Exploring the Dilemmas Faced by Depressed Patients in China Based on Deep Learning Methods

Depression is a major global public health problem, with high prevalence, recurrence, and mortality rates, and is a significant factor contributing to the global disease burden. Depression has caused great harm to the health of patients. The purpose of the paper is to identify the problems faced by patients with depression, understand their needs, and provide evidence for medical institutions and society to better serve and help patients with depression. We collected posts and comments from the help-seeking module in an online depression community. The topics and emotions of text content were got by the BERTopic and BERT, respectively. The word co-occurrence network under each topic was constructed to analyze the dilemma faced by users. We divided user needs into 7 categories: doctor, medication, symptom, study, family, emotion, and work. In the help-seeking module, users receive not only information but also emotional support. Keywords under each topic and the word co-occurrence networks indicate that users have a lot of problems in the treatment of depression; they not only need the help of experienced patients but also need explanations and suggestions from doctors. There are a large number of adolescent patients in this community. How to help adolescent patients get effective and timely treatment and overcome study difficulties is a problem that these patients are concerned about, and it also needs to be solved by relevant sectors of society.