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Emotion in everyday risk perception 2 ABSTRACT Although research has documented the importance of emotion in risk perception, little is known about its prevalence in everyday life. Using the Experience Sampling Method, 94 part-time students were prompted at random -via cellular telephones -to report on mood state and three emotions and to assess risk on thirty occasions during their working hours. The emotionsvalence, arousal, and dominance -were measured using self-assessment manikins (Bradley & Lang, 1994). Hierarchical linear models (HLM) revealed that mood state and emotions explained significant variance in risk perception. In addition, valence and arousal accounted for variance over and above "reason" (measured by severity and possibility of risks). Six risks were reassessed in a post-experimental session and found to be lower than their real-time counterparts.The study demonstrates the feasibility and value of collecting representative samples of data with simple technology. Evidence for the statistical consistency of the HLM estimates is provided in an Appendix.

The experience sampling method (ESM) was used to collect data from 74 part‐time students who described and assessed the risks involved in their current activities when interrupted at random moments by text messages. The major categories of perceived risk were short term in nature and involved “loss of time or materials” related to work and “physical damage” (e.g., from transportation). Using techniques of multilevel analysis, we demonstrate effects of gender, emotional state, and types of risk on assessments of risk. Specifically, females do not differ from males in assessing the potential severity of risks but they see these as more likely to occur. Also, participants assessed risks to be lower when in more positive self‐reported emotional states. We further demonstrate the potential of ESM by showing that risk assessments associated with current actions exceed those made retrospectively. We conclude by noting advantages and disadvantages of ESM for collecting data about risk perceptions.

Emotion in everyday risk perception 2 ABSTRACT Although research has documented the importance of emotion in risk perception, little is known about its prevalence in everyday life. Using the Experience Sampling Method, 94 part-time students were prompted at random -via cellular telephones -to report on mood state and three emotions and to assess risk on thirty occasions during their working hours. The emotionsvalence, arousal, and dominance -were measured using self-assessment manikins (Bradley & Lang, 1994). Hierarchical linear models (HLM) revealed that mood state and emotions explained significant variance in risk perception. In addition, valence and arousal accounted for variance over and above "reason" (measured by severity and possibility of risks). Six risks were reassessed in a post-experimental session and found to be lower than their real-time counterparts.The study demonstrates the feasibility and value of collecting representative samples of data with simple technology. Evidence for the statistical consistency of the HLM estimates is provided in an Appendix.

No abstract