LAUSR

AIM This study aimed to determine advice-seeking interactions of nurses in a private hospital by using social network analysis. DESIGN This study was designed as a cross-sectional descriptive study. METHODS The study was conducted in a private hospital with 70 nurses. The data were collected with a social network analysis questionnaire. The social network analysis (SNA) focused on certain values such as network density, component, degree centrality, and betweenness centrality. The SNA was carried out using UCINET, and statistical analyses were performed with SPSS version 23.0. RESULTS The network density was reported to be 0.062, and it was composed of three components. It was further noted that nurse Y1 was found to have the highest scores of degree and betweenness centrality. Chi-Square Automatic Interaction Detector (CHAID) analysis indicated that the most common variables that affected degree centrality score were education, department, and position. CONCLUSION It was concluded that social network analysis was a useful instrument to delineate strengths and weaknesses of seeking advice relationships among nurses. IMPLICATIONS FOR NURSING AND HEALTH POLICY Top- and middle-level nursing managers occupy a significant position in advice-seeking networks. Nursing managers with higher education degrees will absolutely improve advice-seeking networks.