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Use of Health Belief Model-based Deep Learning to Understand Public Health Beliefs in Breast Cancer Screening from Social Media Before and During the COVID-19 Pandemic.

AMIA Annual Symposium proceedings AMIA Symposium(2024)

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Abstract
Breast cancer is the second leading cause of cancer death for women in the United States. While breast cancer screening participation is the most effective method for early detection, screening rate has remained low. Given that understanding health perception is critical to understand health decisions, our study utilized the Health Belief Model-based deep learning method to predict and examine public health beliefs in breast cancer and its screening behavior. The results showed that the trends in public health perception are sensitive to political (i.e., changes in health policy), sociological (i.e., representation of disease and its preventive care by public figure or organization), psychological (i.e., social support), and environmental factors (i.e., COVID-19 pandemic). Our study explores the roles social media can play in public health surveillance and in public health promotion of preventive care.
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