Exploring Research Topics and Trends in Nursing-related Communication in Intensive Care Units Using Social Network Analysis

Son, Youn‐Jung; Lee, Sook-Young; Nam, So Hyun; Shim, Jae Lan

doi:10.1097/cin.0000000000000444

Cited by 11 publications

(13 citation statements)

References 44 publications

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“…And a node represents a keyword and an edge relatedness between two keywords. In this study, the relatedness between two keywords is calculated by weighted Jaccard similarity using frequencies of the keywords [15,16]. The weight (that is, importance) of a node in the network was determined by the PageRank algorithm.…”

Section: Network Analysismentioning

confidence: 99%

Network Analysis for Directing Standardization Efforts in Genomics Using MEDLINE

Bae

Nam

Lee

et al. 2022

Preprint

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Background: Biotechnology in genomics, such as sequencing devices and gene quantification software, has proliferated and been applied to clinical settings. However, the lack of standards applicable to it poses practical problems in interoperability and reusability of the technology across various application domains. This study aims to visualize and identify the standard trends in clinical genomics and to suggest areas on which standardization efforts must focus. Methods: Of 16,538 articles retrieved from PubMed, published from 1975 to 2020, using search keywords “genomics and standard” and “clinical genomic sequence and standard”, terms were extracted from the abstracts and titles of 15,855 articles. Our analysis includes 1) keyword-based network analysis, considering the characteristics of keyword clusters; 2) period analysis with six phases; 3) statistical analysis; 4) content analysis.Results: Our research trend showed an increasing trend from 2003, years marked by the completion of the human genome project (2003). The content analysis showed that keywords related to such concepts as gene types for analysis, and analysis techniques were increased in phase 3 when US-FDA first approved the next-generation sequencer. During 2017-2019, oncology-relevant terms were clustered and contributed to the increasing trend in phase 4 of the content analysis. In the statistical analysis, all the categories showed high regression values (R2>.586) throughout the whole analysis period and phase-based statistical analysis showed significance only in Genetics terminology category (P=.039*) at phase 4.Conclusions: This study investigated, through the network and statistical analysis, trend shifts in relation to clinical genomics. The shifts offer a solid basis for standards development that shows where future standardization opportunities and gaps lie.

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Section: Network Analysismentioning

confidence: 99%

Network Analysis for Directing Standardization Efforts in Genomics Using MEDLINE

Bae

Nam

Lee

et al. 2022

Preprint

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“…It has been used to depict information use patterns among ICU nurses, [21] describe patterns and methods of communication during patient handoffs, [22] and explore research topics and trends in nursing-related communication in ICU. [23] NA use has been even more limited in ICU decision-making. It has been used to explore implementation of evidence-informed decision-making interventions, [24] evaluate decisionmaking under risk using functional MRI, [25] and identify nursing diagnosis patterns in ICU.…”

Section: Researchmentioning

confidence: 99%

Identifying ICU admission decision patterns in a ‘20-questions game’ approach using network analysis

Gopalan

Pershad

2021

S Afr J Crit Care

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Background. The complex intensive care unit (ICU) admission decision process has numerous non-linear relationships involving multiple factors. To better describe and analyse this process, exploration of novel techniques to clearly delineate the importance and interrelationships of factors is warranted. Network analysis (NA), based on graph theory, attempts to identify patterns of connections within a network and may be useful in this regard. Objectives. To identify patterns of ICU decision-making pertaining to patients referred for admission to ICU and to identify key factors, their distribution, connection and relative importance. The secondary aim was to compare subgroups as per decision outcomes and case labels. Methods. NA was performed using Gephi software package as a secondary analysis on a dataset generated from a previous study on ICU admission decision-making process using a 20-questions game approach. The data were standardised and coded up to a quaternary level for this analysis. Results. The coding process generated 31 nodes and 964 edges. Regardless of the measure used (centrality, prestige, authority and hubs), properties of the acute illness, progress of the acute illness and properties of comorbidities emerged consistently as among the most important factors and their relative rankings differed. Using different measures allowed important factors to emerge differentially. The six subgroups that emerged from the modularity measure bore little resemblance to traditional factor subgroups. Differences were noted in the subgroup comparisons of decision outcomes and case prognoses. Conclusions. The use of NA with its various measures has facilitated a more comprehensive exploration of the ICU admission decision, allowing us to reflect on the process. Further studies with larger datasets are needed to elucidate the exact role of NA in decision-making processes.

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“…The overall network analysis was performed as previous studies [20][21][22]. In the network analysis of research articles, the frequency of keywords indicates the major research topic in a particular year.…”

Section: Network Analysismentioning

confidence: 99%

Network Analysis for Estimating Standardization Trends in Genomics

Bae

Nam

Ahn

2021

Preprint

Self Cite

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With the development of biotechnology in genomics, such as droplet digital PCR, sequencing device, gene analysis software, an increase in the clinical application of those new developed technologies in genomics is observed. However, the lack of established international standards regarding the use of genomics in clinics is of concern. To visualize trend of international standards in clinical genomics and explore high demanded sub-specific field, we performed a social network analysis. We searched 16,538 articles using the search keywords, “genomics and standard” and “clinical genomic sequence and standard”. All terms extracted from full text articles were classified into academic and technical categories and conducted general linear model analysis. Assuming from the results, research in the fields of software, proteomics and genetics terminology categories is likely to increase. From our results, such international critical issue of genomics, human genome project in 2003, primary US-FDA approval of sequencing device in 2013, and pandemic state of COVID-19 in 2020, were affected to research of standard in genomics. In further proposal and standardization of new items, summing critical social issues and research trends, we could suggest and considering promising sub-specific field of genomics.

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Exploring Research Topics and Trends in Nursing-related Communication in Intensive Care Units Using Social Network Analysis

Cited by 11 publications

References 44 publications

Network Analysis for Directing Standardization Efforts in Genomics Using MEDLINE

Network Analysis for Directing Standardization Efforts in Genomics Using MEDLINE

Identifying ICU admission decision patterns in a ‘20-questions game’ approach using network analysis

Network Analysis for Estimating Standardization Trends in Genomics

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