ArticleSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2024
Assessing the needs of patients with breast cancer and their families across various treatment phases using a Latent Dirichlet Allocation model: a text-mining approach to online health communities.
Article in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- The patient journey of adolescents and young adults with thyroid cancer: A social media listening study in China.Asia-Pacific journal of oncology nursing · 2026Article
- Thematic patterns of social media content by patient-led breast cancer key opinion leaders: A topic modeling study.Asia-Pacific journal of oncology nursing · 2026Article
- Understanding Public Perceptions of Lung Cancer in China: Infodemiology Study of Baidu Index and Weibo Posts.Journal of medical Internet research · 2026Article
- Application of the LDA model to identify topics in telemedicine conversations on the X social network.BMC health services research · 2025Article
- Can China's national fitness policy contribute to achieving universal health? Analysis based on the three-dimensional framework.Frontiers in public health · 2025Article
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Authors and funding
9 authors.
Funding
Abstract
purposeThis study aimed to assess the different needs of patients with breast cancer and their families in online health communities at different treatment phases using a Latent Dirichlet Allocation (LDA) model.
methodsUsing Python, breast cancer-related posts were collected from two online health communities: patient-to-patient and patient-to-doctor. After data cleaning, eligible posts were categorized based on the treatment phase. Subsequently, an LDA model identifying the distinct need-related topics for each phase of treatment, including data preprocessing and LDA topic modeling, was established. Additionally, the demographic and interactive features of the posts were manually analyzed.
resultsWe collected 84,043 posts, of which 9504 posts were included after data cleaning. Early diagnosis and rehabilitation treatment phases had the highest and lowest number of posts, respectively. LDA identified 11 topics: three in the initial diagnosis phase and two in each of the remaining treatment phases. The topics included disease outcomes, diagnosis analysis, treatment information, and emotional support in the initial diagnosis phase; surgical options and outcomes, postoperative care, and treatment planning in the perioperative treatment phase; treatment options and costs, side effects management, and disease prognosis assessment in the non-operative treatment phase; diagnosis and treatment options, disease prognosis, and emotional support in the relapse and metastasis treatment phase; and follow-up and recurrence concerns, physical symptoms, and lifestyle adjustments in the rehabilitation treatment phase.
conclusionThe needs of patients with breast cancer and their families differ across various phases of cancer therapy. Therefore, specific information or emotional assistance should be tailored to each phase of treatment based on the unique needs of patients and their families.
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38683417What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.