ScholarWorks@중앙대학교

초록

Objectives: This study examined the symptoms and emotions expressed by older adults with cancer and their caregivers inSouth Korean online cancer communities. It aimed to identify narrative patterns and provide insights to inform personalizedcare strategies. Methods: We analyzed 6,908 user-generated posts collected from major online cancer communities in SouthKorea. Keyword frequency analysis, term frequency-inverse document frequency, 2-gram analysis, and latent Dirichlet allocation-based topic modeling were applied to explore language patterns. Sentiment analysis identified 12 emotional categories,and Pearson correlation coefficients were calculated to examine associations between symptoms and emotional expressions. All data were cleaned and standardized prior to analysis. Results: Many users expressed anxiety (20.63%) and depression(19.59%), frequently associated with chemotherapy and sleep disturbances. Among reported symptoms, sleep problems carriedthe highest negative sentiment (79.81%), underscoring their profound impact on well-being. Topic modeling consistentlyrevealed seven recurring themes, including treatment decision-making, symptom management, and concerns aboutfamily, demonstrating the layered and personalized experiences of older cancer patients and their caregivers. Conclusions:This study explored treatment-related and symptom-related difficulties faced by older adults with cancer. Many reportedsignificant emotional strain, especially anxiety, depression, and sleep disturbances. These findings highlight the necessity forsupportive strategies addressing both psychological and physical aspects of care. Future research could investigate the utilityof large language models in analyzing these narratives, provided the data is ethically managed and appropriate for such use.

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