From mother to infant: predicting infant temperament using maternal mental health measures and tabular machine learning models.

ABSTRACT:

Background

Negative emotionality is a core dimension of infant temperament, characterized by heightened distress, reactivity, and difficulty with self-regulation. It has been consistently associated with later behavioral and emotional difficulties. Emerging evidence suggests that maternal mental health (MMH) in the postpartum period may influence infant temperament. However, few studies have applied machine learning (ML) methods to examine the predictive capacity of MMH profiles for early infant emotional development.

Objectives

This study aimed to investigate whether postpartum maternal depression, anxiety, and birth-related trauma, along with sociodemographic factors, can predict infant negative emotionality during the first year postpartum using tabular ML models.

Meth

SUBMITTER: AlSaad R 

PROVIDER: S-EPMC12490419 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature