 1, with smaller values being indicative of good fit. Finally, we calculated the CFI32 for which a value of 0.95 or greater indicates a good model-data fit.31 Again, this index can range from 0 to 1 but with larger values that approximate 1 reflecting better fit. Construct validity. To further examine the construct validity of the Multidimensional Outcome Expectations for Exercise Scale, we conducted a series of analyses testing relationships with the outcome expectations scale that would be hypothesized by social cognitive theory.8 For example, we first examined the theoretic associations between outcome expectations and our measures of self-efficacy and physical activity by using bivariate correlation analyses. Higher outcome expectations would be expected to be associated with being more efficacious and more physically active. Importantly, partial correlations were then conducted to determine whether any association between outcome expectations and physical activity was attenuated when controlling for self-efficacy, as would theoretically be expected. Finally, correlational analyses determined whether the 3 types of outcome expectations were differentially associated with measures of physical health status and demographic variables. RESULTS Participant Characteristics The mean age ⫾ SD of the sample was 48.67⫾10.14 years (range, 20 – 84y). The majority of participants were female (85.0%), 68.5% were married, and 66% had an annual household income greater than $40,000. The majority were well educated (58.9% with at least a college degree). Thus, we have a relatively limited sample in the context of socioeconomic status. In addition, the mean duration ⫾ SD of MS was 10.54⫾7.79 years (range, 0.5–37y), and the majority of the sample (80.8%) reported being diagnosed with relapse remitting MS. The median PDDS was 2.0 (range, 0 – 6). Arch Phys Med Rehabil Vol 91, January 2010

Confirming the Factor Structure of the Multidimensional Outcome Expectations for Exercise Scale The confirmatory factor analysis examining the suitability of a 3-factor solution to the 15 items proposed in the original Multidimensional Outcome Expectations for Exercise Scale development resulted in a reasonably good fit to the data (␹287⫽185.05, P⬍.001, RMSEA [95% CI] ⫽ .07 [.06 –.08], CFI⫽.92). After inspecting the modification indices, we reran the model, allowing a single correlation between the residuals of 2 of the social outcome expectation items (“Exercise will improve my social standing” and “Exercise will increase my acceptance by others”) based on the overlapping nature of the item content. This model, proved to be a substantially better fitting model (␹286⫽144.62, P⬍.001, RMSEA [95% CI] ⫽ .05 [.04 –.07], CFI⫽.96), with the difference between the 2 models being statistically significant (␹2diff1⫽40.43, P⬍.001). Correlations between factors were significant (P⬍.001) and moderate to large (physical – self-evaluative, r⫽.90; physical – social, r⫽.48; self-evaluative – social, r⫽.70). All scale items and their standardized factor loadings are shown in table 1. The high correlation between the physical and self-evaluative dimensions might suggest that these could be represented by a single factor. However, such a strong relationship might be expected given that persons often evaluate themselves based on their physical characteristics. Nonetheless, because of this strong correlation between these 2 factors, we conducted an alternative 2-factor confirmatory factor analysis in which the self-evaluative and physical items were loaded on a common factor. This model provided a poorer fit to the data (␹288⫽ 174.61, P⬍.001, RMSEA [95% CI] ⫽ .06 [0.5–.08], CFI⫽.93). Indeed, the chi-square difference test indicated that the 3-factor model representing the physical, social, and selfevaluative outcome expectation categories, as proposed by Bandura,6,8 was a significantly better fit to these data than the 2-factor approach (␹2diff1⫽30.18, P⬍.001).

Table 1: Multidimensional Outcome Expectations Scale Items and Confirmatory Factor Loadings Item

Physical outcome expectations Exercise will improve my ability to perform daily activities. Exercise will improve my overall body functioning. Exercise will strengthen my bones. Exercise will increase my muscle strength. Exercise will aid in weight control. Exercise will improve the functioning of my cardiovascular system. Social outcome expectations Exercise will improve my social standing. Exercise will make me more at ease with people. Exercise will provide companionship. Exercise will increase my acceptance by others. Self-evaluative expectations Exercise will help manage stress. Exercise will improve my mood. Exercise will improve my psychological state. Exercise will increase my mental alertness. Exercise will give me a sense of personal accomplishment. *All loadings significant (P⬍.001) and standardized.

Factor Loading*

.64 .48 .53 .71 .63 .56 .55 .89 .52 .62 .72 .59 .76 .70 .77

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OUTCOME EXPECTATIONS FOR EXERCISE, McAuley Table 2: Descriptive Statistics for All Study Variables Variable

Mean ⫾ SD

Range

Physical outcome expectations Social outcome expectations Self-evaluative expectations Accelerometer Godin Leisure Time Exercise MSSE Functional disabilities Symptom management Exercise self-efficacy SF-12 physical health Upper-extremity limitations Basic lower-extremity limitations Advanced lower-extremity function Total functional limitations PDDS

26.2⫾2.7 13.0⫾2.7 21.1⫾2.7 222,557.2⫾123,919.3 26.7⫾22.3

18.0–30.0 4.0–20.0 11.0–25.0 32,010.6–760,721.7 0.0–110.0

81.2⫾9.5 67.1⫾18.7 7.5⫾3.2 42.2⫾9.0 19.8⫾4.2 21.2⫾3.8 14.0⫾5.7 55.0⫾11.8 2.3⫾1.7

31.0–90.0 13.0–90.0 0.0–10.0 22.6–62.7 8.0–25.0 10.0–25.0 5.0–25.0 28.0–75.0 0.0–6.0

Internal Consistency and Validity of the Multidimensional Outcome Expectations for Exercise Scale The internal consistency of the 3 outcome expectations scales was adequate (ie, physical [␣⫽.76], self-evaluative [␣⫽.83], social [␣⫽.77]). Table 2 shows the mean values for each of the Multidimensional Outcome Expectations for Exercise Scale subscales and all other study measures. As can be seen, participants had very positive physical and self-evaluative beliefs about exercise and moderately positive beliefs about the social benefits of exercise. Spearman rank order correlations indicated that reporting greater activity on the GLTEQ and having higher activity counts on the accelerometer, respectively, were significantly correlated (Pⱕ.050) with stronger physical (r⫽.17, P⫽.008; r⫽.22, P⫽.001), self-evaluative (r⫽.19, P⫽.004; r⫽.20, P⫽.002), and social (r⫽.20, P⫽.002; r⫽.19, P⫽.003) outcome expectations. Higher self-efficacy for exercise was significantly associated with physical (r⫽.32, P⬍.001), self-evaluative (r⫽.33, P⬍ .001), and social (r⫽.18, P⫽.006) outcome expectations. Selfefficacy for function and controlling MS symptoms, respectively, were correlated with physical (r⫽.17, P⫽.004; r⫽.15, P⫽.011), and self-evaluative (r⫽.17, P⬍.004; r⫽.21, P⫽.001) but not with social outcome expectations (r⫽.11, P⫽.097; r⫽.11, P⫽.061). Because outcome expectations for exercise were associated with physical activity, the next set of analyses examined the extent to which these correlations were attenuated when controlling for self-efficacy. With respect to the correlations with GLTEQ, partial correlation analyses rendered relationships with all 3 outcome expectations nonsignificant (rⱕ.10, P⬎.05). Correlations between the accelerometer data and outcome expectations remained statistically significant but were all slightly attenuated. The correlation with physical outcome expectations was reduced from .17 to .16, self-evaluative

expectations from .19 to .14, and social outcome expectations from .20 to .15. The next set of correlational analyses examined the extent to which the 3 outcome expectation scales were differentially related to health status. These correlations are shown in table 3. As can be seen, higher physical, social, and self-evaluative outcome expectations were modestly but significantly associated with reporting better physical health status as measured by the SF-12 and fewer advanced lower-extremity limitations. Only self-evaluative and physical outcome expectations were significantly correlated with total functional limitations. Finally, the only significant association of outcome expectations with the PDDS was for self-evaluative expectations (r⫽⫺.17, P⫽.012). Finally, we correlated the outcome expectation dimensions with demographic factors. Women had more positive social outcome expectations (r⫽.15, P⫽.005), whereas men had higher physical outcome expectations (r⫽⫺.11, P⫽.044). Older participants had lower physical outcome expectations (r⫽⫺.13, P⫽.021). All other correlations were nonsignificant. DISCUSSION There has been an increasing interest in studying the physical activity patterns of persons with MS and, in particular, applying social cognitive models to understand this health behavior.3 However, although some of these studies have examined the potential role that barriers to being active might play, to our knowledge there are no studies that have assessed outcome expectations, an important element of social cognitive theory.8 In some respects, this may well be caused by the lack of validated measures for assessing this construct. The present study validated a recently developed measure of outcome expectations for exercise13 in a sample of ambulatory adults with MS who were symptom free over the previous 30 days.

Table 3: Correlations Among Outcome Expectations and Measures of Physical Health Status Outcome Expectations

Physical Social Self-Evaluative

SF-12 Physical Health Status †

0.17 0.11 0.16*

Upper-Extremity Limitations †

0.17 0.08 0.16*

Basic Lower-Extremity Limitations

0.16* 0.03 0.17†

Advanced Lower-Extremity Function †

0.17 0.13* 0.17†

Total Functional Limitations †

0.19 0.10 0.18†

PDDS

⫺0.11 ⫺0.06 ⫺0.16*

*Pⱕ.05; †Pⱕ.01.

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The Multidimensional Outcome Expectations for Exercise Scale was developed to assess the 3 primary dimensions of outcome expectations: physical, social, and self-evaluative. In the original development and validation study, initial confirmatory factor analyses and measurement invariance analyses provided good support for the independent assessment of these 3 dimensions and provided evidence of construct validity in the context of significant associations with self-efficacy, physical activity, and health status. Results from the present study provided further validation evidence to suggest that the psychometric properties of the Multidimensional Outcome Expectations for Exercise Scale are sustained in this sample of well-educated, ambulatory persons with MS who were symptom free within the last 30 days. The 3-factor structure provided a good fit to the data and was a significantly better fit than an alternative 2-factor model in which the highly correlated factors of physical and self-evaluative outcome expectations were combined as 1 factor. A high correlation between the self-evaluative and physical dimensions of outcome expectations was also reported by Wójcicki et al.13 In many ways, this is not unexpected because older persons, as well as persons with chronic disease conditions that ultimately impair function and mobility, are likely to consider these physical aspects as important in their day-to-day lives, resulting in them becoming a salient aspect of self-evaluation. Thus, we have further testimony to Bandura’s5 position that outcome expectations are formulated to reflect social, self-evaluative, and physical beliefs about the consequences of participating in health behaviors. Such findings call into question the previously held practice of using outcome expectation scales that include social, physical, and self-evaluative items under 1 dimension. Our construct validation analyses examining relationships among outcome expectations and theoretically relevant variables also provide evidence to support the psychometric properties of the Multidimensional Outcome Expectations for Exercise Scale. As would be expected, higher levels of exercise- and MS-specific self-efficacy were associated with more positive outcome expectations, which were associated with being more physically active, as assessed by both objective and subjective measures. Interestingly, these latter associations were either attenuated or became nonsignificant when exercise self-efficacy was statistically controlled. Indeed, Bandura8 has noted that this is likely to be the case when self-efficacy expectations are relatively strong and overshadow the relationship with the target behavior. In the present study, self-efficacy scores, particularly relative to functional abilities and exercise, were quite strong. However, it is important to realize that this does not make outcome expectations unimportant in the behavioral process because they act as potential motivators for engagement in new behaviors. Subsequent determination of the individual contributions of physical, social, and self-evaluative beliefs to behavioral engagement for persons across the spectrum of MS remains to be determined. Our validity analyses further suggest that persons in this sample who had more positive expectations relative to outcomes associated with physical activity reported fewer functional limitations and more positive health status. Importantly, it would appear that the degree of limitations experienced with respect to advanced lower-extremity functioning is driving this relationship. Such a finding does make sense given that those with MS tend to experience progressive mobility problems and exercise is associated with better mobility.33 Only self-evaluative outcome expectations were associated with patient-determined disease steps, and this latter measure may not be sufficiently sensitive to reflect other important elements of mobility that appear to be related to outcome expectations. We present further evidence to support the 3-dimensional factor structure proposed in the original development of the Arch Phys Med Rehabil Vol 91, January 2010

Multidimensional Outcome Expectations for Exercise Scale13 as well as internal consistency and construct validity for this measure. As the use of social cognitive models to understand and predict physical activity behavior in persons increases, it will be important to include measures that encompass the complexity of such models. For example, Bandura5 has carefully laid out how self-efficacy, outcome expectations, goals, facilitating conditions, and impediments are related in the context of examining behavior change. However, very few efforts have been made to include constructs other than self-efficacy and occasionally outcome expectations. Even in these latter cases, unidimensional, omnibus measures of outcome expectations are used. In the context of studying physical activity and other health behaviors in persons with MS, to our knowledge, outcome expectations have rarely been assessed. In several studies,34,35 measures of barriers to physical activity participation have been used as a social cognitive correlate of physical activity. Whether they have been used as a surrogate for outcome expectations cannot be determined. However, barriers are conceptually distinct from outcome expectations. Barriers represent hurdles to behavioral engagement, whereas outcome expectations are beliefs about those outcomes that are expected to occur once the behavior has been carried out. The validation of the Multidimensional Outcome Expectations for Exercise Scale in persons with MS provides us with another valuable measure with which to assess an important social cognitive correlate of physical activity in MS. Study Limitations It is important to acknowledge a number of important limitations that must be considered in the interpretation of these data. Our study is limited in the sense that it is cross-sectional and focuses on primarily white females with MS who were well-educated, ambulatory, and generally unimpaired based on PDDS scores. This, of course, is not a sample that is representative of the larger population of persons with MS, although for the purpose of verifying the factor structure of a measure such an approach may suffice. However, we believe that it is important to conduct further cross-validation analyses of the Multidimensional Outcome Expectations for Exercise Scale in larger samples of persons with MS who are likely to be more impaired than our sample and who represent a broader strata of socioeconomic status. Whether the Multidimensional Outcome Expectations for Exercise Scale is suitable for the assessment of outcome expectation in persons with other neurologic diseases also remains to be determined. In addition, we note that we did not collect data for this validation effort on other functional impairments associated with MS such as vision and cognitive problems and bladder and bowel incontinence. These issues as well as the progressive nature of physical impairments resulting from MS and inability of current treatment modalities to attenuate these declines are likely to influence individual perceptions of exercise and physical activity outcomes and should be considered in future studies. The present study represents a psychometric evaluation of a measure developed within an established theoretic framework, social cognitive theory. Our findings suggest that the Multidimensional Outcome Expectations for Exercise Scale has adequate construct validity in this sample of relatively well-functioning and ambulatory persons with MS. It does not attempt to place outcome expectations and other social cognitive constructs within the framework of a clinical model. Such an endeavor is beyond the scope of these data and this article. However, we do recognize the importance of such a clinical model for describing how chronic and disabling diseases influence outcome expectations. Clearly, validation of the

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psychometric properties of the Multidimensional Outcome Expectations for Exercise Scale in a more diverse sample of persons with MS is needed to determine this. This will allow clinicians to best determine how outcome expectations might operate in patient perception of disease progress and how such expectations might change as impairment progresses. CONCLUSIONS As noted earlier, the interest in physical activity as a potentially useful behavioral modality for improving health and well-being in this population has gained increasing popularity. However, we know very little about what MS patients perceive as being the benefits associated with being physically active, whether these benefits differ by type of MS or duration of condition and, therefore, which type of outcome expectations may be the most prevalent and under which conditions. Such knowledge might allow health promotion specialists and health care personnel to plan appropriate strategies for changing or enhancing outcome expectations. The present study provides encouraging support for the psychometric properties of the Multidimensional Outcome Expectations for Exercise Scale in a somewhat limited sample of well-educated, relapse-free, and ambulatory adults with MS. As the measure is further validated in more diverse samples of persons with MS, researchers and clinicians alike will be able to examine the roles played by outcome expectations in physical activity behavior change. References 1. Motl RW, McAuley E, Snook EM. Physical activity and multiple sclerosis: a meta-analysis. Mult Scler 2005;11:459-63. 2. Motl RW, Snook E, McAuley E. Physical activity and its correlates among people with multiple sclerosis: literature review and future directions. In: Columbus F, editor. Progress in multiple sclerosis research. Hauppauge: Nova Science; 2005. p 185-201. 3. Motl RW, Gosney JL. Effect of exercise training on quality of life in multiple sclerosis: a meta-analysis. Mult Scler 2008;14:129-35. 4. Motl RW, McAuley E, Snook EM, Gliottoni RC. Physical activity and quality of life in multiple sclerosis: intermediary roles of disability, mood, pain, self-efficacy, and social support. Psychol Health Med 2009;14:111-24. 5. Bandura A. Health promotion by social cognitive means. Health Educ Behav 2004;31:143-64. 6. Bandura A. The explanatory and predictive scope of self-efficacy theory. J Soc Clin Psychol 1986;4:359-73. 7. McAuley E, Blissmer B. Self-efficacy determinants and consequences of physical activity. Exerc Sport Sci Rev 2000;28:85-8. 8. Bandura A. The anatomy of stages of change [editorial]. Am J Health Promot 1997;12:8-10. 9. McAuley E, Motl RW, Morris KS, et al. Enhancing physical activity adherence and well-being in multiple sclerosis: a randomised controlled trial. Mult Scler 2007;13:652-9. 10. Motl RW, Snook EM, McAuley E, Scott JA, Douglass ML. Correlates of physical activity among individuals with multiple sclerosis. Ann Behav Med 2006;32:154-61. 11. King AC. The coming of age of behavioral research in physical activity. Ann Behav Med 2001;23:227-8. 12. Williams DM, Anderson ES, Winett RA. A review of the outcome expectancy construct in physical activity research. Ann Behav Med 2005;29:70-9. 13. Wójcicki TW, White SM, McAuley E. Assessing outcome expectations in older adults: the multidimensional outcome expectations for exercise scale. J Gerontol B Psychol Sci Soc Sci 2009;64:33-40. 14. Gecht MR, Connell KJ, Sinacore JM, Prohaska TR. A survey of exercise beliefs and exercise habits among people with arthritis. Arthritis Care Res 1996;9:82-8.

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15. Kim KK, Horan ML, Gendler P, Patel MK. Development and evaluation of the Osteoporosis Health Belief Scale. Res Nurs Health 1991;14:155-63. 16. Gosney JL, Scott JA, Snook EM, Motl RW. Physical activity and multiple sclerosis: validity of self-report and objective measures. Fam Community Health 2007;30:144-50. 17. Motl R, McAuley E, Snook E, Scott J. Validity of physical activity measures in ambulatory individuals with multiple sclerosis. Disabil Rehabil 2006;28:1151-6. 18. Godin GS, Shephard RJ. A simple method to assess exercise behavior in the community. Can J Appl Sport Sci 1985;10:141-6. 19. Schwartz CE, Coulthard-Morris L, Zeng Q, Retzlaff P. Measuring self-efficacy in people with multiple sclerosis: a validation study. Arch Phys Med Rehabil 1996;77:394-8. 20. McAuley E. Self-efficacy and the maintenance of exercise participation in older adults. J Behav Med 1993;16:103-13. 21. Ware JE, Kosinski M, Keller SD. A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity. Med Care 1996;34:220-3. 22. McAuley E, Konopack JF, Motl RW, Rosengren K, Morris KS. Measuring disability and function in older women: psychometric properties of the Late-Life Function and Disability Instrument. J Gerontol A Biol Sci Med Sci 2005;60:901-9. 23. Motl RW, Snook E, Gosney JL, McAuley E. Measuring disability and function in individuals with multiple sclerosis: psychometric properties of the Late-Life Function and Disability Instrument. In: Goldfarb PM, editor. Psychological tests and testing. Hauppauge: Nova Science Publishers; 2007. p 251-63. 24. Hadjimichael O, Kerns RD, Rizzo MA, Cutter G, Vollmer T. Persistent pain and uncomfortable sensations in persons with multiple sclerosis. Pain 2007;127:35-41. 25. Muthén LK, Muthén BO. Mplus user’s guide. Los Angeles: Muthén & Muthén; 2006. 26. Arbuckle JL. Full information estimation in the presence of incomplete data. In: Schumacker RE, Marcoulides GA, editors. Advanced structural equation modeling. Mahwah: Lawrence Erlbaum Associates Inc; 1996. p 243-77. 27. Enders CK. A primer on maximum likelihood algorithms available for use with missing data. Structural Equation Modeling. 2001;8:128-41. 28. Enders CK, Bandalos DL. The relative performance of full information maximum likelihood estimation for missing data in structural equation models. Struct Equ Modeling 2001;8:430-57. 29. Joreskog KG, Sorbom D. LISREL 8: User’s reference guide. Chicago: Scientific Software International; 1996. 30. Browne MW, Cudeck R. Alternative ways of assessing model fit. In: Bollen KA, Long JS, editors. Testing structural equation models. Newbury Park: Sage; 1993. p 136-62. 31. Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Modeling 1999;6:1-55. 32. Bentler PM. Fit indexes, lagrange multipliers, constraint changes and incomplete data in structural models. Multivariate Behav Res 1990;25: 163-72. 33. Snook EM, Motl RW. Effect of exercise training on walking mobility in multiple sclerosis: a meta-analysis. Neurorehabil Neural Repair 2009;23:108-16. 34. Stuifbergen AK. Barriers and health behaviors of rural and urban persons with MS. Am J Health Behav 1999;23:415-25. 35. Zalewski K. Exploring barriers to remaining physically active: a case report of a person with multiple scleroris. J Neurol Phys Ther 2007;30:40-5. Supplier a. Model 7164 version; Manufacturing Technology Inc, (MTI), 70 Ready Ave NW, Fort Walton Beach, FL 32548. b. Muthén & Muthén, 3463 Stoner Ave, Los Angeles, CA 90066.

Arch Phys Med Rehabil Vol 91, January 2010