Social support before and after childbirth is a possible protective factor for perinatal depression. Currently, there is a lack of longitudinal studies beyond the first year postpartum exploring the relationship of social support with depression and anxiety. Social support is also a possible protective factor for adverse child development, which is a known consequence of perinatal depression. The present study followed up a cohort of depressed women (n = 54) from a randomised controlled trial of psychological treatment for antenatal depression. We examined the trajectory of the relationships between perceived social support (Social Provisions Scale), depression (Beck Depression Inventory), and anxiety (Beck Anxiety Inventory) twice in pregnancy and twice postpartum up to two years. The influence of social support on child development and parenting-related stress was also explored. Two aspects of social support, Reassurance of Worth and Reliable Alliance, were strongly related to perinatal depression and anxiety, particularly when predicting symptoms in late pregnancy. However, the effect of postnatal depression on child development at 9 and 24 months post-birth was not mediated by social support. These results suggest the importance of adjusting current interventions for depressed perinatal women to focus on social support in late pregnancy and the first six months postpartum.

In an increasingly connected world and in the midst of a global pandemic, digital trials offer numerous advantages over traditional trials that rely on physical study sites. Digital trials have the potential to improve access to research and clinical treatments for the most vulnerable and minoritized, including pregnant and postpartum individuals. However, digital trials are underutilized in maternal and child health research, and there is limited evidence to inform the design and conduct of digital trials. Our research collaborative, consisting of 5 research teams in the U.S. and Australia, aimed to address this gap. We collaborated to share lessons learned from our experiences recruiting and retaining pregnant and postpartum individuals in digital trials of social and behavioral interventions. We first discuss the promise of digital trials in improving participation in research during the perinatal period, as well as the unique challenges they pose. Second, we present lessons learned from 12 completed and ongoing digital trials that have used platforms such as Ovia, Facebook, and Instagram for recruitment. Our trials evaluated interventions for breastfeeding, prenatal and postpartum depression, insomnia, decision making, and chronic pain. We focus on challenges and lessons learned in 3 key areas: (1) rapid recruitment of large samples with a diversity of minoritized identities, (2) retention of study participants in longitudinal studies, and (3) prevention of fraudulent enrollment. We offer concrete strategies that we pilot-tested to address these challenges. Strategies presented in this commentary can be incorporated, as well as formally evaluated, in future studies.

Although it is well-established that maternal depression can be treated successfully with psychological treatments, it is not yet clearwhether successful treatment has a positive effect on the development and mental health of their children. We conducted a random-effects meta-analysis of randomized trials on psychological treatments of depressed pregnant women and mothers, which also reported outcomes on parental functioning /marital distress, the interaction between mother and child, child development, mental health, length and weight. We included 47 randomized trials (51 comparisons between treatment and control groups; 7,745 participants). The interventions had a moderate effect on depression in the mothers (SMD=0.57; 95% CI: 0.43; 0.70). We also found significant effects on parental functioning/marital distress (k=31; g=0.23; 95% CI: 0.07; 0.39), on the interaction between mother and child (k=27; g=0.34; 95% CI: 0.12; 0.56) and on child mental health (k=10; g=0.29; 95% CI: 0.12; 0.45). No significant effect was found for child development, length, and weight, possibly because of low power. Heterogeneity was high in most analyses. Sensitivity analyses resulted in mixed outcomes, with some main results not supported, while others resulted in significant outcomes (child development, child length and weight) that were not significant in the main analyses. Treatment of depressed mothers probably has small but significant effects on parental functioning/marital distress, the interaction between mother and child, and child mental health. This substantially increases the importance of making psychological treatments available to pregnant women and mothers with depression. The effects of psychological treatment of maternal depression on children and parental functioning: A meta-analysis; https://osf.io/m5xys/overview.

Internet-based interventions for perinatal depression reduce depressive symptoms in new and expectant mothers. However, modifiers of their effects, and prognostic factors of adherence, are unknown. To assess modifiers of effectiveness and deterioration, and prognostic factors of adherence in internet-based interventions for perinatal depression. Systematic searches were conducted in three bibliographic databases on February 7, 2025. Two independent researchers identified randomized controlled trials (RCTs) of internet-based interventions for perinatal depression. We conducted conventional and two-stage individual participant data meta-analysis (IPDMA). Eighteen studies were eligible, and data from nine (n = 1094 participants) were pooled in IPDMA. We found evidence of a difference in post-treatment depressive symptoms between participants in the internet-based intervention and controls (SMD = 0.29 [95%CI: 0.03-0.54], small effect size), increase in response (RR = 1.97 [95%CI: 1.57-2.47]) and remission (RR = 1.73 [95%CI: 1.38-2.18]). The interventions were effective for anxiety symptoms (SMD = 0.26 [95%CI: 0.11-0.40]) but not for reliable deterioration (OR = 0.80 [95%CI: 0.49-1.32]). No modifiers of effectiveness or deterioration, or prognostic factors of adherence were identified. Baseline depressive symptoms and comorbid anxiety were prognostic factors for higher depressive symptoms at post-treatment. Internet-based interventions for perinatal depression are effective for depressive and anxiety symptoms in new and expectant mothers. They may be offered to patients regardless of their age, education, relationship status, employment, baseline depressive or anxiety symptoms, previous treatment, number of children, or ethnic minority status, if they wish to follow them. RCTs should collect more information on factors relevant to the perinatal period, such as partner's mental health and pregnancy complications. Open Science Framework (https://osf.io/98tms).

UNSTRUCTURED In an increasingly connected world and in the midst of a global pandemic, digital trials offer numerous advantages over traditional trials that rely on physical study sites. Digital trials have the potential to improve access to research and clinical treatments for the most vulnerable and minoritized, including pregnant and postpartum individuals. However, digital trials are underutilized in maternal and child health research, and there is limited evidence to inform the design and conduct of digital trials. Our research collaborative, consisting of 5 research teams in the U.S. and Australia, aimed to address this gap. We collaborated to share lessons learned from our experiences recruiting and retaining pregnant and postpartum individuals in digital trials of social and behavioral interventions. We first discuss the promise of digital trials in improving participation in research during the perinatal period, as well as the unique challenges they pose. Second, we present lessons learned from 12 completed and ongoing digital trials that have used platforms such as Ovia, Facebook, and Instagram for recruitment. Our trials evaluated interventions for breastfeeding, prenatal and postpartum depression, insomnia, decision making, and chronic pain. We focus on challenges and lessons learned in 3 key areas: (1) rapid recruitment of large samples with a diversity of minoritized identities, (2) retention of study participants in longitudinal studies, and (3) prevention of fraudulent enrollment. We offer concrete strategies that we pilot-tested to address these challenges. Strategies presented in this commentary can be incorporated, as well as formally evaluated, in future studies.

Perinatal mental health remains a critical global challenge, with maternal mortality, preterm birth, and persistent disparities in care contributing to adverse outcomes for mothers. In addition, mental health difficulties in the perinatal period are associated with poorer developmental outcomes for young children and impose an economic burden on societies. Addressing these issues requires innovative approaches that can complement traditional clinical practices. Artificial intelligence (AI) has emerged as a powerful tool with the potential to transform perinatal care by enabling early risk prediction, personalised interventions, and scalable support systems. However, there are no existing reviews on use of AI across different stages of perinatal mental health. We conclude with a call to action for clinicians, researchers, policymakers, and technology developers to collaborate on a consensus framework that ensures ethical, safe, and equitable integration of AI into perinatal care.