Year: 2025
Type: article
Abstract: OBJECTIVE: Menopause has a significant effect on a woman's quality of life, which leads to physical illnesses and mental stresses. Social media listening (SML) studies reveal the experiences of users, sources of information on disease experiences and health dynamics in populations. The aim of this study was to assess the overview of portraits, complaints, symptom distribution and treatment methods of menopausal women through SML. METHODS: An info-surveillance study was conducted wherein the search was performed in the question and answer (Q&A) search and online consultation forums. Using the Python + Scrapy crawl technology tool, the search involved single or combined keywords related to menopause, including population, diagnosis, symptom, treatment and treatment comparison. RESULTS: Data were extracted from three menopause-related Q&A search platforms and 15 online consultation forums. Menstrual disorders, menopausal symptoms, and menopausal examination and treatment were the high-frequency keywords while irritability, insomnia and hot flashes were the most commonly mentioned symptoms. A total of 76.62% of menopausal women had a willingness for tier 3 hospitals, with gynecology being the most preferred department chosen by the majority. Among the 359 women reporting hormone treatment to be effective, 90.96% women showed an improvement in symptoms, and the rest had improvement in emotions, various improvements and overall improvement. CONCLUSION: The results of this SML study indicate that menopausal women in China have a strong urge for menopause-related knowledge but are not well informed. Thus, there is a need for science popularization to sensitize menopausal women to choose the right department, and explore the long-term management of menopause and menopausal hormone therapy.
Source: Climacteric
Authors: Yujie Xu, Shujin Ye, Lan Shi, Zhifen Zhang
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4409683475