Partner enhancement versus verification and emotional responses to daily conflict

Abstract

This study investigated the moderating role of partner enhancement and verification on couples’ emotional responses to daily conflicts. Each evening for 5 weeks, 264 couples in which one partner was under stress reported whether a conflict occurred and both positive and negative relationship feelings. Partners rated each other on relationship-central and relationship-peripheral traits before the diary period, allowing us to examine the consequences of derogation (partner views more negative than self-views) and enhancement (partner views more positive than self-views) relative to verification. Derogation on both relationship-central and relationship-peripheral traits was associated with more negative conflict responses. Enhancement on relationship-peripheral traits was associated with more negative conflict responses than verification. Although not as consistent a pattern, results suggest that enhancement on relationship-central traits was beneficial.

Keywords

Conflict daily diary intimate relationships positive illusions self-verification

The way intimate partners view one another can have an important impact on relationship functioning (e.g., Murray, Holmes, & Griffin, 1996a, 1996b; Swann, De La Ronde, & Hixon, 1994; see Gagné & Lydon, 2004; Niehuis, Lee, Reifman, Swenson, & Hunsaker, 2011, for reviews). According to self-verification theory, individuals seek information that confirms existing self-views and are more intimate with marriage partners who confirm these views (Swann et al., 1994). However, research on positive illusions suggests that being viewed by one’s partner in an overly positive manner is more beneficial than being viewed accurately (Fowers, Lyons, Montel, & Shaked, 2001; Murray et al., 1996a, 1996b). To date, studies of self-verification and idealization have largely focused on global outcomes associated with such states. However, how individuals are viewed by their partners is likely to be related not only to global states but also to how they respond to particular relational events, such as conflict. The relative accuracy of partner evaluations may influence the cause, course, and resolution of a conflict. The current study uses a daily diary design to investigate how being idealized versus verified by one’s romantic partner moderates the impact of daily relational conflict on relationship evaluation.

Self-verification versus positive illusions

According to self-verification theory (De La Ronde & Swann, 1998; Swann et al., 1994), individuals are more satisfied in relationships in which their partners’ views confirm their views of themselves. Thus, individuals should be less satisfied when their partners’ views are incongruent with self-views, whether such views are overly negative (derogation) or overly positive (enhancement).¹ Self-verification theory assumes that people want to maintain a coherent image of themselves and feel better when they receive information consistent with their own expectations (Swann, 2012; Swann & Hill, 1982). Individuals are likely to seek out interpersonal relationships in which their self-views will be confirmed (Swann, 2012; Swann, Pelham, & Krull, 1989), and they are more satisfied in marriages in which these views are confirmed (Schafer, Wickrama, & Keith, 1996; Swann et al., 1994). In addition, as couples become increasingly interdependent, pursuing important personal and couple-level goals, they may come to look to their partners to better understand their own behavior and they must be able to accurately identify each other’s strengths and weaknesses in order to succeed in these mutual goals (Swann et al., 1994). In a survey of married couples, Swann and colleagues (1994) found that individuals whose spouses verified their own self-views reported greater intimacy than those with spouses who held incongruent views, regardless of the positivity of those self-views. Self-verification theory acknowledges that both self-enhancement and self-verification motives exist and can be in conflict with one another (Swann, 2012; Swann, Griffin, Predmore, & Gaines, 1987). However, in a meta-analysis of the self-verification and enhancement literature, Kwang and Swann (2010) concluded that in secure marital relationships, self-verifying feedback is generally preferred to self-enhancing feedback.

In contrast, Murray and colleagues (1996a, 1996b) claim that positive illusions are associated with greater relationship satisfaction than accuracy. In both married and dating couples, being the object of such positive illusions predicts greater relationship satisfaction (Claxton, O’Rourke, Smith, & DeLongis, 2012; Murray et al., 1996a). According to Murray and colleagues (1996a), a “reflected illusions” process is at work, whereby a sense of being accepted and valued despite one’s flaws leads to more satisfying relationships. Positive illusions also build up a store of goodwill that allows couples to deal more effectively with disappointments and conflicts as their relationship progresses (Murray et al., 1996b). However, there are limitations on the amount of idealization with which partners are most comfortable, and feelings of overidealization can lead to discomfort and dissatisfaction (Tomlinson, Aron, Carmichael, Reis, & Holmes, 2014).

Given the existence of data in support of both perspectives, how can the apparent discrepancy between them be resolved? Several lines of work have attempted to do so. For instance, some research suggests that relationship length or marital status is an important moderator of such effects (Campbell, Lackenbauer, & Muise, 2006; Swann et al., 1994), such that verification is more highly valued in established relationships, whereas enhancement is preferred in newer relationships. Neff and Karney (2005) provided evidence that whether verification or enhancement will lead to greater satisfaction depends on the specificity of the domain being assessed, such that highly satisfying relationships combine partner enhancement at a global level with accuracy in specific trait domains. Another class of explanations focuses on the trait domains themselves. Boyes and Fletcher (2007) and Seidman (2007) showed that enhancement is particularly important for relationally relevant traits, whereas verification is more beneficial for traits peripheral to the relationship.

Although each of these perspectives likely contributes in important ways to resolving the self-verification and positive illusion frameworks, we focus on this third possibility in the current research. Research has shown that individuals prefer that their romantic partners perceive them in an unrealistically positive manner on traits that are central to the relationship (Boyes & Fletcher, 2007; Swann, Bosson, & Pelham, 2002), and people are more likely to enhance their romantic partners on such traits (Boyes & Fletcher, 2007; Morry, Kito, & Ortiz, in press). Moreover, overly positive evaluations on these central traits (e.g., warmth) are associated with greater relationship satisfaction than such evaluations on more peripheral traits (e.g., extroversion; Boyes & Fletcher, 2007). Not only are such biases common, but both satisfied and dissatisfied partners are consciously aware of their partners’ biases (Boyes & Fletcher, 2007). Thus, enhancement motives are likely to influence judgments on relationally relevant criteria, whereas self-verification motives are more influential on relationally peripheral criteria (Boyes & Fletcher, 2007). Given this evidence that the impact of enhancement versus verification on global outcomes like relationship satisfaction varies as a function of trait domain, the present work tests whether similar effects are observed for responses to daily relational conflict.

Before discussing the link between relational conflict and verification versus enhancement, it should be noted that the verification and enhancement perspectives do agree on at least one point: Derogation (in which the partner’s evaluation is more negative than the individual’s self-evaluation) should be associated with poor relationship outcomes, and research has shown that even when enhancement is not beneficial, derogation is generally predictive of less satisfaction (Seidman, 2012). Thus, in the present study, we compare not only the consequences of being enhanced versus verified by one’s partner but also the consequences of each to those of being derogated by one’s partner.

Relational conflict and verification/enhancement processes

Conflict is a relatively rare event in most romantic relationships (occurring about twice a month on average during typical periods; Kennedy, Bolger, & Shrout, 2002; McGonagle, Kessler, & Schilling, 1992). As conflict-free days are the norm for most couples, conflicts tend to capture each partner’s attention and are laden with emotion, making them focal events for the study of relationship functioning. More specifically, research shows that negative relationship events like conflict tend to have a larger impact than positive events (Gottman, 1994; see Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001 for review), and conflict interactions are often used in lab-based studies of relationship functioning to infer relational health (e.g., Gottman, 1994; Levenson & Gottman, 1985; Overall, Fletcher, Simpson, & Sibley, 2009). Conflict can be detrimental to individual (Burman & Margolin, 1992; Umberson, Williams, Powers, Liu, & Needham, 2006) and relationship (Gottman & Levenson, 2000; Rusbult, Johnson, & Morrow, 1986) health when not handled effectively. Whether or not a conflict is destructive may partly depend upon its immediate emotional impact. Therefore, it is important to understand what factors may buffer or exacerbate the impact of conflict.

Research has shown that chronic relational orientations can moderate the effect of conflict. Research on adult attachment has shown that anxiously attached individuals tend to interpret their partners’ conflict behavior more negatively than securely attached individuals (Campbell, Simpson, Boldry, & Kashy, 2005; Simpson, Rholes, & Phillips, 1996), which can then affect conflict behavior. Similarly, those who do not feel valued by their partners respond more negatively to relationship threats (Murray, Bellavia, Rose, & Griffin, 2003), and these insecure individuals often express their insecurities to their partners, further threatening the relationship (Lemay & Clark, 2008; Murray et al., 2003). Relatedly, Downey, Freitas, Michaelis, and Khouri (1998) found, in a daily diary study, that the partners of highly rejection sensitive (RS) women were more likely than partners of low RS women to consider ending the relationship on days of conflict, but there was no association between RS and the partner’s commitment on no conflict days. This finding suggests that, on conflict days, high RS women behaved in ways that led their partners to feel less committed. Taken together, these findings demonstrate that chronic relational orientations can moderate responses to conflict.

Given these findings, might reactions to conflict also depend on whether individuals are derogated, verified, or enhanced by their partners? Some work by Murray and colleagues (1996b) began to address this question. They proposed a buffering hypothesis, whereby positive illusions can reduce the negative impact of conflicts after they occur, providing benefits to both partners. They asked both dating and married couples to complete self-report measures of their tendency to engage in overt conflicts and expressions of negativity toward their partner and their tendency to engage in destructive behaviors during conflicts. Their results indicated that being idealized by one’s partner predicted less frequent and less destructive conflicts.

Other researchers have posited that such positive illusions may not be beneficial in the face of conflict, as conflict situations may bring these misconceptions to the fore. In a survey of married couples, Weger (2005) found that feeling understood by one’s partner predicted less engagement in the destructive demand–withdrawal pattern during conflict, and self-verifying feedback is one way to feel understood (Swann, 2012). Similarly, Cohen, Schulz, Weiss, and Waldinger (2012) found that those who perceived their partners as understanding their emotions during a lab-based conflict discussion reported greater overall relationship satisfaction. Swann and colleagues (1994) emphasized how achieving mutual goals depends on accurately understanding the partner’s strengths and weaknesses. Acitelli, Douvan, and Veroff (1993) have argued that during conflicts, unexposed differences between partners and their interpretations of conflict behavior may reinforce separate rather than shared realities. This is especially problematic in the face of a conflict, in which partners are attempting to come to a shared agreement or resolution. Thus, this research suggests that when experiencing conflict, partners who are verified will respond more positively than those who are enhanced.

The benefits of verification in the face of conflict, however, may be limited to certain trait domains. According to Kwang and Swann (2010), self-verifying feedback is preferred when it does not put one at risk of being abandoned by one’s partner, but when risk is high, enhancing feedback is preferred. Relational conflict may heighten sensitivity to relational threat, and the relationship relevance of the feedback domain may be a key determinant of the extent to which feedback threatens the relationship. Relationship-central traits should be closely tied to the overall quality of the relationship, so self-verifying feedback on relationship-central traits (if such feedback is negative) should be seen as threatening the relationship, leading people to prefer enhancing feedback on these traits, particularly in times of conflict. Consistent with this reasoning, Fletcher and Boyes (2008) have posited that positive feedback, even if inaccurate, is desired and expected during times of personal doubt and uncertainty—conditions that are inherent in conflict situations. However, they argue that because both positivity and accuracy goals coexist in successful relationships (Kenny & Acitelli, 2001), partners must sometimes see one another accurately. Boyes and Fletcher (2007) posit that positively biased feedback is most desired for domains central to the relationship, as high-relevance relationship judgments serve to fulfill positivity goals, whereas low-relevance judgments can fulfill accuracy goals. Furthermore, those who idealize their partners on central traits may be more likely to give their partners the benefit of the doubt and treat them warmly during conflict, as positive illusions help individuals to reinterpret their partners’ negative behaviors in a more positive light (Murray et al., 1996b). Idealized partners may in turn have more positive experiences during conflicts, despite the fact that their partners’ perceptions are inaccurate, because they perceive that their partners truly have their best interests at heart.

In contrast, feedback that verifies negative self-views on relationship-peripheral traits should be less threatening to the relationship, allowing individuals to instead satisfy their self-verification motives. In other words, when feedback is not threatening, the individual should appreciate feeling understood by the partner, which should facilitate more adaptive conflict responses. Because achieving mutual goals is dependent upon accurate understanding of one’s partner (Swann et al., 1994) and inaccuracies are especially likely to come to the fore during conflicts (Acitelli et al., 1993), being enhanced on relationship-peripheral traits may have detrimental consequences in conflict situations, as these inaccurate perceptions would simply stand out as incorrect and as an indication that the partner lacks a true understanding of the individual and his/her abilities without the added benefits that come from being enhanced on relationship-central traits. For these reasons, we expect that the negative consequences of conflict on relationship evaluation will be mitigated by partner enhancement on traits central to the relationship and partner verification on traits peripheral to the relationship.

The only research to directly address the question of how discrepancies in partner views relate to conflict, as opposed to studies assessing the extent to which individuals felt understood by their partner, was the study by Murray and colleagues (1996b) described earlier, which provided some evidence for the benefits of positive illusions in conflict situations. However, that study used cross-sectional measures of conflict behaviors, rather than examining reactions to conflicts as they occurred. Cross-sectional data can be prone to retrospection bias, as events may be reinterpreted, half-forgotten, and combined into a general perception, possibly making their responses more reflective of global relationship satisfaction than of responses to specific conflicts. Such biases can be avoided through the use of daily diaries (Bolger, Davis, & Rafaeli, 2003) that allow researchers to examine events in their natural context (Reis, 1994). Murray and colleagues also did not distinguish between traits central versus peripheral to the relationship, which more recent research (e.g., Boyes & Fletcher, 2007) has pointed to as an important distinction.

Study overview and hypotheses

In the current study, we use a daily diary design to investigate daily conflict experiences in a sample of committed romantic couples, in which one member of the couple is experiencing an external stressor. These stressed couples are likely to have an unusually high rate of conflict, as stress is negatively associated with relationship quality (e.g., Harper, Schaalje, & Sandberg, 2000; Totenhagen, Butler, & Ridley, 2012) and partners’ abilities to have quality interactions with one another (Gordon & Chen, 2013; Neff & Karney, 2009), making them especially suitable for examining the occurrence of daily conflicts that are normally rather rare (e.g., Kennedy et al., 2002; McGonagle et al., 1992). As described below, we expect the nonstressed member of the couple to show a clearer pattern of results, as the stressed members of the couples are likely to be preoccupied with the external stressor rather than attending to relational processes.

Prior to the diary period, participants rated themselves and their committed romantic partners on a variety of traits, both central and peripheral to the relationship, from which we derived indicators of derogation, verification, and enhancement. Subsequently, they completed 5 weeks of daily diaries, in which they reported daily relational conflicts and affective relationship evaluation. The overarching goal is to examine how being chronically derogated, verified, and enhanced on both relationship-central and relationship-peripheral traits influences the association between daily relational conflict and relationship evaluation. Based on the above discussion, we propose the following four hypotheses:
Hypothesis 1: The presence of conflict will be associated with more negative relational evaluation in general.

Hypothesis 2: Individuals who are derogated by their partners will show more negative relational evaluation in response to conflict than individuals who are verified or enhanced by their partners. This hypothesis should hold for derogation on both central and peripheral traits.

Hypothesis 3: Individuals who are enhanced by their partners on central traits should report less negative responses to conflict than those who are verified on central traits.

Hypothesis 4: Individuals who are verified by their partners on peripheral traits should report less negative responses to conflict than those who are enhanced on peripheral traits.

Method

Design and participants

The data presented here were collected as part of a larger daily diary study designed to examine social support in romantic couples experiencing stress (see Gleason, Iida, Shrout, & Bolger, 2008, for additional details). One member of each couple was a graduating law student preparing for the state bar examination. Thus, the study took place during a highly stressful period for the examinee and a challenging time for the relationship (Bolger, Zuckerman, & Kessler, 2000). Because the examinees are immersed in a personally important stressor, they may be less focused on their relationship relative to their exam preparation, and their reports of relational evaluation (and even the presence or absence of conflict) may deviate systematically from their values during more mundane times. In contrast, the non-examinees may be particularly attuned to their relationships during this time, making both positive and negative relational events more salient to them. For these reasons, we expected the pattern of results to be clearer for non-examinees than for the examinees. For the sake of thoroughness, however, we conducted dyadic analyses to simultaneously model the pattern of results for the examinees and non-examinees, using interaction terms as described below to test for statistical differences in the patterns for the two members of the couple.

The data were collected over the summers of 2002 and 2003, as the bar examination is given at the end of July. Over 100 law schools in the U.S. were contacted, with 27 schools participating in 2002 and 30 schools in 2003. A letter or e-mail was sent to all graduating students at each school. Eligible couples had to be cohabiting for at least 6 months, and only one member of the couple could be planning to take the July bar examination. The researchers contacted 643 eligible couples, of whom 466 (72%) agreed to participate. A subset of 344 of these couples were assigned to complete daily diaries, with the remaining participants assigned to complete a different questionnaire schedule not relevant to the present analyses. Two hundred and eighty-six couples completed at least 1 week of diaries. We removed 11 homosexual couples from the sample, and another 25 examinees and 24 non-examinees who did not complete all measures required for the analyses. The final sample consisted of 250 examinees and 251 non-examinees representing 264 couples. The average age was 29.8 years (SD = 7.8) for non-examinees and 29.2 years (SD = 6.2) for examinees. The average length of romantic involvement was 6.2 years (SD = 5.2) and 64% of the couples were married. Eighty-three percent of non-examinees had at least a bachelor’s degree and 46.6% were female.

Each couple received US$150 for participation and was entered in a US$1000 raffle upon completing the study. Upon agreeing to participate, couples received an initial payment of US$10, two consent forms, two background questionnaires, and two return envelopes. They returned the completed questionnaires an average of 3 weeks before the diary period, which began 5 weeks before the exam and lasted until 1 week after the exam. Both members of each couple received their initial diary packet 1–2 weeks before the start of the diary period. This packet contained seven identical daily diary questionnaires, a return envelope, and instructions for completing the diaries. Packets of diaries were mailed to each participant each subsequent week. The diary form included questions regarding mood, relationship feelings, daily troubles, conflicts, and support transactions. Participants were instructed to complete their diary questionnaires separately and to refrain from consulting with each other. They were asked to complete the diaries on the designated days and indicate if they had completed them on the correct day. The analyses reported here focus on the period leading up to and including the exam, a total of 36 days. The participants used in the analyses reported here completed an average of 29.9 days (SD = 9.3 days) during this period. The median days completed was 34, with 76% completing at least 4 weeks (28 days) of diary questionnaires.

Measures

Perceptions of self and partner

The background questionnaire, administered prior to the diary period, assessed participants’ evaluations of their own and their partners’ traits. Participants were asked to rate both themselves and their partners on several personality traits by indicating how accurately they felt each trait described them/their partners on a 5-point scale from 0 (very inaccurate) to 4 (very accurate). Six interpersonal virtues thought to be important for relationship functioning comprised the relationship-central traits scale: accepting, kind, warm, cold (reverse coded), unsympathetic (reverse coded), and sympathetic (α_self-ratings = .78, α_{partner-ratings} = .74). This scale was designed to be similar to the interpersonal virtues scale used by Murray and colleagues (1996a). Participants also rated themselves and their partners on Pelham and Swann’s (1989) 10-item Self-Attributes Questionnaire (SAQ). This measure asks participants to rate themselves relative to their peers on several abilities and attributes, such as athletic ability and leadership ability. These ratings are based on percentile rankings, such that participants could indicate, for example, that they were in the top 10% or lower 20% relative to their peers. The units of this scale range from 5% to 95%, but these items were rescaled from 0 to 4 to make them comparable to the trait rating items. We computed a relationship-peripheral traits scale from a subset of four of these items that, although important, should be relatively peripheral to the relationship: athletic ability, leadership ability, common sense, and discipline (α_self-ratings = .64, α_{partner-ratings} = .64).²

Daily relationship moods

Participants reported their feelings about their relationship each day using a modified version of Berscheid, Snyder, and Omoto’s (1989) Emotional Tone Index created by Thompson and Bolger (1999). Each item asked participants to rate the extent to which they felt emotions in the relationship “right now” on a 5-point scale, ranging from not at all (0) to extremely (4). The positive relationship mood scale was the average of 6 items: content, excited, loved, satisfied, passionate, and emotionally close. The average positive mood score across all days was 2.40 (SD = 0.92). The negative relationship mood scale was the average of 4 items: fearful, sad, worried, and depressed. The average negative mood score across all days was 0.26 (SD = 0.48).

Conflict

In the diary, participants were asked to place a check mark next to each individual with whom they experienced “any disagreements, arguments, or tensions” during the past 24 h. Of interest in the current study was whether or not participants had experienced conflict with their romantic partner. Responses to this item were coded 1 if “partner” was checked and 0 if it was not. Both partners agreed that a conflict occurred on 7% of days. On an additional 15% of days, one partner reported a conflict and the other did not. In the analyses reported below, conflict days are taken as those days on which the focal participant perceived that conflict occurred. Because the daily relational mood of the focal participant is the dependent measure of interest, this individual’s perspective on whether or not conflict occurred is most relevant in predicting that mood.

Results

Analytic approach

The primary aim of the current study is to examine whether being the object of global enhancement versus verification on relationship-central and relationship-peripheral traits moderates the impact of conflict on relationship mood, as reported by the participant. To do so, however, we use an analytic approach that defines verification as the absence of derogation or enhancement, highlighting the consequences of relational conflict for relationship evaluation as a function of the degree of enhancement and derogation (relative to verification). We conducted separate multilevel regression analyses for each of two outcome variables (positive and negative relational mood) and each of two trait domains (relationship-central and relationship-peripheral traits), for a total of four analyses. We approached these analyses from a dyadic framework, estimating the pattern of effects for examinees and non-examinees simultaneously, and using interaction terms to test for differences between the two members of the couples. The structure of these analyses is described in detail below.

Assessing enhancement/derogation

Two data analytic approaches may be used to examine how the relative agreement of two partners' ratings relates to outcomes of interest: (1) the regressed change approach and (2) the difference score or discrepancy approach (see Griffin, Murray, & Gonzalez, 1999 for discussion). The regressed change approach examines the relationship between the positivity of the partner's view of the individual, adjusted for the individual’s self-view (i.e., Mary’s view of John adjusted for John’s self-view). The difference score approach examines the discrepancy between the two partners’ views of the same member of the couple, adjusting for the average view of that individual (i.e., Mary’s view of John and John’s self-view adjusted for the mathematical average of Mary’s view of John and John’s self-view). In a regressed change analysis, the effect of Mary’s view of John (the measure used to assess positive illusions) on relationship outcomes is a combination of the effect of the discrepancy and half the effect of the average rating of John (Shrout & Seidman, 2008). When a difference score approach is used, adjusting for the average rating of the individual whose discrepancy is of interest allows one to focus on the discrepancy, holding constant the extent to which the individual “possesses” the trait (Shrout & Seidman, 2008). Both analytical approaches account for the same variability in the outcome variable, but the difference score approach separates the contributions of the overall positivity of the views of the individual and the discrepancy between partners’ views of each other (Shrout & Seidman, 2008). In order to ensure equivalence between these two approaches, we adjusted for the average of the two partners’ views of the participant, which is an estimate of the participant's true level of the focal trait domain. We also allowed this average to interact with conflict to account for the possibility that the impact of conflict depends on this average level. Including these two terms ensures that the main effect of discrepancy and the discrepancy by conflict interaction are not biased by differences in the overall level of the focal trait domain. Because of our focus on the difference between derogation and enhancement, we used the difference score approach in the current analyses, but we also ran the analyses using the regressed approach recommended by Edwards (1994) and obtained similar results.

We first computed discrepancy scores for each trait to determine the extent to which the participant was enhanced or derogated by the partner (partner’s view of participant minus participant’s self-view). We then created indices of relationship-peripheral and relationship-central traits by averaging together the discrepancy scores for the corresponding traits. The discrepancy scores constituting the central traits index had a Cronbach’s α of .74, and the discrepancy scores constituting the peripheral traits index had an α of .66.

To allow us to dissociate the consequences of enhancement and verification, we then separated each trait discrepancy index variable into distinct derogation and enhancement variables. The derogation variable took on the value of the discrepancy itself when the discrepancy was less than or equal to zero, but equaled zero otherwise. The enhancement variable took on the value of the discrepancy itself when the discrepancy was greater than zero, and zero otherwise. Values close to zero on these variables would indicate an individual who is verified by his or her partner. This method has been recommended by Edwards (1994) and Griffin et al. (1999), and it is consistent with the use of spline models in regression analysis (Cudeck & Klebe, 2002; Marsh & Cormier, 2002).

Modeling changes in daily relational mood

We used the MIXED procedure of SAS (SAS Institute Inc., 2010) to estimate multilevel models (see Raudenbush & Bryk, 2002) that take into account the dependence of observations within each individual over time (see Bolger & Shrout, 2007; Kenny, Kashy, & Cook, 2006). Multilevel models contain two types of effects: fixed effects, which represent the average effect in the population, and random effects, which capture variability in the effects across individuals. In the equation below, fixed effects are represented as γs and random effects are represented as us. The model of interest can be represented as follows:
${R M}_{i j} = (γ_{0} + u_{0 j}) + {A D J}_{i j} + γ_{1} C_{i j} + γ_{2} D_{j} + γ_{3} E_{j} + γ_{4} C_{i j} D_{j} + γ_{5} C_{i j} E_{j} + e_{i j} .$
1

In this equation, RM _ij represents the observed relationship mood for person j on day i. The γ₀ term is the fixed intercept—the expected relationship mood on no conflict days for someone who is verified, adjusting for all of the other effects in the model. The u _0j term is the random intercept, or the extent to which person j deviates from this expected relationship mood. The ADJ _ij term is a placeholder for the effects of the set of adjustment variables that are described in detail below. C_ij is person j's report of conflict on day i. D_j and E_j represent the derogation and enhancement variables described above. They are entered both as main effects (γ₂ and γ₃, respectively) and in interactions with conflict (γ₄ and γ₅). The coefficients for the main effects quantify how relationship mood on no conflict days changes as derogation and enhancement increase. The interaction coefficients indicate how much the effect of conflict on relationship mood changes as derogation and enhancement increase. The residual, e_i , captures the discrepancy between the observed mood score and that predicted by the model.

In each of the analyses, we included a set of adjustment variables (represented as ADJ _ij in Equation (1)) to facilitate testing the hypotheses of interest. First, we included the previous day's report of relationship mood to focus the interpretation on changes in relationship mood rather than on global differences in relationship mood. Because this variable was measured each day, we person-centered it (i.e., we subtracted out each participant's personal mean from each observation), and we included both a fixed and random effect. We included three between-subject covariates: participant gender, the length of romantic involvement with the partner, and the average number of conflicts reported over the diary period. The average number of conflicts was included because it is likely that participants who experience conflict frequency perpetually evaluate their relationship more negatively. Finally, in order to ensure unbiased estimates with the difference score approach (Shrout & Seidman, 2008), we included the average rating of the participant (i.e., the average of the partner rating and the self-rating) on the focal trait domain. As noted above, this average represents the best indicator of the participant's “true” value on the focal trait domain. We also included the interaction of this average rating with daily conflict to account for the possibility that reactions to conflict vary systematically as a function of these average ratings. Each of these between-subject variables was centered at its grand mean before being entered into the analysis.³

Finally, to conduct a dyadic analysis, we used the multivariate approach described by Raudenbush and Bryk (2002; see also Gleason et al., 2008) to simultaneously estimate the pattern of results for examinees and non-examinees. This process involves stacking the examinee and non-examinee data and creating a new effect-coded variable to distinguish the two members of the couple. We coded this variable (represented as P_j in Equation (2) below) −0.5 for examinees and +0.5 for non-examinees. We added it to the model as a main effect and allowed it to interact with all other terms in the model, including the adjustment variables. Thus, the main effects and interactions that do not include this new variable represent the overall pattern of results averaging across the two members of the couples, and the terms that do include this new variable test the difference between examinees and non-examinees on that effect. Because of the distinct roles held by the two members of the couple, they were treated as distinguishable dyads in the analysis by allowing the two groups to have their own random effects and residual variances. Building on Equation (1), the equation for this dyadic model is as follows:
$\begin{aligned} {R M}_{i j} = (γ_{00} + γ_{01} P_{j} + u_{0 j}) + {A D J}_{i j} + γ_{10} C_{i j} + γ_{11} C_{i j} P_{j} + γ_{20} D_{j} + γ_{21} D_{j} P_{j} + γ_{30} E_{j} \\ + γ_{31} E_{j} P_{j} + γ_{40} C_{i j} D_{j} + γ_{41} C_{i j} D_{j} P_{j} + γ_{50} C_{i j} E_{j} + γ_{51} C_{i j} E_{j} P_{j} + e_{i j} . \end{aligned}$
2

Main analyses

Table 1 provides basic descriptive statistics for all of the variables used in the main analyses, and Table 2 shows the zero-order correlations of the between-subject variables. Figure 1 displays box plots of the trait rating discrepancy scores for participants to show the distribution of ratings in the sample. This figure shows that, while there is a slight enhancement bias on average, there is a wide range of derogation and enhancement in the sample. The results of our main analyses are presented in Tables 3 to 6. Each table shows the results (coefficients and standard errors) for examinees and non-examinees combined as well as the separate estimates of the examinees and non-examinees. The tables also note parameters for which examinees and non-examinees varied significantly. In each table, variables of interest are presented first, followed by adjustment variables. Likewise, the results are plotted in Figures 2 and 3 both overall and separately for examinees and non-examinees. The results are described below in the order of the four hypotheses listed above.

Figure 1.
Box plots of the trait discrepancy scores for examinee and non-examinee participants. Negative values indicate derogation by the partner, and positive values indicate enhancement by the partner.

Figure 2.
Negative relationship mood for all participants (left) as a function of trait-rating discrepancy scores on no conflict and conflict days for relationship-central and relationship-peripheral traits. Values on the x-axis represent number of standard deviations from agreement on each trait domain, with positive values representing enhancement, negative values representing derogation, and zero values representing verification. The inset graphs show the distinct patterns for examinee and non-examinee partners using the same axis scales as the overall graph.

Figure 3.
Positive relationship mood for all participants (left) as a function of trait-rating discrepancy scores on no conflict and conflict days for relationship-central and relationship-peripheral traits. Values on the x-axis represent number of standard deviations from agreement on each trait domain, with positive values representing enhancement, negative values representing derogation, and zero values representing verification. The inset graphs show the distinct patterns for examinee and non-examinee partners using the same axis scales as the overall graph.

Table 1.
Descriptive statistics for study variables.

Non-examinees (N = 251) Examinees (N = 250)

Variable Mean (SD) Proportion Mean (SD) Proportion

Positive relationship mood (0–4 scale) 2.40 (0.74) 2.39 (0.78)

Negative relationship mood (0–4 scale) 0.26 (0.34) 0.32 (0.42)

Daily conflict 15.6% 14.9%

Female 46.6% 52.6%

Relationship length (years) 6.27 (5.22) 6.22 (5.29)

Discrepancy on relationship central traits 0.15 (0.75) 0.13 (0.75)

– Derogated by partner (discrepancy < 0) 32.7% 35.2%

– Verified by partner (discrepancy = 0) 16.3% 11.6%

– Enhanced by partner (discrepancy > 0) 51.0% 53.2%

Discrepancy on relationship peripheral traits 0.06 (0.63) 0.17 (0.66)

– Derogated by partner (discrepancy < 0) 39.4% 33.2%

– Verified by partner (discrepancy = 0) 8.0% 7.6%

– Enhanced by partner (discrepancy > 0) 52.6% 59.2%

Table 2.
Between-subject correlation matrix of study variables.

Non-examinees 1 2 3 4 5 6 7

1. Positive relationship mood 1

2. Negative relationship mood −0.35* 1

3. Conflict −0.29* 0.24* 1

4. Female 0.06 0.01 −0.06 1

5. Relationship length −0.04 −0.15* −0.13* 0.12 1

6. Discrepancy (central) −0.12* 0.06 −0.04 −0.21* −0.06 1

7. Discrepancy (peripheral) −0.03 0.00 −0.03 −0.00 −0.05 0.27* 1

Examinees 1 2 3 4 5 6 7

1. Positive relationship mood 1

2. Negative relationship mood −0.34* 1

3. Conflict −0.30* 0.20* 1

4. Female −0.19* −0.10 0.16* 1

5. Relationship length −0.03 −0.08 −0.17* −0.14* 1

6. Discrepancy (central) 0.02 0.01 −0.13* −0.19* 0.10 1

7. Discrepancy (peripheral) −0.11 0.08 −0.12 0.02 0.10 0.33* 1

p < .05.

Table 3.
Estimates and standard errors for relationship-peripheral traits predicting daily negative relationship mood.

Variable Overall Examinees Non-examinees

Derogation −0.08 (0.05) −0.12 (0.08) −0.05 (0.06)

Enhancement 0.12 (0.04) 0.17 (0.07) 0.07 (0.06)

Daily conflict^a 0.17 (0.01) 0.24 (0.02)* 0.09 (0.02)***

Derogation × Conflict^a −0.05 (0.03)* 0.10 (0.04)* −0.21 (0.03)*

Enhancement × Conflict 0.11 (0.02)* 0.07 (0.03)^† 0.15 (0.03)*

Lagged relationship Mood 0.20 (0.01)* 0.19 (0.02)* 0.21 (0.02)*

Average rating −0.02 (0.03) 0.04 (0.05) −0.07 (0.04)^†

Average Rating × Conflict 0.01 (0.02) 0.03 (0.03) −0.01 (0.02)

Mean level of conflict 0.30 (0.10)** 0.37 (0.16)* 0.23 (0.13)^†

Gender −0.05 (0.03) −0.10 (0.05)* −0.00 (0.04)

Relationship length −0.008 (0.003)* −0.007 (0.005) −0.009 (0.004)*

Intercept 0.20 (0.03)* 0.20 (0.04)* 0.20 (0.03)***

Note. Derogation = discrepancy between partner view and self-view < 0; enhancement = discrepancy between partner view and self-view > 0.

^aDifference between examinees and non-examinees is significant at the .05 level.

^† p < .10; p < .05; p < .01; p < .001.

Table 4.
Estimates and standard errors for relationship-central traits predicting daily negative relationship mood.

Variable Overall Examinees Non-examinees

Derogation 0.01 (0.05) 0.04 (0.07) −0.01 (0.06)

Enhancement 0.03 (0.04) −0.01 (0.06) 0.08 (0.05)

Daily conflict 0.20 (0.01)* 0.21 (0.02)* 0.18 (0.02)*

Derogation × Conflict −0.11 (0.03)* −0.12 (0.03)* −0.11 (0.04)

Enhancement × Conflict^a −0.01 (0.02) 0.03 (0.03) −0.05 (0.03)^†

Lagged relationship mood 0.20 (0.01)* 0.19 (0.02)* 0.21 (0.02)*

Average rating −0.03 (0.04) −0.03 (0.06) −0.03 (0.05)

Average Rating × Conflict 0.06 (0.02) 0.07 (0.03)* 0.05 (0.03)^†

Mean level of conflict 0.30 (0.11)** 0.34 (0.17)* 0.26 (0.13)*

Gender^a −0.03 (0.03) −0.10 (0.05)* 0.04 (0.04)

Relationship length −0.008 (0.003)* −0.007 (0.005) −0.009 (0.004)*

Intercept 0.25 (0.03)* 0.29 (0.04)* 0.20 (0.03)***

Note. Derogation = discrepancy between partner view and self-view < 0; enhancement = discrepancy between partner view and self-view > 0.

^aDifference between examinees and non-examinees is significant at the .05 level.

^† p < .10; p < .05; p < .01; p < .001.

Table 5.
Estimates and standard errors for relationship-peripheral traits predicting daily positive relationship mood.

Variable Overall Examinees Non-examinees

Derogation −0.07 (0.10) −0.08 (0.14) −0.06 (0.14)

Enhancement −0.17 (0.09)* −0.23 (0.12)^† −0.12 (0.13)

Daily conflict −0.39 (0.02)* −0.43 (0.03)* −0.35 (0.03)***

Derogation × Conflict^a 0.09 (0.04)* −0.01 (0.06) 0.19 (0.05)***

Enhancement × Conflict^a −0.03 (0.04) 0.06 (0.05) −0.12 (0.05)*

Lagged relationship mood 0.28 (0.01)* 0.27 (0.02)* 0.29 (0.02)*

Average rating 0.27 (0.06)* 0.26 (0.09) 0.28 (0.09)

Average Rating × Conflict −0.01 (0.02) 0.00 (0.04) −0.02 (0.03)

Mean level of conflict −1.07 (0.20)* −1.16 (0.29)* −0.99 (0.29)***

Gender^a −0.03 (0.07) −0.21 (0.10)* 0.15 (0.09)

Relationship length −0.009 (0.006) −0.008 (0.009) −0.010 (0.008)

Intercept 2.51 (0.05)* 2.53 (0.07)* 2.49 (0.07)***

Note. Derogation = discrepancy between partner view and self-view < 0; enhancement = discrepancy between partner view and self-view > 0.

^aDifference between examinees and non-examinees is significant at the .05 level.

^† p < .10; p < .05; p < .01; p < .001.

Table 6.
Estimates and standard errors for relationship-central traits predicting daily positive relationship mood.

Variable Overall Examinees Non-examinees

Derogation −0.19 (0.09)* −0.20 (0.13) −0.18 (0.13)

Enhancement −0.07 (0.07) 0.01 (0.11) −0.14 (0.10)

Daily conflict −0.39 (0.02)* −0.42 (0.03)* −0.36 (0.03)*

Derogation × Conflict^a 0.16 (0.04)* 0.05 (0.05) 0.27 (0.05)*

Enhancement × Conflict 0.03 (0.03) 0.07 (0.04) −0.01 (0.04)

Lagged relationship mood 0.28 (0.01)* 0.27 (0.02)* 0.29 (0.02)*

Average rating 0.35 (0.07)* 0.35 (0.10)* 0.35 (0.10)*

Average Rating × Conflict^a −0.10 (0.03)* −0.03 (0.04) −0.17 (0.04)*

Mean level of conflict −0.96 (0.20)* −0.95 (0.29) −0.97 (0.28)*

Gender^a −0.20 (0.07) −0.35 (0.09)* −0.04 (0.09)

Relationship length −0.011 (0.006)^† −0.010 (0.009) −0.011 (0.008)

Intercept 2.45 (0.05)* 2.42 (0.07)* 2.48 (0.07)***

Note. Derogation = discrepancy between partner view and self-view < 0; enhancement = discrepancy between partner view and self-view > 0.

^aDifference between examinees and non-examinees is significant at the .05 level.

^† p < .10; p < .05; p < .01; p < .001.

First, in accordance with Hypothesis 1, the main effect of conflict was significant for both trait domains and for both positive and negative relationship mood (see Tables 3 to 6; Figures 2 and 3) (ts > 11.92, ps < .001). Because the discrepancy variables were coded such that values of zero corresponded to individuals who are verified by their partners, this main effect can be interpreted as the effect of conflict for verified individuals. Negative relationship mood increased by about 0.18 and positive relationship mood decreased by about 0.39 on conflict days among individuals verified by their partners. In one of the four analyses (negative relationship mood, peripheral traits), examinees showed a significantly larger effect of conflict than non-examinees, t(489) = 5.24, p < .001. However, the simple effect of conflict remains highly significant for both partners across all analyses (ts > 4.72, ps < .001). The interaction terms reported below test whether the conflict effect varies as a function of the degree of derogation or enhancement.

Hypothesis 2 suggests that derogation will lead to more negative conflict responses regardless of domain. Before reporting these results, we report the main effects of derogation, which correspond to the associations between derogation and relationship mood on days of no conflict. For negative relationship mood, the main effects of derogation were nonsignificant (ts < 1.64, ps > 0.102) for both relationship-central and relationship-peripheral traits. For positive relationship mood, the main effect of derogation was nonsignificant for relationship-peripheral traits, t(489) = 0.72, p = .470, but it was significant for relationship-central traits, t(489) = 2.04, p = .042. Somewhat counterintuitively, this effect indicates that individuals who are derogated on relationship-central traits report somewhat more positive relationship mood on no conflict days than those who are verified. None of the main effects of derogation varied across examinees and non-examinees (ts < 0.74, ps > .460).

For negative relationship mood, the interactions between daily conflict and derogation on both peripheral, t(489) = 2.03, p = .043, and central, t(489) = 4.49, p < .001, traits were significant (see Tables 3 and 4 and Figure 2). In both cases, these interactions indicated that association between conflict and negative relationship mood was stronger for individuals with higher derogation scores. The dyadic analysis revealed that this interaction between conflict and derogation on peripheral traits was significantly stronger for non-examinees than for examinees, t(489) = 5.84, p < .001, as seen in Figure 2. Similarly, for positive relationship mood there were significant interactions between derogation and conflict for both relationship-peripheral, t(489) = 2.36, p = .019, and relationship-central traits, t(489) = 4.40, p < .001. These interactions (seen in Tables 5 and 6 and Figure 3) indicated that the link between daily conflict and positive relationship mood was more negative for those high on derogation relative to individuals verified by their partners. This time, both interactions were significantly stronger for non-examinees than for examinees (ts > 2.61, ps < .009), as seen in the inset graphs of Figure 3. Thus, Hypothesis 2 was supported by the analyses, with non-examinees generally showing a clearer pattern of results than examinees.

The results for Hypothesis 3, which suggested that enhancement would yield less negative responses to conflict than verification for relationship-central traits, were more mixed. We expected the enhancement by conflict interactions to be significant for relationship-central traits for both negative and positive relationship mood. As with derogation, we start by noting that the main effects of enhancement on relationship-central traits were nonsignificant for both positive and negative relationship mood (ts < 0.95, ps > .344), and they did not vary across examinees and non-examinees (ts < 1.12, ps > .264). In addition, the overall conflict by enhancement interactions were nonsignificant for both negative, t(489) = 0.66, p = .507, and positive, t(489) = 0.92, p = .356, relationship mood. However, this interaction varied significantly between examinees and non-examinees for negative relationship mood, t(489) = 1.98, p = .048. The simple conflict by enhancement interaction was marginal for non-examinees, t(245) = 1.96, p = .052, such that conflict was somewhat less costly for non-examinees whose partners enhanced them on central traits (see Figure 3). This interaction was nonsignificant, t(244) = 0.90, p = 0.372, for examinees. Thus, Hypothesis 3 was partially supported for non-examinees, but it was not supported for examinees for whom enhancement was associated with the same conflict response as verification.

Hypothesis 4 predicted significant conflict by enhancement interactions for peripheral traits, but in the opposite direction to those expected for central traits. Once again, we first report the main effects of enhancement on relationship-peripheral traits. These main effects were significant for both negative, t(489) = 2.75, p = .006, and positive, t(489) = 1.99, p = 0.047, relationship mood, indicating that on no conflict days individuals who were enhanced by their partners on peripheral traits reported more negative and less positive relationship mood than individuals who were verified by their partners (see Figures 2 and 3). The overall conflict by enhancement interaction for negative mood was significant, t(489) = 4.35, p < .001, such that individuals higher on enhancement showed a more negative conflict response than those verified on peripheral traits (see Figure 2). This interaction did not vary significantly across members of the couples, t(489) = 1.66, p = .098. For positive relationship mood, the overall conflict by enhancement interaction was not significant, t(489) = 0.89, p = .371. However, examinees and non-examinees significantly differed in this interaction effect, t(489) = 2.62, p = .009. As seen in Figure 3, examinees showed a nonsignificant improvement in conflict response to the extent that they were higher in enhancement, t(244) = 1.27, p = .204. Non-examinees, on the other hand, showed a significantly more negative conflict response to the extent that they were enhanced on peripheral traits, t(245) = 2.38, p = .018. Hypothesis 4 was primarily supported by the analyses, indicating that individuals enhanced by their partners on relationship-peripheral traits experienced more negative conflict responses than those verified by their partners. The exception was for examinees in the analysis of positive relationship mood, in which the conflict response was statistically equivalent for enhanced and verified individuals.

Discussion

The goal of the present study was to examine the moderating role of self-verification and enhancement processes in both relationship-central and relationship-peripheral domains on emotional responses to daily conflict. In line with Hypothesis 1, the main effect of conflict on relationship mood was consistently negative across all analyses, suggesting unsurprisingly that individuals' relationship mood is lower on days of conflict than on no conflict days. However, as expected, the magnitude of this conflict effect varied as a function of whether the individual was derogated, verified, or enhanced by his/her partner on the set of relationship-central and -peripheral traits that we investigated. Hypothesis 2 stated that being derogated on either relationship-peripheral or relationship-central traits should augment the negative impact of conflict. Across all four analyses, this hypothesis was supported, consistent with both the self-verification and enhancement perspectives and previous research (Seidman, 2012).

Hypotheses 3 and 4 distinguished the consequences of enhancement for relationship-central versus relationship-peripheral traits on responses to conflict. According to Hypothesis 3, we expected individuals enhanced on relationship-central traits to show less negative conflict responses than verified individuals. This hypothesis was not supported for examinees, who showed the same conflict response whether they were verified or enhanced on relationship-central traits. There was partial support for this hypothesis for non-examinees who showed a somewhat smaller conflict response on negative relationship mood to the extent that they were enhanced rather than verified by their partners. Hypothesis 4 stated that enhancement on relationship-peripheral traits would lead to more negative conflict responses relative to verification. This hypothesis was largely supported, with the expected pattern emerging for both partners when the outcome was negative relationship mood and for non-examinees when the outcome was positive relationship mood. Taken together, these results suggest that verification on relationship-peripheral traits leads to less negative emotional responses to conflict than enhancement. The support for the hypothesis that enhancement on relationship-central traits would lead to less negative conflict responses than verification was more equivocal, and additional research is necessary to evaluate this hypothesis.

These results have several theoretical and practical implications. First, they contribute to the ongoing discussion of when verification may be preferable to enhancement and vice versa. This work bolsters support for the importance of distinguishing relationship-central and relationship-peripheral traits when examining verification and enhancement (Boyes & Fletcher, 2007; Fletcher & Boyes, 2008; Swann et al., 2002). The benefits of verification were most clearly visible for relationship-peripheral traits, while more modest benefits were observed for enhancement on relationship-central traits. The differential effects of enhancement and verification as a function of trait domain also highlight the complexity of cognitive representations of romantic partners. The most stable relationships do not involve blindness to faults but rather integrating positive and negative traits of the partner into a coherent whole (Murray & Holmes, 1999). Thus, it is not surprising that overly positive evaluation on all traits is not the most beneficial pattern. Most importantly, these results show how chronic verifying or enhancing beliefs relate to the reactions to immediate relational events, such as relational conflict, further demonstrating the import role of these beliefs in determining relational health.

Second, this study contributes to the understanding of how global perceptions of self and other can alter the course of relational conflict. It is clear from the results that being derogated by one’s partner on both relationship-central and relationship-peripheral traits is disadvantageous during times of relational conflict. Although the present study did not assess the cognitive and behavioral correlates of derogation, derogated individuals likely feel neither understood nor valued by their partners, which might contribute to more negative conflict responses. Likewise, to the extent that the derogating partners truly do not understand or value their partners, their behavior in the conflict situation may incite a stronger response from the derogated individual. These results suggest that couples may benefit the most during conflict situations from having a partner who understands them. With only one exception, verified partners showed either less negative or equivalent responses to conflict as enhanced individuals regardless of trait domain. This finding suggests that when it comes to the immediate responses to conflict, couples might benefit the most by forming and maintaining accurate partner views.

There are several possible reasons why enhancement on relationship-central traits did not relate more clearly to a less negative conflict response. It is likely that most of the conflicts reported during this 5-week diary period were minor, as major disagreements are relatively rare. Many of the conflicts analyzed in the current study were reported by only one member of the couple, suggesting that these events were not momentous enough to be construed as conflicts by both partners, further suggesting that these were not major conflicts. Perhaps only when a conflict is serious and potentially threatening to the relationship does enhancement on relationship-central traits buffer its potential negative impact. We were able to partially test this possibility by rerunning the analyses using only observations in which the two partners agreed on whether or not a conflict occurred on a given day (approximately 50% of each person's conflict reports). Although this approach involved a high amount of data loss, the results did provide stronger evidence that enhancement on central traits buffered the impact of conflict, particularly for the non-examinees. This interpretation may be consistent with Murray et al. (1996b) who found that enhancement predicted fewer and less destructive conflicts. However, because they relied on retrospective reports of conflict, which are likely to be biased toward major conflicts that stand out more in memory, the degree of correspondence with the present results is unclear. The current findings do lend support to Murray and colleagues’ notion that partner views can buffer the negative impact of relational conflict.

In addition to conflict severity, which was not measured in the current study, the buffering effects of enhancement may also depend upon other elements of the conflict situation, such as whether or not the conflict was discussed or the self-relevance of the conflict. It is also possible that objects of enhancement with low self-esteem or attachment anxiety may interpret their partners’ expressions of positivity during conflict as condescending or insincere, creating a negative effect of enhancement for these participants, even if the effect is positive for others (e.g., Lemay & Clark, 2008; Murray, Holmes, MacDonald, & Ellsworth, 1998). Another possibility is that relatively negative assessments are more likely than relatively positive assessments to surface during a conflict, leading to minimal enhancement effects. It is also important to note that the current study only examined relationship feelings on the day the conflict occurred and did not examine any possible long-term effects of enhancement. Conflict behaviors that are negative in the short term can prove beneficial in the long term (Gottman & Krokoff, 1989), suggesting that the long-term consequences of enhancement may differ from its immediate consequences. In fact, longitudinal research has shown that enhancement can lead to positive future relationship outcomes (Miller, Niehuis, & Huston, 2006; Murray et al., 1996b). It is important for future research to examine the longer term effects of the conflicts experienced by those who are enhanced or verified.

One important limitation to the current study that makes it difficult to rule out these explanations is the dichotomous conflict measure, which simply asked participants whether or not a conflict occurred each day. It was impossible to examine the severity or cause of the conflict or who initiated it. There was also no way of knowing what specific behaviors occurred during the conflict discussion, or if the conflict was discussed at all. Such clarification about the nature of the conflicts would be especially useful on the 15% of days that only one member of the couple indicated that a conflict occurred. In addition to the concerns discussed previously, these aspects of the conflict itself could play a role in how self-verification and enhancement processes operate during conflicts, particularly if the subject of the conflict is highly self-relevant to one or both of the partners. Although we were able to verify with the present data that being enhanced or derogated on the focal traits did not predict the overall frequency of conflicts reported, future research should employ laboratory discussions of conflict as well as more detailed diary records of the cause and severity of conflict to better understand how enhancement or verification processes affect specific conflict behaviors.

There are several ways that the nature of our sample limits the generalizability of our findings. The current sample consisted of stressed couples; thus, it is unclear if our findings could be extended to couples who are not under stress. In addition, this sample was highly educated, being comprised of law students and their partners, most of whom had at least a bachelor’s degree. Our sample may also have been somewhat biased toward better relationship health, as suggested by the relatively low mean and variability of our measure of negative relationship mood. Although Table 1 shows that fewer participants were derogated than enhanced, Figure 1 shows that the distribution of derogation and enhancement for both central and peripheral traits was comparable. Still, given the selective nature of the sample, it is unlikely that the present sample represents the full range of relations in the population. Future research should investigate whether similar results are obtained for more diverse samples of couples, including those who are less educated and at greater risk for relationship dissolution.

In the current research, we drew a distinction between two different types of traits, those that were central and those that were peripheral to the functioning of an intimate relationship (Boyes & Fletcher, 2007). Another distinction that has been drawn in the positive illusions literature is between global and specific traits (Neff & Karney, 2002, 2005). Neff and Karney proposed that enhancement is desirable at a global level, but that accuracy is preferable for specific traits. One alternative explanation for our findings is that the relationship-peripheral traits we used (e.g., athletic ability, leadership ability, and discipline) were more specific than the relationship-central traits (e.g., warmth and acceptance). However, with the exception of athletic ability, the peripheral traits were rather general. For example, discipline could refer to work ethic, personal fitness/hygiene, fulfilling social obligations, and so on. Thus, we do not believe that this explanation can fully account for the reported pattern of results, although we do acknowledge that relationship centrality and specificity are not completely independent (Boyes & Fletcher, 2007).

The current findings, in which verification predicted more positive affect than enhancement, may seem to contradict research showing that affect is a domain in which enhancement motives usually trump verification motives (see Kwang & Swann, 2010, for a review). However, most of the studies showing these effects involve participants’ immediate affective reactions to experimentally manipulated feedback from a stranger in the laboratory (e.g., Jussim, Yen, & Aiello, 1995; Swann et al., 1987). In addition, studies that have found greater positive affect in response to enhancement over verification have tended to find such effects for short-term but not long-term relationships (Burke & Harrod, 2005; Campbell et al., 2006). In addition, the current study’s data are unique because (1) it examines affective changes on the day that a conflict has occurred and (2) the dependent measure is relationship-related affect, rather than general affect and thus is not equivalent to individual mood.

In conclusion, poorly handled conflict can be detrimental to relational well-being, and how constructive conflicts are may depend, in part, on how upsetting they are soon after their occurrence. The current findings illustrate one cognitive mechanism, self-verification, which may in some cases affect the immediate negative impact of conflict. These findings add to past research that has identified several conflict-modifying relationship processes, including rejection sensitivity (Downey et al., 1998), perceived regard (Murray et al., 2003), and attachment style (Campbell et al., 2005; Simpson et al., 1996). The current findings also demonstrate under what circumstances verification processes are likely to have the greatest impact. Future research should examine the possible moderating role of verification on additional relational processes, such as social support. Taken as a whole, this work demonstrates the importance of global relational beliefs on the course of relationship events like conflict.

	Non-examinees (N = 251)	Examinees (N = 250)
Positive relationship mood (0–4 scale)	2.40 (0.74)		2.39 (0.78)
Negative relationship mood (0–4 scale)	0.26 (0.34)		0.32 (0.42)
Daily conflict		15.6%		14.9%
Female		46.6%		52.6%
Relationship length (years)	6.27 (5.22)		6.22 (5.29)
Discrepancy on relationship central traits	0.15 (0.75)		0.13 (0.75)
– Derogated by partner (discrepancy < 0)		32.7%		35.2%
– Verified by partner (discrepancy = 0)		16.3%		11.6%
– Enhanced by partner (discrepancy > 0)		51.0%		53.2%
Discrepancy on relationship peripheral traits	0.06 (0.63)		0.17 (0.66)
– Derogated by partner (discrepancy < 0)		39.4%		33.2%
– Verified by partner (discrepancy = 0)		8.0%		7.6%
– Enhanced by partner (discrepancy > 0)		52.6%		59.2%

Non-examinees	1	2	3	4	5	6	7
1. Positive relationship mood	1
2. Negative relationship mood	−0.35*	1
3. Conflict	−0.29*	0.24*	1
4. Female	0.06	0.01	−0.06	1
5. Relationship length	−0.04	−0.15*	−0.13*	0.12	1
6. Discrepancy (central)	−0.12*	0.06	−0.04	−0.21*	−0.06	1
7. Discrepancy (peripheral)	−0.03	0.00	−0.03	−0.00	−0.05	0.27*	1

Examinees	1	2	3	4	5	6	7
1. Positive relationship mood	1
2. Negative relationship mood	−0.34*	1
3. Conflict	−0.30*	0.20*	1
4. Female	−0.19*	−0.10	0.16*	1
5. Relationship length	−0.03	−0.08	−0.17*	−0.14*	1
6. Discrepancy (central)	0.02	0.01	−0.13*	−0.19*	0.10	1
7. Discrepancy (peripheral)	−0.11	0.08	−0.12	0.02	0.10	0.33*	1

Variable	Overall	Examinees	Non-examinees
Derogation	−0.08 (0.05)	−0.12 (0.08)	−0.05 (0.06)
Enhancement	0.12 (0.04)**	0.17 (0.07)**	0.07 (0.06)
Daily conflict^a	0.17 (0.01)***	0.24 (0.02)***	0.09 (0.02)***
Derogation × Conflict^a	−0.05 (0.03)*	0.10 (0.04)*	−0.21 (0.03)***
Enhancement × Conflict	0.11 (0.02)***	0.07 (0.03)^†	0.15 (0.03)***
Lagged relationship Mood	0.20 (0.01)***	0.19 (0.02)***	0.21 (0.02)***
Average rating	−0.02 (0.03)	0.04 (0.05)	−0.07 (0.04)^†
Average Rating × Conflict	0.01 (0.02)	0.03 (0.03)	−0.01 (0.02)
Mean level of conflict	0.30 (0.10)**	0.37 (0.16)*	0.23 (0.13)^†
Gender	−0.05 (0.03)	−0.10 (0.05)*	−0.00 (0.04)
Relationship length	−0.008 (0.003)*	−0.007 (0.005)	−0.009 (0.004)*
Intercept	0.20 (0.03)***	0.20 (0.04)***	0.20 (0.03)***

Variable	Overall	Examinees	Non-examinees
Derogation	0.01 (0.05)	0.04 (0.07)	−0.01 (0.06)
Enhancement	0.03 (0.04)	−0.01 (0.06)	0.08 (0.05)
Daily conflict	0.20 (0.01)***	0.21 (0.02)***	0.18 (0.02)***
Derogation × Conflict	−0.11 (0.03)***	−0.12 (0.03)***	−0.11 (0.04)**
Enhancement × Conflict^a	−0.01 (0.02)	0.03 (0.03)	−0.05 (0.03)^†
Lagged relationship mood	0.20 (0.01)***	0.19 (0.02)***	0.21 (0.02)***
Average rating	−0.03 (0.04)	−0.03 (0.06)	−0.03 (0.05)
Average Rating × Conflict	0.06 (0.02)**	0.07 (0.03)*	0.05 (0.03)^†
Mean level of conflict	0.30 (0.11)**	0.34 (0.17)*	0.26 (0.13)*
Gender^a	−0.03 (0.03)	−0.10 (0.05)*	0.04 (0.04)
Relationship length	−0.008 (0.003)*	−0.007 (0.005)	−0.009 (0.004)*
Intercept	0.25 (0.03)***	0.29 (0.04)***	0.20 (0.03)***

Variable	Overall	Examinees	Non-examinees
Derogation	−0.07 (0.10)	−0.08 (0.14)	−0.06 (0.14)
Enhancement	−0.17 (0.09)*	−0.23 (0.12)^†	−0.12 (0.13)
Daily conflict	−0.39 (0.02)***	−0.43 (0.03)***	−0.35 (0.03)***
Derogation × Conflict^a	0.09 (0.04)*	−0.01 (0.06)	0.19 (0.05)***
Enhancement × Conflict^a	−0.03 (0.04)	0.06 (0.05)	−0.12 (0.05)*
Lagged relationship mood	0.28 (0.01)***	0.27 (0.02)***	0.29 (0.02)***
Average rating	0.27 (0.06)***	0.26 (0.09)**	0.28 (0.09)**
Average Rating × Conflict	−0.01 (0.02)	0.00 (0.04)	−0.02 (0.03)
Mean level of conflict	−1.07 (0.20)***	−1.16 (0.29)***	−0.99 (0.29)***
Gender^a	−0.03 (0.07)	−0.21 (0.10)*	0.15 (0.09)
Relationship length	−0.009 (0.006)	−0.008 (0.009)	−0.010 (0.008)
Intercept	2.51 (0.05)***	2.53 (0.07)***	2.49 (0.07)***

Variable	Overall	Examinees	Non-examinees
Derogation	−0.19 (0.09)*	−0.20 (0.13)	−0.18 (0.13)
Enhancement	−0.07 (0.07)	0.01 (0.11)	−0.14 (0.10)
Daily conflict	−0.39 (0.02)***	−0.42 (0.03)***	−0.36 (0.03)***
Derogation × Conflict^a	0.16 (0.04)***	0.05 (0.05)	0.27 (0.05)***
Enhancement × Conflict	0.03 (0.03)	0.07 (0.04)	−0.01 (0.04)
Lagged relationship mood	0.28 (0.01)***	0.27 (0.02)***	0.29 (0.02)***
Average rating	0.35 (0.07)***	0.35 (0.10)***	0.35 (0.10)***
Average Rating × Conflict^a	−0.10 (0.03)***	−0.03 (0.04)	−0.17 (0.04)***
Mean level of conflict	−0.96 (0.20)***	−0.95 (0.29)**	−0.97 (0.28)***
Gender^a	−0.20 (0.07)**	−0.35 (0.09)***	−0.04 (0.09)
Relationship length	−0.011 (0.006)^†	−0.010 (0.009)	−0.011 (0.008)
Intercept	2.45 (0.05)***	2.42 (0.07)***	2.48 (0.07)***

Footnotes

Funding

This research was supported by grant MH60366 from the National Institute of Mental Health to Niall Bolger at New York University.

Notes

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	Non-examinees (N = 251)		Examinees (N = 250)
Variable	Mean (SD)	Proportion	Mean (SD)	Proportion
Positive relationship mood (0–4 scale)	2.40 (0.74)		2.39 (0.78)
Negative relationship mood (0–4 scale)	0.26 (0.34)		0.32 (0.42)
Daily conflict		15.6%		14.9%
Female		46.6%		52.6%
Relationship length (years)	6.27 (5.22)		6.22 (5.29)
Discrepancy on relationship central traits	0.15 (0.75)		0.13 (0.75)
– Derogated by partner (discrepancy < 0)		32.7%		35.2%
– Verified by partner (discrepancy = 0)		16.3%		11.6%
– Enhanced by partner (discrepancy > 0)		51.0%		53.2%
Discrepancy on relationship peripheral traits	0.06 (0.63)		0.17 (0.66)
– Derogated by partner (discrepancy < 0)		39.4%		33.2%
– Verified by partner (discrepancy = 0)		8.0%		7.6%
– Enhanced by partner (discrepancy > 0)		52.6%		59.2%