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. Author manuscript; available in PMC: 2026 Jun 26.
Published in final edited form as: J Affect Disord Rep. 2025 Sep 7;21:100968. doi: 10.1016/j.jadr.2025.100968

How does maternal “belief in a dangerous world” affect maternal and child depressive symptoms during times of crisis?

Ning Huang a,b, Evelyn Law c, Helen Chen d,e, Birit Broekman f,g, Jonathan Huang h, Shirong Cai h,i, Ai Peng Tan j, Jerry Chan k,l, Chong Yap Seng m, Bobby Cheon n, Anne Rifkin-Graboi a,c,o,*
PMCID: PMC13297608  NIHMSID: NIHMS2184360  PMID: 42367315

Abstract

Background:

Crises like a pandemic can exacerbate maternal and child depressive symptoms. The relationship between a pre-existing maternal dangerous world belief (BDWPre) with subsequent maternal (DEPPost_Mat) and child depressive symptoms (DEPPost_Child) during the actual crisis, and related mechanisms, remain unclear. This study 1) examines associations between BDWPre, DEPPost_Mat and DEPPost_Child, and 2) explores moderating and mediating roles of COVID-19 stress and pre-pandemic maternal depressive symptoms (DEPPre_Mat), along with the mediating effect of household conflict (HCpost).

Methods:

This cohort data were from the Singapore PREconception Study of Long-Term Maternal and Child Outcomes, including 90 complete cases and 373 imputed cases. Multiple linear regression detected longitudinal associations between BDWPre, DEPPost_Mat, and DEPPost_Child, with COVID-19 stress and DEPPre_Mat as moderators. Structural equation modeling tested mediating roles of COVID-19 stress, DEPPre_Mat, and HCpost; insensitive maternal behavior was examined as an additional mediator.

Results:

There were total associations of BDWPre with DEPPost_Mat (β = 0.172, 90 % CI [0.039, 0.306]) and DEPPost_Child (β = 0.161, 90 % CI [0.031,0.291]). DEPPre_Mat directly associated with an increase in DEPPost_Mat (β = 0.361, 90 % CI [0.248, 0.475]) and DEPPost_Child (β = 0.262, 90 % CI [0.121, 0.401]). COVID-19 stress and HCPost sequentially mediated the association between DEPPre_Mat and DEPPost_Mat, and this relationship could be independently mediated by the HCPost.

Conclusions:

Early interventions for pre-existing maternal depressive symptoms and BDW are critical to protect maternal and preschooler mental health during crises. Interventions prioritizing household conflict, alongside crises-related stress, livelihood impacts, and media exposure, may be beneficial for susceptible preschoolers and their mothers during crises.

Keywords: Crisis, Maternal depressive symptoms, Child depressive symptoms, Dangerous world belief, Maternal sensitivity

1. Introduction

Crises can exacerbate depressive symptoms in mothers, especially those with young children, due to increased stress (Hausman et al., 2020; Newnham et al., 2022). A meta-analysis found that the pandemic crisis elevated maternal depressive symptoms (Hessami et al., 2022), with the prevalence reaching 26.9 % (Racine et al., 2022). Maternal depressive symptoms negatively impact child mental health by fostering problematic parenting behaviors, which can escalate to child maltreatment and strain the parent-child relationship (Prime et al., 2020). It is therefore not surprising that child depressive symptoms surged after the COVID-19 crisis (Madigan et al., 2023; Nomura et al., 2023), with prevalence reaching 31 % during the pandemic (Deng et al., 2023). Depressive symptoms in the preschool period, a critical developmental stage, can have long-term adverse effects on children. However, few studies have explored the relationship between preschool children’s and their mothers’ depressive symptoms during the pandemic, highlighting a gap in preventive research.

Belief in a Dangerous World (BDW) is a conviction that the world is disorderly and threatening (Duckitt, 2001). For example, individuals with BDW beliefs often feel that chaos and anarchy could erupt at any moment and believe that many dangerous people exist who might attack others out of pure meanness and without provocation (Duckitt et al., 2002). People with a high level of BDW generally have chronic concerns about safety and may be more prone to neuroticism (Clifton, 2020a). Moreover, BDW is characterized by the belief that the world is threatening and hostile (Clifton, 2020a).

Accordingly, less belief in the world as a safe place has recently been found moderately (r = 0.39) associated with greater depressive symptoms (Ludwig et al., 2023).In contrast, belief that the world is a safe place correlates with optimism and hopefulness (Clifton, 2020a; McGrath, 2023). The association between basic beliefs and hope has been demonstrated across various cultural groups, including the French, Italians, Singaporeans, and Filipinos (Clifton, 2020a; Krafft, 2025; McGrath, 2023). Indeed, the BDW cognitive patterns also closely over-lap with depressive schemas, which involve negative beliefs about oneself, the world, and the future, leading to feelings of hopelessness and helplessness, as described in Beck’s cognitive theory of depression (Beck and Alford, 2009; Cook et al., 2018). Likewise, Nejat et al. (2023) found BDW was associated with a bigger proportion of negative than positive emotions regarding COVID-19.

As such, it is easy to imagine a bidirectional relation between BDW and depression. Firstly, depression could be expected to lead to an increase in BDW, similar to interpretative theories of BDW itself wherein pre-existing levels of BDW influence the solidification of BDW beliefs when new adversities are encountered (Clifton, 2020b). Still, extrapolating from work examining relations between depression and beliefs about the potential for oneself versus others to achieve a specific task (Garber and Hollon, 1980), it is also possible that depression does not increase the likelihood of believing that the world is generally a harsh or dangerous place (i.e., BDW), but rather that it is more harsh or dangerous place specifically for me. Secondly, BDW could lead to depressive symptoms. According to the cognitive appraisal model for depressive symptoms (Mehu and Scherer, 2015), individuals with a high level of BDW tend to appraise a threat or risk as greater, thereby intensifying negative emotional experiences associated with depressive symptoms. Furthermore, research has shown that higher risk perception is associated with depressive symptoms (Liu et al., 2021, 2024). Therefore, it is possible that BDW may contribute to increased depressive symptoms.

Still, while there is work indicating BDW increases mental health problems amongst people who are regularly exposed to dangerous circumstances (e.g., those in high-risk occupations like firefighters, Bryant and Guthrie, 2005; Su and Chen, 2018), there is limited attention to its impact on general population depressive symptoms, particularly among mothers. This gap necessitates further investigation, especially as crises can increase the actual experience of living in a “dangerous world” for families, including those living in both high-risk and low-risk pre-crisis conditions.

Potential mechanisms linking pre-pandemic BDW (BDWPre) to post-pandemic maternal (DEPPost_Mat) and child (DEPPost_Child) depressive symptoms remain unexplored. Pre-pandemic maternal depressive symptoms (DEPPre_Mat) may mediate this relationship, given the above-mentioned proposed effect of BDW on mental health and the demonstrated relationship between DEPPre_Mat and DEPPost_Mat (Benke et al., 2022). In addition, pandemic-related stressors may contribute to the adverse effects of BDWPre and DEPPre_Mat due to increased sensitivity to stressors. Similar to Beck’s cognitive theory of depression (Beck and Alford, 2009; Beck and Clark, 1988), individuals with constituent high BDW, who feel hopeless or anxious about the world, may exhibit heightened susceptibility to specific stressors. Indeed, recent work in America indicates that whilst a crisis (i.e., the COVID-19 pandemic) itself did not exacerbate BDW for most people, those exposed to greater crises-related adversity were slightly more susceptible to changes in primal beliefs about the nature of the world (Ludwig et al., 2023). These crisis-related stressors may disrupt positive self-perceptions and rein-force negative beliefs, heightening vulnerability to mental health problems (Su and Chen, 2018). Thus, both BDW and DEPPre_Mat may be associated with increased perceived COVID-19 stress, which in turn raises DEPPost_Mat. Therefore, COVID-19 stress may also heighten the vulnerability of mothers with high BDW and DEPPre_Mat, enhancing the relationship from both BDW and DEPPre_Mat to DEPPost_Mat. However, research on how perceived COVID-19 stress mediates or moderates the relationship between BDW, pre-existing depressive symptoms, and subsequent depressive symptoms is limited.

Household conflict may also be important to the relation between BDW and DEPPost_Mat. According to the family stress model, external stressors increase parental depression through heightened interparental relationship problems (Masarik and Conger, 2017; Weber, 2011). These household conflicts could also disrupt parenting, which in turn impacts child development (Masarik and Conger, 2017; Weber, 2011). A Singapore study indicated maternal stress about COVID-19 was associated with more post-pandemic household conflict (HCPost) (Low et al., 2023). As such, it could be expected that COVID-19 stress may elevate DEPPost_Mat and DEPPost_Child by amplifying HCPost.

This study examined the prospective association between BDWPre and both DEPPost_Mat and DEPPost_Child, considering DEPPre_Mat, COVID-19 stress, and HCPost as mediators. It additionally examined the moderating role of COVID-19 stress on the relationships between both BDWPre and DEPPre_Mat with DEPPost_Mat. We focused on preschool children and their mothers given the proposed vulnerability of young children to environmental stress (Hegde and Mitra, 2020). The COVID-19 pandemic provided an opportunity to explore how pre-crisis BDW affects pre- and post-crisis depressive symptoms in an actual dangerous situation. During the pandemic, BDWPre may be fueled by the increased perception of social disorder and safety concerns (e.g., people hoarding, stealing, exploiting, or harming each other) (Nouri and Kochel, 2021; Zhao et al., 2022). We hypothesized that BDWPre could increase DEP-Post_Mat via increasing COVID-19 stress and subsequently elevating HCPost, and that the increased DEPPost_Mat may ultimately lead to higher DEPPost_Child. Further, COVID-stress could exacerbate the relationship between BDWPre and DEPPost_Mat and between DEPPre_Mat and DEPPost_Child.

2. Method

2.1. Data source

We used data from the Singapore PREconception Study of Long-Term Maternal and Child Outcomes (S-PRESTO). This longitudinal cohort study enrolled healthy women aged 18 to 45 in Singapore planning to have a child. Recruitment occurred between February 2015 to October 2017. Of the 1039 women recruited, 475 became pregnant and 373 delivered. Follow-up of their offspring (N = 373 singleton pregnancies) is ongoing, with data from the 6-month and Year 4–6 timepoints included in this analysis (see eAppendix 1).

In this study, we focused on three-time points: Timepoint 1 (T1) was before January 23, 2020, prior to Singapore reporting its first case of COVID-19; Timepoint 2 (T2) was during the Circuit Breaker (i.e., Singaporean version of a “lock-down”) from 7 Apr 2020 to 1 June 2020; and Time point 3 (T3) was after June 19, 2020, when Circuit Breaker measures had been lifted until the COVID-19 pandemic was over. The dataset at Postnatal Month 6 corresponds to T1 (pre-Covid), while the dataset examining COVID-19 responses as well as the Postnatal Year 4–6 dataset corresponded to the later phase of T3, i.e., after the Circuit-Breaker measures had been lifted.

Participants provided written informed consent. The study has been ethically approved by the SingHealth Centralised Institutional Review Board (CIRB reference 2014/692/D) and registered with ClinicalTrials.gov (NCT 03531658).

2.2. Measurement

BDWPre was assessed using the 10-item self-reported Dangerous Worldview Scale (Duckitt et al., 2002) (Cronbach’s α = 0.721). DEP-Pre_Mat and DEPPost_Mat were assessed at T1 (Cronbach’s α = 0.904) and the later phase of T3 (Cronbach’s α = 0. 925) using the Beck Depression Inventory II (Beck et al., 1996). DEPPost_Child was assessed at the later phase of T3 (Cronbach’s α =0.744) using the DSM-IV–oriented depressive problems scale of the Child Behavior Checklist (CBCL) for ages 1.5–5 (Achenbach and Rescorla, 2000). COVID-19 stress (Cronbach’s α =0.952) and HCPost (Cronbach’s α =0.803) were assessed at the later phase of T3 during the Circuit Breaker period (April 7, 2020, to June 1, 2020), using a self-reported questionnaire with high reliability (Low et al., 2023) (More details about each measurement see eAppendix 2).

2.3. Statistical analysis

Initially, we employed standard descriptive statistics to characterize the sample with regards to complete and incomplete data (see eAppendix 3).

Given that all dependent variables in this study are continuous, multivariable linear regression analyses (MLR) were conducted to investigate (1) the relation of BDWPre with DEPPre_Mat (Model 1) and DEPPost_Mat (Model 2); (2) the association between DEPPre_Mat and DEP-Post_Mat (Model 2); and (3) the link between DEPPost_Mat and DEPPost_Child (Model 3). To explore the moderating role of COVID-19 stress on the relationship of BDWPre and DEPPre_Mat with DEPPost_Mat, models 4 and 5 separately introduced the corresponding interaction terms based on Model 2 (see Fig. 1).

Fig. 1.

Fig. 1.

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The relationship from BDWPre to DEPPost_Mat and DEPPost_Child.

Note: Dashed lines represent potential correlation paths, solid lines represent hypothesized pathways, and the thick grey arrows indicate hypothesized moderation effects. DEPPre_Mat and DEPPost_Mat represent pre-pandemic and post-pandemic maternal depressive symptoms, respectively; DEPPost_Child indicates post-pandemic child depressive symptoms; BDWPre represents pre-pandemic Belief in a Dangerous World; HCPost represents post pandemic household conflict.

Structural equation modeling (SEM) was utilized to explore the mediating roles of DEPPre_Mat, COVID-19 stress, and HCPost on the relationships between BDWPre, DEPPost_Mat, and DEPPost_Child. The statistical significance of the indirect effects was determined by 90 % confidence intervals (CIs) calculated from 20,000 Monte Carlo simulations in the R package semTools (Jorgensen et al., 2016).

Finally, in an exploratory analysis (see Supplement 2) we also examined the role of observed maternal behavior (i.e., a composite score of forms of insensitive or “negative” behavior, namely intrusivity, hostility/rejection, and frightenting/aggressive behavior). Meta-analytic work finds maternal depression inversely related to maternal sensitivity, which in turn predicts child mental health problems.

Before conducting MLR and SEM analyses, correlation analyses were used to identify key covariates, based on previous research related to DEPPost_Mat (Whaley and Pfefferbaum, 2023; Zhang et al., 2022) (More measurement details see eAppendix 2). Both unadjusted and adjusted models for the identified key covariates, including maternal education level, Pandemic Livelihood Impact (PLI) and Pandemic Media Exposure (PME), COVID-19 Diagnosis/Isolation Orders (COID), pre- and post-pandemic household income (HIPre, HIPost), were performed.

To address potential bias from missing data, multiple imputation using chained equations was implemented in the R package mice, generating 200 imputed datasets. Results were synthesized from all datasets using Rubin’s rules. The results from multiple imputation were considered the primary findings to enhance the generalizability of our study. Concurrently, we refitted all models using complete-case analysis as a sensitivity check in supplement 1. Statistical significance was set at 0.1 with 2-sided P values if the 90 % CI excluded zero. All analyses were conducted using R version 4.3.3 software.

3. Results

3.1. Participants

Table 1 shows that most characteristics are similar between incomplete and complete datasets (More details see eAppendix5)

Table 1.

Description of study population.

Variables Mean (± SD) P-
value
Incomplete
data
(N = 373)		 Complete data

(N = 90)
Post-pandemic Maternal Age 34.164 (± 3.272) 33.837 (± 2.803) 0.374
Ethnicity, N (%)
Chinese 287 (77 %) 73 (81 %) 0.913
Malay 50 (13 %) 10 (11 %)
Indian 27 (7 %) 5 (6 %)
Mix/Others 9 (2 %) 2 (2 %)
Post-pandemic Child Age 2.633 (± 0.759) 2.629 (± 0.655) 0.964
Child Sex, N (%)
Boy 199 (53 %) 51 (57 %) 0.725
Girl 166 (45 %) 39 (43 %)
Pre-Pandemic Maternal Education Level 6.635 (± 1.201) 6.944 (± 0.866) 0.006
Pre-Pandemic Household Income 8.132 (± 2.816) 8.989 (± 2.520) 0.010
Post-Pandemic Household Income 7.767 (± 3.050) 8.711 (± 2.728) 0.009
Pandemic Media Exposure 2.399 (± 0.732) 2.425 (± 0.714) 0.778
Pandemic livelihood Impact 1.749 (± 0.891) 1.672 (± 0.906) 0.503
COVID-19 Diagnoses & Isolation Orders, N (%)
Yes 40 (11 %) 15 (17 %) 1.000
No 187 (50 %) 75 (83 %)
Post-Pandemic Pregnant Status, N (%)
Pregnant 67 (18 %) 32 (36 %) 0.347
Not Pregnant 159 (43 %) 58 (64 %)
Depressive symptoms interval pre- and post-pandemic 1.636 (± 0.152) 1.625 (± 0.134) 0.555
Pre-Pandemic Belief in a Dangerous world 3.817 (± 0.774) 3.717 (± 0.827) 0.347
Pre-Pandemic Maternal Depressive Symptoms 8.787 (± 7.596) 8.078 (± 6.411) 0.423
COVID-19 Stress 3.238 (± 2.204) 2.972 (± 2.232) 0.345
Post-Pandemic Household Conflict 2.142 (± 2.044) 1.972 (± 2.119) 0.525
Post-Pandemic Maternal Depressive Symptoms 8.432 (± 8.113) 6.611 (± 7.369) 0.056
Post-Pandemic Child Depressive Symptoms 1.835 (± 2.362) 1.744 (± 2.382) 0.760
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Note: P values of difference between incomplete and complete data set were extracted from analysis of t-test for continuous variables and Fisher’s exact test for categorical variables. Bold font indicates statistically significant results (p < 0.01).

3.2. Multivariable linear regression analysis

Both unadjusted and adjusted Model 1 in Table 2 showed that BDWPre was significantly positively associated with DEPPre_Mat. Both unadjusted and adjusted Models 4 and 5 in Table 3 showed that the moderating role of COVID-19 stress on the relationship between BDWPre and DEPPre_Mat with DEPPost_Mat was insignificant (More details see eAppendix6)

Table 2.

Pooled linear regression results for relationships between BDWPre, DEPPre_Mat, HCPost, DEPPost_Mat and DEPPost_Child in imputed data (n = 373).

Variables DEPPre_Mat
Unadjusted Model
1 B(SE)		 DEPPre_Mat
Adjusted Model 1
B(SE)		 DEPPost_Mat
Unadjusted Model 2
B(SE)		 DEPPost_Mat
Adjusted Model 2
B(SE)		 DEPPost_Child
Unadjusted Model 3
B(SE)		 DEPPost_Child
Adjusted Model 3
B(SE)
BDWPre 1.444* (0.774) 1.322* (0.782) 1.259* (0.739) 1.076 (0.709) 0.363 (0.221) 0.306 (0.219)
DEPPre_Mat 0.392*** (0.088) 0.384*** (0.090) 0.082** (0.032) 0.083** (0.033)
DEPPost_Mat 0.054** (0.026) 0.041 (0.026)
HCPost 0.829*** (0.290) 0.837*** (0.289) 0.092 (0.102) 0.106 (0.101)
COVID-19 Stress 0.464* (0.264) 0.369 (0.280) −0.010 (0.084) −0.018 (0.089)
Pre-Pandemic Maternal Education Level −0.100 (0.586) −0.037 (0.525) −0.074 (0.170)
Pre-Pandemic household income −0.317 (0.251) −0.354 (0.502) 0.035 (0.158)
Post-Pandemic household income −0.021 (0.472) −0.145 (0.144)
Pandemic Media Exposure 0.618 (0.677) −0.046 (0.218)
Pandemic livelihood Impact 0.953 (0.611) 0.122 (0.198)
COVID-19 Diagnoses & Isolation Orders 1.028 (1.249) 0.350 (0.432)
Constant 3.618 (2.986) 7.283 (4.828) −3.208 (2.742) −2.258 (4.684) −0.885 (0.828) 0.573 (1.524)
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Note: Significance levels:

***

p < 0.01

**

p < 0.05

*

p < 0.1. B represents the unstandardized coefficient, SE represents the standard error; DEPPre_Mat and DEPPost_Mat represent pre-pandemic and post-pandemic maternal depressive symptoms, respectively; DEPPost_Child indicates post-pandemic child depressive symptoms; BDWPre represents pre pandemic Belief in a Dangerous World. HCPost represents post pandemic household conflict; Bold font indicates statistically significant results (p < 0.01). Adjusted models for DEPPre_Mat controlled for demographic variables, including Pre-Pandemic Maternal Education Level and household income. Adjusted Models for DEPPost_Mat and DEPPost_Child additionally control for COVID-19-related factors, including Post-Pandemic household income, Pandemic Media Exposure, Pandemic Livelihood Impact, and COVID-19 Diagnoses & Isolation Orders.

Table 3.

Pooled linear regression results for the interaction of COVID-19 stress on the relationship of BDWPre and DEPPre_Mat with DEPPost_Mat in imputed data (n = 373).

Variables DEPPost_Mat
Unadjusted
Model 4		 DEPPost_Mat
Adjusted
Model 4		 DEPPost_Mat
Unadjusted
Model 5		 DEPPost_Mat
Adjusted
Model 5
B(SE) B(SE) B(SE) B(SE)
BDWPre 1.254 *
(0.740) 		1.071
(0.709)		 0.429
(1.009)		 0.346
(0.976)
DEPPre_Mat 0.280 **
(0.131) 		0.273 **
(0.129) 		0.390 ***
(0.088) 		0.382 ***
(0.090)
HCPost 0.851 ***
(0.293) 		0.856 ***
(0.290) 		0.833 ***
(0.292) 		0.842 ***
(0.291)
COVID-19 Stress 0.165
(0.376)		 0.066
(0.393)		 −0.592
(1.203)		 −0.565
(1.180)
DEPPost_Mat*COVID-19 stress 0.031
(0.029)		 0.031
(0.029)
BDWPre*COVID-19 stress 0.269
(0.296)		 0.238
(0.289)
Pre-pandemic Maternal Education Level −0.008
(0.526)		 −0.046
(0.526)
Pre-pandemic household income −0.358
(0.500)		 −0.360
(0.502)
Post-pandemic household income −0.019
(0.470)		 −0.015
(0.472)
Pandemic Media Exposure 0.604
(0.676)		 0.589
(0.675)
Pandemic livelihood Impact 0.984
(0.616)		 0.934
(0.611)
COVID-19 Diagnoses & Isolation Orders 1.032
(1.244)		 1.031
(1.246)
Constant −2.261
(2.867)		 −1.500
(4.647)		 −0.008
(3.874)		 0.713
(5.443)
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Note: Significance levels:

***

p < 0.01

**

p < 0.05

*

p < 0.1. B represents the unstandardized coefficient, SE represents the standard error; DEPPre_Mat and DEPPost_Mat represent pre-pandemic and post-pandemic maternal depressive symptoms, respectively; DEPPost_Child indicates post-pandemic child depressive symptoms; BDWPre represents pre pandemic Belief in a Dangerous World; HCPost represents post pandemic household conflict; Bold font indicates statistically significant results (p < 0.01). Adjusted Models for DEPPost_Mat additionally control for COVID-19-related factors, including Post-Pandemic household income, Pandemic Media Exposure, Pandemic Livelihood Impact, and COVID-19 Diagnoses & Isolation Orders.

3.3. Mediation analysis

The model with covariates and using imputed data demonstrated a good fit to the data, with χ2=3.872, p = 0.424, SRMR =0.058, RMSEA =0.000, CFI = 1.000. As shown in Table 4, no significant mediators were identified for the relationship between BDWPre and DEPPost_Mat or the relationship between BDWPre and DEPPost_Child. While the total effect of the relationship between BDWPre and DEPPost_Mat is significant (β = 0.172, 90 % CI [0.039, 0.306]; P < .001). Similarly, the total effect of the relationship between BDWPre and DEPPost_Child is significant (β = 0.161, 90 % CI [0.031,0.291]).

Table 4.

Direct, indirect and total associations of BDWPre with DEPPost_Mat and DEPPost_Child in imputed data.

Association Path β 90 %CI.
lower		 90 %CI.
upper
Mediation Model between BDWPre and DEPPost_Mat
Direct association BDWPre → DEPPost_Mat 0.105 −0.007 0.217
Total indirect association BDWPre → DEPPost_Mat 0.067 −0.012 0.148
Indirect association1 BDWPre → DEPPre_Mat → COVID-19 Stress → HCPost → DEPPost_Mat 0.003 0.000 0.008
Indirect association2 BDWPre → DEPPre_Mat → COVID-19 Stress → HCPost 0.013 −0.001 0.032
Indirect association3 BDWPre → DEPPre_Mat → COVID-19 Stress → DEPPost_Mat 0.004 −0.001 0.012
Indirect association4 BDWPre → DEPPre_Mat → HCPost → DEPPost_Mat 0.007 0.000 0.017
Indirect association5 BDWPre → DEPPre_Mat → DEPPost_Mat 0.045 −0.002 0.098
Indirect association6 BDWPre → COVID-19 Stress → HCPost → DEPPost_Mat 0.006 −0.005 0.019
Indirect association7 BDWPre → COVID-19 Stress → DEPPost_Mat 0.007 −0.007 0.029
Indirect association8 BDWPre → HCPost → DEPPost_Mat −0.011 −0.040 0.013
Total association BDWPre → DEPPost_Mat 0.172 0.039 0.306
Mediation Model between BDWPre and DEPPost_Child
Direct association BDWPre → DEPPost_Child 0.105 −0.018 0.226
Total indirect association BDWPre → DEPPost_Child 0.056 −0.002 0.117
Indirect association1 BDWPre → DEPPre_Mat → COVID-19 Stress → HCPost → DEPPost_Mat → DEPPost_Child 0.000 0.000 0.001
Indirect association2 BDWPre → DEPPre_Mat → COVID-19 Stress → HCPost → DEPPost_Child 0.001 −0.001 0.005
Indirect association3 BDWPre → DEPPre_Mat → COVID-19 Stress → DEPPost_Mat → DEPPost_Child 0.000 0.000 0.002
Indirect association4 BDWPre → DEPPre_Mat → COVID-19 Stress → DEPPost_Child 0.000 −0.007 0.005
Indirect association5 BDWPre → DEPPre_Mat → HCPost → DEPPost_Mat → DEPPost_Child 0.001 0.000 0.003
Indirect association6 BDWPre → DEPPre_Mat → HCPost → DEPPost_Child 0.003 −0.002 0.010
Indirect association7 BDWPre → DEPPre_Mat → DEPPost_Mat → DEPPost_Child 0.006 −0.001 0.019
Indirect association8 BDWPre → DEPPre_Mat → DEPPost_Child 0.033 −0.002 0.077
Indirect association9 BDWPre → COVID-19 Stress → HCPost → DEPPost_Mat → DEPPost_Child 0.001 −0.001 0.003
Indirect association10 BDWPre → COVID-19 Stress → HCPost → DEPPost_Child 0.003 −0.003 0.011
Indirect association11 BDWPre → COVID-19 Stress → DEPPost_Mat → DEPPost_Child 0.001 −0.001 0.005
Indirect association12 BDWPre → COVID-19 Stress → DEPPost_Child −0.001 −0.016 0.013
Indirect association13 BDWPre → HCPost → DEPPost_Mat → DEPPost_Child −0.002 −0.007 0.002
Indirect association14 BDWPre → HCPost → DEPPost_Child −0.005 −0.025 0.008
Indirect association15 BDWPre → DEPPost_Mat → DEPPost_Child 0.014 −0.003 0.042
Total association BDWPre → DEPPost_Child 0.161 0.031 0.291
Mediation Model between DEPPre_Mat and DEPPost_Mat
Direct association DEPPre_Mat → DEPPost_Mat 0.361 0.248 0.475
Total indirect association DEPPre_Mat → DEPPost_Mat 0.103 0.051 0.162
Indirect association1 DEPPre_Mat → COVID-19 Stress → HCPost → DEPPost_Mat 0.023 0.007 0.044
Indirect association2 DEPPre_Mat → COVID-19 Stress → DEPPost_Mat 0.028 −0.007 0.070
Indirect association3 DEPPre_Mat → HCPost → DEPPost_Mat 0.052 0.016 0.097
Total association DEPPre_Mat → DEPPost_Mat 0.464 0.361 0.566
Mediation Model between DEPPre_Mat and DEPPost_Child
Direct association DEPPre_Mat → DEPPost_Child 0.262 0.121 0.401
Total indirect association DEPPre_Mat → DEPPost_Child 0.093 0.019 0.174
Indirect association1 DEPPre_Mat → COVID-19 Stress → HCPost → DEPPost_Mat → DEPPost_Child 0.003 0.000 0.008
Indirect association2 DEPPre_Mat → COVID-19 Stress → HCPost → DEPPost_Child 0.010 −0.005 0.029
Indirect association3 DEPPre_Mat → COVID-19 Stress → DEPPost_Mat → DEPPost_Child 0.004 −0.001 0.013
Indirect association4 DEPPre_Mat → COVID-19 Stress → DEPPost_Child −0.003 −0.044 0.038
Indirect association5 DEPPre_Mat → HCPost → DEPPost_Mat → DEPPost_Child 0.007 −0.001 0.019
Indirect association6 DEPPre_Mat → HCPost → DEPPost_Child 0.023 −0.012 0.065
Indirect association7 DEPPre_Mat → DEPPost_Mat → DEPPost_Child 0.049 −0.004 0.107
Total association DEPPre_Mat → DEPPost_Child 0.355 0.239 0.472
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Note: Significant results are indicated in bold, defined as those with 90 % confidence intervals that do not include zero. Indirect association: The effect of the independent variable (X) on dependent variable (Y) that passes through the mediator (M). Direct Association: The effect of X on Y that occurs without the mediator (M). Total Association: The combined effect of X on Y, including both direct and indirect paths. DEPPre_Mat and DEPPost_Mat represent pre-pandemic and post-pandemic maternal depressive symptoms, respectively; DEPPost_Child indicates post-pandemic child depressive symptoms; BDWPre represents pre-pandemic Belief in a Dangerous World; HCPost represents post pandemic household conflict.

Fig. 2 presents DEPPre_Mat directly associated with increased DEPPost_Mat (β =0.361, 90 % CI [0.248, 0.475]) and DEPPost_Child (β =0.262, 90 % CI [0.121, 0.401]). The positive relationship between DEPPre_Mat and DEPPost_Mat was found to be mediated by HCPost (β =0.052, 90 % CI [0.016, 0.097]). HCPost explained 11.2 % of the variance (calculated as β for indirect effect / β for total effect=0.052/0.464) in the association between DEPPre_Mat and DEPPost_Mat. A chain mediating effect of COVID-19 stress and HCPost (β =0.023, 90 % CI [0.007, 0.044]) account for 5 % of the variance in this association. Moreover, the total indirect effect of the relationship from DEPPre_Mat to DEPPost_Child is significant (β =0.093, 90 % CI [0.019, 0.174]), accounting for 26.3 % of the significant total effect (β =0.355, 90 % CI [0.239, 0.472]).

Fig. 2.

Fig. 2.

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Direct Path from BDWPre to DEPPost_Mat and DEPPost_Child in adjusted SEM using imputed data.

Note: Significance levels: *** p < 0.01, ** p < 0.05, * p < 0.1. DEPPre_Mat and DEPPost_Mat represent pre-pandemic and post-pandemic maternal depressive symptoms, respectively; DEPPost_Child indicates post-pandemic child depressive symptoms; BDWPre represents pre-pandemic Belief in a Dangerous World; HCPost represents post pandemic household conflict. PLI and PME are two covariates, representing Pandemic Livelihood Impact and Pandemic Media Exposure, respectively. Other covariates, including maternal education level, pre- and post-pandemic household income, and COVID-19 Diagnosis and/or Isolation Orders, are not shown in this figure as they are not significantly associated with any key variables. The width of the lines represents the size of the standardized coefficients.

With few exceptions, significant results from the analysis were similar in the mediation analysis without covariates using imputed data (eFigure4) and the analysis using complete data (eFigure5).

4. Discussion

Using the COVID-19 pandemic as a context to understand risks for mental health problems during times of crisis, this study examined the interplay between mothers’ pre-COVID beliefs in a dangerous world and mother’s and children’s mental states and experiences, as their worlds, indeed, became more dangerous. Here we found total associations involving pre-pandemic Belief in a Dangerous World and post-pandemic onset maternal and child outcomes. Individual pathways suggested combined influences of pre-pandemic depression, Covid-19 stress, and household conflict on maternal mental states, as well as a particularly important role of pre-pandemic maternal health on child outcomes.

Although the direct and indirect associations between BDWPre and DEPPost_Mat are insignificant in the imputed data, a significant total association between them also demonstrated BDWPre does influence DEPPost_Mat. According to Beck’s theory of depression (Beck and Alford, 2009), negative schemas, which focus on perceived threats, vulnerability, and negative beliefs about the self, future, and world, may heighten an individual’s vulnerability to stressors. As such, BDW may be considered a negative cognition that could increase perceived risk and induce marked distress in the crisis (Kiral Ucar et al., 2022), leading to impaired psychosocial functioning (Lyons et al., 2020). Similarly, complete data analysis also showed a sequential mediating effect of COVID-19 stress and HCPost on the relationship between BDWPre and DEPPost_Mat. It is possible that BDWPre adversely affected maternal depressive symptoms, especially during the crisis.

The positive relationship between pre- and post-pandemic depressive symptoms in mothers aligns with previous research (Benke et al., 2022). As mentioned, this relationship was also sequentially mediated by COVID-19 stress and household conflict. This may have occurred for at least two reasons. First, though not examined, it is possible that higher levels of post-pandemic depressive symptoms may have marked more difficult living experiences including less social, marital, and financial support or opportunities during the pandemic (Guo et al., 2022; Santos et al., 2023; Whaley and Pfefferbaum, 2023), and so less reserve capacity during times of crisis and accordingly higher distress during these times (Yang et al., 2023). Second, it is additionally possible that mothers with higher levels of pre-existing depressive symptoms are more susceptible to perceiving difficult situations as especially unmanageable and stressful (Beck and Alford, 2009). As such, then, maladaptive responses like hostility (Pietromonaco and Overall, 2021) and negative conflict solution styles (Işık and Kaya, 2022) could augment the occurrence of COVID-19 stressors, such as taking on greater housework and experiencing poor work-family balance, which could increase conflict with other household members (Yang et al., 2023). In either case, mothers with more household conflict during the pandemic may have a less harmonious family environment and lack good social support, which could increase depressive symptoms during the pandemic (Wu et al., 2020). Therefore, pre-crisis maternal depressive symptoms could increase crisis-related stress and then contribute to more conflict between household members, which could highlight the level of maternal depressive symptoms. Of note, DEPPre_Mat and HCPost were consistent risk factors for DEPPost_Mat in all adjusted or unadjusted models within all data sets. Therefore, it is important to recognize that for mothers of young children, strategies to prevent mental health difficulties during a crisis must also prioritize strategies to improve pre-crisis maternal mental health as well as post-crisis onset household conflict.

With regards to post onset child outcomes, our total model showed mothers’ BDWPre elevated DEPPost_Child. In particular, our findings revealed a strong relationship between DEPPre_Mat and DEPPost_Child. This is in keeping with much past research demonstrating that mothers can transmit depressive symptoms to their young children through both genetic predispositions and environmental factors, such as harmful rearing environments and parenting behaviors (Goodman, 2020; Rice, 2022). Importantly, maternal mental health before the crisis appeared more critical for child mental health than during the crisis. Of note, in our study pre-crisis maternal mental state was reported when their children were infants. Thus, the current findings are in keeping with a large body of research highlighting the crucial impact of mothers’ mental health during children’s early-years on children’s long-term well-being (Fan et al., 2024; Santos et al., 2024; Spry et al., 2020). Indeed, even in the face of a crisis, prior maternal mental health during the child’s infancy was the only direct predictor of child depression after crisis onset. This highlights the potential for perinatal and postpartum maternal heath to serve as a buffer against child risk during crises, and so, alongside past research, suggests that policy makers may wish to prioritize programs to support maternal mental health in an increasingly unpredictable world.

There are several limitations in this study. First, despite using multiple imputation to improve generalizability, the small, predominantly ethnic Chinese sample may still lack statistical power, potentially obscuring the association of BDWPre with DEPPost_Mat and DEPPost_Child. Second, all variables were measured using maternal self-reported questionnaires, which may introduce bias due to recall or social desirability. Future studies should incorporate clinical interviews or observer-rated tools for maternal and child mental health to reduce bias. Relatedly, our COVID-19 stressors were measured retrospectively after the Circuit Breaker had ended. Although past research (Low et al., 2023) suggests that the time elapsed since the Circuit Breaker does not predict reports of Circuit-Breaker related distress, retrospective reporting of stress not fully reflect the dynamics of stress during the Circuit Breaker and its effects on mental health. To gain a better understanding, future studies should use prospective or real-time stress assessments. Third, given the younger age of the children (i.e., 6 months of age) at the pre-Covid visit, accurately assessing children’s depressive symptoms was not possible. Therefore, we did not control for pre-pandemic child mental health. Future studies should include pre-existing child mental health as a covariate to provide a clearer picture of the causal pathways involved. Fourth, while the current model focused on household conflict and maternal depressive symptoms as mediators, the indirect effects were modest. In a post-hoc attempt to find additional mediators, we also examined maternal observed caregiving (See Supplement 2), though the sample with available data was limited and, perhaps therefore not surprisingly, the majority of the results were not significant. Future research should explore additional potential mediators such as coping strategies and parenting practices (Schlesinger et al., 2025; Borairi et al., 2024), to provide a more comprehensive understanding of these pathways. Fifth, future research should include vaccination status, as it may improve mental health by reducing COVID-19-related stress (Zilver et al., 2024). Finally with regards to generalizability, it is possible that BDW and its influence may differ across various sociopolitical contexts, and that people raised in harsher contexts (e.g., war, famine, totalitarianism, disease) may have higher baseline rates of dangerous world beliefs. While, past work suggests that BDW is relatively stable (Duckitt et al., 2002) and that BDW development may fit better to a confirmatory rather than retrospective model, less is known about this in early development (Clifton, 2020b; Lansford et al., 2023). In other words, evidence suggests that adults are likely to incorporate new knowledge in a way that fits to their pre-existing schema concerning the negative nature of the world, though less is known about this process in childhood with some evidence suggesting lifetime trauma may play a role (Ludwig et al., 2023). Likewise, generalizability may be limited by cultural differences in policies, vaccination rates, and mental health responses, which may limit the generalizability of our findings (Zilver et al., 2021). Future studies should focus on larger, more diverse samples across different countries, sociopolitical settings, and developmental stages.

Despite the limitations, this study has several important implications. First, the significant total association of BDWPre with DEPPost_Mat and DEPPost_Child underscores the importance of addressing negative cognitive patterns. Second, considering the crucial impact of mothers’ past mental state on both their own and their children’s post-crisis depressive symptoms, early prevention, and regular monitoring are vital. These measures are essential for preventing mental health issues in both children and their mothers during times of crisis. The implication here is that emergency intervention strategies will be more effective if good pre-crisis intervention and prevention programs targeting mental health are already in place. In addition, during a crisis, household conflict should be addressed. The significant impact of interpersonal relationships on DEPPost_Mat emphasizes the need to provide better social support to mothers with pre-existing depressive symptoms and to increase mothers’ self-efficacy and positive parenting (IJzendoorn et al., 2023). Furthermore, although crisis-related stress did not directly affect the mental health of mothers and children in the short term, its long-term effects remain unknown, and it is a primary factor in household conflict. Therefore, policymakers may wish to address crisis-related stress by providing economic support and implementing effective crisis communication comprehensively during an emergency (Su et al., 2021; Witteveen and Velthorst, 2020), given the impact of PLI and PME on crisis-related stress.

5. Conclusion

This cohort study suggests a positive association between BDWPre and both DEPPost_Mat and DEPPost_Child. Furthermore, DEPPre_Mat showed the strongest direct association with DEPPost_Mat, with the relationship potentially sequentially mediated by COVID-19 stress and HCPost. Additionally, DEPPre_Mat was more strongly linked to DEPPost_Child. Our study underscores the importance of developing targeted mental health interventions for children and mothers during early childhood. More importantly, these findings indicate that societies interested in promoting limiting mother-child mental health problems during crises need to proactively work towards greater maternal well-being and quickly intervene during crises to reduce family conflict.

Supplementary Material

Supplemental materials
Supplemental materials - observed maternal behavior

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.jadr.2025.100968.

Acknowledgements

We acknowledge the SPRESTO (A*STAR) study group. The S-PRESTO study group includes: Airu Chia, Andrea Cremaschi, Anna Magdalena Fogel, Anne Eng Neo Goh, Anne Rifkin-Graboi, Anqi Qiu, Bee Wah Lee, Bernard Su Min Chern, Candida Vaz, Chan Shi Yu, Dawn Xin Ping Koh, Dennis Wang, Desiree Y. Phua, Elaine Phaik Ling Quah, Elizabeth Huiwen Tham, Evelyn Chung Ning Law, Evelyn Keet Wai Lau, Evelyn Xiu Ling Loo, Fabian Kok Peng Yap, Falk Müller-Riemenschneider, George Seow Heong Yeo, Gerard Chung Siew Keong, Hannah Ee Juen Yong, Helen Yu Chen, Hong Pan, Huang Jian, Huang Pei, Hugo P S van Bever, Hui Min Tan, Ives Lim Yubin, Jadegoud Yaligar, Jerry Kok Yen Chan, Jia Xu, Johan Gunnar Eriksson, Jonathan Tze Liang Choo, Jonathan Y. Bernard, Jonathan Yinhao Huang, Jun Shi Lai, Karen Mei Ling Tan, Keith M. Godfrey, Keri McCrickerd, Kok Hian Tan, Kok Wee Chong, Kothandaraman Narasimhan, Kuan Jin Lee, Li Chen, Lieng Hsi Ling, Ling-Wei Chen, Lourdes Mary Daniel, Lynette Pei-Chi Shek, Maria De Iorio, Marielle V. Fortier, Mary Foong-Fong Chong, Mary Wlodek, Mei Chien Chua, Melvin Khee-Shing Leow, Michael J. Meaney, Michelle Zhi Ling Kee, Min Gong, Mya Thway Tint, Navin Michael, Neerja Karnani, Ngee Lek, Noor Hidayatul Aini Bte Suaini, Oon Hoe Teoh, Peter David Gluckman, Priti Mishra, Queenie Ling Jun Li, Sambasivam Sendhil Velan, See Ling Loy, Seng Bin Ang, Shiao-Yng Chan, Shirong Cai, Shu-E Soh, Si Hui Goh, Stephen Chin-Ying Hsu, Suresh Anand Sadananthan, Tan Ai Peng, Teng Hong Tan, Varsha Gupta, Victor Samuel Rajadurai, Wee Meng Han, Wei Wei Pang, Yap Seng Chong, Yin Bun Cheung, Yiong Huak Chan, Yung Seng Lee, Zai Ru Cheng, Zhang Han.

Funding

This study was funded by the CARE project (Covid-19, Attachment, Resilience, and Early Life) under the Social Science Research Thematic Grant (SSRTG; 2/21 AR) from the Singapore Ministry of Education. This study was also supported by the National Research Foundation (NRF) under the Open Fund-Large Collaborative Grant (OF-LCG; MOH-000504) administered by the Singapore Ministry of Health’s National Medical Research Council (NMRC) and the Agency for Science, Technology and Research (A*STAR). In RIE2025, the study is supported by funding from the NRF’s Human Health and Potential (HHP) Domain, under the Human Potential Programme. Also, this study was supported by the China Scholarship Council.

Footnotes

Declaration of generative AI and AI-assisted technologies in the writing process

During the preparation of this work the lead author used Grammarly in order to check the grammar and improve the language. After using this tool/service, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication.

CRediT authorship contribution statement

Ning Huang: Writing – original draft, Methodology, Formal analysis, Data curation. Evelyn Law: Writing – review & editing. Helen Chen: Writing – review & editing. Birit Broekman: Writing – review & editing. Jonathan Huang: Writing – review & editing. Shirong Cai: Writing – review & editing. Ai Peng Tan: Writing – review & editing. Jerry Chan: Writing – review & editing. Chong Yap Seng: Writing – review & editing, Project administration, Funding acquisition. Bobby Cheon: Writing – review & editing. Anne Rifkin-Graboi: Writing – review & editing, Supervision, Project administration, Investigation, Funding acquisition, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Supplementary Materials

Supplemental materials
NIHMS2184360-supplement-Supplemental_materials.docx (3.6MB, docx)
Supplemental materials - observed maternal behavior
NIHMS2184360-supplement-Supplemental_materials_-_observed_maternal_behavior.docx (205.2KB, docx)

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