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An Analysis of Interviews between Nurse Educators and Newly Graduated Nurses Regarding Adaptation to Clinical Nursing Practice: Text Network Analysis and Topic Modeling

  • Hyowon Jo
  • , Hyunjung Ko*
  • , Seulki Jeong
  • , Minyoung Park
  • , Seul Lee
  • , Seok Hee Jeong
  • *Corresponding author for this work
  • Jeonbuk National University

Research output: Contribution to journalJournal articlepeer-review

Abstract

Purpose: This study identified themes associated with the clinical adaptation of newly graduated nurses. Methods: We collected 522 interview journals from newly graduated nurses and nurse educators at a tertiary hospital between January 2021 and December 2023. After excluding incomplete data, 407 “promoting enjoyment” entries and 426 “presenting challenges” entries were analyzed using network analysis and topic modeling in NetMiner 4.5.1. Results: Topic modeling identified four themes in each category. For promoting enjoyment, the themes were: “Upon completing my designated responsibilities, I depart from the workplace,” “On my days off, I enjoy indulging in my favorite activities,” “Being recognized by my colleagues makes me feel like I’m contributing my part to the team,” and “The condition of my patient has improved.” For presenting challenges, the themes were: “The numerous responsibilities I must handle make it difficult to complete everything within the designated time frame,” “I struggle with both my tasks and relationships with colleagues,” “I’m anxious about caring for patients on my own,” and “Irregular shift patterns and occupational distress significantly impair my sleep quality.” Conclusion: Educational methodologies need to be developed to facilitate the clinical adaptation of newly graduated nurses. These findings can inform the Ministry of Health and Welfare’s nurse educator policy and future nursing workforce strategies.

Original languageEnglish
Pages (from-to)123-135
Number of pages13
JournalJournal of Korean Academy of Nursing Administration
Volume32
Issue number2
DOIs
StatePublished - 2026.03

Keywords

  • Data mining
  • Education
  • Interview
  • Nurses
  • Social network analysis

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