Developing a Game Interface to Assess Risk Perception with Respect to Two Key Dimensions of Risk (Frequency and Severity) in Contexts Where Risks Are Elevated from Their Accepted, “Typical” Values

OBJECTIVE: This four-stage study culminated in a game interface designed to calibrate people's perceptions of net risk (combining frequency and severity), in contexts where risks are elevated from their accepted, "typical" values, as when avalanche threats elevate the risks of "skiing" above levels skiers normally accept. Risk prompts are displayed dynamically, in naturalistic language, and not, for example, as static displays of dollar amounts or probabilities. Individual differences are measured. MATERIALS AND METHODS: In Stage 1 (pilot), focus groups (n=9) piloted procedures, visual prompts, and examples of contexts where risks elevated from the "usual," for use in upcoming stages. In Stage 2 (exploratory), participants (primarily students; n=119; mean age, 20.1 years; 64 percent male) were assigned to risk contexts, answered demographic and risk-history questions, and then matched risk-description prompts to perceived "appropriate" levels along an ordinal risk scale. Descriptive measures and graphs showed response distributions; chi-squared analyses compared responses for different demographics. In Stage 3 (manipulating "cards"), participants (n=80; mean age, 37 years; 60 percent male) matched naturalistic risk prompts with ordinal risk positions. Regressions compared cards' placements with their "expected" (per exploratory Stage 2) placements. In Stage 4, the interface was coded in the Unity(®) (implemented at Business and IT Capstone, University of Ontario Institute of Technology, Oshawa, ON, Canada) development environment. RESULTS: In Stage 1, ambiguities in draft wordings/displays for Stage 2 were identified and corrected. Three risk contexts emerged: traffic/hidden intersection; skiing/avalanche; and swimming/drowning. In Stage 2, for traffic and skiing contexts, responses relating ordinal risk categories to realistic examples were observed to cluster around values potentially usable as markers. No associations appeared with demographic variables. In Stage 3, actual and "expected" ordinal-risk-category assignments for naturalistic risk markers were well correlated. "Approximate mappings" between markers and categories appeared stable. In Stage 4, the interface design incorporated the "approximate mappings"-yet also incorporated a "tuning phase," for measuring and recording individual differences. CONCLUSIONS: The interface can capture individual differences in risk perception on two key dimensions (frequency and severity)-viewed in dynamic, naturalistic scenarios, where risk levels are increased.

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