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All Journal Journal of Applied Data Sciences Jurnal Bidan Cerdas
Fitriana Fitriana
Departement Of Midwifery, Faculty Of Health, Aisyah University, Lampung, Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Public Health

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Islamic-Informed Spiritual-Empathic Listening Support for Postpartum Trauma: A Rapid Evidence Review Fitriana Fitriana; Yudhia Fratidina; Feri Kameliawati; Rahayu Sri Astutik
Jurnal Bidan Cerdas Vol. 8 No. 1 (2026)
Publisher : Poltekkes Kemenkes Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33860/jbc.v8i1.4333

Abstract

Background: A worldwide health concern is postnatal psychological discomfort, which includes symptoms of anxiety, and despair. Although listening-based therapies have become popular as flexible, low-cost ways to treat maternal mental health, there is currently little data on their efficacy and cultural fit. With an emphasis on Islamic-informed approaches, this study sought to compile the most recent data on the efficacy, viability, and cultural significance of listening services in enhancing maternal psychological outcomes. Methods: A Rapid Evidence Review (RER) was conducted following PRISMA 2020 guidelines. Twelve empirical studies published between 2018 and May 2025 were included (4 randomized controlled trials, 3 quasi-experimental studies, 3 observational studies, 1 qualitative, and 1 mixed-method design). Results: Ten of the twelve studies (83%) reported statistically significant reductions in maternal psychological distress. Randomized controlled trials demonstrated measurable decreases in EPDS, PCL-5, and DASS-21 scores following structured midwife-led debriefing or counseling sessions. Several interventions showed significant reductions in postpartum anxiety and PTSD symptoms after brief (1–4 session) models. Faith-integrated listening approaches in Muslim-majority settings enhanced spiritual resilience, emotional validation, and cultural acceptability. Digital and telehealth modalities improved accessibility, particularly during the COVID-19 pandemic, although higher attrition rates and short follow-up durations were frequently noted. Conclusion: Postnatal listening services are an efficient and affordable way to improve the psychological well-being of mothers when paired with treatment that is sensitive to cultural and spiritual differences. Future studies and clinical applications should place a high priority on formalizing Islamic informed listening frameworks in midwifery practice in Muslim communities.
Software to predict maternal and child health risks with machine learning Fitriana Fitriana; Zulkifli Zulkifli; Sri Rahayu
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1088

Abstract

Objective: Maternal healthcare services are essential in public health, prioritizing the health and well-being of women throughout pregnancy, childbirth, as well as the postpartum period. The services include various efforts to safeguard the health of both the mother and the unborn child. During these stages, mothers face numerous risks and complications, making early risk detection critical for ensuring the safety of the pregnancy. Method: A novel method is needed that enables more accurate and affordable screening to improve early detection as well as increase maternal and child healthcare. Therefore, this study aimed to propose a solution including the development of software that uses the Naive Bayes algorithm to predict maternal and child health risks. The perceptions provided by the application served as an initial diagnostic reference for both expectant mothers and healthcare providers, offering a cost-effective as well as precise alternative. Result: During the analysis, the Naive Bayes algorithm was compared with Neural Network (NN) and Random Forest (RF) models to evaluate the prediction accuracy. Among the models used, NN produced the lowest accuracy at 48%. Conclusion: The estimated cost for developing this application was IDR 1,635,913.
Co-Authors Feri Kameliawati Rahayu Sri Astutik Sri Rahayu Yudhia Fratidina Zulkifli Zulkifli