AI Article Synopsis
- The paper evaluated the METRICS model’s effectiveness for analyzing healthcare simulation scholarship by categorizing articles from four journals into seven scholarship areas and examining trends in three specific research programs.
- Two raters reviewed 432 articles from 2015 to 2017, finding that evaluation, innovation, and conceptual scholarship were the most prevalent types, indicating a diverse range of research activities.
- The findings suggest that the METRICS model effectively represents various scholarship patterns, aiding in the planning of future research directions in healthcare simulation.
Article Abstract
Introduction: In this paper, we explored the utility and value of the METRICS model for modeling scholarship in healthcare simulation by: (1) describing the distribution of articles in four healthcare simulation journals across the seven areas of METRICS scholarship; and (2) appraising patterns of scholarship expressed in three programs of simulation scholarship and reflecting on how these patterns potentially influence the pursuit of future scholarly activities.
Methods: Two raters reviewed abstracts of papers published between January 2015 and August 2017 in four healthcare simulation journals and coded them using METRICS. Descriptive statistics were calculated for scholarship type and distribution across journals. Twenty-eight articles from three scholars were reviewed, with patterns of scholarship within articles mapped to METRICS. Descriptive synthesis was constructed through discussion between two reviewers.
Results: A total of 432 articles from four journals were reviewed. The three most commonly published areas of scholarship were: 32.2% (139/432) evaluation, 18.8% (81/432) innovation, and 15.3% (66/432) conceptual. The METRICS model was able to represent different kinds of scholarship expressed in all of the papers reviewed and across programs of research. Reflecting on patterns of scholarship within their scholarly programs was helpful for research in planning future directions.
Conclusions: The METRICS model for scholarship can describe a wide range of patterns of simulation scholarship within individual articles, programs of research, or across journals.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1080/0142159X.2018.1465184 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
An Artificial Intelligence Model Using Diffusion Basis Spectrum Imaging Metrics Accurately Predicts Clinically Significant Prostate Cancer.
J Urol
January 2025
Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO.
Purpose: Conventional prostate magnetic resonance imaging has limited accuracy for clinically significant prostate cancer (csPCa). We performed diffusion basis spectrum imaging (DBSI) prior to biopsy and applied artificial intelligence models to these DBSI metrics to predict csPCa.
Materials And Methods: Between February 2020 and March 2024, 241 patients underwent prostate MRI that included conventional and DBSI-specific sequences prior to prostate biopsy.
The misalignment of incentives in academic publishing and implications for journal reform.
Proc Natl Acad Sci U S A
February 2025
Department of Data and Decision Science, Technion-Israel Institute of Technology, Haifa 3200003, Israel.
For most researchers, academic publishing serves two goals that are often misaligned-knowledge dissemination and establishing scientific credentials. While both goals can encourage research with significant depth and scope, the latter can also pressure scholars to maximize publication metrics. Commercial publishing companies have capitalized on the centrality of publishing to the scientific enterprises of knowledge dissemination and academic recognition to extract large profits from academia by leveraging unpaid services from reviewers, creating financial barriers to research dissemination, and imposing substantial fees for open access.
View Article and Find Full Text PDFIntelligent classification of computer vulnerabilities and network security management system: Combining memristor neural network and improved TCNN model.
PLoS One
January 2025
School of Information and Communication Engineering, Beijing University of Information Science and Technology, Bei Jing City, China.
To enhance the intelligent classification of computer vulnerabilities and improve the efficiency and accuracy of network security management, this study delves into the application of a comprehensive classification system that integrates the Memristor Neural Network (MNN) and an improved Temporal Convolutional Neural Network (TCNN) in network security management. This system not only focuses on the precise classification of vulnerability data but also emphasizes its core role in strengthening the network security management framework. Firstly, the study designs and implements a neural network model based on memristors.
View Article and Find Full Text PDFExploring the impact of urban spatial morphology on land surface temperature: A case study in Linyi City, China.
PLoS One
January 2025
Science and Technology Innovation Team of Shandong Provincial Department of Natural Resources, Shandong Institute of Land Spatial Data and Remote Sensing Technology, Jinan, China.
The increasing population density and impervious surface area have exacerbated the urban heat island effect, posing significant challenges to urban environments and sustainable development. Urban spatial morphology is crucial in mitigating the urban heat island effect. This study investigated the impact of urban spatial morphology on land surface temperature (LST) at the township scale.
View Article and Find Full Text PDFThe development and evaluation of nine obesity-based indices for gallstones in U.S. adults.
Int J Surg
January 2025
Department of General Surgery.
Objective: Gallstones have gradually become a highly prevalent digestive disease worldwide. This study aimed to investigate the association of nine different obesity-related indicators (BRI, RFM, BMI, WC, LAP, CMI, VAI, AIP, TyG) with gallstones and to compare their predictive properties for screening gallstones.
Methods: Data for this study were obtained from the National Health and Nutrition Examination Survey (NHANES) for the 2017-2020 cycle, and weighted logistic regression analyses with multi-model adjustment were conducted to explore the association of the nine indicators with gallstones.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!