Let’s Talk,Honey: An Analysis of Associations Between Communication Patterns and Dyadic Adjustment in Married Couples

Abstract

Good communication is an integral part of successful intimate relationships. The present study examined the factor structure of the Communication Pattern Questionnaire-Short Form (CPQ-SF) and the dyadic associations between communication patterns and dyadic adjustment in a sample of 162 married couples from Turkey (mean age = 39.09 years). Psychometric analyses support that the Turkish version of the Communication Patterns Questionnaire with 7 items (the CPQ-TR-7) is a reliable measure to assess partners’ communication patterns in the form of positive interactions, self-demand, and self-withdraw. Actor-Partner Interdependence Model analysis revealed that husbands’ and wives’ positive interactions were positively associated with their own as well as their partners’ dyadic adjustment, the more husbands’ and wives’ withdraw, the lower their own dyadic adjustment, and the more wives demand, the lower their own dyadic adjustment.

Keywords

dyadic adjustment communication patterns actor effects partner effects couples actor-partner interdependence model

Introduction

Good communication is key in close relationships. Couple communication has been found to be strongly associated with dyadic adjustment in romantic relationships (e.g., Carroll et al., 2013; Feeney, 1994; Ledermann et al., 2010; Noller & Feeney, 2002; Perrone & Worthington, 2001). Dyadic adjustment, which is related to stability in marriage (Bui et al., 1996; Karney & Bradbury, 1995; Le & Agnew, 2003), has also been shown to be linked to communication within the context of married couples (e.g., Caughlin & Huston, 2002; Christensen & Shenk, 1991; Richmond, 2009). The present study examined the factor structure and reliabilities of the Communication Pattern Questionnaire-Short Form (CPQ-SF) and the dyadic associations between communication patterns and dyadic adjustment in a sample of Turkish married couples.

Literature Review

Over the last several decades, dyadic adjustment has become one of the most studied constructs in relationship research.). Despite the conceptual overlap between relationship satisfaction and dyadic adjustment, they are in fact conceptually distinct from one another (e.g., Bradbury et al., 2000; Eddy et al., 1991). While relationship satisfaction is associated with adjustment to the partner and the relationship (Schumm, 1985), dyadic adjustment is a comprehensive term referring to the quality of a marriage in terms of relationship satisfaction and happiness (Lewis & Spanier, 1979).

Dyadic adjustment has been shown to be linked with both physiological and psychological well-being in couples (Kiecolt-Glaser & Newton, 2001; Robles et al., 2014; Waite & Gallagher, 2000). Beyond its contribution to well-being, dyadic adjustment is also a key variable for successful intimate relationships and can help to strengthen the quality of the relationship and prevent breaking up (Bui et al., 1996; Gottman, 1994; Karney & Bradbury, 1995; Mirfardi et al., 2010). Therefore, examining factors that contribute to relationship adjustment in couples can contribute to a better understanding of both individual and dyadic effects that affect partners’ dyadic adjustment.

The quality of communication (Holman, 2006) and communication patterns (Lewis & Spanier, 1979) were found to be strong predictors of marital quality (Carroll et al., 2013), relationship stability (Gottman, 1994), well-being (Siffert & Schwarz, 2010), and dyadic adjustment (Carrère & Gottman, 1999; Christensen & Shenk, 1991; Heavey, et al., 1996). While most of these studies focused on communication patterns in individuals (e.g., Carroll et al., 2013; Ebrahimi & Ali Kimiaei, 2014; Perrone & Worthington, 2001), some studies included couples revealing significant associations between communication patterns and relationship satisfaction, particularly positive interactions are positively and demand-withdraw communication is negatively associated with relationship satisfaction (Burleson & Denton, 1997; Heavey et al., 1995; Lavner et al., 2016; Ledermann et al., 2010; Kurdek, 2001; Litzinger & Gordon, 2005, Siffert & Schwarz, 2010).

A limited number of studies tested for actor (within-partner) effects and partner (between-partner) effects between couple communication and dyadic adjustment (e.g., Chi et al., 2013; Li & Johnson, 2018; Tan et al., 2017). The study by Li and Johnson (2018) examined the effects of depression on couples’ dyadic adjustment and found that the variable male demand and female withdraw moderated the partners’ effects of depression on their own dyadic adjustment. Chi et al. (2013) found that both partners’ communication was associated with their own dyadic adjustment and that wives’ communication was associated with their husbands’ dyadic adjustment. The study by Tan et al. (2017) revealed that one’s own positive interactions and demand/withdraw were associated with one’s own but not with the partner’s dyadic adjustment. Although the findings of these studies highlighted the dyadic role of communication patterns on dyadic adjustment in American, European, and Chinese samples, how a person’s communication patterns are associated with his or her own as well as with the partner’s dyadic adjustment in Turkish couples remains unclear. Zhang and Kline (2020) stated that there is much speculation that communication behaviors differ markedly between Eastern and Western cultures. More specifically, it is speculated that the relationship between communication and satisfaction is stronger in Western couples than in non-Western couples. Considering cultural differences in couple communication, there is a need for more studies outside of Western cultures to capture differences in communication patterns in couples across cultures (see also Iida et al., in press).

Studies investigating the association between communication patterns and dyadic adjustment (e.g., Kurdek, 2001; Noller & White, 1990; Troy et al., 2006) often used the Communication Patterns Questionnaire (CPQ) developed and introduced by Christensen and colleagues (Christensen, 1987; 1988; Christensen & Sullaway, 1984). This self-report questionnaire provides insights into interaction patterns between romantic partners and assesses two dimensions, known as constructive communication and demand/withdraw communication (Christensen & Shenk, 1991). Studies testing the factor structure of the CPQ revealed inconclusive results (e.g., Heavey et al., 1996; Noller & White, 1990). Although a short version of the CPQ (CPQ-SF) was developed (Christensen & Heavy, 1990), Futris et al. (2010) highlighted inconsistencies in how it is used, including the use of different rating scales and subscales. Using the CPQ-SF, Futris et al. (2010) found support for a four-factor structure. However, there is no comprehensive study that examined the factor structure and reliabilities of the CPQ-SF in a Turkish sample. It is debated in the literature whether couple communication processes are influenced by cultural factors or not (Hooley & Hahlweg, 1989; Rehman & Holtzworth-Munroe, 2007). Turkey is a collectivistic culture (Göregenli, 1997), and individuals from collectivistic cultures tend to withdraw from conversations, compromise on conflict, and engage less in problem-solving compared to those from individualistic cultures (Holt & DeVore, 2005). Consistent with this, a cross-cultural study found that Turkish people tend to avoid and postpone interpersonal conflicts (Cingöz-Ulu & Ladonde, 2007). Thus, it is unclear how these cultural factors affect the factor structure and reliabilities of the CPQ-SF.

The CPQ and its short form are widely used to assess couples’ self-perpetuating interactions (e.g., Caughlin, 2002; Caughlin & Huston, 2002; Kurdek, 2001). Studies conducted with the CPQ-SF found that positive interactions are a strong positive predictor of marital satisfaction, relationship quality, and relationship stability (Feeney, 1994; Heavey et al., 1996; Holman, 2006; Johnson et al., 2005; Larson & Holman, 1994). A longitudinal study on newlywed couples found that low levels of positive interactions were associated with declining marital quality (Johnson et al., 2005). Low levels of positive interactions were also found to be associated with a higher risk for divorce (Matthews et al., 1996). Thus, a better understanding of the dyadic associations between positive interactions and dyadic adjustment will help couples maintain a stable and happy relationship.

The negative communication pattern has been found to be negatively associated with marital satisfaction (Bodenmann et al., 1998; Caughlin & Huston, 2002; Noller & White, 1990). Studies by Christensen and colleagues revealed that distressed couples reported less mutually positive interactions and more demand-withdraw communication than non–distressed couples (Christensen & Heavey, 1990; Christensen & Shenk, 1991). Christensen and Shenk (1991) further divided the demand/withdraw communication subscale into gender-specific patterns (female demand/male withdraw vs. male demand/female withdraw), and they suggested to use of the term ‘positive interactions’ instead of ‘constructive communication’ (Christensen & Heavey, 1990; Heavey et al., 1993).

Demand/withdraw reflects the negative aspect of the communication patterns and is found to be negatively associated with marital satisfaction (Caughlin & Huston, 2002; Christensen & Heavey, 1990). Withdraw behaviors involve leaving the situation or being silent about the conflict or person. Withdraw in communication has also been found to increase the risk of divorce in both newlyweds (Gottman, 1994; Gottman et al., 1998) and longer-married couples (Gottman & Levenson, 2002). Gottman and Krokoff (1989) showed that unsolved problems tend to lead to growing distance and alienation, which, in turn, tend to lead to deterioration in marriage over time. A study that examined the association between communication patterns and dyadic adjustment in married couples found that an elevated demand-withdraw pattern (i.e., one partner makes demands while the other partner attempts to withdraw) was a strong predictor of a decrease in dyadic adjustment over 2.5 years (Heavey et al., 1995). Although most of the studies focused on the combination of demand and withdraw as a demand/withdraw pattern (e.g., Chi et al., 2013; Li & Johnson, 2018; Tan et al., 2017), it is also important to have a good understanding of the individual effects of demand and withdraw on dyadic adjustment.

A couple study examined the effect of the demand and withdraw pattern on subjective well-being and marital satisfaction as a single measure as well as separate measures and revealed a stronger effect for the separate measures than for the single measure (Sieffert & Schwarz, 2010). The current study builds on this research by taking a closer look at the associations between one’s own and the partner’s communication patterns and their dyadic adjustment in couples.

The Present Study

This study aimed to examine the factor structure and reliabilities of the CPQ-SF in Turkish couples and the dyadic associations between communication patterns, in the form of positive interactions, self-withdrawal, self-demand, and dyadic adjustment. Using data from heterosexual married couples, we sought to investigate whether a person’s positive interactions, withdraw, and demand were associated with his or her own as well as the spouse’s dyadic adjustment. Based on previous findings (e.g., Chi et al., 2013; Christensen et al., 2006; Falconier & Epstein, 2011; Gottman, 1994), we hypothesized that positive associations occur between one’s own positive interactions and one’s own dyadic adjustment and negative associations occur between one’s own self withdraw and self-demand and one’s own dyadic adjustment (actor effects). In addition, substantial associations are expected between the partners, but these partner effects are smaller in size than the actor effects (Orth, 2013). Figure 1 shows the conceptual model. We used first-married couples because marital satisfaction has been found to be associated with the number of marriages (e.g., Coleman & Ganong, 1990; Kheshgi-Genovese & Genovese, 1997) and controlled for the marital duration, which, in turn, is negatively associated with dyadic adjustment (Lavner & Bradbury, 2010; Orathinkal & Vansteenwegen, 2007).

Figure 1.

Conceptual model.

Method

Participants

The sample of this study consists of 162 heterosexual married couples (162 women, 162 men, N = 324 participants) from Turkey. The inclusion criteria were being 18 years old or older, that this is the first marriage for both spouses as marital satisfaction has been found to be associated with the number of marriages (e.g., Coleman & Ganong, 1990; Kheshgi-Genovese & Genovese, 1997). The participants of this study included the international post-doctoral research fellowship project with first-married heterosexual couples supported by The Scientific and Technological Research Council of Turkey (TÜBİTAK). The ages of the participants ranged from 22 to 74 years, and the average age of participants was 39.09 years (SD = 10.04). The average age of participants at marriage was 27.27.0 years (SD = 4.37), the average age difference in marriage was 3.12 years (SD = 2.99) and the average duration of marriage was 11.89 years (SD = 10.15).

Most participants graduated from university (29.9%), followed by high school (29.6%), college (14.5%), postgraduate (8.9%), primary school (10.2%), and secondary school (6.8%). The majority of participants were working (82.1%), followed by not (17.9%). Most participants described their family income level as middle (43.2%), followed by low-middle (30.2%), middle-high (19.4%), low (4.6%), and high (2.5%). The majority of the participants met their spouse at work or school (42.3%), followed by friends (33.6%), family (11.4%), social media (6.8%), and others (3.9%). Most of the couples have one child (53.4%), followed by two children (26.5%), did not have a child (16.2%), three children (2.2%), four children (0.9%), and five children (0.6%).

Measures

Demographics

Demographic information included participants’ age, sex, educational attainment, income, marriage duration, age at marriage, age differences in marriage, number of children, and whether participants are in their first marriage. Family income was assessed by a five-point self-rating scale: 1 = low, 2 = low-middle, 3 = middle, 4 = middle-high, and 5 = high.

The Communication Patterns Questionnaire Short Form

The communication patterns among couples were measured using the Communication Patterns Questionnaire Short Form (CPQ-SF; Christensen & Heavey, 1990, 1993). The CPQ-SF consists of 11 items, and respondents were asked to rate each item on a 9-point scale (1 = very unlikely; 9 = very likely). The CPQ-SF has three subscales, male demand/female withdrawal, female demand/male withdrawal, and positive interactions. Example items for the three subscales are “Female tries to start a discussion while male tries to avoid a discussion,” “Male tries to start a discussion while female tries to avoid a discussion,” and, “Both spouses express feelings to each other”.

Studies that assessed the factor structure of the CPQ-SF proposed different factor solutions. In addition to the three-factor solution proposed by (Christensen & Heavey, 1990), Futris et al. (2010) found support for an additional factor that they call criticize/defend, which is normally subsumed within the demand/withdrawal subscales (Christensen & Heavey, 1990; Holtzworth-Munroe et al., 1998). The factor structure of the CPQ-SF in Turkish couples was examined in this study as part of the preliminary results.

Revised Dyadic Adjustment Scale

The Revised Dyadic Adjustment Scale (RDAS; Busby et al., 1995) was used to assess the relationship adjustment of participants. This is a condensed version of the Dyadic Adjustment Scale (DAS; Spanier, 1976). The RDAS consists of 14 items, and participants were asked to rate the first six items on a four-point scale (1 = never, 4 = always) and the rest of the items on a six-point scale (1 = never, 6 = always). The RDAS consists of three subscales consensus, satisfaction, and cohesion. Example items are “agreement about career decisions” for consensus, having a stimulating exchange of ideas” for satisfaction, and “how often the partners quarrel” for consensus. In addition to the subscales, there are also total scores, indicating greater marital satisfaction, with higher scores indicating higher levels of marital satisfaction. This study used the Turkish version of the RDAS (Bayraktaroğlu & Çakıcı, 2017). Cronbach’s alphas were .85 for wives’ marital satisfaction and .86 for husbands’ total marital satisfaction.

Procedure

The ethical approval was obtained from The Scientific Research and Publication Ethics Center of FMV Isik University before the beginning of the data collection. The study announcement, which was shared on social network sites (e.g., WhatsApp, Instagram, Twitter) to recruit married couples, included information about the research and the inclusion criteria. After signing the informed consent, participants were directed to the study. The data were collected between February and November 2021 using SurveyMonkey.

Statistical Analyses

Descriptive statistics and factor analysis were performed using the Statistical Software Package IBM SPSS – 27. We first tested the factor structure of the CPQ-SF using Principal Component Analysis with varimax rotation. The varimax rotation method is suggested when factors are not substantially correlated (Tabachnick & Fidell, 2013). An acceptable solution is indicated when the standardized factor loadings are above .50 (Fabrigar et al., 1999). Kaiser–Meyer–Olkin (KMO) value is above .50. (Kaiser, 1974), Bartlett’s test is not above .05 (Bartlett, 1951), explained variance by factor analysis is at least 60% (Hair et al., 2012), and Cronbach’s alpha is at least .60 (Nunnally & Bernstein, 1994).

To determine the effects of wives’ and husbands’ positive interactions, self-withdraw, and self-demand on their own and their spouses’ dyadic adjustment, the Actor-Partner Interdependence Model (APIM; Kenny et al., 2006) for distinguishable dyads was used. Actor effects refer to the association between a person’s predictor variable and his or her own outcome. Partner effects refer to the association between the person’s predictor variable and the partner’s outcome variable. In this study, the actor effect is the effect from one’s own positive interactions, self-withdraw, and self-demand on one’s own dyadic satisfaction. The partner effect is the effect from one’s own positive interactions, self-withdraw, and self-demand on his or her partner’s dyadic adjustment. Three separate models were estimated that differed in the predictor variables: positive interactions (model 1), self-withdraw (model 2), and self-demand (model 3). Dyadic satisfaction was used as an outcome and duration of marriage was included as a covariate in all three models. We first estimated an unrestricted model for each predictor variable and then tested for specific dyadic patterns (Kenny & Cook, 1999; Kenny & Ledermann, 2010). Specifically, parameter k, which is the ratio of the partner effect to the actor effect, was estimated. If k is 0 or close to 0, the actor-only pattern is indicated, and if k is 1 or close to 1, the couple pattern is indicated (see Kenny & Ledermann, 2010, for details). Bootstrapping with 5000 bootstrap samples was used to estimate the confidence intervals of the k parameters. Power was estimated for the actor and partner effects adapting the code for power simulations for the simple APIM developed by Ledermann et al. (2022). APIM analyses were conducted using Structural Equation Modeling (SEM) and the Full Information Maximum Likelihood (FIML) Estimation method in Mplus (Muthén & Muthén, 1998–2022), which allows the testing of specific patterns and the comparison of effects (Ledermann & Kenny, 2017).

Results

Psychometric Analyses of the CPQ-SF

The factor structure of the Turkish CPQ-SF was tested separately for wives and husbands. Using all 11 items, the results of the exploratory factor analysis suggest a structure with four latent factors for both genders (see supplemental material Table S1). The KMO and Bartlett’s test indicated that the 11 items were adequate for wives (KMO = .631; χ² (55) = 510.359, p < .001) and for husbands (.611; χ² (55) = 489.563, p < .001). These four factors accounted for 69% of the variance in husbands and 68% in wives. However, this four-factor solution was not in line with our expectations and the interpretation of the four factors is difficult. The inter-correlations of the items revealed low correlations for items 1, 6, 10, and 11 (see Table S2). Using items 2, 3, 4, 5, 7, 8, and 9, the KMO test and Bartlett’s test demonstrated that the sampling and the data of the 7 items were adequate for wives (KMO = .653; χ² (21) = 303.302, p < .001) and for husbands (.551; χ² (21) = 252.524, p < .001). The principal component analysis supported a solution with three latent factors, explaining 74% of the variance in wives and 71% in husbands. Table 1 shows the standardized factor loadings for the seven items (see Table S3 for the Turkish items). Items 2, 5, and 7 reflect positive interactions, items 3 and 8 self-withdraw, and items 4 and 9 self-demand. Cronbach’s alphas for wives were .77 for positive interactions, .61 for self-demand, and .70 for self-withdraw. For husbands, Cronbach’s alphas were.74 for positive interactions, .70 for self-demand, and .61 for self-withdraw.

Table 1.

Standardized Factor Loadings for Exploratory Factor Analysis.

Item		Wives			Husbands
Item		Positive Interactions	Self-Demand	Self-Withdrawal	Positive Interactions	Self-Demand	Self-Withdrawal
1	Both spouses try to discuss the problem	.849	−.048	−.007	.747	.030	−.125
2	I try to start a discussion while spouse tries to avoid a discussion	−.223	.783	−.121	−.074	.859	.040
3	My spouse tries to start a discussion while I try to avoid a discussion	−.159	−.120	.774	−.126	−.042	.861
4	Both spouses express feelings to each other	.885	−.088	−.134	.878	−.080	−.027
5	Both spouses suggest possible solutions and compromises	.784	−.060	−.196	.849	.055	−.015
6	I pressure, nag, or demand while my spouses withdraw, becomes silent, or refuses to discuss the matter further	.055	.890	.031	0.83	.876	−.019
7	My spouse pressures, nags, or demands while I withdraw, become silent, or refuse to discuss the matter further	−.068	.035	.866	−.010	.062	.872

Note. For each column the factor loadings in bold reflect specific subscales.

Wives’ positive interactions were negatively correlated with their own self-demand and husbands’ positive interactions were negatively correlated with their own self-withdraw. No correlation emerged between wives’ and husbands’ self-demand and self-withdraw, rectifying the use of Varimax rotation for the factor analysis. Wives’ and husbands’ dyadic adjustment were positively correlated with their own positive interactions and negatively correlated with their own self-withdraw.

Descriptive Statistics and Correlations

Descriptive statistics and correlations between the study variables are shown in Table 2. In wives, positive interactions were positively correlated with their dyadic adjustment. No such association emerged for self-withdraw and self-demand. In husbands, positive interactions were positively correlated with their dyadic adjustment. A negative correlation emerged for self-withdraw. No association emerged for self-demand.

Table 2.

Descriptive Statistics and Correlations of the Study variables.

Variable	1	2	3	4	5	6	7	8	9
1. Dyadic adjustment wife		.539^***	−.175^*	−.204^**	.551^***	.359^***	−.052	.020	.024
2. Positive interactions wife			−.135	−.420^***	.392^***	.390^***	−.131	.001	.002
3. Self-withdraw wife				.065	−.133	−.018	−.014	.356^***	.024
4. Self-demand wife					−.028	−.104	.365^***	−.101	−.010
5. Dyadic adjustment husband						.586^***	−.196^*	−.046	.037
6. Positive interactions husband							−.184^*	.060	−.008
7. Self-withdraw husband								.137	−.024
8. Self-demand husband									−.021
9. Marital duration
M	59.57	19.67	6.30	8.58	59.44	20.50	9.70	6.81	11.89
SD	7.94	5.64	4.43	5.01	10.15	5.27	4.90	4.21	10.15
Minimum (Possible)	0	2	2	2	0	2	2	2
Maximum (Possible)	69	27	18	18	69	27	18	18

Note. SD = standard deviation. *p < .05. **p < .01. ***p < .001 (two-tailed).

Dependent-sample t-tests indicated that husbands and wives differed significantly on self-withdraw, t (162) = 1.763, p < .001, with husbands reporting on average higher levels of self-withdraw than wives, and self-demand, t (162) = 3.296, p < .001, with wives reporting on average higher levels of self-demand than husbands. No significant gender differences emerged for positive interactions, t (162) = 1.763, p = .080, and dyadic adjustment, t (162) = 0.551, p = .583.

APIM Analysis

The results of the APIM analyses are shown in Table 3. In the first model, dyadic adjustment of each spouse was regressed on both spouses’ positive interactions controlling for marriage duration. In the second model, dyadic adjustment was regressed on spouses’ self-withdraw and in the third model, it was regressed on spouses’ self-demand.

Table 3.

Results of the Actor-Partner Interdependence Model Analyses with Dyadic Adjustment as Outcome.

Predictor	Wife				Husband
Predictor	Estimate	SE	Stand. Est	Power	Estimate	SE	Stand. Est	Power
Model 1
Positive interactions wife	0.636^***	0.095	.470	1.00	0.331^**	0.115	.193	.82
Positive interactions husband	0.255^*	0.102	.176	.70	0.935^***	0.123	.511	1.00
Marital duration	0.019	0.050	.025		0.038	0.059	.040
Model 2
Self-withdraw wife	−0.303*	0.133	−.176	.63	−0.298	0.166	−.137	.63
Self-withdraw husband	−0.084	0.120	−.054	.13	−0.388**	0.150	−.197	.74
Marital duration	0.020	0.058	.027		0.033	0.072	.035
Model 3
Self-demand wife	−0.310**	0.117	−.204	.75	−0.062	0.151	−.032	.04
Self-demand husband	−0.000	0.140	.000	.06	−0.111	0.180	−.048	.09
Marital duration	0.017	0.050	.022		0.034	0.074	.035

Note. Stand. Est. = standardized estimate, SE = standard error. Power = estimated Power.

*p < .05. **p < .01. ***p < .001 (two-tailed).

Actor Effects

In the first model, there were positive and significant actor effects from positive interactions on dyadic adjustment for both husbands and wives. Negative and significant actor effects emerged for self-withdraw and dyadic adjustment in both husbands and wives. In the third model, the actor path from self-demand on dyadic adjustment was negative and significant for wives. No such effect emerged for husbands.

Partner Effects

There were positive partner effects from wives’ and husbands’ positive interactions on their spouses’ dyadic adjustment, indicating that one’s own dyadic adjustment was associated with one’s own as well as with the partner’s positive interactions. In contrast, neither one’s own self-withdraw nor self-demand was associated with the spouse’s dyadic adjustment.

Comparison of Actor and Partner Effects

Comparing husbands’ significant actor effect of self-withdraw with the non-significant partner effect from the wives on husbands’ dyadic adjustment, the results indicated that the actor effect was not significantly stronger in size than the partner effect (χ² (1) = 0.163, p = .686). Comparing wives’ significant actor effect of self-withdraw and self-demand with the non-significant partner effects from the husbands on wives’ dyadic adjustment, the results indicated that the actor effects were not significantly stronger in size than the partner effects (χ² (1) = 1.518, p = .217 for self-withdraw, χ² (1) = 3.045, p = .081 for self-demand).

Comparing husbands’ and wives’ significant actor effects for positive interactions and self-withdraw, the results indicated no gender differences for positive interactions (χ² (1) = 3.198, p = .073) and for self-withdraw (χ² (1) = .180, p = .671). Also, no significant difference emerged for self-demand between husbands’ non-significant actor effect and wives’ significant actor effect (χ² (1) = .902, p = .342).

Dyadic Patterns

Next, we tested for specific dyadic patterns. For husbands’ withdraw, parameter k indicated that the size of the partner effect was about three-quarters of the actor effect, k = 0.769, 95% CI [-0.328, 3.433]. Actor-only patterns were indicated for wives’ self-withdraw (k = 0.277, 95% CI [-0.728, 2.292]) and self-demand (k = 0.001, 95% CI [-1.241, 1.313]). These actor-only patterns were further supported by estimating models with the partner effects fixed to zero (χ² (1) = 0.493, p = .481 for wives’ self-withdraw, χ² (1) = 0.000, p = .998 for wives’ self-demand). For positive interactions, k suggested a pattern that was between an actor-only and a couple pattern (k = 0.401, 95% CI [0.069, 0.897] for husbands and k = 0.354, 95% CI [0.092, 0.757] for wives).

Discussion

Communication is vital for a happy and well-functioning intimate relationship. This is evident by the fact that most couple training, including ENRICH, The Couples Coping Enhancement Training, and the Compassion for Couples Training, include a part on couple communication, which helps to maintain dyadic adjustment (Bodenmann et al., 2001; Bodenmann & Shantinath, 2004; Knutson & Olson, 2003; Ledermann et al., 2007; Mabodi, 2016; Widmer et al., 2005). The present study tested the factor structure and reliability of the Communication Pattern Questionnaire-Short Form (CPQ-SF) and examined the dyadic associations between communication patterns, particularly positive interactions, self-withdraw, self-demand, and dyadic adjustment in a sample of Turkish first-married couples. Although there is good evidence supporting the positive link between positive interactions patterns and dyadic adjustment and the negative link between destructive communication patterns and dyadic adjustment across cultures (Johnson et al., 2005; Siffert & Schwarz, 2010; Zhang & Kline, 2020), this is one the first study that examined the associations between communication patterns and dyadic adjustment among Turkish married couples using the APIM.

The results of the APIM analysis partially support the first hypothesis that one’s own communication behavior is associated with one’s own dyadic adjustment. Specifically, positive associations emerged for both husbands and wives between their own positive interactions and their own dyadic adjustment, while negative association emerged between their own self-withdraw and dyadic adjustment. There was also a negative association between self-demand and dyadic adjustment in wives but not in husbands. The finding that more positive interactions were associated with higher dyadic adjustment is consistent with the findings of Litzinger and Gordon (2005) who examined associations between relationship communication and dyadic adjustment in U.S. couples. This result also corroborates with findings of studies conducted with individuals supporting the positive link between positive interactions and marital quality (Carroll et al., 2013; Perrone & Worthington, 2001).

The finding that self-demand was negatively associated with one’s own dyadic adjustment for wives is consistent with the literature that consistently demonstrated that higher levels of demand/withdraw are linked to lower levels of marital satisfaction (Caughlin & Huston, 2002; Christensen et al., 2006). Our findings highlighted that a more demanding communication pattern is associated with lower dyadic adjustment in wives. It is also in line with findings of a couple study documenting that wives’ demand was negatively associated with their own marital satisfaction (Siffert & Schwart, 2010). Roberts (2000) found that it is more destructive for a relationship when women demand and men withdraw than when men demand and women withdrawal. This is in line with our finding that demanding behavior is associated with lower relationship adjustment in women. For withdraw, the associations did not differ across gender. This difference in the findings may be because we assessed withdrawing and demanding separately and not as a combined measure.

We also hypothesized that substantial associations emerge between partners, but that these effects are smaller in size than the within-partner effects. The results indicated that there were significant partner effects from both husbands’ and wives’ positive interactions on their partners’ dyadic adjustment. This finding is consistent with couple studies that examined the relationship between communication and relationship satisfaction (e.g., Lavner et al., 2016; Ledermann et al., 2010). It also supports the notion of the communication skills-deficit model according to which deficient communication skills lead to relationship distress in couples (Burleson & Denton, 1997; Halford et al., 1990). Chi et al. (2013) studied couples in China and found evidence of an effect from wives’ perceived communication on husbands’ dyadic adjustment but not from husbands to wives.

Although the use of communication patterns as predictor variables and dyadic adjustment as the outcome is in line with previous studies (e.g., Burleson & Denton, 1997; Carroll et al., 2013; Chi et al., 2013; Ebrahimi & Ali Kimiaei, 2014; Hou et al., 2019; Kurdek, 2001; Li & Johnson, 2018; Litzinger & Gordon, 2005; Tan et al., 2017), it is also possible that dyadic adjustment affects relationship communication. A longitudinal study by Lavner et al. (2016) tested this alternative model and found that while comparatively satisfied couples had more positive and less negative communication cross-sectionally, communication skills predicted couples’ relationship satisfaction longitudinally.

Analyses of mean differences revealed that wives and husbands differed significantly on self-withdraw and self-demand, with husbands engaging, on average, in more self-withdraw than wives, and wives displaying, on average, more self-demand than husbands. This corroborates with the findings of Ball et al. (1995), Heavey et al. (1993), and Hou et al. (2019) and the notion that men rarely demand in relationships but tend to withdraw (Siffert & Schwarz, 2010). There is also solid evidence that women demand more in communication than men (Christensen & Heavey, 1990; Christensen et al., 2006). It is worth noting that demand/withdraw are complementary behaviors (Futris et al., 2010), and therefore, one spouse is expected to score high in self-demand while the other spouse is expected to score low in self-withdraw.

No significant differences emerged between wives’ and husbands’ dyadic adjustment and positive interactions. Although some studies reported that women reported higher dyadic adjustment than men (e.g., Berg et al., 2001; Gabriel et al., 2010; Litzinger & Gordon, 2005), other studies did not find gender differences in dyadic adjustment (Gordon & Baucom, 2009; Jackson et al., 2014; Renaud et al., 1997). In line with our findings, there were no gender differences in positive interactions in the couple study of Litzinger and Gordon (2005). It is worth noting that the level of distress in both husbands and wives was low in our study given the average dyadic adjustment and the cutoff of 48 that is used to classify individuals as stressed versus non-stressed in terms of their relationship.

We also tested the factor structure of the Turkish version of the CPQ-SF in couples. The 11-item version yielded a factor solution that was not in line with previous research and was difficult to interpret. Dropping four items, our new alternative version of the Turkish CPQ-SF with 7 items, the CPQ-TR-7, and three latent factors: positive interactions, self-demand, and self-withdraw, which is consistent with the factor structure proposed by Christensen and Heavy (1990, 1993). This solution yielded good internal consistencies that are comparable to those reported in previous studies ranging from .61 to .83 (e.g., Caughlin, 2002; Denton & Burleson, 2007; Futris et al., 2010; Troy et al., 2006). The correlations between self-demand and withdraw and positive interactions were negligible, indicating that these two subscales represent distinct and independent aspects of relationship communication. Taken together, the preliminary psychometric analyses demonstrated that the CPQ-TR-7 could be used to assess different aspects of dyadic communication in Turkish couples.

Strengths and Limitations

This study has various strengths, including the collection of data from 162 married couples, the assessment of the factor structure of the CPQ-TR-7 in a Turkish sample, and the testing of effects within and between spouses in a non-WEIRD (Western, Educated, Industrialized, Rich, Democratic) sample. Despite these strengths, this study also has some limitations. First, the cross-sectional design does not provide insights into the causal relationship between communication patterns and dyadic adjustment and how they relate to one another over time. For example, Richmond (2009) stated that communication may impact people’s satisfaction and people’s satisfaction may impact their communication. Also, the data were collected using self-report measures, which do not provide an objective assessment of the communication patterns. Thus, future studies should combine self-report methods with observational techniques and test associations between communication patterns and dyadic adjustment longitudinally. Second, the convenient sample consisted of first-married heterosexual couples, which controls for the number of marriages but limits the generalizability of the findings to non-married, re-married, and same-sex couples. Furthermore, the data were collected during the COVID-19 pandemic. Most couples spend more time together during that time than usual, which may affect both their communication patterns and dyadic adjustment. Third, although the findings demonstrated substantial relationships between communication patterns and dyadic adjustment, communication is not the only factor that impacts relationship satisfaction (Karney & Bradbury, 1995; Litzinger & Gordon, 2005. Therefore, future research should assess communication patterns in combination with personality characteristics, dyadic processes (e.g., time spent together), and external factors (internal and external stress). Fourth, the power estimates suggest that future studies examining the effect of self-withdraw and self-demand on dyadic adjustment should include larger samples. Lastly, the reliability and factor structure of the CPQ-TR-7 should be replicated and tested in other languages and cultures.

Conclusion

The results of the present study reveal that the more positive interactions a person reports, the higher both partners’ dyadic adjustment, the more a person withdraws, the lower his or her dyadic adjustment, and the more a wife demands the lower her dyadic adjustment. Our similar results with individualistic culture suggested the universality of positive interactions is a key concept to having a better relationship in couples. Also, our findings proved that the CPQ-TR-7 is a valid and reliable instrument to assess partners’ communication patterns in the form of positive interactions, self-demand, and self-withdraw.

Supplemental Material

Supplemental Material - Let’s Talk, Honey: An Analysis of Associations Between Communication Patterns and Dyadic Adjustment in Married Couples

Supplemental Material for Let’s Talk, Honey: An Analysis of Associations Between Communication Patterns and Dyadic Adjustment in Married Couples by Selin Karakose and Thomas Ledermann in Journal of Social and Personal Relationships

Footnotes

Acknowledgement

The authors would like to thank TÜBİTAK – BİDEB 2219 program and all of the couples who participated in this study.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by The Scientific and Technological Research Council of Turkey (TÜBİTAK) under the program BİDEB 2219 - International Post-Doctoral Research Fellowship.

Open research statement

As part of IARR’s encouragement of open research practices, the author(s) have provided the following information: This research was not pre-registered. The data used in the research cannot be publicly shared but are available upon request. The data can be obtained at: skarakose@fsu.edu. The materials used in the research cannot be publicly shared but are available upon request/ The materials can be obtained at: skarakose@fsu.edu

ORCID iDs

Selin Karakose

Thomas Ledermann

Supplemental Material

Supplemental material for this article is available online.

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