Coparenting Dimensions and Preschooler Outcomes: A Network Analysis in Only-Child and Multi-Child Families

doi:10.21203/rs.3.rs-8510680/v1

Coparenting behaviours predict various child outcomes, yet the specific dimensions that are most influential remain unclear, presenting challenges for the development of intervention strategies. This study used network analysis to map the interconnectedness of coparenting dimensions (integrity, disparagement, conflict, and reprimand) and preschool child outcomes, aiming to identify coparenting behaviours that are closely related to child problems. A total of 752 Chinese parents of preschool children (M_age = 4.76 ± 0.89) reported both their coparenting behaviours and their children’s strengths and challenges. We estimated the relative importance of each node in this network and found that maternal integrity, disparagement and conflict were the most influential nodes, with disparagement showing comparatively lower bridging centrality. Child problems in the emotional and conduct aspects were found to be more centralized within the coparenting network than problems in the social or attention aspects were. Network connectivity remained consistent across birth order, although maternal disparagement was more closely associated with emotional symptoms in Children in Multi-Child Families (p < .01). The results indicate the comparable significance of negative and positive coparenting behaviours in shaping child adjustment and their critical role as intervention targets to reduce child problems.

Psychology

coparenting

child adjustment

network analysis

birth order

Healthy child development depends on family cooperation, with coparenting playing a crucial role. Coparenting refers to the ways in which parents relate to each other in the role as parent, and how parents share their responsibilities of child-rearing (Feinberg, 2003). Coparenting behaviors have been found to have a significant influence on child adjustment during the critical early childhood period. These behaviors are linked to children’s internalizing problems, such as emotional distress, anxiety, and depression (Aguilar-Yamuza et al., 2023; Jacobvitz et al., 2004; Kolak and Volling, 2013), as well as externalizing problems, including disruptive or antisocial behaviors (Choi and Becher, 2019; Schoppe et al., 2001) .

While existing research has reported associations between coparenting behaviors and child outcomes (Cunha et al., 2025), few adopt a systematic perspective. This is important because focusing on single behaviors in isolation can obscure the dynamic interplay among coparenting dimensions and their collective relation to child adjustment. According to family systems theory, the family is an organized, complex system where each member’s interactions shape, and are shaped by, the interactions of others (Minuchin, 1985). Therefore, only by analyzing the system as a whole, rather than examining each coparenting behavior in isolation, can a comprehensive picture be obtained.

The idea of examining coparenting as a system is evident in how its multiple dimensions are interrelated. McHale’s (1997) factor analysis identified four coparenting components—integrity, conflict, disparagement, and reprimand. Integrity refers to promoting coparental and family unity, similar to coparenting cooperation and support (Margolin et al., 2001). Conflict refers to overt parental arguments in the presence of a child, while disparagement occurs covertly when one parent is absent. Feinberg (2003) also described the overt behaviors as ‘undermining’, which enhances one parent’s authority while reducing the other’s. Reprimand refers to directing a partner to set limits or discipline the child. Importantly, these coparenting components do not influence children in isolation but interact within the triadic system of parents and child, mutually affecting one another (Teubert and Pinquart, 2010). For example, supportive coparenting has been shown to buffer the negative effects of undermining behavior on preschoolers’ behavioral problems (Kolak and Volling, 2013).

Another key aspect of coparenting complexity is the different ways paternal and maternal behaviors relate to child outcomes. Several studies have shown that maternal coparenting is associated with child compliance and behavioral problems (Kwon and Elicker, 2012; LeRoy et al., 2013), whereas paternal coparenting shows no association. Some researchers also emphasize paternal and maternal consistency, compensation, and deterioration rather than solely focusing on the individual coparenting behaviors of each parent (Kara and Sümer, 2022). The interdependence between paternal and maternal coparenting behaviors indicates that each parent’s actions can complement or counteract the other’s, influencing child adjustment in nuanced ways (Cunha, et al., 2025).

Coparenting research has long faced a dilemma between dimension-separation and total-score strategies: the former dissects each behavioral dimension in isolation (Mendez et al., 2015), whereas the latter collapses coparenting into a single latent variable (He et al., 2024). Both approaches implicitly assume independence among dimensions, potentially obscuring within-system interactions and leaving key questions unanswered—e.g., Which dimension still exerts an independent effect after controlling for the others? How do dimensions reciprocally amplify or offset one another? and Should interventions target fathers or mothers?—thereby limiting the precision of family interventions.

Network analysis offers a new lens to resolve this impasse (Borsboom and Cramer, 2013; Boccaletti et al., 2006). By modeling each coparenting dimension and child outcome as nodes and their associations as edges, the method uses strength centrality to identify the core behaviors that most contribute to system connectivity, and bridge centrality to locate the pivotal hubs that transmit information across communities (Liu et al., 2014). Once high-centrality nodes are pinpointed, interveners can follow the map to prioritize the most systemically influential behaviors, thereby maximizing intervention efficiency.

Accordingly, we argue that future research must treat number of children as a stratifying variable and systematically compare the topological properties of coparenting networks—such as density, centrality distribution, and core-periphery structure—between only-child and multi-child families, so as to clarify whether family structure indirectly affects child development by altering network connectivity. Specifically, the study aimed to (1) map the interactions among different types of coparenting behaviors and their relations with children’s internalizing and externalizing problems, (2) identify which coparenting dimensions are most central or influential within the network, and (3) examine how family structure—specifically, having an only child versus multiple children—affects the organization and connectivity of the coparenting network. This study provides a comprehensive, system-level perspective on coparenting, offering insights that can inform targeted interventions and advance understanding of family dynamics.

Participants

The present study adopted a cross-sectional design and included a sample of 850 preschool children’s parents from Sichuan Province in China recruited via convenience sampling. The research was carried out in May 2023. After informed consent was obtained from the teachers and parents, surveys was conducted at the class level. The parents were briefed by the examiner on the precautions for completing the questionnaire, emphasizing the authenticity of the responses and the confidentiality of personal information. The parents took the questionnaire home, voluntarily completed it, and then returned it the next day. After excluding participants with incomplete data, 752 participants remained for analysis (381 Male children [50.7%] and 371 female children [49.3%]). The mean age of the preschool children was 4.76 years (SD = 0.89, aged 3–6 years). The children’s parents completed the survey for course credit after receiving a detailed explanation of the research purpose. Demographic characteristics of the sample, see Table 1.

Table 1

Demographic Characteristics of the Sample (N = 752)
Variable		n	%
Gender	Male	381	50.7
	Female	371	49.3
Only Child Status	Only Child	457	60.8
	Multi Child	295	39.2
Region	Rural	91	12.1
	Urban	661	87.9
Living	Two-Generation Cohabitation	347	46.1
	Three-Generation Cohabitation	405	53.9
Father's Employment Status	Full-time Employed	697	92.7
	Part-time Employed	25	3.3
	Unemployed and Seeking Job	6	0.8
	Other	24	3.2
Mother's Employment Status	Full-time Employed	548	72.9
	Part-time Employed	58	7.7
	Unemployed and Seeking Job	9	1.2
	Other	137	18.2
Child's Age	Range	1 ~ 7
	M	4.76
	SD	0.89
Father's Age	Range	24 ~ 51
	M	35.8
	SD	4.40
Mother's Age	Range	23 ~ 48
	M	33.84
	SD	4.05
Number of Family Members	Range	1 ~ 8
	M	4.51
	SD	1.11

Measures

Coparenting Scale

The coparenting Scale was used to evaluate maternal and paternal coparenting behaviours (McHale et al., 1999), and the Chinese version was validated by Liu (2014). The scale consists of four dimensions: the integrity, conflict, disparagement, and reprimand dimensions. The parents responded to the items for mothers and fathers via a 7-point Likert-type scale ranging from 1 (never) to 7 (always). The Cronbach’s alpha values of paternal integrity and negative coparenting behaviours were .712 and .711, respectively, in the present study. The Cronbach’s alpha values for maternal integrity and negative coparenting behaviours were .783 and .780, respectively.

The Strengths and Difficulties Questionnaire

The Strengths and Difficulties Questionnaire (SDQ) for parents is a self-reported instrument that is widely used for the assessment of different social, emotional and behavioural problems related to mental health in children and adolescents (Goodman, 1997). The Chinese version was validated by Kou et al. (2005). The SDQ comprises a total of 25 statements distributed across five subscales: hyperactivity, emotional symptoms, prosocial behaviour, conduct problems, and peer problems. A Likert-type response format with three options (0 = “Not true”, 1 = “Somewhat true”, 2 = “Certainly true”) is used. Hence, the score for each subscale ranges from 0 to 10 points. The Cronbach’s alpha of the prosocial behaviour subscale of the SDQ was .714 in the present study. The Cronbach’s alpha of all difficulty subscales (including the hyperactivity, emotional symptoms, conduct problems and peer relationship problems subscales) of the SDQ was .744.

Statistical Analysis

Network Estimation

Descriptive statistics were obtained via SPSS 24.0. Two networks (for only-child and multi-child families) were estimated via the R package qgraph. The variables are depicted as nodes, and the associations between symptoms are depicted as edges in the network. Following the guidelines offered by Epskamp et al. (2018), the gLASSO procedure, which conservatively identifies only the relevant edges and accurately discovers the underlying network structure (Friedman et al., 2008), was employed to compute networks with the penalty parameter assigned a value of 0.5. The estimate of each edge can be interpreted as a partial correlation that presents a unique relationship between two variables independent of all others (Borsboom and Cramer, 2013).

Networks were visualized via the Fruchterman–Reingold algorithm (Fruchterman and Reingold, 1991). Stronger connections are represented by thicker and more saturated edges, and nodes with stronger and/or more connections are positioned in closer proximity. To facilitate visual comparison, an identical layout of nodes according to their average position across networks was imposed.

Centrality Estimation

To quantify the centrality of nodes within the network, the strength centrality index was calculated via the “centralityPlot” function in the R package “qgraph”. This function is used to measure the connectivity of nodes, which is the sum of the absolute edge weights connected to a node (Richetin et al., 2017). Bridge strength was also computed to quantify the associations between different variable communities (Jones et al., 2021).

Accuracy and Stability Estimation

Given that network models are subject to sampling variation, it was necessary to check the accuracy and stability of the edge weights and centrality indice. The "bootnet" package in R was used for this bootstrapping analysis (Borsboom et al., 2018; Epskamp et al., 2018).

For edge weights, accuracy and stability were assessed by resampling the data with replacement, and the parameter estimates obtained from these resampled samples were used to construct 95% confidence intervals (CIs) (Hastie et al., 2015). Nonparametric bootstrap methods were applied to evaluate edge accuracy. Narrower constructed CIs indicated that the network was trustworthy (Marchetti, 2019).

For centrality indices, we used a case-drop bootstrap to check the estimation accuracy of centrality indices (Epskamp et al., 2018). This procedure examines stability by checking the correlation of estimated centrality between the original sample and subsets. If centrality indices (e.g., strength centrality) do not significantly change in minimal subsamples (randomly excluding 70% of the original dataset), they are considered stable. Stability was quantified on the basis that the correlation stability (CS) coefficient should exceed 0.5 but be no less than 0.25 .

Finally, the bootstrapped difference test was also performed via nonparametric bootstrapping. The CIs were checked—whether zero was included—to determine if one edge weight or centrality was different from another. All bootstrapping processes were conducted 2,000 times.

Network Comparison

We divided our sample to two subgroups according to child birth order (only-child families: n = 457; multi-child families: n = 295), and network models were constructed for each. The "NetworkComparisonTest (NCT)" package in R was used to estimate the differences in network structure between the models (Van Borkulo et al., 2023). A higher value of global strength (the sum of all edges) indicates stronger connectivity among variables (Opsahl et al., 2010). Differences in edge weights and centrality strengths were also computed to describe the local variance between the networks, which refers to differences in individual edge weights or centrality indices.

Descriptive Statistics

The mean scores and standard deviations of paternal coparenting behaviours, maternal coparenting behaviours and children’s strengths and difficulties are shown in Table 2. The independent sample t test results indicated that maternal integrity (t = 2.17, p = .03), maternal conflict (t = 2.48, p = .02), children’s hyperactivity (t = 2.49, p = .01) and children’s emotions (t = 2.36, p = 0.02) significantly differed between two groups.

Table 2

Descriptive statistics of all variables
	Abbr.	only-child families		multi-child families		t	p
	Abbr.	M	SD	M	SD	t	p
Paternal Integrity	Fcop1	4.53	1.07	4.39	0.99	1.80	.07
Paternal Disparagement	Fcop2	2.46	0.72	2.45	0.77	0.12	.91
Paternal Conflict	Fcop3	2.68	1.03	2.58	1.00	1.31	.19
Paternal Reprimand	Fcop4	4.29	1.02	4.33	1.07	-0.45	.65
Maternal Integrity	Mcop1	4.92	0.85	4.79	0.87	2.17	.03
Maternal Disparagement	Mcop2	2.65	0.91	2.58	0.88	1.07	.28
Maternal Conflict	Mcop3	2.97	1.10	2.77	1.07	2.48	.02
Maternal Reprimand	Mcop4	4.63	1.07	4.54	1.03	1.09	.28
Children’s Hyperactivity /Inattention	Csd1	0.78	0.30	0.73	0.29	2.49	.01
Children’s Emotional Symptoms	Csd2	0.44	0.36	0.38	0.32	2.36	.02
Children’s Prosocial Behaviour	Csd3	1.33	0.40	1.38	0.40	-1.37	.17
Children’s Conduct Problems	Csd4	0.36	0.27	0.34	0.28	1.12	.26
Children’s Peer Relationship Problems	Csd5	0.87	0.26	0.84	0.3	1.42	.16

Network Analysis

Network Estimation

Figure 1 shows the network structure of paternal coparenting behaviours, maternal coparenting behaviours, and children’s strengths and difficulties (n = 752). Each variable is represented by a node, with orange nodes representing paternal coparenting behaviours, blue nodes representing maternal coparenting behaviours, and green nodes representing children’s strengths and difficulties. The blue lines indicate positive correlations, and the red lines indicate negative correlations. The thickness of the edges represents the strength of the connections between nodes. The coloured area within the rings around each node indicates the predictability (the percentage of variance in a given node explained by the surrounding nodes).

The variable networks are presented in Fig. 2. Thirteen subdimensions were treated as nodes, and the partial correlations between each pair of nodes were treated as edges, examining the interactions within the regularized network. The network included 91 edges, with 38 nonzero weight connections (partial r = − .13 to .34). In the entire network, the highest edge weights were observed between maternal disparagement and maternal conflict (partial r = .34), paternal integrity and maternal integrity (partial r = .33), paternal conflict and maternal conflict (partial r = .31), paternal disparagement and paternal conflict (partial r = .31), and children’s emotional symptoms and children’s conduct problems (partial r = .28), indicating the tightest node connections.

Centrality Estimation

The plots of the strength centrality and bridge strength centrality are shown in Figs. 3 and 4. Among all nodes, maternal intergrity (strength = .84), maternal disparagement (strength = .84), maternal conflict (strength = .83), and children’s emotional symptoms (strength = .80) had the highest strength centrality values, indicating that these nodes had the greatest influence on the network. Within the maternal coparenting community, maternal integrity (bridge strength = .54) and maternal conflict (bridge strength = .46) had the highest bridge strength centrality. Within the paternal coparenting community, paternal integrity (bridge strength = .42) and paternal conflict (bridge strength = .34) had the highest bridge strength centrality value. With respect to the children’s strengths and difficulties community, children’s prosocial behaviour (bridge strength = .23) and children’s conduct problems (bridge strength = .19) had the highest bridge strength centrality values. These nodes were key diffusion bridges across different communities. The differences(p < .05) in strength centrality and bridge strength centrality are shown in Figs. 5 and 6.

Accuracy and Stability Estimation

The network structure demonstrated good stability and accuracy in this study. Figure 7 shows the bootstrapped-estimated CIs for the edge weights. The relatively narrow CIs indicate acceptable accuracy. Figure 8 shows the results of the centrality stability case-drop bootstrap estimation process. The CS coefficients for strength centrality and bridge strength centrality were .362 and .673, respectively.

Network Comparison

Figure 9 displays the network graphs for the subgroups of only-child and multi-child families. We compared the global and local structures of the network models for only-child and multi-child families. The results revealed that there was no significant difference in global strength between the networks of only-child families (global strength = 3.83) and multi-child families (global strength = 4.62; p = .42). There was also no significant difference in network structure (p = .30).

There were no significant differences in the centrality strength of the nodes between the networks of only-child and multi-child families. However, differences were observed in bridge strength centrality and edge weights between the networks. In terms of bridge strength centrality (Fig. 10), the bridge strength centrality of maternal disparagement was significantly lower in the network of only-child families than in that of multi-child families (p = .02), and the bridge strength centrality of children’s emotional symptoms was significantly lower in the network of only-child families than in that of multi-child families (p < .01), indicating a greater bridging effect for these two variables in the network of multi-child families.

In terms of edge weights, there were significant differences in the 6 edges between the networks (p < .05). Notably, the edge weight between maternal disparagement and children’s emotional symptoms was significantly lower in the network of only-child families than in that of multi-child families (t = .20, p < .01), and the edge weight between coparenting conflict and children’s emotional symptoms was significantly lower in the network of only-child families than in that of multi-child families (t = .04, p < .01). The edge weight between maternal disparagement and children’s hyperactivity was significantly lower in the network of only-child families than in that of multi-child families (t = .04, p = .03); and the edge weight between children’s emotional symptoms and children’s hyperactivity was significantly lower in the network of only-child families than in that of multi-child families (t = .09, p = .04).

The present study adopted a network analysis approach to examine the structural connectivity between coparenting behaviors and their impact on preschool child adjustment. This approach allowed for the examination of the complex interplay among multiple coparenting and child behaviors within the family system, while also identifying the unique influence of each coparenting dimension after accounting for other variables. Our findings from the centrality analysis showed that integrity, conflict, and disparagement in maternal coparenting show the strongest node strengths, highlighting their central role in the coparenting network. Among child outcomes, emotional symptoms and conduct problems exhibited higher node strengths, indicating that these outcomes are more strongly associated with coparenting than hyperactivity or peer problems. No significant differences in overall connectivity were found for only-child families or families with multiple children, but the link between maternal disparagement and child emotional symptoms was stronger for the latter. These findings emphasize the complex relationship between coparenting dimensions and child outcomes, suggesting potential targets for future interventions.

Central Components of Coparenting

In the coparenting effect network, maternal coparenting behaviors had higher centrality indices than paternal behaviors, suggesting a stronger association with the coparenting system and child outcomes. Previous research has consistently shown that mothers play a significant role in children’s development, reflecting traditional gender views that position them as primary caregivers who often spend more time with their children (Brown et al., 2011; Milevsky et al., 2007). This pattern is also evident in Chinese culture, where mothers are frequently regarded as indispensable, and in some cases the sole figures, in parenting (Li, 2022). The present study extends these findings to coparenting, indicating that, although both maternal and paternal behaviors involve both parents, maternal-led coparenting is generally more prominent within the family system.

Next, we examined the relative importance of each coparenting dimension. For bridge centrality indices, coparenting integrity and conflict showed particularly high values, highlighting their key role in linking coparenting behaviors to child outcomes. The central role of coparenting integrity aligns with the findings of Liu et al. (2023). Since it contributes to family warmth and positive interactions, coparenting integrity is a key factor in child adjustment and a major intervention target.

Bridge centrality for coparenting conflict was found to be comparable to that of integrity, suggesting that conflict also plays an important bridging role within the network. Previous research has found that coparenting conflict has numerous adverse effects on children, both physically and emotionally (Sarrazin and Cyr, 2007), which may be attributed to its salient nature (Baril et al., 2007). Due to its bridging role, a reduction in the intensity of coparenting conflict could weaken the connections between key clusters within the coparenting network. This implies that interventions targeting coparenting conflict may not only directly decrease the child behavior issues it causes, but also hinder the spread of adverse effects from other coparenting behaviors across the network.

In terms of strength centrality, maternal disparagement was the node with the strongest connections within the network, surpassing both integrity and conflict. This aspect of coparenting, also referred to as triangulation, occurs when children are drawn into parental conflicts and pressured to take sides (Buehler et al., 1998). Coparenting disparagement can induce stress, contributing to emotional problems such as depression and anxiety (Miller et al., 2004). From a network perspective, the high strength centrality of coparenting disparagement indicates its far-reaching influence and its interactions with other components, such as coparenting conflict. For instance, coparenting disparagement may contribute to a tense family environment and heightened emotional reactivity in children. Elevated emotional reactivity, in turn, has been shown to worsen the negative effects of parental conflict (Buehler and Welsh, 2009). However, although the high strength centrality of coparenting disparagement indicates its central role, the low bridging centrality suggests it is not a unique connector and should be considered in combination with other intervention targets.

Coparenting Behaviors and Child Outcomes

Beyond the centrality of coparenting dimensions, we further examined how these behaviors relate to distinct child outcomes. Unlike most previous studies that collapsed child outcome dimensions into a few variables, we treated each dimension as a separate node (Bai et al., 2024). We found that emotional symptoms and conduct problems, which are typically classified as internalizing and externalizing problems, respectively, had stronger strength and bridge strength within the coparenting network. In contrast, hyperactivity, which is often grouped with conduct problems as an externalizing problem in previous research, showed weaker strength and bridge strength.

These findings indicate that emotional symptoms and conduct problems were closely linked with coparenting behaviors. This pattern may be explained as high-quality coparenting can create a safe and supportive home environment, helping children form secure attachments with their parents. This, in turn, enables them to express emotions openly, release stress, and lower the risk of emotional problems (Qian et al., 2020). In contrast, poor coparenting can lead to a lack of parental authority and impaired household rule-setting, increasing the risk of children's conduct problems. Additionally, children who frequently face coparenting conflicts and disparagement tend to experience hostility, increasing the risk of disruptive behaviors.

Hyperactivity correlated less with coparenting networks than emotional symptoms or conduct problems. This aligns with previous research on parenting, which found that hyperactive traits, which have a stronger genetic basis (Kleppesto et al., 2024), are less influenced by parental behaviors compared with other externalizing problems. Notably, many coparenting studies categorize child outcomes into internalizing and externalizing problems. Yet in our network, hyperactivity and conduct problems—both classified as externalizing—differed in their connections to coparenting. Our results suggest that a more nuanced classification of child outcomes should be considered when examining coparenting effects.

Coparenting-Child Outcome Network for Only-children and Non-only Children Families

To examine whether family type plays a role in shaping the coparenting network, we divided the original sample into only-child and non-only-child families. We compared the two subnetworks in terms of overall network strength, edge weights, and centrality strength, and no significant difference was found. Given China’s one-child policy, the stability of coparenting effects across family types is particularly noteworthy, suggesting that coparenting dynamics are shaped more by the quality of parental cooperation and conflict management than by family size.

Importantly, the correlation between maternal disparagement and child emotional symptoms was stronger in the non-only-child group, indicating a stronger relationship between the two variables. One possible explanation is that children in non-only-child families often develop higher sociability through sibling interactions (Eckstein et al., 2010). These children may be more sensitive to subtle relational signals, such as coparenting disparagement, which could contribute to emotional symptoms. Alternatively, from a network perspective, the effectiveness of the coparenting network in processing subtle emotional dynamics between parents and children may be higher in non-only-child families, thereby amplifying the association between maternal disparagement and child emotional symptoms.

Previous research has reported that parents of only children tend to invest more time and attention than those in non-only-child families (Young and Beutel, 2024). However, when we focus on the coparenting system—a process involving corporation from both parents—the pattern changed. This dynamic is relatively stable across family sizes, except for its subtle relationship to children’s emotional adjustment. These findings also provide evidence for the importance of examining coparenting as a system, rather than focusing on individual parental behaviors.

Implications for Interventions

Our study confirms the significant bridging role of coparenting integrity and conflict within the network. Previous interventions have focused mainly on coparenting support, while coparenting conflict has received less attention (Eira Nunes et al., 2021). We propose that reducing coparenting conflict is just as critical as increasing coparenting support in improving child development. However, previous interventions addressing coparenting conflicts focused primarily on general interpersonal conflict resolution (Xiao and Loke, 2021), overlooking the specific role that coparenting conflicts play within the family system.

We believe that interventions for coparenting conflicts should not only teach parents how to resolve the conflicts themselves but also how to maintain a positive family atmosphere during disputes. Interventions should prevent children from internalizing coparenting conflicts as their responsibility, thereby reducing potential guilt and emotional burden. Additionally, parents can model conflict resolution to help children learn how to manage family relationships, recognize family resilience, and thereby enhance their sense of security.

Furthermore, to examine the effects of coparenting interventions on children, it is recommended to measure different aspects of child outcomes separately rather than combining emotions, attention, socialization, and other domains into a single construct of child adjustment. In situations with limited measurement conditions, we suggest the use of emotional symptoms and conduct problems (rather than hyperactivity or attention problems) as an indicator to capture the specific effects of coparenting behaviors and increase the sensitivity of the study.

Limitations and Future Outlook

The present study has several limitations. First, the sample was drawn from a specific region, limiting its representativeness. Future research could explore whether coparenting dynamics differ across cultures to understand the broader applicability of these findings. It should also include those who are non-marital, divorced, or involved in grandparent-led caregiving.

Second, the data on coparenting behaviors and child outcomes were collected through parental reports, which introduced the possibility of individual perception biases and common method biases. Future research could benefit from using multiple data sources, such as observations and reports from both parents and children, for a more comprehensive understanding of coparenting behaviors.

Third, we used a cross-sectional design, which only allows us to examine the relationship between coparenting behaviors and child development at the time of measurement. Thus, we cannot draw causal conclusions or rule out alternative explanations. In particular, the observed associations may reflect bidirectional influences: while coparenting behaviors can affect child adjustment, children’s behaviors and emotional states may also shape parental interactions. For example, children with more conduct problems might elicit greater disparagement or conflict in coparenting. Future longitudinal studies should investigate these bidirectional effects to clarify the temporal dynamics between coparenting behaviors and child outcomes.

Finally, the present study focused only on the coparenting network in early childhood, which might not capture the full extent of their association to child development. Some latent effects of coparenting behaviors become apparent only in late childhood or even adulthood. Follow-up studies are needed to examine how the coparenting network evolves and changes across different life stages.

This study offers valuable insights into the role of coparenting in child development. The findings suggest that interventions should target specific coparenting behaviors, particularly conflict and disparagement. Building on this, future studies could trace the long-term impacts of coparenting behaviors across diverse family structures and cultures.

Ethical statement

All procedures were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments. Approval from Ethics Committee of the Sichuan Psychological Society approved the study protocol (No. 20230216)on 02/16/2023.

Informed consent

Informed consent was electronically obtained in writing from all participants before their involvement in the study. Conducted via an online questionnaire, the consent process included a dedicated section explaining the study’s purpose, procedures, data usage, and participants’ rights, including voluntary participation and withdrawal without consequences. Participants confirmed consent by selecting an “Agree” button; those who declined were redirected away from the survey. Data collection took place between 10 May till 30 May 2023, overseen by the principal investigator and co-researchers. Consent was obtained directly from adult participants, without third-party involvement, as they were legally capable of providing consent independently. All data were collected and processed anonymously, with no personally identifiable information disclosed. Participants were given the opportunity to contact the researchers for clarifications before consenting. The study did not involve vulnerable individuals, and no financial or material incentives were provided.

Acknowledgements

This study was supported by Sichuan Provincial Department of Education, College Ideological and Political Work Team Training Center (Southwest Jiaotong University) [Grant Number CJSFZ22-06].

Author contributions

X. N. L and J. Y: Conceptualization, Methodology, Formal analysis, Software, Visualization, Investigation, Supervision, Writing - original draft, Writing - Review & Editing; L. C and H. Z: Project administration, Data curation, Supervision, Writing - Review & Editing.

Competing interests

The authors declare no competing interests.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The ethics approval was obtained from the institutional review board of Institute of ****, with the following ID number: 20230216. The Institute of *** Research Ethics Committee reviewed and approved the study protocol, involving research design and methods, recruitment approach for participants, data collection and privacy protection, and informed consent.

Informed consent

Informed consent was obtained from all individual participants included in the study.

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The authors declare no competing interests.

Coparenting Dimensions and Preschooler Outcomes: A Network Analysis in Only-Child and Multi-Child Families

Status:

Version 1

Abstract

Figures

Introduction

Methods

Participants

Measures

Coparenting Scale

The Strengths and Difficulties Questionnaire

Statistical Analysis

Network Estimation

Accuracy and Stability Estimation

Network Comparison

Results

Descriptive Statistics

Network Analysis

Network Estimation

Centrality Estimation

Accuracy and Stability Estimation

Network Comparison

Discussion

Central Components of Coparenting

Coparenting Behaviors and Child Outcomes

Coparenting-Child Outcome Network for Only-children and Non-only Children Families

Implications for Interventions

Limitations and Future Outlook

Declarations

References

Additional Declarations

Status:

Version 1