Purpose: To examine site-specific differences in managing labor and to describe variations in intrapartum practice in the context of clinical midwifery education.
Design: Descriptive design based on secondary analysis of an existing data set collected to evaluate the intrapartum clinical experiences of nurse-midwifery students. The data set included 498 records collected by midwifery students in 23 sites from 1995-1998. The unit of analysis was the intrapartum record.
Methods: Students used The American College of Nurse-Midwives Clinical data Set for Intrapartum Care to collect data during clinical experiences, including patient demographic data, risk factors, and specific care processes and interventions.
Findings: Significant variations were found among settings despite use of the same clinical guidelines. Discrepancies between theoretical preparation of students for clinical practice and the realities of clinical practice were noted.
Conclusions: Despite a stated commitment to evidence-based practice, practice patterns varied significantly. Clinicians and educators need to find common ground for combining evidence-based theory with evidence-based practice.
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http://dx.doi.org/10.1111/j.1547-5069.2002.00153.x | DOI Listing |
PLoS One
January 2025
School of Mathematics and Finance, Hunan University of Humanities, Science and Technology, Loudi, China.
During the iterative process of the progressive iterative approximation, it is necessary to calculate the difference between the current interpolation curve and the corresponding data points, known as the adjustment vector. To achieve more precise adjustments of control points, this paper decomposes the adjustment vector into its coordinate components and introduces a weight for each component. By dynamically adjusting these weights, we can accelerate the convergence of iterations and enhance approximation accuracy.
View Article and Find Full Text PDFmSystems
January 2025
Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland.
Average nucleotide identity (ANI) is a widely used metric to estimate genetic relatedness, especially in microbial species delineation. While ANI calculation has been well optimized for bacteria and closely related viral genomes, accurate estimation of ANI below 80%, particularly in large reference data sets, has been challenging due to a lack of accurate and scalable methods. To bridge this gap, we introduce MANIAC, an efficient computational pipeline optimized for estimating ANI and alignment fraction (AF) in viral genomes with divergence around ANI of 70%.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Department of Grain Science and Industry, Kansas State University, Manhattan, Kansas 66506, United States.
Cell-penetrating peptides (CPPs) are short peptides capable of penetrating cell membranes, making them valuable for drug delivery and intracellular targeting. Accurate prediction of CPPs can streamline experimental validation in the lab. This study aims to assess pretrained protein language models (pLMs) for their effectiveness in representing CPPs and develop a reliable model for CPP classification.
View Article and Find Full Text PDFJ Rural Health
January 2025
Muskie School of Public Service, University of Southern Maine, Portland, Maine, USA.
Purpose: To address the extent to which Federally Qualified Health Centers (FQHCs) and independent and provider-based Rural Health Clinics (RHCs) were using telehealth prior to and during the COVID-19 pandemic.
Methods: A nationally representative 5% sample of Medicare Fee-for-Service beneficiaries who used outpatient services at FQHCs and RHCs were identified within the 2019-2021 5% Medicare Limited Data Set Outpatient and Carrier files. Rural-Urban Continuum Codes were used to identify rural-urban clinic locations.
Data Brief
February 2025
Institute for Geography, Leipzig University, Johannisallee 19a, Leipzig, 04103, Germany.
This data set includes the spatial model of the thickness and distribution of fine-grained floodplain deposits in the Leipzig floodplain area. The data set originates from borehole records provided by the Saxon State Office for Environment, Agriculture, and Geology [1]. The data processing involved the categorization of the stratigraphic descriptions of the borehole logs.
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