Patterns and trends in infection control nursing research: text network analysis.

BACKGROUND: Despite the advancement of the medical environment, health-related infections continue to increase. The study was to explore the knowledge structure of infection control nursing research using keywords and networks. It was also to identify theoretical groundings regarding the current infection control nursing theory and presented the area and level of future theory. METHODS: A quantitative content analysis design was employed. Using text network analysis, keywords were derived from the abstracts of 2,651 studies conducted from 1974 to 2022, and centrality and network connection structure analyses were used to identify the keywords' structure and characteristics. RESULTS: In the frequency of occurrence, vaccine is the most frequent, followed by health personnel, influenza, and glove. The connection structure analyzed using weights that the terms influenza and vaccine appeared simultaneously, followed by injury and needle, hepatitis and vaccine, immunization and vaccine, and injury and needlestick injury in order. The words health personnel, vaccine, and glove, which all showed high centrality, indicate that they are keywords studied in relation to various words in infection control nursing research. CONCLUSION: This study confirmed that keywords revealed through text network analysis were medical workers, vaccines, and gloves. Vaccine was closely related to terms such as influenza, hepatitis, and healthcare provider, while the term gloves was closely related to respiratory protection, injury and needles, and healthcare provider. Infection control for healthcare providers is based on evidence-based knowledge and practices, and quality evaluation of the evidence and verification of effectiveness are required. CLINICAL TRIAL NUMBER: Not applicable.