Medication safety education in nursing research: Text network analysis and topic modeling

Abstract

Objectives: This study aimed to identify the knowledge structure of medication safety nursing education literature by developing schematic diagrams of the relationship between keywords from a macro perspective. This study also identifies the research topics and trends over time.

Design: This quantitative content study used text network analysis to explore keywords and research topics using topic modeling within the medication safety nursing education literature.

Data sources: PubMed, EMBASE, and Cochrane databases were used to search for the medication safety nursing education literature published until December 2021.

Methods: Keywords from 2085 articles were examined using text network analysis and topic modeling with NetMiner 4.4.3.

Results: The keywords with the most frequency and the highest networking degree in centrality were "patient," "medication," "program," "nurse," and "care." The emerging keywords assessed by time periods were identified; the first phase ("heart failure," "insulin," "chemotherapy," and "infusion"), the second phase ("medication errors," "staff," and "information"), the third phase ("program," "management," and "data"). The results of topic modeling were as follows: safe medication administration, safe medication reconciliation process, medication education for patients, medication errors in nursing practice, and multidisciplinary teamwork for medication safety.

Conclusion: These findings will help nursing researchers and educators to understand the trends and insights for medication safety education and educate future nurses to provide safer nursing care.

Keywords: Education; Knowledge structure; Medication safety; Nurses; Nursing; Text network analysis; Topic analysis.