{"title":"Exploring the Knowledge Structure of Research for Nurse Preceptor Training Programs Using Text Network Analysis and Topic Modeling.","authors":"Sun Hee Seon, Hye Won Jeong, Ja Yun Choi","doi":"10.1097/CIN.0000000000001347","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>This study utilized text network analysis and topic modeling to examine the research landscape of nurse preceptor training programs and facilitate the adaptation of new nurses in Korea and internationally.</p><p><strong>Methods: </strong>Abstracts from three Korean and 45 international studies on preceptor nurse training programs were collected. Keywords and meaningful morphemes from the abstracts and main text were analyzed and refined. A co-occurrence matrix of keywords was generated to analyze degree, closeness, and betweenness centrality using NetMiner 4.5.0 software. Topic modeling was used to identify key thematic structures.</p><p><strong>Results: </strong>Among the top 10 ranked keywords, five common terms-\"clinical competence,\" \"educator,\" \"nursing practice,\" \"teaching strategy,\" and \"mentoring\"-emerged across both frequency and centrality measures. Topic modeling identified four major subtopics: nurse preceptor programs for strengthening partnership skills and professional insights, communication programs to enhance the self-care competence of nurse preceptors, simulation programs to strengthen the expertise of nurse preceptors, and nurse preceptor programs to foster emotional empathy and growth.</p><p><strong>Conclusion: </strong>This study improves patient safety and professional competence by promoting optimal clinical decision-making for new nurse preceptees. Future research should develop educational programs that foster mutual empathy and professional growth between nurse preceptors and new nurse preceptees.</p>","PeriodicalId":520598,"journal":{"name":"Computers, informatics, nursing : CIN","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers, informatics, nursing : CIN","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1097/CIN.0000000000001347","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract
Purpose: This study utilized text network analysis and topic modeling to examine the research landscape of nurse preceptor training programs and facilitate the adaptation of new nurses in Korea and internationally.
Methods: Abstracts from three Korean and 45 international studies on preceptor nurse training programs were collected. Keywords and meaningful morphemes from the abstracts and main text were analyzed and refined. A co-occurrence matrix of keywords was generated to analyze degree, closeness, and betweenness centrality using NetMiner 4.5.0 software. Topic modeling was used to identify key thematic structures.
Results: Among the top 10 ranked keywords, five common terms-"clinical competence," "educator," "nursing practice," "teaching strategy," and "mentoring"-emerged across both frequency and centrality measures. Topic modeling identified four major subtopics: nurse preceptor programs for strengthening partnership skills and professional insights, communication programs to enhance the self-care competence of nurse preceptors, simulation programs to strengthen the expertise of nurse preceptors, and nurse preceptor programs to foster emotional empathy and growth.
Conclusion: This study improves patient safety and professional competence by promoting optimal clinical decision-making for new nurse preceptees. Future research should develop educational programs that foster mutual empathy and professional growth between nurse preceptors and new nurse preceptees.
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