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

Abstract Postpartum 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 r...

Full description

Bibliographic Details
Main Authors: Lisa Hahn, Simon B. Eickhoff, Ute Habel, Elmar Stickeler, Patricia Schnakenberg, Tamme W. Goecke, Susanne Stickel, Matthias Franz, Juergen Dukart, Natalia Chechko
Format: Article
Language:English
Published: Nature Publishing Group 2021-02-01
Series:Translational Psychiatry
Online Access:https://doi.org/10.1038/s41398-021-01245-6
id doaj-893533bc704b4c4cb9ae99ea25aac5ce
record_format Article
spelling doaj-893533bc704b4c4cb9ae99ea25aac5ce2021-02-14T12:49:20ZengNature Publishing GroupTranslational Psychiatry2158-31882021-02-0111111010.1038/s41398-021-01245-6Early identification of postpartum depression using demographic, clinical, and digital phenotypingLisa Hahn0Simon B. Eickhoff1Ute Habel2Elmar Stickeler3Patricia Schnakenberg4Tamme W. Goecke5Susanne Stickel6Matthias Franz7Juergen Dukart8Natalia Chechko9Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre JülichInstitute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre JülichDepartment of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, Uniklinik RWTH Aachen UniversityDepartment of Gynecology and Obstetrics, Medical Faculty, Uniklinik RWTH Aachen UniversityInstitute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre JülichDepartment of Gynecology and Obstetrics, Medical Faculty, Uniklinik RWTH Aachen UniversityDepartment of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, Uniklinik RWTH Aachen UniversityClinical Institute of Psychosomatic Medicine and Psychotherapy, Medical Faculty, Heinrich-Heine-Universität DüsseldorfInstitute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre JülichInstitute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre JülichAbstract Postpartum 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.https://doi.org/10.1038/s41398-021-01245-6
collection DOAJ
language English
format Article
sources DOAJ
author Lisa Hahn
Simon B. Eickhoff
Ute Habel
Elmar Stickeler
Patricia Schnakenberg
Tamme W. Goecke
Susanne Stickel
Matthias Franz
Juergen Dukart
Natalia Chechko
spellingShingle Lisa Hahn
Simon B. Eickhoff
Ute Habel
Elmar Stickeler
Patricia Schnakenberg
Tamme W. Goecke
Susanne Stickel
Matthias Franz
Juergen Dukart
Natalia Chechko
Early identification of postpartum depression using demographic, clinical, and digital phenotyping
Translational Psychiatry
author_facet Lisa Hahn
Simon B. Eickhoff
Ute Habel
Elmar Stickeler
Patricia Schnakenberg
Tamme W. Goecke
Susanne Stickel
Matthias Franz
Juergen Dukart
Natalia Chechko
author_sort Lisa Hahn
title Early identification of postpartum depression using demographic, clinical, and digital phenotyping
title_short Early identification of postpartum depression using demographic, clinical, and digital phenotyping
title_full Early identification of postpartum depression using demographic, clinical, and digital phenotyping
title_fullStr Early identification of postpartum depression using demographic, clinical, and digital phenotyping
title_full_unstemmed Early identification of postpartum depression using demographic, clinical, and digital phenotyping
title_sort early identification of postpartum depression using demographic, clinical, and digital phenotyping
publisher Nature Publishing Group
series Translational Psychiatry
issn 2158-3188
publishDate 2021-02-01
description Abstract Postpartum 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.
url https://doi.org/10.1038/s41398-021-01245-6
work_keys_str_mv AT lisahahn earlyidentificationofpostpartumdepressionusingdemographicclinicalanddigitalphenotyping
AT simonbeickhoff earlyidentificationofpostpartumdepressionusingdemographicclinicalanddigitalphenotyping
AT utehabel earlyidentificationofpostpartumdepressionusingdemographicclinicalanddigitalphenotyping
AT elmarstickeler earlyidentificationofpostpartumdepressionusingdemographicclinicalanddigitalphenotyping
AT patriciaschnakenberg earlyidentificationofpostpartumdepressionusingdemographicclinicalanddigitalphenotyping
AT tammewgoecke earlyidentificationofpostpartumdepressionusingdemographicclinicalanddigitalphenotyping
AT susannestickel earlyidentificationofpostpartumdepressionusingdemographicclinicalanddigitalphenotyping
AT matthiasfranz earlyidentificationofpostpartumdepressionusingdemographicclinicalanddigitalphenotyping
AT juergendukart earlyidentificationofpostpartumdepressionusingdemographicclinicalanddigitalphenotyping
AT nataliachechko earlyidentificationofpostpartumdepressionusingdemographicclinicalanddigitalphenotyping
_version_ 1724269970614910976