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. Author manuscript; available in PMC: 2020 Feb 1.
Published in final edited form as: J Fam Psychol. 2018 Nov 26;33(1):34–43. doi: 10.1037/fam0000476

Parent-Adolescent Conflict and Young Adult Romantic Relationship Negativity: Genetic & Environmental Influences

Giorgia Picci 1, Amanda M Griffin 1,2, David Reiss 3, Jenae M Neiderhiser 4
PMCID: PMC6355366  NIHMSID: NIHMS989894  PMID: 30475004

Abstract

Prior work indicates that aspects of interpersonal relationships are heritable, including negativity within parent-adolescent relationships as well as romantic relationships during adulthood. There have not, however, been systematic studies to disentangle genetic and environmental influences on relationship dynamics with parents as they relate to romantic partner relationship dynamics. Thus, the present study examined genetic and environmental influences on associations between parent-adolescent conflict and young adult reports of negativity with a romantic partner using a longitudinal twin/sibling design. We found that genetic, shared, and nonshared environmental factors contributed to conflict in parent-adolescent relationships and that genetic and nonshared environmental factors uniquely contributed to negativity in the romantic partnership during young adulthood. The longitudinal association between parent-adolescent conflict and romantic relationship conflict was explained entirely by genetic influences shared by the two constructs. These findings have implications for understanding the interpersonal functioning across different relationship types that span multiple developmental periods.

Keywords: Adolescent Development, Behavior Genetics, Parent-Adolescent Relationships, Romantic Relationships, Young Adulthood

Introduction

Conflict in parent-adolescent relationships has been associated with individuals’ functioning within adult romantic relationships (Aloia & Solomon, 2013; Linder, Crick, & Collins, 2002; Surjadi, et al., 2013). Prior findings suggest that conflict with parents during adolescence may be linked to conflict with a romantic partner during emerging adulthood (Aloia & Solomon, 2013). These associations have largely been attributed to exposure to familial conflict (Aloia & Solomon, 2013) and parent-child relationship quality (e.g., communication, warmth, consistency; Linder, et al., 2002; Surjadi, et al., 2013). Specifically, previous literature has attributed romantic relationship styles to parents modeling behavior, which is thought to teach children and adolescents intimacy and communication skills via internalization that can be applied to relationships outside of the home (Bandura, 1977; Johnson & Galambos, 2014; Kim et al., 2014; Kochanska & Kim, 2014; Raudino, Fergusson, & Horwood, 2013; Smokowski, Bacallao, Cotter, & Evans, 2015; White, Johnson, Buyske, 2000). Based on this conceptualization of environmental exposure, adolescents’ expand their nonrelative relationship network (i.e., to peers and romantic partners; Collins, Gleason, & Sesma, 1997) by applying previously learned behaviors and skills from parents to peers and romantic partners.

Another, more nuanced conceptualization of these pathways is the Emotional Security Theory (EST; Davies & Cummings, 1994), which is rooted in attachment theory. EST posits that family conflict poses a threat to children’s feelings of emotional security (Davies & Cummings, 1994, 1998). Studies testing this model have shown that the association between interparental conflict and children’s adjustment is mediated by children’s emotional security (Cummings, Schermerhorn, & Davies, 2006; Davies & Cummings, 1998; Davies, Harold, Goeke-Morey, Cummings, 2002). Though not tested directly in prior work, this model could also be applied to understanding pathways from interpersonal conflict between parents and adolescents and individuals’ functioning within subsequent romantic relationship.

There is also evidence, however, that interpersonal relationships, including parent-child and marital relationships, are influenced by the heritable characteristics of the individuals (e.g., emotional reactivity, internalizing and externalizing behaviors, positive emotionality; see Horwitz & Neiderhiser, 2015 for reviews of this work). Parent-child communication styles are not entirely due to parenting or social learning per se, but rather due also to the effects of genes shared within families (e.g., Harris, 1995; Rowe, 1994; Scarr, 1992). Therefore, an alternative explanation for previous findings that conflict in parent-child relationships relates to later conflict in romantic relationships may be that individuals are demonstrating a communication style that is inherited from parents. To glean whether this finding may be attributable to heritable characteristics and not just mere environmental exposure, employing a genetically-informed design is needed to disentangle the genetic and environmental contributions to relationship dynamics with parents as they relate to romantic partner relationship dynamics. The present study will be one of the first steps in examining the genetic and environmental pathways of these associations.

Genetically Informed Studies of Relationships

There are many studies demonstrating that the dynamics of various interpersonal relationships (i.e., parent-child and spousal relationships) may be influenced by genetic factors (for review, see Chen & Deater-Deckard, 2015). Prior work in this area has shown that both genetic and nonshared environmental factors (i.e., environmental characteristics that are not common to siblings) contribute to adolescent reports of parental warmth and acceptance, while shared (i.e., environmental characteristics common to siblings) and nonshared environmental influences explain the majority of variance for adolescent reports of parental control (Plomin, 1994; Reiss, Neiderhiser, Hetherington, & Plomin, 2000; Rowe, 1983). In addition, adoption study designs have shown heritable contributions to the association between negative parenting behaviors and diminished social competence and psychopathology in children (Elam et al., 2014; Harold, et al., 2013). For example, Harold and colleagues (2013) found that children elicited particular parenting styles based on their inherited characteristics that, in turn, influenced the children’s functioning within peer relationships. Together, this work demonstrates that there is reason to consider both genetic and environmental influences on the dynamics of the parent-child relationship and the ways in which they might change and influence relationships outside of the family of origin across development. In addition, genetically-informed designs point to the notion that characteristics of the parent-adolescent relationship are bidirectional in nature, whereby both parents’ and adolescents’ genetically influenced traits are playing an active role in influencing the dyad’s communication style.

There is also evidence for the importance of genetic influences on romantic partner relationships. Specifically, such studies have consistently found both genetic and environmental influences on romantic relationship quality in adulthood (Spotts, et al., 2004; Spotts, et al., 2005; Spotts, Prescott, & Kendler, 2006; for review, Horwitz & Neiderhiser, 2015), often with near equal influences from genetic and nonshared environmental factors (Horwitz & Neiderhiser, 2011). Some work has shown that genetically influenced characteristics in one spouse influences the marital satisfaction of the other spouse, demonstrating that an individual’s genetically-influenced characteristics can elicit particular behaviors from their romantic partner (Spotts et al., 2004). It is important to note that nonshared environmental influences are consistently found to account for a sizable portion (typically about half) of the total variance in marital quality. This indicates that any experiences that are distinguishable between siblings (e.g., romantic partners, parenting practices) contribute to the perceptions of marital quality (Whisman, et al., under review). Given that both genetic and nonshared environmental influences account for functioning within romantic relationships in adulthood, it is unlikely that social learning in adults’ family of origin is playing a pivotal role in romantic relationship quality. If modeling were a key component of adult romantic relationships, we would expect to see a lasting impact of shared environmental influences on these relationships, which is not the case.

Given that prior work has found genetic influences on interpersonal relationships (both relative and nonrelative), there is reason to believe that the association between behaviors across relationship types is also due in part to shared heritable effects. For example, heritable characteristics of the adolescent may evoke a particular pattern of interactions with both their parents and their romantic partner, perhaps reflecting heritable influences on interpersonal relationships more generally (e.g., Spotts, et al., 2004). This has been demonstrated in at least one report, as common heritable and shared environmental factors (i.e., interparental conflict, sibling relationships, and peer delinquency) influenced the initiation of illicit drug use by young adulthood (Neiderhiser, Marceau, & Reiss, 2013). These findings suggest that interpersonal relationships with family members may have a persistent influence across development and across relationships and that these effects may be accounted for by common heritable or shared environmental influences. Understanding how conflict within these interpersonal relationships may be associated can provide novel insight into whether and how individuals’ develop a “relationship style” across multiple interpersonal relationship types and developmental shifts (e.g., from adolescence to emerging adulthood). In addition, prior work has indicated that shared heritable and non-shared environmental factors are both implicated in pair-bonding behavior, meaning that it is also plausible that conflict within spousal relationships may be at least partially explained by phenotypic assortment and not just partners’ similar background experiences (Horwitz, et al., 2016). More broadly, using a genetically-informed design provides a powerful method to gain understanding into whether and to what extent individuals’ inherited and/or environmentally influenced characteristics underlie outcomes in interpersonal relationships; in so doing, this approach could contribute new insights into the continuities in how individuals function within different types of interpersonal relationships (e.g., parent-adolescent, spousal relationships).

To date, however, there has not been an investigation of how genetic and environmental influences may contribute to the association between parent-adolescent conflict and later conflict with a romantic partner. In the present study, we sought to evaluate the ways in which genetic and environmental influences account for the associations between parent-adolescent conflict and negativity in young adult romantic relationships. Using a twin/sibling design, we estimated the genetic, shared environmental, and nonshared environmental influences within each of these interpersonal relationships and their association, further elucidating the developmental mechanisms that operate on and connect these two crucial relationship types.

Methods

The present study used data from the Nonshared Environment in Adolescent Development (NEAD) study (Neiderhiser, Reiss, & Hetherington, 2007; Reiss, Neiderhiser, Plomin & Hetherington, 2000). NEAD is a longitudinal study consisting of 720 families (256 sibling pairs were included in the current report), including same-sex twin and sibling pairs (< 4 year age difference for the nontwin sibling pairs) assessed during late childhood/early adolescence, later adolescence, and young adulthood. Nontwin sibling pairs with a <4 year age difference were selected to mitigate potential confounds of larger sibling age differences (e.g., differences in household income, resources, parenting). For the present study, data from sibling pairs during adolescence and young adulthood were examined (adolescence: child 1, Mage = 13.5(2.0), range = 10–18; for child 2 Mage = 12.1(1.8), range = 9–18; young adulthood: child 1, Mage = 25.9(2.2), range = 21–31; for child 2 Mage = 24.6(2.1), range = 20–30). Sibling pairs included identical twins (monozygotic (MZ); n = 50 pairs), fraternal twins (dizygotic (DZ); n = 48 pairs), and full siblings (full intact (FI); n = 33 pairs) in non-divorced families. In addition, full siblings (full step (FS); n = 53 pairs), half siblings (half step (HS); n = 34 pairs), and genetically unrelated step-siblings (unrelated step (US); n = 38 pairs) in step families were also included. Twins were rated for physical similarity (e.g., eye and hair color) with interviewer ratings, parent-report, and self-report using a modified version of a zygosity questionnaire for adolescents (Nichols & Bilbro, 1966). If respondents reported that people were never confused about the identity of the twins or if there were any reported differences in physical characteristics of the twins, the twin pair was categorized as dizygotic. Importantly, questionnaire methods used to assign twin zygosity have previously been found to be more than 95% accurate compared to DNA assessments (Nichols & Bilbro, 1966; Spitz et al., 1996).

Participants were primarily Caucasian (94% of mothers and 93% of fathers) and middle class. At Time 1 (in the late 1980s), the median household income ranged from $25,000 to $35,000 and the mothers’ and fathers’ average years of education were 13.6 and 14.0, respectively. Only 7% of mothers and 10% of fathers did not complete their high school education, and 93% of mothers and 90% of fathers completed at least their high school education or more. During young adulthood (late 1990s to early 2000s), approximately 59% of child 1 and 50% child 2 of the sibling pairs were married. The median income of participants ranged from $40,000 to $49,000 for child 1 and $30,000 to $39,000 for child 2. The average years of education were 14.9 and 14.6 for child 1 and child 2, respectively. All procedures were approved by the George Washington University Institutional Review Boards prior to conducting this research.

Attrition Analyses

The data collection from adolescence to young adulthood spanned 7 to 13 years, with over 50% of the families contributing data to the first assessment and the third assessment. To ensure that there were no systematic differences between participants who did and did not participate in the young adult follow-up, we conducted attrition analyses on child and parent age, child sex, family income, and education level as well as other variables we thought might contribute to potential differences in attrition rates (i.e., internalizing and externalizing symptoms; Davis & Addis, 1999; Graaf, Bijl, Smit, Ravelli, & Vollebergh, 2000; Kendall & Sugarman, 1997). There were no systematic differences on any of the demographic or mental health variables between the families who participated in the third assessment compared to those who did not participate in the third assessment (findings available upon request). We also conducted attrition analyses that compared individuals on whether they were or were not in a long-term relationship during the young adulthood assessment on the variables previously mentioned. There were no systematic differences on any of the demographic or mental health variables between the individuals who were in a relationship compared to participants who were not in a relationship during the young adulthood assessment.

Measures

Parent-Adolescent Conflict.

Parent-adolescent conflict was assessed using mother, father, and adolescent reports on the Parent-Child Relationship scale (Hetherington & Clingempeel, 1992; α = .70 – .77), the Child-Rearing Issues questionnaire (Hetherington & Clingempeel, 1992; α = .83– .87), and the Conflict Tactics Scale (Straus, 1979; α = .72– .85). These scales measured frequency and nature of disagreements (i.e., topic) as well as responses to disagreements between the parent and adolescent. For example, items from the Conflict Tactics Scale had participants rate on a 1 to 5 scale of how common or uncommon specific responses to conflict with adolescents or parents (separately) were including: ‘Discussed the issue calmly’, ‘Sulked and/or refused to talk about it’, and ‘Stomped out of the room (or house or yard)’. Responses were collapsed across reporters to create a composite score (i.e., a sum of all reporters; see Reiss et al., 2000 for a detailed description of the composite creation). Table 1 displays the correlations between the raters across the composites and times of assessment. Time 1 and Time 2 composites were combined to create one measure of parent-adolescent conflict.

Table 1.

Phenotypic Correlations, Means, and Standard Deviations by Reporter

1 2 3 4 5 6 M(SD)
Parent-Adolescent Conflict
1. Mother T1 0.31* 0.23* 0.59* 0.28* 0.22* 9.87(2.74)
2. Father T1 0.19* 0.28* 0.59* 0.15* 8.78(2.56)
3. Adolescent T1 0.25* 0.17* Ch-Mom: 8.35(3.12)
Ch-Dad: 7.94(3.12)
4. Mother T2 0.32* 0.26* 9.48(2.51)
5. Father T2 0.21* 8.63(2.48)
6. Adolescent T2 Ch-Mom: 8.45(3.03)
Ch-Dad: 7.94(2.95)
Offspring-Partner Conflict 1 2 3 4
1. Offspring – Criticism T3 0.67* 0.45* 0.49* 16.72(5.66)
2. Partner – Criticism T3 0.38* 0.41* 11.93(4.44)
3. Offspring – Symbolic Agg 0.80*
T3 11.61(5.17)
4. Partner – Symbolic Agg T3 11.48(5.14)
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Notes:

*

p<.01. Includes Adolescent 1 & 2 for each measure.

Romantic Partner Conflict.

Partner negativity was assessed at Time 3 using adult twin/sibling self-report on the criticism of partner and partner’s criticism subscales from Expressed Emotion (EE; Hansson & Jarbin, 1997; α = .81 – .87) and the symbolic aggression to twin/sibling and symbolic aggression of the partner subscales from the Conflict Tactics Scale (CTS; Hansson & Jarbin, 1997; α = .67 – .84). These subscales were then collapsed to create a mean composite score of overall criticism in the relationship. In the CTS symbolic aggression subscales, participants were asked to rate negative behaviors to and from their romantic partners on a scale of 1 to 7 (never to daily). Example items from the CTS included ‘He/she argued heatedly but short of yelling’, ‘He/she stomped out of the room’, and ‘I sulk and/or refused to talk about it’. In the EE criticism subscale, participants were asked to rate negative behaviors to and from their romantic partners on a scale of 1 to 5 (never/almost never to always/almost always). Example items from the EE scale included ‘He/she is unkind (hostile) toward me’, ‘He/she tries to change my behavior or image’, and ‘I must be careful with what I am doing or he/she will put me down’. The majority of respondents were in a relationship (i.e., 90% of those who participated in Time 3 were in a relationship; adult child 1 = 230; adult child 2 = 241). Note, 53 (i.e., adult child 1 = 25; adult child 2 = 28) respondents did not provide responses on these Time 3 questionnaires because they were not in a romantic relationship.

Analytic Plan

This study uses a twin/sibling design to disentangle heritable and environmental influences on each of the study’s constructs and to examine the covariation of influences between the constructs. This type of design decomposes the measured variance into three components: additive genetic influences (A), shared environmental influences (C), and nonshared environmental influences (E) (Knopik, Neiderhiser, DeFries & Plomin, 2017). To partition potential genetic influences, this design takes advantage of the differences in the proportion of segregating genes shared between various sibling types; MZ twins share 100% of their genes, DZ twins, FI and FS siblings share 50% of their genes on average, HS share 25% of their genes on average, and US do not share any genes.

This approach relies on two assumptions: 1) equal environments, and 2) non-assortative mating. The equal environments assumption states that twin and sibling pairs are equally correlated for the environments relevant for the constructs under study. It is important to note that this assumption does not state that the environments are the same but rather that the influence of these environments on the similarity of the twins is not different. The second assumption is that there is no assortative mating (in the parents in our sample) that would contribute to variables examined in our study. Specifically, the assumption is that parents in our sample are not selecting spouses based on non-random, genetically influenced traits examined in the current study (e.g., Luo & Klohnen 2005; Watson et al. 2004; Zietsch et al. 2011), which could lead to over-estimation of shared environmental effects and underestimation of genetic effects. Both of these assumptions have been tested and found valid for a number of phenotypes (Cronk et al., 2002; Kendler, Neale, Kessler, Heath, & Eaves, 1993; Morris-Yates, Andrews, Howie, & Henderson, 1990; Pike, McGuire, Hetherington, Reiss, & Polmin, 1996), including within the NEAD sample (Pike et al., 1996). Relevant to the current study, prior results from the NEAD sample have tested, and found support for, the equal environments assumption for familial negativity (e.g., O’Connor et al., 1996; Pike et al., 1995). Consistent with the EEA, both papers reported that there were no differences across sibling types in divorced and non-divorced families on the basis of parental negativity (O’Connor et al., 1996; Pike et al., 1995).

Prior to analysis, all variables were corrected for adolescent’s age, the adolescent’s sex, and the interaction of the adolescent’s age and sex (McGue & Bouchard, 1984). Analyses were conducted using OpenMx, a structural equation modeling package in “R” (Boker et al., 2011). This program deals with incomplete data (missing at random) using maximum likelihood estimation. Once full model was estimated, model-fitting analyses provided estimates of fit between the assumed model and the observed data, and allowed for hypothesis testing with alternative models (Neale & Cardon, 1992).

First, maximum likelihood model-fitting analyses were used to estimate the contributions of additive genetic (A), shared environmental (C), and nonshared environmental (E) influences by partitioning the variance of each phenotype into these three influences. The fit between the ACE model and the observed data was assessed using Akaike’s Information Criterion (AIC; large and negative AIC indicating a good fit) and −2 log likelihood (−2lnL; large −2lnL indicating a good fit). To establish the best fit for the data, alternative models were tested by systematically dropping paths from the full model. That is, the data were fit to a nested model in which the phenotypic variance was accounted for by A and E, or C and E, as compared with the full model including A, C, and E. The nested and full models were compared using the likelihood ratio test (Neale & Cardon, 1992) and the relative improvement or worsening of the fit relative to the change in degrees of freedom.

To examine the genetic and environmental contributions to the covariation between the parent-adolescent conflict and young adult romantic relationship negativity, a Cholesky decomposition was used (see Figure 1). Thus, there are two potential sources of genetic, shared environmental, and nonshared environmental variance in a Cholesky model: 1) the association between constructs (referred to hereafter as common A, C, and E pathways), and 2) those unique to each construct (residual A, C, and E).

Figure 1.

Figure 1.

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Paths for Unique A, C, and E Influences and Covariance Between Parent-Adolescent Conflict and Romantic Relationship Negativity</p/>Notes: a = additive genetic effects, c = shared environmental effects, e = nonshared environmental effect. In parentheses, 95% confidence intervals (CIs) are presented below each parameter estimate. Akaike’s Information Criterion (AIC) = 3414.68, −2 log likelihood (−2lL)= 7220.68, degrees of freedom (df) = 1903.

Results

The results are presented in three parts. First, the univariate genetic and environmental estimates of parent-adolescent conflict and young adult romantic relationship negativity are described. Second, the bivariate intraclass correlations and results of the bivariate Cholesky decomposition of parent-adolescent conflict and young adult romantic relationship negativity are provided.

Univariate Results

Genetic, shared environmental, and nonshared environmental parameter estimates were obtained by fitting ACE models using maximum-likelihood estimates with 95% confidence intervals (see Table 2). Confidence intervals and fit indices indicated that of the initial models examined (ACE, CE, AE), the ACE model provided the best fit for parent-adolescent conflict and the AE model provided the best fit for romantic relationship negativity. Heritable influences on parent-adolescent conflict accounted for 62% of the variance, with the remaining 25% and 13% accounted for by shared environmental and nonshared environmental effects, respectively (–2lnL = 4287.22, df = 1410, AIC = 1467.22). For romantic relationship negativity, the ACE model indicated the shared environmental influence was estimated at zero and confidence intervals included zero (95% CI [−.02, 25]) indicating the path should be dropped (−2lnL = 2979.93, df = 494, AIC = 1989.93). The change in model fit between the ACE and AE model was not significant indicating that dropping shared environmental influences did not result in a reduction in fit (−2lnL = 2979.92, df = 494, AIC = 1991.92; Δ–2lnL = 0.01, Δdf = 1, ns). The majority of variance in romantic relationship negativity was due to nonshared environmental influences (66%) with the remaining 21% of variance due to heritable influences.

Table 2.

Proportion of Variance in Each Phenotype; Univariate Results

Parameter Estimates Fit Indices
Trait a2 c2 e2 −2LL df AIC BIC
Parent-Adolescent Conflict 0.62 0.25 0.13 4287.22 1410 1467.22 −4966
  CI (.52, .72) (.16, .33) (.09, .18)
Romantic Negativity 0.21 – 0.66 2979.93 495 1989.93 −268
  CI (.08, .48) (.49, .89)
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Notes: a = additive genetic effects, c = shared environmental effects, e = nonshared environmental effect, df = degress of freedom, AIC = Akaike’s Information Criterion, and −2lnL = −2 log likelihood. In parentheses 95% confidence intervals (CIs) are presented below each parameter estimate. A parameter estimate is considered significant if its CI does not overlap with zero.

Bivariate Results

Phenotypic correlations were computed for parent-adolescent conflict and subsequent romantic partner negativity (r = .31, p = .000). A bivariate Cholesky decomposition was fit to distinguish between heritable and environmental contributions to the covariance between parent-adolescent conflict and romantic relationship negativity and to estimate the unique heritable and environmental contributions to romantic relationship negativity. A series of nested models were fit by dropping parameters and comparing nested models to the full model to determine if a more parsimonious model could be obtained. Fit statistics for nested models are presented in Table 3. Dropping the unique and common shared environmental paths provided a better fit to the data than the full model (–2lnL = 7220.68, df = 1903, AIC = 3074.36; Δ–2lnL = 3.71, Δdf = 2, ns). This is not surprising based on the univariate AE model that was fit to romantic relationship negativity. Results suggest that heritable influences on parent-adolescent conflict account for most of the variance shared with subsequent romantic partner negativity (common A = 10%). This common path indicates that 80% of the covariation in parent-adolescent conflict and romantic partner negativity was explained by heritable influences. In contrast, neither shared nor nonshared environmental variance contributed to the covariation of parent-adolescent conflict and romantic relationship negativity (see Figure 1). There were also unique heritable influences (62%), shared environmental influences (25%), and nonshared environmental influences (13%) on parent-adolescent conflict. Not all of the heritable variance on romantic partner negativity was due to variance shared with parent-adolescent conflict. There were both unique heritable influences (21%) and nonshared environmental influences (66%) on romantic partner negativity after accounting for variance shared with parent-adolescent conflict.

Table 3.

Fit Statistics for Nested Models, Relative to the Full Model

Model −2lnL df Adf AIC
Full 7216.97 1901 3414.97
Drop unique c22 7216.97 1902 1 3412.97
Drop unique c22 and common c21 7220.68 1903 2 3074.36
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Notes: −2lnL = twice the negative log-likelihood of the data, df= degrees of freedom, and AIC = Akaike’s Information Criterion.

Discussion

This study employed a longitudinal genetically informed design to examine how heritable and environmental influences contribute to the association between adolescents’ conflict with their parents and negativity in their romantic partnerships in young adulthood. We sought to understand the extent to which unique and common pathways accounted for conflict within and between these two interpersonal relationships (i.e., parent-adolescent, romantic relationships) that are paramount to development and adaptive functioning. We report three main findings: 1) the majority of the variance in romantic relationship negativity in young adulthood is explained by nonshared environmental factors; 2) there are unique heritable influences on parent-adolescent conflict and negativity in the romantic relationship in young adulthood; 3) the association between parent-adolescent conflict and romantic relationship negativity during young adulthood is entirely explained by heritable influences of the young adult.

Results from this study parallel and expand upon previous developmental findings indicating that parent-adolescent conflict is associated with an increase in negativity within the romantic relationship in young adulthood (Aloia & Solomon, 2013; Linder, Crick, & Collins, 2002; Surjadi, et al., 2013). To build on this consistent finding, we accounted for heritable influences on the development of these relationships, which is nearly unprecedented in prior work. Developmental studies have tended to assume that the association between parent-adolescent conflict and negativity in romantic partnerships is due to social learning within the family of origin (i.e., environmental exposure to negativity) (Aloia & Solomon, 2013; Linder, Crick, & Collins, 2002; Surjadi, et al., 2013).

The findings were able to expand upon previous research by using an extended twin/sibling design, which allowed us to estimate the full spectrum of genetic relatedness (from twins who share 100% of their genes to step-siblings who share no genes). This study is novel in that it uses multi-informant constructs of parent-adolescent conflict and romantic relationship negativity by including mother, father, adolescent, as well as young adult self- and romantic partner report, respectively. In contrast, prior genetically informed studies on romantic relationships have typically focused on examining self- and partner-report (Spotts, et al., 2005; Spotts et al., 2006) of the relationship and have not examined longitudinal associations between parent-adolescent and romantic partnerships as we sought to do here.

In contrast to this prevailing explanation, our findings do not demonstrate that adolescents transfer their communication styles developed in their family of origin to romantic partnerships later in young adulthood on the basis of modeling internalized representations alone. The reason for this is two-fold. First, we found heritable influences on parent-adolescent conflict, a relationship that is thought to result in adolescents internalizing maladaptive relationships pattern. Second, we also found that the association between parent-adolescent conflict and negativity in romantic partnerships in young adulthood was exclusively explained by heritable influences. We interpret this to indicate that environmental factors, such as parents modeling negative behaviors, do not explain negative interaction styles within these relationships and their associations across development from adolescence to young adulthood.

Pathways to Parent-Adolescent Conflict

Results from the present investigation indicate that heritable, shared, and nonshared environmental influences contribute to parent-adolescent conflict. In other words, influences endogenous to the adolescent (e.g., heritable traits) seem to be most impactful in explaining conflict within the parent-adolescent relationship. Previous genetically informed designs have demonstrated heritable and environmental influences in the quality of these relationships, including the extent to which they are antagonistic (Burt, McGue, Krueger, & Iacono, 2005; Elkins, McGue, & Iacono, 1997; for review, see Chen & Deater-Decker, 2015). Previous work has suggested that adolescents’ perceptions of their relationships with their parents may be attributable to either passive rGE, evocative rGE, or both (e.g., Neiderhiser, et al., 2004). An evocative rGE may be operating in the current study, whereby adolescents are eliciting a particular (in this case, conflictual) response from parents based on their heritable characteristics. Prior work has demonstrated that as adolescents become more autonomous, evocative rGE effects become more prominent in family systems (Elkins, et al., 1997; South, Krueger, Johnson, & Iacono, 2008). In the current study, this notion is further bolstered by our finding that to the extent that there is an association between negativity in both parent-adolescent and young adult romantic relationships, it is explained by genetic contributions. Therefore, it may be the case that participants continued to elicit negative interactions with romantic partners in young adulthood on the basis of their heritable characteristics.

In this study we found that shared environmental influences contribute to parent-adolescent conflict more than nonshared environmental influences (e.g., relationships outside of family and activities that are unique to each sibling). This finding is consistent with prior work on parent-adolescent relationships, including reports from the NEAD sample (Klahr, McGue, Iacono, & Burt, 2011; Klahr, Rueter, McGue, Iacono, & Burt, 2011; Neiderhiser, et al., 2004; Reiss, et al., 2000). Prior work has indicated that environments can differ dramatically between adolescent twins/siblings in the same family (Deater-Deckard, 2009; Neiderhiser, et al., 2007), which may diminish the role of shared environmental influences on parent-adolescent conflict. However, we did not find that this is the case in our study; nonshared environmental influences only accounted for 13% of the variance in parent-adolescent conflict. By including both twin and sibling pairs in this design, we were able to incorporate siblings with varying levels of genetic relatedness (from 100% genetic relatedness in MZ twins to 0% in unrelated step siblings), which allowed us to uniquely estimate shared environmental influences. For this reason, we may have achieved a more accurate estimate of the influence of shared environmental factors on the parent-adolescent relationship, as has previously been demonstrated in the NEAD sample (e.g., Feinberg, Button, & Neiderhiser, 2007; Neiderhiser, et al., 2004).

Pathways to Romantic Relationship Negativity in Young Adulthood

Romantic relationship negativity during young adulthood was primarily influenced by nonshared environmental factors with some heritable influences. This finding is consistent with the notion that as siblings develop and transition into more autonomous adult social roles, they may become less similar; also, pertinent to the current study, they have different romantic partners, which contributes to nonshared environmental factors. Moreover, the shared environment in young adulthood is the shared environment from the family of origin, which young adults are likely less involved in as they gain more independence from parents. As a result, shared environmental influences are likely not as important in explaining similarity in behaviors of siblings in their romantic relationships during young adulthood and beyond. Nonshared environmental influences include experiences with the romantic partner, relationships with other family members, friends, acquaintances, and work colleagues. Our findings are consistent with previous studies on spousal relationships (Spotts, et al., 2004) that have found substantial nonshared environmental contributions to perceptions of relationship dynamics (i.e., both positive and negative aspects of the partnership).

Heritable Influences Across Relationships

The covariation between parent-adolescent conflict and young adult romantic partner negativity was explained solely by heritable influences with no evidence of shared or nonshared environmental contributions. These findings suggest that previous literature that has reported on the associations between parent-adolescent conflict and later functioning in romantic partnerships may be overestimating the environmental contributions to these constructs. Though, it will also be important for future studies to examine the robustness of these associations in higher-risk samples than the present study. As previously mentioned, it may be the case that this association is due to evocative rGE whereby the same heritable characteristics of the individual are eliciting conflict from parents during adolescence and negativity with romantic partners during young adulthood. For instance, it is plausible that there are some child-specific temperamental factors that lead to continuity in eliciting negative responses across different relationship types. Alternatively, it is also possible that individuals choose partners that will allow them to carry out similar patterns of negativity for heritable reasons, suggesting that active rGE may be involved. Previous work has shown that heritable characteristics may play an important role in mate selection and pair-bonding behaviors (Horwitz, et al., 2016). In other words, it is plausible that individuals are seeking partners with similar heritable characteristics as their own, which may support the continuation of heritable behaviors (e.g., a propensity for negative interactions).

Limitations

There are several limitations that must be considered when interpreting our results. First, it is important to acknowledge that there was attrition of participants in our sample across time (see Table 2). This concern is attenuated, in part, as there were no systematic differences in any of the demographic or mental health constructs examined for a) families who participated in the third assessment compared to those who did not, and b) individuals who were in a relationship compared to participants who were not in a relationship during young adulthood. Nonetheless, the resulting young adult sample size is modest by the current standards of twin studies likely resulting in larger confidence intervals for the parameter estimates.

Though the present study focused on relationships during young adulthood, prior work has focused on married or cohabitating couples. Though, our findings may be consistent with and applicable to prior work because some of our participants (i.e., 59% of older siblings and 50% of younger siblings) are married. It is unclear whether and to what extent the status of the romantic partnership (e.g., dating, cohabitating, or married) contributes to the associations we observed. The present study does not have adequate power to examine how relationship status may influence our results. Future work using genetically informed designs should examine whether different types of relationships vary for genetic and environmental influences on relationship quality. For instance, it may be the case that the duration and seriousness of the romantic relationship is important to consider. It is notable, though, that we asked our participants to only report on serious, committed relationships.

It is also important to acknowledge the possible role of assortative mating when interpreting these findings because we have included both romantic partner report and twin/sibling reports (Horwitz, et al., 2016; Spotts, et al., 2004; Watson, et al., 2004). Two processes may be at work to influence assortative mating. First, it is plausible that individuals choose partners possessing similar social backgrounds, which may contribute to a particular relational style (e.g., negative interactions). Second, it may be the case individuals choose romantic partners who have similar heritable characteristics, such as a proclivity for interpersonal conflict. Prior work demonstrates support for the latter explanation, indicating that mate selection and pair-bonding behaviors are largely influenced by heritable characteristics, and not social background characteristics (Horwitz, et al., 2016).

Two non-mutually exclusive limitations that must be discussed are the use of self-report measures and how results may vary depending upon which rater report is used in family relationships research. First, the use and predictive validity of self-report measures, particularly for psychological phenomena, have been subject to criticism (Shrauger & Osberg, 1981). For example, some have speculated that social desirability bias, or individuals’ penchant for depicting themselves in more a favorable light, may taint survey-based research (van de Mortel, 2008). However, it is difficult and expensive to obtain more “objective” reporting about family and romantic relationships beyond survey measures, without using observational measures. In research addressing similar topics as the present study, it has been shown that the role of rGE in the parent-adolescent relationship may differ as a function of the informant (i.e., adolescent, mother, father, or observation) (for review, see Chen & Deater-Deckard, 2015). Thus, it is important to acknowledge that the results of this study may have differed had we employed observational report. This concern is attenuated by the use of multiple-raters in this study. Moreover, the adolescent, mother, and father reports that contributed to our parent-adolescent conflict construct (and the self and partner report in young adulthood) all correlated with each other.

Finally, the present study only examined the negative aspects of the parent-adolescent and romantic relationships without considering positive aspects. We cannot assume that individuals in these relationships who participated in our study experienced conflict in the absence of warmth and positivity. In other words, given that this study did not over-sample individuals from atypical rearing environments, it is likely that they experienced normative levels of positivity and negativity within their relationships. In this way, we are demonstrating processes of normative development that may not generalize to more atypical trajectories. The present study does help to clarify how genetic and environmental pathways may explain why individuals from high-conflict families choose romantic partners with whom they have similar levels of conflict (e.g., Cui, Fincham, & Pasley, 2008). Future work using genetically informed designs should explore these associations in individuals who experience adverse rearing environments and/or atypical caregiving (e.g., maltreatment).

In addition, we did not include other family context variables that could potentially impact the associations between parent-adolescent and romantic relationships that individuals have later in development. For example, though outside of the scope of this study, we did not incorporate parent’s marital conflict, which has been shown to influence parenting quality (Krishnakumar & Buehler, 2000) and child adjustment (Davies, et al., 2002). It would be advantageous for future work to explore the contributions of these variables. For example, from an Emotional Security Theory perspective, it would be valuable to investigate potential genetic and environmental contributions to the association between parent-adolescent conflict and adolescent emotional security, and subsequent functioning within later romantic relationships.

Conclusions

Findings from the present study suggest that there are important differences in the heritable and environmental contributions to parent-adolescent conflict and romantic partnership negativity in young adulthood. Our findings showing that the longitudinal association between parent-adolescent conflict and romantic partnership negativity in young adulthood is entirely genetic suggests that there may be an evocative rGE. That is, there may be characteristics endogenous to the individual that elicit particular responses from both parents and romantic partners at different developmental periods. These findings reveal the importance of disentangling the genetic and environmental contributions to functioning in these interpersonal relationships in order to better understand their developmental trajectories. This work has relevance for thinking about both normative and maladaptive development of conflict within the parent-child relationship and how heritable and environmental factors underlie conflict in other kinds of relationships that span different developmental periods.

Acknowledgments

This report is part of the Nonshared Environment in Adolescent Development project. Time 1 and Time 2 data collection was supported by the National Institute of Mental Health (5R01MH43373, 5RO1MH48825) and the William T. Grant Foundation. Time 3 data collection was supported by the National Institute of Mental Health (5R01MH059014). The first author’s work was supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE1255832. The second author’s work on this manuscript was support by the Kligman Dissertation Fellowship and a National Science Foundation grant (F32 FHD093347A). Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the National Science Foundation. Finally, we are grateful to the participants, without whom this work would not have been possible.

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