Social determinants of perinatal mental health and well-being: A social network analysis

Social determinants of perinatal mental health and well-being: A social network analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Social determinants of perinatal mental health and well-being: A social network analysis Florencia Canessa, Martín Miranda, Susanne Schweizer This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9490400/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Background The transition to motherhood is a time of marked social changes. It is also a time of mental health vulnerability. This study examined the role that changes in women’s social environment during the peripartum period have on mental health and well-being. Methods Adopting a matched case-control design, we used social network analyses to capture changes in the social environment of women during (N = 378) and outside (N = 378) the peripartum and measured individual differences in social sensitivity, anxiety and depressive symptoms, and mental well-being. Changes in social environments and their association with individuals’ mental health and well-being were tracked three times across a six-month period. Results Compared to controls, peripartum women reported reduced social sensitivity, and greater emotional closeness, network density and family:friends ratio. Peripartum women also showed fewer mental health symptoms and greater well-being. Emotionally closer and closely-knit social environments were protective for women during the peripartum but not for controls. Conclusions The observed mental health and well-being benefits of social changes during the peripartum add to growing evidence of the peripartum as a time of heightened malleability characterised not only by vulnerability but also opportunity. perinatal mental health social sensitivity social networks anxiety depression Figures Figure 1 Figure 2 Figure 3 Background The peripartum period, the time from conception to one year after birth, is a period of heightened vulnerability for the onset and recurrence of mental health problems in women 1 , with as many as one in five experiencing anxiety ( 1 ) and/or depression ( 2 ). However, while average symptoms of anxiety and depression tend to show increases across pregnancy and the early postpartum period (e.g., ( 3 )), analyses of symptom trajectories show that the largest group of people report consistently low symptoms despite going through a period of major biological and social changes ( 4 ). What’s more, very few studies have directly compared symptoms in women in the peripartum to those outside the peripartum. Studies that have, largely show lower symptoms in peripartum compared to non-peripartum women ( 5 – 8 ). Understanding determinants of good mental health and well-being during the peripartum is essential to better inform mental health prevention efforts and identify novel avenues for intervention during this period. Growing evidence suggests that the peripartum is not only a time of vulnerability, but also a time of heightened plasticity and opportunity ( 9 ). The novel environmental conditions and experiences of pregnancy, childbirth and the postpartum period - from physiological changes to caring for the child - may confer opportunities for adaptation ( 10 , 11 ), the acquisition of new skills and maternal behaviours ( 12 , 13 ), as well as cognitive advantages ( 14 ). Whether these adaptations could account for the large number of individuals who show persistently low levels of anxiety and depression across the peripartum period remains poorly understood. Social (re)orientation Arguably, a major (yet little researched) change during the peripartum, that may provide mental health benefits, is the social re-orientation towards the foetus and later the baby. Social re-orientation, the shift in social focus ( 15 ), has been more extensively studied in adolescence, another developmental period associated with significant hormonal changes, as well as changes in brain structure and function that are of similar magnitude to those observed during the peripartum ( 16 – 18 ). Considering social re-orientation from a lifespan perspective can provide insights into its potential role in maternal well-being. Social re-orientation from a lifespan perspective During adolescence, individuals become more independent from caregivers and re-orient their social behaviours and attention towards peers ( 15 , 19 ). As their social environment expands beyond the family, the relationships with peers become increasingly rewarding and a relevant source of emotional support ( 20 , 21 ), and stronger predictor of well-being than the relationships with caregivers ( 22 ). At the same time, however, the re-orientation towards peers can be a source of risk for mental health problems, as adolescents become more sensitive to social information in their environment, especially to social rejection ( 23 ). Social rejection sensitivity is elevated during adolescence ( 24 , 25 ) and a factor associated with increased risk of anxiety and depression across the lifespan ( 26 ). Together, these findings suggest that the impact of social re-orientation towards peers in adolescence is two-fold: It is protective when it leads to strong social peer relationships but can also be a source of risk by elevating social sensitivity towards peer evaluation. In the peripartum, instead, social sensitivity to peer evaluation may decrease, as a novel source of social affection and valuation is introduced into the parent’s life. During this period, women – and arguably non-birthing partners though they are beyond the scope of this article – re-orient their social behaviours and attention towards the baby. While affection can take time to emerge ( 27 ), social orientation towards the baby is innate. Immediately following delivery, females of all species of mammals – likely triggered by hormones – shift their behaviour towards the care and the survival of their offspring ( 28 – 31 ). There is evidence that physical social behaviours, such as physical contact, benefit maternal well-being (e.g., ( 32 , 33 )). Little is known, however, about the impact of psychological changes following social re-orientation, including potential changes in social sensitivity, on maternal well-being. Social networks to study social re-orientation One way to explore changes in the social environment is through the analysis of social networks. Social networks are a way of representing social connections as a set of nodes (actors) and the ties (relationships) between them ( 34 ). By identifying relevant alters , individuals to whom people relate, and analysing the composition of networks and the characteristics of these relationships (e.g. emotional closeness), social network analyses can capture changes in individuals’ social environments and how these interact with behavioural and health outcomes ( 35 , 36 ). Preliminary evidence examining social networks and maternal well-being has mainly focused on capturing the social support available to mothers (e.g., ( 37 )). While not using formal network analyses, but instead deriving network size, frequency of contact and satisfaction with social contacts from 137 first-time parent dyads, one study showed that size and satisfaction with friends’ networks decreased from the antenatal period to 24 months postpartum, whereas family networks’ size and satisfaction showed an initial decrease early in the postpartum and then increased ( 38 ). Larger family networks and greater satisfaction with family and friend networks were associated with fewer symptoms of depression ( 38 ). While providing further evidence for the importance of social support, these findings fail to capture the process of social re-orientation during the peripartum. The current study The current study applied network analyses to capture changes in the social environment of women during the peripartum period, including changes in the interconnectedness (or density), emotional closeness and composition of their networks, reflecting social (re-) orientation. Adopting a matched case-control design, these changes and their association with individuals’ mental health and well-being were tracked across a six-month period and compared to social network changes of age- and country-matched non-peripartum women. The adoption of a matched case-control design was particularly important in the context of the current study, as data was collected thrice in three-month intervals during the COVID-19 pandemic, which had considerable impacts on people’s social connections. Women in the peripartum and controls would have been similarly affected, allowing us to infer that any group differences observed are due to peripartum status rather than the pandemic. To examine whether social re-orientation during the peripartum leads to reduced social sensitivity, the current study also measured individual differences in social sensitivity. Specifically, the study tested the following hypotheses: Social re-orientation among peripartum compared to non-peripartum control women would be reflected in reduced social sensitivity (H1a) and differences in social networks, with peripartum women reporting greater density, closeness and a higher family:friends ratio in their social networks compared to the control group, indexing a re-orientation towards the family environment (H1b); and this same pattern would be observed within the peripartum from pregnancy to postpartum (H1c). H2 : These structural (i.e., degree and family:friends ratio) and functional (i.e., emotional closeness) network changes would be associated with lower anxiety and depressive symptoms and greater well-being in peripartum compared to control women (H2a) and these association would strengthen within the peripartum period from pregnancy to postpartum (H2b). Methods Study design Data was analysed from the COVID-19 Risks Across the Lifespan (CORAL) study ( 39 ) ( https://www.thecoralstudy.com/ ). A three-wave longitudinal online study of the cognitive, social and psychological functioning during the COVID-19 pandemic that ran between May 2020 and April 2021. The study protocol was approved by the University of New South Wales Human Research Ethics Committee (HC200287). Procedure Participants were recruited via social media and advertisement in mothers’ groups. After providing informed consent, participants completed an online survey at three assessment timepoints: baseline (T1), three months (T2) and six months (T3) follow-up. Participants responded to a series of questions concerning their pregnancy, COVID-19, mental health and well-being, and social networks. At each timepoint, every 100th participant was rewarded with an AUD $ 100 (GBP£50 or US $ 60) Amazon voucher, and those participants that completed T2 and T3 were compensated with an AUD $ 10 (GBP£5/ USD $ 6) voucher. Participants At T1, 742 participants from the CORAL sample (N = 3,208) reported being pregnant. Participants were included in the peripartum subsample of this study if they met the following inclusion criteria: (a) were pregnant at T1 as verified by the screening question and the provision of a due date, (b) were 17–45 years old at T1 and (c) completed the social network questions at least once. A sample of eligible non-peripartum participants was randomly selected. Participants were eligible for inclusion in the non-peripartum sample if they: (a) identified as female and reported consistent gender across timepoints, (b) were 17–45 years old at T1, (c) completed the social network alters question at least once, and (d) were not pregnant at all time points. From this group, the sample of non-peripartum control women was then selected. Participants were paired with a pregnant case based on exact matching by country, followed by greedy nearest-neighbour matching by age. Prioritisation was based on the number of completed time points. For each participant in the peripartum group, matched cases in the same country of residence were found. Next, from the pool of cases with more completed time points, we selected the case with the closest age. This resulted in two subsamples of similar ages and exact same country of residence including, 378 peripartum women ( M age = 32.21 years, SD = 4.66) and 378 non-peripartum control women ( M age = 31.49 years, SD = 7.51) who met all inclusion criteria. Samples differ in their educational background (see Table 1). Table 1 Sample Demographics Variable Peripartum Control n 378 378 t test / χ ² Age 32.21 (4.66) 31.49 (7.51) -1.59 Education University 308 (81%) 271 (72%) 13.23*** Professional/ Vocational training 45 (12%) 54 (14%) High School 25 (7%) 53 (14%) Country United States of America 104 (28%) 104 (28%) 0 United Kingdom 160 (42%) 160 (42%) Australia 114 (30%) 114 (30%) Ethnicity Caucasian 328 (87%) 308 (81%) 7.99 Asian 15 (4%) 21 (6%) Hispanic 8 (2%) 5 (1%) African 3 (1%) 5 (1%) Aboriginal or Torres Strait Islander 1 (0%) 2 (1%) Mixed 8 (2%) 18 (5%) Other 12 (3%) 15 (4%) Prefer not to say 2 (1%) 4 (1%) Have children in the house Yes 181 (48%) 200 (53%) 1.71 Note . Demographic characteristics of the sample. *** p < .001 Measures Only the measures used in the analyses for the present study are reported in the following section: Social Networks Participants provided information about their social networks. Participants were asked to endorse between one and six ‘ alters ’, people with whom they spent most of their free time with over the past year before COVID-19 at T1, and over the past month in T2 and T3. For each alter, participants provided information about the nature of their relationship (e.g. friend, husband), how close they felt and how the alters in their network were related. Based on this information, the following parameters were obtained: Density . Density reflects the number of connections within a network. It is computed by dividing the number of ties in a network by all possible ties in the network, using the following formula: $$\:\frac{n+\:aa}{n+n\left(\frac{n-1}{2}\right)}$$ Where n is the number of alters in the network, and aa the number of ties between alters. A denser network would indicate that the network's members tend to know each other and that the network is oriented towards more closely knit, family-type relationships. Closeness. Closeness reflects the strength of the connections within a network. For each alter, participants indexed how close they feel to that person from 1 (“Not close at all”) to 10 (“Extremely close / closer than any other person I know”). Closeness was computed as the average strength of all the ties in the network. Higher closeness reported in the network would reflect emotionally closer social environments. Family:friends ratio . Family:friends ratio reflects the composition of a network. It was computed as the proportion of alters who are family members, compared to those who are friends. When participants did not report any friend alter, the variable was computed as the number of family members. A higher family:friends ratio would indicate a prioritisation of time spent with family members over friends. Social Sensitivity The 18-item Online and Offline Social Sensitivity Scale (O2S3) ( 26 ) was used to assess social sensitivity and was administered only at T1. The scale requires participants to index the extent to which they agree with statements describing feelings towards both online and offline interactions (e.g. “I worry about being criticised for things I have said or done”), from 0 (strongly disagree) to 3 (strongly agree). The scale is psychometrically well-validated across the lifespan ( 26 ). The scale demonstrated good internal consistency (ω = 0.92). Anxiety symptoms The 7-item Generalized Anxiety Disorders-7 scale (GAD-7) ( 40 ) was used to measure symptoms of anxiety, with participants indicating how often they experienced symptoms of generalized anxiety (e.g. “Worrying too much about different things”) over the past two weeks from 0 (not at all) to 3 (nearly every day). The scale is psychometrically well-validated, including in perinatal populations ( 41 , 42 ). The scale demonstrated good internal consistency (ω T1 = 0.93, ω T2 = 0.92, ω T3 = 0.92). Depressive symptoms The 8-item Patient Health Questionnaire (PHQ-8) ( 43 ) was administered to measure symptoms of depression. The scale requires participants to index how often they have experienced symptoms of depression (e.g. “Feeling down, depressed or hopeless”) in the past 2 weeks from 0 (not at all) to 3 (nearly every day). The scale is psychometrically well-validated, including for use in the perinatal period ( 44 ). The scale demonstrated good internal consistency (ω T1 = 0.90, ω T2 = 0.89, ω T3 = 0.91). Mental well-being The 7-item Short Warwick-Edinburgh Mental Well-being scale (WEMWBS) ( 45 ) was used to measure mental well-being. The scale requires participants to report how often they experienced certain feelings or thoughts (e.g. “I’ve been dealing with problems well”) over the past two weeks from 1 (none of the time) to 5 (all of the time). The scale is psychometrically well-validated ( 45 ). The scale demonstrated good internal consistency (ω T1 = 0.87, ω T2 = 0.87, ω T3 = 0.87). Data analysis All analyses were conducted in R (version 4.3.1). Linear mixed-effects models were conducted using the lme4 ( 46 ), lmerTest ( 47 ) and emmeans ( 48 ) packages. Effect sizes and confidence intervals were obtained using effectsize ( 49 ) and parameters ( 50 ) packages. Coefficients were standardised, with the exception of time, which was recoded as 0, 1, 2 for interpretability. Plot figures were made using ggplot2 ( 51 , 52 ) and ggeffects ( 53 ) packages. Missing at random was assumed for all analyses. For further detail on missing data, please refer to the supplementary material (S1). Group differences in social sensitivity were investigated with a linear regression. Linear mixed effect models were fitted to investigate group differences in social network indices (i.e., degree, closeness, family:friends ratio) and whether these vary across time. The association of social re-orientation with mental well-being was tested separately for each mental well-being outcome (anxiety symptoms, depressive symptoms and mental well-being). For each outcome, a linear mixed-effect model was fitted to investigate the association of the outcome with social network measures over time and between groups. To limit overfitting due to the high multi-collinearity between the structural network indices density and family:friend ratio, only density and closeness were used as network indices. These analyses were repeated in sensitivity analyses that tested whether any observed effects would hold, when controlling for potential confounds. First, to control for the observed group differences in education at baseline (Table 1), and because educational attainment has been associated with mental health status ( 54 , 55 ), educational background was included as a covariate in the models predicting mental health. Second, as social re-orientation also occurs during adolescence (10–24 years; ( 56 )), and given the observed age-related differences in mental health in this cohort, with young people reporting poorer mental health ( 39 ), sensitivity analyses were conducted restricting the sample to participants aged 25 or over in the models predicting mental health. This restriction prevented the overlap of two developmental periods of marked social changes. Third, being in a relationship may confer mental health benefits ( 57 ), especially during periods of social isolation. While relationship status was not assessed in CORAL, relationship status was inferred from the social network composition at each timepoint. If participants indexed any of the members of their network as Husband/Wife or Boyfriend/Girlfriend they were coded as being in a relationship (yes/no). This variable was included as a covariate in the models predicting mental health. This inclusion would help elucidate whether differences in mental health between the peripartum and non-peripartum control groups are also associated with relationship status. Finally, an exploratory analysis was conducted to examine whether these reductions in social sensitivity lasted beyond the peripartum. While the number of children someone had was not captured for non-pregnant participants in CORAL, there was a question on participants’ household composition. Those who reported children in the household were classified as mothers. Repeating the social sensitivity analyses with maternal status as predictor would allow preliminary inferences on lasting reductions in social sensitivity. Additionally, testing the association of social re-orientation with well-being using maternal status as a predictor could provide preliminary evidence on the lasting protective effects of social re-orientation during the peripartum. Analyses testing the association of social re-orientation with mental well-being were Bonferroni corrected with α ≤ .016 to account for the inclusion of three outcomes of interest (i.e., anxiety and depressive symptoms, mental well-being). Results Means and standard deviations of the analysed variables (Table S1 ) as well as bivariate correlations between variables (Table S2) can be found in the supplementary materials. Social sensitivity in peripartum women and non-peripartum control women As predicted, the peripartum group ( M = 22.38) reported significantly lower levels of social sensitivity than the non-peripartum control group ( M = 26.39); β = -4.01, SE = 0.85, t (577) = − 4.72, d = .39 [.23, .56], p < .001. Social re-orientation in peripartum women and non-peripartum control women over time Linear-mixed effects models yielded a significant main effect of both Group and Time on the three social network variables, with the peripartum group showing greater network density, closeness and family:friends ratio (Fig. 1 ) and the indices increasing over time (Table 2 ). The effect of Group did not interact with Time suggesting the differences in network structure and function observed in peripartum vs. control women remained stable across the three timepoints (Table 2 ). Distribution of mean Density, Closeness and Family:friends ratio among peripartum and non-peripartum controls Table 2 Linear mixed-effects models investigating group differences in social network indices and their variation over time. Density Closeness Family:friends Ratio β SE 95% CI p β SE 95% CI p β SE 95% CI p (Intercept) 0.71 0.01 [ 0.69, 0.73] < .001*** 7.28 0.08 [ 7.13, 7.43] < .001*** 1.58 0.10 [ 1.39, 1.77] < .001*** Group 0.06 0.01 [ 0.03, 0.08] < .001*** 0.50 0.10 [ 0.30, 0.71] < .001*** 0.32 0.14 [ 0.06, 0.59] .018* Time 0.03 0.01 [ 0.02, 0.05] < .001*** 0.27 0.05 [ 0.17, 0.38] < .001*** 0.28 0.06 [ 0.15, 0.40] < .001*** Group × Time 0.01 0.01 [-0.01, 0.03] .425 0.03 0.09 [-0.15, 0.20] .771 0.12 0.10 [-0.08, 0.33] .247 Note. * p < .05, *** p < .001 Social orientation as a predictor of well-being in peripartum women and non-peripartum women over time. The linear mixed models examining whether differential network properties were differentially associated with mental health and well-being across groups and time showed a main effect of Group, with peripartum women reporting lower anxiety and depression and greater well-being (Fig. 2 ). Anxiety and Depressive symptoms, and Mental Well-being among peripartum and non-peripartum controls. Closeness also showed a significant main effect for depression and mental well-being, with closer networks being associated with greater well-being and fewer symptoms of depression. No significant effects of Time or Density or interactions were observed (Table 3 ). Table 3 Linear mixed-effects models for all well-being outcomes including Density, Closeness, Group, and Time as covariates Anxiety model Depression model Mental well-being model β SE 95% CI p β SE 95% CI p β SE 95% CI p (Intercept) 8.84 0.32 [ 8.21, 9.48] < .001*** 10.18 0.33 [ 9.53, 10.84] < .001*** 20.56 0.27 [20.02, 21.10] < .001*** Group -2.03 0.45 [-2.90, -1.15] < .001*** -2.43 0.46 [-3.33, -1.53] < .001*** 1.65 0.37 [ 0.92, 2.38] < .001*** Time − 0.09 0.18 [-0.44, 0.26] .616 -0.29 0.18 [-0.64, 0.07] .115 0.05 0.17 [-0.28, 0.37] .785 Density 0.16 0.26 [-0.35, 0.68] .531 0.16 0.27 [-0.36, 0.69] .546 0.11 0.24 [-0.36, 0.57] .649 Closeness -0.56 0.27 [-1.09, -0.02] .042† -0.97 0.28 [-1.52, -0.43] < .001*** 0.74 0.25 [ 0.26, 1.22] .003* Group x Time -0.09 0.33 [-0.73, 0.55] .779 0.34 0.33 [-0.31, 0.99] .308 -0.58 0.30 [-1.17, 0.02] .057 Group x Density -0.72 0.41 [-1.53, 0.09] .083 -0.20 0.42 [-1.03, 0.63] .632 0.05 0.37 [-0.67, 0.77] .891 Group x Closeness 0.33 0.44 [-0.54, 1.19] .459 0.50 0.45 [-0.38, 1.38] .268 -0.36 0.39 [-1.12, 0.40] .355 Time x Density 0.26 0.20 [-0.13, 0.65] .196 0.30 0.20 [-0.10, 0.69] .143 -0.25 0.18 [-0.62, 0.11] .169 Time x Closeness -0.19 0.21 [-0.60, 0.22] .357 -0.13 0.21 [-0.55, 0.28] .527 0.22 0.19 [-0.16, 0.59] .262 Group x Time x Density -0.29 0.38 [-1.04, 0.46] .447 -0.86 0.39 [-1.62, -0.10] .026† 0.38 0.35 [-0.30, 1.07] .270 Group x Time x Closeness 0.78 0.39 [ 0.01, 1.55] .048† 0.57 0.40 [-0.21, 1.36] .152 -0.09 0.36 [-0.79, 0.61] .805 Note. † p < .05, * p < .016, *** p < .001 Sensitivity Analyses Social sensitivity Sensitivity analyses showed that the observed effect of social sensitivity remained significant after controlling for educational level. Higher educational level was associated with lower levels of social sensitivity (Table S3). When excluding adolescents (i.e., individuals age 24 years or younger) from the analyses (retained sample: n control = 301, n peripartum = 356), the group difference held (Table S4), with the peripartum group reporting lower social sensitivity compared to the non-peripartum controls. The same was observed when accounting for relationship status at Time 1, which did not have a significant effect on social sensitivity (Table S5). Mental health and well-being In the sensitivity analysis controlling for educational background (Table S6), the effect of Group remained. Higher education was associated with fewer mental health symptoms and greater well-being. Similarly, the effect of Group remained significant when accounting for relationship status, which did not have a significant effect on mental health or well-being (Table S7). When excluding adolescents from the analyses, the main effect of Group remained significant for anxiety, depression and well-being. In the depression model the main effect was qualified by a higher-order three-way interaction between Group, Time, and Density (Table S8). For mental well-being, a significant two-way interaction was observed between Time and Density. No significant higher-order interactions were observed for anxiety symptoms. Simple slope analyses were used to deconstruct the higher-order interactions for depression and well-being across time. These analyses showed that, over time, higher density was associated with fewer depressive symptoms in the peripartum group, whereas it was associated with greater symptoms of depression in the non-peripartum control group (Fig. 3 , Table S9). Simple slopes analyses showed no statistically significant association between density and well-being at any timepoints. The observed pattern showed that the association was positive at T1, became negative at T2 and strengthened at T3 (Table S10). Interaction between Time, Group and Density in Adult Women Exploratory analyses To examine whether reduced social sensitivity persists beyond the peripartum, having children was included as a predictor in the model testing H1a. Results showed that the effect of Group remained significant and having children showed an independent main effect, with those reporting having children in the household, reporting lower social sensitivity than individuals without children (Table S11). Similarly, having children in the household showed a significant main effect on depressive symptoms, with those reporting having children in the household, reporting fewer symptoms of depression (Table S12). Discussion While the peripartum is a period marked by changes in social behaviour and social focus, little is known about the impact of these changes on maternal mental health and well-being. Here, longitudinal data on social networks and social sensitivity captured social re-orientation during the peripartum period and its association with mental health. Social re-orientation was reflected in reduced social sensitivity, and greater network density, emotional closeness and family:friends ratio of peripartum compared to non-peripartum control women. Analyses of the association of the social network characteristics with mental health and well-being showed that peripartum women reported on average lower levels of anxiety and depressive symptoms and greater well-being compared to non-peripartum control women. However, network indices only significantly interacted with group status to predict symptoms of depression when excluding adolescents from the sample. These results provide preliminary evidence of a shift towards family-oriented environments and support the theoretical framework suggesting that as focus shifts towards the offspring, mothers seek contact with their child and stable close relationships (i.e. family) ( 15 ). Although social sensitivity is an individual trait, which is a risk factor for mental health across the lifespan ( 26 ), our findings show this might be reduced during the peripartum, conferring a protective advantage as women re-orient toward a novel source of social affection and valuation. The observed differences in mental health symptoms and well-being between the two groups align with previous research showing that maternal psychological well-being peaks from pregnancy to postpartum, remaining higher than that of nulliparous control in the same period of time, and then decreasing ( 58 ). Additionally, emotionally closer networks were associated with greater well-being and fewer symptoms of depression. This supports previous research showing that social connections are protective for well-being ( 59 ). The finding that, when limiting the sample to adult women, higher density was associated with fewer depressive symptoms in the peripartum group and more symptoms in controls, suggests that the orientation towards a closely-knit, family-related environment can be protective during the peripartum but not outside this period. During the peripartum, contact with the offspring and stable close relationships can be a source of well-being ( 15 , 32 , 33 ). Outside the peripartum, instead, diverse group affiliations (i.e., lower interconnectedness/less dense networks) have been shown to be protective ( 60 ). The impact of COVID-related social restrictions on social interaction then, may have particularly affected those with very dense friendship networks, who were additionally excluded from their groups due to the same restrictions. This effect of density on depressive symptoms, is in line with social theories of depression (e.g., social rank theory; social risk hypothesis) that argue individuals at-risk of depression are particularly sensitive to social group in- and exclusion ( 61 – 63 ). Together, these findings suggest that network composition can promote or adversely impact mental health, in particular symptoms of depression, differently at different developmental stages. Our exploratory analyses examining whether the observed reductions in social sensitivity lasted beyond the peripartum period showed that those who have children in the household report lower social sensitivity than those who do not. Although this effect is smaller than the effect of group, this result suggests that reduced social sensitivity may last beyond the peripartum. Moreover, analyses showed that those who reported having children in the household reported fewer symptoms of depression. These results align with previous studies indicating that the experience of pregnancy, childbirth and caregiving can lead to fundamental long-lasting changes for women (e.g. ( 14 , 64 , 65 )). While the impact of the mother-child relationship on child health and development has been long investigated ( 66 , 67 ), the present study highlights how the shift in social focus towards the child can impact maternal well-being as well. The finding that, on average, women in the peripartum group reported better mental health, does not challenge the well-documented vulnerability to mental health problems during this period (e.g. ( 55 , 68 )). Instead, it suggests that for many women the peripartum is also a period with potential mental health benefits. In a larger, cross-sectional sample from the CORAL study, it was found that although anxiety and depressive symptoms were lower in pregnant compared to matched case-control women, the effect of COVID stress on mental health was greater for the pregnant group ( 69 ), indicating greater susceptibility to mental health risk factors for peripartum women. In the same line, our findings can be understood in light of the heightened plasticity that characterises this period ( 9 – 11 ). Our results suggest that, as for adolescents, the impact of the introduction of a new social target during the peripartum may be two-fold. Although the peripartum increases the exposure to mental health risk factors and perinatal stressors ( 70 ), including many infant-related stressors such as crying ( 71 ) and sleep deprivation ( 72 ), it may also protect mental well-being when reducing the sensitivity to social rejection and leading to emotionally closer relationships and closely-knit social environments. It is noteworthy that the data was collected during the COVID-19 pandemic, when social interactions were naturally disrupted and interfered with, making this social network analysis a representation of a very specific time. However, the inclusion of a control group allows for inferring differences in social orientation between peripartum and non-peripartum women. Future research should examine these associations across longer time intervals to understand whether reduced social sensitivity is a gain for women’s well-being in the long term in line with the preliminary evidence of the present findings. Conclusions In sum, this study captures the social re-orientation process during the peripartum and provides a more nuanced picture of risks and opportunities during the peripartum period. The findings provide evidence that the shift in social focus towards the pregnancy and then the child might be protective for maternal well-being, by reducing sensitivity to peer rejection and leading to emotionally closer and closely-knit environments. As maternal mental health remains a global concern, using a clinical and developmental perspective to examine the impact of peripartum changes on maternal well-being, are essential to inform mental health prevention and intervention efforts. Declarations Ethics approval and consent to participate All participants provided their consent to participate in the research. The study protocol was approved by the University of New South Wales Human Research Ethics Committee (HC200287) and was performed in accordance with the 1964 Declaration of Helsinki and its later amendments. Clinical trial number: not applicable. Consent for publication Not applicable. Availability of data and materials For the full list of study measures please refer to (39). The data and materials are currently not publicly available. De-identified data and analyses script will be made available upon publication, they are accessible for review through a private link here: https://tinyurl.com/y2n7vmf3. Competing interests The authors declare that they have no competing interests. Funding The CORAL study was funded by the UNSW COVID-19 Rapid Response initiative. FC is funded by a UNSW Tuition Fee Scholarship (RSRE7059/ RSRE7081), and the ANID Scholarship grant for Doctorate studies abroad (72250067) by the Government of Chile. SS is funded by an Australian Research Council Discovery Early Career Researcher Award (DE240101039). The funding sources did not have any involvement in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication. Authors' contributions FC and SS conceptualized and designed the study. FC and MM analysed data and drafted results. FC drafted the manuscript and SS substantially revised it. All authors read and approved the final manuscript. Acknowledgements Not applicable. References Fawcett EJ, Fairbrother N, Cox ML, White IR, Fawcett JM. The Prevalence of Anxiety Disorders During Pregnancy and the Postpartum Period: A Multivariate Bayesian Meta-Analysis. J Clin Psychiatry. 2019;80(4). 10.4088/JCP.18r12527 . Wang Z, Liu J, Shuai H, Cai Z, Fu X, Liu Y, et al. Mapping global prevalence of depression among postpartum women. Transl Psychiatry. 2021;11(1):543. 10.1038/s41398-021-01663-6 . Astbury L, Pinnington DM, Milgrom J, Bei B. The longitudinal trajectory of depression and anxiety across the perinatal period. J Affect Disord. 2025;370:1–8. 10.1016/j.jad.2024.10.080 . Vanwetswinkel F, Bruffaerts R, Arif U, Hompes T. The longitudinal course of depressive symptoms during the perinatal period: A systematic review. J Affect Disord. 2022;315:213–23. 10.1016/j.jad.2022.06.087 . Eberhard-Gran M, Tambs K, Opjordsmoen S, Skrondal A, Eskild A. A comparison of anxiety and depressive symptomatology in postpartum and non-postpartum mothers. Soc Psychiatry Psychiatr Epidemiol. 2003;38(10):551–6. 10.1007/s00127-003-0679-3 . Suenaga H. Comparison of response options and actual symptom frequency in the Japanese version of the Edinburgh Postnatal Depression Scale in women in early pregnancy and non-pregnant women. BMC Pregnancy Childbirth. 2022;22(1):937. 10.1186/s12884-022-05257-y . Zhou Y, Shi H, Liu Z, Peng S, Wang R, Qi L, et al. The prevalence of psychiatric symptoms of pregnant and non-pregnant women during the COVID-19 epidemic. Transl Psychiatry. 2020;10(1):319. 10.1038/s41398-020-01006-x . Pereira AT, Marques M, Soares MJ, Maia BR, Bos S, Valente J, et al. Profile of depressive symptoms in women in the perinatal and outside the perinatal period: similar or not? J Affect Disord. 2014;166:71–8. 10.1016/j.jad.2014.04.008 . Pawluski JL, Hoekzema E, Leuner B, Lonstein JS. Less can be more: Fine tuning the maternal brain. Neurosci Biobehav Rev. 2022;133:104475. 10.1016/j.neubiorev.2021.11.045 . Glynn LM, Howland MA, Fox M. Maternal programming: Application of a developmental psychopathology perspective. Dev Psychopathol. 2018;30(3):905–19. 10.1017/S0954579418000524 . Howland MA. Recalibration of the stress response system over adult development: Is there a perinatal recalibration period? Dev Psychopathol. 2023;35(5):2315–37. 10.1017/S0954579423000998 . Servin-Barthet C, Martínez-García M, Paternina-Die M, Marcos-Vidal L, De Martín D, Soler A, et al. Pregnancy entails a U-shaped trajectory in human brain structure linked to hormones and maternal attachment. Nat Commun. 2025;16(1):730. 10.1038/s41467-025-55830-0 . Spalek K, Straathof M, Koyuncu L, Grydeland H, Van Der Geest A, Van ‘T, Hof SR, et al. Pregnancy renders anatomical changes in hypothalamic substructures of the human brain that relate to aspects of maternal behavior. Psychoneuroendocrinology. 2024;164:107021. 10.1016/j.psyneuen.2024.107021 . Orchard ER, Rutherford HJV, Holmes AJ, Jamadar SD. Matrescence: lifetime impact of motherhood on cognition and the brain. Trends Cogn Sci. 2023;27(3):302–16. 10.1016/j.tics.2022.12.002 . Nelson EE, Jarcho JM, Guyer AE. Social re-orientation and brain development: An expanded and updated view. Dev Cogn Neurosci. 2016;17:118–27. 10.1016/j.dcn.2015.12.008 . Carmona S, Martínez-García M, Paternina‐Die M, Barba‐Müller E, Wierenga LM, Alemán‐Gómez Y, et al. Pregnancy and adolescence entail similar neuroanatomical adaptations: A comparative analysis of cerebral morphometric changes. Hum Brain Mapp. 2019;40(7):2143–52. 10.1002/hbm.24513 . Hoekzema E, Van Steenbergen H, Straathof M, Beekmans A, Freund IM, Pouwels PJW, et al. Mapping the effects of pregnancy on resting state brain activity, white matter microstructure, neural metabolite concentrations and grey matter architecture. Nat Commun. 2022;13(1). 10.1038/s41467-022-33884-8 . Mills KL, Lalonde F, Clasen LS, Giedd JN, Blakemore SJ. Developmental changes in the structure of the social brain in late childhood and adolescence. Soc Cogn Affect Neurosci. 2014;9(1):123–31. 10.1093/scan/nss113 . Lam CB, McHale SM, Crouter AC. Time With Peers From Middle Childhood to Late Adolescence: Developmental Course and Adjustment Correlates. Child Dev. 2014;85(4):1677–93. 10.1111/cdev.12235 . De Goede IHA, Branje SJT, Delsing MJMH, Meeus WHJ. Linkages Over Time Between Adolescents’ Relationships with Parents and Friends. J Youth Adolesc. 2009;38(10):1304–15. 10.1007/s10964-009-9403-2 . Foulkes L, Blakemore SJ. Is there heightened sensitivity to social reward in adolescence? Curr Opin Neurobiol. 2016;40:81–5. 10.1016/j.conb.2016.06.016 . Van Harmelen AL, Kievit RA, Ioannidis K, Neufeld S, Jones PB, Bullmore E, et al. Adolescent friendships predict later resilient functioning across psychosocial domains in a healthy community cohort. Psychol Med. 2017;47(13):2312–22. 10.1017/S0033291717000836 . Andrews JL, Ahmed SP, Blakemore SJ. Navigating the Social Environment in Adolescence: The Role of Social Brain Development. Biol Psychiatry. 2021;89(2):109–18. 10.1016/j.biopsych.2020.09.012 . Altikulaç S, Bos MGN, Foulkes L, Crone EA, Van Hoorn J. Age and Gender Effects in Sensitivity to Social Rewards in Adolescents and Young Adults. Front Behav Neurosci. 2019;13:171. 10.3389/fnbeh.2019.00171 . Minihan S, Kwok C, Schweizer S. Social rejection sensitivity and its role in adolescent emotional disorder symptomatology. Child Adolesc Psychiatry Ment Health. 2023;17(1):8. 10.1186/s13034-022-00555-x . Andrews JL, Khin AC, Crayn T, Humphreys K, Schweizer S. Measuring online and offline social rejection sensitivity in the digital age. Psychol Assess. 2022;34(8):742–51. 10.1037/pas0001136 . Røseth I, Bongaardt R, Lyberg A, Sommerseth E, Dahl B. New mothers’ struggles to love their child. An interpretative synthesis of qualitative studies. Int J Qual Stud Health Well-Being. 2018;13(1):1490621. 10.1080/17482631.2018.1490621 . Kinsley CH, Lambert KG. The Maternal Brain. Sci Am. 2006;294(1):72–9. 10.1038/scientificamerican0106-72 . Kristal MB. The Biopsychology of Maternal Behavior in Nonhuman Mammals. ILAR J. 2009;50(1):51–63. 10.1093/ilar.50.1.51 . Marshall PJ, Fox NA. The Development of Social EngagementNeurobiological Perspectives [Internet]. Oxford University Press; 2006 [cited 2025 Nov 21]. Available from: http://www.oxfordscholarship.com/view/10.1093/acprof:oso/9780195168716. 001.0001/acprof-9780195168716 doi:10.1093/acprof:oso/9780195168716.001.0001. Rosenblatt J. Psychobiology of maternal behavior: contribution to the clinical understanding of maternal behavior among humans. Acta Paediatr. 1994;83(s397):3–8. 10.1111/j.1651-2227.1994.tb13259.x . Cong S, Wang R, Fan X, Song X, Sha L, Zhu Z, et al. Skin-to‐skin contact to improve premature mothers’ anxiety and stress state: A meta‐analysis. Matern Child Nutr. 2021;17(4):e13245. 10.1111/mcn.13245 . Scime NV, Gavarkovs AG, Chaput KH. The effect of skin-to-skin care on postpartum depression among mothers of preterm or low birthweight infants: A systematic review and meta-analysis. J Affect Disord. 2019;253:376–84. 10.1016/j.jad.2019.04.101 . Wasserman S, Faust K. Social Network Analysis: Methods and Applications [Internet]. 1st ed. Cambridge University Press; 1994 [cited 2025 Dec 2]. Available from: https://www.cambridge.org/core/product/identifier/9780511815478/type/book 10.1017/CBO9780511815478 Burgette JM, Rankine J, Culyba AJ, Chu KH, Carley KM. Best Practices for Modeling Egocentric Social Network Data and Health Outcomes. HERD Health Environ Res Des J. 2021;14(4):18–34. 10.1177/19375867211013772 . Perry BL, Pescosolido BA, Borgatti SP. Egocentric Network Analysis: Foundations, Methods, and Models [Internet]. 1st ed. Cambridge University Press; 2018 [cited 2025 Oct 22]. Available from: https://www.cambridge.org/core/product/identifier/9781316443255/type/book 10.1017/9781316443255 Dembo RS, Mailick MR, Rudolph AE, Huntington N, DaWalt LS, Mitra M. Social Network Diversity and Mental Health Among Mothers of Individuals With Autism. Am J Intellect Dev Disabil. 2023;128(2):101–18. 10.1352/1944-7558-128.2.101 . Bost KK, Cox MJ, Burchinal MR, Payne C. Structural and Supportive Changes in Couples’ Family and Friendship Networks Across the Transition to Parenthood. J Marriage Fam. 2002;64(2):517–31. 10.1111/j.1741-3737.2002.00517.x . Minihan S, Orben A, Songco A, Fox E, Ladouceur CD, Mewton L, et al. Social determinants of mental health during a year of the COVID-19 pandemic. Dev Psychopathol. 2023;35(4):1701–13. 10.1017/S0954579422000396 . Spitzer RL, Kroenke K, Williams JBW, Löwe B. A Brief Measure for Assessing Generalized Anxiety Disorder: The GAD-7. Arch Intern Med. 2006;166(10):1092. 10.1001/archinte.166.10.1092 . Lutkiewicz K, Bieleninik Ł, Jurek P, Bidzan M. Psychometric properties of the generalized anxiety disorder questionnaire (GAD-7) in a polish postpartum women sample. BMC Public Health. 2024;24(1). 10.1186/s12889-024-20194-5 . Simpson W, Glazer M, Michalski N, Steiner M, Frey BN. Comparative Efficacy of the Generalized Anxiety Disorder 7-Item Scale and the Edinburgh Postnatal Depression Scale as Screening Tools for Generalized Anxiety Disorder in Pregnancy and the Postpartum Period. Can J Psychiatry. 2014;59(8):434–40. 10.1177/070674371405900806 . Kroenke K, Spitzer RL, Williams JBW. Patient Health Questionnaire-9 [Internet]. 2011 [cited 2025 Jun 6]. Available from: https://doi.apa.org/doi/ 10.1037/t06165-000 doi:10.1037/t06165-000. Wang L, Kroenke K, Stump TE, Monahan PO. Screening for perinatal depression with the Patient Health Questionnaire depression scale (PHQ-9): A systematic review and meta-analysis. Gen Hosp Psychiatry. 2021;68:74–82. 10.1016/j.genhosppsych.2020.12.007 . Stewart-Brown S, Tennant A, Tennant R, Platt S, Parkinson J, Weich S. Internal construct validity of the Warwick-Edinburgh Mental Well-being Scale (WEMWBS): a Rasch analysis using data from the Scottish Health Education Population Survey. Health Qual Life Outcomes. 2009;7(1):15. 10.1186/1477-7525-7-15 . Bates D, Mächler M, Bolker B, Walker S. Fitting Linear Mixed-Effects Models Using lme4. J Stat Softw. 2015;67(1). 10.18637/jss.v067.i01 . Kuznetsova A, Brockhoff PB, Christensen RHB. lmerTest Package: Tests in Linear Mixed Effects Models. J Stat Softw. 2017;82(13). 10.18637/jss.v082.i13 . Lenth RV, Piaskowski J. emmeans: Estimated Marginal Means, aka Least-Squares Means [Internet]. 2017 [cited 2026 Mar 31]. p. 2.0.2. Available from: https://CRAN.R-project.org/package=emmeans 10.32614/CRAN.package.emmeans Ben-Shachar M, Lüdecke D, Makowski D. effectsize: Estimation of Effect Size Indices and Standardized Parameters. J Open Source Softw. 2020;5(56):2815. 10.21105/joss.02815 . Lüdecke D, Ben-Shachar M, Patil I, Makowski D, Extracting. Computing and Exploring the Parameters of Statistical Models using R. J Open Source Softw. 2020;5(53):2445. 10.21105/joss.02445 . Wickham H. ggplot2: elegant graphics for data analysis. Second edition. Cham: Springer international publishing; 2016. 1 p. (Use R!). Wickham H, Chang W, Henry L, Pedersen TL, Takahashi K, Wilke C et al. ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics [Internet]. 2007 [cited 2025 Dec 5]. p. 4.0.1. Available from: https://CRAN.R-project.org/package=ggplot2 10.32614/CRAN.package.ggplot2 Lüdecke D. ggeffects: Tidy Data Frames of Marginal Effects from Regression Models. J Open Source Softw. 2018;3(26):772. 10.21105/joss.00772 . Chlapecka A, Kagstrom A, Cermakova P. Educational attainment inequalities in depressive symptoms in more than 100,000 individuals in Europe. Eur Psychiatry. 2020;63(1):e97. 10.1192/j.eurpsy.2020.100 . Yang K, Wu J, Chen X. Risk factors of perinatal depression in women: a systematic review and meta-analysis. BMC Psychiatry. 2022;22(1):63. 10.1186/s12888-021-03684-3 . Sawyer SM, Azzopardi PS, Wickremarathne D, Patton GC. The age of adolescence. Lancet Child Adolesc Health. 2018;2(3):223–8. 10.1016/S2352-4642(18)30022-1 . Grundström J, Konttinen H, Berg N, Kiviruusu O. Associations between relationship status and mental well-being in different life phases from young to middle adulthood. SSM - Popul Health. 2021;14:100774. 10.1016/j.ssmph.2021.100774 . Kuipers YJ, Beeck EV, Cijsouw A, Van Gils Y. The impact of motherhood on the course of women’s psychological wellbeing. J Affect Disord Rep. 2021;6:100216. 10.1016/j.jadr.2021.100216 . Wickramaratne PJ, Yangchen T, Lepow L, Patra BG, Glicksburg B, Talati A et al. Social connectedness as a determinant of mental health: A scoping review. Pan X, editor. PLOS ONE. 2022;17(10):e0275004. 10.1371/journal.pone.0275004 Jetten J, Haslam C, Haslam SA, Dingle G, Jones JM. How Groups Affect Our Health and Well-Being: The Path from Theory to Policy. Soc Issues Policy Rev. 2014;8(1):103–30. 10.1111/sipr.12003 . Allen NB, Badcock PBT. The Social Risk Hypothesis of Depressed Mood: Evolutionary, Psychosocial, and Neurobiological Perspectives. Psychol Bull. 2003;129(6):887–913. 10.1037/0033-2909.129.6.887 . Slavich GM, Irwin MR. From stress to inflammation and major depressive disorder: A social signal transduction theory of depression. Psychol Bull. 2014;140(3):774–815. 10.1037/a0035302 . Wetherall K, Robb KA, O’Connor RC. Social rank theory of depression: A systematic review of self-perceptions of social rank and their relationship with depressive symptoms and suicide risk. J Affect Disord. 2019;246:300–19. 10.1016/j.jad.2018.12.045 . Martínez-García M, Paternina-Die M, Barba-Müller E, De Martín D, Beumala L, Cortizo R, et al. Do Pregnancy-Induced Brain Changes Reverse? The Brain of a Mother Six Years after Parturition. Brain Sci. 2021;11(2):168. 10.3390/brainsci11020168 . Pritschet L, Taylor CM, Cossio D, Faskowitz J, Santander T, Handwerker DA, et al. Neuroanatomical changes observed over the course of a human pregnancy. Nat Neurosci. 2024;27(11):2253–60. 10.1038/s41593-024-01741-0 . Feldman R. The Neurobiology of Human Attachments. Trends Cogn Sci. 2017;21(2):80–99. 10.1016/j.tics.2016.11.007 . Frosch CA, Schoppe-Sullivan SJ, O’Banion DD. Parenting and Child Development: A Relational Health Perspective. Am J Lifestyle Med. 2021;15(1):45–59. 10.1177/1559827619849028 . Munk-Olsen T, Maegbaek ML, Johannsen BM, Liu X, Howard LM, Di Florio A, et al. Perinatal psychiatric episodes: a population-based study on treatment incidence and prevalence. Transl Psychiatry. 2016;6(10):e919–919. 10.1038/tp.2016.190 . Songco A, Minihan S, Fox E, Ladouceur C, Mewton L, Moulds M, et al. Social and cognitive vulnerability to COVID-19-related stress in pregnancy: A case-matched-control study of antenatal mental health. J Affect Disord. 2023;325:739–46. 10.1016/j.jad.2023.01.053 . Marr MC, Graham AM, Feczko E, Nolvi S, Thomas E, Sturgeon D, et al. Maternal Perinatal Stress Trajectories and Negative Affect and Amygdala Development in Offspring. Am J Psychiatry. 2023;180(10):766–77. 10.1176/appi.ajp.21111176 . De Barbaro K, Micheletti M, Yao X, Khante P, Johnson M, Goodman S. Infant crying predicts real-time fluctuations in maternal mental health in ecologically valid home settings. Dev Psychol. 2023;59(4):733–44. 10.1037/dev0001530 . Witkowska-Zimny M, Zhyvotovska A, Isakov R, Boiko D, Nieradko-Iwanicka B. Maternal Sleeping Problems Before and After Childbirth - A Systematic Review. Int J Womens Health 2024;Volume 16:345–71. 10.2147/IJWH.S446490 Footnotes We use the term woman to refer to birthing people, as this will be more parsimonious in terms of word count. However, we acknowledge that people of any gender can be birthing parents. Additional Declarations No competing interests reported. Supplementary Files BMCpsychologySupplementarymaterial.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 07 May, 2026 Reviewers invited by journal 07 May, 2026 Editor assigned by journal 07 May, 2026 Editor invited by journal 28 Apr, 2026 Submission checks completed at journal 27 Apr, 2026 First submitted to journal 27 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9490400","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":638071635,"identity":"ebc874ce-2a74-4f6c-9318-0545bf0db934","order_by":0,"name":"Florencia Canessa","email":"","orcid":"","institution":"University of New South Wales","correspondingAuthor":false,"prefix":"","firstName":"Florencia","middleName":"","lastName":"Canessa","suffix":""},{"id":638071636,"identity":"f93f9698-69b0-4e8c-bd5c-eb43125132a5","order_by":1,"name":"Martín Miranda","email":"","orcid":"","institution":"University of New South Wales","correspondingAuthor":false,"prefix":"","firstName":"Martín","middleName":"","lastName":"Miranda","suffix":""},{"id":638071637,"identity":"b29475bc-3a3d-48ba-b17b-10d95ec10a55","order_by":2,"name":"Susanne Schweizer","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYJACZiDmAWLGB1ABA6K1MMOUEqcFBNgkiNIi38D+8HNhm42MfHvvs2reHXWJDezN2yQYag7j1GJwgMdYemZbGg9jz3Gz27xnDic28Bwrk2A4hkcLAw8bM++2wzzMEmlst3nbDuQ2SOSYSTCw4dYCdNgzoJb/PGzyz9iKedvqchvk3wC1/MOtheEAgxlQywEeHgk2oHVtzEBbeMwkGNvwOOww0C+8/5J5JHjSmCXnth2ub+NJK7ZI7EvH7bD29oefec7Y2cu3H2P88Latzpif/fDGGx++WeN2GDO6ABuISMCtYRSMglEwCkYBEQAAto1FN1iSkysAAAAASUVORK5CYII=","orcid":"","institution":"University of New South Wales","correspondingAuthor":true,"prefix":"","firstName":"Susanne","middleName":"","lastName":"Schweizer","suffix":""}],"badges":[],"createdAt":"2026-04-22 03:53:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9490400/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9490400/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109332780,"identity":"e05b3c8b-74b0-411f-b0f0-6533f774f2cb","added_by":"auto","created_at":"2026-05-15 16:21:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":121214,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eDistribution of mean Density, Closeness and Family:friends ratio among peripartum and non-peripartum controls\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9490400/v1/32d7a4bea8545dc95ffaee61.png"},{"id":109332779,"identity":"4f64214c-13ed-478b-89d2-c1c43fa68433","added_by":"auto","created_at":"2026-05-15 16:21:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":142404,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eAnxiety and Depressive symptoms, and Mental Well-being among peripartum and non-peripartum controls\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9490400/v1/0065d6aaca073944a2e47432.png"},{"id":109332782,"identity":"33133579-e9ee-47c2-9658-c0918f39749a","added_by":"auto","created_at":"2026-05-15 16:21:39","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":78810,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eInteraction between Time, Group and Density in Adult Women\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9490400/v1/03a911cc560896ea2921aff0.png"},{"id":109332798,"identity":"605c8710-587e-422d-a8ef-0d877cbd660e","added_by":"auto","created_at":"2026-05-15 16:21:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":745016,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9490400/v1/09a95254-1598-4672-991f-204585746bc2.pdf"},{"id":109332778,"identity":"6519662f-b984-4854-8d09-09446c9a462f","added_by":"auto","created_at":"2026-05-15 16:21:37","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":89666,"visible":true,"origin":"","legend":"","description":"","filename":"BMCpsychologySupplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-9490400/v1/a9029a027b621d57be1bbdb2.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Social determinants of perinatal mental health and well-being: A social network analysis","fulltext":[{"header":"Background","content":"\u003cp\u003eThe peripartum period, the time from conception to one year after birth, is a period of heightened vulnerability for the onset and recurrence of mental health problems in women\u003csup\u003e1\u003c/sup\u003e, with as many as one in five experiencing anxiety (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) and/or depression (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). However, while average symptoms of anxiety and depression tend to show increases across pregnancy and the early postpartum period (e.g., (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)), analyses of symptom trajectories show that the largest group of people report consistently low symptoms despite going through a period of major biological and social changes (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). What\u0026rsquo;s more, very few studies have directly compared symptoms in women in the peripartum to those outside the peripartum. Studies that have, largely show lower symptoms in peripartum compared to non-peripartum women (\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Understanding determinants of good mental health and well-being during the peripartum is essential to better inform mental health prevention efforts and identify novel avenues for intervention during this period.\u003c/p\u003e \u003cp\u003eGrowing evidence suggests that the peripartum is not only a time of vulnerability, but also a time of heightened plasticity and opportunity (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). The novel environmental conditions and experiences of pregnancy, childbirth and the postpartum period - from physiological changes to caring for the child - may confer opportunities for adaptation (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), the acquisition of new skills and maternal behaviours (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), as well as cognitive advantages (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Whether these adaptations could account for the large number of individuals who show persistently low levels of anxiety and depression across the peripartum period remains poorly understood.\u003c/p\u003e\n\u003ch3\u003eSocial (re)orientation\u003c/h3\u003e\n\u003cp\u003eArguably, a major (yet little researched) change during the peripartum, that may provide mental health benefits, is the social re-orientation towards the foetus and later the baby. Social re-orientation, the shift in social focus (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), has been more extensively studied in adolescence, another developmental period associated with significant hormonal changes, as well as changes in brain structure and function that are of similar magnitude to those observed during the peripartum (\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Considering social re-orientation from a lifespan perspective can provide insights into its potential role in maternal well-being.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSocial re-orientation from a lifespan perspective\u003c/h2\u003e \u003cp\u003eDuring adolescence, individuals become more independent from caregivers and re-orient their social behaviours and attention towards peers (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). As their social environment expands beyond the family, the relationships with peers become increasingly rewarding and a relevant source of emotional support (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), and stronger predictor of well-being than the relationships with caregivers (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). At the same time, however, the re-orientation towards peers can be a source of risk for mental health problems, as adolescents become more sensitive to social information in their environment, especially to social rejection (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Social rejection sensitivity is elevated during adolescence (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) and a factor associated with increased risk of anxiety and depression across the lifespan (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Together, these findings suggest that the impact of social re-orientation towards peers in adolescence is two-fold: It is protective when it leads to strong social peer relationships but can also be a source of risk by elevating social sensitivity towards peer evaluation.\u003c/p\u003e \u003cp\u003eIn the peripartum, instead, social sensitivity to peer evaluation may decrease, as a novel source of social affection and valuation is introduced into the parent\u0026rsquo;s life. During this period, women \u0026ndash; and arguably non-birthing partners though they are beyond the scope of this article \u0026ndash; re-orient their social behaviours and attention towards the baby. While affection can take time to emerge (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), social orientation towards the baby is innate. Immediately following delivery, females of all species of mammals \u0026ndash; likely triggered by hormones \u0026ndash; shift their behaviour towards the care and the survival of their offspring (\u003cspan additionalcitationids=\"CR29 CR30\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). There is evidence that physical social behaviours, such as physical contact, benefit maternal well-being (e.g., (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e)). Little is known, however, about the impact of psychological changes following social re-orientation, including potential changes in social sensitivity, on maternal well-being.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSocial networks to study social re-orientation\u003c/h3\u003e\n\u003cp\u003eOne way to explore changes in the social environment is through the analysis of social networks. Social networks are a way of representing social connections as a set of \u003cem\u003enodes\u003c/em\u003e (actors) and the \u003cem\u003eties\u003c/em\u003e (relationships) between them (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). By identifying relevant \u003cem\u003ealters\u003c/em\u003e, individuals to whom people relate, and analysing the composition of networks and the characteristics of these relationships (e.g. emotional closeness), social network analyses can capture changes in individuals\u0026rsquo; social environments and how these interact with behavioural and health outcomes (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePreliminary evidence examining social networks and maternal well-being has mainly focused on capturing the social support available to mothers (e.g., (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e)). While not using formal network analyses, but instead deriving network size, frequency of contact and satisfaction with social contacts from 137 first-time parent dyads, one study showed that size and satisfaction with friends\u0026rsquo; networks decreased from the antenatal period to 24 months postpartum, whereas family networks\u0026rsquo; size and satisfaction showed an initial decrease early in the postpartum and then increased (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Larger family networks and greater satisfaction with family and friend networks were associated with fewer symptoms of depression (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). While providing further evidence for the importance of social support, these findings fail to capture the process of social re-orientation during the peripartum.\u003c/p\u003e\n\u003ch3\u003eThe current study\u003c/h3\u003e\n\u003cp\u003eThe current study applied network analyses to capture changes in the social environment of women during the peripartum period, including changes in the interconnectedness (or density), emotional closeness and composition of their networks, reflecting social (re-) orientation. Adopting a matched case-control design, these changes and their association with individuals\u0026rsquo; mental health and well-being were tracked across a six-month period and compared to social network changes of age- and country-matched non-peripartum women. The adoption of a matched case-control design was particularly important in the context of the current study, as data was collected thrice in three-month intervals during the COVID-19 pandemic, which had considerable impacts on people\u0026rsquo;s social connections. Women in the peripartum and controls would have been similarly affected, allowing us to infer that any group differences observed are due to peripartum status rather than the pandemic. To examine whether social re-orientation during the peripartum leads to reduced social sensitivity, the current study also measured individual differences in social sensitivity. Specifically, the study tested the following hypotheses: Social re-orientation among peripartum compared to non-peripartum control women would be reflected in reduced social sensitivity (H1a) and differences in social networks, with peripartum women reporting greater density, closeness and a higher family:friends ratio in their social networks compared to the control group, indexing a re-orientation towards the family environment (H1b); and this same pattern would be observed within the peripartum from pregnancy to postpartum (H1c). \u003cem\u003eH2\u003c/em\u003e: These structural (i.e., degree and family:friends ratio) and functional (i.e., emotional closeness) network changes would be associated with lower anxiety and depressive symptoms and greater well-being in peripartum compared to control women (H2a) and these association would strengthen within the peripartum period from pregnancy to postpartum (H2b).\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eData was analysed from the COVID-19 Risks Across the Lifespan (CORAL) study (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.thecoralstudy.com/\u003c/span\u003e\u003cspan address=\"https://www.thecoralstudy.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). A three-wave longitudinal online study of the cognitive, social and psychological functioning during the COVID-19 pandemic that ran between May 2020 and April 2021. The study protocol was approved by the University of New South Wales Human Research Ethics Committee (HC200287).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eProcedure\u003c/h2\u003e \u003cp\u003eParticipants were recruited via social media and advertisement in mothers\u0026rsquo; groups. After providing informed consent, participants completed an online survey at three assessment timepoints: baseline (T1), three months (T2) and six months (T3) follow-up. Participants responded to a series of questions concerning their pregnancy, COVID-19, mental health and well-being, and social networks. At each timepoint, every 100th participant was rewarded with an AUD\u003cspan\u003e$\u003c/span\u003e100 (GBP\u0026pound;50 or US\u003cspan\u003e$\u003c/span\u003e60) Amazon voucher, and those participants that completed T2 and T3 were compensated with an AUD \u003cspan\u003e$\u003c/span\u003e10 (GBP\u0026pound;5/ USD\u003cspan\u003e$\u003c/span\u003e6) voucher.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eAt T1, 742 participants from the CORAL sample (N\u0026thinsp;=\u0026thinsp;3,208) reported being pregnant. Participants were included in the peripartum subsample of this study if they met the following inclusion criteria: (a) were pregnant at T1 as verified by the screening question and the provision of a due date, (b) were 17\u0026ndash;45 years old at T1 and (c) completed the social network questions at least once. A sample of eligible non-peripartum participants was randomly selected. Participants were eligible for inclusion in the non-peripartum sample if they: (a) identified as female and reported consistent gender across timepoints, (b) were 17\u0026ndash;45 years old at T1, (c) completed the social network alters question at least once, and (d) were not pregnant at all time points. From this group, the sample of non-peripartum control women was then selected. Participants were paired with a pregnant case based on exact matching by country, followed by greedy nearest-neighbour matching by age. Prioritisation was based on the number of completed time points. For each participant in the peripartum group, matched cases in the same country of residence were found. Next, from the pool of cases with more completed time points, we selected the case with the closest age. This resulted in two subsamples of similar ages and exact same country of residence including, 378 peripartum women (\u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eage\u003c/em\u003e\u003c/sub\u003e= 32.21 years, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.66) and 378 non-peripartum control women (\u003cem\u003eM\u003c/em\u003e\u003csub\u003eage\u003c/sub\u003e= 31.49 years, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;7.51) who met all inclusion criteria. Samples differ in their educational background (see Table\u0026nbsp;1).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eTable\u0026nbsp;1\u003c/p\u003e \u003cp\u003e\u003cem\u003eSample Demographics\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePeripartum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et test / \u003cem\u003eχ\u003c/em\u003e\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.21 (4.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.49 (7.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e308 (81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e271 (72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e13.23***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProfessional/ Vocational training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54 (14%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53 (14%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnited States of America\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104 (28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e104 (28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnited Kingdom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160 (42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e160 (42%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAustralia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e114 (30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e114 (30%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCaucasian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e328 (87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e308 (81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAfrican\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAboriginal or Torres Strait Islander\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrefer not to say\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHave children in the house\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e181 (48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e200 (53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNote\u003c/em\u003e. Demographic characteristics of the sample. *** \u003cem\u003ep\u003c/em\u003e \u0026lt; .001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cp\u003eOnly the measures used in the analyses for the present study are reported in the following section:\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSocial Networks\u003c/h2\u003e \u003cp\u003eParticipants provided information about their social networks. Participants were asked to endorse between one and six \u0026lsquo;\u003cem\u003ealters\u003c/em\u003e\u0026rsquo;, people with whom they spent most of their free time with over the past year before COVID-19 at T1, and over the past month in T2 and T3. For each alter, participants provided information about the nature of their relationship (e.g. friend, husband), how close they felt and how the alters in their network were related. Based on this information, the following parameters were obtained:\u003c/p\u003e \u003cp\u003e \u003cb\u003eDensity\u003c/b\u003e. Density reflects the number of connections within a network. It is computed by dividing the number of ties in a network by all possible ties in the network, using the following formula:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\frac{n+\\:aa}{n+n\\left(\\frac{n-1}{2}\\right)}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere \u003cem\u003en\u003c/em\u003e is the number of alters in the network, and \u003cem\u003eaa\u003c/em\u003e the number of ties between alters. A denser network would indicate that the network's members tend to know each other and that the network is oriented towards more closely knit, family-type relationships.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCloseness.\u003c/b\u003e Closeness reflects the strength of the connections within a network. For each alter, participants indexed how close they feel to that person from 1 (\u0026ldquo;Not close at all\u0026rdquo;) to 10 (\u0026ldquo;Extremely close / closer than any other person I know\u0026rdquo;). Closeness was computed as the average strength of all the ties in the network. Higher closeness reported in the network would reflect emotionally closer social environments.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFamily:friends ratio\u003c/b\u003e. Family:friends ratio reflects the composition of a network. It was computed as the proportion of alters who are family members, compared to those who are friends. When participants did not report any friend alter, the variable was computed as the number of family members. A higher family:friends ratio would indicate a prioritisation of time spent with family members over friends.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSocial Sensitivity\u003c/h2\u003e \u003cp\u003eThe 18-item Online and Offline Social Sensitivity Scale (O2S3) (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) was used to assess social sensitivity and was administered only at T1. The scale requires participants to index the extent to which they agree with statements describing feelings towards both online and offline interactions (e.g. \u0026ldquo;I worry about being criticised for things I have said or done\u0026rdquo;), from 0 (strongly disagree) to 3 (strongly agree). The scale is psychometrically well-validated across the lifespan (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). The scale demonstrated good internal consistency (ω\u0026thinsp;=\u0026thinsp;0.92).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAnxiety symptoms\u003c/h2\u003e \u003cp\u003eThe 7-item Generalized Anxiety Disorders-7 scale (GAD-7) (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e) was used to measure symptoms of anxiety, with participants indicating how often they experienced symptoms of generalized anxiety (e.g. \u0026ldquo;Worrying too much about different things\u0026rdquo;) over the past two weeks from 0 (not at all) to 3 (nearly every day). The scale is psychometrically well-validated, including in perinatal populations (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). The scale demonstrated good internal consistency (ω\u003csub\u003eT1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.93, ω\u003csub\u003eT2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.92, ω\u003csub\u003eT3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.92).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eDepressive symptoms\u003c/h2\u003e \u003cp\u003eThe 8-item Patient Health Questionnaire (PHQ-8) (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e) was administered to measure symptoms of depression. The scale requires participants to index how often they have experienced symptoms of depression (e.g. \u0026ldquo;Feeling down, depressed or hopeless\u0026rdquo;) in the past 2 weeks from 0 (not at all) to 3 (nearly every day). The scale is psychometrically well-validated, including for use in the perinatal period (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). The scale demonstrated good internal consistency (ω\u003csub\u003eT1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.90, ω\u003csub\u003eT2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.89, ω\u003csub\u003eT3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.91).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eMental well-being\u003c/h2\u003e \u003cp\u003eThe 7-item Short Warwick-Edinburgh Mental Well-being scale (WEMWBS) (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e) was used to measure mental well-being. The scale requires participants to report how often they experienced certain feelings or thoughts (e.g. \u0026ldquo;I\u0026rsquo;ve been dealing with problems well\u0026rdquo;) over the past two weeks from 1 (none of the time) to 5 (all of the time). The scale is psychometrically well-validated (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). The scale demonstrated good internal consistency (ω\u003csub\u003eT1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.87, ω\u003csub\u003eT2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.87, ω\u003csub\u003eT3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.87).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eAll analyses were conducted in R (version 4.3.1). Linear mixed-effects models were conducted using the lme4 (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e), lmerTest (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e) and emmeans (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e) packages. Effect sizes and confidence intervals were obtained using effectsize (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e) and parameters (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e) packages. Coefficients were standardised, with the exception of time, which was recoded as 0, 1, 2 for interpretability. Plot figures were made using ggplot2 (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e) and ggeffects (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e) packages. Missing at random was assumed for all analyses. For further detail on missing data, please refer to the supplementary material (S1).\u003c/p\u003e \u003cp\u003eGroup differences in social sensitivity were investigated with a linear regression. Linear mixed effect models were fitted to investigate group differences in social network indices (i.e., degree, closeness, family:friends ratio) and whether these vary across time.\u003c/p\u003e \u003cp\u003eThe association of social re-orientation with mental well-being was tested separately for each mental well-being outcome (anxiety symptoms, depressive symptoms and mental well-being). For each outcome, a linear mixed-effect model was fitted to investigate the association of the outcome with social network measures over time and between groups. To limit overfitting due to the high multi-collinearity between the structural network indices density and family:friend ratio, only density and closeness were used as network indices.\u003c/p\u003e \u003cp\u003eThese analyses were repeated in sensitivity analyses that tested whether any observed effects would hold, when controlling for potential confounds. First, to control for the observed group differences in education at baseline (Table\u0026nbsp;1), and because educational attainment has been associated with mental health status (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e), educational background was included as a covariate in the models predicting mental health. Second, as social re-orientation also occurs during adolescence (10\u0026ndash;24 years; (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e)), and given the observed age-related differences in mental health in this cohort, with young people reporting poorer mental health (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), sensitivity analyses were conducted restricting the sample to participants aged 25 or over in the models predicting mental health. This restriction prevented the overlap of two developmental periods of marked social changes. Third, being in a relationship may confer mental health benefits (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e), especially during periods of social isolation. While relationship status was not assessed in CORAL, relationship status was inferred from the social network composition at each timepoint. If participants indexed any of the members of their network as Husband/Wife or Boyfriend/Girlfriend they were coded as being in a relationship (yes/no). This variable was included as a covariate in the models predicting mental health. This inclusion would help elucidate whether differences in mental health between the peripartum and non-peripartum control groups are also associated with relationship status.\u003c/p\u003e \u003cp\u003eFinally, an exploratory analysis was conducted to examine whether these reductions in social sensitivity lasted beyond the peripartum. While the number of children someone had was not captured for non-pregnant participants in CORAL, there was a question on participants\u0026rsquo; household composition. Those who reported children in the household were classified as mothers. Repeating the social sensitivity analyses with maternal status as predictor would allow preliminary inferences on lasting reductions in social sensitivity. Additionally, testing the association of social re-orientation with well-being using maternal status as a predictor could provide preliminary evidence on the lasting protective effects of social re-orientation during the peripartum.\u003c/p\u003e \u003cp\u003eAnalyses testing the association of social re-orientation with mental well-being were Bonferroni corrected with \u003cem\u003eα\u003c/em\u003e\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;.016 to account for the inclusion of three outcomes of interest (i.e., anxiety and depressive symptoms, mental well-being).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eMeans and standard deviations of the analysed variables (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) as well as bivariate correlations between variables (Table S2) can be found in the supplementary materials.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eSocial sensitivity in peripartum women and non-peripartum control women\u003c/h2\u003e \u003cp\u003eAs predicted, the peripartum group (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;22.38) reported significantly lower levels of social sensitivity than the non-peripartum control group (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;26.39); \u003cem\u003eβ\u003c/em\u003e = -4.01, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.85, \u003cem\u003et\u003c/em\u003e (577)\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;4.72, \u003cem\u003ed\u003c/em\u003e =\u0026thinsp;.39 [.23, .56], \u003cem\u003ep\u003c/em\u003e \u0026lt; .001.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eSocial re-orientation in peripartum women and non-peripartum control women over time\u003c/h2\u003e \u003cp\u003eLinear-mixed effects models yielded a significant main effect of both Group and Time on the three social network variables, with the peripartum group showing greater network density, closeness and family:friends ratio (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and the indices increasing over time (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The effect of Group did not interact with Time suggesting the differences in network structure and function observed in peripartum vs. control women remained stable across the three timepoints (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eDistribution of mean Density, Closeness and Family:friends ratio among peripartum and non-peripartum controls\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eLinear mixed-effects models investigating group differences in social network indices and their variation over time.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eDensity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eCloseness\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e \u003cp\u003eFamily:friends Ratio\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003e95% CI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003e95% CI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003e95% CI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Intercept)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.71\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e[ 0.69, 0.73]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001***\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e7.28\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e[ 7.13, 7.43]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001***\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.58\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e[ 1.39, 1.77]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001***\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e[ 0.03, 0.08]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001***\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e[ 0.30, 0.71]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001***\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.32\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.14\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e[ 0.06, 0.59]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e.018*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e[ 0.02, 0.05]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001***\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.27\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e[ 0.17, 0.38]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001***\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.28\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e[ 0.15, 0.40]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001***\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup \u0026times; Time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[-0.01, 0.03]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[-0.15, 0.20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e[-0.08, 0.33]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.247\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e\u003cem\u003eNote.\u003c/em\u003e *\u003cem\u003ep\u003c/em\u003e \u0026lt; .05, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; .001\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSocial orientation as a predictor of well-being in peripartum women and non-peripartum women over time.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe linear mixed models examining whether differential network properties were differentially associated with mental health and well-being across groups and time showed a main effect of Group, with peripartum women reporting lower anxiety and depression and greater well-being (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eAnxiety and Depressive symptoms, and Mental Well-being among peripartum and non-peripartum controls.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eCloseness also showed a significant main effect for depression and mental well-being, with closer networks being associated with greater well-being and fewer symptoms of depression. No significant effects of Time or Density or interactions were observed (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eLinear mixed-effects models for all well-being outcomes including Density, Closeness, Group, and Time as covariates\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eAnxiety model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eDepression model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e \u003cp\u003eMental well-being model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003e95% CI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003e95% CI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003e95% CI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Intercept)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[ 8.21, 9.48]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[ 9.53, 10.84]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e20.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e[20.02, 21.10]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-2.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.45\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e[-2.90, -1.15]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001***\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e-2.43\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.46\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e[-3.33, -1.53]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001***\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.65\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.37\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e[ 0.92, 2.38]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001***\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[-0.44, 0.26]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.616\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[-0.64, 0.07]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e[-0.28, 0.37]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.785\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[-0.35, 0.68]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.531\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[-0.36, 0.69]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e[-0.36, 0.57]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.649\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCloseness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[-1.09, -0.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.042\u0026dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e-0.97\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.28\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e[-1.52, -0.43]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001***\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.74\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e[ 0.26, 1.22]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e.003*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup x Time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[-0.73, 0.55]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[-0.31, 0.99]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e[-1.17, 0.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.057\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup x Density\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[-1.53, 0.09]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[-1.03, 0.63]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e[-0.67, 0.77]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.891\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup x Closeness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[-0.54, 1.19]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[-0.38, 1.38]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e[-1.12, 0.40]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.355\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime x Density\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[-0.13, 0.65]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[-0.10, 0.69]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e[-0.62, 0.11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.169\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime x Closeness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[-0.60, 0.22]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[-0.55, 0.28]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e[-0.16, 0.59]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.262\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup x Time x Density\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[-1.04, 0.46]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.447\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[-1.62, -0.10]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.026\u0026dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e[-0.30, 1.07]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.270\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup x Time x Closeness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[ 0.01, 1.55]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.048\u0026dagger;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[-0.21, 1.36]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e[-0.79, 0.61]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e.805\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e\u003cem\u003eNote.\u003c/em\u003e \u0026dagger;\u003cem\u003ep\u003c/em\u003e \u0026lt; .05, *\u003cem\u003ep\u003c/em\u003e \u0026lt; .016, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; .001\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity Analyses\u003c/h2\u003e \u003cdiv id=\"Sec22\" class=\"Section3\"\u003e \u003ch2\u003eSocial sensitivity\u003c/h2\u003e \u003cp\u003eSensitivity analyses showed that the observed effect of social sensitivity remained significant after controlling for educational level. Higher educational level was associated with lower levels of social sensitivity (Table S3). When excluding adolescents (i.e., individuals age 24 years or younger) from the analyses (retained sample: \u003cem\u003en\u003c/em\u003e \u003csub\u003e\u003cem\u003econtrol\u003c/em\u003e\u003c/sub\u003e= 301, \u003cem\u003en\u003c/em\u003e \u003csub\u003e\u003cem\u003eperipartum\u003c/em\u003e\u003c/sub\u003e= 356), the group difference held (Table S4), with the peripartum group reporting lower social sensitivity compared to the non-peripartum controls. The same was observed when accounting for relationship status at Time 1, which did not have a significant effect on social sensitivity (Table S5).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003eMental health and well-being\u003c/h2\u003e \u003cp\u003eIn the sensitivity analysis controlling for educational background (Table S6), the effect of Group remained. Higher education was associated with fewer mental health symptoms and greater well-being. Similarly, the effect of Group remained significant when accounting for relationship status, which did not have a significant effect on mental health or well-being (Table S7).\u003c/p\u003e \u003cp\u003eWhen excluding adolescents from the analyses, the main effect of Group remained significant for anxiety, depression and well-being. In the depression model the main effect was qualified by a higher-order three-way interaction between Group, Time, and Density (Table S8). For mental well-being, a significant two-way interaction was observed between Time and Density. No significant higher-order interactions were observed for anxiety symptoms.\u003c/p\u003e \u003cp\u003eSimple slope analyses were used to deconstruct the higher-order interactions for depression and well-being across time. These analyses showed that, over time, higher density was associated with fewer depressive symptoms in the peripartum group, whereas it was associated with greater symptoms of depression in the non-peripartum control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Table S9). Simple slopes analyses showed no statistically significant association between density and well-being at any timepoints. The observed pattern showed that the association was positive at T1, became negative at T2 and strengthened at T3 (Table S10).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e \u003ch2\u003eInteraction between Time, Group and Density in Adult Women\u003c/h2\u003e \u003cdiv id=\"Sec25\" class=\"Section4\"\u003e \u003ch2\u003eExploratory analyses\u003c/h2\u003e \u003cp\u003eTo examine whether reduced social sensitivity persists beyond the peripartum, having children was included as a predictor in the model testing H1a. Results showed that the effect of Group remained significant and having children showed an independent main effect, with those reporting having children in the household, reporting lower social sensitivity than individuals without children (Table S11). Similarly, having children in the household showed a significant main effect on depressive symptoms, with those reporting having children in the household, reporting fewer symptoms of depression (Table S12).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eWhile the peripartum is a period marked by changes in social behaviour and social focus, little is known about the impact of these changes on maternal mental health and well-being. Here, longitudinal data on social networks and social sensitivity captured social re-orientation during the peripartum period and its association with mental health. Social re-orientation was reflected in reduced social sensitivity, and greater network density, emotional closeness and family:friends ratio of peripartum compared to non-peripartum control women. Analyses of the association of the social network characteristics with mental health and well-being showed that peripartum women reported on average lower levels of anxiety and depressive symptoms and greater well-being compared to non-peripartum control women. However, network indices only significantly interacted with group status to predict symptoms of depression when excluding adolescents from the sample.\u003c/p\u003e \u003cp\u003eThese results provide preliminary evidence of a shift towards family-oriented environments and support the theoretical framework suggesting that as focus shifts towards the offspring, mothers seek contact with their child and stable close relationships (i.e. family) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Although social sensitivity is an individual trait, which is a risk factor for mental health across the lifespan (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), our findings show this might be reduced during the peripartum, conferring a protective advantage as women re-orient toward a novel source of social affection and valuation. The observed differences in mental health symptoms and well-being between the two groups align with previous research showing that maternal psychological well-being peaks from pregnancy to postpartum, remaining higher than that of nulliparous control in the same period of time, and then decreasing (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). Additionally, emotionally closer networks were associated with greater well-being and fewer symptoms of depression. This supports previous research showing that social connections are protective for well-being (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe finding that, when limiting the sample to adult women, higher density was associated with fewer depressive symptoms in the peripartum group and more symptoms in controls, suggests that the orientation towards a closely-knit, family-related environment can be protective during the peripartum but not outside this period. During the peripartum, contact with the offspring and stable close relationships can be a source of well-being (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Outside the peripartum, instead, diverse group affiliations (i.e., lower interconnectedness/less dense networks) have been shown to be protective (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). The impact of COVID-related social restrictions on social interaction then, may have particularly affected those with very dense friendship networks, who were additionally excluded from their groups due to the same restrictions. This effect of density on depressive symptoms, is in line with social theories of depression (e.g., social rank theory; social risk hypothesis) that argue individuals at-risk of depression are particularly sensitive to social group in- and exclusion (\u003cspan additionalcitationids=\"CR62\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e). Together, these findings suggest that network composition can promote or adversely impact mental health, in particular symptoms of depression, differently at different developmental stages.\u003c/p\u003e \u003cp\u003eOur exploratory analyses examining whether the observed reductions in social sensitivity lasted beyond the peripartum period showed that those who have children in the household report lower social sensitivity than those who do not. Although this effect is smaller than the effect of group, this result suggests that reduced social sensitivity may last beyond the peripartum. Moreover, analyses showed that those who reported having children in the household reported fewer symptoms of depression. These results align with previous studies indicating that the experience of pregnancy, childbirth and caregiving can lead to fundamental long-lasting changes for women (e.g. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e)).\u003c/p\u003e \u003cp\u003eWhile the impact of the mother-child relationship on child health and development has been long investigated (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e), the present study highlights how the shift in social focus towards the child can impact maternal well-being as well. The finding that, on average, women in the peripartum group reported better mental health, does not challenge the well-documented vulnerability to mental health problems during this period (e.g. (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e)). Instead, it suggests that for many women the peripartum is also a period with potential mental health benefits. In a larger, cross-sectional sample from the CORAL study, it was found that although anxiety and depressive symptoms were lower in pregnant compared to matched case-control women, the effect of COVID stress on mental health was greater for the pregnant group (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e), indicating greater susceptibility to mental health risk factors for peripartum women. In the same line, our findings can be understood in light of the heightened plasticity that characterises this period (\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Our results suggest that, as for adolescents, the impact of the introduction of a new social target during the peripartum may be two-fold. Although the peripartum increases the exposure to mental health risk factors and perinatal stressors (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e), including many infant-related stressors such as crying (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e) and sleep deprivation (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e), it may also protect mental well-being when reducing the sensitivity to social rejection and leading to emotionally closer relationships and closely-knit social environments.\u003c/p\u003e \u003cp\u003eIt is noteworthy that the data was collected during the COVID-19 pandemic, when social interactions were naturally disrupted and interfered with, making this social network analysis a representation of a very specific time. However, the inclusion of a control group allows for inferring differences in social orientation between peripartum and non-peripartum women. Future research should examine these associations across longer time intervals to understand whether reduced social sensitivity is a gain for women\u0026rsquo;s well-being in the long term in line with the preliminary evidence of the present findings.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn sum, this study captures the social re-orientation process during the peripartum and provides a more nuanced picture of risks and opportunities during the peripartum period. The findings provide evidence that the shift in social focus towards the pregnancy and then the child might be protective for maternal well-being, by reducing sensitivity to peer rejection and leading to emotionally closer and closely-knit environments. As maternal mental health remains a global concern, using a clinical and developmental perspective to examine the impact of peripartum changes on maternal well-being, are essential to inform mental health prevention and intervention efforts.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eAll participants provided their consent to participate in the research. The study protocol was approved by the University of New South Wales Human Research Ethics Committee (HC200287) and was performed in accordance with the 1964 Declaration of Helsinki and its later amendments. Clinical trial number: not applicable.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eFor the full list of study measures please refer to (39). The data and materials are currently not publicly available. De-identified data and analyses script will be made available upon publication, they are accessible for review through a private link here: https://tinyurl.com/y2n7vmf3.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThe CORAL study was funded by the UNSW COVID-19 Rapid Response initiative. FC is funded by a UNSW Tuition Fee Scholarship (RSRE7059/ RSRE7081), and the ANID Scholarship grant for Doctorate studies abroad (72250067) by the Government of Chile. SS is funded by an Australian Research Council Discovery Early Career Researcher Award (DE240101039). The funding sources did not have any involvement in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026apos; contributions\u003c/h2\u003e\n\u003cp\u003eFC and SS conceptualized and designed the study. FC and MM analysed data and drafted results. FC drafted the manuscript and SS substantially revised it. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFawcett EJ, Fairbrother N, Cox ML, White IR, Fawcett JM. The Prevalence of Anxiety Disorders During Pregnancy and the Postpartum Period: A Multivariate Bayesian Meta-Analysis. J Clin Psychiatry. 2019;80(4). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4088/JCP.18r12527\u003c/span\u003e\u003cspan address=\"10.4088/JCP.18r12527\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Z, Liu J, Shuai H, Cai Z, Fu X, Liu Y, et al. Mapping global prevalence of depression among postpartum women. Transl Psychiatry. 2021;11(1):543. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41398-021-01663-6\u003c/span\u003e\u003cspan address=\"10.1038/s41398-021-01663-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAstbury L, Pinnington DM, Milgrom J, Bei B. The longitudinal trajectory of depression and anxiety across the perinatal period. J Affect Disord. 2025;370:1\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2024.10.080\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2024.10.080\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVanwetswinkel F, Bruffaerts R, Arif U, Hompes T. The longitudinal course of depressive symptoms during the perinatal period: A systematic review. J Affect Disord. 2022;315:213\u0026ndash;23. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2022.06.087\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2022.06.087\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEberhard-Gran M, Tambs K, Opjordsmoen S, Skrondal A, Eskild A. A comparison of anxiety and depressive symptomatology in postpartum and non-postpartum mothers. Soc Psychiatry Psychiatr Epidemiol. 2003;38(10):551\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00127-003-0679-3\u003c/span\u003e\u003cspan address=\"10.1007/s00127-003-0679-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuenaga H. Comparison of response options and actual symptom frequency in the Japanese version of the Edinburgh Postnatal Depression Scale in women in early pregnancy and non-pregnant women. BMC Pregnancy Childbirth. 2022;22(1):937. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12884-022-05257-y\u003c/span\u003e\u003cspan address=\"10.1186/s12884-022-05257-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou Y, Shi H, Liu Z, Peng S, Wang R, Qi L, et al. The prevalence of psychiatric symptoms of pregnant and non-pregnant women during the COVID-19 epidemic. Transl Psychiatry. 2020;10(1):319. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41398-020-01006-x\u003c/span\u003e\u003cspan address=\"10.1038/s41398-020-01006-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePereira AT, Marques M, Soares MJ, Maia BR, Bos S, Valente J, et al. Profile of depressive symptoms in women in the perinatal and outside the perinatal period: similar or not? J Affect Disord. 2014;166:71\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2014.04.008\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2014.04.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePawluski JL, Hoekzema E, Leuner B, Lonstein JS. Less can be more: Fine tuning the maternal brain. Neurosci Biobehav Rev. 2022;133:104475. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neubiorev.2021.11.045\u003c/span\u003e\u003cspan address=\"10.1016/j.neubiorev.2021.11.045\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlynn LM, Howland MA, Fox M. Maternal programming: Application of a developmental psychopathology perspective. Dev Psychopathol. 2018;30(3):905\u0026ndash;19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/S0954579418000524\u003c/span\u003e\u003cspan address=\"10.1017/S0954579418000524\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHowland MA. Recalibration of the stress response system over adult development: Is there a perinatal recalibration period? Dev Psychopathol. 2023;35(5):2315\u0026ndash;37. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/S0954579423000998\u003c/span\u003e\u003cspan address=\"10.1017/S0954579423000998\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eServin-Barthet C, Mart\u0026iacute;nez-Garc\u0026iacute;a M, Paternina-Die M, Marcos-Vidal L, De Mart\u0026iacute;n D, Soler A, et al. Pregnancy entails a U-shaped trajectory in human brain structure linked to hormones and maternal attachment. Nat Commun. 2025;16(1):730. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41467-025-55830-0\u003c/span\u003e\u003cspan address=\"10.1038/s41467-025-55830-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSpalek K, Straathof M, Koyuncu L, Grydeland H, Van Der Geest A, Van \u0026lsquo;T, Hof SR, et al. Pregnancy renders anatomical changes in hypothalamic substructures of the human brain that relate to aspects of maternal behavior. Psychoneuroendocrinology. 2024;164:107021. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.psyneuen.2024.107021\u003c/span\u003e\u003cspan address=\"10.1016/j.psyneuen.2024.107021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOrchard ER, Rutherford HJV, Holmes AJ, Jamadar SD. Matrescence: lifetime impact of motherhood on cognition and the brain. Trends Cogn Sci. 2023;27(3):302\u0026ndash;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.tics.2022.12.002\u003c/span\u003e\u003cspan address=\"10.1016/j.tics.2022.12.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNelson EE, Jarcho JM, Guyer AE. Social re-orientation and brain development: An expanded and updated view. Dev Cogn Neurosci. 2016;17:118\u0026ndash;27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.dcn.2015.12.008\u003c/span\u003e\u003cspan address=\"10.1016/j.dcn.2015.12.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarmona S, Mart\u0026iacute;nez-Garc\u0026iacute;a M, Paternina‐Die M, Barba‐M\u0026uuml;ller E, Wierenga LM, Alem\u0026aacute;n‐G\u0026oacute;mez Y, et al. Pregnancy and adolescence entail similar neuroanatomical adaptations: A comparative analysis of cerebral morphometric changes. Hum Brain Mapp. 2019;40(7):2143\u0026ndash;52. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/hbm.24513\u003c/span\u003e\u003cspan address=\"10.1002/hbm.24513\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoekzema E, Van Steenbergen H, Straathof M, Beekmans A, Freund IM, Pouwels PJW, et al. Mapping the effects of pregnancy on resting state brain activity, white matter microstructure, neural metabolite concentrations and grey matter architecture. Nat Commun. 2022;13(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41467-022-33884-8\u003c/span\u003e\u003cspan address=\"10.1038/s41467-022-33884-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMills KL, Lalonde F, Clasen LS, Giedd JN, Blakemore SJ. Developmental changes in the structure of the social brain in late childhood and adolescence. Soc Cogn Affect Neurosci. 2014;9(1):123\u0026ndash;31. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/scan/nss113\u003c/span\u003e\u003cspan address=\"10.1093/scan/nss113\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLam CB, McHale SM, Crouter AC. Time With Peers From Middle Childhood to Late Adolescence: Developmental Course and Adjustment Correlates. Child Dev. 2014;85(4):1677\u0026ndash;93. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/cdev.12235\u003c/span\u003e\u003cspan address=\"10.1111/cdev.12235\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Goede IHA, Branje SJT, Delsing MJMH, Meeus WHJ. Linkages Over Time Between Adolescents\u0026rsquo; Relationships with Parents and Friends. J Youth Adolesc. 2009;38(10):1304\u0026ndash;15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10964-009-9403-2\u003c/span\u003e\u003cspan address=\"10.1007/s10964-009-9403-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFoulkes L, Blakemore SJ. Is there heightened sensitivity to social reward in adolescence? Curr Opin Neurobiol. 2016;40:81\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.conb.2016.06.016\u003c/span\u003e\u003cspan address=\"10.1016/j.conb.2016.06.016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan Harmelen AL, Kievit RA, Ioannidis K, Neufeld S, Jones PB, Bullmore E, et al. Adolescent friendships predict later resilient functioning across psychosocial domains in a healthy community cohort. Psychol Med. 2017;47(13):2312\u0026ndash;22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/S0033291717000836\u003c/span\u003e\u003cspan address=\"10.1017/S0033291717000836\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndrews JL, Ahmed SP, Blakemore SJ. Navigating the Social Environment in Adolescence: The Role of Social Brain Development. Biol Psychiatry. 2021;89(2):109\u0026ndash;18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.biopsych.2020.09.012\u003c/span\u003e\u003cspan address=\"10.1016/j.biopsych.2020.09.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAltikula\u0026ccedil; S, Bos MGN, Foulkes L, Crone EA, Van Hoorn J. Age and Gender Effects in Sensitivity to Social Rewards in Adolescents and Young Adults. Front Behav Neurosci. 2019;13:171. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fnbeh.2019.00171\u003c/span\u003e\u003cspan address=\"10.3389/fnbeh.2019.00171\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinihan S, Kwok C, Schweizer S. Social rejection sensitivity and its role in adolescent emotional disorder symptomatology. Child Adolesc Psychiatry Ment Health. 2023;17(1):8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13034-022-00555-x\u003c/span\u003e\u003cspan address=\"10.1186/s13034-022-00555-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndrews JL, Khin AC, Crayn T, Humphreys K, Schweizer S. Measuring online and offline social rejection sensitivity in the digital age. Psychol Assess. 2022;34(8):742\u0026ndash;51. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/pas0001136\u003c/span\u003e\u003cspan address=\"10.1037/pas0001136\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eR\u0026oslash;seth I, Bongaardt R, Lyberg A, Sommerseth E, Dahl B. New mothers\u0026rsquo; struggles to love their child. An interpretative synthesis of qualitative studies. Int J Qual Stud Health Well-Being. 2018;13(1):1490621. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/17482631.2018.1490621\u003c/span\u003e\u003cspan address=\"10.1080/17482631.2018.1490621\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKinsley CH, Lambert KG. The Maternal Brain. Sci Am. 2006;294(1):72\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/scientificamerican0106-72\u003c/span\u003e\u003cspan address=\"10.1038/scientificamerican0106-72\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKristal MB. The Biopsychology of Maternal Behavior in Nonhuman Mammals. ILAR J. 2009;50(1):51\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ilar.50.1.51\u003c/span\u003e\u003cspan address=\"10.1093/ilar.50.1.51\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarshall PJ, Fox NA. The Development of Social EngagementNeurobiological Perspectives [Internet]. Oxford University Press; 2006 [cited 2025 Nov 21]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.oxfordscholarship.com/view/10.1093/acprof:oso/9780195168716.\u003c/span\u003e\u003cspan address=\"http://www.oxfordscholarship.com/view/10.1093/acprof:oso/9780195168716.\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cdiv class=\"ExternalRefDOI\"\u003e001.0001/acprof-9780195168716\u003c/div\u003e doi:10.1093/acprof:oso/9780195168716.001.0001.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosenblatt J. Psychobiology of maternal behavior: contribution to the clinical understanding of maternal behavior among humans. Acta Paediatr. 1994;83(s397):3\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1651-2227.1994.tb13259.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1651-2227.1994.tb13259.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCong S, Wang R, Fan X, Song X, Sha L, Zhu Z, et al. Skin-to‐skin contact to improve premature mothers\u0026rsquo; anxiety and stress state: A meta‐analysis. Matern Child Nutr. 2021;17(4):e13245. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/mcn.13245\u003c/span\u003e\u003cspan address=\"10.1111/mcn.13245\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScime NV, Gavarkovs AG, Chaput KH. The effect of skin-to-skin care on postpartum depression among mothers of preterm or low birthweight infants: A systematic review and meta-analysis. J Affect Disord. 2019;253:376\u0026ndash;84. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2019.04.101\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2019.04.101\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWasserman S, Faust K. Social Network Analysis: Methods and Applications [Internet]. 1st ed. Cambridge University Press; 1994 [cited 2025 Dec 2]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cambridge.org/core/product/identifier/9780511815478/type/book\u003c/span\u003e\u003cspan address=\"https://www.cambridge.org/core/product/identifier/9780511815478/type/book\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/CBO9780511815478\u003c/span\u003e\u003cspan address=\"10.1017/CBO9780511815478\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurgette JM, Rankine J, Culyba AJ, Chu KH, Carley KM. Best Practices for Modeling Egocentric Social Network Data and Health Outcomes. HERD Health Environ Res Des J. 2021;14(4):18\u0026ndash;34. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/19375867211013772\u003c/span\u003e\u003cspan address=\"10.1177/19375867211013772\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePerry BL, Pescosolido BA, Borgatti SP. Egocentric Network Analysis: Foundations, Methods, and Models [Internet]. 1st ed. Cambridge University Press; 2018 [cited 2025 Oct 22]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cambridge.org/core/product/identifier/9781316443255/type/book\u003c/span\u003e\u003cspan address=\"https://www.cambridge.org/core/product/identifier/9781316443255/type/book\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/9781316443255\u003c/span\u003e\u003cspan address=\"10.1017/9781316443255\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDembo RS, Mailick MR, Rudolph AE, Huntington N, DaWalt LS, Mitra M. Social Network Diversity and Mental Health Among Mothers of Individuals With Autism. Am J Intellect Dev Disabil. 2023;128(2):101\u0026ndash;18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1352/1944-7558-128.2.101\u003c/span\u003e\u003cspan address=\"10.1352/1944-7558-128.2.101\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBost KK, Cox MJ, Burchinal MR, Payne C. Structural and Supportive Changes in Couples\u0026rsquo; Family and Friendship Networks Across the Transition to Parenthood. J Marriage Fam. 2002;64(2):517\u0026ndash;31. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1741-3737.2002.00517.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1741-3737.2002.00517.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinihan S, Orben A, Songco A, Fox E, Ladouceur CD, Mewton L, et al. Social determinants of mental health during a year of the COVID-19 pandemic. Dev Psychopathol. 2023;35(4):1701\u0026ndash;13. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/S0954579422000396\u003c/span\u003e\u003cspan address=\"10.1017/S0954579422000396\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSpitzer RL, Kroenke K, Williams JBW, L\u0026ouml;we B. A Brief Measure for Assessing Generalized Anxiety Disorder: The GAD-7. Arch Intern Med. 2006;166(10):1092. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/archinte.166.10.1092\u003c/span\u003e\u003cspan address=\"10.1001/archinte.166.10.1092\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLutkiewicz K, Bieleninik Ł, Jurek P, Bidzan M. Psychometric properties of the generalized anxiety disorder questionnaire (GAD-7) in a polish postpartum women sample. BMC Public Health. 2024;24(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12889-024-20194-5\u003c/span\u003e\u003cspan address=\"10.1186/s12889-024-20194-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSimpson W, Glazer M, Michalski N, Steiner M, Frey BN. Comparative Efficacy of the Generalized Anxiety Disorder 7-Item Scale and the Edinburgh Postnatal Depression Scale as Screening Tools for Generalized Anxiety Disorder in Pregnancy and the Postpartum Period. Can J Psychiatry. 2014;59(8):434\u0026ndash;40. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/070674371405900806\u003c/span\u003e\u003cspan address=\"10.1177/070674371405900806\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKroenke K, Spitzer RL, Williams JBW. Patient Health Questionnaire-9 [Internet]. 2011 [cited 2025 Jun 6]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.apa.org/doi/\u003c/span\u003e\u003cspan address=\"https://doi.apa.org/doi/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/t06165-000\u003c/span\u003e\u003cspan address=\"10.1037/t06165-000\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e doi:10.1037/t06165-000.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang L, Kroenke K, Stump TE, Monahan PO. Screening for perinatal depression with the Patient Health Questionnaire depression scale (PHQ-9): A systematic review and meta-analysis. Gen Hosp Psychiatry. 2021;68:74\u0026ndash;82. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.genhosppsych.2020.12.007\u003c/span\u003e\u003cspan address=\"10.1016/j.genhosppsych.2020.12.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStewart-Brown S, Tennant A, Tennant R, Platt S, Parkinson J, Weich S. Internal construct validity of the Warwick-Edinburgh Mental Well-being Scale (WEMWBS): a Rasch analysis using data from the Scottish Health Education Population Survey. Health Qual Life Outcomes. 2009;7(1):15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/1477-7525-7-15\u003c/span\u003e\u003cspan address=\"10.1186/1477-7525-7-15\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBates D, M\u0026auml;chler M, Bolker B, Walker S. Fitting Linear Mixed-Effects Models Using lme4. J Stat Softw. 2015;67(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.18637/jss.v067.i01\u003c/span\u003e\u003cspan address=\"10.18637/jss.v067.i01\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKuznetsova A, Brockhoff PB, Christensen RHB. lmerTest Package: Tests in Linear Mixed Effects Models. J Stat Softw. 2017;82(13). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.18637/jss.v082.i13\u003c/span\u003e\u003cspan address=\"10.18637/jss.v082.i13\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLenth RV, Piaskowski J. emmeans: Estimated Marginal Means, aka Least-Squares Means [Internet]. 2017 [cited 2026 Mar 31]. p. 2.0.2. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://CRAN.R-project.org/package=emmeans\u003c/span\u003e\u003cspan address=\"https://CRAN.R-project.org/package=emmeans\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.32614/CRAN.package.emmeans\u003c/span\u003e\u003cspan address=\"10.32614/CRAN.package.emmeans\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBen-Shachar M, L\u0026uuml;decke D, Makowski D. effectsize: Estimation of Effect Size Indices and Standardized Parameters. J Open Source Softw. 2020;5(56):2815. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.21105/joss.02815\u003c/span\u003e\u003cspan address=\"10.21105/joss.02815\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eL\u0026uuml;decke D, Ben-Shachar M, Patil I, Makowski D, Extracting. Computing and Exploring the Parameters of Statistical Models using R. J Open Source Softw. 2020;5(53):2445. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.21105/joss.02445\u003c/span\u003e\u003cspan address=\"10.21105/joss.02445\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWickham H. ggplot2: elegant graphics for data analysis. Second edition. Cham: Springer international publishing; 2016. 1 p. (Use R!).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWickham H, Chang W, Henry L, Pedersen TL, Takahashi K, Wilke C et al. ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics [Internet]. 2007 [cited 2025 Dec 5]. p. 4.0.1. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://CRAN.R-project.org/package=ggplot2\u003c/span\u003e\u003cspan address=\"https://CRAN.R-project.org/package=ggplot2\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.32614/CRAN.package.ggplot2\u003c/span\u003e\u003cspan address=\"10.32614/CRAN.package.ggplot2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eL\u0026uuml;decke D. ggeffects: Tidy Data Frames of Marginal Effects from Regression Models. J Open Source Softw. 2018;3(26):772. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.21105/joss.00772\u003c/span\u003e\u003cspan address=\"10.21105/joss.00772\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChlapecka A, Kagstrom A, Cermakova P. Educational attainment inequalities in depressive symptoms in more than 100,000 individuals in Europe. Eur Psychiatry. 2020;63(1):e97. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1192/j.eurpsy.2020.100\u003c/span\u003e\u003cspan address=\"10.1192/j.eurpsy.2020.100\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang K, Wu J, Chen X. Risk factors of perinatal depression in women: a systematic review and meta-analysis. BMC Psychiatry. 2022;22(1):63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12888-021-03684-3\u003c/span\u003e\u003cspan address=\"10.1186/s12888-021-03684-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSawyer SM, Azzopardi PS, Wickremarathne D, Patton GC. The age of adolescence. Lancet Child Adolesc Health. 2018;2(3):223\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S2352-4642(18)30022-1\u003c/span\u003e\u003cspan address=\"10.1016/S2352-4642(18)30022-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrundstr\u0026ouml;m J, Konttinen H, Berg N, Kiviruusu O. Associations between relationship status and mental well-being in different life phases from young to middle adulthood. SSM - Popul Health. 2021;14:100774. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ssmph.2021.100774\u003c/span\u003e\u003cspan address=\"10.1016/j.ssmph.2021.100774\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKuipers YJ, Beeck EV, Cijsouw A, Van Gils Y. The impact of motherhood on the course of women\u0026rsquo;s psychological wellbeing. J Affect Disord Rep. 2021;6:100216. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jadr.2021.100216\u003c/span\u003e\u003cspan address=\"10.1016/j.jadr.2021.100216\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWickramaratne PJ, Yangchen T, Lepow L, Patra BG, Glicksburg B, Talati A et al. Social connectedness as a determinant of mental health: A scoping review. Pan X, editor. PLOS ONE. 2022;17(10):e0275004. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0275004\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0275004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJetten J, Haslam C, Haslam SA, Dingle G, Jones JM. How Groups Affect Our Health and Well-Being: The Path from Theory to Policy. Soc Issues Policy Rev. 2014;8(1):103\u0026ndash;30. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/sipr.12003\u003c/span\u003e\u003cspan address=\"10.1111/sipr.12003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAllen NB, Badcock PBT. The Social Risk Hypothesis of Depressed Mood: Evolutionary, Psychosocial, and Neurobiological Perspectives. Psychol Bull. 2003;129(6):887\u0026ndash;913. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/0033-2909.129.6.887\u003c/span\u003e\u003cspan address=\"10.1037/0033-2909.129.6.887\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSlavich GM, Irwin MR. From stress to inflammation and major depressive disorder: A social signal transduction theory of depression. Psychol Bull. 2014;140(3):774\u0026ndash;815. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/a0035302\u003c/span\u003e\u003cspan address=\"10.1037/a0035302\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWetherall K, Robb KA, O\u0026rsquo;Connor RC. Social rank theory of depression: A systematic review of self-perceptions of social rank and their relationship with depressive symptoms and suicide risk. J Affect Disord. 2019;246:300\u0026ndash;19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2018.12.045\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2018.12.045\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMart\u0026iacute;nez-Garc\u0026iacute;a M, Paternina-Die M, Barba-M\u0026uuml;ller E, De Mart\u0026iacute;n D, Beumala L, Cortizo R, et al. Do Pregnancy-Induced Brain Changes Reverse? The Brain of a Mother Six Years after Parturition. Brain Sci. 2021;11(2):168. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/brainsci11020168\u003c/span\u003e\u003cspan address=\"10.3390/brainsci11020168\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePritschet L, Taylor CM, Cossio D, Faskowitz J, Santander T, Handwerker DA, et al. Neuroanatomical changes observed over the course of a human pregnancy. Nat Neurosci. 2024;27(11):2253\u0026ndash;60. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41593-024-01741-0\u003c/span\u003e\u003cspan address=\"10.1038/s41593-024-01741-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeldman R. The Neurobiology of Human Attachments. Trends Cogn Sci. 2017;21(2):80\u0026ndash;99. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.tics.2016.11.007\u003c/span\u003e\u003cspan address=\"10.1016/j.tics.2016.11.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrosch CA, Schoppe-Sullivan SJ, O\u0026rsquo;Banion DD. Parenting and Child Development: A Relational Health Perspective. Am J Lifestyle Med. 2021;15(1):45\u0026ndash;59. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/1559827619849028\u003c/span\u003e\u003cspan address=\"10.1177/1559827619849028\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMunk-Olsen T, Maegbaek ML, Johannsen BM, Liu X, Howard LM, Di Florio A, et al. Perinatal psychiatric episodes: a population-based study on treatment incidence and prevalence. Transl Psychiatry. 2016;6(10):e919\u0026ndash;919. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/tp.2016.190\u003c/span\u003e\u003cspan address=\"10.1038/tp.2016.190\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSongco A, Minihan S, Fox E, Ladouceur C, Mewton L, Moulds M, et al. Social and cognitive vulnerability to COVID-19-related stress in pregnancy: A case-matched-control study of antenatal mental health. J Affect Disord. 2023;325:739\u0026ndash;46. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2023.01.053\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2023.01.053\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarr MC, Graham AM, Feczko E, Nolvi S, Thomas E, Sturgeon D, et al. Maternal Perinatal Stress Trajectories and Negative Affect and Amygdala Development in Offspring. Am J Psychiatry. 2023;180(10):766\u0026ndash;77. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1176/appi.ajp.21111176\u003c/span\u003e\u003cspan address=\"10.1176/appi.ajp.21111176\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Barbaro K, Micheletti M, Yao X, Khante P, Johnson M, Goodman S. Infant crying predicts real-time fluctuations in maternal mental health in ecologically valid home settings. Dev Psychol. 2023;59(4):733\u0026ndash;44. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/dev0001530\u003c/span\u003e\u003cspan address=\"10.1037/dev0001530\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWitkowska-Zimny M, Zhyvotovska A, Isakov R, Boiko D, Nieradko-Iwanicka B. Maternal Sleeping Problems Before and After Childbirth - A Systematic Review. Int J Womens Health 2024;Volume 16:345\u0026ndash;71. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2147/IJWH.S446490\u003c/span\u003e\u003cspan address=\"10.2147/IJWH.S446490\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e We use the term woman to refer to birthing people, as this will be more parsimonious in terms of word count. However, we acknowledge that people of any gender can be birthing parents.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"perinatal mental health, social sensitivity, social networks, anxiety, depression","lastPublishedDoi":"10.21203/rs.3.rs-9490400/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9490400/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe transition to motherhood is a time of marked social changes. It is also a time of mental health vulnerability. This study examined the role that changes in women\u0026rsquo;s social environment during the peripartum period have on mental health and well-being.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eAdopting a matched case-control design, we used social network analyses to capture changes in the social environment of women during (N\u0026thinsp;=\u0026thinsp;378) and outside (N\u0026thinsp;=\u0026thinsp;378) the peripartum and measured individual differences in social sensitivity, anxiety and depressive symptoms, and mental well-being. Changes in social environments and their association with individuals\u0026rsquo; mental health and well-being were tracked three times across a six-month period.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eCompared to controls, peripartum women reported reduced social sensitivity, and greater emotional closeness, network density and family:friends ratio. Peripartum women also showed fewer mental health symptoms and greater well-being. Emotionally closer and closely-knit social environments were protective for women during the peripartum but not for controls.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe observed mental health and well-being benefits of social changes during the peripartum add to growing evidence of the peripartum as a time of heightened malleability characterised not only by vulnerability but also opportunity.\u003c/p\u003e","manuscriptTitle":"Social determinants of perinatal mental health and well-being: A social network analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-15 16:21:31","doi":"10.21203/rs.3.rs-9490400/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"263199718217301315447652841758404165576","date":"2026-05-07T12:29:16+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-07T07:53:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-07T05:28:13+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-28T06:04:32+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-28T03:00:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychology","date":"2026-04-28T02:56:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1a4b2e90-2ede-435d-ba29-38ca5de597b6","owner":[],"postedDate":"May 15th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"263199718217301315447652841758404165576","date":"2026-05-07T12:29:16+00:00","index":35,"fulltext":""},{"type":"reviewersInvited","content":"11","date":"2026-05-07T07:53:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-07T05:28:13+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-15T16:21:31+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-15 16:21:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9490400","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9490400","identity":"rs-9490400","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}