Information Seeking in Uncertainty Management Theory: Exposure to Information About Medical Uncertainty and Information-Processing Orientation as Predictors of Uncertainty Management Success

Abstract

Uncertainty management theory outlines the processes through which individuals cope with health-related uncertainty. Information seeking has been frequently documented as an important uncertainty management strategy. The reported study investigates exposure to specific types of medical information during a search, and one's information-processing orientation as predictors of successful uncertainty management (i.e., a reduction in the discrepancy between the level of uncertainty one feels and the level one desires). A lab study was conducted in which participants were primed to feel more or less certain about skin cancer and then were allowed to search the World Wide Web for skin cancer information. Participants’ search behavior was recorded and content analyzed. The results indicate that exposure to two health communication constructs that pervade medical forms of uncertainty (i.e., severity and susceptibility) and information-processing orientation predicted uncertainty management success.

Notes

¹The outliers for time spent per webpage, in particular, are noteworthy because they suggest that these participants failed to follow the study instructions. Although the average participant viewed about seven different webpages (not websites) and spent about 90 seconds per page, most of the outlying cases on time per webpage viewed one or two webpages and spent approximately six or more minutes per webpage. In reviewing the actual webpages that these participants visited, it seems very unlikely that there was 6 min worth of content to be considered. For example, one participant spent the entire search time on a webpage that featured less than 150 words of text and contained no audio or video content. Another only viewed the landing page for a major website; yet that page provides no information per se, only links to various articles. We believe that these extreme scores are the result of participants failing to close their browser when they were done searching. As a result, it is impossible to know how much time they actually spent per webpage. Excluding these cases ensures that they do not unduly influence the results.

²An after-the-fact power analysis (O'Keefe, 2007) showed that the sample size provided adequate power (>.95) to detect a medium size effect (f² = .10).