title: Learning from social media: utilizing advanced data extraction techniques to understand barriers to breast cancer treatment.
abstract: Past examinations of breast cancer treatment barriers have typically included registry, claims-based, and smaller survey studies. We examined treatment barriers using a novel, comprehensive, social media analysis of online, candid discussions about breast cancer. Using an innovative toolset to search postings on social networks, message boards, patient communities, and topical sites, we performed a large-scale qualitative analysis. We examined the sentiments and barriers expressed about breast cancer treatments by Internet users during 1 year (2/1/14-1/31/15). We categorized posts based on thematic patterns and examined trends in discussions by race/ethnicity (white/black/Hispanic) when this information was available. We identified 1,024,041 unique posts related to breast cancer treatment. Overall, 57 % of posts expressed negative sentiments. Using machine learning software, we assigned treatment barriers for 387,238 posts (38 %). Barriers included emotional (23 % of posts), preferences and spiritual/religious beliefs (21 %), physical (18 %), resource (15 %), healthcare perceptions (9 %), treatment processes/duration (7 %), and relationships (7 %). Black and Hispanic (vs. white) users more frequently reported barriers related to healthcare perceptions, beliefs, and pre-diagnosis/diagnosis organizational challenges and fewer emotional barriers. Using a novel analysis of diverse social media users, we observed numerous breast cancer treatment barriers that differed by race/ethnicity. Social media is a powerful tool, allowing use of real-world data for qualitative research, capitalizing on the rich discussions occurring spontaneously online. Future research should focus on how to further employ and learn from this type of social intelligence research across all medical disciplines.
authors.affiliation: Department of Medical Oncology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02215, USA. rafreedman@partners.org.
authors.forename: Rachel A
authors.initials: RA
authors.lastname: Freedman
authors.affiliation: Center for Community-Based Research, Dana-Farber Cancer Institute, Boston, MA, USA.|Department of Society and Behavioral Sciences, Harvard School of Public Health, Boston, MA, USA.
authors.forename: Kasisomayajula
authors.initials: K
authors.lastname: Viswanath
authors.affiliation: Department of Medical Oncology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02215, USA.
authors.forename: Ines
authors.initials: I
authors.lastname: Vaz-Luis
authors.affiliation: Department of Health Care Policy, Harvard Medical School, Boston, MA, USA.|Division of General Internal Medicine, Brigham and Women's Hospital, Boston, MA, USA.
authors.forename: Nancy L
authors.initials: NL
authors.lastname: Keating
mesh_terms: D001943:Breast Neoplasms / Q000523:psychology* / Q000628:therapy*; D005260:Female; D006297:Health Services Accessibility; D006801:Humans; D020407:Internet; D000069550:Machine Learning; D017060:Patient Satisfaction; D044469:Racial Groups; D061108:Social Media
keywords: Adherence; Breast cancer; Qualitative research; Race and ethnicity; Underserved populations