Predicting online information seeking on Douyin, Baidu, and other Chinese search engines among gynecologic oncology patients: a cross-sectional study

Abstract

Objective: The rise of online platforms like Douyin, Baidu, and other Chinese search engines has changed how gynecologic oncology patients seek information about their diagnosis or condition. This study aimed to investigate the factors associated with information seeking among these patients and to evaluate their predictive performance. Methods: A cross-sectional study was conducted among 199 gynecologic oncology patients at a single hospital in China. The patients’ demographic characteristics and scores on the State–Trait Anxiety Inventory (STAI-S and STAI-T) and the Hospital Anxiety and Depression Scale (HADS-A and HADS-D) were compared between those who sought information online and those who did not. Logistic regression analyses and receiver operating characteristic (ROC) curve analyses were performed. Results: The patients’ age, marital status, STAI-S scores, and HADS-A scores were significantly associated with online information seeking. The combined model that included these factors showed good predictive performance with an area under the ROC curve of 0.841. Conclusion: The combination of demographic and psychological factors can be used to predict the likelihood of gynecologic oncology patients seeking information online. These findings can help healthcare providers understand their patients’ information-seeking behaviors and tailor their communication strategies accordingly.