ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2016
Symptom clusters in women with breast cancer: an analysis of data from social media and a research study.
Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 3 of them syntheses that pooled it.
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Who cites it
19 citing papers in PubMed, 3 syntheses or guidelines pooled it, 50 citations in OpenAlex.
- Symptom clusters experienced by breast cancer patients at various treatment stages: A systematic review.Cancer medicine · 2021Pooled it
- A systematic literature review of machine learning in online personal health data.Journal of the American Medical Informatics Association : JAMIA · 2019Pooled it
- A systematic review of natural language processing and text mining of symptoms from electronic patient-authored text data.International journal of medical informatics · 2019Pooled it
- Symptom Clusters in Brazilian Women With Stage I and Stage III Nonmetastatic Breast Cancer: A Cross-Sectional Study.The breast journal · 2026Article
- Effects of nonpharmacological interventions on symptom clusters in breast cancer survivors: A systematic review of randomized controlled trials.Asia-Pacific journal of oncology nursing · 2024Review
- Impact of post-treatment symptoms on supportive care needs among breast cancer survivors in South Korea.Asia-Pacific journal of oncology nursing · 2023Article
- Cluster Analysis on Gastrointestinal Symptoms during Menopausal Transition.Western journal of nursing research · 2023Article
- Social Media Mining of Long-COVID Self-Medication Reported by Reddit Users: Feasibility Study to Support Drug Repurposing.JMIR formative research · 2022Article
- Distress among Korean Cancer Survivors: A Latent Profile Analysis.International journal of environmental research and public health · 2022Article
- Information Patients With Melanoma Spontaneously Report About Health-Related Quality of Life on Web-Based Forums: Case Study.Journal of medical Internet research · 2021Article
- Determination of Patient Sentiment and Emotion in Ophthalmology: Infoveillance Tutorial on Web-Based Health Forum Discussions.Journal of medical Internet research · 2021Article
- Development of a Lexicon for Pain.Frontiers in digital health · 2021Article
- Symptom Clusters in Breast Cancer Survivors: A Latent Class Profile Analysis.Oncology nursing forum · 2020Article
- Mining of Textual Health Information from Reddit: Analysis of Chronic Diseases With Extracted Entities and Their Relations.Journal of medical Internet research · 2019Article
- Impact of Self-Acupressure on Co-Occurring Symptoms in Cancer Survivors.JNCI cancer spectrum · 2018Article
- Use of Social Media in the Assessment of Relative Effectiveness: Explorative Review With Examples From Oncology.JMIR cancer · 2018Article
- Differences in symptom clusters before and twelve months after breast cancer surgery.European journal of oncology nursing : the official journal of European Oncology Nursing Society · 2018Article
- Introduction to special section on patient-reported outcomes in nonstandard settings.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2016Article
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Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
purposeUser-generated content on social media sites, such as health-related online forums, offers researchers a tantalizing amount of information, but concerns regarding scientific application of such data remain. This paper compares and contrasts symptom cluster patterns derived from messages on a breast cancer forum with those from a symptom checklist completed by breast cancer survivors participating in a research study.
methodsOver 50,000 messages generated by 12,991 users of the breast cancer forum on MedHelp.org were transformed into a standard form and examined for the co-occurrence of 25 symptoms. The k-medoid clustering method was used to determine appropriate placement of symptoms within clusters. Findings were compared with a similar analysis of a symptom checklist administered to 653 breast cancer survivors participating in a research study.
resultsThe following clusters were identified using forum data: menopausal/psychological, pain/fatigue, gastrointestinal, and miscellaneous. Study data generated the clusters: menopausal, pain, fatigue/sleep/gastrointestinal, psychological, and increased weight/appetite. Although the clusters are somewhat different, many symptoms that clustered together in the social media analysis remained together in the analysis of the study participants. Density of connections between symptoms, as reflected by rates of co-occurrence and similarity, was higher in the study data.
conclusionsThe copious amount of data generated by social media outlets can augment findings from traditional data sources. When different sources of information are combined, areas of overlap and discrepancy can be detected, perhaps giving researchers a more accurate picture of reality. However, data derived from social media must be used carefully and with understanding of its limitations.
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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 OpenQuestion graph.