Early identification of postpartum depression using demographic, clinical, and digital phenotyping

Abstract

AbstractPostpartum depression (PPD) and adjustment disorder (AD) affect up to 25% of women after childbirth. However, there are no accurate screening tools for either disorder to identify at-risk mothers and enable them to benefit from early intervention. Combinations of anamnestic, clinical, and remote assessments were evaluated for an early and accurate identification of PPD and AD. Two cohorts of mothers giving birth were included in the study (N = 308 and N = 193). At baseline, participants underwent a detailed sociodemographic-anamnestic and clinical interview. Remote assessments were collected over 12 weeks comprising mood and stress levels as well as depression and attachment scores. At 12 weeks postpartum, an experienced clinician assigned the participants to three distinct groups: women with PPD, women with AD, and healthy controls (HC). Combinations of these assessments were assessed for an early an accurate detection of PPD and AD in the first cohort and, after pre-registration, validated in a prospective second cohort. Combinations of postnatal depression, attachment (for AD) and mood scores at week 3 achieved balanced accuracies of 93 and 79% for differentiation of PPD and AD from HC in the validation cohort and balanced accuracies of 87 and 91% in the first cohort. Differentiation between AD and PPD, with a balanced accuracy of 73% was possible at week 6 based on mood levels only with a balanced accuracy of 73% in the validation cohort and a balanced accuracy of 76% in the first cohort. Combinations of in clinic and remote self-assessments allow for early and accurate detection of PPD and AD as early as three weeks postpartum, enabling early intervention to the benefit of both mothers and children.