Session chair: Natalie Taylor
Is Ignorance Really Bliss?: Exploring the Interrelationships among Information Avoidance, Health Literacy, and Health Justice
Beth St. Jean, Gagan Jindal, & Yuting Liao
Although many people cope with an illness by seeking information, a considerable proportion of the population prefers to avoid information, aiming to maintain or increase their uncertainty in order to control their anxiety and/or maintain hope. Drawing on a large (n = 3,677), nationally-representative survey data set (the U.S. National Cancer Institute’s 2014 Health Information National Trends Survey (HINTS)), this paper investigates the prevalence of information avoidance (defined here as agreement with the statement, “I’d rather not know my chance of getting cancer”) among the U.S. adult population and identifies associations between information avoidance and other types of demographic, information-seeking, cognitive/perceptual, and social factors. The overarching aim of this research is to explore whether and how the concepts of information avoidance, health literacy, and health justice are interrelated. Based on a literature review and a secondary analysis of the HINTS data set, information avoidance, limited health literacy, and a lack of health justice appear to be intricately interwoven. In conclusion, suggestions are made as to how we might use these findings to interrupt the usual progression from low health literacy to poor health outcomes, thereby helping to decrease health disparities and address the lack of health justice in this country.
Healthy Users’ Personal Health Information Management from Activity Trackers: The Perspective of Gym-Goers
Yuanyuan Feng, Kai Li, & Denise E. Agosto
This paper examines how healthy activity tracker users, particularly gym-goers, manage personal health information generated by their activity tracking devices. Findings from 117 valid responses to a web survey are presented to provide an overall picture of healthy activity tracker users’ health or fitness-related needs, their personal health information management (PHIM) practices, and the gaps between their needs and PHIM. Based on the survey findings, we suggest considering future activity tracker design improvements for addressing users’ currently unmet needs while recognizing the limitations of current technology. We conclude with a discussion of the necessity for reexamining PHIM in a new era of broader self-tracking activities and needs.
Computational Content Analysis of Negative Tweets for Obesity, Diet, Diabetes, and Exercise
George Shaw, Jr. & Amir Karami
Social media based digital epidemiology has the potential to support faster response and deeper understanding of public health related threats. This study proposes a new framework to analyze unstructured health related textual data via Twitter users’ post (tweets) to characterize the negative health sentiments and non-health related concerns in relations to the corpus of negative sentiments; regarding Diet Diabetes Exercise, and Obesity (DDEO). Through the collection of 6 million Tweets for one month, this study identiﬁed the prominent topics of users as it relates to the negative sentiments. Our proposed framework uses two text mining methods, sentiment analysis and topic modeling, to discover negative topics. The negative sentiments of Twitter users support the literature narratives and the many morbidity issues that are associated with DDEO and the linkage between obesity and diabetes. The framework offers a potential method to understand the publics’ opinions and sentiments regarding DDEO. More importantly, this research provides new opportunities for computational social scientists, medical experts, and public health professionals to collectively address DDEO-related issues.