When one plus one equals three: Early parenting as a dyadic process
How an individual experiences the transition to parenthood, adapts during the perinatal period, and engages in parenting in early childhood are critical predictors of child emotional, psychological, and social development (e.g., Pinquart, 2017; Richter et al., 2022). Mothers and co-parents - here referred to as “fathers” in line with most prior research, though we later address more diverse family forms - may experience the transition to and the time of early parenthood (i.e., the birth of the child and the first few years as a parent) in similar ways, or in strikingly different ones. To illustrate, imagine a family where one parent is relatively structured and emphasizes close guidance whereas the other parent is non-directive and encourages the child to explore the world. The discrepancy between parents’ personalities might lead to interparental tension when the more structured parent objects to too much freedom granted to the child and the other parent might perceive the emphasis on routines and boundaries overly restrictive. The first few years after the birth of the child are especially relevant in that regard as two partners’ behaviors, expectations, and needs in this new situation might clash and affect effective functioning as a family. In brief, it is not only either parent’s isolated effect on the child that can affect development but also the interplay within the parental dyad. We argue that this dyadic interplay needs to be considered in statistical analyses in family research.
Our argument that the interplay between parents affects child development above and beyond the individual contributions of each parent is influenced by family systems theories (e.g., Bowen, 1993) which commonly emphasize that systems within families are not independent of each other, and that, for instance, the interparental system affects the separate parent-child systems and by extension child development (Cox & Paley, 1997). Testing assumptions from family systems theory requires suitable data, namely from both parents, and statistical approaches that go beyond examining the predictive power of only one parent’s traits on child development. Fortunately, after decades of collecting data on the transition to parenthood, parenting, and early child development nearly exclusively from mothers, an emerging body of research now also focuses on the fathers’ traits, behaviors, and experiences of the transition to parenthood, and the effect of those factors on child development. Ideally, information from both parents is available. Such dyadic data, i.e., data of meaningfully connected individuals who share an intense social relationship and therefore influence each other, do not meet the commonly required statistical assumption of independence of data points and must therefore be analyzed using appropriate statistical methods. We discuss such methods here.
Recent methodological developments allow researchers to compare maternal and paternal parenting and both parents’ relationships to the child and test whether congruent, complementary, or compensatory patterns result in different patterns of child development. For instance, specific modelling techniques based on dyadic data allow us to rigorously test for moderation, i.e., buffering or exacerbating mechanisms where, for instance, a lack of sensitivity of one parent toward the child is ameliorated by the other parent’s sensitivity. As such, family and child development research can now conceptualize both parents’ traits, experiences, parenting practices and relationship with the other parent and with the child as antecedents of individual differences in child development and utilize appropriate statistical techniques. Dyadic models in which information from both parents are included and where the interplay between parents’ traits and behaviors is explicitly statistically modeled, recognize parents’ experiences and behaviors as mutually influential and inform about how parents together shape early child development.
That said, despite the theoretical backing and methodological possibilities, actual dyadic research in the field of early parenting and child development is still scarce. We hope to change this by 1) highlighting recent work, 2) describing suitable statistical methods, and 3) providing suggestions for future research. In doing so, we focus on co-parenting as example of research based on family systems principles where use of dyadic data is common. Moreover, co-parenting constitutes a novel challenge of collaboration and compromise (at least when the couple has not had previous children) at a time when parental influence on child development is particularly important. Co-parenting in the first few years of the child’s life thus is an aspect in family research that deserves particular substantive attention in combination with rigorous methodological approaches.
Dyadic data in co-parenting research
As argued by perinatal mental health researchers, dyadically-oriented studies improve our understanding of how interparental similarities and differences in traits, adjustment to the transition to parenthood, and parenting affect child health and development (Bergunde et al., 2024; Garthus-Niegel et al., 2021; Seefeld et al., 2022). Within developmental psychology, dyadic data and methods have mostly been limited to the study of mother-child interactions. However, dyadic data of both parents to study parents’ impact on child development have been used less systematically, despite their value for understanding child psychological, emotional, and social development in the family context. That said, co-parenting research constitutes an avenue where variation in the interparental interplay is of substantive interest as predictor of child outcomes and where data from mothers and fathers are routinely collected.
For instance, in a study on nearly 2000 ethnically diverse families in the US, co-parenting, conceptualized as individual perceptions of cooperation and mutual support and modeled as separate latent variables was associated with parental mental health and child adjustment, such that fathers were at greater risk for depression and anxiety in families where mothers were less satisfied with the co-parenting. Children in these families were more likely to exhibit internalizing and externalizing problems (Yang et al., 2023). In large British and US American studies, co-parenting in early childhood was examined as predictor of offspring externalizing problems later on, alongside both parents’ individual parenting behaviors (Parkes et al., 2019). In both samples, co-parenting, conceptualized as averages of both parents’ reports on agreement over parenting, exerted an independent effect on offspring externalizing problems, as well as on individual parent’s conflict and closeness with the child in the British data and on maternal harsh discipline and paternal involvement with the child in the US data. A US study on 452 couples who were unmarried and expecting a child at the beginning of data collection showed that co-parenting at 15 months child age, conceptualized as individual perceptions of parental alliance and included in analyses as common latent variable reflecting both parents’ scores, predicted maternal and paternal responsive parenting and child prosocial behavior at age 3 (Lee et al., 2021). Finally, in a study of 856 US families, co-parenting trajectories over time, modeled as averages of both parents’ perceptions of interparental coordination, communication, trust, support, and respect at ages 1, 3, and 5 were associated with child development outcomes such that variation in how co-parenting developed across the first five years after the child had been born predicted variation in child behavior problems later on (Park et al., 2025).
Despite the value of this work for emphasizing the importance of including more than one parent in family studies and for understanding how dynamics in the interparental system affect child outcomes, research was conducted in Western samples with traditional families consisting of mothers and fathers as parents and many measures assessed only once, even in longitudinal studies, so no actual modelling of development over time was possible. Finally, not all studies have modelled dyadic data in the statistically most suitable way. Whereas some studies included both mothers’ and fathers’ reports into the model separately (Lee et al., 2021; Yang et al., 2023), others used averages of both or created latent variables based on the two indicators (Park et al., 2025; Parkes et al., 2019), which may be suitable for studies looking at constructs at the couple-level. To zoom in on the interplay between both parents’ traits, perceptions, and behaviors, i.e., to model moderating or mediating dynamics or co-development, however, specific techniques are available.
Statistical strategies for analyzing dyadic data
We present five statistical dyadic frameworks, which enable researchers to capture relational complexities central to child development, shifting the focus toward a deeper understanding of relational processes: the Actor Partner Interdependence Model (APIM), the Actor Partner Interdependence Mediation Model (APIMeM), the Actor Partner Interdependence Moderation Model (APIMoM), the Dyadic Growth Curve Model (DGCM), and Dyadic Response Surface Analysis (DRSA).
The Actor Partner Interdependence Model (Kenny, 1996) was specifically developed for analyzing dyadic data and quantifies how each partner’s attributes shape both their own and the other’s outcomes. Actor Partner Interdependence Models account for both intraindividual effects (actor effects), such as how a mother’s stress level influences her perception of her own co-parenting abilities, and interindividual effects (partner effects), such as how a father’s stress level affects the mother’s perception of her own co-parenting abilities. Unlike traditional multiple regression models, which may treat the father’s stress as merely a covariate in predicting the mother’s parenting confidence, Actor Partner Interdependence Models explicitly calculate the bidirectional influences between partners and offer a clearer understanding of the mutual interdependence within the parental dyad and the relational dynamics that shape early parenthood. Actor Partner Interdependence Models have shown that for both mothers and fathers, higher own marital satisfaction predicted higher own parent-child relationship quality (actor effects), while also enhancing the partner’s parent-child relationship quality (partner effects) (Peltz et al., 2018). From the realm of co-parenting research, we have learned from Actor Partner Interdependence Models that mothers’ and fathers’ parenting stress predicted their partner’s perception of co-parenting (Liu et al., 2025).
Extending the possibilities offered by the Actor Partner Interdependence Model, the Actor Partner Interdependence Mediation Model (Ledermann et al., 2011) can be used to test explanatory mechanisms between variables. As such, these models clarify through which mechanisms these effects operate, and under which conditions they strengthen or weaken. For example, the link between higher own marital satisfaction and partner’s parent-child relationship quality was actually mediated by co-parenting cooperation (Peltz et al., 2018). That is, fathers’ co-parenting cooperation played a key role in explaining the association between both parents’ higher marital satisfaction and higher father-child relationship quality. As such, greater marital satisfaction in both parents may particularly strengthen the father’s cooperative parenting, which in turn enhances the father-child relationship. Given that third variables such as child temperament, parental stress, or socioeconomic status might buffer or exacerbate actor and partner effects, the Actor-Partner Interdependence Moderation Model (Garcia et al., 2015) offers a suitable framework to test such interaction effects.
Another scenario may be that researchers would like to analyze how partners’ developmental trajectories evolve together across time or how explore the trajectory of child development through a dyadic lens. Depending on how involved parents are with their child’s upbringing, they might have differing views on their child’s developmental status, specifically regarding its social-emotional skills. Therefore, it may be of interest to examine both parents’ perceptions of their child’s social-emotional development over time and whether these interdependent trajectories are predicted by parents’ involvement with the child. Research questions like this can be analyzed using Dyadic Growth Curve Models (Kashy et al., 2008; Kashy & Donnellan, 2011), which extend individual growth curve modelling by accounting for parents’ interdependence.
Finally, Dyadic Response Surface Analysis explicitly examines how the similarity or mismatch between partners shapes child outcomes. For example, (Buyukcan-Tetik et al., 2024) investigated whether a discrepancy in birth expectations between mothers and their birth companions was associated with post-traumatic stress symptoms after childbirth. Dyadic Response Surface Analysis (Schönbrodt et al., 2018) provides a powerful tool for addressing such similarity questions. This approach captures both parents’ individual contributions and their interaction, overcoming the limitations of traditional approaches such as difference scores (Edwards & Parry, 1993). A key advantage of dyadic response surface analysis is its ability to test and compare nuanced effect patterns and to visualize them in a three-dimensional
plot.
Taken together, these frameworks provide answers to fundamental dyadic questions in child development research: who influences whom, through which mechanisms, under which conditions or for whom effects hold, how dyads change together over time, what constructs are inherently dyadic rather than individual, and how congruence or mismatch between partners matters. Of course, researchers should use the analytic methods that best answer their research questions. Adherence to methodological standards and reporting guidelines are already critical for ensuring the rigor and reproducibility of research using dyadic data. As the field continues to grow and the use of dyadic designs in parenting research becomes more widespread, maintaining and advancing these standards will be essential to support comparability across studies and facilitate future meta-analyses. Future work should also prioritize specificity in analytic approaches, clear justification for dyadic frameworks, and transparent reporting of interdependence and role distinctions within parent pairs.
Recommendations for future research
So far, we have discussed a selection of existing studies and introduced methodological approaches to analyzing dyadic data. Based on the characteristics of previous research on family dynamics in the field of child development studies and our proposed statistical strategies, we have five recommendations for future research.
1.
Examine associations between dyadic processes between parents and child development over time
Existing research with dyadic data in co-parenting does not always extend to child outcomes (Durtschi et al., 2017; Estlein & Shai, 2024), or when included, child outcomes are assessed once, with little possibility to truly model continuity and change over time (Lee et al., 2021). This means that the influence of couple dynamics on developmental trajectories of child development has so far been largely overlooked. Key research questions that could be answered with longitudinal child data include: Are there specific developmental windows when dyadic interactions exert a particularly strong influence on children’s social and emotional capabilities? Can targeted interventions improve parents’ dyadic functioning and, in turn, change the course of child developmental outcomes? What mechanisms drive such effects? Related to this, evaluating the role of critical life events—such as relocation, variations in parental employment, parental job loss, severe illness, or the birth of siblings—would shed light on how such transitions shape children’s emotional, social, and cognitive development over time.
2.
Broaden assessment methods to include parent-child observations and utilize technological advances
As in most family research, the child’s perspective should be integrated by using developmentally appropriate assessment methods. Relying solely on parent-reported measures of child behaviour can not only introduce subjective bias but also increases the risk of shared method variance when the same parent reports on couple functioning, parenting quality, and child outcomes. To mitigate this, behavioural observations, teacher or caregiver reports, and physiological or neuro-developmental indicators can provide a more reliable and multifaceted understanding of the child’s experience.
Longitudinal dyadic or triadic designs that are partially based on observations demand substantial resources especially in terms of observational coding and repeated assessments, but emerging technologies may help offset this burden. For example, wearable sensors to track physiological synchrony or smartphone data can enhance both the scalability and ecological validity of resource-intensive family studies. Future research should explore how these tools can be integrated with robust dyadic models to capture interparental processes and to understand how these dynamics affect and are affected by child development across time. Finally, observational studies might benefit from further development of AI-based models trained for data management (e.g., transcription of data) and data analysis (e.g., supporting the analysis of dialogues or bodily movements or gaze during interaction). Machine learning applications can be used for coding which tends to be one of the most time-consuming tasks in observational research.
3.
Account for diversity in family forms
Early on, we noted that we would write about “fathers” but return to the question of diversity in family forms in the discussion. Although, especially in recent years, family psychology research begins to represent the diversity of family forms that we increasingly find in society, most studies that involve two parents focus on fathers. We hope that future work will be broader and explore dyadic effects for other parents than just fathers. Investigating parental gender roles, societal gender expectations, and the gender-associated expectations of the dyad, particularly within same-sex parenting and non-binary caregiver contexts, would further enhance our understanding of how these factors influence dyadic interactions and subsequent child outcomes.
4.
Account for diversity in caregivers
Of course, diversity in family forms goes further than the gender of parents and future studies should incorporate diverse caregiving figures beyond the predominantly Western dyadic model. This could involve intergenerational analyses that recognize the roles of grandparents or other family members, as well as studies of separated couples (due to relationship dissolution or geographic distance related to employment) and intentional co-parenting arrangements formed outside of romantic partnerships. Much of the research on co-parenting has taken place in the US and despite ethnic and socioeconomic diversity in samples, findings can likely not be generalized to families in other areas of the world. Cross-cultural research would not only inform about associations between interparental dynamics and child outcomes elsewhere but it could also show how cultural norms moderate such links.
5.
Explore the role of the digital context for parenting
Finally, although digital contexts are becoming ever more pervasive, their effects on dyadic processes and child outcomes remain insufficiently understood and warrant further study. Future work could, for instance, systematically assess technological influences on family dynamics and developmental trajectories through an explicitly dyadic lens. The duration and manner with which each parent cultivates an online presence (e.g., one parent being very active on social media while the other parent shuns it) may become a novel arena of concordance or divergence, shaping co-parenting quality, conflict spill-over, and the coherence of behavioural signals that reach the child. To zoom in on these dynamics, researchers should measure not only the absolute screen time but also cross-parent synchrony or mismatch in digital practices, because asymmetric engagement can erode collaborative decision-making and increase triangulation pressure on the child.
Naturally, dyadic data analysis requires increased efforts to recruit both parents (and their children, if we are interested in how dyadic processes affect child development), complex statistical modeling, and the need for large samples to ensure sufficient statistical power. However, these challenges are outweighed by the advantages of capturing the highly interdependent behaviors that mark family life in early childhood – dynamics that single-source data cannot fully represent. Child development research using dyadic data should build on open science initiatives such as the Many Babies program (https://manybabies.org) and learn from other disciplines in how to harmonize and pool data to join forces in bringing progress to the field. We believe that increased efforts are worth it, because by adopting a dyadic perspective, researchers can gain a more holistic, more system-level understanding of the most formative period in life.
Ethics and consent
Ethical approval and consent were not required.
