Understanding how people make decisions about their health care is of critical importance for developing effective health care policies. While multiple factors influence health behavior, social and cultural factors play a significant role. People turn to each other and culturally sanctioned sources of information to help them make their decisions. With the advent of the Internet and the proliferation of informal information sharing sites such as blogs, discussion forums, comment threads and social media, a previously hidden informal interactional resource has become widely accessible at an enormous scale. In this context, one of the most persuasive rhetorical tools is the story, a form of discourse that relates particular events about specific people in a structured manner with a discrete beginning and end. Stories are grounded in broader master narratives, which are implicit, persistent overarching stories that often present a highly ideological point of view. In the pervasive information sources we consider, master narratives are constituted by stories and comments on those stories and, taken as a whole, these stories and comments contribute to a dynamic series of overlapping, at times conflicting, master narratives. While it is clear that people are talking about health care on all of these different channels, our project aims to develop methods to move beyond the simple observation that people are talking about these issues, and discover who is saying what, how they are saying it, and how this might be associated with real world behaviors. To meet these challenges, we propose to develop novel computational methods that will allow us to examine the association between the master narratives that govern discourse related to health care in these pervasive information sources on the one hand and health behaviors on the other hand. Our initial focus will be on stories and comments from a broad range of sources related to human papillomavirus (HPV) vaccination. HPV vaccination has been the subject of considerable public debate both in the official journalistic realm and in the unofficial realms of the Internet and Infotainment at leas since the FDA approved the vaccine in 2006. The vaccine itself is widely available and recommended by health professionals, and still largely voluntary in most of the U.S., making it an ideal test case for studying the relationship of vaccination rates to the emergence of coherent master narratives related to vaccines in general and the HPV vaccine in particular.

Public Health Relevance

The project aims at understanding and modeling the public discourse that is being played out right now at an unprecedented scale via the confluence of multiple information channels, including official media, social media and Infotainment shows. In particular, the focus is on creating a geo-temporal map of the narratives that drive discourse on HPV vaccines, and then exploring if there is an association between such discourse and actual rates of HPV vaccinations. The results will have direct impact on how we understand the decision making processes that drive health care behavior, and also potentially provide guidance for future public health policies on how to better inform the public on the critical issues related to immunization.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM105033-03
Application #
8916794
Study Section
Special Emphasis Panel (ZGM1-BBCB-9 (MS))
Program Officer
Marcus, Stephen
Project Start
2013-09-25
Project End
2018-06-30
Budget Start
2015-07-01
Budget End
2016-06-30
Support Year
3
Fiscal Year
2015
Total Cost
$379,921
Indirect Cost
$82,660
Name
University of California Los Angeles
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
Himmelstein, Philip; Barb, Scott; Finlayson, Mark A et al. (2018) Linguistic analysis of the autobiographical memories of individuals with major depressive disorder. PLoS One 13:e0207814
Tangherlini, Timothy R; Roychowdhury, Vwani; Glenn, Beth et al. (2016) ""Mommy Blogs"" and the Vaccination Exemption Narrative: Results From A Machine-Learning Approach for Story Aggregation on Parenting Social Media Sites. JMIR Public Health Surveill 2:e166
Simkin, M V; Roychowdhury, V P (2015) Chess players' fame versus their merit. Appl Econ Lett 22:1499-1504
Simkin, Mikhail V; Roychowdhury, Vwani P (2015) Why Does Attention to Web Articles Fall With Time? J Assoc Inf Sci Technol 66:1847-1856
Simkin, M V; Roychowdhury, V P (2014) Stochastic modeling of a serial killer. J Theor Biol 355:111-6