Looking Ahead: Pre- and Perinatal Interventions for Maternal Distress to Prevent Neurodevelopmental Vulnerability

Brown, Hilary; Krogh-Jespersen, Sheila; Tandon, Darius; Graham, Alice M.; Seghete, Kristen Mackiewicz; Wakschlag, Lauren S.

doi:10.1007/978-3-030-60159-1_20

Cited by 8 publications

(7 citation statements)

References 84 publications

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“…Creating a sustainable system that incorporates the collection of perceived mental health status will require directly providing more value to users. Furthermore, as perceived stress is malleable to psychological intervention whereas chronic stress is not, perceived stress is a viable intervention target [ 45 , 58 ].…”

Section: Discussionmentioning

confidence: 99%

Predicting the Next-Day Perceived and Physiological Stress of Pregnant Women by Using Machine Learning and Explainability: Algorithm Development and Validation

Ng¹,

Wei²,

Jain³

et al. 2022

JMIR Mhealth Uhealth

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Background Cognitive behavioral therapy–based interventions are effective in reducing prenatal stress, which can have severe adverse health effects on mothers and newborns if unaddressed. Predicting next-day physiological or perceived stress can help to inform and enable pre-emptive interventions for a likely physiologically and perceptibly stressful day. Machine learning models are useful tools that can be developed to predict next-day physiological and perceived stress by using data collected from the previous day. Such models can improve our understanding of the specific factors that predict physiological and perceived stress and allow researchers to develop systems that collect selected features for assessment in clinical trials to minimize the burden of data collection. Objective The aim of this study was to build and evaluate a machine-learned model that predicts next-day physiological and perceived stress by using sensor-based, ecological momentary assessment (EMA)–based, and intervention-based features and to explain the prediction results. Methods We enrolled pregnant women into a prospective proof-of-concept study and collected electrocardiography, EMA, and cognitive behavioral therapy intervention data over 12 weeks. We used the data to train and evaluate 6 machine learning models to predict next-day physiological and perceived stress. After selecting the best performing model, Shapley Additive Explanations were used to identify the feature importance and explainability of each feature. Results A total of 16 pregnant women enrolled in the study. Overall, 4157.18 hours of data were collected, and participants answered 2838 EMAs. After applying feature selection, 8 and 10 features were found to positively predict next-day physiological and perceived stress, respectively. A random forest classifier performed the best in predicting next-day physiological stress (F1 score of 0.84) and next-day perceived stress (F1 score of 0.74) by using all features. Although any subset of sensor-based, EMA-based, or intervention-based features could reliably predict next-day physiological stress, EMA-based features were necessary to predict next-day perceived stress. The analysis of explainability metrics showed that the prolonged duration of physiological stress was highly predictive of next-day physiological stress and that physiological stress and perceived stress were temporally divergent. Conclusions In this study, we were able to build interpretable machine learning models to predict next-day physiological and perceived stress, and we identified unique features that were highly predictive of next-day stress that can help to reduce the burden of data collection.

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Section: Discussionmentioning

confidence: 99%

Predicting the Next-Day Perceived and Physiological Stress of Pregnant Women by Using Machine Learning and Explainability: Algorithm Development and Validation

Ng¹,

Wei²,

Jain³

et al. 2022

JMIR Mhealth Uhealth

Self Cite

View full text Add to dashboard Cite

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“…Prior studies suggest that MB can influence parenting and child outcomes. Although a number of studies have shown post-hoc effects of perinatal intervention on child outcomes [69], studies apriori designed to examine mechanisms of effect on improved child outcomes are far less common [23]. EPIC is designed with power to examine mechanisms by which improved maternal regulation leads to children's self-regulatory competence, a theorized pathway by which bolstered maternal mental health provides the foundation for a robust adaptive pathway for offspring.…”

Section: Discussionmentioning

confidence: 99%

“…Thus, even if they are able to improve their parenting practices in the short term, mothers at risk for depression are likely to revert back to emotional and cognitive patterns that impair their ability to engage in responsive, positive interactions with their child. Given evidence of an association between improvement in maternal depression and improvement in parenting and young child outcomes [21], interventions explicitly focused on promoting maternal mental health may result in greater impact on parenting and child development [22,23].…”

Section: Introductionmentioning

confidence: 99%

Testing the effects of a prenatal depression preventive intervention on parenting and young children’s self-regulation and functioning (EPIC): protocol for a longitudinal observational study

et al. 2021

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Background Perinatal depression is a pervasive public health concern that disproportionately affects low-income women and can have negative impacts on parenting and child developmental outcomes. Few interventions focus on preventing perinatal depression. Previous studies suggest that Mothers and Babies is efficacious in preventing the worsening of depressive symptoms and the onset of postpartum depression. This manuscript presents the protocol of the EPIC study (Effects of a Prenatal Depression Preventive Intervention on parenting and young children’s Self-Regulation and Functioning) to test the effects of Mothers and Babies on parenting and child developmental outcomes through 54 months postpartum. EPIC is an observational study that builds on a completed cluster-randomized trial (CRT). Innovations of this study are direct observations of a subsample of mother-child dyads and the inclusion of fathers/caregivers’ variables as moderators of maternal mental health. Methods For this study, we plan to enroll 738 women with children under 30 months old, ≥18 years old, and who speak English or Spanish. Additionally, 429 fathers, partners, or other adult caregivers will be recruited through women participating in the study. Women will be recruited through the parent study (intervention and control participants) or through one of 10 home visiting programs in Illinois (control participants). Data collection will take place through maternal self-report at five time points (when the child is 30, 36, 42, 48, and 54 months), paternal self-report at three time points (when the child is 30, 42, and 54 months), and through mother-child observations at three time points (when the child is 36, 42, and 48 months). Outcome domains include maternal mental health, cognitive-behavioral and parenting skills, and child self-regulation and functioning. Moderators include the contributions of fathers/caregivers, race-ethnicity, and socioeconomic disadvantage. Power and sample size were calculated assuming a two-sided 5% type I error rate and assumed analyses on the individual level. Discussion This study has several key strengths and innovations, as well as great potential significance to influence the long-term trajectories of parenting and child development via prenatal intervention. Trial registration The study was retrospectively registered at ClinicalTrials.gov (Identifier: NCT04296734) on March 5, 2020.

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“…Number of children in the home as an imperfect proxy for parity was also considered, as previous research has demonstrated links between parity and prenatal stress and infant emotional reactivity (Grant et al., 2010 ; Katus et al., 2022 ). Finally, prenatal anxious and depressive symptoms have been linked to prenatal stress and infant emotional problems (Brown et al., 2021 ; Davis et al., 2007 ), thus we included correlations with the State‐Trait Anxiety Inventory Trait sum score (Spielberger, 1983 ) and the PROMIS Depression Short Form T scores (Pilkonis et al., 2011 ).…”

Section: Methodsmentioning

confidence: 99%

“…Elucidating intraindividual variation in perceived stress, and the contexts under which this variation occurs, may help pinpoint nonoptimal patterns of stress and therefore aid in the translation from research to prevention of poor child outcomes. Such prevention/intervention efforts in pregnancy may be particularly advantageous because the majority of US women receive regular prenatal care (Brown et al., 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Lability of prenatal stress during the COVID‐19 pandemic links to negative affect in infancy

MacNeill

Krogh-Jespersen

Zhang

et al. 2022

Infancy

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The association between prenatal stress and children's socioemotional development is well established. The COVID‐19 pandemic has been a particularly stressful period, which may impact the gestational environment. However, most studies to‐date have examined prenatal stress at a single time point, potentially masking the natural variation in stress that occurs over time, especially during a time as uncertain as the pandemic. This study leveraged dense ecological momentary assessments from a prenatal randomized control trial to examine patterns of prenatal stress over a 14‐week period (up to four assessments/day) in a U.S. sample of 72 mothers and infants. We first examined whether varied features of stress exposure (lability, mean, and baseline stress) differed depending on whether mothers reported on their stress before or during the pandemic. We next examined which features of stress were associated with 3‐month‐old infants' negative affect. We did not find differences in stress patterns before and during the pandemic. However, greater stress lability, accounting for baseline and mean stress, was associated with higher infant negative affect. These findings suggest that pathways from prenatal stress exposure to infant socioemotional development are complex, and close attention to stress patterns over time will be important for explicating these pathways.

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Looking Ahead: Pre- and Perinatal Interventions for Maternal Distress to Prevent Neurodevelopmental Vulnerability

Cited by 8 publications

References 84 publications

Predicting the Next-Day Perceived and Physiological Stress of Pregnant Women by Using Machine Learning and Explainability: Algorithm Development and Validation

Predicting the Next-Day Perceived and Physiological Stress of Pregnant Women by Using Machine Learning and Explainability: Algorithm Development and Validation

Testing the effects of a prenatal depression preventive intervention on parenting and young children’s self-regulation and functioning (EPIC): protocol for a longitudinal observational study

Lability of prenatal stress during the COVID‐19 pandemic links to negative affect in infancy

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