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Nur Agustini
Fakultas Ilmu Keperawatan Universitas Indonesia
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Diagnostic Accuracy of Delirium Assessment Tools Among Critically Ill Infant : A Systematic Review Rahmadhani, Dewi Astika; Ningsih, Risna; Setiawati, Atik; Chodidjah, Siti; Agustini, Nur; Huda, Mega Hasanul
Indonesian Journal of Global Health Research Vol 7 No 3 (2025): Indonesian Journal of Global Health Research
Publisher : GLOBAL HEALTH SCIENCE GROUP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37287/ijghr.v7i3.6214

Abstract

Delirium is an acute change in neurologic function that can potentially lead to longterm impacts on children’s cognitive development and the quality of life. Infants under 12 months are particularly vulnerable because their cognitive and language abilities are not fully developed. Therefore, healthcare professionals need to enhance their knowledge of delirium symptoms, child development stages, and how to identify it in this age group to better detection and management. This study aims to evaluate the diagnostic accuracy of delirium assessment tools, namely the Cornell Assessment of Pediatric Delirium (CAPD), the Preschool Confusion Assessment Method for the ICU (psCAM-ICU), and the Sophia Observation Withdrawal Symptoms Pediatric Delirium (SOSPD), in detecting delirium in critically ill infants. This systematic review follows the PRISMA 2020 guidelines and includes a literature search in PubMed, Scopus, ProQuest, ScienceDirect, and Taylor & Francis from 2013 to 2023. Inclusion criteria consist of observational studies involving infants aged 0-11 months in ICU settings that utilized CAPD, psCAM-ICU, or SOSPD for delirium detection. The quality of the studies was assessed using the JBI Critical Appraisal Checklist for Studies Reporting Diagnostic Test Accuracy. Result : The analysis indicates that the SOSPD tool has a sensitivity ranging from 76.9% to 96.8% and specificity between 92% and 96.4%. The CAPD shows sensitivity from 87% to 94.1% and specificity from 88% to 98%. The psCAM exhibits sensitivity from 75% to 95% and specificity from 81% to 91%. The results demonstrate variability in accuracy depending on the age group and clinical condition of the children. Based on the research findings, psCAM is recommended as the most effective tool for detecting delirium in the infant population due to its ease of use and high accuracy. Early detection of delirium is crucial for enhancing clinical management and improving outcomes in critically ill infants.
Intervensi keperawatan berdasarkan teori Becoming a Mother dari Mercer: Sebuah kajian pustaka Yani, Erna Rahma; Rustina, Yeni; Agustini, Nur; Mudzakkir, Muhammad
Holistik Jurnal Kesehatan Vol. 19 No. 10 (2025): Volume 19 Nomor 10
Publisher : Program Studi Ilmu Keperawatan-fakultas Ilmu Kesehatan Universitas Malahayati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33024/hjk.v19i10.1854

Abstract

Background: The process of becoming a mother requires mothers to adapt during the transition that occurs immediately after childbirth. Nursing interventions based on Mercer's theory of becoming a mother have been developed in several countries, but their form and scope have not been comprehensively mapped. Purpose: To explore and map the scientific evidence for nursing interventions based on Mercer's theory of becoming a mother. Method: A scoping review was conducted based on Joanna Briggs Institute (JBI) guidelines. Articles were searched in PubMed, Scopus, Proquest, and ScienceDirect databases using a search strategy based on the Population-Concept-Context (PCC) framework. Keywords and synonyms relevant to nursing interventions, the process of becoming a mother, and the postpartum period were identified. A combination of free keywords and standard terms (Medical Subject Headings/MeSH) were used in the search using Boolean operators (AND and OR). Analysis included the population, intervention characteristics, implementation methods, and reported outcomes. Results: Five articles met the inclusion criteria for further analysis. Nursing interventions based on Mercer's theory were generally developed in the form of structured education, training, counseling, and technology-based multimodal approaches. Interventions delivered from the third trimester of pregnancy through the postpartum period have been shown to be effective in improving maternal role adaptation, self-efficacy, and mother-infant bonding. However, the duration of the interventions and study designs varied across the five articles. Conclusion: Nursing interventions based on Mercer's theory effectively support the parenting process by strengthening knowledge, parenting skills, and emotional adjustment. Further studies are needed for standardization and long-term evaluation. Suggestion: In order to improve the quality of nursing services, it is recommended that nurses develop a theory-based standardized nursing intervention model.   Keywords: Mothering; Mercer's Theory; Nursing Interventions.   Pendahuluan: Proses menjadi ibu memerlukan kemampuan adaptasi maternal pada masa transisi yang terjadi segera setelah melahirkan. Intervensi keperawatan berdasarkan teori Becoming a Mother dari Mercer telah dikembangkan di beberapa negara, namun bentuk dan cakupannya belum dipetakan secara komprehensif. Tujuan: Untuk mengeksplorasi dan memetakan bukti ilmiah dari intervensi keperawatan berdasarkan teori Becoming a Mother dari Mercer. Metode: Scoping review dilakukan dengan berpedoman pada Joanna Briggs Institute (JBI). Pencarian artikel dilakukan pada basis data PubMed, Scopus, Proquest, dan ScienceDirect dengan strategi pencarian berdasarkan kerangka Populasi-Concept-Context (PCC) dengan mengidentifikasi istilah utama dan sinonim yang relevan dengan intervensi keperawatan, proses menjadi ibu (becoming a mother), serta periode postpartum. Kombinasi kata kunci bebas dan istilah baku (Medical Subject Headings/MeSH) digunakan dalam pencarian dengan operator Boolean (AND dan OR). Analisis mencakup populasi, karakteristik intervensi, metode implementasi, dan luaran yang dilaporkan. Hasil: Didapatkan lima artikel memenuhi kriteria inklusi untuk dianalisis lebih lanjut. Intervensi keperawatan berdasarkan teori Mercer umumnya dikembangkan dalam bentuk edukasi terstruktur, pelatihan, konseling, dan pendekatan multimodal berbasis teknologi. Intervensi yang diberikan sejak trimester ketiga kehamilan hingga periode postpartum menunjukkan efektifitas dalam emningkatkan adaptasi peran maternal, efikasi diri, serta ikatan ibu dan bayi. Namun durasi intervensi dan desain penelitian menunjukkan variasi pada kelima artikel. Simpulan: Intervensi keperawatan berbasis teori Mercer efektif mendukung proses menjadi ibu melalui penguatan pada aspek pengetahuan, kemampuan pengasuhan, dan penyelarasan emosional. Studi lanjutan diperlukan untuk standardisasi dan evaluasi jangka panjang. Saran: Guna meningkatkan kualitas layanan keperawatan, disarankan perawat mengembangkan model intervensi keperawatan terstandar berbasis teori.   Kata Kunci: Becoming a Mother; Intervensi Keperawatan; Teori Mercer.
Automated Young Children’s Pain Detection via Facial Expressions with YOLO v11 Ramdhanie, Gusgus Ghraha; Nurdina Widanti; Bambang Aditya Nurgraha; Tomy Abuzairi; Nur Agustini; Dessie Wanda
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 1 (2026): February 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i1.7206

Abstract

This study demonstrates that pain detection in young children using a YOLO v11-based deep learning model can be performed effectively. By utilizing image data taken from video recordings of immunization and IV infusion procedures, then processed into photo frames and labeled using Roboflow, the model is able to provide good evaluation results. The dataset was divided into 70:20:10 for training, validation, and testing. Model performance evaluation uses accuracy, precision, recall, and F1-score metrics, and is visualized through a performance curve and confusion matrix. The results show that YOLO v11 has great potential as a pain detection method, with an mAP@0.5 achievement of 0.893, an accuracy of 78%, a precision of 89.3%, a recall of 97%, and an F1-score of 83%. The high recall value indicates the model's excellent ability to recognize pain expressions, making it relevant for use in clinical contexts to ensure pain symptoms are not overlooked. Overall, this performance demonstrates that YOLO v11 can be a more objective and accurate approach than manual instruments, and has the potential to be developed as a tool for healthcare professionals in pediatric pain assessment.
Co-Authors Adawiyah, Robiyatul Ade Silvia Handayani Allenidekania Allenidekania Allenidekania Anisah Fadhilah Atika Widyanti Bambang Aditya Nurgraha Budi Anna Keliat Budi Keliat Budi Keliat, Budi Chodidjah, Siti Dewi Hayati, Dewi Diah Ayu Agustin Dwi Novrianda ERNA RAHMA YANI Gusgus Ghraha Ramdhanie Hazrina Adelia Ibnu Ziad, Ibnu Ida Ruwaida, Ida Imami Nur Rachmawati Imami Rachmawati, Imami Imas Mulyani Islamia, Ina Krisna Yetti La Ode Abdul Rahman Lina Budiyarti Mega Hasanul Huda Meriam Efendi Meriam Efendi, Meriam Mieska Despitasari Mudzakkir, Muhammad Nani Nurhaeni Nenty Septiana Ningsih, Risna Ninis Indriani Novita Dewi Rahmayanti Nurdina Widanti Nyayu Latifah Husni Putri Melisa Duha Rachmawati, Anita Rahma Fadillah Sopha Rahmadhani, Dewi Astika Ramadhani, Dewi Astika Riswal Hanafi Siregar Rokhaidah, Rokhaidah Sanny Rachmawati Setyaningsih Saudi, La Setiawati, Atik Setiawati, Santun Siti Chodidjah Sri Chodidjah Susanti Widiastuti Suyami - Syarifah Aini Tanjung Titin Ungsianik Tomy Abuzairi Wanda , Dessie Yati Afiyati Yati Afiyati, Yati Yeni Rustina Yeni Rustina Yeni Rustina Yersi Ahzani Yudan Whulanza