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Kecemasan Akademik sebagai Prediktor Kualitas Tidur Mahasiswa Keperawatan dalam Persiapan Ujian Objective Structured Clinical Examination (Osce) Fiana, Marista; fitri, Riki ukhtul fitri; Komariah, Ade; Muhka, Reni; Maulana, Nova; Ningsih, Rastia; Wahaningtyas, Nova Listya; Risnandhia, Risnandhia; Pahila, Fevi; Hernawati, Hernawati; Aliun, Fatimah Wahab
Malahayati Nursing Journal Vol 8, No 2 (2026): Volume 8 Nomor 2 (2026)
Publisher : Universitas Malahayati Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33024/mnj.v8i2.24219

Abstract

ABSTRACT The Objective Structured Clinical Examination (OSCE) is an evaluation method used to assess students' clinical competence. The demands of the exam trigger psychological pressure and increase students' anxiety. The purpose of this study was to determine the relationship between anxiety levels and sleep quality among fifth-year nursing students at Bina Bangsa University in preparation for the OSCE. This study was a quantitative correlational study with a cross-sectional approach. The research population consisted of fifth-year undergraduate nursing students at Bina Bangsa University who were going to take the OSCE exam. The sample size was 113 respondents, using total sampling technique. Data analysis was performed using Spearman's rank correlation test. The results showed a significant relationship with a p-value of 0.002 (P0.05) and a correlation coefficient of 0.305, indicating a weak to moderate relationship between anxiety levels and sleep quality among students facing the OSCE exam. Keywords: Anxiety, Sleep Quality, Objective Structured Clinical Examination (OSCE).  ABSTRAK Objective Structured Clinical Examination (OSCE) merupakan metode evaluasi untuk menilai kompetensi klinik mahasiswa, tuntutan ujian menjadi pemicu yang menimbulkan tekanan psikologis dan meningkatkan kecemasan mahasiswa.Tujuan penelitian ini untuk mengetahui hubungan tingkat kecemasan terhadap kualitas tidur pada mahasiswa program studi sarjana keperawatan tingkat V Universitas Bina Bangsa dalam menghadapi OSCE. Jenis Penelitian ini adalah kuantitatif korelasional dengan pendekatan cross sectional. Populasi penelitian yaitu Mahasiswa Program Studi Sarjana Keperawatan Tingkat V di Universitas Bina Bangsa yang akan mengikuti ujian OSCE, jumlah sampel sebanyak 113 responden, teknik sample total sampling. Analisis data menggunakan uji korelasi Spearmen Rank. Hasil penelitian menunjukan hubungan yang signifikan dengan p value 0,002 (P0,05) dengan nilai koefisien korelasi 0,305 menunjukkan kekuatan hubungan dalam kategori lemah hingga sedang antara hubungan tingkat kecemasan terhadap kualitas tidur pada mahasiswa dalam menghadapi ujian OSCE. Kata Kunci: Kecemasan, Kualitas Tidur, Objective Structured Clinical Examination (OSCE).
Artificial intelligence in cardiac nursing practice: A systematic review of applications, challenges, and patient outcomes Wahananingtyas, Nova Listya; Aprilio, ⁠Rachmad; Risnadhia, Risnadhia; Fiana, Marista; Padhila, Fevi; Azhar, Sabrina Rahmatillah
Science Midwifery Vol 13 No 6 (2026): February: Health Sciences and related fields
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/midwifery.v13i6.2250

Abstract

Cardiovascular diseases remain the leading cause of global mortality, requiring innovative approaches to improve cardiac care. This systematic review aimed to examine the applications of Artificial Intelligence (AI) in cardiac nursing practice, identify implementation challenges, and assess its impact on patient outcomes. The review was conducted in accordance with PRISMA 2020 guidelines, using PubMed, ScienceDirect, CINAHL, and Web of Science. Original studies published between 2020 and 2025 that explicitly addressed nursing roles in cardiac care were included. Eleven studies met the inclusion criteria and were appraised using the Joanna Briggs Institute (JBI) tools. The results show that AI applications, including ChatGPT and machine learning models, support cardiac nursing through clinical decision support, patient education, risk prediction, and home-based monitoring. These applications were associated with improved nursing efficiency, enhanced patient self-management, early detection of clinical deterioration, and potential reduction in hospitalization. However, challenges such as data accuracy, ethical concerns, algorithm transparency, and limited digital literacy among nurses were consistently reported. In conclusion, AI has strong potential to enhance evidence-based and patient-centered cardiac nursing practice. Successful integration requires ethical governance, adequate training, and interdisciplinary collaboration to ensure safe and effective implementation.