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Depression in multiple sclerosis: Review and theoretical proposal

Published online by Cambridge University Press:  03 September 2008

PETER A. ARNETT ,
FIONA H. BARWICK  and
JOE E. BEENEY
PETER A. ARNETT*
Affiliation:
Psychology Department, Pennsylvania State University, University Park, Pennsylvania
FIONA H. BARWICK
Affiliation:
Psychology Department, Pennsylvania State University, University Park, Pennsylvania
JOE E. BEENEY
Affiliation:
Psychology Department, Pennsylvania State University, University Park, Pennsylvania
*
Correspondence and reprint requests to: Peter Arnett, Penn State University, Psychology Department, 522 Bruce V. Moore Bldg., College of the Liberal Arts, University Park, PA 16802-3105. E-mail: paa6@psu.edu
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Abstract

Because of its high prevalence and implications for quality of life and possibly even disease progression, depression has been intensively studied in multiple sclerosis (MS) over the past 25 years. Despite the publication of numerous excellent empirical research papers on this topic during that time, the publication of theoretical work that attempts to explain depression in a comprehensive way is scarce. In this study, we present a theoretical model that attempts to integrate existing work on depression in MS and provide testable hypotheses for future work. The model suggests that risk for depression begins with the onset of MS. MS results in disease-related changes such as increased lesion burden/brain atrophy and immunological anomalies that are associated with depression in MS, but explain only a relatively limited proportion of the variance. Common sequelae of MS including fatigue, physical disability, cognitive dysfunction, and pain, have all been shown to have an inconsistent or relatively weak relationship to depression in the literature. In the model, we propose that four variables—social support, coping, conceptions of the self and illness, and stress—may moderate the relationship between the above common MS sequelae with depression and help to explain inconsistencies in the literature. (JINS, 2008, 14, 691–724.)

Keywords

MSBrain atrophy and lesion damageDepression and cognitive functioningStress and copingFatiguePainSocial support

Information

Type
Critical Review
Information
Journal of the International Neuropsychological Society , Volume 14 , Issue 5 , September 2008 , pp. 691 - 724
Copyright
Copyright © The International Neuropsychological Society 2008

INTRODUCTION

The prevalence of depression is high in multiple sclerosis (MS), a chronic and common autoimmune disease that results in the destruction of myelin and gray matter atrophy in the central nervous system. The lifetime risk for depression has been estimated at around 50% (Patten & Metz, Reference Patten and Metz1997; Sadovnick et al., Reference Sadovnick, Remick, Allen, Swartz, Yee, Eisen, Farquhar, Hashimoto, Hooge, Kastrukoff, Morrison, Nelson, Oger and Paty1996), compared with a lifetime risk in the general population of around 10–15% (American Psychiatric Association, 1994). Because of its high prevalence, importance to quality of life and patients' well-being (Kenealy et al., Reference Kenealy, Beaumont, Lintern and Murrell2000), association with suicidality (Feinstein et al., Reference Feinstein, O'Conner and Feinstein2002), and possible influence on the disease course itself (Ackerman et al., Reference Ackerman, Rabin, Heyman, Anderson, Houch and Frank2000; Dalos et al., Reference Dalos, Rabins, Brooks and O'Donnell1983; Franklin et al., Reference Franklin, Nelson, Heaton, Burkes and Thompson1988; Mohr et al., Reference Mohr, Goodkin, Bacchetti, Boudewyn, Huang and Marrietta2000), depression has been intensively studied in MS. Nonetheless, although several brief, focused reviews of the literature have been conducted (Dalton & Heinrichs, Reference Dalton and Heinrichs2005; Siegert & Abernethy, Reference Siegert and Abernethy2006), and a practical consensus statement on depression published (Goldman Consensus Group, 2005) in recent years, no comprehensive theoretical model of depression in MS has been articulated. The goal of this article is to present an integrated theoretical model of depression in MS that links key findings in the literature, identifies gaps based on existing work, and makes suggestions for future research. We will begin with the articulation of a theoretical model that integrates a variety of factors that have been found to be associated with depression in MS. Following this, we will devote much of the rest of the review to providing some empirical support for the theoretical model.

A MODEL OF DEPRESSION IN MS

A model of depression in MS, incorporating several variables that have been shown to be associated with depression in MS samples, is shown in Figure 1. The onset of MS, depicted at the far left side of the figure, denotes the beginning of risk for depression in MS. As detailed later, all of the factors included in the model have some evidence supporting their association with depression. The “MS Disease Factors” have been directly associated with depression as well as with physical disability, cognitive dysfunction, pain, and fatigue. The “Common MS Sequelae” variables, including depression, are arranged in a circle, as evidence shows that they may be associated with one another as well as being related to disease factors and moderating variables. The “Possible Moderator” variables, which represent factors related to the external circumstances of individuals with MS or to their internal representations of those circumstances, are theorized to impact the relationship between the common MS sequelae and depression, but they have also been shown to be directly associated with depression in MS. They, too, are arranged in a circle, as they are theorized to interact with one another in addition to the common MS sequelae. Although depression is at the intersection of the two circles because it is the focus of the current review, any one of the common MS sequelae could be moved into the intersection from whence associations with disease factors and possible moderators could be systematically investigated. Thus, there is no implicit statement on the direction of influence in the model; rather, dynamic and complex relationships among the variables are likely, as described throughout.

Fig. 1.

Model of depression in multiple sclerosis (MS): Disease factors predict common MS sequelae.

We now turn to a review of the evidence supporting the association of the variables depicted in the model with depression in MS. Although most of the research on these variables has been correlational, thus making causal inferences problematic, the literature that has developed over the past 20 years provides impressive insight into the range of factors that may causally contribute to depression in MS. The review will start with disease factors associated with depression in MS. It will then examine some common MS sequelae that are sometimes associated with depression, followed by an examination of possible moderators in the relationship between these common MS sequelae and depression.

In the tables accompanying this article, where possible, we provide effect sizes for the different associations reported. Using the Cohen's (Cohen & Cohen, Reference Cohen and Cohen1983) framework, effect sizes (Cohen's d) between .20 and .49 were considered small, .50 to .79 moderate, and .80 and above large. Correlations from .20 to .29 were considered small, those from .30 to .49 moderate, and those .50 and above large.

FACTORS ASSOCIATED WITH DEPRESSION IN MS

MS Disease-Related Factors

A detailed review of the MS disease factors associated with depression in MS is beyond the scope of the present article. However, it is assumed that disease factors are distal causes of depression in MS either directly or via their influence on other variables in the model (see Figure 1). Of relevance to the current review is the finding that most studies have shown that risk for depression follows the onset of MS (Joffe et al., Reference Joffe, Lippert, Gray, Sawa and Horvath1987; Minden et al., Reference Minden, Orav and Reich1987; Sadovnick et al., Reference Sadovnick, Remick, Allen, Swartz, Yee, Eisen, Farquhar, Hashimoto, Hooge, Kastrukoff, Morrison, Nelson, Oger and Paty1996) (but cf. Sullivan et al., Reference Sullivan, Weinshenker, Mikail and Edgley1995).

The weight of most recent work favors an association between depression and demyelination, suggesting some disease-related contribution to depression in MS (Bakshi et al., Reference Bakshi, Czarnecki, Shaikh, Priore, Janardhan, Kaliszky and Kinkel2000a; Berg et al., Reference Berg, Supprian, Thomae, Warmuth-Metz, Horowski, Zeiler, Magnus, Rieckman and Becker2000; Fassbender et al., Reference Fassbender, Schmidt, Mofsner, Kischka, Kuhnen, Schwartz and Hennerici1998; Feinstein, Reference Feinstein2004; Pujol et al., Reference Pujol, Bello, Dues, Marti-Vilalta and Capdevila1997, Reference Pujol, Bello, Dues, Cardoner, Marti-Vilalta and Capdevila2000; Reischies et al., Reference Reischies, Baum, Brau, Hedde and Schwindt1988; Zorzon et al., Reference Zorzon, de Masi, Nasuelli, Ukmar, Mucelli, Cazzato, Bratina and Zivadinov2001). Certain brain regions may contribute disproportionately, as at least five published studies have reported greater temporal region involvement in depressed compared with nondepressed MS patients (Berg et al., Reference Berg, Supprian, Thomae, Warmuth-Metz, Horowski, Zeiler, Magnus, Rieckman and Becker2000; Feinstein et al., Reference Feinstein, Roy, Lobaugh, Feinstein, O'Connor and Black2004; Honer et al., Reference Honer, Hurwitz, Li, Palmer and Paty1987; Pujol et al., Reference Pujol, Bello, Dues, Marti-Vilalta and Capdevila1997; Zorzon et al., Reference Zorzon, de Masi, Nasuelli, Ukmar, Mucelli, Cazzato, Bratina and Zivadinov2001).

Depression in MS also appears to be related to changes in important immunological parameters caused by the disease process. Several studies show that higher levels of T4+ (helper/inducer) cell counts (Foley et al., Reference Foley, Miller, Traugott, LaRocca, Scheinberg, Bedell and Lennox1988) and higher levels of central nervous system (CNS) inflammation, as measured by cerebrospinal fluid white blood cell counts (Fassbender et al., Reference Fassbender, Schmidt, Mofsner, Kischka, Kuhnen, Schwartz and Hennerici1998), are associated with greater depression. Decreased depression has also been associated with reduced interferon-gamma production over time (Mohr et al., Reference Mohr, Goodkin, Islar, Hauser and Genain2001). Longitudinally, MS patients' period of greatest depression during a 2-year interval coincided with lower CD8+ (suppressor/cytotoxic) cell counts and higher CD4/CD8 ratio (Foley et al., Reference Foley, Traugott, LaRocca, Smith, Perlman, Caruso and Scheinberg1992). Taken together, the existing data suggest that depression in MS is associated with neuroimmunological and neurophysiological abnormalities.

Some associations have been established among disease-related factors and the common MS sequelae outlined in the model. Fatigue has been shown to be significantly associated with hyperintense MRI lesions in the brainstem and midbrain in at least one study (Moller et al., Reference Moller, Wiedemann, Rohde, Backmund and Sonntag1994), and with measures of axonal integrity (Tartaglia et al., Reference Tartaglia, Narayanan, Francis, Santos, De Stefano, Lapierre and Arnold2004). Cognitive problems in MS are associated with the extent of lesion damage in the brain (Arnett, Reference Arnett, Halligan, Kischka and Marshall2003; Rao et al., Reference Rao, Leo, Haughton, St. Aubin-Faubert and Bernardin1989a), gray matter hypointensities (Brass et al., Reference Brass, Benedict, Weinstock-Guttman, Munschauer and Bakshi2006), and especially atrophy (Benedict et al., Reference Benedict, Bruce, Dwyer, Abdelrahman, Hussein, Weinstock-Guttman, Garg, Munschauer and Zivadinov2006). Gray matter atrophy has also been shown to be associated with physical disability in MS (Pirko et al., Reference Pirko, Lucchinetti, Sriram and Bakshi2007), and primary dysfunction or lesion of the CNS is associated with pain in MS (Mersky & Bogduk, Reference Mersky and Bogduk1994).

Common MS Sequelae Associated With Depression That May Be Moderated by Other Variables

For the common MS sequelae shown in Figure 2, findings regarding their association with depression in the literature have been mixed. Inconsistent or weak associations between a predictor and criterion variable often indicate the existence of moderators (Baron & Kenny, Reference Baron and Kenny1986). Consideration of moderator variables may help to clarify the mixed relationships reported in the literature. Details on the studies summarized in this section can be found in Table 1. Note that the acronyms in this table and in Table 2 are defined in the Appendix.

Fig. 2.

Model of depression in multiple sclerosis (MS): Common MS sequelae predict depression. Note. The different types of lines in this and subsequent figures indicate the strength or weakness of the evidence supporting the influence of a particular factor on MS-related depression: An unbroken line indicates that evidence consistently supports the influence of that factor, a dashed line indicates that evidence for the influence of a particular factor appears to be less consistent on the surface but is more consistent when subject to careful analysis, and a dotted line indicates that the evidence supporting the influence of the particular factor is decidedly mixed. The thickness of the lines reflects the number of studies that have examined the influence of a particular variable on MS-related depression: Thicker lines indicate a greater number of studies, whereas thinner lines indicate fewer studies.

Table 1.

Studies examining the relationship between common disease sequelae and depression in MS

Table 1.

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Note

See Appendix for listing of all acronyms.

Table 2.

Studies examining relationship between proposed moderators and depression in MS

Table 2.

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Table 2.

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Table 2.

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Table 2.

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Table 2.

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Table 2.

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Note

See Appendix for listing of all acronyms.

Fatigue

Up to 88% of MS patients complain of significant fatigue (Krupp et al., Reference Krupp, Alvarez, LaRocca and Scheinberg1988), and 28% report fatigue as one of their most troubling symptoms. Additionally, fatigue has been identified by MS patients as the one symptom most responsible for them having to cut back on their work hours (Smith & Arnett, Reference Smith and Arnett2005), and patients identify fatigue as a central factor in their subsequently becoming unemployed (Edgley et al., Reference Edgley, Sullivan and Dehoux1991; Jackson et al., Reference Jackson, Quaal and Reeves1991). Thus, fatigue has significant real world consequences for patients.

The existing data examining the relationship between fatigue and depression in MS are more consistent than with the other sequelae. Eight studies have reported significant associations, whereas four have reported null results. Notably, all four studies reporting null results had much smaller sample sizes than the eight studies reporting significant associations, so low statistical power is likely to be an important contributor to the null findings. Two studies reported large effect sizes (Bakshi et al., Reference Bakshi, Shaikh, Miletich, Czarnecki, Dmochowski, Henschel, Janardhan, Dubey and Kinkel2000b; Fisk et al., Reference Fisk, Pontefract, Ritvo, Archibald and Murray1994; Kroencke, Reference Kroencke2000), one medium (Flachenecker et al., Reference Flachenecker, Kumpfel, Kallmann, Gottschalk, Grauer, Rieckmann, Trenkwalder and Toyka2002), and four small (Krupp et al., Reference Krupp, Alvarez, LaRocca and Scheinberg1988, Reference Krupp, LaRocca, Muir-Nash and Steinberg1989; Schwartz et al., Reference Schwartz, Coulthard-Morris and Zeng1996; Vercoulen et al., Reference Vercoulen, Swanink, Galama, Fennis, Jongen, Hommes, van der Meer and Bleijenberg1998). Three reported both medium and small effect sizes (Mohr et al., Reference Mohr, Hart and Goldberg2003; Schreurs et al., Reference Schreurs, de Ridder and Bensing2002; Voss et al., Reference Voss, Arnett, Higginson, Randolph, Campos and Dyck2002), and one reported both medium and large effects (Kroencke, Reference Kroencke2000). Although results did not reach traditional levels of statistical significance due to low statistical power, Krupp and colleagues' as well as the study by Vercoulen et al. had effect sizes in the small range. Thus, the bulk of the evidence suggests a relationship between depression and fatigue in MS that is in the small to moderate range of effect size.

Physical disability

The relationship between physical/neurological disability and depression in MS is more mixed in the literature than that between depression and fatigue. When operationalized using Kurtzke's (Kurtzke, Reference Kurtzke1983) Expanded Disability Status Scale (EDSS), some studies (11) have found no relationship between physical disability and depression. However, a comparable number of studies (11) have reported positive findings. The null findings in at least five studies (Fassbender et al., Reference Fassbender, Schmidt, Mofsner, Kischka, Kuhnen, Schwartz and Hennerici1998; Minden et al., Reference Minden, Orav and Reich1987; Moller et al., Reference Moller, Wiedemann, Rohde, Backmund and Sonntag1994; Pujol et al., Reference Pujol, Bello, Dues, Marti-Vilalta and Capdevila1997; Sabatini et al., Reference Sabatini, Pozzilli, Pantano, Koudriavtseva, Padovani, Millefiorini, DiBiasi, Gualdi, Salvetti and Lenzi1996) can be attributed, in part, to small sample size. Another study (Ron & Logsdail, Reference Ron and Logsdail1989) appeared to use a nonstandardized measure of disability. However, the remaining studies reporting null findings (Beatty et al., Reference Beatty, Goodkin, Hersgaard and Monson1990; Huber et al., Reference Huber, Rammohan, Bornstein and Christy1993; Provinciali et al., Reference Provinciali, Ceravolo, Bartolini, Logullo and Danni1999; Rabins et al., Reference Rabins, Brooks, O'Donnell, Pearlson, Moberg, Jubelt, Coyle, Dalos and Folstein1986; Schreurs et al., Reference Schreurs, de Ridder and Bensing2002) had reasonably large sample sizes and used standard measures of depression and disability. Mixed findings such as these suggest the presence of moderators.

Regarding effect sizes, four studies reported moderate effect sizes (McIvor et al., Reference McIvor, Riklan and Reznikoff1984; Mohr et al., Reference Mohr, Goodkin, Gatto and Van Der Wende1997; Pujol et al., Reference Pujol, Bello, Dues, Cardoner, Marti-Vilalta and Capdevila2000; Zorzon et al., Reference Zorzon, de Masi, Nasuelli, Ukmar, Mucelli, Cazzato, Bratina and Zivadinov2001), one large (Kneebone & Dunmore, Reference Kneebone and Dunmore2004) and another small (Voss et al., Reference Voss, Arnett, Higginson, Randolph, Campos and Dyck2002), with two studies reporting both small and moderate effect sizes (Devins et al., Reference Devins, Seland, Klein, Edworthy and Saary1993; Lynch et al., Reference Lynch, Kroencke and Denney2001). Due to the way the data were presented, it was not possible to estimate effect sizes for three studies but the findings they reported were statistically significant (Chwastiak et al., Reference Chwastiak, Ehde, Gibbons, Sullivan, Bowen and Kraft2002; Goodin & the Northern California MS Study Group, Reference Goodin1999; Janssens et al., Reference Janssens, van Doorn, de Boer, Kalkers, van der Merche, Passchier and Hintzen2003). Taken together, these positive findings suggest that the effect size for the relationship between depression and physical disability in MS is in the moderate range.

Cognitive dysfunction

Approximately 50% of MS patients display significant cognitive impairments (Brassington & Marsh, Reference Brassington and Marsh1998; Rao et al., Reference Rao, Leo, Bernardin and Unverzagt1991), and cognitive impairments occur both with and without depression. As Table 1 illustrates, existing studies are evenly divided between studies that reported null effects (12) and those reporting significant associations (10). Regarding the studies reporting null findings, the majority (10 of 12) were characterized by small sample sizes, suggesting that low statistical power could account for the absence of significant effects (DeLuca et al., Reference DeLuca, Barbieri-Berger and Johnson1994; Fischer, Reference Fischer1988; Grafman et al., Reference Grafman, Rao, Bernardin and Leo1991; Krupp et al., Reference Krupp, Sliwinski, Masur, Friedberg and Coyle1994; Millefiorini et al., Reference Millefiorini, Padovani, Pozzilli, Loriedo, Bastianello, Buttinelli, DiPiero and Fieschi1992; Minden & Schiffer, Reference Minden and Schiffer1990; Moller et al., Reference Moller, Wiedemann, Rohde, Backmund and Sonntag1994; Rao et al., Reference Rao, Hammeke, McQuillen, Khatri and Lloyd1984, Reference Rao, Leo and St. Aubin-Faubert1989b; Schiffer & Caine, Reference Schiffer and Caine1991). The other study reporting null findings (Good et al., Reference Good, Clark, Oger, Paty and Klonoff1992) excluded significantly depressed MS patients from their sample.

Studies reporting significant associations between depression and cognitive performance in MS patients have involved correlating standard measures of depression with measures of cognitive functioning within a heterogeneous MS sample (Aikens et al., Reference Aikens, Fischer, Namey and Rudick1997; Arnett, Reference Arnett2005; Arnett et al., Reference Arnett, Higginson, Voss and Randolph2002; Denney et al., Reference Denney, Lynch, Parmenter and Horne2004; Landro et al., Reference Landro, Celius and Sletvold2004) or comparing depressed and nondepressed MS groups (Arnett et al., Reference Arnett, Higginson and Randolph2001, Reference Arnett, Higginson, Voss, Bender, Wurst and Tippin1999a,Reference Arnett, Higginson, Voss, Wright, Bender, Wurst and Tippinb; Beatty et al., Reference Beatty, Goodkin, Monson, Beatty and Hertsgaard1988; Gilchrist & Creed, Reference Gilchrist and Creed1994).

Studies reporting positive associations did so using a variety of depression measures [e.g., BDI, CES-D, and Chicago Multiscale Depression Inventory [CMDI]) that were either examined continuously or used to create extreme depressed/nondepressed groups. It was not possible to calculate effect size in five of the studies. In the other five, three effect sizes were large (Aikens et al., Reference Aikens, Fischer, Namey and Rudick1997; Arnett et al., Reference Arnett, Higginson and Randolph2001, Reference Arnett, Higginson, Voss and Randolph2002), and two moderate (Arnett, Reference Arnett2005; Landro et al., Reference Landro, Celius and Sletvold2004).

Taken together, a critical examination suggests that studies with adequate sample sizes generally have reported a positive association between depression and cognitive dysfunction in MS of moderate to large effect size.

Pain

Over 50% of MS patients (Kassirer & Osterberg, Reference Kassirer and Osterberg1987; Moulin et al., Reference Moulin, Foley and Ebers1988; Stenager et al., Reference Stenager, Knudsen and Jensen1991, Reference Stenager, Knudsen and Jensen1995), and as many as 86% (Indaco et al., Reference Indaco, Iachetta, Nappi, Socci and Carrieri1994), report pain at some time during the course of their MS. As many as 32% of MS patients rate pain as one of their worst symptoms, and a 5-year longitudinal study on pain in MS showed that pain problems increased substantially over time (Stenager et al., Reference Stenager, Knudsen and Jensen1991, Reference Stenager, Knudsen and Jensen1995). Findings from studies that have examined the relationship between pain and depression have been mixed, with roughly equal numbers of studies showing a positive versus a null relationship. Despite this inconsistent relationship, it is important to note that not only have few studies been published in this area but, of the three studies with null findings, two (Indaco et al., Reference Indaco, Iachetta, Nappi, Socci and Carrieri1994; Newland et al., Reference Newland, Wipke-Tevis, Williams, Rantz and Petroski2005) had significant methodological flaws that may have accounted for their results. All of the studies reporting positive findings used adequate sample sizes, and three of the four (Archibald et al., Reference Archibald, McGrath, Ritvo, Fisk, Bhan, Maxner and Murray1994; Kalia & O'Connor, Reference Kalia and O'Connor2005; Tedman et al., Reference Tedman, Young and Williams1997) used rigorous measures of pain and standard and well-validated measures of depression or distress. The remaining study (Ehde et al., Reference Ehde, Gibbons, Chwastiak, Bombardier, Sullivan and Kraft2003) used a well-validated measure of depression, but the measure of pain was simply four items on a mail-in survey questionnaire and MS diagnosis was based upon self-report. In terms of effect size, two revealed small and two a moderate effect size. Taken together, if the quality of the study is factored into the analysis, the weight of the evidence supports a relationship between depression and pain in MS, with effect size in the small-moderate range (see Table 1).

As the previous section shows, the research literature on these four common MS sequelae—fatigue, physical disability, cognitive dysfunction, and pain—shows that on the surface their association with depression is mixed. If the literature is critically evaluated, however, the association between depression and three of these sequelae—fatigue, cognitive dysfunction, and pain—shows consistently positive associations with studies that use adequate sample sizes and good methodology. The studies on physical disability and depression are evenly divided between those with null findings versus those with positive associations. A more critical analysis continues to show a mixed literature overall, which suggests the presence of moderator variables that may help to explain these inconsistencies. For fatigue, cognitive dysfunction, and pain, though a critical analysis suggests a more consistent relationship for these variables with depression, the fact that such relationships are less robust suggests that they may be moderated by other variables.

Factors That May Moderate the Relationship Between Common MS Sequelae and Depression

Before turning to our discussion of possible factors that may moderate the relationship between common MS sequelae and depression, it is important to clarify our intent regarding moderator variables. According to Baron and Kenny (Reference Baron and Kenny1986) moderation involves the interaction between two variables, one of which is an independent variable and the other the moderator, which significantly predict some outcome variable after the independent effects of the two predictors have been controlled. In the case of our proposed model, each of the common MS sequelae in our model would be considered independent variables, whereas the proposed moderator variables would be the moderators. Any interaction between one of the common MS sequelae and a moderator variable could theoretically lead to depression if the interaction between the severity of the MS sequelae and a given moderator variable was great enough. Generally, more interactions between the common MS sequelae and the moderators are theorized to lead to greater risk for depression. Based upon the research literature, the common MS sequelae may or may not significantly predict depression directly. Regardless, their interaction with the moderator variables is predicted to elevate risk for depression.

It could be argued that the variables we identify as potential moderators would be better conceptualized as mediators. The distinction between moderation and mediation is important. According to Baron and Kenny (Baron & Kenny, Reference Baron and Kenny1986) moderation occurs when one variable (the moderator) affects the direction or intensity of the relation between a second (independent) variable and a third (dependent) variable. In contrast, mediation occurs when one variable (the mediator) explains the relationship between a second (independent) and third (dependent) variable. Although a mediational model may be possible in some instances, we characterize our model as predominantly moderational for two reasons. First, in the case of mediation, both the independent variable and the mediator are expected to significantly and consistently predict the dependent variable. However, at least one of the common MS sequelae that we propose as an independent variable fails to meet this requirement, and the extent to which the other three sequelae meet it is debatable. Critical evaluation of the literature on the relationship between physical disability and depression shows that physical disability (the independent variable) inconsistently predicts depression (the dependent variable), a pattern of results that favors a moderational rather than mediational model. Critical analysis of the relationship between the other three MS sequelae and depression shows that some of the relationships may be more consistent than a cursory examination of the literature makes them appear. Although it is possible that the relationship between these three sequelae—fatigue, pain, or cognitive dysfunction—and depression could be mediated by the variables we are proposing as moderators, inconsistencies in the literature appear when sample sizes and methodological parameters are not ideal. These inconsistencies suggest that the relationships are not robust and may best be explained when moderators are considered, making a mediation model less appealing.

A second reason that we mostly focus on moderation in our model is that there are several studies in the MS literature, which we describe below, that show evidence for significant interactions (i.e., moderation) between the common MS sequelae we have identified and the moderators in predicting depression. Although not all of the proposed moderational relationships have been empirically tested or validated in the MS literature, enough have to warrant further theorizing on other possible moderating relationships. We hope that our proposed model will lead to other empirical tests of moderational relationships, with the additional suggestion that possible mediational relationships could still be explored.

We now review evidence pertaining to proposed moderators in the model. The proposed moderators represent factors related to either the external circumstances of individuals with MS or to their internal representation of those circumstances. These variables have been shown to have a more consistent relationship with depression in MS (see Figure 3). The specific studies summarized by this section are presented in more detail in Table 2.

Fig. 3.

Model of depression in MS: Possible moderators predict depression.

Stress/negative life events/stress appraisal

Most studies on stress and depression in MS have been examined in the context of coping. Whether studies measure either general stress or MS-specific stress, the association between stressful events and depression is consistent in the literature. As shown in Table 2, all eight studies reported some positive associations between depression and stress in MS. One study reported small effect size (Kneebone & Dunmore, Reference Kneebone and Dunmore2004), two reported moderate (Devins et al., Reference Devins, Styra, O'Connor, Gray, Seland, Klein and Shapiro1996; McCabe & de Judicibus, Reference McCabe and de Judicibus2005), two large (Aikens et al., Reference Aikens, Fischer, Namey and Rudick1997; Gilchrist & Creed, Reference Gilchrist and Creed1994), one small and moderate (Pakenham, Reference Pakenham1999), and for two (Patten et al., Reference Patten, Metz and Reimer2000; Ron & Logsdail, Reference Ron and Logsdail1989) it was not possible to determine effect size. Although the studies in this section were of mixed quality, positive findings always emerged, suggesting that the relationship between depression and stress in MS is a robust one and likely of moderate to large effect size.

Coping

Coping and stress/hassles are commonly linked in the coping literature, because coping strategies are typically used in response to stressful events. Lazarus and Folkman's (Reference Lazarus and Folkman1984) stress and coping model has been commonly applied to the chronic illness literature in general, as well as to MS. According to this model, a central factor moderating the relationship between stress and adjustment is coping (Pakenham, Reference Pakenham1999). More specifically, coping strategies that patients use appear to put them at greater or lesser risk for depression.

Coping has been conceptualized in different ways. Traditionally, theorists have identified two broad ways of coping with stressors: Problem-focused and emotion-focused. Problem-focused strategies aim to alter the source of stress, whereas emotion-focused strategies attempt to reduce the emotional distress elicited by a situation (Lazarus, Reference Lazarus1993). As Table 2 illustrates, high levels of depression are typically associated with emotion-focused coping whereas low levels of depression are associated with problem-focused coping in MS.

Some investigators have suggested that these broad categories of coping are not unitary constructs and have developed alternative ways of conceptualizing coping. Carver and colleagues (Reference Carver, Scheier and Weintraub1989) identified active and avoidance coping scales. Greater use of avoidance coping strategies and less use of active coping strategies have been shown to be associated with higher levels of depression symptoms (Arnett et al., Reference Arnett, Higginson, Voss and Randolph2002). Longitudinally, greater use of active coping strategies has been associated with improved mood in MS patients over a 3-year period, whereas decreased use of such strategies is associated with worsening mood (Arnett & Randolph, Reference Arnett and Randolph2006).

Despite the unpredictability of MS, most studies have found that emotion-focused and avoidant coping strategies are consistently positively associated with depression, whereas problem-focused and active coping strategies are inversely related to depression (see Table 2).

Social Support/Psychosocial Factors

Outside the MS literature, Sarason and colleagues (Reference Sarason, Levine, Basham and Sarason1983) have noted that individuals with fewer social supports and/or greater dissatisfaction with those supports are more likely to experience negative affect. Consistent with this more general observation, the relationship between social support and depression in MS is very consistent. Although only a few studies have examined this relationship, they have shown that patients with better social support are less likely to be depressed than patients with poorer social support (McIvor et al., Reference McIvor, Riklan and Reznikoff1984; Schwartz & Kraft, Reference Schwartz and Kraft1999).

Conceptions of self and illness

Studies examining the association of conceptions of the self and illness with depression in MS are relatively few in number. One way of thinking about conceptions of the self and others is via cognitive schemas. Cognitive schemas represent ways in which we organize our understanding of ourselves, our relations with others, and our place in the world. Although most studies assessing cognitive schema in MS have used self-report measures, performance-based measures can also be used. In fact, performance-based measures may avoid the shared method variance that can lead to possible correlations between self-report measures of cognitive schema and self-report measures of depression. A recent study used a performance based measure, the affective reading span task, to quantify negative cognitive schema in a group of MS patients and found that depressed MS patients showed evidence of a negative bias compared with nondepressed MS patients (Bruce & Arnett, Reference Bruce and Arnett2005).

Using self-report measures, negative cognitive schema have been operationalized in a variety of ways, including lower self-efficacy (Shnek et al., Reference Shnek, Foley, LaRocca, Smith and Halper1995), internal and global attributions of negative life events (Kneebone & Dunmore, Reference Kneebone and Dunmore2004), perception of disability and illness variables related to MS (Smith & Young, Reference Smith and Young2000), and negative outcome expectancies and unrealistic thinking (Fournier et al., Reference Fournier, de Ridder and Bensing1999). The finding that efficacy expectancies and outcome expectancies predicted depression via emotion-oriented coping (Fournier et al., Reference Fournier, de Ridder and Bensing1999) is one of the few mediational findings reported in this literature. In this model, MS patients with negative expectancies of their ability to cope and expectations of negative outcomes are more likely to use emotion-oriented coping that, in turn, leads to depression.

Negative cognitive schema can also be examined by looking at patients' representations of their illness. Guided by a model of illness representation developed by Leventhal and colleagues (Reference Leventhal, Nerenz, Steele, Baum and Singer1984), Jopson and Moss-Morris (Reference Jopson and Moss-Morris2003) evaluated the role of illness representations in both general adjustment and depression in MS. Even after controlling for illness severity, beliefs in the serious consequences of the illness, in poor personal control, and in psychological causes of the illness, all significantly predicted depression.

Evers and colleagues (Reference Evers, Kraaimaat, van Lankveld, Jongen, Jacobs and Bijlsma2001) note that, when faced with the long-term stress of a chronic disease like MS, cognitive schema can be re-evaluated in at least three ways: (a) To emphasize the negative meaning of the event (e.g., helplessness, hopelessness); (b) to diminish the aversive meaning of the event (e.g., acceptance); and (c) to add a positive meaning to the event (e.g., benefit finding). In their sample of MS patients, they found that helplessness was directly correlated, and acceptance and perceived benefits inversely correlated, with negative mood. Evers and colleagues' study also underscores the potential importance of positive, as well as negative, cognitions in relation to MS patients' risk for depression.

To summarize, stress and stress appraisal, coping variables, social support, and conceptions of the self and illness all appear to be consistently associated with depression in MS. But how do these moderating variables impact the relationship between depression and the common MS sequelae? A handful of studies have examined the moderating effect of coping but, to our knowledge, only two studies have examined conceptions of the self and illness (in the form of cognitive schemas) and none have examined social support as possible moderators in the relationship between depression and the sequelae. What follows is a review of the few studies that have examined these proposed moderator variables. More detail on each study can be found in Table 2 and Figure 4. Note in Figure 4 that, in the interest of clarity, most of the interactions represented are those that have empirical support in the literature with at least one study; a few hypothetical interactions are also presented. It is assumed, however, that an interaction between any of the common MS sequelae and any of the moderator variables can lead to depression. Another important assumption is that interactions between moderators can also predict depression, and two areas where this has been empirically supported are discussed below and also represented in the model in Figure 4 with intersecting arrows.

Fig. 4.

Model of depression in MS: Possible moderators interact with common MS sequelae to predict depression. Note. The differently colored arrows convey the category of variable in this figure: Green represents MS disease factors and blue represents common MS sequelae. The red arrows represent possible moderators. Note that the risk for depression either decreases or increases with the occurrence of the moderating variables in the right-hand circle depending upon whether they are in the adaptive or the maladaptive direction, as indicated by the upward and downward arrows underneath the right-hand circle. Empirically supported interactions between moderating variables and common MS sequelae, or between proposed moderators, are represented by pink lines from each variable intersecting at a small pink circle with an arrow leading to depression. A few hypothesized, but as yet untested, interactions between moderating variables and common MS sequelae, or between proposed moderators, are represented by orange lines from each variable intersecting at a small orange circle with an arrow leading to depression. Other possible interactions based upon the model could be derived as well

Studies Examining Moderating Variables of Common MS Sequelae

Cognitive dysfunction and coping

Using Carver and colleagues' COPE (Reference Carver, Scheier and Weintraub1989) to measure active and avoidant coping strategies, we found that both coping strategies significantly moderated the relationship between cognitive dysfunction and depression (Arnett et al., Reference Arnett, Higginson, Voss and Randolph2002). Specifically, MS patients with cognitive difficulties were only at risk for depression if they used high levels of avoidance coping or low levels of active coping.

Pain and conceptions of the self and illness

In a recent study (Bruce et al., Reference Bruce, Polen and Arnett2007), we used the affective reading span task mentioned earlier to examine whether affective memory biases moderated the relationship between pain and depression in MS. The interaction of negative bias and pain significantly predicted variance in depression. Specifically, patients with negative biases experienced more depressive symptoms as pain increased. Additionally, patients with positive biases experienced fewer depressive symptoms as pain increased. Our results highlighted both the potentially adverse effects of negative cognitive bias and the potentially protective effects of a positive cognitive bias.

Physical disability and coping

Lynch and colleagues (Reference Lynch, Kroencke and Denney2001) reported that coping did not moderate the significant relationship they found between disability and depression. However, they examined the interaction variable of coping and physical disability only after they had first entered individual predictors for coping and physical disability, along with measures of hope and illness uncertainty. All of these variables had significant zero-order correlations with depression scores, enough to account for 40% of the variance when entered into a simultaneous regression analysis, leaving little variance to be accounted for by interaction variables. A more focused approach might have revealed a more significant moderating influence of coping on the relationship between disability and depression in MS.

Taking a different tack, Mohr and colleagues (Reference Mohr, Goodkin, Gatto and Van Der Wende1997) suggested that level of physical disability moderated the relationship between coping and depression in MS. They found significant interactions between physical disability and two types of active coping in predicting depression. However, given the cross-sectional nature of these data, their findings could just as easily suggest coping as a moderator of physical disability. The findings from this study are at least consistent with the notion that coping moderates the relationship between disability and depression.

To review, a few studies have empirically examined the moderators in the proposed model in relation to the common MS sequelae and depression. Evidence supports some of the proposed relationships—for example, coping as a moderator of physical disability or cognitive dysfunction, and conceptions of the self and illness as a moderator of pain—but the data are admittedly sparse at this point. Although much of this aspect of the model is speculative and remains to be tested, it is designed to provide a theoretical framework for future work.

Studies Examining Interactions Between Moderators

Although most of the model focuses on the moderator variables influencing the outcome of common MS sequelae, moderator variables can also interact with one another to predict depression. There is some empirical evidence in the literature that this occurs for at least two of the possible interactions.

Stress and coping

Pakenham (Reference Pakenham1999) examined a model of stress, stress appraisal, and coping in MS. He found that stress appraisal interacted with emotion-focused coping to significantly predict distress. Specifically, patients appraising high levels of stress and using emotion-focused coping showed more distress.

In another study, Pakenham (Reference Pakenham2005) examined benefit-finding coping as a moderator of stress appraisal and adjustment and reported a significant interaction. Patients reporting high benefit finding in the context of high stress appraisals reported lower distress, whereas those reporting low benefit finding in the context of high stress appraisals reported higher distress.

One caveat to this work is that, Pakenham used a measure which includes a subscale for depression but is not specific to depression. Because he did not analyze the depression subscale specifically, he reported broad-based distress rather than depression. Nonetheless, we included the results of these two studies because they are among the few in the MS literature that examine the interaction of stress and coping in predicting psychological adjustment and distress.

Stress and conceptions of the self and illness

Kneebone and Dunmore (Reference Kneebone and Dunmore2004) examined the possibility that negative cognitive schema, as reflected in attributional style, moderate the relationship between negative life events (i.e., stress) and depression in MS. Consistent with Abramson and colleagues' view that negative life events represent the beginning of a causal chain that leads to a hopelessness type of depression (Abramson et al., Reference Abramson, Metalsky and Alloy1989), Kneebone and Dunmore found that negative life events—both general negative events and those specific to MS—interacted significantly with global negative attributions in predicting depression in their MS sample. More specifically, they found that negative life events predicted depression when global attributions for negative events were high but not when global attributions for negative events were low.

Congruent with the above study, we (Beeney & Arnett, Reference Beeney and Arnett2008) found that cognitive schema, measured using a performance-based measure of memory bias to avoid same method bias, moderated the relationship between stress appraisal and depression in MS. Similarly to Kneebone and Dunmore, we found that MS patients' reports of high amounts of stressful events relative to uplifting events were associated with depression only when patients evidenced a negative memory bias.

How the Model Works

We now present a detailed explanation of how the model might work in light of the empirical evidence described above (see Figure 4). Concomitant and subsequent to the onset of MS, patients experience disease-related changes. These changes represent a distal level of risk for depression. Although they play a central role in the model, such changes do not explain all of the variance in depression; hence, the need for other explanatory factors.

Arrows lead from disease-related changes to fatigue, pain, cognitive dysfunction, and physical disability, because evidence has shown that these changes are associated with such symptoms. Common MS sequelae can further increase risk for depression in MS. The inconsistency or lack of robustness of the relationship between these common MS sequelae and depression, however, suggests that the extent to which these factors increase the risk for depression is moderated by other variables, such as stress, coping, social support, and conceptions of the self and illness.

When the influence of these moderator variables is in the adaptive direction, then the common MS sequelae are less likely to lead to depression. When the influence of these variables is in the maladaptive direction, the common MS sequelae are more likely to lead to depression. For example, good social support, positive conceptions of the self and illness, higher levels of problem-focused or active coping, and lower levels of emotion-focused or avoidance coping have been consistently associated with reduced depression in MS. In contrast, poor social support, negative conceptions of the self and illness, lower levels of problem-focused or active coping, and higher levels of emotion-focused or avoidance coping have been associated with increased depression.

Some of the interactions between common MS sequelae and the proposed moderators which can influence depression in MS have been supported by at least one study in the literature. These include physical disability and coping, cognitive dysfunction and coping, and pain and conceptions of the self and illness. At least two studies support the influence of interactions between proposed moderators, including stress and coping as well as stress and conceptions of the self and illness. The majority of the proposed interactions, however, whether between common MS sequelae and proposed moderators or between two moderating variables, have not been empirically tested. We propose them here because, in the case of the four common MS sequelae, inconsistent or lack of robust relationships have been reported in the empirical literature. As noted, such inconsistent or weak relationships between variables in a literature suggest the presence of moderators.

In MS-related depression, common MS sequelae may be influenced by both external circumstances (e.g., stressful events or social support) as well as internal representations of those external circumstances (e.g., coping style, conceptions of self and illness). It further suggests that external circumstances can themselves be affected by internal representations of those circumstances. Coping and conceptions of the self and illness have proved to be moderators for some of the common MS sequelae already (i.e., physical disability, cognitive dysfunction, and pain) in relation to depression, and so we reasoned that they might be likely candidates for moderators of the other variable, namely fatigue. Regarding the other proposed moderators, stress and social support, there are as yet no empirical studies showing that they moderate any of the common MS sequelae in relation to depression. Nonetheless, we identified both variables as potential moderators based upon their consistent relationship with depression in the MS literature as well as the consideration that high levels of stress or poor social support might magnify the effects of MS symptomatology. Similarly, coping and conceptions of the self and illness have proved to interact with other proposed moderators already (i.e., stress) in MS-related depression, and so we reasoned that other interactions between proposed moderators—such as stress and social support, coping and social support, or coping and conceptions of self and illness—might influence depression in MS as well.

In the model, any of the proposed interactions are theorized to be sufficient to lead to depression. This conclusion is based upon evidence from several individual studies showing that one interaction can be a significant predictor of depression. With that said, it is further proposed that individuals who have more extensive and severe common MS sequelae, along with moderator variables in the maladaptive direction, are going to be at greatest risk for depression. In sum, the interaction of all these variables is not necessary for depression to result, as even one interaction is sufficient. However, the more interactions that are present, the greater the risk for depression.

The model is not intended to be linear and unidirectional. We assume that depression feeds back to the moderator variables and possibly to other variables as well, including fatigue, cognitive dysfunction, and pain. By design, the time course of risk is not specified. Given the variability of symptomatology in most MS patients, common sequelae can appear at any time during the disease course. The model is also neutral with regard to how the individual comes to have low levels of social support, negative conceptions of the self and illness, or maladaptive coping. It simply states that if these variables are present within individuals who experience one or more of the common MS sequelae, then these common sequelae will more likely be associated with depression. The degree to which the sequelae are present increases the risk for depression in MS. In turn, the likelihood that these sequelae get manifested in depression is importantly influenced by the presence of the proposed moderators.

Possible testable hypotheses from the model can range from simple two-factor associations to complex, multi-factor interactions. For example, more studies could be conducted to bolster the few to date showing an association between pain and depression, social support and depression, or conceptions of the self and illness with depression. Hypothesized interactions between common MS sequelae and proposed moderators that remain to be demonstrated include those between fatigue and coping or fatigue and conceptions of self and illness in relation to depression. More complex interactions that might significantly predict depression in MS which have yet to be investigated include predictions that physical disability will interact with conceptions of self and illness, cognitive dysfunction will interact with social support, pain will interact with coping, and stress will interact with social support. These proposed hypotheses do not represent an exhaustive list of the possible associations and interactions between common MS sequelae, possible moderators, and depression in MS that could be tested; a more comprehensive list of possible combinations can be derived from Figure 4.

SUMMARY AND CONCLUSIONS

Depression is highly prevalent in MS and is generally stable longitudinally. It is associated with disease-related changes as well as with several common disease sequelae, all of which have significant negative consequences for patients' quality of life. Although depression in MS develops after disease onset, research suggests that it is very treatable. Because of the stability of depression in MS and the fact that it is unlikely to remit without treatment, it can have devastating long-term consequences for patients' day-to-day functioning.

The present review of the research literature was conducted to provide an overview of key factors associated with depression in MS and to present a theoretical model that integrates these key factors. An attempt was also made to identify gaps in the empirical literature. Although some aspects of the model are supported by research, many aspects remain speculative and in need of further testing. This is especially true for the interaction between the common sequelae and the moderator variables in predicting depression in MS. Future research is clearly necessary to evaluate the validity of these relationships.

Another important limitation is that the proposed model is largely based on cross-sectional data. Although causal relationships are proposed in the model, the causal nature of the relationships remains unclear. Additionally, many of the hypothesized relationships may be reciprocal rather than unidirectional. While future cross-sectional research to test these hypothesized relationships is important, longitudinal data would provide a more powerful test of how these relationships in MS evolve over time.

Depression has been intensively studied in MS over the past 20–25 years because of its high prevalence, implications for quality of life, and possibly its influence on disease progression. Despite the publication of numerous excellent empirical papers on this topic, theoretical work that attempts to integrate the range of research findings into a comprehensive explanatory model is scarce. The present study has taken a step toward incorporating existing empirical work into a coherent, testable, theoretical model of depression in MS that we hope will provide a better understanding of past work as well as directions for future research. Ultimately, we hope that this review and theoretical model will help clinicians and researchers to understand the multitude of factors that are associated with depression in MS, leading to better care for patients suffering from this devastating disease.

ACKNOWLEDGMENTS

There are no sources of financial or other relationships that could be interpreted as a conflict of interest affecting this manuscript and there are no sources of financial support for this manuscript. Information in this manuscript and the manuscript itself has never been published either electronically or in print. Special thanks to Jeffrey Arnett and Frank Hillary, both of whom provided invaluable input on earlier drafts of this article. Finally, we express our gratitude to the MS participants and their significant others who have generously contributed their time in our research studies over the years to helping us better understand the nature of multiple sclerosis.

APPENDIX A: General Tables Appendix: Acronyms of Measures Defined According to Category

    Cognitive Schema

  • ARST: Affective Reading Span Task

  • ASQ: Attributional Style Questionnaire

  • ASQ-S: Attributional Style Questionnaire-Survey

  • CBQ: Cognitive Beliefs Questionnaire

  • GSES: Generalized Self-Efficacy Scale

  • ICQ: Illness Cognitions Questionnaire

  • IPQ-R: Illness Perceptions Questionnaire-Revised

  • LOT: Life Orientation Test

  • MSAI: Multiple Sclerosis Attitudes Index

  • MSBS: Multiple Sclerosis Beliefs Scale

  • O&P: Optimism and Pessimism Scale

  • OPPQ: Optimism-Pessimism Prescreening Questionnaire

  • RSD/H: Rankin Scale of Disability/Handicap

    Cognition

  • AVLT: Auditory Verbal Learning Test

  • BCT: Booklet Category Test

  • BFRT: Benton Facial Recognition Test

  • BNT: Boston Naming Test

  • BPIT: Brown Peterson Interference Test

  • BPMT: Brown Peterson Memory Test

  • BVRT: Benton Visual Retention Test

  • CFT: Complex Figure Test

  • COWAT: Controlled Oral Word Association Test

  • DS: Digit Span

  • FR: Facial Recognition

  • FT: Finger Tapping

  • FVRT: Free Verbal Recall Test

  • HFMT: Hasher Frequency Monitoring Task

  • HVOT: Hooper Visual Organization test

  • JLO: Judgment of Line Orientation

  • LTM: Long Term Memory

  • MHVS: Mill Hill Vocabulary Scale

  • MMSE: Mini Mental Status Exam

  • MST: Sternberg's Memory Scanning Task

  • MSO: Memory Span for Objects

  • PA: Paired Associates Learning Test

  • PASAT: Paced Auditory Serial Addition Test

  • PT: President's Test

  • RBMT: Rivermead Behavioral Memory Test

  • RPM: Raven's Progressive Matrices

  • SDMT: Symbol Digit Modalities Test

  • 7/24: 7/24 Spatial Recall

  • SIDAM: Structured Interview for Diagnosis of Alzheimer Dementias

  • STM: Short Term Memory

  • Stroop: Stroops' Color-Word Interference Test

  • TMT: Trail Making Test

  • TOL: Tower of London

  • VE: Visual Elevator

  • VFD: Visual Form Discrimination

  • VSRT: Verbal Selective Reminding Task

  • WAIS-R: Wechsler Adult Intelligence Scale, Revised

  • WCST: Wisconsin Card Sorting test

  • WMS: Wechsler Memory Scale

    Coping

  • BABS: Bradburn Affect Balance Scale

  • BFS: Benefit Finding Scale

  • CMSS: Coping with Multiple Sclerosis Scale

  • COPE: No acronym

  • FDCQ: Freiburg Disease Coping Questionnaire

  • PEMS: Psychosocial Effects of Multiple Sclerosis

  • WCC: Ways of Coping Checklist\MRevised

  • WOC: Ways of Coping

    Depression

  • AIMS: Arthritis Impact Measurement Scale\Mdepression subscale

  • BDI: Beck Depression Inventory

  • BSI: Brief Symptom Inventory

  • CES-D: Center for Epidemiological Studies Depression Scale

  • CIDI: Composite International Diagnostic Interview

  • CIS: Clinical Interview Schedule

  • CIS-D: Clinical Interview Schedule for Depression

  • DSM-IV: Diagnostic and Statistical Manual of Mental Disorders, 4th edition

References

REFERENCES

Abramson, L.Y., Metalsky, G.I., & Alloy, L.B. (1989). Hopelessness depression: A theory based sub-type of depression. Psychological Review, 96, 358–372.CrossRefGoogle Scholar
Ackerman, K.D., Rabin, B., Heyman, R., Anderson, B.P., Houch, P.R., & Frank, E. (2000). Stressful life events preceded multiple sclerosis disease exacerbations. Psychosomatic Medicine, 62, 147.Google Scholar
Aikens, J.E., Fischer, J.S., Namey, M., & Rudick, R.A. (1997). A replicated prospective investigation of life stress, coping, and depressive symptoms in multiple sclerosis. Journal of Behavioral Medicine, 20, 433–445.Google Scholar
American Psychiatric Association. (1994). Diagnostic and Statistical Manual of Mental Disorders (4thed.). Washington, DC: American Psychiatric Association.Google Scholar
Archibald, C.J., McGrath, P.J., Ritvo, P.G., Fisk, J.D., Bhan, V., Maxner, C.E., & Murray, T.J. (1994). Pain prevalence, severity and impact in a clinic sample of multiple sclerosis patients. Pain, 58, 89–93.CrossRefGoogle Scholar
Arnett, P.A. (2003). Neuropsychological presentation and treatment of demyelinating disorders. In Halligan, P., Kischka, U., & Marshall, J. (Eds.), Handbook of Clinical Neuropsychology (pp. 528–543). Oxford: Oxford University Press.Google Scholar
Arnett, P.A. (2005). Longitudinal consistency of the relationship between depression symptoms and cognitive functioning in multiple sclerosis. CNS Spectrums, 10, 372–382.CrossRefGoogle ScholarPubMed
Arnett, P.A., Higginson, C.I., & Randolph, J.J. (2001). Depression in multiple sclerosis: Relationship to planning ability. Journal of the International Neuropsychological Society, 7, 665–674.CrossRefGoogle ScholarPubMed
Arnett, P.A., Higginson, C.I., Voss, W.D., Bender, W.I., Wurst, J.M., & Tippin, J. (1999a). Depression in multiple sclerosis: Relationship to working memory capacity. Neuropsychology, 13, 546–556.Google Scholar
Arnett, P.A., Higginson, C.I., Voss, W.D., & Randolph, J.J. (2002). Relationship between coping, depression, and cognitive dysfunction in multiple sclerosis. The Clinical Neuropsychologist, 16, 341–355.CrossRefGoogle ScholarPubMed
Arnett, P.A., Higginson, C.I., Voss, W.D., Wright, B., Bender, W.I., Wurst, J.M., & Tippin, J.M. (1999b). Depressed mood in multiple sclerosis: Relationship to capacity-demanding memory and attentional functioning. Neuropsychology, 13, 434–446.Google Scholar
Arnett, P.A. & Randolph, J.J. (2006). Longitudinal course of depression symptoms in multiple sclerosis. Journal of Neurology, Neurosurgery, and Psychiatry, 77, 606–610.Google Scholar
Bakshi, R., Czarnecki, D., Shaikh, Z.A., Priore, R.L., Janardhan, V., Kaliszky, Z., & Kinkel, P.R. (2000a). Brain MRI lesions and atrophy are related to depression in multiple sclerosis. Neuroreport, 11, 1153–1158.Google Scholar
Bakshi, R., Shaikh, Z.A., Miletich, R.S., Czarnecki, D., Dmochowski, J., Henschel, K., Janardhan, V., Dubey, N., & Kinkel, P.R. (2000b). Fatigue in multiple sclerosis and its relationship to depression and neurologic disability. Multiple Sclerosis, 6, 181–185.Google Scholar
Baron, R.M. & Kenny, D.A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. The Journal of Personality and Social Psychology, 51, 1173–1182.Google Scholar
Beatty, W.W., Goodkin, D.E., Hersgaard, D., & Monson, N. (1990). Clinical and demographic predictors of cognitive performance in multiple sclerosis. Archives of Neurology, 47, 305–308.CrossRefGoogle ScholarPubMed
Beatty, W.W., Goodkin, D.E., Monson, N., Beatty, P.A., & Hertsgaard, D. (1988). Anterograde and retrograde amnesia in patients with chronic progressive multiple sclerosis. Archives of Neurology, 45, 611–619.Google Scholar
Beeney, J.E. & Arnett, P.A. (2008). Stress and memory bias interact to predict depression in multiple sclerosis. Neuropsychology, 22, 118–126.CrossRefGoogle ScholarPubMed
Benedict, R.H.B., Bruce, J.M., Dwyer, M.G., Abdelrahman, N., Hussein, S., Weinstock-Guttman, B., Garg, N., Munschauer, F., & Zivadinov, R. (2006). Neocortical atrophy, third ventricular width, and cognitive dysfunction in multiple sclerosis. Archives of Neurology, 63, 1301–1306.CrossRefGoogle ScholarPubMed
Berg, D., Supprian, T., Thomae, J., Warmuth-Metz, M., Horowski, A., Zeiler, B., Magnus, T., Rieckman, P., & Becker, G. (2000). Lesion pattern in patients with multiple sclerosis and depression. Multiple Sclerosis, 6, 156–162.Google Scholar
Brass, S.D., Benedict, R.H.B., Weinstock-Guttman, B., Munschauer, F., & Bakshi, R. (2006). Cognitive impairment is associated with subcortical magnetic resonance imaging grey matter T2 hypointensity in multiple sclerosis. Multiple Sclerosis, 12, 437–444.Google Scholar
Brassington, J.C. & Marsh, N.V. (1998). Neuropsychological aspects of multiple sclerosis. Neuropsychology Review, 8, 43–77.CrossRefGoogle ScholarPubMed
Bruce, J.M. & Arnett, P.A. (2005). Depressed MS patients exhibit affective memory biases during and after a list learning task that suppresses higher-order encoding strategies. Journal of the International Neuropsychological Society, 11, 514–521.CrossRefGoogle Scholar
Bruce, J.M., Polen, D.M., & Arnett, P.A. (2007). Pain and affective memory biases interact to predict depressive symptoms in multiple sclerosis. Multiple Sclerosis, 13, 58–66.Google Scholar
Carver, C.S., Scheier, M.F., & Weintraub, J.K. (1989). Assessing coping strategies: A theoretically based approach. The Journal of Personality and Social Psychology, 56, 267–283.CrossRefGoogle ScholarPubMed
Chwastiak, L., Ehde, D.M., Gibbons, L.E., Sullivan, M., Bowen, J.D., & Kraft, G.H. (2002). Depressive symptoms and severity of illness in multiple sclerosis: Epidemiologic study of a large community sample. The American Journal of Psychiatry, 159, 1862–1868.CrossRefGoogle ScholarPubMed
Cohen, J. & Cohen, P. (1983). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences (2nded.). Hillside, NJ: Lawrence Erlbaum Associates.Google Scholar
Dalos, N.P., Rabins, P.V., Brooks, B.R., & O'Donnell, P. (1983). Disease activity and emotional state in multiple sclerosis. Annals of Neurology, 13, 573–577.Google Scholar
Dalton, J.E. & Heinrichs, R.W. (2005). Depression in multiple sclerosis: A quantitative review of the evidence. Neuropsychology, 19, 152–158.Google Scholar
DeLuca, J., Barbieri-Berger, S., & Johnson, S.K. (1994). The nature of memory impairments in multiple sclerosis: Acquisition versus retrieval. Journal of Clinical and Experimental Neuropsychology, 16, 183–189.Google Scholar
Denney, D.R., Lynch, S.G., Parmenter, B.A., & Horne, N. (2004). Cognitive impairment in relapsing and primary progressive multiple sclerosis: Mostly a matter of speed. Journal of the International Neuropsychological Society, 10, 948–956.Google Scholar
De Ridder, D., Schreurs, K., & Bensing, J. (2000). The relative benefits of being optimistic: Optimism as a coping resource in multiple sclerosis and Parkinson's disease. British Journal of Health Psychology, 5, 141–155.CrossRefGoogle Scholar
Devins, G.M., Seland, T.P., Klein, G., Edworthy, S.M., & Saary, M.J. (1993). Stability and determinants of psychosocial well-being in multiple sclerosis. Rehabilitation Psychology, 38, 11–26.Google Scholar
Devins, G.M., Styra, R., O'Connor, P., Gray, T., Seland, T.P., Klein, G., & Shapiro, C.M. (1996). Psychosocial impact of illness intrusiveness moderated by age in multiple sclerosis. Psychology, Health and Medicine, 1, 179–191.Google Scholar
Edgley, K., Sullivan, M.J.L., & Dehoux, E. (1991). A survey of multiple sclerosis. Part 2. Determinants of employment status. Canadian Journal of Rehabilitation, 4, 127–132.Google Scholar
Ehde, D.M., Gibbons, L.E., Chwastiak, L., Bombardier, C.H., Sullivan, M.D., & Kraft, G.H. (2003). Chronic pain in a large community sample of persons with multiple sclerosis. Multiple Sclerosis, 9, 605–611.CrossRefGoogle Scholar
Evers, A.W.M., Kraaimaat, F.W., van Lankveld, W., Jongen, P.J.H., Jacobs, J.W.G., & Bijlsma, J.W.J. (2001). Beyond unfavorable thinking: The Illness Cognition Questionnaire for chronic diseases. Journal of Consulting and Clinical Psychology, 69, 1026–1036.CrossRefGoogle ScholarPubMed
Fassbender, K., Schmidt, R., Mofsner, R., Kischka, U., Kuhnen, J., Schwartz, A., & Hennerici, M. (1998). Mood disorders and dysfunction of the hypothalamic-pituitary-adrenal axis in multiple sclerosis. Archives of Neurology, 55, 66–72.Google Scholar
Feinstein, A. (2004). The neuropsychiatry of multiple sclerosis. Canadian Journal of Psychiatry, 49, 157–163.Google Scholar
Feinstein, A., O'Conner, P., & Feinstein, K. (2002). Multiple sclerosis, interferon beta 1b and depression. Journal of Neurology, 24, 815–820.CrossRefGoogle Scholar
Feinstein, A., Roy, P., Lobaugh, N., Feinstein, K., O'Connor, P., & Black, S. (2004). Structural brain abnormalities in multiple sclerosis patients with major depression. Neurology, 62, 586–590.Google Scholar
Fischer, J.S. (1988). Using the Wechsler Memory Scale-Revised to detect and characterize memory deficits in multiple sclerosis. The Clinical Neuropsychologist, 2, 149–172.Google Scholar
Fisk, J.D., Pontefract, A., Ritvo, P.G., Archibald, C.J., & Murray, T.J. (1994). The impact of fatigue on patients with multiple sclerosis. Canadian Journal of Neurological Sciences, 21, 9–14.Google Scholar
Flachenecker, P., Kumpfel, T., Kallmann, B., Gottschalk, M., Grauer, O., Rieckmann, P., Trenkwalder, C., & Toyka, K.V. (2002). Fatigue in multiple sclerosis: A comparison of different rating scales and correlation to clinical parameters. Multiple Sclerosis, 8, 523–526.Google Scholar
Foley, F.W., Miller, A.H., Traugott, U., LaRocca, N.G., Scheinberg, L.C., Bedell, J.R., & Lennox, S.S. (1988). Psychoimmunological dysregulation in multiple sclerosis. Psychosomatics, 29, 398–404.CrossRefGoogle ScholarPubMed
Foley, F.W., Traugott, U., LaRocca, N.G., Smith, C.R., Perlman, K.R., Caruso, L.S., & Scheinberg, L.C. (1992). A prospective study of depression and immune dysregulation in multiple sclerosis. Archives of Neurology, 49, 238–244.Google Scholar
Fournier, M., de Ridder, D., & Bensing, J. (1999). Optimism and adaptation to multiple sclerosis: What does optimism mean? Journal of Behavioral Medicine, 22, 303–326.Google Scholar
Franklin, G.M., Nelson, L.M., Heaton, R.K., Burkes, J.S., & Thompson, D.S. (1988). Stress and its relationship to acute exacerbations of multiple sclerosis. The Journal of Neurological Rehabilitation, 2, 7–11.Google Scholar
Gilchrist, A.C. & Creed, F.H. (1994). Depression, cognitive impairment, and social stress in multiple sclerosis. Journal of Psychosomatic Research, 38, 193–201.Google Scholar
Goldman Consensus Group. (2005). The Goldman Consensus statement on depression in multiple sclerosis. Multiple Sclerosis, 11, 328–337.Google Scholar
Good, K., Clark, C.M., Oger, J., Paty, D., & Klonoff, H. (1992). Cognitive impairment and depression in mild multiple sclerosis. Journal of Nervous and Mental Disease, 180, 730–732.Google Scholar
Goodin, D.S., & the Northern California MS Study Group. (1999). Survey of multiple sclerosis in northern California. Multiple Sclerosis, 5, 78–88.Google Scholar
Grafman, J., Rao, S.M., Bernardin, L., & Leo, G.J. (1991). Automatic memory processes in patients with multiple sclerosis. Archives of Neurology, 48, 1072–1075.CrossRefGoogle ScholarPubMed
Honer, W.G., Hurwitz, T., Li, D.K., Palmer, M., & Paty, D.W. (1987). Temporal lobe involvement in multiple sclerosis patients with psychiatric disorders. Archives of Neurology, 44, 187–190.Google Scholar
Huber, S.J., Rammohan, K.W., Bornstein, R.A., & Christy, J.A. (1993). Depressive symptoms are not influenced by severity of multiple sclerosis. Neuropsychiatry, Neuropsychology, & Behavioral Neurology, 6, 177–180.Google Scholar
Indaco, A., Iachetta, C., Nappi, C., Socci, L., & Carrieri, P.B. (1994). Chronic and acute pain syndromes in patients with multiple sclerosis. Acta Neurologica (Napoli), 16, 97–102.Google Scholar
Jackson, M., Quaal, C., & Reeves, M. (1991). Effects of multiple sclerosis on occupational and career patterns. Axon, 13, 16–22.Google Scholar
Janssens, A.C.J.W., van Doorn, P.A., de Boer, J.B., Kalkers, N.F., van der Merche, F.G.A., Passchier, J., & Hintzen, R.Q. (2003). Anxiety and depression influence the relation between disability status and quality of life in multiple sclerosis. Multiple Sclerosis, 9, 397–403.CrossRefGoogle ScholarPubMed
Joffe, R.T., Lippert, G.P., Gray, T.A., Sawa, G., & Horvath, Z. (1987). Mood disorder and multiple sclerosis. Archives of Neurology, 44, 376–378.CrossRefGoogle ScholarPubMed
Jopson, N.M. & Moss-Morris, R. (2003). The role of illness severity and illness representations in adjusting to multiple sclerosis. Journal of Psychosomatic Research, 54, 503–511.Google Scholar
Kalia, L.V. & O'Connor, P.W. (2005). Severity of chronic pain and its relationship to quality of life in multiple sclerosis. Multiple Sclerosis, 11, 322–327.Google Scholar
Kassirer, M.R. & Osterberg, D.H. (1987). Pain in chronic multiple sclerosis. Journal of Pain Symptom Management, 2, 95–97.Google Scholar
Kenealy, P.M., Beaumont, G.J., Lintern, T., & Murrell, R. (2000). Autobiographical memory, depression and quality of life in multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 22, 125–131.Google Scholar
King, K.E. & Arnett, P.A. (2005). Predictors of dyadic adjustment in multiple sclerosis. Multiple Sclerosis, 11, 700–707.Google Scholar
Kneebone, I. & Dunmore, E. (2004). Attributional style and symptoms of depression in persons with multiple sclerosis. International Journal of Behavioral Medicine, 11, 110–115.Google Scholar
Kroencke, D.C. (2000). Fatigue in multiple sclerosis: Relationship to depression, disability, and disease pattern. Multiple Sclerosis, 6, 131–136.Google Scholar
Kroencke, D.C., Lynch, S.G., & Denney, D.R. (2000). Fatigue in multiple sclerosis: Relationship to depression, disability, and disease pattern. Multiple Sclerosis, 6, 131–136.Google Scholar
Krupp, L.B., Alvarez, L.A., LaRocca, N.G., & Scheinberg, L.C. (1988). Fatigue in multiple sclerosis. Archives of Neurology, 45, 435–438.Google Scholar
Krupp, L.B., LaRocca, N.G., Muir-Nash, J., & Steinberg, A.D. (1989). The Fatigue Severity Scale: Application to patients with multiple sclerosis and systemic lupus erythematosus. Archives of Neurology, 46, 1121–1123.Google Scholar
Krupp, L.B., Sliwinski, M., Masur, D.M., Friedberg, F., & Coyle, P.K. (1994). Cognitive functioning and depression in patients with chronic fatigue syndrome. Archives of Neurology, 51, 705–710.Google Scholar
Kurtzke, J.F. (1983). Rating neurologic impairment in multiple sclerosis: An expanded disability status scale (EDSS). Neurology, 33, 1444–1452.CrossRefGoogle ScholarPubMed
Landro, N.I., Celius, E.G., & Sletvold, H. (2004). Depressive symptoms account for deficient information processing speed but not for impaired working memory in early phase multiple sclerosis (MS). Journal of the Neurological Sciences, 217, 211–216.Google Scholar
Lazarus, R.S. (1993). Coping theory and research: Past, present, and future. Psychosomatic Medicine, 55, 234–247.Google Scholar
Lazarus, R.S. & Folkman, S. (1984). Stress, Appraisal, and Coping. New York: Springer.Google Scholar
Leventhal, H., Nerenz, D.R., & Steele, D.J. (1984). Illness representations and coping with health threats. In Baum, A. & Singer, J. (Eds.), A Handbook of Psychology and Health (pp. 219–252). Hillsdale, NJ: Erlbaum.Google Scholar
Lynch, S.G., Kroencke, D.C., & Denney, D.R. (2001). The relationship between disability and depression in multiple sclerosis: The role of uncertainty, coping, and hope. Multiple Sclerosis, 7, 411–416.CrossRefGoogle ScholarPubMed
McCabe, M.P. & de Judicibus, M. (2005). The effects of economic disadvantage on psychological well-being and quality of life among people with multiple sclerosis. Journal of Health Psychology, 10, 163–173.Google Scholar
McCabe, M.P., McKern, S., & McDonald, E. (2004). Coping and psychological adjustment among people with multiple sclerosis. Journal of Psychosomatic Research, 56, 355–361.Google Scholar
McIvor, G.P., Riklan, M., & Reznikoff, M. (1984). Depression in multiple sclerosis as a function of length and severity of illness, age, remissions, and perceived social support. Journal of Clinical Psychology, 40, 1028–1033.Google Scholar
Mersky, H. & Bogduk, N. (1994). Classification of Chronic Pain. Seattle: IASP Press.Google Scholar
Millefiorini, E., Padovani, A., Pozzilli, C., Loriedo, C., Bastianello, S., Buttinelli, C., DiPiero, V., & Fieschi, C. (1992). Depression in the early phase of MS: Influence of functional disability, cognitive impairment, and brain abnormalities. Acta Neurologica Scandinavica, 86, 354–358.CrossRefGoogle ScholarPubMed
Minden, S.L., Moes, E.J., Orav, J., Kaplan, E., & Reich, P. (1990). Memory impairment in multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 12, 566–586.CrossRefGoogle ScholarPubMed
Minden, S.L., Orav, J., & Reich, P. (1987). Depression in multiple sclerosis. General Hospital Psychiatry, 9, 426–434.Google Scholar
Minden, S.L. & Schiffer, R.B. (1990). Affective disorders in multiple sclerosis. Archives of Neurology, 47, 98–104.Google Scholar
Mohr, D.C., Dick, L.P., Russo, D., Likosky, W., Pinn, J., & Boudewyn, A.C. (1999). The psychosocial impact of multiple sclerosis: Exploring the patient's perspective. Health Psychology, 18, 376–382.Google Scholar
Mohr, D.C., Goodkin, D.E., Bacchetti, P., Boudewyn, A.C., Huang, L., & Marrietta, P. (2000). Psychological stress and the subsequent appearance of new brain MRI lesions in MS. Neurology, 55, 55–61.Google Scholar
Mohr, D.C., Goodkin, D.E., Gatto, N., & Van Der Wende, J. (1997). Depression, coping and level of neurological impairment in multiple sclerosis. Multiple Sclerosis, 3, 254–258.Google Scholar
Mohr, D.C., Goodkin, D.E., Islar, J., Hauser, S.L., & Genain, C.P. (2001). Treatment of depression is associated with suppression of nonspecific and antigen-specific Th1 responses in multiple sclerosis. Archives of Neurology, 58, 1081–1086.Google Scholar
Mohr, D.C., Hart, S.L., & Goldberg, A. (2003). Effects of treatment for depression on fatigue in multiple sclerosis. Psychosomatic Medicine, 65, 542–547.Google Scholar
Moller, A., Wiedemann, G., Rohde, U., Backmund, H., & Sonntag, A. (1994). Correlates of cognitive impairment and depressive mood disorder in multiple sclerosis. Acta Psychiatrica Scandinavica, 89, 117–121.Google Scholar
Moulin, D.E., Foley, F.W., & Ebers, G.C. (1988). Pain syndromes in multiple sclerosis. Neurology, 38, 1830–1834.Google Scholar
Newland, P.K., Wipke-Tevis, D.D., Williams, D.A., Rantz, M.J., & Petroski, G.F. (2005). Impact of pain on outcomes in long-term care residents with and without multiple sclerosis. Journal of the American Geriatrics Society, 53, 1490–1496.CrossRefGoogle ScholarPubMed
Pakenham, K.I. (1999). Adjustment to multiple sclerosis: Application of a stress and coping model. Health Psychology, 18, 383–392.CrossRefGoogle ScholarPubMed
Pakenham, K.I. (2001). Coping with multiple sclerosis: Development of a measure. Psychology, Health, and Medicine, 6, 411–428.CrossRefGoogle Scholar
Pakenham, K.I. (2005). Benefit finding in multiple sclerosis and associations with positive and negative outcomes. Health Psychology, 24, 123–132.Google Scholar
Patten, S.B. & Metz, L.M. (1997). Depression in multiple sclerosis. Psychotherapy and Psychosomatics, 66, 286–292.Google Scholar
Patten, S.B., Metz, L.M., & Reimer, M.A. (2000). Biopsychosocial correlates of lifetime major depression in a multiple sclerosis population. Multiple Sclerosis, 6, 115–120.CrossRefGoogle Scholar
Pirko, I., Lucchinetti, C.F., Sriram, S., & Bakshi, R. (2007). Gray matter involvement in multiple sclerosis. Neurology, 68, 634–642.Google Scholar
Provinciali, L., Ceravolo, M.G., Bartolini, M., Logullo, F., & Danni, M. (1999). A multidimensional assessment of multiple sclerosis: Relationships between disability domains. Acta Neurologica Scandinavica, 100, 156–162.Google Scholar
Pujol, J., Bello, J., Dues, J., Cardoner, N., Marti-Vilalta, J.L., & Capdevila, A. (2000). Beck depression inventory factors related to demyelinating lesions of the arcuate fasciculus region. Psychiatry Research, 99, 151–159.Google Scholar
Pujol, J., Bello, J., Dues, J., Marti-Vilalta, J.L., & Capdevila, A. (1997). Lesions in the left arcuate fasciculus region and depressive symptoms in multiple sclerosis. Neurology, 49, 1105–1110.Google Scholar
Rabins, P.V., Brooks, B.R., O'Donnell, P., Pearlson, G.D., Moberg, P., Jubelt, B., Coyle, P., Dalos, N., & Folstein, M.F. (1986). Structural brain correlates of emotional disorder in multiple sclerosis. Brain, 109, 585–597.Google Scholar
Rao, S.M., Hammeke, T.A., McQuillen, M.P., Khatri, B.O., & Lloyd, D. (1984). Memory disturbance in chronic progressive multiple sclerosis. Archives of Neurology, 41, 625–631.Google Scholar
Rao, S.M., Leo, G.J., Bernardin, L., & Unverzagt, F. (1991). Cognitive dysfunction in multiple sclerosis. 1. Frequency, patterns, and prediction. Neurology, 41, 685–691.Google Scholar
Rao, S.M., Leo, G.J., Haughton, V.M., St. Aubin-Faubert, P., & Bernardin, L. (1989a). Correlation of magnetic resonance imaging with neuropsychological testing in multiple sclerosis. Neurology, 39, 161–166.Google Scholar
Rao, S.M., Leo, G.J., & St. Aubin-Faubert, P. (1989b). On the nature of memory disturbance in multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 11, 699–712.Google Scholar
Reischies, F.M., Baum, K., Brau, H., Hedde, J.P., & Schwindt, G. (1988). Cerebral magnetic resonance imaging findings in multiple sclerosis. Relation to disturbance of affect, drive, and cognition. Archives of Neurology, 45, 1114–1116.Google Scholar
Ron, M.A. & Logsdail, S.J. (1989). Psychiatric morbidity in multiple sclerosis: A clinical and MRI study. Psychological Medicine, 19, 887–895.Google Scholar
Sabatini, U., Pozzilli, C., Pantano, P., Koudriavtseva, T., Padovani, A., Millefiorini, E., DiBiasi, C., Gualdi, G.F., Salvetti, M., & Lenzi, G.L. (1996). Involvement of the limbic system in multiple sclerosis patients with depressive disorders. Biological Psychology, 39, 970–975.Google ScholarPubMed
Sadovnick, A.D., Remick, R.A., Allen, J., Swartz, E., Yee, I.M.L., Eisen, K., Farquhar, R., Hashimoto, S.A., Hooge, J., Kastrukoff, L.F., Morrison, W., Nelson, J., Oger, J., & Paty, D.W. (1996). Depression and multiple sclerosis. Neurology, 46, 628–632.Google Scholar
Sarason, I.G., Levine, H.M., Basham, R.B., & Sarason, B.R. (1983). Assessing social support: The Social Support Questionnaire. Journal of Personality and Social Psychology, 44, 127–139.Google Scholar
Schiffer, R.B. & Caine, E.D. (1991). The interaction between depressive affective disorder and neuropsychological test performance in multiple sclerosis patients. Journal of Neuropsychiatry and Clinical Neurosciences, 3, 28–32.Google ScholarPubMed
Schreurs, K.M.G., de Ridder, D.T.D., & Bensing, J.M. (2002). Fatigue in multiple sclerosis. Reciprocal relationships with physical disabilities and depression. Journal of Psychosomatic Research, 53, 775–781.Google Scholar
Schwartz, C.E. (1999). Teaching coping skills enhances quality of life more than peer support: Results of a randomized trial with multiple sclerosis patients. Health Psychology, 18, 211–220.Google Scholar
Schwartz, C.E., Coulthard-Morris, L., & Zeng, Q. (1996). Psychosocial correlates of fatigue in multiple sclerosis. Archives of Physical Medicine and Rehabilitation, 77, 165–170.Google Scholar
Schwartz, L. & Kraft, G.H. (1999). The role of spouse responses to disability and family environment in multiple sclerosis. American Journal of Physical Medicine and Rehabilitation, 78, 525–532.Google Scholar
Shnek, Z.M., Foley, F.W., LaRocca, N.G., Smith, C.R., & Halper, M.S. (1995). Psychological predictors of depression in multiple sclerosis. Journal of Neurologic Rehabilitation, 9, 15–23.Google Scholar
Siegert, R.J. & Abernethy, D.A. (2006). Depression in multiple sclerosis: A review. Journal of Neurology, Neurosurgery, and Psychiatry, 76, 469–475.Google Scholar
Smith, M.M. & Arnett, P.A. (2005). Factors related to employment status change in individuals with multiple sclerosis. Multiple Sclerosis, 11, 602–609.Google Scholar
Smith, S.J. & Young, C.A. (2000). The role of affect on the perception of disability in multiple sclerosis. Clinical Rehabilitation, 14, 50–54.CrossRefGoogle ScholarPubMed
Stenager, E., Knudsen, L., & Jensen, K. (1991). Acute and chronic pain syndromes in multiple sclerosis. Acta Neurologica Scandinavica, 84, 197–200.Google Scholar
Stenager, E., Knudsen, L., & Jensen, K. (1995). Acute and chronic pain syndromes in multiple sclerosis: A 5-year follow-up study. Italian Journal of Neurological Sciences, 16, 629–632.Google Scholar
Sullivan, M.J., Weinshenker, B., Mikail, S., & Edgley, K. (1995). Depression before and after diagnosis of multiple sclerosis. Multiple Sclerosis, 1, 104–108.Google Scholar
Tartaglia, M.C., Narayanan, S., Francis, S.J., Santos, A.C., De Stefano, N., Lapierre, Y., & Arnold, D.L. (2004). The relationship between diffuse axonal damage and fatigue in multiple sclerosis. Archives of Neurology, 61, 201–207.Google Scholar
Tedman, B.M., Young, C.A., & Williams, I.R. (1997). Assessment of depression in patients with motor neuron disease and other neurologically disabling illness. Journal of Neurological Sciences, 152(Suppl. 1), S75–S79.Google Scholar
Tesar, N., Baumhackl, U., Kopp, M., & Gunther, V. (2003). Effects of psychological group therapy in patients with multiple sclerosis. Acta Neurologica Scandinavica, 107, 394–399.Google Scholar
Vercoulen, J.H., Swanink, C.M., Galama, J.M., Fennis, J.F., Jongen, P.J., Hommes, O.R., van der Meer, J.W., & Bleijenberg, G. (1998). The persistence of fatigue in chronic fatigue syndrome and multiple sclerosis: Development of a model. Journal of Psychosomatic Research, 45, 507–517.Google Scholar
Voss, W.D., Arnett, P.A., Higginson, C., Randolph, J.J., Campos, M.D., & Dyck, D.G. (2002). Contributing factors to depressed mood in multiple sclerosis. Archives of Clinical Neuropsychology, 17, 103–115.Google Scholar
Zorzon, M., de Masi, R., Nasuelli, D., Ukmar, J., Mucelli, R.P., Cazzato, G., Bratina, A., & Zivadinov, R. (2001). Depression and anxiety in multiple sclerosis: A clinical and MRI study in 95 subjects. Journal of Neurology, 248, 416–421.CrossRefGoogle ScholarPubMed
Figure 0

Fig. 1. Model of depression in multiple sclerosis (MS): Disease factors predict common MS sequelae.

Figure 1

Fig. 2. Model of depression in multiple sclerosis (MS): Common MS sequelae predict depression. Note. The different types of lines in this and subsequent figures indicate the strength or weakness of the evidence supporting the influence of a particular factor on MS-related depression: An unbroken line indicates that evidence consistently supports the influence of that factor, a dashed line indicates that evidence for the influence of a particular factor appears to be less consistent on the surface but is more consistent when subject to careful analysis, and a dotted line indicates that the evidence supporting the influence of the particular factor is decidedly mixed. The thickness of the lines reflects the number of studies that have examined the influence of a particular variable on MS-related depression: Thicker lines indicate a greater number of studies, whereas thinner lines indicate fewer studies.

Figure 2

Table 1. Studies examining the relationship between common disease sequelae and depression in MS

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Figure 9

Table 2. Studies examining relationship between proposed moderators and depression in MS

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Table 2. Continued

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Figure 17

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Figure 18

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Figure 19

Table 2. Continued

Figure 20

Fig. 3. Model of depression in MS: Possible moderators predict depression.

Figure 21

Fig. 4. Model of depression in MS: Possible moderators interact with common MS sequelae to predict depression. Note. The differently colored arrows convey the category of variable in this figure: Green represents MS disease factors and blue represents common MS sequelae. The red arrows represent possible moderators. Note that the risk for depression either decreases or increases with the occurrence of the moderating variables in the right-hand circle depending upon whether they are in the adaptive or the maladaptive direction, as indicated by the upward and downward arrows underneath the right-hand circle. Empirically supported interactions between moderating variables and common MS sequelae, or between proposed moderators, are represented by pink lines from each variable intersecting at a small pink circle with an arrow leading to depression. A few hypothesized, but as yet untested, interactions between moderating variables and common MS sequelae, or between proposed moderators, are represented by orange lines from each variable intersecting at a small orange circle with an arrow leading to depression. Other possible interactions based upon the model could be derived as well