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Self-Management, Perceived Control, and Subjective Quality of Life in Multiple Sclerosis An Exploratory Study

Rehabilitation Counseling Bulletin Volume 52 Number 1 October 2008 45-56 © 2008 Hammill Institute on Disabilities 10.1177/0034355208320000 http://rcb.sagepub.com hosted at http://online.sagepub.com

Malachy Bishop University of Kentucky, Lexington

Michael P. Frain Florida Atlantic University, Boca Raton

Molly K. Tschopp Ball State University, Muncie, Indiana Self-management has been shown to increase perceived control over both illness and nonillness aspects of life among people with chronic conditions but has not received significant research attention among persons with multiple sclerosis (MS). Based on relationships proposed in the illness intrusiveness and disability centrality models, this study explored the relationships between subjective and objective measures of MS impact, self-management, perceived control, and subjective quality of life (SQOL). A sample of 157 adults with MS participated in this research. The results suggest that self-management is strongly associated with perceived control and that both perceived control and self-management mediate the relationship between MS impact and SQOL. The rehabilitation counseling implications of these findings are discussed. Keywords:

M

psychosocial adaptation; quality of life; multiple sclerosis; self-management; perceived control; adherence

ultiple sclerosis (MS) is one of the most common acquired neurological illnesses and is the leading cause of neurological disability in early to middle adulthood. Generally diagnosed during early adulthood, MS is a chronic and typically progressive condition associated with an array of physical and cognitive symptoms and an unpredictable course and prognosis. As a result of the uncertainty associated with the course, symptoms, and prognosis of MS, a reduced sense of control is frequently reported. The perception of reduced control, described as a hallmark of MS, has been associated with such outcomes as depressed mood, hopelessness, reduced quality of life (QOL), and poor psychosocial adjustment (Devins & Shnek, 2000; McNulty, Livneh, & Wilson, 2004; Mishel, 1988; Wineman, O’Brien, Nealon, & Kaskel, 1993; Wineman, Schwetz, Goodkin, & Rudick, 1996). The significant impact of reduced control on the individual and his or her ability to achieve personal and rehabilitation goals makes identifying rehabilitation counseling interventions to address this aspect of living with MS an important pursuit. Self-management has been identified as an important means of increasing perceived control over chronic

illness and enhancing QOL (Devins & Shnek, 2000; Lorig, 1993). Self-management has been broadly defined as learning and practicing the skills necessary to carry on an active and emotionally satisfying life in the face of a chronic condition (Lorig, 1993). Self-management has been found to be associated with increased perceived control over both illness and nonillness aspects of life among people with a variety of chronic illnesses (Devins & Shnek, 2000; Dilorio, Faherty, & Manteuffel, 1992; Lorig, Gonzalel, Laurent, Morgan, & Laris, 1998); however, self-management has not yet received significant research attention among persons with MS (Devins & Shnek, 2000; Stutely, Hewett, & Wheeler, 2004).

Authors’ Note: This work was supported by a Pilot Research Award from the National Multiple Sclerosis Society. The authors would like to acknowledge the assistance of Doug Dressman (president), Sonya Sandridge (director of chapter programs), and the staff and volunteers of the National Multiple Sclerosis Society, Kentucky-Southeast Indiana Chapter; and Beth Smith (vice president of programs) and the staff and volunteers of the National Multiple Sclerosis Society, Mid South Chapter. Elizabeth Lowe and Christina T. Espinosa assisted in the data collection and analysis.

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46 Rehabilitation Counseling Bulletin

The purpose of the research described in this article was to explore the relationships between perceived control, self-management, and subjective quality of life (SQOL) among a sample of adults with MS. Specifically, based on relationships proposed in the illness intrusiveness (Devins, 1994; Devins et al., 1983) and disability centrality (Bishop, 2005a, 2005b) models, we explored (a) the relationship between self-management and perceived control and (b) the hypothesis that these variables act as mediators in the relationship between MS impact and SQOL. The following discussion provides an overview of the elements of this study, including MS, self-management, and perceived control, and describes the theory-based framework on which this study is based. Following this, the results of the study are presented and their practical implications for rehabilitation counseling are described.

Multiple Sclerosis: Overview MS affects approximately 400,000 people in the United States, and worldwide prevalence estimates range from 1 to 2.5 million (Munschauer & WeinstockGuttman, 2005; National Multiple Sclerosis Society [NMSS], 2006). MS is a chronic degenerative disease of the central nervous system characterized by demyelination (destruction of the myelin sheath) and subsequent damage to central nervous system axons. Thought to be an autoimmune disorder, the complex pathophysiological mechanisms of MS are not yet fully understood, although significant progress toward understanding has been made in the past several years. Usually diagnosed between the ages of 20 and 40, the median age at onset of MS is 28. Fifty percent of persons with MS require an assistive walking device within 15 years of diagnosis, and 83% after 30 years (Munschauer & WeinstockGuttman, 2005). Typically presenting with a relapsing– remitting course, after an average of 15 years, most people with MS experience a secondary progressive phase wherein the course becomes either continuously progressive or progresses between exacerbations (Johnson et al., 2006). The processes by which MS affects the central nervous system can result in an array of symptoms. The most commonly reported symptoms include changes in mood; alterations in cognitive functioning, including problems with memory, attention, and problem solving; bowel and bladder dysfunction; fatigue; pain; balance problems and difficulties with walking; vision problems; spasticity; abnormal sensations such as numbness or “pins and needles”; and sexual dysfunction (NMSS, 2006).

At this time, there is no cure for MS, and treatment includes lifelong disease and symptom management (Munschauer & Weinstock-Guttman, 2005). Currently, several disease-modifying therapies (DMTs) form the basis of treatment for relapsing MS and secondary progressive MS. These medications can reduce the frequency and severity of relapses and resulting disability (Munschauer & Weinstock-Guttman, 2005). The DMTs have been shown in clinical trials to reduce the number and severity of attacks by more than 30%, reduce disease activity by up to 75%, and prolong the onset of disability by nearly 40% in individuals with both relapsing– remitting MS and secondary progressive MS (Johnson et al., 2006). To achieve the maximum benefit from DMTs, patients with MS must adhere closely to the prescribed therapeutic regimen and continue treatment throughout the course of the disease (Munschauer & Weinstock-Guttman, 2005). It is unfortunate that survey research suggests that only 50% of all MS patients in the United States and 60% of those with relapsing–remitting MS are using DMTs, and many people who initiate therapy discontinue after a brief duration (Johnson et al., 2006). Many factors have been identified as affecting therapy adherence, including medication side effects (e.g., flu-like symptoms, injection site reactions), self-injection anxiety, concerns about the cost-effectiveness of treatment, patients’ lack of knowledge about DMTs, lack of visible results or improvements in functional status, low treatment self-efficacy, and cognitive or physical impairment (Johnson et al., 2006; Munschauer & Weinstock-Guttman, 2005).

Self-Management Self-management is a complex and evolving construct. The term has traditionally been defined in terms of medical disease management and treatment compliance, but more recent conceptions incorporate a broader and more patient-centered perspective. Self-management is generally considered to be a multidimensional construct, incorporating elements of illness treatment management, relationships with health care providers, and general coping or QOL (Devins & Shnek, 2000; Dilorio et al., 1992; Lorig, 1993). Corbin and Strauss (1988) defined self-management in terms of three tasks: (a) caring for the disease, including medication and treatment adherence, visiting physicians, and caring for oneself through exercise and diet; (b) maintaining and engaging in one’s normal life activities, including work and leisure activities, and maintaining social relationships; and (c) coping emotionally with

Bishop et al. / Self-Management in MS 47

the feelings associated with living with the disease and realizing and developing a new sense of future. This definition is typical of recent definitions found in the selfmanagement literature (e.g., Devins & Shnek, 2000; Dilorio et al., 1992; Kralik, Koch, Price, & Howard, 2004; Lorig, 1993) in that it is multidimensional and incorporates elements of medical treatment and relationships with caregivers, as well as more personal and broadly based elements of behavioral strategies to maintain health and prevent or alleviate symptoms, and coping with a chronic illness. Self-management has received relatively little research attention among persons with MS (Devins & Shnek, 2000; Stutely et al., 2004), and with the exception of the recently developed instrument used in this study, no self-management scales have been developed specifically for use with persons with MS. In this study, selfmanagement was measured using the Multiple Sclerosis Self-Management Scale (MSSM), which was developed to provide a comprehensive and psychometrically sound assessment of self-management among adults with MS (Bishop & Frain, 2007). Designed specifically for use with persons with MS, the MSSM incorporates both general elements of chronic illness self-management and elements that are specifically relevant to persons with MS.

Perceived Control The belief that one has control over one’s life has been identified as a central human motivation, and its various social, emotional, and adaptive benefits have long been a focus of general psychological research (Thompson, 2002). The construct of perceived control has been defined somewhat differently by researchers working from different theoretical perspectives (for reviews, see Bandura, 1997; Jacelon, 2007) but may be generally defined as a person’s self-assessment of the ability to exert control over his or her life (Thompson, 2002). Perceived control has been defined by some researchers as relating to specific domains of behavior, such as control over one’s symptoms (Wallhagen & Brod, 1997), and by others as a global construct, or general belief that a desired outcome can be achieved through personal agency (Carver et al., 2000). Perceived control is conceptually similar to, and has sometimes been defined so as to incorporate, such related theoretical constructs as self-efficacy (Bandura, 1997), generalized self-efficacy (Wallston, 1989), mastery (Kempen, Vansonderen, & Ormel, 1999), and locus of control (Rotter, 1954). The perception of control over one’s circumstances has been identified as a critical determinant of psychosocial

adaptation to chronic illness (Carver et al., 2000). In a rapidly expanding body of research, perceived control has been associated with a variety of positive health outcomes and adaptive processes among persons with chronic illnesses. Higher levels of perceived control have been associated with reduced anxiety and depression, better physical health, reduced impairment in daily living, higher levels of subjective well-being, and an increased likelihood that an individual will take action to improve or protect his or her physical health (Affleck, Tennen, Pfeiffer, & Fifield, 1987; Bandura, 1997; Carver et al., 2000; Endler, Kocovski, & Macrodimitris, 2001; Thompson, 2002). Conversely, low levels of perceived control have been associated with higher levels of depression and anxiety, increased physiological reactivity to stress, and depressed immune function (Thompson, 2002). Among persons with MS, low perceived control has been identified by several researchers as playing a key role in the development of negative psychosocial consequences (e.g., Devins, Seland, Klein, Edworthy, & Saary, 1993; Devins & Shnek, 2000; Johnson, Amtmann, Yorkston, Klasner, & Kuehn, 2004; Mullins et al., 2001). In this study, perceived control was operationalized in the context of the disability centrality model (Bishop, 2005a, 2005b). Consistent with extant definitions, in this QOL-based model of psychosocial adaptation, perceived control is defined as a person’s belief that he or she has the ability to effect change in various areas of life to maintain satisfaction in the face of changing conditions and expectations (Bishop, 2005a).

Self-Management, Perceived Control, and Quality of Life: Conceptual Framework Prior research among people with a variety of chronic conditions has shown that higher levels of self-management are associated with increased perceived control over both illness and nonillness aspects of life (Dilorio et al., 1992; Lorig et al., 1998). This research explored this relationship among persons with MS but also simultaneously examined the relationship of self-management and perceived control to subjective quality of life (SQOL). The following discussion describes the theory-based mechanisms by which these relationships are proposed to exist. In his illness intrusiveness model, Devins (1994; Devins et al., 1983) proposed that various illness and treatment factors associated with chronic illness compromise psychosocial well-being both directly, by reducing positively reinforcing outcomes of participation in meaningful and valued activities, and indirectly, by reducing feelings of personal control by limiting the ability to

48 Rehabilitation Counseling Bulletin

obtain positive outcomes or avoid negative ones (Devins, Mandin, Beanlands, & Paul, 1997). The impact of MS on well-being may, thus, be said to be mediated by perceived control as well as by satisfaction in life domains identified in prior research (see Devins et al., 1983) as being important to one’s QOL. Frazier, Tix, and Barron (2004) defined a mediator as a variable that explains the relationship between a predictor and an outcome. “In other words, a mediator is the mechanism through which a predictor influences an outcome variable” (p. 116). The mediating relationships proposed in the illness intrusiveness model have consistently found support in research among persons with MS and other chronic illnesses (e.g., Devins et al., 1997; Devins et al., 1993; Mullins et al., 2001). Similarly, perceived control and satisfaction have been shown to mediate the relationship between illness impact and SQOL among persons with MS and other disabilities in research evaluating the disability centrality model (Bishop, 2005a; Bishop, Stenhoff, & Shepard, 2007). In the disability centrality model, domain satisfaction and domain control are proposed to mediate the relationship between disability impact and SQOL, and domain importance is proposed to moderate the relationship between domain satisfaction and SQOL such that satisfaction in more important domains contributes disproportionately to overall SQOL (Bishop, 2005a; Bishop et al., 2007). By extension of the relationships proposed in these models, it has been suggested that interventions such as self-management, which increase an individual’s perceived control over a chronic illness, may be expected to ameliorate illness impact and produce broad-based positive effects on SQOL (Bishop, 2005b; Devins, 1994; Devins & Shnek, 2000). Although persons with a chronic illness may not have control over the course and symptoms of the illness, identifying available opportunities to exercise control over one’s condition may enhance predictability and perceived control. Such opportunities may include “obtaining extensive medical information, getting good medical care, following the course of treatment, reducing stress in their lives, improving overall fitness,” and otherwise taking an active role in their care (Thompson, 2002, p. 204). Thus, engaging in self-management, which collectively incorporates all of these behaviors, may enhance the perception of control. In this study, we explored whether, based on (a) the mediating role of perceived control proposed in these models and (b) the role of self-management in enhancing perceived control, self-management might also act to mediate the relationship between MS impact and SQOL, both independently and through its relationship with

perceived control. The hypotheses tested in this research were as follows: Hypothesis 1: Domain satisfaction, self-management, perceived control, and SQOL are positively correlated with each other and negatively correlated with MS impact. Hypothesis 2: Self-management and perceived control independently mediate the relationship between MS impact and SQOL. Hypothesis 3: Self-management and perceived control mediate the relationship between MS impact and SQOL in combination.

The cross-sectional nature of this research did not allow the testing of a temporal relationship between selfmanagement and perceived control, wherein higher levels of self-management may lead to higher levels of perceived control over time. The third hypothesis was examined based on the belief that such a synergistic relationship exists, such that a larger degree of mediation would be expected when the variables are considered together than would be seen with either variable in isolation. The impact of chronic illness may be operationalized in a number of ways, including the objectively measured severity of biological and physical processes, measured or reported functional limitations, and perceived psychosocial impact (Stein et al., 1987). In this study, two measures of MS impact were separately explored. The impact of psychological and physical symptoms was assessed using the Multiple Sclerosis Impact Scale–29 (MSIS-29; Hobart, Lamping, & Fitzpatrick, 2001), and subjective impact was assessed using the impact subscale of the Disability Centrality Scale (DCS; Bishop, 2005a). These scales are described in the following section.

Method Participants Data for this analysis were collected as part of an ongoing multiphase longitudinal research project. The participants in this study were adults with MS randomly selected from the mailing lists of two chapters of the NMSS located in the Southeastern United States. Five hundred participants were mailed the survey instrument, a letter of invitation, a statement of informed consent, and a description of the study. To ensure participant anonymity, staff at the NMSS chapters were responsible for selecting the participants and attaching mailing labels to the research packet on behalf of the researchers. At the time of this analysis, 199 completed questionnaires had been returned, providing a response rate to date of approximately 40%. When data for participants who had not completed a sufficient percentage of the items

Bishop et al. / Self-Management in MS 49

on each measure evaluated in this study were eliminated from the analysis, the total sample size was 157, providing an effective response rate of 31%. The mean age of the participants was 45.6 years (SD = 11.3). Approximately 82% of the sample was female (n = 129). Participants identified their race/ethnicity as White (non-Hispanic) (n = 145; 92.4%), African American (n = 8; 5.1%), Hispanic (n = 1; 0.6%), Native American (n = 1; 0.6%), and Other (n = 2; 1.3%). The majority of participants reported a monthly household income of $4,000 or more (28.7%), followed by those reporting income between $1,000 and $1,999 (19.7%), between $2,000 and $2,999 (17.8%), between $3,000 and $3,999, and less than $500 per month (2.5%). Participants reported their employment status as follows: employed full-time (38.9%), employed part-time (5.7%), unemployed— seeking work (2.5%), and unemployed—not seeking work (52.9%). The latter category included persons who identified themselves as retired, students, homemakers, and persons on permanent disability. Approximately two thirds (66.2%) were married, and the remainder identified themselves as single/never married (15.3%), divorced (3.8%), separated (3.1%), or widowed (11.5%). The average age at MS onset was 37.9 years. The average duration of MS since onset was 7.82 years (SD = 7.7). Seventy-nine percent (n = 124) reported that they were currently using MS medications.

Instruments Four research instruments were used in this study. These include the Delighted–Terrible Scale (DTS; Andrews & Withey, 1976), the DCS (Bishop, 2005a), the MSIS-29 (Hobart et al., 2001), and the MSSM (Bishop & Frain, 2007). Delighted–Terrible Scale. Subjective QOL was measured using the DTS. This single-item scale assesses participants’ feelings about their QOL as a whole using seven response categories, ranging from terrible (1) to delighted (7). The DTS has been used in hundreds of studies in the past three decades and has proved highly valid and reliable (Andrews & Robinson, 1991). Disability Centrality Scale. The DCS assesses the participants’ level of satisfaction, illness- or disability-related impact, and perceived control within 10 life domains, as well as the level of importance ascribed to each of the domains. The domains were identified based on a review of the literature and previous research by the first author (Bishop & Allen, 2003) and were selected as being those domains most frequently represented in multidimensional QOL instruments. The domains include the following (as

phrased on the questionnaire): physical health, mental health (e.g., emotional well-being, happiness, enjoyment of life), work (or studies), leisure activities (e.g., sports, hobbies, things you do to relax or have fun), financial situation, relationship with your spouse (or partner if not married), family relations, other social relations (e.g., friends, people who offer you support), autonomy/ independence (e.g., the ability to do the things you want, independence, freedom), and religious/spiritual expression (e.g., spiritual health, church life, relationship with God). The participants responded to the following questions for each of the 10 domains based on a 7-point interval scale ranging from not very to very, followed by the appropriate descriptor (e.g., “not very important”): 1. 2. 3. 4.

How important is this part of your life to your overall quality of life? How satisfied are you with how this part of your life is going? How much control do you have over changing this part of your life? How much does your illness or disability and/or its treatment impact your ability to function in this area of your life as you would like to?

In this study, reliability analysis of the DCS indicated that the scale had an acceptable level of internal consistency (Cronbach α = .82). The four component scales had the following Cronbach’s coefficient alphas: satisfaction (Cronbach α = .87), control (Cronbach α = .87), impact (Cronbach α = .88), and importance (Cronbach α = .74). Multiple Sclerosis Self-Management Scale. Self-management was assessed using the MSSM (Bishop & Frain, 2007). This 40-item scale was developed to provide a multidimensional assessment of self-management knowledge and behavior among adults with MS. Initial item development for the MSSM was based on a review of the MS and self-management literature, existing selfmanagement instruments, and professional consultation. A review of both the self-management literature and existing self-management instruments led to the identification of a set of elements typically included in selfmanagement instruments, including aspects of the relationship with medical care providers, self-efficacy, knowledge and understanding of one’s illness, and social and informational barriers and resources. Through a review of the MS literature and consultation with professionals in neurology and MS advocacy, additional items specific to MS were developed, including items concerning adherence to treatment, barriers to adherence, knowledge about MS and access to MS information, and health-maintenance behaviors (Bishop & Frain, 2007).

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An initial version of the MSSM was pilot tested among a sample of 102 individuals with MS. Based on the results of the pilot study, several items were revised or eliminated and additional items were developed to better address factors that were judged to be lacking sufficient information. The revised MSSM included 40 items, scored on a 5-point Likert-type scale. The revised version was then administered to a sample of 266 adults with MS, and its factor structure, reliability, and validity were assessed (Bishop & Frain, 2007). Construct validity of the MSSM was supported by factor analysis and correlation of the MSSM with other constructs known to be related to self-management. The MSSM was significantly positively correlated with QOL ratings and significantly negatively correlated with psychological and physical impact of MS, as measured with the MSIS-29 (Hobart et al., 2001). Internal consistency reliability for the scale was found to be acceptable (α = .86) in this initial analysis (Bishop & Frain, 2007). In this study, a Cronbach’s coefficient alpha of .84 was calculated for the scale. The scores were converted to a 100-point scale. Scores on the converted scale ranged from 45 to 93 with a mean of 74.85 (SD = 10.14). Higher scores indicate higher levels of self-management knowledge and behavior. The MSSM is made up of seven factor analytically derived scales measuring a range of self-management domains and behaviors (Bishop & Frain, 2007). The first factor, termed “treatment adherence,” includes several items addressing the participant’s attitude toward adherence, barriers to treatment maintenance, and understanding of the purpose of treatments. The second factor, “care provider–patient relationship,” addresses elements of communication with health care providers and degree of participation in treatment decision making. The third factor addresses “emotional health and social support/resources,” including feelings about self, adherence self-efficacy, and support from family members and others. The fourth factor, “health and symptom awareness,” addresses knowledge of and participation in symptom management behaviors. The fifth factor, “MS knowledge and information,” addresses the individual’s understanding of MS and active information seeking behavior. The sixth factor, termed “health maintenance behavior,” assesses awareness of and participation in positive health behaviors. The final factor, “communication about symptoms/changes,” explores the participant’s comfort and willingness to discuss problems and changes with health care providers (Bishop & Frain, 2007). Multiple Sclerosis Impact Scale–29. The MSIS-29 is a measure of the physical and psychological impact of MS from the patient’s perspective. It assesses the individual’s

experience with a range of physical, cognitive, and emotional symptoms over the preceding 2-week period. Original psychometric evaluation of this scale was conducted in two large independent postal surveys of randomly selected, geographically stratified members of the NMSS. It has since been evaluated in several additional studies and found to be a valid and reliable instrument for assessing the physical and mental impact of MS (Hobart, Riazi, Lamping, Fitzpatrick, & Thompson, 2005; McGuigan & Hutchinson, 2004). Reliability analysis of the MSIS-29 in this study showed that the scale had a high level of internal consistency (Cronbach α = .97). The MSIS-29 was used in this study as one means of assessing MS impact. The MSIS-29 provides a physical impact score, based on items related to physical limitations and symptoms, and a psychological impact score, based on items related to cognitive limitations and emotional or psychological symptoms. These scores were converted to a 100-point scale according to the directions provided by the scale developers (Hobart, Riazi, Lamping, Fitzpatrick, & Thompson, 2004) and then summed to create a combined score. The distribution of scores on the combined scale approximated a normal distribution and ranged from 0 to 200, with a mean of 90.6 (SD = 48.9). Higher scores on this scale indicate a higher level of impact. It should be noted that combining the physical and psychological impact scores into an overall impact score has been identified as permissible by the MSIS-29 developers, as the total scale satisfies criteria as a summed rating scale (Hobart et al., 2001). The scale’s developers do not, however, recommend use of an overall summary score for clinical trials or epidemiological studies for several reasons. First, evidence indicates that the two scales are measuring related but distinct constructs (Hobart et al., 2001). Second, the physical and psychological scales are not the only important variables impacting the individual with MS. Thus, to consider the overall score achieved by combining the physical and psychological scales as a comprehensive measure of MS impact could be misleading (J. Hobart, personal communication, November 27, 2007). We elected to combine the scores in this study due to its exploratory nature and because MS impact was simultaneously measured with the inclusion of a corollary, more comprehensive assessment of MS impact in the form of the impact subscale of the DCS.

Statistical Analysis Zero-order correlation coefficients were calculated to evaluate the hypothesized relationships between selfmanagement, control, the MS impact variables, and SQOL.

Bishop et al. / Self-Management in MS 51

Tests of the proposed mediating roles of self-management and control in the relationship between MS impact variables and overall SQOL were conducted using the criteria outlined by Baron and Kenny (1986) and Holmbeck (1997), including (a) that the predictor variable (MS impact) has an effect on the mediators, (b) that the predictor variable and the proposed mediator each have an effect on the outcome variable (SQOL) when considered separately, and (c) that the predictor variable’s effect on the outcome variable is significantly less when the mediator is in the model than when the mediator is not in the model. Path analytic methods (AMOS; Arbuckle & Wothke, 1999) were used to assess mediation. Although the sample size in this study was lower than the 200 recommended for assessing mediation using structural equation modeling, this approach was chosen over the more frequently used regression method because it provides overall goodness-of-fit estimates, minimizes measurement error, and is recommended for models exploring multiple mediators (Frazier et al., 2004). Mediation analysis was conducted using the following procedures (Holmbeck, 1997; Hoyle & Smith, 1994). First, the fit of the direct effect model (MS impact–SQOL) was assessed to establish the effect of the predictor variable on the outcome variable. If this model had an adequate fit, the fit of the full model (including the mediating paths) was then assessed. The full model should provide an adequate fit, and the coefficients of the direct path (MS impact–SQOL), and the paths from the predictor variable to the mediators, and from the mediators to the outcome variable should all be significant and in the directions predicted. A mediational effect is supported if, when the mediating paths are included, the fit of the model improves and the predictor–outcome path is reduced (Hoyle & Smith, 1994). In the case of full mediation, the previously significant predictor–outcome path is reduced to nonsignificance. If this direct path is reduced but remains significant, partial mediation is evident. Separate mediation analyses were conducted for each of the MS impact variables, including the impact subscale of the DCS, hereafter referred to as subjective impact, and the combined physical and psychological impact scales of the MSIS-29, hereafter referred to as symptom impact. In both sets of analyses, the mediating effects of self-management and control were tested first independently and then as related variables by adding an additional path representing this relationship to the model. Three goodness-of-fit indices were examined to test the overall model. These indices included the comparative fit index (CFI), Bollen incremental fit index (IFI), and root mean square error of approximation (RMSEA). Acceptable goodness-of-fit in this study is

typically defined as CFI and IFI values of .90 or higher, and RMSEA values of less than .05 (Kline, 2005). Prior to the analyses, the variables were inspected to determine whether assumptions of normality and linearity were met. Although the model variables were skewed, none of the skewness values exceeded ±.60 and were, therefore, judged appropriate for further analysis (Tabachnick & Fidell, 2001). A visual examination of the correlational matrix suggested that some of the predictor variables had relatively high intercorrelations. Therefore, prior to running the subsequent analyses, we examined the tolerance and variance inflation factor (VIF) for each variable, with tolerance < .10 or VIF > 10, indicating that multicollinearity may be an issue. In each case, tolerance was well above the .10 range and VIF was well below the 10 value that is considered cause for multicollinearity concerns (Pedhazur, 1997). Due to correlations among the model variables, each model variable was normalized prior to entry into the models. Normalization minimizes the degree of association between the variables and reduces the likelihood that multicollinearity is distorting the estimated parameters (Cronbach, 1987).

Results Intervariable Correlations Zero-order correlation coefficients were calculated to examine correlations between the model variables, including MSIS combined score, MSSM score, SQOL, and the impact scale score and perceived control scale scores from the DCS. The domain importance and satisfaction scores from the DCS were also included in the analysis as a single score in which the two scale scores were multiplied to produce an interaction term. As presented in Table 1, self-management, perceived control, the importance-satisfaction interaction term, and SQOL were all significantly positively correlated with each other and significantly negatively correlated with the two measures of MS impact.

Mediation Analyses In the mediation analyses, the fit of the direct effects model (MS impact–SQOL) was first assessed. The direct effects model testing the subjective impact of MS (DCS impact scale) on SQOL was judged to demonstrate adequate fit (CFI = .971; IFI = .971), although the RMSEA was higher than desired (RMSEA = .14) and the chi-square test statistic was significant, p = .000. The path coefficient from subjective MS impact to SQOL was significant and negative, β = –.38, t(1, 155) = –5.09, p < .001. The direct

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Table 1 Intercorrelations Among Variables Variable 1. SQOL 2. MSIS combined 3. MSSM 4. Control 5. Impact 6. Import/satisfaction

1

2

3

4

5

6

— –.642* — .482* –.376* — .687* –.695* .425* — –.380* .429* –.241* –.367* — .668* –.657* .420* .812* –.379* —

Note: SQOL = Delighted–Terrible Scale; MSIS combined = Multiple Sclerosis Impact Scale–29, Physical Impact Scale, and Psychological Impact Scale (note that higher scores on this scale indicate higher levels of impact); MSSM = Multiple Sclerosis Self-Management Scale; Control and Impact = mean scores across domains on the Disability Centrality Scale; and Import/satisfaction = interaction term: product of mean importance and satisfaction scores across domains on the Disability Centrality Scale. *p < .01.

effects model of the symptom impact score (combined MSIS-29 scores) on SQOL also demonstrated adequate fit (CFI = .914; IFI = .920), although the RMSEA was once again higher than desired (RMSEA = .15) and the chi-square test statistic was significant, p = .000. The path coefficient from combined MSIS-29 scores to SQOL was also significant and negative, β = –.64, t(1, 155) = –9.973, p < .001. Although both models suggested only adequate fit to the data, the size, direction, and significance of the path coefficient suggested that the requirement of a predictor–outcome effect was met, and so the full models, including the mediator variables, were then evaluated. The full model for subjective impact provided a slightly improved fit (CFI = .981; IFI = .98; RMSEA = .14), although the chi-square test statistic was still significant, p = .000. With the inclusion of the mediating paths, however, the path coefficient from subjective MS impact to SQOL was no longer significant, β = –.111, t(4, 155) = –1.802, p = .074, signifying full mediation. Figure 1 presents the standardized path coefficients for the mediating and direct paths, with the direct effects model coefficient in parentheses. The full model for symptom impact also provided an improved fit (CFI = .992; IFI = .991; RMSEA = .107), although the chi-square test statistic was still significant, p = .001. The path coefficient from symptom impact to SQOL remained significant but was reduced, β = –.007, t(4, 155) = –3.218, p = .002, suggesting partial mediation. Figure 2 presents the mediating and direct paths with the direct effects model coefficient in parentheses.

Figure 1 Mediating and Direct Standardized Path Coefficients for Subjective Multiple Sclerosis (MS) Impact DCS Domain Satisfaction/ Importance

–.094

.268

–.111 (ns)

DCS Domain Impact –.241

Subjective QOL

(–.38) .209 MS SelfManagement

–.367

.373

DCS Domain Control

Note: Direct effects model coefficient in parentheses. All paths significant at p < .05 unless noted. DCS = Disability Centrality Scale; QOL = quality of life.

Figure 2 Mediating and Direct Standardized Path Coefficients for Multiple Sclerosis (MS) Symptom Impact DCS Domain Satisfaction/ Importance

–.039

.025

–.007

Symptom Impact –.078

Subjective QOL

(–.64) .025

–.018

MS SelfManagement

.278

DCS Domain Control

Note: Direct effects model coefficient in parentheses. All paths significant at p < .05. DCS = Disability Centrality Scale; QOL = quality of life.

Finally, a theory-based modification to the full model was made to explore the effect of the positive relationship between self-management and perceived control. An additional path representing this relationship (from self-management to perceived control) was added to the model and the fit of this model was examined. With subjective impact as the predictor variable, this modified model provided an improved fit over the prior model (CFI = .998; IFI = .998; RMSEA = .10), and the chisquare test statistic became nonsignificant, p = .11. The

Bishop et al. / Self-Management in MS 53

Figure 3 Modified Full Model Standardized Path Coefficients for Subjective Multiple Sclerosis (MS) Impact DCS Domain Satisfaction/ Importance

–.094

Subjective QOL

(–.38)

DCS Domain Satisfaction/ Importance

–.173

.258

–.106 (ns)

DCS Domain Impact

Figure 4 Modified Full Model Standardized Path Coefficients for Multiple Sclerosis (MS) Symptom Impact

.211

–.249

Symptom Impact

Subjective QOL

(–.64)

–.241

–.362

.201 MS SelfManagement

.195 MS SelfManagement

.359

–.281

.265

–.617 .358

DCS Domain Control

.202

DCS Domain Control

Note: Direct effects model coefficient in parentheses. All paths significant at p < .05 unless noted. DCS = Disability Centrality Scale; QOL = quality of life.

Note: Direct effects model coefficient in parentheses. All paths significant at p < .05. DCS = Disability Centrality Scale; QOL = quality of life.

path coefficient from MS impact to SQOL remained nonsignificant, β = –.106, p < .069, suggesting full mediation. The modified model with symptom impact as the predictor variable also provided an improved fit over the prior model (CFI = .999; IFI = .998; RMSEA = .09), and the chi-square test statistic was nonsignificant, p = .126. The path coefficient from MS impact to SQOL remained significant but was reduced from the direct effects model, β = –.249, p = .002, suggesting partial mediation. These models are presented in Figures 3 and 4.

relational effect. It is unfortunate that the cross-sectional design of this study precludes addressing the question of temporal influence. That is, it is impossible to say whether engaging in self-management enhances perceived control over time. The relationships proposed in the disability centrality and illness intrusiveness models would suggest that such a relationship is likely, and longitudinal assessment of this question, which is currently under way, will further inform understanding of these relationships. Regardless of this limitation, the results underscore the importance of self-management among persons with MS in promoting both enhanced control and SQOL and have a number of important implications for rehabilitation counseling practice.

Discussion The results of this exploratory study are consistent with previous research suggesting a positive relationship between self-management and perceived control among persons with chronic illnesses. Hypotheses concerning the correlations between the study variables and the more complex mediating relationships derived from the disability centrality and illness intrusiveness models were supported. The subjective impact of MS on SQOL was fully mediated, and symptom impact was partially mediated by the three mediating variables, self-management, perceived control, and the satisfaction-importance interaction variable. When the path signifying the positive relationship between self-management and perceived control was included in the models, the fit of the models to the data was improved, signifying the identification of an important

Rehabilitation Counseling Interventions to Promote Self-Management Effective MS self-management involves a multidimensional approach to living with MS. Each dimension may present specific challenges to the individual. Examples of the elements of MS self-management include (a) understanding and staying up-to-date on information about this complex condition and emerging treatment options; (b) adhering to treatments that may be expensive, may require self-injection, and often have significant side effects; (c) participating in treatment decisions and communicating effectively with physicians; and (d) engaging in behaviors to maintain physical and

54 Rehabilitation Counseling Bulletin

emotional health. Rehabilitation counselors can promote self-management and assist clients to overcome challenges by understanding these elements and gaining an understanding of their clients’ personal experience with, and barriers to, self-management. This process of understanding can begin during the initial intake interview. Assessment of the client’s awareness of and participation in self-management behaviors is an important initial step in promoting self-management and identifying barriers. Such assessment may be accomplished either through an unstructured interview process or through the use of self-management inventories. As previously stated, there currently exist no MS-specific self-management scales, with the exception of the recently developed MSSM, which will require further psychometric evaluation before it is appropriate for clinical use. However, the above description of the MSSM’s scales and items may provide a useful guide for focusing the assessment interview. Self-management barriers may arise due to financial or resource limitations, lack of information, or barriers to accessing information, or may result from interpersonal, social, physical, cognitive, emotional, or attitudinal issues. Addressing these barriers effectively requires that rehabilitation counselors have both a general understanding of MS and its treatment and an awareness of the unique situation of the client. Simply asking clients about the cost and schedule of their treatment often elicits open responses concerning barriers faced by the client. Adherence to disease-modifying therapies is a critical self-management consideration for many persons with MS. It is the consensus of researchers and clinicians that DMTs can reduce future disease activity and improve quality of life for many individuals with relapsing forms of MS (NMSS, 2006). It is unfortunate that, as noted above, numerous barriers to DMTs maintenance exist. For persons struggling with the adverse effects of DMTs, the prescribing physician may be able to identify treatment modifications or corollary treatments to reduce adverse effects. The availability of resources to overcome financial obstacles should also be explored. Information about DMTs and resources for overcoming barriers to maintenance are available from the National MS Society and its many regional affiliates. Effective communication with physicians and other health care providers is another important component of self-management, promoting both a more comprehensive understanding of one’s condition and more participatory control in treatment decisions. Common barriers to such communication, including discomfort discussing various questions and asserting oneself with frequently hurried physicians, may be effectively addressed in the context of the rehabilitation counseling relationship. Helpful

interventions include assertiveness training and role playing to encourage more effective communication, and encouraging the client to prepare a list of questions or concerns prior to health care visits. Finally, asking questions both initially and at follow-up appointments about the client’s health behavior and goals and discussing any barriers to optimal health the client may be facing can reinforce the importance of self-management behaviors. Promoting positive physical and mental health and creating or reinforcing the client’s awareness of the relationship between health behaviors and MS are also important components of self-management.

Limitations This study has a number of limitations to internal and external validity that should be considered in interpreting the results. The response rate was relatively low, and the sample was geographically and demographically restricted, with only a small proportion of participants from racial or ethnic minority backgrounds. These factors may limit the generalization of the results to larger populations. Internal validity was threatened by the operationalization of the variables in the study. In particular, although combining the scale scores of the MSIS-29 into a single score was judged by the researchers to be a sound methodological approach to assessing combined psychological and physical symptoms, the scale was designed to provide two separate scores that are not typically combined. In addition, although the reliability of the DCS scales was acceptable, the variables measured with this instrument (satisfaction, perceived control, importance, and impact) are, like SQOL, broadly defined constructs that can be assessed by numerous other methods. Finally, due to the noted limitations with regard to the fit of the evaluated models, the results can best be considered exploratory until further analysis of the modeled relationships with a larger sample confirms the relationships.

Conclusion This study provided an analysis of the role of selfmanagement in relation to perceived control and SQOL among adults with MS. It represents the first research to directly explore these relationships among persons with MS. The results suggested that self-management is positively related to perceived control and partially mediates the impact of MS symptoms on SQOL. Although further research into the timing and nature of these relationships is needed, the results of this study clearly support the importance and benefit of engaging in self-management behaviors.

Bishop et al. / Self-Management in MS 55

Self-management is a multidimensional construct, made up of several distinct areas of complex behavior. Understanding the components of self-management and identifying specific rehabilitation counseling interventions to promote and encourage self-management remains an important pursuit. Although several rehabilitation counseling interventions to promote self-management were identified in this article, research aimed at further delineating clinically effective rehabilitation counseling interventions is needed.

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Malachy Bishop, PhD, CRC, is an associate professor and coordinator of the Rehabilitation Counseling Program in the Department of Special Education and Rehabilitation Counseling at the University of Kentucky. He conducts research in the areas of quality of life and psychosocial adaptation to chronic illness and disability. Michael P. Frain, PhD, CRC, is an assistant professor and Rehabilitation Counseling Program Director at the Florida Atlantic University, Boca Raton, Florida. His research interests include self-management and adherence in chronic illness, outcome research, Internet research design, and veterans rehabilitation. Molly K. Tschopp, PhD, CRC, is an assistant professor and the director of the Rehabilitation Counseling Program in the Department of Counseling Psychology and Guidance Services at Ball State University. Her research interests include attitudinal barriers, discrimination, stigma, advocacy, and empowerment issues.