Human social sensing is an untapped resource for computational social science.

The ability to 'sense' the social environment and thereby to understand the thoughts and actions of others allows humans to fit into their social worlds, communicate and cooperate, and learn from others' experiences. Here we argue that, through the lens of computational social science, this ability can be used to advance research into human sociality. When strategically selected to represent a specific population of interest, human social sensors can help to describe and predict societal trends. In addition, their reports of how they experience their social worlds can help to build models of social dynamics that are constrained by the empirical reality of human social systems.

Food and Nutrition Insecurity: Experiences That Differ for Some and Independently Predict Diet-Related Disease, Los Angeles County, 2022.

BACKGROUND: National surveillance shows that food insecurity affects ≥1 in 10 Americans each year. Recently, experts have advocated for surveillance of nutrition and food insecurity. Nutrition security refers to the nutritional adequacy of accessible food and factors that impact one's ability to meet food preferences. OBJECTIVES: This study presents representative estimates of food insecurity and nutrition insecurity for Los Angeles County, CA, United States; compares predictors of these constructs; and examines whether they independently predict diet-related health outcomes. METHODS: In December 2022, a representative sample of Los Angeles County adults participating in the Understanding America Study (N = 1071) was surveyed about household food insecurity and nutrition insecurity over the past 12 mo. Data were analyzed in 2023. RESULTS: Reported rates were similar for food insecurity (24%) and nutrition insecurity (25%), but the overlap of these subgroups was <60%. Logistic regression models indicated that non-Hispanic Asian individuals had higher odds of nutrition insecurity but not food insecurity. Moreover, nutrition insecurity was a stronger predictor of diabetes compared with food insecurity, and both constructs independently predicted poor mental health. CONCLUSIONS: Food and nutrition insecurity affect somewhat different populations. Both constructs are valuable predictors of diet-related health outcomes. Monitoring nutrition insecurity in addition to food insecurity can provide new information about populations with barriers to healthy diets.

Socio-ecological factors linked with changes in adults' dietary intake in Los Angeles County during the peak of the coronavirus 2019 pandemic.

OBJECTIVE: Comprehensive studies examining longitudinal predictors of dietary change during the coronavirus disease 2019 pandemic are lacking. Based on an ecological framework, this study used longitudinal data to test if individual, social and environmental factors predicted change in dietary intake during the peak of the coronavirus 2019 pandemic in Los Angeles County and examined interactions among the multilevel predictors. DESIGN: We analysed two survey waves (e.g. baseline and follow-up) of the Understanding America Study, administered online to the same participants 3 months apart. The surveys assessed dietary intake and individual, social, and neighbourhood factors potentially associated with diet. Lagged multilevel regression models were used to predict change from baseline to follow-up in daily servings of fruits, vegetables and sugar-sweetened beverages. SETTING: Data were collected in October 2020 and January 2021, during the peak of the coronavirus disease 2019 pandemic in Los Angeles County. PARTICIPANTS: 903 adults representative of Los Angeles County households. RESULTS: Individuals who had depression and less education or who identified as non-Hispanic Black or Hispanic reported unhealthy dietary changes over the study period. Individuals with smaller social networks, especially low-income individuals with smaller networks, also reported unhealthy dietary changes. After accounting for individual and social factors, neighbourhood factors were generally not associated with dietary change. CONCLUSIONS: Given poor diets are a leading cause of death in the USA, addressing ecological risk factors that put some segments of the community at risk for unhealthy dietary changes during a crisis should be a priority for health interventions and policy.

Understanding food insecurity in Los Angeles County during the COVID-19 pandemic and its aftermath: A qualitative interview study.

The COVID-19 pandemic brought increases in food insecurity in Los Angeles (L.A.) County, defined as lacking household access to adequate food because of limited money or other resources. Here, we aimed to understand the lived experiences of food insecurity during the COVID-19 pandemic and its aftermath. In August-December 2022, we interviewed 30 residents of L.A. County who were participants in an ongoing internet panel and had reported experiencing food insecurity between April 2020 and July 2021. A stratified-sampling approach was used to recruit a diverse sample with and without government food assistance. We report five key findings, which underscore the stress and worry associated with the experience of food insecurity, and the coping strategies people implemented: (1) The pandemic prompted food insecurity as well as stressful shifts in eating behaviors compared to before the pandemic, with some eating much less food, some eating less nutritious food, and some eating much more due to being stuck at home; (2) Buying food became more effortful and financially challenging; (3) Government food assistance from the Supplemental Nutrition Assistance Program (SNAP) was important for reducing food insecurity, but was sometimes insufficient, inconsistent, and didn't cover all retailers or food items; (4) Interviewees had to rely on their social networks, food banks or pantries, churches, and schools to meet their food needs and cope with food insecurity, but some faced barriers in doing so; (5) For some, food insecurity was worse in late 2022, almost two years after the pandemic started. We conclude with implications for policymakers and practitioners, emphasizing the importance of meeting the needs of diverse residents and addressing food insecurity in the aftermath of the COVID-19 pandemic.

Public Concern about Water Safety, Weather, and Climate: Insights from the World Risk Poll.

Water safety refers to the quality of one's drinking water and whether it lacks dangerous contaminants. Limited access to safe water is projected to impact approximately 5 billion people worldwide by 2050. Climate change and worsening severe weather events pose increasing threats to global water safety. However, people may not perceive links between climate change and water safety, potentially undermining their willingness to implement behaviors that improve water safety. Existing studies on water safety risk perceptions have mostly been conducted in single-country contexts, which limits researchers' ability to make cross-national comparisons. Here, we assessed the extent to which people's severe weather concern and climate change concern predict their water safety concern. Our analyses used survey data from the 142-country 2019 Lloyd's Register Foundation World Risk Poll, including 21 low-income and 34 lower-middle-income countries. In mixed-effects models, severe weather concern was significantly more predictive of water safety concern than was climate change concern, although both resulted in positive associations. Worldwide, this finding was robust, insensitive to key model specifications and countries' varying protection against unsafe drinking water. We suggest communicators and policymakers improve messaging about water safety and other environmental threats by explaining how they are impacted by worsening severe weather.

Ecological risk and protective factors for food insufficiency in Los Angeles County during the COVID-19 pandemic.

OBJECTIVE: The COVID-19 pandemic increased food insufficiency: a severe form of food insecurity. Drawing on an ecological framework, we aimed to understand factors that contributed to changes in food insufficiency from April to December 2020, in a large urban population hard hit by the pandemic. DESIGN: We conducted internet surveys every 2 weeks in April-December 2020, including a subset of items from the Food Insecurity Experience Scale. Longitudinal analysis identified predictors of food insufficiency, using fixed effects models. SETTING: Los Angeles County, which has a diverse population of 10 million residents. PARTICIPANTS: A representative sample of 1535 adults in Los Angeles County who are participants in the Understanding Coronavirus in America tracking survey. RESULTS: Rates of food insufficiency spiked in the first year of the pandemic, especially among participants living in poverty, in middle adulthood and with larger households. Government food assistance from the Supplemental Nutrition Assistance Program was significantly associated with reduced food insufficiency over time, while other forms of assistance such as help from family and friends or stimulus funds were not. CONCLUSIONS: The findings highlight that during a crisis, there is value in rapidly monitoring food insufficiency and investing in government food benefits.

Reflections on an interdisciplinary collaboration to inform public understanding of climate change, mitigation, and impacts.

We describe two interdisciplinary projects in which natural scientists and engineers, as well as psychologists and other behavioral scientists, worked together to better communicate about climate change, including mitigation and impacts. One project focused on understanding and informing public perceptions of an emerging technology to capture and sequester carbon dioxide from coal-fired power plants, as well as other low-carbon electricity-generation technologies. A second project focused on public understanding about carbon dioxide's residence time in the atmosphere. In both projects, we applied the mental-models approach, which aims to design effective communications by using insights from interdisciplinary teams of experts and mental models elicited from intended audience members. In addition to summarizing our findings, we discuss the process of interdisciplinary collaboration that we pursued in framing and completing both projects. We conclude by describing what we think we have learned about the conditions that supported our ongoing interdisciplinary collaborations.

Private Well Testing in Peri-Urban African-American Communities Lacking Access to Regulated Municipal Drinking Water: A Mental Models Approach to Risk Communication.

Majority African-American neighborhoods on the edges of North Carolina municipalities are less likely than white peri-urban neighborhoods to be served by a community system regulated under the Safe Drinking Water Act. These households rely on unregulated private wells, which are at much higher risk of contamination than neighboring community water supplies. Yet, risk awareness of consuming well water is low, and no prior research has tested risk communication interventions for these communities. We present a randomized-controlled trial of an oversized postcard to promote water testing among this audience. The postcard design followed the mental models approach to risk communication. To our knowledge, this is the first U.S. randomized-controlled trial of a mailed communication to promote water testing in any audience and one of few trials of the mental models approach. We evaluated the postcard's effects on self-reported water testing with and without a free water test offer (vs. no-intervention control) via a survey mailed one month after the interventions. The combined communication and free test doubled the odds of self-reported water testing, compared to the control group (p = 0.046). It increased the odds of testing by 65%, compared to the free test alone. Recall of receiving a postcard about water testing increased the odds of self-reported testing twelve-fold (p < 0.001). Although these results suggest that targeted risk information delivered by mail can promote water testing when paired with a free test, the mechanism remains unclear. Additional research on beliefs influencing perceptions about well water may yield interventions that are even more effective.

Self-reported dietary changes among Los Angeles County adults during the COVID-19 pandemic.

Poor diets are historically the leading cause of morbidity and mortality in the United States (U.S.), causing over 44,000 deaths each month. Dietary patterns have likely changed during the COVID-19 pandemic due to major shifts and crises in social, economic, and food systems. This study examines self-reported dietary changes in Los Angeles (L.A.) County during COVID-19, and identifies factors associated with making healthy and unhealthy changes. Data are from the Understanding Coronavirus in America Study, an internet panel of adults representative of L.A. County households (N = 1080). Multinomial logistic regression was used to test if self-reported change in diet healthiness assessed in July 2020 was associated with socio-ecological factors known to be associated with diet, assessed between April-July 2020. More than half of L.A. County residents reported making changes to their diet: 28.3% reported eating healthier food since the beginning of the pandemic, while 24.8% reported eating less healthy food. Individuals who were significantly more likely to report healthy changes were Non-Hispanic Black or Hispanic/Latino (vs. Non-Hispanic White), had received unemployment insurance, or had larger social networks. Individuals who were significantly more likely to report unhealthy changes were younger, of mixed race, had children in their household, had transportation barriers, or had obesity. Individuals who were significantly more likely to report both healthy and unhealthy changes were Asian, had experienced food insecurity, or had challenges getting food due to store closures. The pandemic may be exacerbating diet-related disease risk in some groups, such as communities of color, and among individuals with obesity and those facing transportation barriers.

Eliciting probabilistic expectations: Collaborations between psychologists and economists.

We describe two collaborations in which psychologists and economists provided essential support on foundational projects in major research programs. One project involved eliciting adolescents' expectations regarding significant future life events affecting their psychological and economic development. The second project involved eliciting consumers' expectations regarding inflation, a potentially vital input to their investment, saving, and purchasing decisions. In each project, we sought questions with the precision needed for economic modeling and the simplicity needed for lay respondents. We identify four conditions that, we believe, promoted our ability to sustain these transdisciplinary collaborations and coproduce the research: (i) having a shared research goal, which neither discipline could achieve on its own; (ii) finding common ground in shared methodology, which met each discipline's essential evidentiary conditions, but without insisting on its culturally acquired tastes; (iii) sharing the effort throughout, with common language and sense of ownership; and (iv) gaining mutual benefit from both the research process and its products.

Probability Size Matters: The Effect of Foreground-Only versus Foreground+Background Graphs on Risk Aversion Diminishes with Larger Probabilities.

Graphs are increasingly recommended for improving decision-making and promoting risk-avoidant behaviors. Graphs that depict only the number of people affected by a risk ("foreground-only" displays) tend to increase perceived risk and risk aversion (e.g., willingness to get vaccinated), as compared to graphs that also depict the number of people at risk for harm ("foreground+background" displays). However, previous research examining these "foreground-only effects" has focused on relatively low-probability risks (<10%), limiting generalizability to communications about larger risks. In two experiments, we systematically investigated the moderating role of probability size on foreground-only effects, using a wide range of probability sizes (from 0.1% to 40%). Additionally, we examined the moderating role of the size of the risk reduction, that is, the extent to which a protective behavior reduces the risk. Across both experiments, foreground-only effects on perceived risk and risk aversion were weaker for larger probabilities. Experiment 2 also revealed that foreground-only effects were weaker for smaller risk reductions, while foreground-only displays decreased understanding of absolute risk magnitudes independently of probability size. These findings suggest that the greater effectiveness of foreground-only versus foreground+background displays for increasing perceived risk and risk aversion diminishes with larger probability sizes and smaller risk reductions. Moreover, if the goal is to promote understanding of absolute risk magnitudes, foreground+background displays should be used rather than foreground-only displays regardless of probability size. Our findings also help to refine and extend existing theoretical accounts of foreground-only effects to situations involving a wide range of probability sizes.

Measuring Subjective Probabilities: The Effect of Response Mode on the Use of Focal Responses, Validity, and Respondents' Evaluations.

Subjective probabilities are central to risk assessment, decision making, and risk communication efforts. Surveys measuring probability judgments have traditionally used open-ended response modes, asking participants to generate a response between 0% and 100%. A typical finding is the seemingly excessive use of 50%, perhaps as an expression of "I don't know." In an online survey with a nationally representative sample of the Dutch population, we examined the effect of response modes on the use of 50% and other focal responses, predictive validity, and respondents' survey evaluations. Respondents assessed the probability of dying, getting the flu, and experiencing other health-related events. They were randomly assigned to a traditional open-ended response mode, a visual linear scale ranging from 0% to 100%, or a version of that visual linear scale on which a magnifier emerged after clicking on it. We found that, compared to the open-ended response mode, the visual linear and magnifier scale each reduced the use of 50%, 0%, and 100% responses, especially among respondents with low numeracy. Responses given with each response mode were valid, in terms of significant correlations with health behavior and outcomes. Where differences emerged, the visual scales seemed to have slightly better validity than the open-ended response mode. Both high-numerate and low-numerate respondents' evaluations of the surveys were highest for the visual linear scale. Our results have implications for subjective probability elicitation and survey design.

Designing Graphs that Promote Both Risk Understanding and Behavior Change.

Graphs show promise for improving communications about different types of risks, including health risks, financial risks, and climate risks. However, graph designs that are effective at meeting one important risk communication goal (promoting risk-avoidant behaviors) can at the same time compromise another key goal (improving risk understanding). We developed and tested simple bar graphs aimed at accomplishing these two goals simultaneously. We manipulated two design features in graphs, namely, whether graphs depicted the number of people affected by a risk and those at risk of harm ("foreground+background") versus only those affected ("foreground-only"), and the presence versus absence of simple numerical labels above bars. Foreground-only displays were associated with larger risk perceptions and risk-avoidant behavior (i.e., willingness to take a drug for heart attack prevention) than foreground+background displays, regardless of the presence of labels. Foreground-only graphs also hindered risk understanding when labels were not present. However, the presence of labels significantly improved understanding, eliminating the detrimental effect of foreground-only displays. Labels also led to more positive user evaluations of the graphs, but did not affect risk-avoidant behavior. Using process modeling we identified mediators (risk perceptions, understanding, user evaluations) that explained the effect of display type on risk-avoidant behavior. Our findings contribute new evidence to the graph design literature: unlike what was previously feared, we demonstrate that it is possible to design foreground-only graphs that promote intentions for behavior change without a detrimental effect on risk understanding. Implications for the design of graphical risk communications and decision support are discussed.

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.

Designing Graphs to Communicate Risks: Understanding How the Choice of Graphical Format Influences Decision Making.

Previous research suggests that the choice of graphical format for communicating risk information affects both understanding of the risk magnitude and the likelihood of acting to decrease risk. However, the mechanisms through which these effects work are poorly understood. To explore these mechanisms using a real-world scenario, we examined the relative impact of two graphical displays for depicting the risk of exposure to unexploded ammunition during potential land redevelopment. One display depicted only the foreground information graphically (a bar graph of the number of people harmed), and a second depicted the foreground and background graphically (a stacked bar graph representing both the number harmed and at risk). We presented 296 participants with either the foreground-only or the foreground and background graphical display and measured a broad set of outcome variables, examining (1) the graphical display effect on each of the outcome measures and (2) the pathways by which any display effects work to influence decision making. We found that the foreground-only graphical display increased perceived likelihood and experienced fear, which produced greater worry, which in turn increased risk aversion. In addition, a positive evaluation of the communication materials increased support for policies related to land redevelopment, whether those policies were risk taking or risk mitigating. Finally, the foreground-only graphical display decreased understanding of the risk magnitude, showing that approaches to accomplish one risk communication goal (promoting risk-averse decisions) may do so at the expense of another goal (increasing understanding).

Informing Public Perceptions About Climate Change: A 'Mental Models' Approach.

As the specter of climate change looms on the horizon, people will face complex decisions about whether to support climate change policies and how to cope with climate change impacts on their lives. Without some grasp of the relevant science, they may find it hard to make informed decisions. Climate experts therefore face the ethical need to effectively communicate to non-expert audiences. Unfortunately, climate experts may inadvertently violate the maxims of effective communication, which require sharing communications that are truthful, brief, relevant, clear, and tested for effectiveness. Here, we discuss the 'mental models' approach towards developing communications, which aims to help experts to meet the maxims of effective communications, and to better inform the judgments and decisions of non-expert audiences.

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.

Informed public choices for low-carbon electricity portfolios using a computer decision tool.

Reducing CO2 emissions from the electricity sector will likely require policies that encourage the widespread deployment of a diverse mix of low-carbon electricity generation technologies. Public discourse informs such policies. To make informed decisions and to productively engage in public discourse, citizens need to understand the trade-offs between electricity technologies proposed for widespread deployment. Building on previous paper-and-pencil studies, we developed a computer tool that aimed to help nonexperts make informed decisions about the challenges faced in achieving a low-carbon energy future. We report on an initial usability study of this interactive computer tool. After providing participants with comparative and balanced information about 10 electricity technologies, we asked them to design a low-carbon electricity portfolio. Participants used the interactive computer tool, which constrained portfolio designs to be realistic and yield low CO2 emissions. As they changed their portfolios, the tool updated information about projected CO2 emissions, electricity costs, and specific environmental impacts. As in the previous paper-and-pencil studies, most participants designed diverse portfolios that included energy efficiency, nuclear, coal with carbon capture and sequestration, natural gas, and wind. Our results suggest that participants understood the tool and used it consistently. The tool may be downloaded from http://cedmcenter.org/tools-for-cedm/informing-the-public-about-low-carbon-technologies/ .

Climate change beliefs and perceptions of weather-related changes in the United Kingdom.

Public perception research in different countries has suggested that real and perceived periods of high temperature strengthen people's climate change beliefs. Such findings raise questions about the climate change beliefs of people in regions with moderate climates. Relatively little is known about whether public concerns about climate change may also be associated with perceived changes in other weather-related events, such as precipitation or flooding. We examine the relationship between perceived changes in weather-related events and climate change beliefs among U.K. residents at a time of below-average winter temperatures and recent flooding. National survey data (n = 1,848) revealed that heat waves and hot summers were perceived to have become less common during respondents' lifetimes, while flooding, periods of heavy rainfall, coastal erosions, and mild winters were perceived to have increased in frequency and cold winters were perceived to be unchanged. Although perceived changes in hot-weather-related events were positively associated with climate change beliefs, perceived changes in wet-weather-related events were found to be an even stronger predictor. Self-reported experience of "flooding in own area" and "heat-wave discomfort" also significantly contributed to climate change beliefs. These findings highlight the importance of salient weather-related events and experiences in the formation of beliefs about climate change. We link our findings to research in judgment and decision making, and propose that those wishing to engage with the public on the issue of climate change should not limit their focus to heat.

Younger Americans are less politically polarized than older Americans about climate policies (but not about other policy domains).

Political polarization of Americans' support for climate policies often impedes the adoption of new, urgently needed climate solutions. However, recent polls suggest that younger conservatives favor adopting pro-climate policies to a greater degree than older conservatives, resulting in less political polarization among younger Americans relative to older Americans. To better understand these patterns, we analyzed Americans' support for various climate policies from 1982-2020, across 16 waves of historical, nationally representative survey data from the American National Election Studies (total N = 29,467). Regression models consistently show that, since 2012, younger Americans have been less politically polarized than older Americans on support for climate policies. Before 2012 and on non-climate policy topics, we did not find consistent statistical evidence for political polarization varying with age. These findings can inform policy debates about climate change and offer hope to environmentalists and policymakers who seek to build broad consensus for climate action at the policy level.