Planning to Reduce the Health Impacts of Extreme Heat: A Content Analysis of Heat Action Plans in Local United States Jurisdictions.

Objectives. To examine commonalities and gaps in the content of local US heat action plans (HAPs) designed to decrease the adverse health effects of extreme heat. Methods. We used content analysis to identify common strategies and gaps in extreme heat preparedness among written HAPs in the United States from jurisdictions that serve municipalities with more than 200 000 residents. We reviewed, coded, and analyzed plans to assess the prevalence of key components and strategies. Results. All 21 plans evaluated incorporated data on activation triggers, heat health messaging and risk communication, cooling centers, surveillance activities, and agency coordination, and 95% incorporated information on outreach to at-risk populations. Gaps existed in the specific applications of these broad strategies. Conclusions. Practice-based recommendations as well as future areas of research should focus on increasing targeted strategies for at-risk individuals and expanding the use of surveillance data outside of situational awareness. (Am J Public Health. 2023;113(5):559-567. https://doi.org/10.2105/AJPH.2022.307217).

Trust and trustworthy artificial intelligence: A research agenda for AI in the environmental sciences.

Demands to manage the risks of artificial intelligence (AI) are growing. These demands and the government standards arising from them both call for trustworthy AI. In response, we adopt a convergent approach to review, evaluate, and synthesize research on the trust and trustworthiness of AI in the environmental sciences and propose a research agenda. Evidential and conceptual histories of research on trust and trustworthiness reveal persisting ambiguities and measurement shortcomings related to inconsistent attention to the contextual and social dependencies and dynamics of trust. Potentially underappreciated in the development of trustworthy AI for environmental sciences is the importance of engaging AI users and other stakeholders, which human-AI teaming perspectives on AI development similarly underscore. Co-development strategies may also help reconcile efforts to develop performance-based trustworthiness standards with dynamic and contextual notions of trust. We illustrate the importance of these themes with applied examples and show how insights from research on trust and the communication of risk and uncertainty can help advance the understanding of trust and trustworthiness of AI in the environmental sciences.

"When people see me, they know me; they trust what I say": characterizing the role of trusted sources for smoke risk communication in the Okanogan River Airshed Emphasis Area.

INTRODUCTION: As wildfire smoke events increase in intensity and frequency in the Pacific Northwest, there is a growing need for effective communication on the health risks of smoke exposure. Delivery through a trusted source or intermediary has been shown to improve reception of risk communication messages. This is especially salient in rural and tribal communities who may be hesitant to trust information from state and federal agency sources. This study aims to identify and characterize trusted sources for smoke risk information in the Okanogan River Airshed Emphasis Area (ORAEA), a rural region of North Central Washington state that is heavily impacted by smoke from wildfires and prescribed fire. METHODS: The research team conducted a qualitative study using data collected through key informant interviews and focus groups to assess the role of various sources and intermediaries in disseminating smoke risk information. We used a consensual coding approach in NVivo Qualitative Analysis Software to sort data into preliminary categories, which were grouped into themes using a thematic analysis approach. We used member checking and iterative feedback processes with local project partners throughout the project to ensure credibility of results. RESULTS: Through the analysis, we identified three themes characterizing trusted sources for smoke risk communication in the ORAEA. These themes were: (1) local and tribal sources of information are perceived as more trustworthy than state and federal government sources, (2) trustworthiness is determined by an evaluation of multiple factors, in particular, perceived credibility, quality of information, and relationship with the source, and (3) conservative political ideology and perceived parallels with COVID-19 communication influence perception of trust. Within each theme, we identified several sub-themes, which contributed additional nuance to our analysis. CONCLUSION: This study provides insights into which sources of information are trusted by rural and tribal community members in the ORAEA and why. Results from our study emphasize the importance of relationships and collaboration with local and tribal partners in smoke risk communication. In this paper, we discuss implications for state and federal agency practitioners and present recommendations for how to work with local and tribal partners on smoke risk communication.

Health and safety risk perceptions and needs of app-based drivers during COVID-19.

BACKGROUND: App-based drivers face work disruptions and infection risk during a pandemic due to the nature of their work, interactions with the public, and lack of workplace protections. Limited occupational health research has focused on their experiences. METHODS: We surveyed 100 app-based drivers in Seattle, WA to assess risk perceptions, supports, and controls received from the company that employs them, sources of trust, stress, job satisfaction, COVID-19 infection status, and how the pandemic had changed their work hours. Data were summarized descriptively and with simple regression models. We complemented this with qualitative interviews to better understand controls and policies enacted during COVID-19, and barriers and facilitators to their implementation. RESULTS: Drivers expressed very high levels of concern for exposure and infection (86%-97% were "very concerned" for all scenarios). Only 31% of drivers reported receiving an appropriate mask from the company for which they drive. Stress (assessed via PSS-4) was significantly higher in drivers who reported having had COVID-19, and also significantly higher in respondents with lower reported job satisfaction. Informants frequently identified supports such as unemployment benefits and peer outreach among the driver community as ways to ensure that drivers could access available benefits during COVID-19. CONCLUSIONS: App-based drivers received few protections from the company that employed them, and had high fear of exposure and infection at work. There is increased need for health-supportive policies and protections for app-based drivers. The most effective occupational and public health regulations would cover employees who may not have a traditional employer-employee relationship.

Indiscriminate, Irrelevant, and Sometimes Wrong: Causal Misconceptions about Climate Change.

Prior research demonstrates widespread persistence of beliefs about climate change causes and risks that are arguably misconceptions. They include believing pollution causes climate change, believing ozone depletion causes climate change, the combination of these two "green beliefs," referred to as environmental problems, and believing natural climate variation significantly contributes to current climate trends. Each of these causal beliefs has the potential to weaken or divert support away from effective climate change risk mitigation policies. To assess this potential, we explore the nature and prevalence of these beliefs in the United States with a national sample of interviews (N = 77) and two national surveys (N = 1,013, N = 1,820), and apply regression and mediation analyses to explore whether they explain any of the variation in individuals' concern or support for policy to mitigate climate change. Adherence to these beliefs-which reflect a variety of misconceptions illustrated in the interviews-differs by political ideology but is common, with over a third of interviewees mentioning one or more. Controlling for general knowledge, political ideology, and other factors, misconceptions about environmental problems are still associated directly with support for climate change policies. On average adherence to the belief that environmental problems cause climate change is associated with a 25% higher probability of policy support. In contrast, believing natural climate variability is a major recent cause of climate change is associated with a 7% lower probability of supporting climate policy, even after controlling for political ideology and other knowledge about climate change.

Efficacy, Action, and Support for Reducing Climate Change Risks.

A growing body of research demonstrates that believing action to reduce the risks of climate change is both possible (self-efficacy) and effective (response efficacy) is essential to motivate and sustain risk mitigation efforts. Despite this potentially critical role of efficacy beliefs, measures and their use vary wildly in climate change risk perception and communication research, making it hard to compare and learn from efficacy studies. To address this problem and advance our understanding of efficacy beliefs, this article makes three contributions. First, we present a theoretically motivated approach to measuring climate change mitigation efficacy, in light of diverse proposed, perceived, and previously researched strategies. Second, we test this in two national survey samples (Amazon's Mechanical Turk N = 405, GfK Knowledge Panel N = 1,820), demonstrating largely coherent beliefs by level of action and discrimination between types of efficacy. Four additive efficacy scales emerge: personal self-efficacy, personal response efficacy, government and collective self-efficacy, and government and collective response efficacy. Third, we employ the resulting efficacy scales in mediation models to test how well efficacy beliefs predict climate change policy support, controlling for specific knowledge, risk perceptions, and ideology, and allowing for mediation by concern. Concern fully mediates the relatively strong effects of perceived risk on policy support, but only partly mediates efficacy beliefs. Stronger government and collective response efficacy beliefs and personal self-efficacy beliefs are both directly and indirectly associated with greater support for reducing the risks of climate change, even after controlling for ideology and causal beliefs about climate change.

Efficacy Foundations for Risk Communication: How People Think About Reducing the Risks of Climate Change.

Believing action to reduce the risks of climate change is both possible (self-efficacy) and effective (response efficacy) is essential to motivate and sustain risk mitigation efforts, according to current risk communication theory. Although the public recognizes the dangers of climate change, and is deluged with lists of possible mitigative actions, little is known about public efficacy beliefs in the context of climate change. Prior efficacy studies rely on conflicting constructs and measures of efficacy, and links between efficacy and risk management actions are muddled. As a result, much remains to learn about how laypersons think about the ease and effectiveness of potential mitigative actions. To bring clarity and inform risk communication and management efforts, we investigate how people think about efficacy in the context of climate change risk management by analyzing unprompted and prompted beliefs from two national surveys (N = 405, N = 1,820). In general, respondents distinguish little between effective and ineffective climate strategies. While many respondents appreciate that reducing fossil fuel use is an effective risk mitigation strategy, overall assessments reflect persistent misconceptions about climate change causes, and uncertainties about the effectiveness of risk mitigation strategies. Our findings suggest targeting climate change risk communication and management strategies to (1) address gaps in people's existing mental models of climate action, (2) leverage existing public understanding of both potentially effective mitigation strategies and the collective action dilemma at the heart of climate change action, and (3) take into account ideologically driven reactions to behavior change and government action framed as climate action.

Public Perceptions of How Long Air Pollution and Carbon Dioxide Remain in the Atmosphere.

The atmospheric residence time of carbon dioxide is hundreds of years, many orders of magnitude longer than that of common air pollution, which is typically hours to a few days. However, randomly selected respondents in a mail survey in Allegheny County, PA (N = 119) and in a national survey conducted with MTurk (N = 1,013) judged the two to be identical (in decades), considerably overestimating the residence time of air pollution and drastically underestimating that of carbon dioxide. Moreover, while many respondents believed that action is needed today to avoid climate change (regardless of cause), roughly a quarter held the view that if climate change is real and serious, we will be able to stop it in the future when it happens, just as we did with common air pollution. In addition to assessing respondents' understanding of how long carbon dioxide and common air pollution stay in the atmosphere, we also explored the extent to which people correctly identified causes of climate change and how their beliefs affect support for action. With climate change at the forefront of politics and mainstream media, informing discussions of policy is increasingly important. Confusion about the causes and consequences of climate change, and especially about carbon dioxide's long atmospheric residence time, could have profound implications for sustained support of policies to achieve reductions in carbon dioxide emissions and other greenhouse gases.

Assessing what to address in science communication.

As members of a democratic society, individuals face complex decisions about whether to support climate change mitigation, vaccinations, genetically modified food, nanotechnology, geoengineering, and so on. To inform people's decisions and public debate, scientific experts at government agencies, nongovernmental organizations, and other organizations aim to provide understandable and scientifically accurate communication materials. Such communications aim to improve people's understanding of the decision-relevant issues, and if needed, promote behavior change. Unfortunately, existing communications sometimes fail when scientific experts lack information about what people need to know to make more informed decisions or what wording people use to describe relevant concepts. We provide an introduction for scientific experts about how to use mental models research with intended audience members to inform their communication efforts. Specifically, we describe how to conduct interviews to characterize people's decision-relevant beliefs or mental models of the topic under consideration, identify gaps and misconceptions in their knowledge, and reveal their preferred wording. We also describe methods for designing follow-up surveys with larger samples to examine the prevalence of beliefs as well as the relationships of beliefs with behaviors. Finally, we discuss how findings from these interviews and surveys can be used to design communications that effectively address gaps and misconceptions in people's mental models in wording that they understand. We present applications to different scientific domains, showing that this approach leads to communications that improve recipients' understanding and ability to make informed decisions.

"Know What to Do If You Encounter a Flash Flood": Mental Models Analysis for Improving Flash Flood Risk Communication and Public Decision Making.

Understanding how people view flash flood risks can help improve risk communication, ultimately improving outcomes. This article analyzes data from 26 mental models interviews about flash floods with members of the public in Boulder, Colorado, to understand their perspectives on flash flood risks and mitigation. The analysis includes a comparison between public and professional perspectives by referencing a companion mental models study of Boulder-area professionals. A mental models approach can help to diagnose what people already know about flash flood risks and responses, as well as any critical gaps in their knowledge that might be addressed through improved risk communication. A few public interviewees mentioned most of the key concepts discussed by professionals as important for flash flood warning decision making. However, most interviewees exhibited some incomplete understandings and misconceptions about aspects of flash flood development and exposure, effects, or mitigation that may lead to ineffective warning decisions when a flash flood threatens. These include important misunderstandings about the rapid evolution of flash floods, the speed of water in flash floods, the locations and times that pose the greatest flash flood risk in Boulder, the value of situational awareness and environmental cues, and the most appropriate responses when a flash flood threatens. The findings point to recommendations for ways to improve risk communication, over the long term and when an event threatens, to help people quickly recognize and understand threats, obtain needed information, and make informed decisions in complex, rapidly evolving extreme weather events such as flash floods.

Flash Flood Risks and Warning Decisions: A Mental Models Study of Forecasters, Public Officials, and Media Broadcasters in Boulder, Colorado.

Timely warning communication and decision making are critical for reducing harm from flash flooding. To help understand and improve extreme weather risk communication and management, this study uses a mental models research approach to investigate the flash flood warning system and its risk decision context. Data were collected in the Boulder, Colorado area from mental models interviews with forecasters, public officials, and media broadcasters, who each make important interacting decisions in the warning system, and from a group modeling session with forecasters. Analysis of the data informed development of a decision-focused model of the flash flood warning system that integrates the professionals' perspectives. Comparative analysis of individual and group data with this model characterizes how these professionals conceptualize flash flood risks and associated uncertainty; create and disseminate flash flood warning information; and perceive how warning information is (and should be) used in their own and others' decisions. The analysis indicates that warning system functioning would benefit from professionals developing a clearer, shared understanding of flash flood risks and the warning system, across their areas of expertise and job roles. Given the challenges in risk communication and decision making for complex, rapidly evolving hazards such as flash floods, another priority is development of improved warning content to help members of the public protect themselves when needed. Also important is professional communication with members of the public about allocation of responsibilities for managing flash flood risks, as well as improved system-wide management of uncertainty in decisions.

Factors Affecting Hurricane Evacuation Intentions.

Protective actions for hurricane threats are a function of the environmental and information context; individual and household characteristics, including cultural worldviews, past hurricane experiences, and risk perceptions; and motivations and barriers to actions. Using survey data from the Miami-Dade and Houston-Galveston areas, we regress individuals' stated evacuation intentions on these factors in two information conditions: (1) seeing a forecast that a hurricane will hit one's area, and (2) receiving an evacuation order. In both information conditions having an evacuation plan, wanting to keep one's family safe, and viewing one's home as vulnerable to wind damage predict increased evacuation intentions. Some predictors of evacuation intentions differ between locations; for example, Florida respondents with more egalitarian worldviews are more likely to evacuate under both information conditions, and Florida respondents with more individualist worldviews are less likely to evacuate under an evacuation order, but worldview was not significantly associated with evacuation intention for Texas respondents. Differences by information condition also emerge, including: (1) evacuation intentions decrease with age in the evacuation order condition but increase with age in the saw forecast condition, and (2) evacuation intention in the evacuation order condition increases among those who rely on public sources of information on hurricane threats, whereas in the saw forecast condition evacuation intention increases among those who rely on personal sources. Results reinforce the value of focusing hurricane information efforts on evacuation plans and residential vulnerability and suggest avenues for future research on how hurricane contexts shape decision making.

Evaluating an equity-focused approach to assess climate resilience and disaster priorities through a community survey.

As the Duwamish Valley community in Seattle, Washington, U.S.A. and other environmental justice communities nationally contend with growing risks from climate change, there have been calls for a more community-centered approach to understanding impacts and priorities to inform resilience planning. To engage community members and identify climate justice and resilience priorities, a partnership of community leaders, government-based practitioners, and academics co-produced a survey instrument and collected data from the community using the Seattle Assessment for Public Health Emergency Response (SASPER), an approach adapted from the Centers for Disease Control and Prevention's Community Assessment for Public Health Emergency Response (CASPER). In addition, we conducted a process and outcome project evaluation using quantitative survey data collected from volunteers and qualitative semi-structured interviews with project team members. In October and November 2022, teams of volunteers from partner organizations collected 162 surveys from households in the Duwamish Valley. Poor air quality, extreme heat, and wildfires were among the highest reported hazards of concern. Most Duwamish Valley households agreed or strongly agreed that their neighborhood has a strong sense of community (64%) and that they have people nearby to call when they need help (69%). Forty-seven percent of households indicated willingness to get involved with resilience planning, and 62% of households said that they would use a Resilience Hub during an emergency. Survey volunteers evaluated their participation positively, with over 85% agreeing or strongly agreeing that they learned new skills, were prepared for the survey, and would participate in future assessments. The evaluation interviews underscored that while the SASPER may have demonstrated feasibility in a pre-disaster phase, CASPER may not meet all community/partner needs in the immediate disaster response phase because of its lack of focus on equity and logistical requirements. Future research should focus on identifying less resource intensive data collection approaches that maintain the rigor and reputation of CASPER while enabling a focus on equity.

Cognitive mapping tools: review and risk management needs.

Risk managers are increasingly interested in incorporating stakeholder beliefs and other human factors into the planning process. Effective risk assessment and management requires understanding perceptions and beliefs of involved stakeholders, and how these beliefs give rise to actions that influence risk management decisions. Formal analyses of risk manager and stakeholder cognitions represent an important first step. Techniques for diagramming stakeholder mental models provide one tool for risk managers to better understand stakeholder beliefs and perceptions concerning risk, and to leverage this new understanding in developing risk management strategies. This article reviews three methodologies for assessing and diagramming stakeholder mental models--decision-analysis-based mental modeling, concept mapping, and semantic web analysis--and assesses them with regard to their ability to address risk manager needs.

Flood risk management: U.S. Army Corps of Engineers and layperson perceptions.

Recent severe storm experiences in the U.S. Gulf Coast illustrate the importance of an integrated approach to flood preparedness planning that harmonizes stakeholder and agency efforts. Risk management decisions that are informed by and address decision maker and stakeholder risk perceptions and behavior are essential for effective risk management policy. A literature review and two expert models/mental models studies were undertaken to identify areas of importance in the flood risk management process for layperson, non-USACE-expert, and two USACE-expert groups. In characterizing and mapping stakeholder beliefs about risks in the literature onto current risk management practice, recommendations for accommodating and changing stakeholder perceptions of flood risks and their management are identified. Needs of the U.S. Army Corps of Engineers (USACE) flood preparedness and response program are discussed in the context of flood risk mental models.

Nanotechnology risk communication past and prologue.

Nanotechnologies operate at atomic, molecular, and macromolecular scales, at scales where matter behaves differently than at larger scales and quantum effects can dominate. Nanotechnologies have captured the imagination of science fiction writers as science, engineering, and industry have leapt to the challenge of harnessing them. Applications are proliferating. In contrast, despite recent progress the regulatory landscape is not yet coherent, and public awareness of nanotechnology remains low. This has led risk researchers and critics of current nanotechnology risk communication efforts to call for proactive strategies that do more than address facts, that include and go beyond the public participation stipulated by some government acts. A redoubling of nanotechnology risk communication efforts could enable consumer choice and informed public discourse about regulation and public investments in science and safety.

Now what do people know about global climate change? Survey studies of educated laypeople.

In 1992, a mental-models-based survey in Pittsburgh, Pennsylvania, revealed that educated laypeople often conflated global climate change and stratospheric ozone depletion, and appeared relatively unaware of the role of anthropogenic carbon dioxide emissions in global warming. This study compares those survey results with 2009 data from a sample of similarly well-educated laypeople responding to the same survey instrument. Not surprisingly, following a decade of explosive attention to climate change in politics and in the mainstream media, survey respondents in 2009 showed higher awareness and comprehension of some climate change causes. Most notably, unlike those in 1992, 2009 respondents rarely mentioned ozone depletion as a cause of global warming. They were also far more likely to correctly volunteer energy use as a major cause of climate change; many in 2009 also cited natural processes and historical climatic cycles as key causes. When asked how to address the problem of climate change, while respondents in 1992 were unable to differentiate between general "good environmental practices" and actions specific to addressing climate change, respondents in 2009 have begun to appreciate the differences. Despite this, many individuals in 2009 still had incorrect beliefs about climate change, and still did not appear to fully appreciate key facts such as that global warming is primarily due to increased concentrations of carbon dioxide in the atmosphere, and the single most important source of this carbon dioxide is the combustion of fossil fuels.

Credible Threat: Perceptions of Pandemic Coronavirus, Climate Change and the Morality and Management of Global Risks.

Prior research suggests that the pandemic coronavirus pushes all the "hot spots" for risk perceptions, yet both governments and populations have varied in their responses. As the economic impacts of the pandemic have become salient, governments have begun to slash their budgets for mitigating other global risks, including climate change, likely imposing increased future costs from those risks. Risk analysts have long argued that global environmental and health risks are inseparable at some level, and must ultimately be managed systemically, to effectively increase safety and welfare. In contrast, it has been suggested that we have worry budgets, in which one risk crowds out another. "In the wild," our problem-solving strategies are often lexicographic; we seek and assess potential solutions one at a time, even one attribute at a time, rather than conducting integrated risk assessments. In a U.S. national survey experiment in which participants were randomly assigned to coronavirus or climate change surveys (N = 3203) we assess risk perceptions, and whether risk perception "hot spots" are driving policy preferences, within and across these global risks. Striking parallels emerge between the two. Both risks are perceived as highly threatening, inequitably distributed, and not particularly controllable. People see themselves as somewhat informed about both risks and have moral concerns about both. In contrast, climate change is seen as better understood by science than is pandemic coronavirus. Further, individuals think they can contribute more to slowing or stopping pandemic coronavirus than climate change, and have a greater moral responsibility to do so. Survey assignment influences policy preferences, with higher support for policies to control pandemic coronavirus in pandemic coronavirus surveys, and higher support for policies to control climate change risks in climate change surveys. Across all surveys, age groups, and policies to control either climate change or pandemic coronavirus risks, support is highest for funding research on vaccines against pandemic diseases, which is the only policy that achieves majority support in both surveys. Findings bolster both the finite worry budget hypothesis and the hypothesis that supporters of policies to confront one threat are disproportionately likely also to support policies to confront the other threat.

Visualizing seismic risk and uncertainty: a review of related research.

Government agencies and other authorities often communicate earthquake risks using maps derived from geographic information systems. Yet, little is known about the effects of these maps on risk perceptions. While mental models research and other approaches are available to inform risk communication text design, similar empirically derived guidance is lacking for visual risk communications, such as maps, which are likely to trump text in their impact and appeal. This paper reviews the empirical research that might inform such guidance. Research on graphs, spatial and visual perception, and map design suggests that graphics increase risk avoidance over numerical risk representations, and countable visuals, like dots, can increase the accuracy of perceived risks, but not always. Cartographic design features, such as color, animation, interactivity, and depth cues, are all candidates to represent risk and uncertainty and to influence risk perception. While there are robust known effects of color (e.g., red = danger), with some cultural variability, animation can increase the salience of otherwise obscure features but is not uniformly effective. Depth cues, dimensionality, and the extent to which a representation depicts versus symbolizes a scene will influence the viewer's perspective and perception, depending on the viewer's familiarity with the scene; their effects on risk perception remain unclear. The translation and representation of technical information about risk and uncertainty is critical to risk communication effectiveness. Our review suggests a handful of candidate criteria for evaluating the effects of risk visualizations, short of changes in behavior: accuracy, accessibility, retention, and perceived risk and usefulness.

Eyeing the storm: How residents of coastal Florida see hurricane forecasts and warnings.

This paper examines the societal dimensions of warning decisions during extreme weather events in one of the most hurricane-prone areas in the U.S., Miami-Dade County, Florida. With the aim of informing improvements in the hurricane forecast and warning system, and better understanding warning decisions in extreme weather events, we explore how members of the public obtain and use hurricane forecasts and warnings in decision making. Results from in depth mental models interviews with members of the public (N=28) and survey data from three counties in Florida (N=460) show that a large majority of respondents have some hurricane experience, which influences their thinking about storm impacts, individual actions to mitigate the hazard, and vulnerability to the hazard. Comparison with results from previous research with warning system professionals (National Weather Service forecasters, media broadcasters, and public officials) indicates several gaps between professionals and laypeople including different perceptions of hurricane risks overall and related to flooding from storm surge. The findings suggest several areas for improvements in the hurricane forecast and warning system.