Research Trends on Factors Influencing the Quality of Life of Cancer Survivors:Text Network Analysis and Topic Modeling Approach

ABSTRACT

Purpose@#This study aimed to identify the major keywords and the structure of the networks for each major topic to gain knowledge on factors influencing the quality of life of cancer survivors using Text Network Analysis (TNA) and topic modeling. @*Methods@#The study was conducted in four steps:(1) collecting abstracts, (2) text preprocessing in Python, (3) building a co-occurrence matrix, and (4) analyzing network features and clustering topic groups. From 2010 to 2020, 133 studies related to factors affecting the quality of life of cancer survivors were collected from several databases (PubMed, Embase, Cochrane, CINAHL RISS, KoreaMed, KISS). @*Results@#As a result of analyzing 9,968 evaluation results on “breast cancer,” “female,” “depression,” “treatment,” “age,” “questionnaire,” “symptom,” and “diagnosis,” five topics were derived after topic modeling considering coherence score and perplexity score. The main themes were breast cancer survivor, symptom experience, colon cancer survivor, psycho-social factors, and lifestyle and health management. @*Conclusion@#Based on the results of this study, symptoms such as depression, physical activity, and lifestyle and health management are significant factors affecting the quality of life of cancer survivors.