Journal Article2026

mHealth apps for maternal mental well-being among pregnant and postpartum women: a systematic review

Syed Niaz Mohtasim, Faiza Omar Arpita, Istiaq Ahmed, Ashraful Islam, M. Ashraful Amin, Beenish Moalla Chaudhry

mHealth

AME Publishing Company, Vol. 12, pp. 23-23, ISBN: 2306-9740

  • Good Health and Well-being — Relevance: 97%
  • Gender Equality — Relevance: 85%

Abstract

Background: Maternal mental well-being during and after pregnancy is often overlooked, posing serious long-term risks to mothers and children. This systematic review aims to synthesize research on mobile health (mHealth) applications (apps) designed to support perinatal and postpartum mental well-being, with a focus on their design characteristics, intervention approaches, and reported effectiveness. Methods: We conducted a systematic review following the PRISMA 2020 guidelines. PubMed and Scopus were searched up to August 2025. Studies were included if they reported original research on mHealth apps targeting maternal mental well-being during or after pregnancy with a diagnostic or intervention component for mental health. Review papers, conference abstracts, and studies without an mHealth component were excluded. Results: From 2,127 articles, 15 met the inclusion criteria. These studies, published between 2017 and 2024, evaluated 13 distinct mHealth apps targeting primarily anxiety (12 studies), depression (8 studies), and stress (4 studies). Across all 15 studies, 24 screening methods were reported. Apps delivered interventions including mindfulness and guided meditation (7 studies) and cognitive behavioral therapy (CBT)-based tools and mood tracking (7 studies). Six app feature categories were identified: mental health screening, physical and mental well-being exercises and meditation, health education, visual design elements, healthcare support, and additional support features. Usability and engagement were most commonly evaluated using questionnaires and surveys (4 studies) and the Mobile Application Rating Scale (MARS) (3 studies). Six studies reported positive outcomes for depression symptoms. Common methodological limitations included small sample sizes, high dropout rates, and lack of long-term follow-up, constraining the generalizability of findings. Conclusions: This review demonstrates the potential of mHealth apps as accessible tools for supporting maternal mental well-being during pregnancy and the postpartum period. Clinicians should regard these tools as supplementary rather than standalone interventions until larger-scale efficacy trials are available. App developers are encouraged to design solutions that span both prenatal and postnatal periods, address multiple mental health conditions simultaneously, integrate validated screening methods, and combine health education, therapeutic, and behavioral support within a single platform. Future research should prioritize robust, longitudinal trials with diverse populations and standardized outcome measures to establish the evidence base needed for broader integration of mHealth into perinatal care.

Keywords

  • mood tracking
  • maternal mental health
  • cognitive behavioral therapy
  • perinatal mental health
  • postpartum depression
  • mental health screening
  • perinatal care
  • mobile health apps
  • prenatal stress
  • prenatal anxiety

CCDS Authors

Istiaq Ahmed
Istiaq Ahmed

Istiaq Ahmed

  • Research Assistant, HCI Wing

Published at

CHI, HCII

Research Interests

mHealth, Human-Computer Interaction, Cross-Platform App/Website Development

Ashraful Islam, PhD
Ashraful Islam

Ashraful Islam, PhD

  • Center Director, CCDS
  • Director, HCI Wing

Assistant Professor

Department of Computer Science and Engineering

Independent University, Bangladesh (IUB)

Published at

CHI, UIST, UbiComp, IJCNN, ICIP, HCII, ICDMW, BLP, IEEE Internet of Things Journal, JMIR, JMIR Human Factors, JMIR Formative Research, IEEE Access, Smart Agricultural Technology, Diabetes Research and Clinical Practice, PLOS ONE

Research Interests

Human-Computer Interaction, AI for Social Good, AI for Public Health, AI for Impact

Prof. M Ashraful Amin, PhD
M Ashraful Amin, PhD

Prof. M Ashraful Amin, PhD

  • Founder Director, CCDS
  • Director, AI/ML, HCI & DS Wings

Professor

+1 more affiliation

Department of Information Sciences and Technology

George Mason University, USA

Published at

ACL, CHI, UbiComp, ECAI, WACV, PAKDD, IJCNN, ICPR, ICIP, HCII, CLEF, BLP, Scientific Reports, JMIR, IEEE Access, Smart Agricultural Technology, Frontiers in Computational Neuroscience, Diabetes Research and Clinical Practice, PLOS ONE

Research Interests

Machine Learning, Cognitive & Vision Science, Cybernetics, Surveillance & Security, ICT in Education, Health, & Agriculture, Human-Computer Interaction, Internet of Things, Robotics

Beenish Moalla Chaudhry, PhD
Beenish Moalla Chaudhry, PhD

Beenish Moalla Chaudhry, PhD

  • Collaborator, HCI Wing

Associate Professor

School of Computing and Informatics

University of Louisiana at Lafayette

Published at

UIST, HCII, JMIR Human Factors, JMIR Formative Research