The impact of probabilistic tornado warnings on risk perceptions and responses.

Many warnings issued to members of the public are deterministic in that they do not include event likelihood information. This is true of the current polygon-based tornado warning used by the American National Weather Service, although the likelihood of a tornado varies within the boundaries of the polygon. To test whether adding likelihood information benefits end users, two experimental studies and one in-person interview study were conducted. The experimental studies compared five probabilistic formats, two with color and three with numeric probabilities alone, to the deterministic polygon. In both experiments, probabilistic formats led to better understanding of tornado likelihood and higher trust than the polygon alone, although color-coding led to several misunderstandings. When the polygon boundary was drawn at 10% chance, those using probabilistic formats made fewer correct shelter decisions at low probabilities and more correct shelter decisions at high probabilities compared to those using the deterministic warning, although overall decision quality, operationalized as expected value, did not differ. However, when the polygon boundary was drawn around 30%, participants with probabilistic forecasts had higher expected value. The interview study revealed that, although tornado-experienced individuals would not shelter at 10% chance, they would take intermediate actions, such as information-seeking and sharing. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Reducing vaccine hesitancy by explaining vaccine science.

Vaccine hesitancy in the COVID-19 pandemic remained a problem long after mRNA vaccines became available. This may be due in part to misunderstandings about the vaccines, arising from complexities of the science involved. Two experiments, conducted on unvaccinated Americans at two periods postvaccine rollout in 2021, demonstrated that providing explanations, expressed in everyday language, and correcting known misunderstandings, reduced vaccine hesitancy compared to a no-information control group. Four explanations addressing misunderstandings about mRNA vaccine safety and effectiveness were tested in Experiment 1 (n = 3,787). Some included expository text while others included refutational text, explicitly stating and refuting the misunderstanding. Vaccine effectiveness statistics were expressed either as text or an icon array. Although all four explanations reduced vaccine hesitancy, the refutational format of those addressing vaccine safety (explaining the mRNA mechanism and mild side effects) was the most effective. These two explanations were retested individually and jointly in Experiment 2 (n = 1,476) later in the summer of 2021. Again, vaccine hesitancy was significantly reduced by all explanations despite differences in political ideology, trust, and prior attitudes. These results suggest that nontechnical explanations of critical issues in vaccine science can reduce vaccine hesitancy, especially when accompanied by refutational text. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Explaining how long CO2 stays in the atmosphere: Does it change attitudes toward climate change?

Despite overwhelming scientific consensus about climate change, the majority of Americans are not very worried about it. This may be due in part to insufficient understanding of the urgency and seriousness, which may be related among some, to distrust of the scientific community. We test these hypotheses in an experimental study using a broadly nationally representative sample. An explanation of the delay between the reduction of greenhouse gas emissions and cessation of global warming was compared to two control groups, one with basic climate change information and another with no information. Participants also received climate predictions that either included or excluded uncertainty estimates for a 3 × 2 complete factorial design. Results suggest that the delay explanation increased participants understanding of this issue and reduced their agreement with a wait-and-see strategy, especially among conservatives. Moreover, uncertainty estimates increased trust in climate predictions and ratings of climate scientists' expertise and understanding. Uncertainty estimates also increased concern about climate change and the perception of scientific consensus. Although in some cases small, these positive effects were seen across political ideology groups. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Risk perception, decision-making, and risk communication in the time of COVID-19.

After first being declared a pandemic by the World Health Organization [WHO], (2020) in March 2020, coronavirus disease (COVID-19) spread rapidly and in the process altered our very way of life. At the same time, it became increasingly clear that a wide range of new behavioral science research was necessary to understand fully how people comprehend and respond to such an unprecedented and long lasting health threat as COVID-19. One of the primary aims for this Special Issue was to gather and publish that research. The studies contained in this Special Issue, conducted between April 2020 and March 2021, were selected to represent experimental research that is relevant to this unique situation and that also inform and extend existing theory. These studies investigate three broad topics: Risk perception, decision-making under risk, and risk communication in the context of COVID-19. Collectively, they advance our knowledge of risk calibration, health communication interventions, and decisions about behaviors that address risk in the context of a global health threat. Perhaps most importantly they also make a practical contribution to how we approach these issues going forward. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

COVID-19: Risk perception, risk communication, and behavioral intentions.

Critical to limiting the spread of Coronavirus disease 2019 (COVID-19) and future pandemics is compliance with behavioral recommendations such as mask wearing and social distancing. Compliance may depend upon understanding the seriousness of the health consequences and the likelihood they will occur. However, the statistics that speak to these issues in an ongoing pandemic are complex and may be misunderstood. An online experiment with a U.S. sample tested the impact on perceived likelihood, trust, concern, behavioral intentions, and agreement with government response of numeric (mortality/infection percentage by age group) and gist expressions (which age group was smaller [mortality] or roughly equivalent [infected]). While the differences in risk perception and willingness to engage in activities between younger and older participants were small, "gist infection and mortality" increased willingness to wear a mask among younger participants. Government restrictions (e.g., social distancing) impacted willingness to engage is risk-reduction and risk-seeking activities. The biggest differences were due to political ideology. Although conservatives perceived similar levels of risk as did liberals, they were much less willing to engage in protective behaviors and support government policies. However, conservatives were affected by some risk communication formats and restrictions suggesting that future work should be aimed at this issue. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Communicating weather forecast uncertainty: Do individual differences matter?

Research suggests that people make better weather-related decisions when they are given numeric probabilities for critical outcomes (Joslyn & Leclerc, 2012, 2013). However, it is unclear whether all users can take advantage of probabilistic forecasts to the same extent. The research reported here assessed key cognitive and demographic factors to determine their relationship to the use of probabilistic forecasts to improve decision quality. In two studies, participants decided between spending resources to prevent icy conditions on roadways or risk a larger penalty when freezing temperatures occurred. Several forecast formats were tested, including a control condition with the night-time low temperature alone and experimental conditions that also included the probability of freezing and advice based on expected value. All but those with extremely low numeracy scores made better decisions with probabilistic forecasts. Importantly, no groups made worse decisions when probabilities were included. Moreover, numeracy was the best predictor of decision quality, regardless of forecast format, suggesting that the advantage may extend beyond understanding the forecast to general decision strategy issues. This research adds to a growing body of evidence that numerical uncertainty estimates may be an effective way to communicate weather danger to general public end users. (PsycINFO Database Record

Understanding clinical and non-clinical decisions under uncertainty: a scenario-based survey.

BACKGROUND: Prospect theory suggests that when faced with an uncertain outcome, people display loss aversion by preferring to risk a greater loss rather than incurring certain, lesser cost. Providing probability information improves decision making towards the economically optimal choice in these situations. Clinicians frequently make decisions when the outcome is uncertain, and loss aversion may influence choices. This study explores the extent to which prospect theory, loss aversion, and probability information in a non-clinical domain explains clinical decision making under uncertainty. METHODS: Four hundred sixty two participants (n = 117 non-medical undergraduates, n = 113 medical students, n = 117 resident trainees, and n = 115 medical/surgical faculty) completed a three-part online task. First, participants completed an iced-road salting task using temperature forecasts with or without explicit probability information. Second, participants chose between less or more risk-averse ("defensive medicine") decisions in standardized scenarios. Last, participants chose between recommending therapy with certain outcomes or risking additional years gained or lost. RESULTS: In the road salting task, the mean expected value for decisions made by clinicians was better than for non-clinicians(-$1,022 vs -$1,061; <0.001). Probability information improved decision making for all participants, but non-clinicians improved more (mean improvement of $64 versus $33; p = 0.027). Mean defensive decisions decreased across training level (medical students 2.1 ± 0.9, residents 1.6 ± 0.8, faculty1.6 ± 1.1; p-trend < 0.001) and prospect-theory-concordant decisions increased (25.4%, 33.9%, and 40.7%;p-trend = 0.016). There was no relationship identified between road salting choices with defensive medicine and prospect-theory-concordant decisions. CONCLUSIONS: All participants made more economically-rational decisions when provided explicit probability information in a non-clinical domain. However, choices in the non-clinical domain were not related to prospect-theory concordant decision making and risk aversion tendencies in the clinical domain. Recognizing this discordance may be important when applying prospect theory to interventions aimed at improving clinical care.

Climate Projections and Uncertainty Communication.

Lingering skepticism about climate change might be due in part to the way climate projections are perceived by members of the public. Variability between scientists' estimates might give the impression that scientists disagree about the fact of climate change rather than about details concerning the extent or timing. Providing uncertainty estimates might clarify that the variability is due in part to quantifiable uncertainty inherent in the prediction process, thereby increasing people's trust in climate projections. This hypothesis was tested in two experiments. Results suggest that including uncertainty estimates along with climate projections leads to an increase in participants' trust in the information. Analyses explored the roles of time, place, demographic differences (e.g., age, gender, education level, political party affiliation), and initial belief in climate change. Implications are discussed in terms of the potential benefit of adding uncertainty estimates to public climate projections.

The use of uncertainty forecasts in complex decision tasks and various weather conditions.

Recent research on weather-related decision-making suggests that the inclusion of numeric uncertainty estimates in weather forecasts improves decision quality over single value forecasts or specific advice. However, it is unclear if the benefit of uncertainty estimates extends to more complex decision tasks, presumably requiring greater cognitive effort, or to tasks in which the decision is clear-cut, perhaps making the additional uncertainty information unnecessary. In the present research, participants completed a task in which they used single value weather forecasts, either alone, with freeze probabilities, advice, or both, to decide whether to apply salt to roads in winter to prevent icing or to withhold salt and risk a penalty. Participants completed either a simple binary choice version of the task or a complex version with 3 response options and accompanying rules for application. Some participants were shown forecasts near the freezing point, such that the need for salt was ambiguous, whereas other participants were shown forecasts well below the freezing point. Results suggest that participants with uncertainty estimates did better overall, and neither the task complexity nor the coldness of the forecasts reduced that advantage. However, unexpectedly colder forecasts lead to poorer decisions and an advantage for specific advice.

The cry wolf effect and weather-related decision making.

Despite improvements in forecasting extreme weather events, noncompliance with weather warnings among the public remains a problem. Although there are likely many reasons for noncompliance with weather warnings, one important factor might be people's past experiences with false alarms. The research presented here explores the role of false alarms in weather-related decision making. Over a series of trials, participants used an overnight low temperature forecast and advice from a decision aid to decide whether to apply salt treatment to a town's roads to prevent icy conditions or take the risk of withholding treatment, which resulted in a large penalty when freezing temperatures occurred. The decision aid gave treatment recommendations, some of which were false alarms, i.e., treatment was recommended but observed temperatures were above freezing. The rate at which the advice resulted in false alarms was manipulated between groups. Results suggest that very high and very low false alarm rates led to inferior decision making, but that lowering the false alarm rate slightly did not significantly affect compliance or decision quality. However, adding a probabilistic uncertainty estimate in the forecasts improved both compliance and decision quality. These findings carry implications about how weather warnings should be communicated to the public.

Uncertainty forecasts improve weather-related decisions and attenuate the effects of forecast error.

Although uncertainty is inherent in weather forecasts, explicit numeric uncertainty estimates are rarely included in public forecasts for fear that they will be misunderstood. Of particular concern are situations in which precautionary action is required at low probabilities, often the case with severe events. At present, a categorical weather warning system is used. The work reported here tested the relative benefits of several forecast formats, comparing decisions made with and without uncertainty forecasts. In three experiments, participants assumed the role of a manager of a road maintenance company in charge of deciding whether to pay to salt the roads and avoid a potential penalty associated with icy conditions. Participants used overnight low temperature forecasts accompanied in some conditions by uncertainty estimates and in others by decision advice comparable to categorical warnings. Results suggested that uncertainty information improved decision quality overall and increased trust in the forecast. Participants with uncertainty forecasts took appropriate precautionary action and withheld unnecessary action more often than did participants using deterministic forecasts. When error in the forecast increased, participants with conventional forecasts were reluctant to act. However, this effect was attenuated by uncertainty forecasts. Providing categorical decision advice alone did not improve decisions. However, combining decision advice with uncertainty estimates resulted in the best performance overall. The results reported here have important implications for the development of forecast formats to increase compliance with severe weather warnings as well as other domains in which one must act in the face of uncertainty.

Reducing probabilistic weather forecasts to the worst-case scenario: anchoring effects.

Many weather forecast providers believe that forecast uncertainty in the form of the worst-case scenario would be useful for general public end users. We tested this suggestion in 4 studies using realistic weather-related decision tasks involving high winds and low temperatures. College undergraduates, given the statistical equivalent of the worst-case scenario (1 boundary of the 80% predictive interval), demonstrated biased understanding of future weather conditions compared with those given both bounds or no uncertainty information. We argue that this was due to an anchoring effect on numeric estimates, which were closer to the worst-case scenario than was warranted and increased linearly as the anchor became more extreme. In many situations tested here, anchoring in numeric estimates also extended to subsequent binary decisions, leading participants with the worst-case scenario to take action more often than did other participants. These results suggest that worst-case scenario forecasts can mislead the user. They appear to convince people that wind speeds will be higher and temperatures will be lower than what are indicated by the forecast. In addition, participants systematically "corrected" the forecast they were given. This effect was most prominent in the condition in which no uncertainty was provided, suggesting that people feel compelled to take uncertainty into account, even when it is not acknowledged by the forecast. Both the anchoring and correction biases were least evident when both bounds were provided, suggesting that balanced uncertainty leads to the best understanding of future weather conditions.

Directed forgetting of autobiographical events.

Two diary experiments demonstrated directed forgetting (DF) of autobiographical events, previously observed only for less complex memory items. Using a 2-week diary paradigm, we compared recall between a group of participants who were directed to forget Week 1 memories (forget group) and a group who did not receive a forget instruction (remember group). In Experiment 1, the forget group remembered fewer items from Week 1 than did the remember group. The effect was observed for negative and positive valence events, as well as for high and low emotional intensity events. The effect was replicated in Experiment 2 despite a memorable holiday (Valentine's Day) that occurred during the manipulation week. Forget participants remembered fewer low emotional intensity items in Experiment 2. We conclude that intentional forgetting is a plausible explanation for the loss of some autobiographical memories.