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Assessing perceived vulnerability to a health threat is essential to understanding how people conceptualize their risk, and to predicting how likely they are to engage in protective behaviors. However, there is limited consensus about which of many measures of perceived vulnerability predict behavior best. We tested whether the ability of different measures to predict protective intentions varies as a function of the type of information people learn about their risk. Online participants (N = 909) read information about a novel respiratory disease before answering measures of perceived vulnerability and vaccination intentions. Type-of-risk information was varied across three between-participant groups. Participants learned either: (1) only information about their comparative standing on the primary risk factors (comparative-only), (2) their comparative standing as well as the base-rate of the disease in the population (+ base-rate), or (3) their comparative standing as well as more specific estimates of their absolute risk (+ absolute-chart). Experiential and affective measures of perceived vulnerability predicted protective intentions well regardless of how participants learned about their risk, while the predictive ability of deliberative numeric and comparative measures varied based on the type of risk information provided. These results broaden the generalizability of key prior findings (i.e., some prior findings about which measures predict best may apply no matter how people learn about their risk), but the results also reveal boundary conditions and critical points of distinction for determining how to best assess perceived vulnerability. 

Past work has suggested that people prescribe optimism—believing it is better to be optimistic, instead of accurate or pessimistic, about uncertain future events. Here, we identified and addressed an important ambiguity about whether those findings reflect an endorsement of biased beliefs—that is, whether people prescribe likelihood estimates that reflect overoptimism. In three studies, participants ( N = 663 U.S. university students) read scenarios about protagonists facing uncertain events with a desired outcome. Results replicated prescriptions of optimism when we used the same solicitations as in past work. However, we found quite different prescriptions when using alternative solicitations that asked about potential bias in likelihood estimations and that did not involve vague terms such as “optimistic.” Participants generally prescribed being optimistic, feeling optimistic, and even thinking optimistically about the events, but they did not prescribe overestimating the likelihood of those events. 

When making decisions involving risk, people may learn about the risk from descriptions or from experience. The description-experience gap refers to the difference in decision patterns driven by this discrepancy in learning format. Across two experiments, we investigated whether learning from description versus experience differentially affects the direction and the magnitude of a context effect in risky decision making. In Study 1 and 2, a computerized game called the Decisions about Risk Task (DART) was used to measure people’s risk-taking tendencies toward hazard stimuli that exploded probabilistically. The rate at which a context hazard caused harm was manipulated, while the rate at which a focal hazard caused harm was held constant. The format by which this information was learned was also manipulated; it was learned primarily by experience or by description. The results revealed that participants’ behavior toward the focal hazard varied depending on what they had learned about the context hazard. Specifically, there were contrast effects in which participants were more likely to choose a risky behavior toward the focal hazard when the harm rate posed by the context hazard was high rather than low. Critically, these contrast effects were of similar strength irrespective of whether the risk information was learned from experience or description. Participants’ verbal assessments of risk likelihood also showed contrast effects, irrespective of learning format. Although risk information about a context hazard in DART does nothing to affect the objective expected value of risky versus safe behaviors toward focal hazards, it did affect participants’ perceptions and behaviors—regardless of whether the information was learned from description or experience. Our findings suggest that context has a broad-based role in how people assess and make decisions about hazards. 

Abstract The phenomenon of ambiguity aversion suggests that people prefer options that offer precisely rather than imprecisely known chances of success. However, past work on people's responses to ambiguity in health treatment contexts found ambiguity seeking rather than aversion. The present work addressed whether such findings reflected a broad tendency for ambiguity seeking in health treatment contexts or whether specific attributions for ambiguity play a substantial role. In three studies, people choose between two treatment options that involved similar underlying probabilities, except that the probabilities for one option involved ambiguity. The attributions offered for the ambiguity played an important role in the results. For example, when the range of probabilities associated with an ambiguous treatment was attributed to the fact that different studies yield different results, participants tended to show ambiguity aversion or indifference. However, when the range was attributed to something that participants could control (e.g., regular application of a cream) or something about which they were overoptimistic (e.g., their immune system function), participants tended to show ambiguity seeking. Health professionals should be mindful of how people will interpret and use information about ambiguity when choosing among treatments. 

Abstract AimSoil microorganisms are essential for the functioning of terrestrial ecosystems. Although soil microbial communities and functions are linked to tree species composition and diversity, there has been no comprehensive study of the generality or context dependence of these relationships. Here, we examine tree diversity–soil microbial biomass and respiration relationships across environmental gradients using a global network of tree diversity experiments. LocationBoreal, temperate, subtropical and tropical forests. Time period2013. Major taxa studiedSoil microorganisms. MethodsSoil samples collected from 11 tree diversity experiments were used to measure microbial respiration, biomass and respiratory quotient using the substrate‐induced respiration method. All samples were measured using the same analytical device, method and procedure to reduce measurement bias. We used linear mixed‐effects models and principal components analysis (PCA) to examine the effects of tree diversity (taxonomic and phylogenetic), environmental conditions and interactions on soil microbial properties. ResultsAbiotic drivers, mainly soil water content, but also soil carbon and soil pH, significantly increased soil microbial biomass and respiration. High soil water content reduced the importance of other abiotic drivers. Tree diversity had no effect on the soil microbial properties, but interactions with phylogenetic diversity indicated that the effects of diversity were context dependent and stronger in drier soils. Similar results were found for soil carbon and soil pH. Main conclusionsOur results indicate the importance of abiotic variables, especially soil water content, for maintaining high levels of soil microbial functions and modulating the effects of other environmental drivers. Planting tree species with diverse water‐use strategies and structurally complex canopies and high leaf area might be crucial for maintaining high soil microbial biomass and respiration. Given that greater phylogenetic distance alleviated unfavourable soil water conditions, reforestation efforts that account for traits improving soil water content or select more phylogenetically distant species might assist in increasing soil microbial functions.