Interplay between marital attributions and conflict behavior in predicting depressive symptoms.

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J Fam Psychol. Author manuscript; available in PMC 2017 March 01. Published in final edited form as: J Fam Psychol. 2016 March ; 30(2): 286–295. doi:10.1037/fam0000181.

Interplay between Marital Attributions and Conflict Behavior in Predicting Depressive Symptoms Jenna K. Ellison, Southern Methodist University

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Chrystyna D. Kouros, Southern Methodist University Lauren M. Papp, and University of Wisconsin-Madison E. Mark Cummings University of Notre Dame

Abstract

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Marital attributions--i.e., causal inferences and explanations spouses make about their partners’ behavior--have been implicated as predictors of relationship functioning. Extending previous work, we examined marital attributions as a moderator of the link between marital conflict and depressive symptoms one year later. Participants were 284 couples who reported on marital attributions and depressive symptoms. Couples also engaged in a videotaped marital conflict interaction, which was later coded for specific conflict behaviors. The results showed that husbands’ and wives’ marital attributions about their partner moderated relations between marital conflict behavior and later depressive symptoms, controlling for global marital sentiments. For husbands, positive behavior and affect during marital conflict predicted a decrease in depressive symptoms, but only for husbands’ who made low levels of responsibility and causal attributions about their wives. Wives’ causal attributions about their partner also moderated relations between positive behavior and affect during marital conflict and husbands’ later depressive symptoms. Reflecting an unexpected finding, negative behavior and affect during marital conflict predicted increases in wives’ depressive symptoms, but only for wives who made low levels of responsibility attributions about their partner. The findings suggest that, for husbands, low levels of negative marital attributions for spouses may be protective, strengthening the positive effect of constructive conflict behaviors for their mental health, whereas for wives low levels of responsibility attributions about their spouse may be a risk factor, exacerbating the negative effect of negative marital conflict behaviors on their later depressive symptoms.

Keywords depressive symptoms; marital attributions; marital conflict; responsibility attributions; causal attributions

Correspondence concerning this article should be addressed to Chrystyna D. Kouros, Department of Psychology, Southern Methodist University, P.O. Box 750442, Dallas, TX 75219. [email protected].

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Marital conflict has been consistently shown to predict depressive symptoms both crosssectionally (Whisman, 2001) and longitudinally (e.g., Choi & Marks, 2008; Kouros, Papp, & Cummings, 2008; Whitton, Stanley, Markman, & Baucom, 2008). Specifically, negative conflict behaviors, such as hostility, personal insults, and withdrawal, are linked to higher levels of depressive symptoms (Du Rocher Schudlich, Papp, & Cummings, 2011; Laurent, Kim, & Capaldi, 2009; Proulx, Buehler, & Helms, 2009), whereas engaging in constructive conflict by using support, affection, calm discussion, and problem solving may be protective against negative mental health outcomes (e.g., Du Rocher Schudlich et al., 2011). The focus of recent research has been to identify which couples are most at risk for depressive symptoms in the context of marital discord (e.g., Davila, Karney, Hall & Bradbury, 2003; Kouros et al., 2008; Whitton et al., 2008). The current study adds to this literature by examining marital attributions about one’s partner as a moderator of the longitudinal link between marital conflict and depressive symptoms. Examining the negative marital attributions that spouses make about their partner can help inform cognitive-based treatment and prevention strategies targeted at minimizing the negative effects of marital conflict for spouses’ well-being.


Examining marital attributions as a moderator is consistent with a cognitive diathesis-stress model of depression (Abramson, Seligman, & Teasdale, 1978), which posits that individuals faced with stress (e.g., marital conflict) are more vulnerable to experiencing depressive symptoms when they make negative attributions (see also Hammen, 2005). Attributions broadly refer to the inferences that one makes to explain negative events. In the context of a negative event, individuals who make internal (caused by the person), stable (negative events will persist), and global (negative events will have wide spread effects) attributions are most at risk for developing or maintaining their depressive symptoms (Abramson, Metalsky, & Alloy, 1989). While the cognitive-diathesis stress model focuses on explanations individuals make about their own behavior, one may also make attributions about his or her partner’s behavior. In the context of close relationships, marital attributions refer to the inferences one makes about their spouse’s behavior (Bradbury & Fincham, 1992). There are two broad categories of marital attributions. One category of negative marital attributions is causal attributions, which refer to internal, stable, and global attributions about one’s partner’s behavior. That is, causal marital attributions would be evaluations that one’s partner’s negative behavior was caused by the partner, and that the negative behavior will persist and have wide spread effects. Another category of negative marital attributions is responsibility attributions, which are attributions of blame, selfishness, and that one’s partner’s negative behavior was on purpose (i.e., negative intent). According to cognitive models of relationships (Bradbury & Fincham, 1990; Karney, McNulty, & Bradbury, 2003), these negative attributions are proposed to over-emphasize spouses’ negative behaviors, while also minimizing spouses’ positive behaviors; therefore, they may exacerbate the effect of marital conflict for spouses’ mental health and well-being. Although both cognitive models of depression and cognitive models of relationships posit that negative attributions can exacerbate the effects of negative events, there is an important conceptual distinction between these two models. The cognitive-diathesis stress model is an individual-level model and emphasizes that attributions about oneself (i.e., blaming one’s

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self for a negative event or believing one is the cause of negative events) is maladaptive for their mental health. In close relationships, in which marital events are the stressor, attributions about one’s partner are naturally elicited; in this dyadic context, it is the negative attributions about the partner (as opposed to the self) that are maladaptive for the individual and the relationship (Fincham, 2003).


Previous research has documented links between negative marital attributions and relationship functioning, even when controlling for marital satisfaction (see Johnson, Karney, Rogge, & Bradbury, 2001). Higher levels of negative attributions about one’s spouse are significantly related to using more negative (e.g., hostility, criticism) and less positive (e.g., problem-solving) behaviors during conflict (Bradbury & Fincham, 1992; Bradbury, Beach, Fincham, & Nelson, 1996; Durtschi, Fincham, Cui, Lorenz, & Conger, 2011; Osterhout, Frame, & Johnson, 2011). Examining within-person relations, Sanford (2006) found that within-person variability in real-time marital attributions across marital interactions significantly predicted both husbands’ and wives’ positive and negative communication. With respect to differential effects of responsibility versus causal attributions, Davey, Fincham, Beach, and Brody (2001) proposed that responsibility attributions are more proximally related to marital conflict than causal attributions. Indeed, they found evidence for longitudinal mediation such that causal attributions were related to marital conflict via responsibility attributions. Similarly, Fincham and Bradbury (1992) found that responsibility, but not causal, attributions related to wives’ affect during a problem-solving discussion. In contrast, Miller and Bradbury (1995) found that both responsibility and causal attributions were related to spouses’ behavior during marital interactions. Specifically, wives’ responsibility attributions were related to her own negative behavior during a problem-solving and social support discussion, and both types of attributions were related to wives reciprocating their husbands’ negative behavior. Husbands’ causal attributions were related to an increased likelihood of reciprocating their wives’ negative behavior. Whereas this research shows a robust link between marital attributions and marital functioning, it is unclear whether marital attributions exacerbate the effects of marital functioning for spouses’ individual health.

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Two studies, to our knowledge, have explicitly tested negative attributions as a moderator of the link between marital discord and depressive symptoms. In one, Heene, Buysse, and Van Oost (2007) found that depressive symptoms were associated with lower levels of marital satisfaction when spouses made fewer causal attributions. The authors suggested that depressed individuals are more likely to see themselves, rather than their partner, as the cause of negative behavior which, in turn, leads to lower levels of relationship satisfaction. In the second, Gordon, Friedman, Miller, and Gaertner (2005) found that the relation between marital distress and depressive symptoms was stronger among individuals who made more responsibility attributions about their partner, whereas making fewer responsibility attributions served a protective function. Causal attributions, on the other hand, did not moderate this link. The authors posited that responsibility attributions likely moderated relations because beliefs that one’s partner as blameworthy, selfish, and purposefully acting negative can foster a sense of betrayal in the relationship, thereby exacerbating depressive symptoms.


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The aim of the present study was to test marital attributions as a moderator of the longitudinal relation between marital conflict and depressive symptoms one year later. That is, we examined positive and negative marital conflict as predictors of change in depressive symptoms over one year, and tested the extent to which these longitudinal relations differed for spouses who tended to evaluate and interpret their partners’ behavior in a blameworthy and causal (e.g., their partners’ negative behavior will persist) manner as compared to spouses who evaluated their partners’ negative behavior in more benign ways. Whereas theoretical perspectives have highlighted the important role of marital attributions for relationship functioning and depressive symptoms, few empirical studies of the moderating role of attributions have been conducted. Rather, previous work has primarily focused on the direct relation between marital distress, broadly defined, and marital attributions. In order to draw more cogent conclusions regarding the role of negative marital attributions—that is, the cognitive inferences one makes about their spouses’ behavior--we controlled for overall, global positive and negative sentiments about one’s partner (i.e., sentiment override; Weiss, 1980). We hypothesized that negative marital attributions would exacerbate the positive relation between negative behavior and affect during marital conflict and later depressive symptoms, and weaken the negative relation between positive behavior and affect during marital conflict and later depressive symptoms.

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Method Participants

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Participants were drawn from a larger study on family processes and child development; the first two waves of data from this study were used (data collected between 1999 and 2002). Families were recruited from the community through newspaper and radio advertisements, flyers, and local public schools. At Time 1 (T1), 296 heterosexual couples participated. As part of the inclusion criteria, couples had to have been living together for at least two years (M = 13.22 years, SD = 6.02 years) and have a child between the ages of 8 and 16 (M = 11.05 years, SD = 2.31). At Time 2 (T2; one year later), 265 families participated in the study. Of the 31 families that dropped from the study, 11 indicated that they were too busy, nine families either moved away or could not be contacted, five couples divorced or separated, and six families were no longer interested in participating. Twelve families did not complete the marital interaction task or the marital attributions measure and dropped from the study at Time 2; these couples were excluded from analyses since they were missing information on all key study variables. Analyses, thus, are based on the 284 couples who provided data on at least one of the key constructs of the study (i.e., marital attributions, marital conflict, depressive symptoms).

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Wives’ mean age was 37.74 years (SD = 5.94) and husbands’ mean age was 40.13 (SD = 6.75) at T1. Approximately 36% of wives and 43% of husbands had at least a college degree, and the median household income was between $40,000 and $65,000 (adjusting for inflation, equivalent to approximately $55,000 and $83,000 in 2015). The sample was primarily European American (88.7% of wives and 87.3% of husbands); 7% of wives and 8.8% of husbands were African American, 2.5% of wives and 3.5% of husbands were


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Hispanic, one wife and one husband reported they were biracial, and one wife reported her race as Native American. Three wives did not report their race. Couples who completed the marital interaction task at T1 did not significantly differ from couples who did not complete the task based on age, household income, years living together, levels of depressive symptoms, or negative marital attributions. Couples who did not complete measures at T2 did not significantly differ from those couples that did complete measures based on age, household income, years living together, or levels of T1 negative attributions; however, couples who did not complete measures at T2 included wives who reported significantly higher levels of T1 depressive symptoms, t(275) = 4.51, p < .001. Procedures

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Each year, couples completed measures and tasks during a laboratory visit. Husbands and wives independently completed questionnaires about themselves and their marriage, and completed an observational marital interaction task (described below). Only the measures relevant to the current study are presented. The study was approved by the institutional review board for the protection of human subjects and couples provided informed consent. Couples were monetarily compensated for their participation: $100 at Time 1 and $120 at Time 2; a subset of couples were paid $200 at Time 2 for completing additional measures and tasks. Measures

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Depressive symptoms—At T1 and T2, depressive symptoms were measured with the Center for Epidemiological Studies on Depression Scale (CES-D; Radloff, 1977). Participants reported how frequently they experienced a list of 20 depressive symptoms in the past week on a scale ranging from 0 (less than a day) to 3 (5–7 days). Items were summed to create an overall depressive symptoms score, with scores of 16 or above indicating potentially clinical levels of depression (Myers & Weissman, 1980). In this sample, Cronbach’s alpha coefficients were .91 and .90 at T1 and T2, respectively, for wives, and .87 and .83 at T1 and T2, respectively, for husbands.

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Observational measure of marital conflict—A videotaped marital interaction task was used to assess everyday marital conflict (see Du Rocher Schudlich & Cummings, 2003). Couples chose and discussed an everyday topic of disagreement for 7.5 minutes. Marital conflict was defined as any difference of opinion, whether minor or major, which allowed for a wide range of conflict behaviors and topics representative of everyday marital conflict to be captured (Cummings, Goeke-Morey, & Papp, 2004). Couples were instructed to choose a topic that had come up recently or often that they felt was problematic and difficult to handle, and to discuss their topic like they would at home, with the goal of working toward a resolution. Tapes of the marital interactions were coded by trained research assistants using a coding system adapted from Mangelsdorf and colleagues (e.g., Frosch, Mangelsdorf, & McHale, 1998). The marital behavior coding scales consist of 8 dyadic scales and 2 scales coded for


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each spouse; each scale is coded on a 7-point Likert scale. The scales include (1) engagement, a dyadic code reflecting interpersonal involvement and partner-directed behaviors (e.g., visual regard, initiation of conversation, attempts at maintenance of conversation); (2) enjoyment, a dyadic scale assessing the degree to which the couple demonstrates enjoyment of their interaction; (3) positive affect toward ones’ partner (e.g., laughing, smiling, vocalizations, signs of affection), which was individually coded for each spouse; (4) antagonism/irritation, a dyadic code representing hurtful comments, derision, and criticism; (5) negative affect towards one’s partner (e.g., eye rolling, anger, frowning), which was individually coded for each spouse; (6) cooperation, a dyadic code reflecting the degree of mutual participation, joint focus on the interaction, and a sense of “we-ness”; (7) balance/reciprocity, a dyadic code assessing control, turn-taking, and equity; (8), global rating of interaction quality, which is a dyadic code tapping the overall quality of the relationship, such as liking, caring, and positive emotional commitment in the couple; (9) sensitivity/support, a dyadic code reflecting the extent to which spouses listened to each other, and perceived and responded to their partner’s feelings and signals appropriately and in a warm manner; and (10) conflict resolution, a dyadic code reflecting the extent to which couples resolved their conflict in a mutually satisfying manner. In this sample, inter-rater reliability (i.e., intra-class correlations) ranged from .68 – .87 for these scales.

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Data Reduction: To reduce the number of marital conflict scales, we conducted a principalaxis factor analysis in SPSS v. 23, using a promax rotation, which allows factors to correlate. Based on the initial results of this factor analysis (eigenvalues, scree plot), and the results of a complementary minimum average partial (MAP) test and parallel principal components analysis (O’Connor, 2000), two factors were retained. The following observational codes (with factor loadings in parentheses) loaded onto one factor and were summed to create a Positive Marital Conflict composite, reflecting positive behavior and affect during marital conflict: engagement (.77), enjoyment (.61), wife positive affect toward partner (.58), husband positive affect toward partner (.75), cooperation (.70), balance (.73), sensitivity/support (.66), and global rating of interaction quality (.71). Cronbach’s alpha of this composite was .89. The following three observational codes (with factor loadings in parentheses) loaded onto a second factor and were summed to create a Negative Marital Conflict composite, reflecting negative behavior and affect during marital conflict: irritation/ antagonism (.88), wife negative affect toward partner (.92), and husband negative affect toward partner (.78). Cronbach’s alpha of this composite was .86. The conflict resolution scale did not load onto either factor and was not analyzed.

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Marital attributions—At T1, couples completed the Relationship Attributions Measure (RAM; Fincham & Bradbury, 1992), which assesses attributions that spouses make about their partner. Couples were given 4 hypothetical situations about their spouses (e.g., “Your husband criticizes something you say”) followed by 6 attributional statements about their spouses’ behavior, representing both causal (“My husband’s behavior was due to something about him (e.g., the type of person he is, the mood he was in”) and responsibility (e.g., “My husband criticized me on purpose rather than unintentionally”) attributions. Participants rated their level of agreement with each statement on a 6-point Likert scale ranging from 1 (Disagree strongly) to 6 (Agree strongly). Although the RAM uses hypothetical situations to


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assess marital attributions, Fincham and Bradbury (1992) found that attributions endorsed on the RAM for hypothetical situations were significantly associated with attributions made about self-selected real marital difficulties. In this sample, Cronbach’s alpha was .86 for both husbands’ and wives’ causal attributions, and .89 and .90 for husbands’ and wives’ responsibility attributions, respectively.

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Marital sentiments—Husbands and wives reported on their global marital sentiments on the Positive and Negative Quality in Marriage Scale (Fincham & Linfield, 1997). The 3item positive marital sentiments (PMQ) and 3-item negative marital sentiments (NMQ) subscales were included as covariates in the current study. Participants separately rated the positive and negative qualities and feelings toward their partner on a 10-point scale; items were summed with higher scores indicating more global positive or negative evaluations of one’s partner. In this sample, Cronbach’s alpha was .92 wives’ PMQ and NMQ, and .89 and .88 for husbands’ PMQ and NMQ, respectively. Analysis Plan

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To control for the interdependence in couple data, we used a moderated Actor Partner Interdependence Model (APIM; Cook & Kenny, 2005; Kashy & Kenny, 2000). Analyses were run using the Analysis of Moment Structures (AMOS, v. 23) software, and full information maximum likelihood estimation (FIML) was used to account for missing data. Figure 1 provides an example of the path models tested. The models included both positive and negative marital conflict as predictors of husbands’ and wives’ depressive symptoms, and controlled for husbands’ and wives’ positive and negative marital sentiments and their T1 depressive symptoms. To test marital attributions as moderators, causal and responsibility attributions and the marital conflict composites were mean-centered to create the interaction terms (Aiken & West, 1991). Mean-centered predictors and the interaction terms were then included in the APIM (e.g., Papp, Kouros, & Cummings, 2010). Acceptable model fit was evaluated with several fit indices, including the χ2 statistic; a relative χ2 index (χ2/df) below 3 (Bollen, 1989), a comparative fit index (CFI; Bentler, 1990) above .95, and a root mean square error of approximation (RMSEA; Browne & Cudeck, 1993) below .08.

Results Descriptive Statistics

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Means, standard deviations, and correlations between the study variables are presented in Table 1. Based on a cut-off score of 16, 15.5% of wives (n = 44) and 10.9% of husbands (n = 31) reported potentially clinical levels of depressive symptoms at T2. Wives reported significantly higher levels of depressive symptoms than their husbands at T2, t(242) = 2.41, p = .02. There was no significant difference between husbands’ and wives’ levels of causal, t(262) = .19, p = .85, or responsibility, t(262) = .45, p = .66, attributions. Husbands’ Marital Attributions as a Moderator of the Relation between Marital Conflict Behavior and Depressive Symptoms Responsibility attributions—The results from the APIM testing husbands’ responsibility attributions about their spouse as a moderator of the link between positive and


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negative marital conflict and spouses’ depressive symptoms is presented in the left-hand side of Table 2. Husbands’ responsibility attributions moderated the relation between positive marital conflict and their own depressive symptoms one year later, b = .02, SE = . 01, p = .02. Specifically, positive behavior and affect during marital conflict was negatively related to husbands’ T2 depressive symptoms, but only for husbands who made low levels of responsibility attributions about their spouse (Figure 2, Panel A). In contrast, positive marital conflict was not related to later depressive symptoms for husbands with higher levels of responsibility attributions.

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Causal attributions—The results from the APIM testing husbands’ causal attributions about their spouse as a moderator are presented in the right-hand side of Table 2. Husbands’ causal attributions about wives moderated the link between positive behavior and affect during marital conflict and husbands’ depressive symptoms one year later, b = .02, SE = .01, p = .006. Similar to the interaction pattern above, positive marital conflict was related to a decrease in husbands’ depressive symptoms, but only for husbands who made low levels of causal attributions about their spouse (Figure 2, Panel B). Wives’ Marital Attributions as a Moderator of the Relation between Marital Conflict Behavior and Depressive Symptoms

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Responsibility attributions—The results from the APIM testing wives’ responsibility attributions about their spouse as a moderator of the link between positive and negative marital conflict and spouses’ depressive symptoms are presented in the left-hand side of Table 3. Wives’ negative responsibility attributions moderated the relation between negative marital conflict and wives’ T2 depressive symptoms; however, this interaction was not in the expected direction. Specifically, higher levels of negative behavior and affect during marital conflict was related to higher levels of wives’ T2 depressive symptoms, but only for wives who made lower levels of responsibility attributions about their husbands, b = −.13, SE = .05, p = .018 (Figure 3). In contrast, negative marital conflict was not significantly related to wives’ depressive symptoms among wives who made higher levels of responsibility attributions about their spouse.

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Causal attributions—The results from the APIM testing wives’ causal attributions about their partner as a moderator are presented in the right-hand side of Table 2, and revealed a significant cross-partner interaction between wives’ causal attributions and positive marital conflict in predicting husbands’ T2 depressive symptoms, b = .02, SE = .01, p = .006. Higher levels of positive marital conflict was related to decreased depressive symptoms among husbands, but only for husbands’ whose wives made lower levels of causal attributions about them (Figure 4). At high levels of wives’ causal attributions, positive marital conflict was not significantly related to husbands’ T2 depressive symptoms.1

1Post-hoc analyses tested marital attributions as a moderator of the cross-sectional relation between marital conflict and depressive symptoms at T1. Although main effects of marital conflict and marital attributions were significant, no significant interactions emerged (results available in Supplemental Tables 1 and 2). J Fam Psychol. Author manuscript; available in PMC 2017 March 01.

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Correction for Multiple Tests

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Given the multiple tests conducted in this study, we applied Benjamini-Hochberg’s false discovery rate correction (Benjamini & Hochberg, 1995) to our findings (maintaining alpha at .05). This method controls for the expected proportion of false positives (i.e., incorrectly rejecting the null hypothesis) by adjusting the p-value based on the number of significant results in a family of tests. The three significant interactions predicting husbands’ depressive symptoms (out of 8 total interaction tests across the 4 APIM models) and the one interaction predicting wives’ depressive symptoms (out of 8 total interaction tests across the 4 APIM models) remained significant after accounting for the multiple tests conducted. Thus, it is unlikely our findings are due to chance.

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The current study examined marital attributions as a moderator of the longitudinal relation between marital conflict behavior and depressive symptoms one year later. The findings from this study extend previous work on moderators of the marital discord-depression link by highlighting an additional factor—one’s cognitive attributions about their partner—that may place some couples at increased risk for depressive symptoms in the context of marital conflict. Given the dearth of longitudinal studies on cognitive processes in close relationships (see Karney et al., 2003), a notable contribution of our study is showing that marital attributions and conflict can have a relatively long-term effect on couples’ mental health. Notably, moderation effects held when accounting for sentiment override (i.e., global positive and negative marital sentiments); thus, increasing confidence in our findings.


Positive behavior and affect during marital conflict predicted fewer depressive symptoms for husbands who made fewer responsibility and causal attributions about their spouse. This is consistent with findings by Gordon et al. (2005), who found that when fewer responsibility attributions are made, the association between marital discord and depressive symptoms is weakened, and Heene et al. (2007) who found that depressive symptoms were related to lower marital satisfaction in the context of low causal attributions. Moreover, a cross-partner effect was found such that positive marital conflict was also associated with a decrease in husbands’ depressive symptoms when their wives made fewer causal attributions about them. Research has consistently documented that positive, constructive marital conflict behaviors (e.g., sensitivity, caring) can have beneficial effects for mental health (e.g., Du Rocher Schudlich et al., 2011); findings from this study extend this work by indicating that this may be especially true for husbands who make fewer negative attributions about their partner and whose wives make fewer causal attributions about them. The findings demonstrate the importance of examining attributions at the dyadic level to better understand factors that may make spouses, particularly husbands, more vulnerable for developing depressive symptoms in the context of marital conflict. Moderator results were in the opposite direction than was expected for wives. Negative affect and behavior during marital conflict positively predicted wives’ depressive symptoms, but only among wives who made fewer responsibility attributions about their partner. One potential explanation of this unexpected finding is that in the context of negative marital interactions, in which one’s partner makes hurtful comments and criticisms, wives who do J Fam Psychol. Author manuscript; available in PMC 2017 March 01.

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not blame their spouses instead blame themselves, which leads to increases in depressive symptoms. This explanation is consistent with theories that suggest that females’ selfrepresentations are more influenced by close, dyadic relationships as compared to males (Acitelli & Young, 1996; Cross & Madson, 1997), and that depression is more of an interpersonal experience for women as compared to men (Gotlib & Hammen, 1992; Hammen, 2003). This explanation also has empirical support. Whisman (2001) reported that negative marital conflict is more strongly related to depressive symptoms for wives compared to husbands (Whisman, 2001). Wives find marital conflict more upsetting than husbands (Almeida & Kessler, 1998), and husbands’ hostile behavior can longitudinally predict wives’ depressive symptoms (Proulx et al., 2009). Further, women perceive themselves as being responsible for resolving and avoiding conflict in the relationship (Madden & Janoff-Bulman, 1981; Nolen-Hoeksema & Girgus, 1994). Thus, in the context of negative marital conflict, wives may tend to direct their negative attributions toward themselves instead of their partner in order to protect the relationship during times of distress. The findings highlight a potentially interesting sex difference in the interpersonal mechanisms underlying depression. For women, attributions about the self are likely linked to later depression, whereas for men, partner attributions (attributions about their partner and their partners’ attributions about them) appear to be a key contributing factor in predicting depression. Given the limited work on the moderating role of attributions in the marital context and that we did not measure self-attributions, our explanations are speculative and warrant further investigation.


Notably, across the significant interactions, a consistent pattern emerged in which the highest levels of depressive symptoms occurred when there was dissonance between ones’ attributions about their partner and the behavior and emotions displayed during marital conflict. For example, husbands who made low levels of responsibility and causal attributions—that is, had more positive views about their partner—experienced the highest levels of depressive symptoms when there was less positive marital conflict. Similarly, for wives, the highest level of depressive symptoms occurred when there was a discordance between their attributions about their partner (low responsibility attributions) and behavior and affect during conflict (more negative). Thus, the psychological distress associated with the mismatch between ones’ thoughts about their partner and the interactions one has with his or her partner may be another potential explanation for the findings. In contrast, when husbands’ and wives’ perceptions of their partner (more negative) and behavior and affect during marital conflict (more negative, less positive) were congruent, these spouses experienced lower levels of depressive symptoms. Consistent with this interpretation, McNulty and Karney (2004) found that when wives’ expectations of their husbands’ behavior and relationship behaviors were both high, marital satisfaction was stable across the 4-year study period; however, when wives’ expectations and relationship behaviors did not match, there was a steeper decline in marital satisfaction. The authors concluded that both positive and negative expectations can be adaptive depending on the positive or negative nature of the relationship context. This explanation of the findings provides an extension of self-verification theory (Swann, 1983) to the dyadic relationship. According to this theory and research, couples experience more positive relationship outcomes (e.g., greater commitment and intimacy) when partners verify their own self view--whether


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positive or negative (Swann, De La Ronde, & Hixon, 1994; Swann, Hixon, & De La Ronde, 1992). Our results show that positive outcomes with regard to individual mental health can also arise from situations when one’s attributions about their partner--whether positive or negative--are verified by observable behavior in the relationship.

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This study found support for responsibility and causal attributions as moderators of the association between marital conflict and depressive symptoms for husbands and wives. Although studies of the moderating role of marital attributions are limited, our findings are in contrast to Gordon and colleagues (2005) who found significant moderation for responsibility but not causal attributions. One potential explanation for this discrepancy may be due to differences in samples; the sample in the current study included both spouses, whereas the sample in Gordon et al. (2005) included married individuals and primarily consisted of women (74% of sample). Thus, Gordon et al. (2005) were unable to examine cross-partner effects and may not have found significant moderation for causal attributions if results were largely driven by the predominately female sample. Given marital attributions inherently occur in a dyadic, marital context, continuing to examine cross-partner effects of negative attributions on individual and relationship well-being is an important future research direction.

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There were several limitations of the current study. First, the sample was generally wellfunctioning, with regard to levels of depressive symptoms and negative conflict behaviors. Marital attributions may differentially moderate the link between marital conflict and depressive symptoms in samples where one or both partners have high levels of depressive symptoms or engage in more destructive conflict behaviors. Second, the sample in this study was predominantly White and middle-class, and therefore the findings may not generalize to more diverse samples, such as low-income or minority couples. Third, the data are correlational, and there may be a third variable that accounts for the relations observed. For example, it is possible that the association between negative marital attributions and depressive symptoms may be accounted for by an individual’s general negative affectivity. For example, Karney, Bradbury, Fincham, and Sullivan (1994) found evidence that spouses high in negative affectivity were more likely to make negative marital attributions; however, results also indicated that the association between marital attributions and marital satisfaction remained significant when accounting for negative affectivity.

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Results from this study have important theoretical and clinical implications for working with couples. In the broader theoretical context, results from the current study integrate prior research by examining both marital attributions and conflict in predicting depressive symptoms. While previous work has long documented the association between marital conflict and depression (see Whisman, 2001), research is needed to determine which factors differentiate who is most at risk for developing symptoms. Results from this study suggest the behaviors that spouses engage in during conflict alone may not be sufficient for explaining variability in depressive symptoms; cognitive processes within relationships are also critical to examine. Results from the current study may also inform clinical work. Although standard couples therapy typically addresses conflict and communication strategies, the current findings suggest that addressing marital attributions may increase the efficacy of therapy. For husbands, teaching constructive conflict behavior and strategies


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(e.g., support) may only decrease later depressive symptoms if the treatment also addresses the attributions that husbands makes about their wives. For wives, reducing negative marital attributions about one’s spouse might not in and of itself be sufficient; treatments may also need to address wives’ attributions about themselves to prevent inaccurate self-responsibility attributions. Directly addressing negative marital attributions in treatment may help spouses better distinguish between internal and external factors accounting for their partners’ behavior, which can lead to improvements in marital interactions and decreases in future depressive symptoms.

Supplementary Material Refer to Web version on PubMed Central for supplementary material.

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Acknowledgments This research was funded by National Institute of Child Health and Human Development Grant R01HD36261 awarded to E. Mark Cummings. C. Kouros is a former trainee on NIMH T32-MH18921 (2008–2011).

References


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Figure 1.

Example of moderated APIM examining marital attributions as a moderator of the link between positive and negative marital conflict and both husbands’ and wives’ depressive symptoms. Four separate APIMS tested the following moderators: husband responsibility attributions, husband causal attributions, wife responsibility attributions, and wife causal attributions. The covariates and predictors were correlated (not depicted in figure)

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Figure 2.

Interactions between husbands’ responsibility attributions and positive marital conflict (Panel A) and husbands’ causal attributions and positive marital conflict (Panel B) in predicting Time 2 depressive symptoms. Note. Low and high husband negative responsibility attributions are plotted at −1 SD and +1 SD, respectively, from the mean.


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Author Manuscript Author Manuscript Figure 3.

Author Manuscript

Interaction between wives’ responsibility attributions and negative marital conflict in predicting wives’ Time 2 depressive symptoms. Note. Low and high wife negative responsibility attributions are plotted at −1 SD and +1 SD, respectively, from the mean.


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Page 18

Author Manuscript Author Manuscript Figure 4.

Author Manuscript

Cross-partner interaction between wives’ causal attributions and positive marital conflict in predicting husbands’ Time 2 depressive symptoms. Note. Low and high wife causal responsibility attributions are plotted at −1 SD and +1 SD, respectively, from the mean.


Author Manuscript

Author Manuscript 269 266 270 269 277 267 267 284 284 284 284

2. Wife Causal Attributions

3. Husband Responsibility Attributions

4. Wife Responsibility Attributions

5. Husband Depressive Symptoms

6. Wife Depressive Symptoms

7. Negative Conflict Communication

8. Positive Conflict Communication

9. Husband NMQ

10. Husband PMQ

11. Wife NMQ

12. Wife PMQ

J Fam Psychol. Author manuscript; available in PMC 2017 March 01. 248


8. Positive Conflict Communication

7. Negative Conflict Communication



4. Wife Responsibility Attributions

3. Husband Responsibility Attributions

2. Wife Causal Attributions

1. Husband Causal Attributions

Time 1

247


Time 2

266

1. Husband Causal Attributions

Time 1

N

9.

9.84

8.41

26.70

9.63

26.51

9.15

37.19

3.73

10.13

8.79

31.49

31.02

40.33

40.07

M

10.

8.63

6.39

3.72

5.90

3.57

5.08

5.40

1.69

9.19

7.61

11.25

10.39

10.73

10.21

SD

−.00

.20** .25** .17** −.28** .29** −.21** .39** −.27**

.31** .19** .07 −.18** .36** −.19** .12* −.16**

.11

.13* 11.

.10

.20**

12.

.03

.61**

.17**

13.

14.

.11

.12

−.21**

.18**

−.18**

.37**

−.15*

.23**

.20**

.27**

.62** ---

3.

---

2.

.26**

---

1.

.04

.09

−.38**

.41**

−.19**

.24**

−.30**

.21**

.21**

.16**

---

4.

.15*

.62**

−.16*

.20**

−.26**

.27**

−.23**

.16*

.23**

---

5.

.67**

.24**

−.19**

.25**

−.16**

.27**

−.24**

.17**

---

6.

---

7.

.12

.07

−.19*

.11

−.06

.17**

−.49**

Author Manuscript

Descriptive Statistics and Correlations among Study Variables

−.14*

−.17*

.24**

−.22**

.25**

−.24**

---

8.

Author Manuscript

Table 1 Ellison et al. Page 19

−.23** .32**

.32** −.35**

11. Wife NMQ 12. Wife PMQ

−.19**

.22**


−.17**

.20**

−.44**

---

11.

−.17**

−.13*

---

12.

.33**

---

13.

---

14.

p< .01,

p< .10.

p< .05,

†

*

**

Note. N = 284 couples for analyses. NMQ = Negative Quality in Marriage Scale, PMQ = Positive Quality in Marriage Scale.

−.26**

.20**


Time 2

---

−.44**

10.

10. Husband PMQ

9.

Author Manuscript ---

Author Manuscript

9. Husband NMQ

Ellison et al. Page 20

Author Manuscript

Author Manuscript


Author Manuscript

Author Manuscript

Author Manuscript −0.17 (.22) −0.03 (.03)

  T1 Negative Conflict

  T1 Husbands’ Marital Attributions

0.06 (.07)

  T1 Negative Marital Sentiments

J Fam Psychol. Author manuscript; available in PMC 2017 March 01. 1.00

CFI

.00 (.00–.06)

1.00

0.64

p< .01,

p< .05,

*

**

Model included the covariates of husbands’ T1 depressive symptoms, positive marital sentiments, and negative marital sentiments as predictors of husbands’ T2 depressive symptoms, and the covariates of wives’ T1 depressive symptoms, positive marital sentiments, and negative marital sentiments as predictors of wives’ T2 depressive symptoms.

a

.51

−0.02 (.08)

−0.09 (.12)

χ2(6) = 3.82, p = .70

.45

0.01 (.07)

−0.03 (.10)

0.67 (.05)**

0.02 (.02)

−0.01 (.01)

0.004 (.04)

0.08 (.28)

−0.11 (.09)

b (SE)

T2 Wife Depressive Symptoms

Note. N= 284 couples. Two separate APIMS tested husbands’ responsibility attributions and casual attributions as moderators.

.00 (.00–.06)

0.62

RMSEA (90% CI)

.52

−0.02 (.08)

−0.07 (.12)

0.53 (.04)**

0.01 (.02)

0.04 (.02)†

0.68 (.05)**

0.02 (.01)**

0.001 (.03)

−0.16 (.22)

−0.06 (.07)

b (SE)

T2 Husband Depressive Symptoms

Moderator: Causal Attributions

0.004 (.01)

0.06 (.04)

0.13 (.28)

−0.08 (.09)

χ2(6) = 3.73, p = .71

χ2/df

χ2 (df) p

Model Fit

−0.02 (.10)

  T1 Positive Marital Sentiments

.45

0.53 (.04)**

  T1 Depressive Symptoms

R2

0.02 (.02)

  Husbands’ Marital Attribution × Negative Conflict

Covariatesa

0.02 (.01)*

  Husbands’ Marital Attribution × Positive Conflict

Moderated Paths

−0.08 (.07)

b (SE)

b (SE)

  T1 Positive Conflict

Main Effects



Moderator: Responsibility Attributions

Interactions between Husbands’ Marital Attributions and Marital Conflict Predicting T2 Depressive Symptoms

Author Manuscript


Page 22

†

p< .10

Ellison et al.

Author Manuscript Author Manuscript Author Manuscript Author Manuscript J Fam Psychol. Author manuscript; available in PMC 2017 March 01.

Author Manuscript

Author Manuscript

Author Manuscript −0.32 (.29) 0.01 (.03)

  T1 Negative Conflict

  T1 Wives’ Marital Attributions

0.02 (.07)

  T1 Negative Marital Sentiments

J Fam Psychol. Author manuscript; available in PMC 2017 March 01. 1.00

CFI

.00 (.00–.07)

1.00

0.88

p < .01,

p < .05,

*

**

Model included the covariates of wives’ T1 depressive symptoms, positive marital sentiments, and negative marital sentiments as predictors of wives’ T2 depressive symptoms, and the covariates of husbands’ T1 depressive symptoms, positive marital sentiments, and negative marital sentiments as predictors of husbands’ T2 depressive symptoms.

a

.51

−0.01 (.08)

−0.09 (.12)

χ2(6) = 5.29, p = .51

.46

0.02 (.07)

−0.04 (.10)

0.68 (.05)**

0.07 (.35)

−0.01 (.01)

−0.03 (.04)

0.07 (.35)

−0.12 (.09)

b (SE)


Note. N = 284 couples. Two separate APIMS tested wives’ responsibility attributions and casual attributions as moderators.

.00 (.00–.06)

0.60

RMSEA (90% CI)

.53

0.03 (.08)

−0.12 (.12)

0.54 (.04)**

0.06 (.03)†

−0.08 (.03)**

0.68 (.04)**

0.02 (.01)**

−0.02 (.03)

−0.43 (.27)

−0.07 (.07)

b (SE)


Moderator: Causal Attributions

−0.01 (.01)

−0.10 (.04)*

0.81 (.37)*

−0.06 (.09)

χ2(6) = 3.57, p = .73

χ2/df

χ2 (df) p

Model Fit

−0.05 (.10)

  T1 Positive Marital Sentiments

.45

0.53 (.04)**

  T1 Depressive Symptoms

R2

0.02 (.02)

  Wives’ Marital Attribution × Negative Conflict

Covariatesa

0.01 (.01)

  Wives’ Marital Attribution × Positive Conflict

Moderated Paths

−0.06 (.07)

b (SE)

b (SE)

  T1 Positive Conflict

Main Effects



Moderator: Responsibility Attributions

Interactions between Wives’ Marital Attributions and Marital Conflict Predicting T2 Depressive Symptoms

Author Manuscript


Page 24

†

p < .10

Ellison et al.

Author Manuscript Author Manuscript Author Manuscript Author Manuscript J Fam Psychol. Author manuscript; available in PMC 2017 March 01.

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