Research Topics and Trends in Interprofessional Education in Nursing: A Text Network Analysis.

To provide nurse-led interprofessional practices in a healthcare setting, carrying out effective research that identifies the trends and characteristics of interprofessional education is necessary. This study aimed to objectively ascertain trends in the field through text network analysis of different types of interprofessional education literature. Titles and thesis abstracts were examined for terms "interprofessional education" and "nursing" and were found in 3926 articles from 1970 to August 2018. Python and Gephi software were used to analyze the data and visualize the networks. Keyword ranking was based on the frequency, degree centrality, and betweenness centrality. The terms "interprofessional," "education," "student," "nursing," and "health" were ranked the highest. According to topic analysis, the methods, provided programs, and outcome measures differed according to the research field. These findings can help create nurse-led research and effective future directions for interprofessional education pathways and topic selection. This will emphasize the importance of expanding research on various education programs and accumulating evidence regarding the professional and interdisciplinary impact these programs have on undergraduate and graduate students.

A Network Analysis of Research Topics and Trends in End-of-Life Care and Nursing.

This study identified the trends in end-of-life care and nursing through text network analysis. About 18,935 articles published until September 2019 were selected through searches on PubMed, Embase, Cochrane, Web of Science, and Cumulative Index to Nursing and Allied Health Literature. For topic modeling, Latent Dirichlet Allocation (K = 8) was applied. Most of the top ranked topic words for the degree and betweenness centralities were consistent with the top 1% through the semantic network diagram. Among the important keywords examined every five years, "care" was unrivaled. When analyzing the two- and three-word combinations, there were many themes representing places, roles, and actions. As a result of performing topic modeling, eight topics were derived as ethical issues of decision-making for treatment withdrawal, symptom management to improve the quality of life, development of end-of-life knowledge education programs, life-sustaining care plan for elderly patients, home-based hospice, communication experience, patient symptom investigation, and an analysis of considering patient preferences. This study is meaningful as it analyzed a large amount of existing literature and considered the main trends of end-of-life care and nursing research based on the core subject control and semantic structure.

Identification of the Knowledge Structure of Cancer Survivors' Return to Work and Quality of Life: A Text Network Analysis.

This study aimed to understand the trends in research on the quality of life of returning to work (RTW) cancer survivors using text network analysis. Titles and abstracts of each article were examined to extract terms, including "cancer survivors", "return to work", and "quality of life", which were found in 219 articles published between 1990 and June 2020. Python and Gephi software were used to analyze the data and visualize the networks. Keyword ranking was based on the frequency, degree centrality, and betweenness centrality. The keywords commonly ranked at the top included "breast", "patients", "rehabilitation", "intervention", "treatment", and "employment". Clustering results by grouping nodes with high relevance in the network led to four clusters: "participants and method", "type of research and variables", "RTW and education in adolescent and young adult cancer survivors", and "rehabilitation program". This study provided a visualized overview of the research on cancer survivors' RTW and quality of life. These findings contribute to the understanding of the flow of the knowledge structure of the existing research and suggest directions for future research.

Energy Efficient Real-Time Scheduling Using DPM on Mobile Sensors with a Uniform Multi-Cores.

In wireless sensor networks (WSNs), sensor nodes are deployed for collecting and analyzing data. These nodes use limited energy batteries for easy deployment and low cost. The use of limited energy batteries is closely related to the lifetime of the sensor nodes when using wireless sensor networks. Efficient-energy management is important to extending the lifetime of the sensor nodes. Most effort for improving power efficiency in tiny sensor nodes has focused mainly on reducing the power consumed during data transmission. However, recent emergence of sensor nodes equipped with multi-cores strongly requires attention to be given to the problem of reducing power consumption in multi-cores. In this paper, we propose an energy efficient scheduling method for sensor nodes supporting a uniform multi-cores. We extend the proposed T-Ler plane based scheduling for global optimal scheduling of a uniform multi-cores and multi-processors to enable power management using dynamic power management. In the proposed approach, processor selection for a scheduling and mapping method between the tasks and processors is proposed to efficiently utilize dynamic power management. Experiments show the effectiveness of the proposed approach compared to other existing methods.

T-L Plane Abstraction-Based Energy-Efficient Real-Time Scheduling for Multi-Core Wireless Sensors.

Energy efficiency is considered as a critical requirement for wireless sensor networks. As more wireless sensor nodes are equipped with multi-cores, there are emerging needs for energy-efficient real-time scheduling algorithms. The T-L plane-based scheme is known to be an optimal global scheduling technique for periodic real-time tasks on multi-cores. Unfortunately, there has been a scarcity of studies on extending T-L plane-based scheduling algorithms to exploit energy-saving techniques. In this paper, we propose a new T-L plane-based algorithm enabling energy-efficient real-time scheduling on multi-core sensor nodes with dynamic power management (DPM). Our approach addresses the overhead of processor mode transitions and reduces fragmentations of the idle time, which are inherent in T-L plane-based algorithms. Our experimental results show the effectiveness of the proposed algorithm compared to other energy-aware scheduling methods on T-L plane abstraction.

Partially covered versus uncovered self-expandable nitinol stents with anti-migration properties for the palliation of malignant distal biliary obstruction: A randomized controlled trial.

OBJECTIVE: Covered self-expandable metal stents (SEMSs) are increasingly used as alternatives to uncovered SEMSs for the palliation of inoperable malignant distal biliary obstruction to counteract tumor ingrowth. We aimed to compare the outcomes of partially covered and uncovered SEMSs with identical mesh structures and anti-migration properties, such as low axial force and flared ends. MATERIALS AND METHODS: One hundred and three patients who were diagnosed with inoperable malignant distal biliary obstruction between January 2006 and August 2013 were randomly assigned to either the partially covered (n = 51) or uncovered (n = 52) SEMS group. RESULTS: There were no significant differences in the cumulative stent patency, overall patient survival, stent dysfunction-free survival and overall adverse events, including pancreatitis and cholecystitis, between the two groups. Compared to the uncovered group, stent migration (5.9% vs. 0%, p = 0.118) and tumor overgrowth (7.8% vs. 1.9%, p = 0.205) were non-significantly more frequent in the partially covered group, whereas tumor ingrowth showed a significantly higher incidence in the uncovered group (5.9% vs. 19.2%, p = 0.041). Stent migration in the partially covered group occurred only in patients with short stenosis of the utmost distal bile duct (two in ampullary cancer, one in bile duct cancer), and did not occur in any patients with pancreatic cancer. CONCLUSIONS: For the palliation of malignant distal biliary obstruction, endoscopic placement of partially covered SEMSs with anti-migration designs and identical mesh structures to uncovered SEMSs failed to prolong cumulative stent patency or reduce stent migration.

Non-neoplastic pathology results after endoscopic submucosal dissection for gastric epithelial dysplasia or early gastric cancer.

BACKGROUND AND STUDY AIMS: Endoscopists sometimes face paradoxical cases in which the endoscopic submucosal dissection (ESD) specimen reveals a non-neoplastic pathology result. The aims of the study were to determine the reasons for such results, and to compare the endoscopic characteristics of non-neoplastic and conventional neoplastic pathology groups after ESD. PATIENTS AND METHODS: A total of 1186 gastric ESDs performed between February 2005 and December 2011 were retrospectively reviewed. The ESD specimens included 52 (4.4 %) that were confirmed as negative or indefinite for neoplasia. Patient characteristics and endoscopic and pathological data were reviewed and compared. RESULTS: Non-neoplastic pathology after ESD was due to complete removal of the lesion at biopsy in 45 cases (86.5 %), pathology overestimation in 5 (9.6 %), and incorrect localization of the original tumor with subsequent ESD performed at the wrong site in 2 (3.8 %). The mean length and surface area of the non-neoplastic lesions were 9.2 ±â€Š2.6 mm and 49.6 ±â€Š23.6 mm (2), respectively. Mean sampling ratios were 3.0 ±â€Š1.5 mm/fragment and 16.3 ±â€Š10.0 mm(2)/fragment. Compared with 1134 cases confirmed as neoplastic on the final ESD specimen, non-neoplastic cases showed a significantly smaller tumor size and surface area, and lower sampling ratios in a logistic regression analysis adjusted for potential confounders (P < 0.001 for all). CONCLUSIONS: Complete lesion removal by biopsy, pathology overestimation, and incorrect localization of the original tumor with subsequent ESD at the wrong site were the main reasons for non-neoplastic results after ESD. Small tumor size and surface area, and low sampling ratios were associated with non-neoplastic pathology results after ESD.