Text Network Analysis Related to Disclosure of Cancer Diagnosis among Korea and other Countries

ABSTRACT

PURPOSE: This study aimed to identify and compare research topics related to disclosure of cancer diagnosis among Korea and other countries using text network analysis. METHODS: Abstracts from 119 studies for the period of 2000~2015 were analyzed. An integrative literature review and text network analysis were applied to examine the research. The keywords from each article's abstracts were extracted by using a program, KrKwic, and analyzed using network-related measures including degree centrality, and clustering using the NetMiner program. RESULTS: The most important core keywords; ‘patient’, ‘cancer’, ‘diagnosis’, ‘disclosure’, ‘truth’, ‘physician’, ‘family’, ‘telling’, ‘information’, ‘preference’, ‘member’, ‘age’, and ‘tell’ ranked highly. Asian countries as Korea, Japan, and China showed a similar high centrality of degree of connection in family, which appeared as a factor that influences cancer diagnosis disclosure. CONCLUSION: These findings showed knowledge structure of disclosure of cancer diagnosis and its research trends. The 11 topics identified in this comparative study can provide further starting points for research of communication with cancer patients and their family.