Correlates of Cancer Information Overload: Focusing on Individual Ability and Motivation

Abstract

The present study defined cancer information overload (CIO) as an aversive disposition wherein a person is confused and overwhelmed by cancer information, which occurs when he or she fails to effectively categorize new information due to a lack of resources for effective learning. Based on the definition and informed by previous studies on information overload and the cognitive mediation model, we hypothesized that low ability and motivation to process cancer information would lead to CIO. We used education level and trait anxiety as factors related to ability. Cancer history and the use of active media channels (such as the Internet and print media) were adopted as motivational factors. Four samples (three from the United States and one from South Korea) were used to explore the relationship between ability/motivation and CIO. Among them, only Sample 4 participants answered questions about stomach cancer, and other participants were asked about cancer in general. In all four samples, trait anxiety was positively associated with CIO. Health information use from active media channels (print or the Internet) was negatively associated with CIO in three samples. The associations between family history and CIO, and between education and CIO, were found in two samples. In short, the present study demonstrated that CIO partly depends on individual ability and motivation, thereby showing that CIO is influenced by personal characteristics as well as environmental factors.

Acknowledgments

Chul-joo Lee acknowledges the support of the SNU Invitation Program for Distinguished Scholar, the ICT R&D program of MSIP/IITP [2013-005-002-013, How to create an ICT-based eco-system for content industry], and Grant #2015S1A58017994 from the National Research 293 Foundation of Korea for this research.

Notes

¹ We chose the cognitive mediation model (CMM) to explain the role of motivation in effective learning. Although there are other theories, such as the elaboration likelihood model (ELM; Petty & Cacioppo, 1986), that can theorize the relationship between ability/motivation and information processing, ELM has been tested mainly via experimental studies, while CMM has been used mainly in survey studies. Moreover, CMM views elaboration as an individual trait, consistent with the present study, which focuses on individual factors.

² The 2012 HINTS also has these four items, but we did not use them to predict CIO. The items describe the feelings that an individual has after information exposure. Thus, they are outcomes of CIO rather than its predictors.

³ It remains unclear whether hedging should be attributed to affiliated or unaffiliated scientists. Jensen (2008) demonstrated a positive association between hedging attributed to primary scientists and trustworthiness for scientists and journalists. On the other hand, Jensen et al. (2011) found that outside experts increased trust in medical professionals.