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All Journal Journal of Maternal and Child Health Jurnal Cakrawala Promkes
Faujiah, Irfa Nur
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Medicine & Pharmacology Public Health

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Meta-Analysis of the Effect of Prenatal Stress on the Premature Birth Faujiah, Irfa Nur; Murti, Bhisma; Prasetya, Hanung
Journal of Maternal and Child Health Vol. 5 No. 6 (2020)
Publisher : Masters Program in Public Health, Universitas Sebelas Maret, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (33.872 KB)

Abstract

Background: Premature birth is a major global public health problem, especially in developing countries. One of the causes of this incident is exposure to psychological stress experienced during pregnancy. This study aims to estimate the magnitude of the effect of prenatal stress on preterm birth using a meta-analysis study.Subjects and Method: The meta-analysis research was conducted by selecting articles published in the years 2006-2020, from the PubMed, Google Scholar, Science Direct, Direc
AI-powered whatsapp chatbots for maternal and child health: a quasi-experimental study among pregnant women in Indonesia Faujiah, Irfa Nur; Raraswati , Rhela Panji
Jurnal Cakrawala Promkes Vol. 7 No. 2 (2025): August
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jcp.v7i2.13858

Abstract

Maternal and child health remains a critical priority in global health strategies, particularly in achieving the Sustainable Development Goals (SDGs). In Indonesia, maternal mortality remains significantly higher than the SDG target, underscoring the urgent need for accessible and high-quality maternal health information. Digital innovations, such as Artificial Intelligence (AI)-based chatbots, have emerged as promising tools to help bridge this gap. This study aimed to evaluate the effectiveness of a Meta-AI chatbot delivered via WhatsApp in improving pregnant women’s access to maternal and child health information. A quasi-experimental one-group pretest–posttest design was employed, involving 30 pregnant women in Singasari Village, Tasikmalaya Regency. Participants received a one-time training session on accessing health information—particularly related to pregnancy care—through the Meta-AI WhatsApp chatbot, supported by a guidance booklet. Data were collected using a validated and reliable questionnaire that assessed participants’ knowledge and skills before and after the intervention. Paired sample t-tests were used to compare pre- and post-intervention scores. The results demonstrated significant improvements in both knowledge and skills. Knowledge scores increased from 5.00 (SD = 2.00) to 9.40 (SD = 0.85), t(29) = 29.0, p < 0.001, Cohen’s d = 1.88, 95% CI [1.27, 2.47]. Similarly, skills scores rose from 26.5 (SD = 5.40) to 36.7 (SD = 3.02), t(29) = 29.0, p < 0.001, Cohen’s d = 2.31, 95% CI [1.61, 2.99]. These findings indicate that the Meta AI chatbot, accessed via WhatsApp, significantly enhanced pregnant women’s knowledge and skills, thereby improving access to accurate maternal health information, strengthening health literacy, and supporting informed decision-making. Future research should explore the long-term effects of this intervention and its potential integration into public health systems.
Stress and Maladaptive Psychological Responses as Predictors of Postpartum Depression Faujiah, Irfa Nur; Ambari, Alvin Alvani Tresna; Saefudin, Muhamad Arif
Journal of Maternal and Child Health Vol. 10 No. 6 (2025)
Publisher : Masters Program in Public Health, Universitas Sebelas Maret, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26911/thejmch.2025.10.06.02

Abstract

Background: Unmanaged stress and maladaptive psychological responses during the postpartum period increase the risk of postpartum depression, highlighting the need for evidence-based interventions in primary health care. This study aimed to analyze the influence of stress levels and psychological adjustment difficulties as risk factors for postpartum depression among mothers in the Singaparna Primary Health Care area.Subjects and Method: A cross-sectional study was conducted in five villages within the Singaparna Primary Health Care. A total of 150 postpartum mothers were recruited purposively. The independent variables were stress levels and psychological adjustment. The was dependent variable was postpartum depression. Data on stress were collected usng the Perceived Stress Scale (PSS-10). Psychological adjustment was measured using the Postpartum Adjustment Questionnaire (PAQ-15).  Postpartum depression was assessed using the Edinburgh Postnatal Depression Scale (EPDS). Reliability and construct validity were confirmed, and Structural Equation Modeling (SEM) was applied to assess predictive relationships.Results: Maladaptive stress responses significantly reduced postpartum depression (β = 0.54, p= 0.002), Positive stress perception (β = 0.133, p= 0.302) and postpartum adjustment (β= 0.124, p= 0.159) were insignificantly associated. The SEM model showed acceptable fit (RMSEA= 0.06; CFI= 0.89; TLI = 0.88; SRMR= 0.07).Conclusion: Maladaptive stress responses are a key psychosocial risk factor for postpartum depression, whereas postpartum adjustment and positive stress perception show limited influence. Early screening and psychosocial interventions in primary care are essential to reduce postpartum depression and improve maternal mental health outcomes.
Co-Authors Ambari, Alvin Alvani Tresna Arif Saefudin Bhisma Murti Prasetya, Hanung Raraswati , Rhela Panji