z-logo
open-access-imgOpen Access
Learning from social media: utilizing advanced data extraction techniques to understand barriers to breast cancer treatment
Author(s) -
Rachel A. Freedman,
Kasisomayajula Viswanath,
Inês Vaz-Luís,
Nancy L. Keating
Publication year - 2016
Publication title -
breast cancer research and treatment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.908
H-Index - 154
eISSN - 1573-7217
pISSN - 0167-6806
DOI - 10.1007/s10549-016-3872-2
Subject(s) - breast cancer , social media , thematic analysis , ethnic group , health care , qualitative research , medicine , psychology , cancer , world wide web , computer science , sociology , political science , social science , anthropology , law
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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here