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Globally, including Indonesia, pregnant women are vulnerable population to experience symptoms of anxiety and depression. If these two symptoms are not identified and treated during pregnancy, it will have an impact on maternal and child health, such as suicide, pre-eclampsia, postpartum depression, premature, and low birth weight. Therefore, screening for symptoms of anxiety and depression in pregnant women is very important. However, Indonesia does not yet have instruments and protocols for screening symptoms of anxiety and depression in pregnant women in antenatal care (ANC) both conventionally and the use of digital technology. In fact, Indonesia already has a mental health assessment policy in ANC since July, 2021 and is currently carrying out a digital health transformation to improve the quality of health services. This study aimed to develop a screening system for symptoms of anxiety and depression in pregnant women based on an expert system in ANC.
The study consists of three stages. Phase 1 tested the validity and reliability of the Indonesian version of the Edinburgh Postnatal Depression Scale (EPDS) instrument on 125 pregnant women online through the dissemination of Google forms. Phase 2 assessed the screening ability of EPDS instrument compared to MINI-International Neuropsychiatric Interview (MINI) instrument as gold standard in 298 pregnant women. This 2nd phase was carried out in Depok City (Beji, Cipayung, Jati Jajar, and Pancoran Mas public health centre). The MINI assessment was carried out online by two trained enumerators. The 3rd stage was carried out by developing a prototype of an anxiety and depression symptom screening system based on expert system. Statistical analysis at stage 1 employed various types of validity and reliability tests. The 2nd stage was carried out to test sensitivity and specificity. The 3rd stage was evaluated on the accuracy of the expert system and the feasibility of the prototype.
This study produced an Indonesian version of the EPDS instrument that was proven to be valid and reliable for use in the population of pregnant women. This instrument had a sensitivity and specificity of > 90% for screening for symptoms of pregnancy anxiety and depression. The proportion of accuracy in expert systems was > 90%. Pregnant women state that this prototype was easy, short assessment time, and useful to use.
The prototype based on expert system called BMoms, was feasible and able to be carried out for screening symptoms of anxiety and depression in pregnant women in ANC. The BMoms prototype can be further developed into a ready and appropriate application so that it becomes an innovative solution for mental health screening in pregnant women.
Family Planning (FP) participation impacts fertility rates and population growth. The use of modern contraception among Generation Z has declined over the past two decades and is the lowest prevalence compared to other age groups. The solution offered is a predictive model for FP participation. This study aims to find a predictive model for FP participation at the community level. The methodology used is a sequential mixed method explanatory design with 5 research stages, stage 1 systemic literature review, stage 2 development of a predictive model using quantitative studies starting with statistics then machine learning, stage 3 analysis of system needs with qualitative studies on FP officers, WUSand related leadership elements, stage 4 development of a prototipe, stage 5 prototipe trials to be used as a digital intervention tool equipped with acceptance tests and efficacy tests with a Quasi-experimental design with a control group in Bandung City. The results of the study indicate that predictors of FP participation in Gen Z, with the most dominant variable related to the use of modern contraceptive methods, are the number of living children, with a p-value of 0.001 and an aOR of 26.63, while the results of feature importance in machine learning indicate that the most crucial feature is fertility status. The algorithm that can be obtained with the best performance is the Neural Network with an AUC value of 0.859, an Accuracy value of 0.839 or 83.9%, an F1-score of 0.838, a Precision 84.3%, a Recall of 0.839, and an MCC of 0.682. The results of the acceptance test of family planning officers and participants stated that the family planning participation prediction model was in the good and very good categories. The use and utilization of this prototype succeeded in improving the performance of family planning officers with performance indicators, satisfaction of WUSGen Z, knowledge, and attitudes of family planning officers. The use of this prototype succeeded in improving the attitude of WUSGen Z but was not significant in improving the knowledge of WUSGen Z. Thus, this study concludes that the family planning participation prediction model built in the Dplan KB app prototype can improve the performance of officers at the community level, and has great potential to be an innovative solution in family planning services
ABSTRAK
Latar Belakang: Tingginya angka kematian ibu dan neonatus di Indonesia dipengaruhi oleh berbagai faktor, termasuk kualitas pelayanan kesehatan ibu dan anak (KIA) yang belum mencapai target. Kinerja bidan desa, sebagai ujung tombak pelayanan, dipandang sebagai salah satu faktor krusial yang dapat ditingkatkan melalui supervisi dari bidan koordinator puskesmas. Meskipun demikian, data menunjukkan pelaksanaan supervisi fasilitatif KIA di provinsi Jambi pada tahun 2022 dan 2023 baru mencapai 10.86% dan 17.38% dari target 90%. Khususnya di kabupaten Muaro Jambi, capaiannya lebih rendah lagi, yaitu 11.64% (2022) dan 15.07% (2023). Kesenjangan ini menunjukkan perlunya intervensi strategis untuk meningkatkan kualitas supervisi demi mengoptimalkan kinerja bidan dalam pelayanan KIA.
Tujuan: Mengetahui pengaruh model integrasi midwifery opinion leader dan supervisi fasilitatif terhadap kinerja bidan dan dampaknya pada cakupan pelayanan kesehatan ibu dan anak di Provinsi Jambi tahun 2025.
Metode Penelitian: Penelitian ini merupakan penelitian mixed methods exploratory sequential design terdiri dari 3 tahap yaitu tahap I diawali scoping review, studi pendahuluan dan uji coba instrumen dilanjutkan identifikasi kebutuhan model menggunakan metode kualitatif dengan desain phenomenology. Tahap II meliputi pengembangan model, panel expert, pelatihan dan uji coba model. Tahap III dilakukan uji model terhadap kinerja bidan dengan indikator standar kompetensi kinerja (SKK) dan cakupan pelayanan KIA dengan penelitian quasi experiment pretest-posttest with control designs. Populasi adalah seluruh bidan desa/pustu di provinsi Jambi. Sampel yaitu kelompok intervensi sebanyak 60 responden (di kabupaten Muaro Jambi) dilakukan intervensi model integrasi MOL dan supervisi fasilitatif, sedangkan kelompok kontrol 60 responden (di kota Jambi) dilakukan hanya supervisi fasilitatif. Waktu penelitian pada bulan Mei 2024 hingga Agustus 2025, analisis data dengan univariat, bivariat dan multivariat (Difference in Difference).
Hasil: Berdasarkan identifikasi kebutuhan ditemukan subtema: kinerja bidan, kebutuhan supervisi dan model supervisi. Selanjutnya dilakukan pengembangan model supervisi dengan pendekatan teori COM-B, supportif supervision, midwifery leadership dan coaching sehingga diperoleh model midwifery opinion leader (MOL) yang dapat diintegrasikan dengan program supervisi fasilitatif KIA puskesmas. Hasil uji penerimaan model diperoleh hasil skor tertinggi yaitu sikap terhadap penggunaan rata-rata 4.9 dan terendah yaitu persepsi manfaat dengan skor 4.71. Hasil analisis diff in diff diketahui pada 2 kelompok sebelum dan sesudah intervensi terhadap skor standar kompetensi kerja: penataan pelayanan 1.36(0.24-1.60), asuhan bayi baru lahir 2.36(0.75-3.12) pemeriksaan kehamilan 1.33(0.48-1.82), pemeriksaan ibu bersalin 1.93(1.72-3.65) dan asuhan ibu nifas 1.43(0.30-1.74).Uji dampak model terhadap cakupan KIA yaitu: kunjungan ibu hamil ke-4 (K4)18.25(3.83-22.08), persalinan nakes (PN) 15.53(3.47-19.00), kunjungan nifas (KNF) 15.59(3.41-19.00), kunjungan neonatal lengkap (KNL) 14.35(9.97-24.33), kunjungan bayi (KBY) 19.08 (7.26-26.35) dan kunjungan balita (KBAL) 5.81 (16.14-21.95).
Kesimpulan dan Saran: Model integrasi Midwifery Opinion Leader (MOL) dan supervisi fasilitatif berpengaruh dalam meningkatkan kinerja bidan dalam pelayanan KIA. Disarankan mempertimbangkan model ini dalam kegiatan program supervisi kesehatan ibu dan anak di Puskesmas.
ABSTRACT
Background: The high maternal and neonatal mortality rates in Indonesia are influenced by various factors, including the quality of maternal and child health (MCH) services, which have not yet reached their targets. The performance of village midwives, as the frontline of service delivery, is seen as a crucial factor that can be improved through supervision by health center coordinator midwives. However, data shows that the implementation of facilitative MCH supervision in Jambi province in 2022 and 2023 has only reached 10.86% and 17.38% of the 90% target. In Muaro Jambi district, in particular, the achievement was even lower, at 11.64% (2022) and 15.07% (2023). This gap indicates the need for strategic interventions to improve the quality of supervision in order to optimize the performance of midwives in MCH services.
Objective: To determine the effect of the midwifery opinion leader integration model and facilitative supervision on midwives' performance and its impact on the coverage of maternal and child health services in Jambi Province in 2025.
Research Method: This research is a mixed methods exploratory sequential design consisting of 3 stages, namely stage I, which begins with a scoping review, preliminary study, and instrument testing, followed by the identification of model requirements using a qualitative method with a phenomenology design. Stage II includes model development, expert panel, training, and model testing. Phase III involved testing the model on midwives' performance using standard competency performance (SKK) indicators and MCH service coverage using a quasi-experimental pretest-posttest with control designs. The population consisted of all village midwives/health workers in Jambi Province. The sample consisted of an intervention group of 60 respondents (in Muaro Jambi district) who underwent the MOL integration model intervention and facilitative supervision, while the control group of 60 respondents (in Jambi city) only underwent facilitative supervision. The research period was from May 2024 to August 2025, with data analysis using univariate, bivariate, and multivariate (Difference in Difference) methods.
Results: Based on the identification of needs, the following sub-themes were found: midwife performance, supervision needs, and supervision models. Subsequently, a supervision model was developed using the COM-B theory, supportive supervision, midwifery leadership, and coaching approaches, resulting in a midwifery opinion leader (MOL) model that can be integrated with the KIA puskesmas facilitative supervision program. The model acceptance test results showed the highest score for attitude toward use, with an average of 4.9, and the lowest score for perceived benefits, with a score of 4.71. The results of the diff in diff analysis showed that in the two groups before and after the intervention, the standard work competency scores were: service management 1.36 (0.24-1.60), newborn care 2.36 (0.75-3.12), pregnancy check-ups 1.33 (0.48-1.82), maternity check-ups 1.93 (1.72-3.65), and postpartum care 1.43 (0.30-1.74). The model's impact on MCH coverage was as follows: fourth antenatal visit (K4) 18.25 (3.83-22.08), skilled birth attendance (PN) 15.53 (3.47-19.00), postnatal visit (KNF) 15.59 (3.41-19. 00), complete neonatal visits (KNL) 14.35 (9.97-24.33), infant visits (KBY) 19.08 (7.26-26.35), and toddler visits (KBAL) 5.81 (16.14-21.95).
Conclusion and Recommendations: The integration model of Midwifery Opinion Leader (MOL) and facilitative supervision has an impact on improving midwives' performance in maternal and child health services. It is recommended to consider this model in maternal and child health supervision program activities at health centers.
