Running head: RELATIONAL MAINTENANCE AND SELF EXPANSION 1. Relational Maintenance Communication and Self Expansion Theory: Low-Inference Measure

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1 Running head: RELATIONAL MAINTENANCE AND SELF EXPANSION 1 Relational Maintenance Communication and Self Expansion Theory: Low-Inference Measure Development and Dyadic Test of Inclusion of the Other in the Self as a Predictor Andrew M. Ledbetter Texas Christian University This manuscript has been accepted for presentation as the top paper in the Interpersonal and Small Group Communication Interest Group of the Central States Communication Association, Cleveland, OH, March This manuscript has not been published in a peer-reviewed journal. The author makes no warranty of this manuscript s merchantability or fitness for a particular purpose. The reader of this manuscript assumes all liability for application, citation, or other use of the information herein. This manuscript may not be reproduced or transmitted in any form, in whole or in part, without the express written permission of the author (excepting fair use as determined by applicable law). Author note: Andrew M. Ledbetter (Ph.D., University of Kansas, 2007) is an assistant professor in the Department of Communication Studies at Texas Christian University and a member of CSCA. The second study reported in this manuscript was supported by an internal grant from Texas Christian University. Please direct all correspondence regarding this manuscript to the author at: Department of Communication Studies, TCU Box , Fort Worth, TX 76129, a.ledbetter@tcu.edu.

2 RELATIONAL MAINTENANCE AND SELF EXPANSION 2 Abstract This manuscript reports a series of two studies that develop and validate a low-inference measure of relational maintenance behavior. The first study evaluated an initial item pool, identified 11 dimensions of maintenance behavior, and established concurrent/divergent validity with theoretically related constructs. The second study further tested the instrument in a sample of 123 romantic dyads, demonstrating that inclusion of the other in the self (Aron, Mashek, & Aron, 2004) predicts frequency of maintenance behavior in a communally-oriented fashion. These results commend self expansion theory as a promising direction for future maintenance research and offer a maintenance measure for such future theoretical development and practical application. Keywords: Relational maintenance, romantic relationships, self expansion theory, actor-partner interdependence model, dyadic data analysis

3 RELATIONAL MAINTENANCE AND SELF EXPANSION 3 Relational Maintenance Communication and Self Expansion Theory: Low-Inference Measure Development and Dyadic Test of Inclusion of the Other in the Self as a Predictor Dominant theoretical models divide the life cycle of close relationships into three phases: (a) relational initiation (i.e., how relationships begin), (b) relational maintenance (i.e., how relationships continue), and (c) relational termination (i.e., how relationships end) (Duck, 1988). Although scholars initially devoted greater attention to initiation and termination (Dindia, 2003), Dindia and Baxter (1987) noted that understanding maintenance is arguably more important, given that across the history of a long-term relationship most of the time is spent in its maintenance (p. 143). Accordingly, communication scholars and those in affiliated fields now have devoted nearly three decades to understanding such relational maintenance behavior. Although multiple typologies and measures of maintenance behavior exist (e.g., Oswald et al., 2004; Stafford & Canary, 1991), these have conceptualized maintenance behavior as abstract categories encompassing several specific acts. Without diminishing the prodigious contribution of such research, what we yet lack is a measure of specific, low-inference communication behaviors that maintain relationships. Apart from such an instrument, the ability to make specific claims about specific communication acts may remain limited (Murray, 1983). Recently, Ledbetter, Stassen, Muhammad, and Kotey (2010) advanced a qualitatively-derived typology of such low-inference maintenance behaviors; they also argued that a communal approach to maintenance, grounded in self expansion theory (Aron, Mashek, & Aron, 2004), may yield theoretical and practical insight complementary to the dominant equity theory approach (Stafford & Canary, 2006). In the context of romantic relationships, the two studies reported here deductively evaluated Ledbetter et al. s (2010) typology and tested the explanatory ability of self expansion theory vis-à-vis frequency of maintenance behavior.

4 RELATIONAL MAINTENANCE AND SELF EXPANSION 4 Theoretical Background Ayres (1983) published one of the first empirical studies measuring relational maintenance behavior, noting that, at the time, only the briefest of excursions into interpersonal communication literature is required to discover... that little is known about the process of communication in stable relationships (p. 62). Other scholars soon noted this paucity of research, offering additional typologies (Bell, Daly, & Gonzalez, 1987; Baxter & Dindia, 1990) and empirical studies (Shea & Pearson, 1986). These early efforts conceptualized relational maintenance in diverse ways, including patterns of exchange (Ayres, 1983), affinity enhancement (Bell et al., 1987), stability reinforcement (Shea & Pearson, 1986), and sustainment of dynamic equilibrium (Baxter & Dindia, 1990). Stafford and Canary (1991) brought a degree of theoretical coherence to the field by conceptualizing their approach to relational maintenance under equity theory, predicting that people who perceive their relationships as equitable will engage in efforts to maintain those relationships as they are (Stafford & Canary, 2006, p. 229). Stafford and Canary s relational maintenance strategy measure (RMSM) assessed five dimensions of maintenance behavior: (a) positivity, (b) openness, (c) assurances, (d) shared social networks, and (e) shared tasks. The RMSM has passed through two revisions (Stafford, Dainton, & Haas, 2000; Stafford, 2011), as well as more minor refinements to assess maintenance germane to specific relationships (e.g., cross-sex friendships; Messman, Canary, & Hause, 2000). More recently, Oswald and her colleagues (2004) advanced a similar four-dimensional measure of friendship maintenance. Table 1 summarizes the (a) definitions, (b) dimensionalities, and (c) scale metrics employed by previous typologies and measures of relational maintenance. Despite the diverse methodologies and assumptions across these studies, three threads unite them. First, most studies

5 RELATIONAL MAINTENANCE AND SELF EXPANSION 5 have defined relational maintenance in regard to some relationship characteristic, such as stability (Dindia & Baxter, 1987) or equity (Canary & Stafford, 1992); moreover, these definitions often have employed social exchange theory as the theoretical link between maintenance and outcomes (Ayres, 1983; Bell et al., 1987; Stafford & Canary, 1991). Second, most measures and typologies have conceptualized maintenance behaviors as individually engaged (e.g., using I as the subject of survey items; Oswald et al., 2004; Stafford & Canary, 1991). Third, all of the foregoing studies have identified maintenance dimensions that are, as Bell and his colleagues (1987) describe, abstract [categories] of largely symbolic behaviors. (p. 446). The measure developed in the current series of studies departs from these trends, offering an instrument that (a) assumes close relationships are communal in nature (Clark & Mills, 1979) and therefore (b) focuses on mutually-enacted behaviors (Goldsmith & Baxter, 1996) at (c) a low level of inference (Murray, 1983). The following addresses each of these qualities in turn. First, extant relational maintenance research has devoted much attention to conceptualizing maintenance (see Dindia, 2003) but has given almost no attention to conceptualizing relationships. Examination of the literature reveals that most maintenance scholarship (a) has studied close relational bonds, typically romantic ties (Stafford, 2003), and (b) has conceptualized such bonds as exchange-oriented in nature (Stafford & Canary, 2006). Although the latter assumption serves as a starting point for a rich body of scholarship (Dindia, 2003), an equally deep tradition has conceptualized close ties as communally-oriented (Clark & Mills, 1979) such that that in a close relationship the individual acts as if some or all aspects of the partner are partially the individual s own (Aron et al., 1992, p. 598). Starting from this perspective, Ledbetter et al. (2010) considered relational maintenance from the standpoint of self expansion theory. The theory contains two central principles. First, it postulates that a central

6 RELATIONAL MAINTENANCE AND SELF EXPANSION 6 human motivation is self-expansion achieved by incorporating the resources, perspectives, and identities of others (Aron & Aron, 2001, p. 478); such self-expansion facilitates the individual s goal attainment. The second principle moves from this general motivation to the specific, arguing that the desire to enter and maintain a particular relationship can be seen as one, especially satisfying, useful, and human, means to this self-expansion (Aron & Aron, 2001, p. 484). Thus, as a close relationship progresses, cognitions alter such that each person includes the other in the sense of the self, and consequentially being in a close relationship... [seems] to subvert the seemingly fundamental distinction of self from other (Aron et al., 2004, p. 31). Building from self-expansion theory, Ledbetter and his colleagues (2010) suggested that relational maintenance may not arise so much from perceived equity (Canary & Stafford, 1992) as from this shared sense of collective identity. Because such a collective identity is subject to entropy over time (Levinger, 1983), maintenance behaviors counteract such entropy (Sigman, 1991) and thus sustain close communal relationships. Second, the I orientation of maintenance measures (Oswald et al., 2004; Stafford & Canary, 1991) is consistent with an exchange orientation but, arguably, not with a communal orientation. Rather, if relational maintenance is located in the essence between two people (Ledbetter et al., 2010, p. 27; Buber, 1923/1970), it stands to reason that maintenance behaviors possess a we rather than I orientation. Such an approach has appeared in other measures of relationally-oriented communication such as relationship rituals (Pearson, Child, & Carmon, 2010) and everyday talk (Ledbetter, Broeckelman-Post, & Krawsczyn, 2011). Following self expansion theory (Aron et al., 2004), this measure does likewise. Third, all extant maintenance typologies have posited categories that are fundamentally high-inference in nature. In other words, they require a high degree of interpretation to determine

7 RELATIONAL MAINTENANCE AND SELF EXPANSION 7 whether a particular communication behavior indicates openness, positivity, supportiveness, and so forth. In this respect, the state of the relational maintenance literature bears remarkable similarity to what Murray (1983) observed in instructional literature three decades ago, noting that measures of student s teaching evaluations assessed global factor-analytic dimensions that may not clearly translate to low inference teaching behaviors, or in other words, specific classroom behaviors of the instructor (p. 138). Murray further noted the practical challenge of providing advice without such low-inference measures. Likewise for the relational maintenance literature, a low-inference measure could greatly enhance practical guidance to dyads seeking relational help, and thus the time is ripe for such a measure. This manuscript reports a series of two studies that developed and validated such an instrument. Guided by Ledbetter et al. s (2010) qualitative analysis, the first study tested and refined the factor structure of an initial item pool. The subsequent study employed a sample of heterosexual romantic dyads to test the tenability of a communal, self expansion theory approach to relational maintenance behavior. Method: Study 1 Participants To obtain a diverse set of romantic relationships, participants were recruited via three mechanisms: (a) with the help of the technology department at a medium-sized U.S. Midwestern university, s were sent to a random sample of undergraduate and graduate students, (b) messages were posted on Facebook by the research team, and (c) participants were solicited through posting on area Craigslist pages. Participants completed an online survey and were instructed to complete several measures with their romantic partner in mind (or a friend if the participant had no romantic partner). After removing participants who reported on a friend and

8 RELATIONAL MAINTENANCE AND SELF EXPANSION 8 other unusable data, the final sample contained 474 participants (120 males, 354 females). Participant age ranged from 18 to 63 years (M = 23.4, SD = 6.1) and most participants (87.8%) reported a white/caucasian ethnic identity. Measures Relational maintenance communication scale. The main purpose of the first study was to establish the validity, reliability, and dimensionality of the relational maintenance communication scale (RMCS). Responses were solicited on a 6-point Likert-type scale (0 = Never, 5 = Very Frequently). The initial version of the measure contained 59 items derived from the categories identified in Ledbetter and his colleagues (2010) inductive analysis (such as spending time together, informal talk, deep talk, and physical affection), with some items informed by Goldsmith and Baxter s (1996) work on everyday talk. Results of confirmatory factor analyses on this scale are described in the results section below. Validity measures. Because establishment of criterion validity is an important step in measure development (Keyton, 2006), participants completed 6 measures designed to assess 3 constructs examined in previous relational maintenance research: (a) Vangelisti and Caughlin s (1997) 7-item relational closeness measure (α =.91), (b) Canary, Weger, & Stafford s (1991) 6- item control mutuality measure (α =.84), and (c) Aron and his colleagues (2004) single-item pictorial measure of inclusion of the other in the self (IOS). Additionally, 2 dimensions of attachment (i.e., anxiety and avoidance) were measured using two 6-item versions of Fraley, Waller, and Brennan s (2000) attachment styles measure (α anxiety =.90, α avoid =.85). Finally, previous research indicates relational communication is associated with well-being (Malis & Roloff, 2006), and thus stress was measured using the 4-item version of Cohen, Kamarch, & Mermelstein s (1983) stress measure (α =.74).

9 RELATIONAL MAINTENANCE AND SELF EXPANSION 9 Data Analysis Exploratory factor analysis (EFA) is commonly used in scale development, including previous relational maintenance measures (e.g., Ayres, 1983; Oswald et al., 2004; Stafford & Canary, 1991). Despite its utility when little or no theoretical guidance exists regarding a measure s factor structure, EFA is a data-driven versus theory-driven method, and thus EFA can fail to accurately report underlying factor structure (Little, Lindenberger, & Nesselroade, 1999). Given the wealth of maintenance research and the inductively-grounded typology (Ledbetter et al., 2010), the measure was tested using confirmatory factor analysis (CFA), an approach that evaluates the extent to which an a priori model fits the data s observed covariance matrix. CFA analyses were conducted using the Lavaan package in the R statistical computing environment (Rosseel, 2011). Three fit indices assessed model fit: (a) model chi-square, (b) root mean square error of approximation (RMSEA), and (c) standardized root mean square residual (SRMR). RMSEA and SRMR values below.08 indicate adequate model fit (Kline, 2005). Results: Study 1 The initially hypothesized model contained 12 factors: (a) shared resources, (b) shared information, (c) shared tasks, (d) shared media use, (e) verbal affection, (f) informal talk, (g) deep talk, (h) relationship management, (i) time together, (j) shared humor, (k) physical affection, and (l) shared social networks. This model exhibited acceptable fit, χ 2 (1109) = , p <.01, RMSEA =.070 [90% CI:.067:.072], SRMR =.078, but examination of the parameters and modification indices suggested two modifications. First, the shared information and shared tasks constructs were strongly correlated (r =.98), with a chi-square difference test indicating that a single-factor solution was statistically equivalent, Δ χ 2 (11) = 15.21, p >.05, and second, a small number of items exhibited tendency toward cross-loadings and correlated residuals. After

10 RELATIONAL MAINTENANCE AND SELF EXPANSION 10 collapsing the information and task factors (deleting four items to reduce survey length), and deleting two cross-loading items and five items with correlated residuals, the simplified model exhibited improved fit, χ 2 (647) = , p <.01, RMSEA =.059 [90% CI:.055:.062], SRMR =.059. Table 2 presents items retained in the final model, with Table 3 reporting items standardized and unstandardized loadings and error residuals. Table 4 presents means, standard deviations, scale alphas, and zero-order correlations for the identified factors. Two additional analyses tested the criterion validity and theoretical coherence of the factor structure. First, a confirmatory model evaluated whether maintenance factors are associated with (a) relational closeness, (b) control mutuality, (c) stress, (d) attachment anxiety, (e) attachment avoidance, and (f) IOS. Because three indicators are ideal for just identification and mathematical representation of latent constructs (Kline, 2005), all constructs in this model were identified by parcels (Little, Cunningham, Shahar, & Widaman, 2002); the only exception was the single-item IOS indicator. Aron and his colleagues (1992) examined the IOS measure s reliability, finding 72.25% shared variance in two-week test-retest reliability and 95% shared variance across two different versions of the instrument (one with circles, one with diamonds). The average of these two estimates (83.6%) was used to fix error variance using the method described by Stephenson and Holbert (2003). This model demonstrated acceptable fit, χ 2 (992) = , p <.01, RMSEA =.051 [90% CI:.048:.054], SRMR =.052. Table 5 presents correlations between the maintenance variables and these theoretically-related constructs. Overall, the maintenance variables were positively associated with relational closeness, control mutuality, and IOS, and inversely associated with attachment anxiety, attachment avoidance, and, to a lesser degree, stress. Most correlations were of moderate magnitude, supporting the discriminant and convergent validity of the factors.

11 RELATIONAL MAINTENANCE AND SELF EXPANSION 11 Study 1 Discussion The primary goal of Study 1 was to develop and validate the RMCS instrument. CFA yielded 39 items assessing 11 dimensions of maintenance communication. Although this represents more dimensions than some previous maintenance typologies (e.g., the 5 in Stafford & Canary, 1991 or 4 in Oswald et al., 2004, but fewer than the 28 in Bell et al., 1987), it is no more than other communication typologies (e.g., the 16 compliance-gaining tactics of Marwell & Schmitt, 1967), and is perhaps to be expected when assessing lower-inference behaviors. The dimensions were associated with related constructs in expected ways, such that maintenance behavior was positively associated with closeness, control mutuality, and IOS and inversely associated with attachment anxiety, attachment avoidance, and, to a lesser degree, stress. Specifically, shared resources, media, deep talk, and relationship management were unassociated with stress. Previous research has reported that shared resources (such as money) are a frequent locus of couple conflict (Erbert, 2000) and perhaps both deep talk and relationship management indicate stressful conflict engagement, thus accounting for the nonsignificant associations between stress and these maintenance behaviors. Study 2 extends these results by testing whether self expansion theory (Aron & Aron, 1986) accounts for frequency of maintenance behavior. Specifically, the study tests whether, as Ledbetter et al. (2010) postulated, relational maintenance arises from the extent to which each relational partner includes the other in the sense of the self. Aron and Aron (2001) claim this process is fundamentally dyadic, such that cognitively, the self is expanded through including the other in the self, a process which in a close relationship becomes mutual, so that each person is including the other in his or her self (p. 484). One flexible approach to dyadic questions is the actor-partner interdependence model

12 RELATIONAL MAINTENANCE AND SELF EXPANSION 12 (APIM; Kenny, Kashy, & Cook, 2006) conducted with an SEM framework. Figure 2 depicts the type of APIM tested in this investigation. Not only do APIMs control for the degree of dyadic interdependence within the data, but particularly relevant to self expansion theory, they also permit direct test of the extent to which relational maintenance is communal. The APIM facilitates such tests by deriving estimates for three different types of paths. First, an actor effect is the extent to which one dyad member s independent variable score predicts that same dyad member s dependent variable score (e.g., in this study, a male actor effect is male IOS predicting male frequency of maintenance behavior). Second, the partner effect is the extent to which one dyad member s independent variable score predicts the other dyad member s dependent variable score (e.g., in this study, a male partner effect is female IOS predicting male frequency of maintenance behavior). According to Kenny et al. (2006), a model is communally oriented when the actor effect equals the partner effect: the person is affected as much by his or her own X as by his or her partner s X.... such an orientation would be characteristic of communal relationships (p. 148). However, this fulfills Aron and his colleagues (1991) definition of a communal relationship only partially. Rather, they argue, to the extent a partner is perceived as part of one's self, allocation of resources is communal (because benefiting other is benefiting self), actor/observer perspective differences are lessened, and other's characteristics become one's own (p. 242, emphasis added). Phrased statistically, the theory predicts not only equality of actor and partner effects within an individual, but also equality of actor and partner effects across both individuals. Thus, we hypothesize that not only do men and women enact relationships communally, but the strength of this effect is equal in magnitude across men and women, such that IOS predicts maintenance behavior in a communal and symmetric fashion: H1: Actor and partner IOS will predict relational maintenance behavior according to

13 RELATIONAL MAINTENANCE AND SELF EXPANSION 13 Aron et al. s (1991) definition of a communal relationship, such that actor and partner effects are (a) equal within each dyad member, (b) equal across dyad members, and (c) significantly positive. Beyond actor and partner effects, Kenny et al. (2006) also call attention to the interaction between the actor and partner independent variables. This interaction is the relationship effect, and it tests whether the actor effect changes as a function of the partner effect (or vice versa). Aron and Aron (2001) frame IOS as fundamentally relational, such that it is a process which in a close relationship becomes mutual, so that each person is including the other in his or her self (p. 484). Thus, it could stand to reason that high levels of partner IOS might magnify the contribution of actor IOS to maintenance frequency: H2: Actor and partner IOS will interact to predict relational maintenance such that high partner IOS increases the predictive strength of actor IOS. Method: Study 2 Participants Dyads were recruited via three mechanisms: (a) messages on Craigslist and listservs, (b) announcements on Facebook, and (c) offering extra credit (less than 3% of course grade) to communication undergraduate students who referred romantic couples to the study. Per IRB requirements, credit was awarded upon reference of a couple regardless of whether the couple eventually completed the survey. The final sample contained complete heterosexual dyads with 123 men (ages 18-75, M = 34.19, SD = 13.69) and 123 women (ages 18-74, M = 33.06, SD = 13.23), with most of the 246 participants reporting a white/caucasian ethnic identity (93.1%). Most dyads reported that they were married (72 dyads, 58.5%), with others dating seriously (41 dyads, 33.3%), engaged to be married (6 dyads, 4.9%), and dating casually (4

14 RELATIONAL MAINTENANCE AND SELF EXPANSION 14 dyads, 3.3%). Couples reported an average relationship length of 9.87 years (SD = 11.6). Measures Relational maintenance communication scale. The final 39-item version of the RMCS, developed in Study 1, assessed relational maintenance communication. Responses were solicited on a 6-point scale (0 = Never, 5 = Very Frequently). With the exception of shared networks (α =.55), informal talk (α =.62), and shared media (α =.65), all 11 dimensions demonstrated internal reliability greater than.70 (mean α =.74). IOS. Aron and his colleagues (2004) single-item pictorial measure assessed IOS. This measure presented participants with a series of seven overlapping circles (1 = minimal overlap, 7 = almost total overlap). Previous research has established the measure s discriminant, construct, and predictive validity, including test-retest reliability (Aron et al., 1992). Data Analysis The hypotheses were investigated via APIMs conducted via SEM using the Lavaan package for the R statistical computing environment (Rosseel, 2011). Missing data were imputed using the Amelia missing data package for R. All maintenance constructs were modeled using three indicators, parceling items where appropriate (Little et al., 2002). The single-item IOS construct was identified as in Study 1, with the interaction term between male IOS and female IOS (i.e., representing the relationship effect) created using the orthogonalization procedure described by Little, Card, Bovaird, Preacher, and Crandall (2007) and error variance fixed using the square of the reliability for the first-order terms (.836 *.836 =.699; see Cohen, Cohen, West, and Aiken, 2003). To control for relationship type effects, all manifest indicators were regressed onto relationship type (dummy code for married vs. unmarried), relationship length, and their interaction. Because the small number of parameters in APIM models renders many traditional

15 RELATIONAL MAINTENANCE AND SELF EXPANSION 15 model fit measures inappropriate (Kenny, 2010), the results report only the chi-square fit statistic for the confirmatory models. Results: Study 2 Prior to conducting APIM analyses, a series of 12 confirmatory models (i.e., one for each maintenance type and for IOS) compared means, standard deviations, and degree of interdependence (i.e., correlations) across men and women. A series of model constraints sequentially evaluated whether the constructs differed by sex on (a) equality of indicator loadings, (b) equality of indicator means, (c) equality of latent construct variances, and (d) equality of latent construct means (Little, 1997). Table 6 presents the results of these analyses. All baseline models obtained excellent model fit as demonstrated by non-significant chi-square statistics; furthermore, all maintenance behaviors demonstrated full equality of indicator loadings (except for verbal affection, which demonstrated partial equality when allowing one indicator loading to vary between the sexes) and equality of indicator intercepts (except for shared humor and time together, which demonstrated partial equality when allowing one indicator mean to vary between the sexes). These tests demonstrate that the constructs are statistically comparable across men and women. Tests for equality of means and standard deviations demonstrated a small number of differences between men and women, with differences in the direction of higher means for women (physical affection, humor, informal talk and deep talk) and larger variances for men (tasks, informal talk, and deep talk). Overall, the maintenance types differed greatly in degree of interdependence, with resources demonstrating the most interdependence (r =.86) and time together the least (r =.22). Building from Kenny et al. s (2006) and Aron et al. s (1991) definitions of a communal relationship, a series of APIM analyses tested H1 by simultaneously (a) constraining actor and

16 RELATIONAL MAINTENANCE AND SELF EXPANSION 16 partner effects to equality within each dyad member, (b) constraining actor/partner effects to equality across dyad members, and (c) constraining relationship effects to equality across dyad members. Because differences in latent construct variances can bias direct tests of structural parameter equality (Kenny et al., 2006), APIMs with significant variance differences (see Table 6) placed constructs on an equivalent variance metric using phantom constructs (Rindskopf, 1984). More specifically, this procedure (a) fixes each maintenance construct s variance to zero, (b) creates a second-order (i.e., phantom) construct for each maintenance behavior with phantom construct variance fixed to 1.0, (c) regresses each first-order maintenance construct onto the relevant phantom construct, and (d) fixes this regression path to 1.0 for men and freely estimates the path for women. This procedure shifts the variance difference to this regression path, permitting direct equality tests on the actor, partner, and relationship effects of interest. For nine of the eleven maintenance behaviors (i.e., all except physical affection and networks), the constraints for H1 were tenable; in other words, constraining all four direct effects in the model (i.e., male actor, male partner, female actor, female partner) to equality, as well as the relationship effects to equality, produced a nonsignificant decline in model fit. Table 7 reports the regression parameters, variance explained, and chi-square difference tests for these nine models. For six of these nine maintenance behaviors (i.e., verbal affection, humor, deep talk, informal talk, relationship management, and tasks) the relationship effect also achieved or approached (p <.08) statistical significance. For physical affection, the communal constraint significantly worsened model fit, Δχ 2 (2) = 13.75, p <.01. According to Kenny et al. (2006), it is possible for one dyad member to possess a communal orientation while the other does not. Follow-up tests indicated that constraining male actor and partner effects to equality was tenable, Δχ 2 (1) = 1.66, p >.05, but such a

17 RELATIONAL MAINTENANCE AND SELF EXPANSION 17 constraint for female actor and partner effects was not, Δχ 2 (1) = 8.12, p <.01. Examination of this model revealed a strong actor effect for women with nonsignificant partner and relationship effects; according to Kenny et al., such a pattern indicates an actor-oriented model in which a person s outcomes are a function of that person s characteristics only (p. 148). The tenability of this model was tested by constraining female partner and interaction effects to zero, and this constraint (along with the communal constraint on the male actor and partner effects) did not differ significantly from the unconstrained model, Δχ 2 (3) = 2.10, p >.05. This constrained model revealed a significant actor/partner effect for men (B = 0.34, SE = 0.07, β =.29, p <.01) and a relationship effect approaching statistical significance (B = -0.21, SE = 0.12, β = -.21, p <.07), explaining 26.4% of men s physical affection. Among women, the actor effect was significant (B = 0.62, SE = 0.12, β =.53, p <.01) and the partner and relationship effects were constrained to zero, explaining 28.0% of the variance in women s physical affection. Like physical affection, the omnibus communal constraint was not tenable for network maintenance, Δχ 2 (2) = 13.80, p <.01; also likewise, follow-up tests revealed the communal constraint was tenable for men, Δχ 2 (1) = 2.46, p <.05, but not women, Δχ 2 (1) = 6.62, p <.05. Examination of the results for women revealed significant actor and partner effects of nearly equivalent magnitude but opposite sign. According to Kenny et al. (2006), actor and partner effects of this pattern indicate a social comparison model whereby the person implicitly or explicitly compares him- or herself with the partner (p. 149). This orientation stands in contradistinction to the communal pattern: In contrast to the couple-oriented case, in which the partner s success is valued as much as one s own outcome, the social comparison orientation typically involves dissatisfaction with the partner s success. Both imply couple effects, but their conceptual meanings are totally opposite (Kenny et al., p. 149). This possibility was tested by

18 RELATIONAL MAINTENANCE AND SELF EXPANSION 18 constraining the female partner effect to equal the female actor effect multiplied by -1. Because Lavaan currently offers only limited support for constraints of this type, this test was performed using LISREL Simultaneously placing this constraint and the communal constraint for men produced a nonsignificant decline in model fit as compared to the unconstrained model, Δχ 2 (1) = 2.54, p >.05. In this model, men obtained significant male actor/partner effects (B = 0.23, SE = 0.07, β =.21, p <.01) but not a significant relationship effect (B = -0.12, SE = 0.14, β = -.11, p >.05), explaining 13.7% of the variance in men s report of network maintenance. A significant relationship effect also did not emerge for women (B = 0.03, SE = 0.14, β =.03, p >.05), with the actor effect producing a significantly positive (B = 0.40, SE = 0.12, β =.37, p <.01) and the partner effect an equivalently negative (B = -0.40, SE = 0.12, β = -.37, p <.01) association. Together, these effects explained 16.7% of the variance in women s report of network maintenance. Thus, it appears network maintenance is distinct not only because an omnibus communal constraint is not tenable, but also because men adopt a communal approach to networks in contrast to women s competitive approach. Overall, then, analyses supported H1 s expectation of a communal orientation toward maintenance for all male maintenance communication, as well as all female maintenance except physical affection and networks. H2 predicted relationship effects, such that high partner IOS magnifies the positive actor effect. Relationship effects were obtained for several behaviors (verbal affection, humor, tasks, informal talk, deep talk, relationship management, and, for men, physical affection). Decomposition using the method described by Cohen et al. (2003) revealed a nearly identical pattern for each maintenance behavior, albeit not as hypothesized. Rather than the expected magnification effect, results indicated that only one member of the dyad needed to possess high IOS for high levels of the maintenance behavior to occur. Speaking in terms of simple slopes, the

19 RELATIONAL MAINTENANCE AND SELF EXPANSION 19 actor effect was significantly positive except in the presence of high partner IOS, in which case the actor effect was nonsignificant. We may refer to this as a compensatory pattern, such that lack of IOS in one pattern is compensated by the presence of IOS in the other vis-à-vis maintenance behavior. In contrast, other communal behaviors (resources, media, time, and, for men, networks) did not obtain relationship effects. Thus, frequency of the maintenance behavior is an additive combination of the two member s IOS, such that members enact low levels of maintenance when both possess low IOS, moderate levels when only one member has high IOS, and high levels when both have high IOS. Taken together with (a) women s actor-oriented approach to physical affection and (b) women s social comparison approach to networks (discussed previously), the communal pattern (c) with relationship effect and (d) without relationship effect yields four distinct dyadic patterns across the behaviors (see Figure 2). General Discussion After establishing the dimensionality and validity of the RMCS in Study 1, the central goal of Study 2 was to test Ledbetter et al. s (2010) claim, building from self expansion theory (Aron et al., 2004), that IOS predicts maintenance communication in heterosexual romantic dyads. With only a few exceptions, results supported this expectation. This discussion will first consider the majority of maintenance behaviors for which a communal approach was tenable, including relationship effects, before considering exceptions to the communal pattern. Relational Maintenance as Communal Central to self expansion theory rests the claim that, in close relationships, actor/observer perspective differences are lessened, and other's characteristics become one's own (Aron et al., 1991, p. 242). Thus, building from Ledbetter et al. (2010) and Kenny et al. (2006), this study reasoned that actor and partner IOS should predict maintenance with equal

20 RELATIONAL MAINTENANCE AND SELF EXPANSION 20 magnitude, both within and across dyad members. Results supported this expectation (H1) for nine of the eleven maintenance behaviors (i.e., all except physical affection and social networks). These deviations will be discussed later, but the overall trend of the results clearly and strongly supports self expansion theory as an explanatory mechanism for relational maintenance behavior. This communal approach differs from the dominant equity theory approach to relational maintenance (Stafford & Canary, 1991). Some have argued the exchange- and communallyoriented approaches to relationships are fundamentally incompatible; if maintenance arises from an individual s cost-benefit analysis and demands equitable reciprocation (Canary & Stafford, 1992), it would seem maintenance does not arise from a sense of interconnectedness (Ledbetter et al., 2010) with reciprocation unnecessary (Clark & Mills, 1993). Yet, at least some previous empirical evidence suggests that equity fosters relational maintenance behavior (Stafford & Canary, 2006). Reconciling these findings is a heuristic theoretical task, and thus three tentative explanations are advanced here. First, it remains possible that methodological differences between the RMCS and RMSM account, at least partially, for evidence supporting both approaches. Whereas the RMCS was designed as a low-inference measure of behavior frequency, the RMSM is a high-inference measure of agreement that behaviors take place. Perhaps equity motivates members overarching agreement about the existence of maintenance behavior, but interconnectedness motivates day-to-day behavior enactment. Second, perhaps equity mediates the association between IOS and maintenance behavior. To the extent that high IOS removes cognitive distinction between self and other (Aron & Aron, 2001), members of such relationships may tend to report that their relationships are equitable and this, in turn, may predict maintenance behavior. Finally, and perhaps most heuristically, some third factor may moderate whether equity or interconnectedness fosters maintenance behavior. For example, some

21 RELATIONAL MAINTENANCE AND SELF EXPANSION 21 work has suggested that orientation toward communality may be trait-like (Clark, Ouellette, Powell, & Milberg, 1987), and this may serve as a moderator; attachment styles may function similarly (Fraley et al., 2000). In any case, understanding when exchange (and communal) orientations do (and do not) operate is a clear direction for future theoretical refinement (Canary & Stafford, 2007). Relationship Effect Despite Aron and Aron s (2001) claim that close relational partners possess mutually high IOS, the moderate correlation between male and female IOS in these data suggests it is quite possible for romantic partners to possess divergent IOS. Such a moderate correlation has been found in prior research as well (Simpson, Oriña, & Ickes, 2003). The relationship effect (i.e., interaction between actor and partner IOS) assessed the extent to which the degree of similarity between members IOS predicted maintenance behavior, and such an effect emerged for several maintenance behaviors (verbal affection, humor, tasks, informal talk, deep talk, and relationship management). The relationship effects did not occur as hypothesized (Aron & Aron, 2001); versus a magnification pattern, a compensatory pattern emerged such that only one member needed to possess high IOS for the maintenance behavior to occur. With the exception of tasks, all of these behaviors are verbal in nature; indeed, every fundamentally verbal behavior in the typology obtained a significant relationship effect. In contrast, the behaviors that exhibited communality but not a relationship effect resources, media, and time are not only nonverbal but scarce. Giving informal talk to one person does not mean one has less to give to another; but giving a resource (such as money) to another person necessarily means the giver cannot allocate it elsewhere. This principle of scarcity may explain why tasks also demonstrated this pattern, for

22 RELATIONAL MAINTENANCE AND SELF EXPANSION 22 the supply of tasks to accomplish approaches inexhaustibility (Demo & Acock, 1993). Maintenance Behaviors Departing From the Communal Trend Results indicated that relationship-level communality was not tenable for physical affection and shared networks, although further tests indicated communality was tenable for men but not women. Rather, women s physical affection unexpectedly emerged as actor-oriented, such that only her level of IOS served as a predictor, and women s network maintenance was competitively oriented, such that her level of IOS positively predicted networks but her partner s IOS was an inverse predictor. The following considers each of these behaviors in turn. Physical affection. Physical affection is foundational to human bonding in romantic relationships (Floyd & Morr, 2003), yet these data suggest that IOS predicts it differentially across men and women. Specifically, only an actor effect predicted women s physical affection, whereas actor, partner, and relationship effects all predicted men s physical affection. Although only future research can identify and test theoretical perspectives that might explain these differences, Andersen, Guerrero, and Jones (2006) interaction-centered model of intimacy processes suggests considering the mismatch between the experience and expression of intimacy as a possible explanatory mechanism. Arguing that nonverbal communication is the sine qua non of intimacy (Andersen et al., 2006, p. 260), the interaction-centered intimacy model has posited that intimacy consists of overlapping relational schemas, an idea clearly akin to IOS (Aron et al., 2004). These schemas, in turn, trigger the experience of intimacy (e.g., warm emotions) which then leads to expression of intimacy via nonverbal communication. Thus, we might expect that men and women would agree on their frequency of physical affection (i.e., intimacy expression) when their IOS levels are equivalent, and decomposition revealed this was the case in these data. When IOS levels are

23 RELATIONAL MAINTENANCE AND SELF EXPANSION 23 not equivalent, the experience and expression of intimacy may be mismatched in the relationship. For example, partners agreed when female IOS was high but male IOS was low, with both reporting a high amount of physical affection; but given that physical affection is primarily driven by the woman s level of IOS, she may expect that such drives the man s level of physical affection as well, and thus a mismatch exists between their mutual expression of intimacy and their divergent experiences of it. Contrariwise, when male IOS is high and female IOS is low, results indicated that a man will seek a high level of physical affection that may not be reciprocated by his partner; in this case, the man s desired intimacy expression may not match his partner s experience of it. Clearly, either case could lead to relational conflict (Erbert, 2006). Networks. As Knobloch and Donovan-Kicken (2006) note, most studies examine the extent to which network members support romantic relationships (e.g., Sprecher & Felmlee, 1992) but few have examined the extent to which network members hinder them. One exception is Bryan, Fitzpatrick, Crawford, and Fischer s (2001) report that support from a woman s network contributes to romantic relationship satisfaction and network hindrance does not detract from it. A clear lacuna in this study is the absence of assessing the extent to which the male partner s network aids or hinders the romantic relationship. Knobloch and Donovan-Kicken (2006) considered perceived helpfulness and perceived hindrance of network members more broadly, examining a sex heterogeneous sample of dating partners. Results indicated that network hindrance was most likely to occur at moderate levels of intimacy and, running counter to their hypothesis, when level of partner uncertainty (i.e., the ambiguity individuals experience about their partner s involvement in the relationship ; Knobloch & Donovan-Kicken, p. 283) was high. Although the association between relational uncertainty and IOS awaits empirical investigation, it could stand to reason that low partner

24 RELATIONAL MAINTENANCE AND SELF EXPANSION 24 uncertainty indicates high partner IOS; and indeed, this study found that high partner IOS reduced women s network maintenance. Taking these results together with the few previous studies, it could be that women tend to view their own networks as helpful and their partner s networks as a hindrance. In contrast, a communal orientation was tenable for men, with no significant relationship effect; this may indicate that men view time with social networks as a scarce resource most devoted to the relationship when both partners IOS is high. This suggests that a man with high IOS may see inclusion of his partner in his social networks as indicative of interconnectedness whereas his partner sees such as a hindrance. Only future research can test this tentative explanation. Conclusion Of course, all investigations possess both strengths and weaknesses, and the studies reported here are no exception. Although both studies move beyond a college student sample, and the second study employs dyadic data analysis for investigating decidedly dyadic questions, both studies are only cross-sectional in nature. Longitudinal designs are complex, and dyadic longitudinal designs especially so (Kenny et al., 2006), but such future research could prove invaluable for theoretical refinement and practical application. Additionally, communal explanations rely, to some extent, on the actor s perception of the partner s IOS; in other words, an actor may think the partner has high IOS, but this may not be the case. Future research could elaborate the model s mechanism by including perception of partner IOS, perhaps as a mediator. Finally, although the samples were heterogeneous by age and relationship type, most participants were Caucasian; only future research can assess generalizability to other populations. The two studies reported here offer a low-inference measure as a complementary alternative to other popular relational maintenance instruments (Oswald et al., 2004; Stafford &

25 RELATIONAL MAINTENANCE AND SELF EXPANSION 25 Canary, 1991). Additionally, these results commend further evidence supporting a communal approach to relational maintenance, such that maintenance arises from partner s perceived mutual interdependence. To the extent that romantic relationship quality predicts psychosocial well-being (Malis & Roloff, 2006), future research may employ these findings to further refine maintenance theory and identify specific maintenance behaviors that foster individual and relational health.

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