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Abstract Background Wildfire smoke contributes substantially to the global disease burden and is a major cause of air pollution in the US states of Oregon and Washington. Climate change is expected to bring more wildfires to this region. Social media is a popular platform for health promotion and a need exists for effective communication about smoke risks and mitigation measures to educate citizens and safeguard public health. Methods Using a sample of 1,287 Tweets from 2022, we aimed to analyze temporal Tweeting patterns in relation to potential smoke exposure and evaluate and compare institutions’ use of social media communication best practices which include (i) encouraging adoption of smoke-protective actions; (ii) leveraging numeric, verbal, and Air Quality Index risk information; and (iii) promoting community-building. Tweets were characterized using keyword searches and the Linguistic Inquiry and Word Count (LIWC) software. Descriptive and inferential statistics were carried out. Results 44% of Tweets in our sample were authored between January-August 2022, prior to peak wildfire smoke levels, whereas 54% of Tweets were authored during the two-month peak in smoke (September-October). Institutional accounts used Twitter (or X) to encourage the adoption of smoke-related protective actions (82% of Tweets), more than they used it to disseminate wildfire smoke risk information (25%) or promote community-building (47%). Only 10% of Tweets discussed populations vulnerable to wildfire smoke health effects, and 14% mentioned smoke mitigation measures. Tweets from Washington-based accounts used significantly more verbal and numeric risk information to discuss wildfire smoke than Oregon-based accounts (p = 0.042 and p = 0.003, respectively); however, Tweets from Oregon-based accounts on average contained a higher percentage of words associated with community-building language (p

Rates of melanoma—the deadliest form of skin cancer—have increased. Early detection can save lives, and patients have a critical role to play in checking their skin. We aim to identify health communication messages that best educate the public and increase intentions toward skin checks. After viewing messages intended to increase melanoma knowledge, participants correctly identified a greater proportion (74.6 vs 70.4%) of moles (mean number = 17.9, 95% confidence interval [CI] = 17.5–18.3 vs 16.9, 95% CI = 16.6–17.3; P < .001, partial eta-squared = 0.03) and had knowledge of more melanoma warning signs (mean number = 5.8, 95% CI = 5.7–5.8 vs 5.6, 95% CI = 5.5–5.7, P = .01, partial eta-squared = 0.02). After viewing messages intended to increase self-confidence in checking their skin accurately, they were also more likely to report greater intentions to do a skin check on a scale of 1–5 (mean number = 3.8, 95% CI = 3.7–3.9 vs 3.6, 95% CI = 3.4–3.7, P = .005, partial eta-squared = 0.02). Online melanoma messages aimed at increasing both melanoma knowledge and skin-check confidence may be most effective in improving the accuracy of skin self-examinations and intentions to do them.

Driving evaluations aim to ensure adequate skills; however, feedback beyond pass/fail is needed for improvement. Therefore, the goal of this study was to inform driving feedback report design to ensure ease of use and understandability while motivating improvements. Participants ages 18–25 years (n = 521) were recruited from CloudResearch Prime Panels to rate one of nine report design conditions with various combinations of five key features: performance summary presence, action plan (AP) length, AP order, AP grading system, and peer comparison presence; they then completed questionnaires. Participants were more motivated to improve when a summary was present (p = 0.02); they rated reports easier to use if they had a long AP (p = 0.01), a short AP paired with a summary (p = 0.007), or an AP with a number grade (p = 0.016); and they rated reports easier to understand if they had a short AP (p = 0.002) or an AP ordered by worst-to-best performance (p = 0.05). These results suggest that feedback reports designed with a performance summary and short, targeted action plan starting with the biggest area for improvement are likely to motivate action to improve driving skills while being easy to use and understand. Future research should evaluate the effect of such a redesigned report on driving outcomes among young drivers.

Background . Wildfire smoke events are increasing in frequency and intensity due to climate change. Children are especially vulnerable to health effects even at moderate smoke levels. However, it is unclear how parents respond to Air Quality Indices (AQIs) frequently used by agencies to communicate air pollution health risks. Methods . In an experiment (3 × 2 × 2 factorial design), 2,100 parents were randomly assigned to view one of twelve adapted AQI infographics that varied by visual (table, line, gauge), index type (AQI [0-500], AQHI [1-11+]), and risk level (moderate, high). Participants were told to imagine encountering the infographic in a short-term exposure scenario. They reported worry about wildfire smoke, intentions to take risk-mitigating actions (e.g., air purifier use), and support for various exposure reduction policies. Subsequently, participants were told to imagine encountering the same infographic daily during a school week in a long-term exposure scenario and again reported worry, action intentions, and policy support. Results . Parents’ responses significantly differentiated between risk levels that both pose a threat to children’s health; worry and action intentions were much higher in the high-risk group than the moderate-risk group in both short-exposure (F = 748.68 p

Numeracy—the ability to understand and use numeric information—is linked to good decision-making. Several problems exist with current numeracy measures, however. Depending on the participant sample, some existing measures are too easy or too hard; also, established measures often contain items well-known to participants. The current article aimed to develop new numeric understanding measures (NUMs) including a 1-item (1-NUM), 4-item (4-NUM), and 4-item adaptive measure (A-NUM). In a calibration study, 2 participant samples (n = 226 and 264 from Amazon’s Mechanical Turk [MTurk]) each responded to half of 84 novel numeracy items. We calibrated items using 2-parameter logistic item response theory (IRT) models. Based on item parameters, we developed the 3 new numeracy measures. In a subsequent validation study, 600 MTurk participants completed the new numeracy measures, the adaptive Berlin Numeracy Test, and the Weller Rasch-Based Numeracy Test, in randomized order. To establish predictive and convergent validities, participants also completed judgment and decision tasks, Raven’s progressive matrices, a vocabulary test, and demographics. Confirmatory factor analyses suggested that the 1-NUM, 4-NUM, and A-NUM load onto the same factor as existing measures. The NUM scales also showed similar association patterns to subjective numeracy and cognitive ability measures as established measures. Finally, they effectively predicted classic numeracy effects. In fact, based on power analyses, the A-NUM and 4-NUM appeared to confer more power to detect effects than existing measures. Thus, using IRT, we developed 3 brief numeracy measures, using novel items and without sacrificing construct scope. The measures can be downloaded as Qualtrics files (https://osf.io/pcegz/).

Park and Brannon (2013, https://doi.org/10.1177/0956797613482944) found that practicing non-symbolic approximate arithmetic increased performance on an objective numeracy task, specifically symbolic arithmetic. Manipulating objective numeracy would be useful for many researchers, particularly those who wish to investigate causal effects of objective numeracy on performance. Objective numeracy has been linked to performance in multiple areas, such as judgment-and-decision-making (JDM) competence, but most existing studies are correlational. Here, we expanded upon Park and Brannon’s method to experimentally manipulate objective numeracy and we investigated whether numeracy’s link with JDM performance was causal. Experimental participants drawn from a diverse internet sample trained on approximate-arithmetic tasks whereas active control participants trained on a spatial working-memory task. Numeracy training followed a 2 × 2 design: Experimental participants quickly estimated the sum of OR difference between presented numeric stimuli, using symbolic numbers (i.e., Arabic numbers) OR non-symbolic numeric stimuli (i.e., dot arrays). We partially replicated Park and Brannon’s findings: The numeracy training improved objective-numeracy performance more than control training, but this improvement was evidenced by performance on the Objective Numeracy Scale, not the symbolic arithmetic task. Subsequently, we found that experimental participants also perceived risks more consistently than active control participants, and this risk-consistency benefit was mediated by objective numeracy. These results provide the first known experimental evidence of a causal link between objective numeracy and the consistency of risk judgments.

Objectives To identify what patient-related characteristics have been reported to be associated with the occurrence of shared decision-making (SDM) about treatment.Design Scoping review.Eligibility criteria Peer-reviewed articles in English or Dutch reporting on associations between patient-related characteristics and the occurrence of SDM for actual treatment decisions.Information sources COCHRANE Library, Embase, MEDLINE, PsycInfo, PubMed and Web of Science were systematically searched for articles published until 25 March 2019.Results The search yielded 5289 hits of which 53 were retained. Multiple categories of patient characteristics were identified: (1) sociodemographic characteristics (eg, gender), (2) general health and clinical characteristics (eg, symptom severity), (3) psychological characteristics and coping with illness (eg, self-efficacy) and (4) SDM style or preference. Many characteristics showed no association or unclear relationships with SDM occurrence. For example, for female gender positive, negative and, most frequently, non-significant associations were seen.Conclusions A large variety of patient-related characteristics have been studied, but for many the association with SDM occurrence remains unclear. The results will caution often-made assumptions about associations and provide an important step to target effective interventions to foster SDM with all patients.

Decision support techniques and online algorithms aim to help individuals predict costs and facilitate their choice of health insurance coverage. Self-reported health status (SHS), whereby patients rate their own health, could improve cost-prediction estimates without requiring individuals to share personal health information or know about undiagnosed conditions. We compared the predictive accuracy of several models: (1) SHS only, (2) a “basic” model adding health-related variables, and (3) a “full” model adding measures of healthcare access. The Medical Expenditure Panel Survey was used to predict 2015 health expenditures from 2014 data. Relative performance was assessed by comparing adjusted-R 2 values and by reporting the predictive accuracy of the models for a new cohort (2015–2016 data). In the SHS-only model, those with better SHS were less likely to incur expenditures. However, after accounting for health variables, those with better SHS were more likely to incur expenses. In the full model, SHS was no longer predictive of incurring expenses. Variables indicating better access to care were associated with higher likelihood of spending and higher spending. The full model ( R 2 = 0.290) performed slightly better than the basic model ( R 2 = 0.240), but neither performed well at the upper tail of the cost distribution. While our SHS-based models perform well in the aggregate, predicting population-level risk well, they are not sufficiently accurate to guide individuals’ insurance shopping decisions in all cases. Policies that rely heavily on health insurance consumers making individually optimal choices cannot assume that decision tools can accurately anticipate high costs.

Communities often unite during a crisis, though some cope by ascribing blame or stigmas to those who might be linked to distressing life events. In a preregistered two-wave survey, we evaluated the dehumanization of Asians and Asian Americans during the COVID-19 pandemic. Our first wave (March 26–April 2, 2020; N = 917) revealed dehumanization was prevalent, between 6.1% and 39% of our sample depending on measurement. Compared to non-dehumanizers, people who dehumanized also perceived the virus as less risky to human health and caused less severe consequences for infected people. They were more likely to be ideologically Conservative and believe in conspiracy theories about the virus. We largely replicated the results 1 month later in our second wave (May 6–May 13, 2020; N = 723). Together, many Americans dehumanize Asians and Asian Americans during the COVID-19 pandemic with related perceptions that the virus is less problematic. Implications and applications for dehumanization theory are discussed.

Although inequality in the US has increased since the 1960s, several studies show that Americans underestimate it. Reasons include overreliance on one's local perspective and ideologically-motivated cognition. We propose a novel mechanism to account for the misperceptions of income inequality. We hypothesize that compared to those who feel less autonomy, the people who believe they are autonomous and have control over their lives also believe that (1) income inequality is lower and (2) income inequality is more acceptable. Using a representative sample of 3,427 Americans, we find evidence to support these hypotheses.

Objective numeracy, the ability to understand and use mathematical concepts, has been related to superior decisions and life outcomes. Unknown is whether it relates to greater satisfaction in life. We investigated numeracy's relations with income satisfaction and overall life satisfaction in a diverse sample of 5,525 American adults. First, more numerate individuals had higher incomes; for every one point higher on the eight-item numeracy test, individuals reported $4,062 more in annual income, controlling for education and verbal intelligence. Combined, numeracy, education, and verbal intelligence explained 25% of the variance in income while Big-5 personality traits explained less than 4%. Further, the higher incomes associated with greater numeracy were related to more positive life evaluations (income and life satisfaction). Second, extant research also has indicated that the highly numerate compare numbers more than the less numerate. Consistent with numeracy-related income comparisons, numeracy moderated the relation between income and life evaluations, meaning that the same income was valued differently by those better and worse at math. Specifically, among those with lower incomes, the highly numerate were less satisfied than the less numerate; this effect reversed among those with higher incomes as if the highly numerate were aware of and made comparisons to others' incomes. Further, no clear income satiation point was seen among those highest in numeracy, and satiation among the least numerate appeared to occur at a point below $50,000. Third, both education and verbal intelligence related to income evaluations in similar ways, and numeracy's relations held when controlling for these other relations. Although causal claims cannot be made from cross-sectional data, these novel results indicate that numeracy may be an important factor underlying life evaluations and especially for evaluations concerning numbers such as incomes. Finally, this study adds to our understanding of education and intelligence effects in life satisfaction and happiness.

Background: Patient portals have emerged as an important tool through which patients can access online health information and engage in their health care. However, we know little about how patients perceive portals and whether patient perceptions might influence portal adoption. Objective: Apply the diffusion of innovation (DOI) theory to assess perceptions of adopters and non-adopters of a patient portal. Methods: We conducted a cross-sectional survey of adopters and non-adopters of the portal. Our survey consisted of perceived attributes from the DOI theory, socio-demographic characteristics and patient perceptions of technology adoption. Results: Three factors representing perceived attributes from DOI theory accounted for 73% of the variance in the data: Factor 1 – Relative Advantage (27%); Factor 2 – Ease of Use (24%) and Factor 3 – Trialability (22%). Adopters perceived greater Relative Advantage [mean (SD)] = 3.8 (0.71) versus 3.2 (0.89), p < 0.001, Ease of Use = 4.1 (0.71) versus 3.3 (0.95), p < 0.001 and Trialability = 4.0 (0.57) versus 3.4 (0.99), p < 0.001 than non-adopters. In multivariate modelling, age [OR = 3.75, 95% CI: (2.17, 6.46), p < 0.001] and income [OR = 1.87, 95% CI: (1.17, 3.00), p < 0.01] predicted adoption of the portal. Among DOI factors, Relative advantage predicted adoption of the portal [OR = 1.48, 95% CI: (1.03, 2.11), p < 0.05]. Conclusion: Patients will adopt a patient portal if they perceive it to offer a relative advantage over existing practices such as telephoning or visiting the doctor’s office. Organisations seeking to increase the adoption of patient portals should implement strategies to promote the relative advantage of portals as, for example, through posters in waiting and exam rooms. A digital divide in the adoption of patient portals may exist with respect to age and income.

As the primary healthcare providers for women, obstetrician-gynecologists' (OB/GYNs) experiences with and opinions about the Affordable Care Act (ACA) are important to understand. An online survey was sent to 1000 randomly selected OB/GYNs who were members of the American College of Obstetricians and Gynecologists (ACOG) in 2014. Of those, 523 opened the email and 163 responded (31% participation rate). Data were collected August 2014-October 2014 and analyzed in 2015–2016. Support for the ACA was widely distributed, with the largest subset of the sample (about 21%) in the “very supportive” category. Opinions of the ACA were more supportive than they were in a previous study conducted in 2011. When given a list of possible positive and negative impacts of the ACA on their practice, roughly 1 in 5 reported that the ACA increased work-related stress (28%), decreased total profits (22%), and lowered career satisfaction (22%), whereas 8.6% reported that the ACA increased quality of care. Around half of the providers thought that their newly insured patients would have the same level of education (42%) and numeric ability (55%) as their current patients. Almost all respondents (87%) indicated that it is at least slightly important for patients to understand their numeric likelihood of risk (such as numeric risk information from medications, treatments, and other procedures you might prescribe) —31% think it is extremely important and 44% think it is moderately important.

Objective. Numerous electronic tools help consumers select health insurance plans based on their estimated health care utilization. However, the best way to personalize these tools is unknown. The purpose of this study was to compare two common methods of personalizing health insurance plan displays: 1) quantitative healthcare utilization predictions using nationally representative Medical Expenditure Panel Survey (MEPS) data and 2) subjective-health status predictions. We also explored their relations to self-reported health care utilization. Methods. Secondary data analysis was conducted with responses from 327 adults under age 65 considering health insurance enrollment in the Affordable Care Act (ACA) marketplace. Participants were asked to report their subjective health, health conditions, and demographic information. MEPS data were used to estimate predicted annual expenditures based on age, gender, and reported health conditions. Self-reported health care utilization was obtained for 120 participants at a 1-year follow-up. Results. MEPS-based predictions and subjective-health status were related ( P < 0.0001). However, MEPS-predicted ranges within subjective-health categories were large. Subjective health was a less reliable predictor of expenses among older adults (age × subjective health, P = 0.04). Neither significantly related to subsequent self-reported health care utilization ( P = 0.18, P = 0.92, respectively). Conclusions. Because MEPS data are nationally representative, they may approximate utilization better than subjective health, particularly among older adults. However, approximating health care utilization is difficult, especially among newly insured. Findings have implications for health insurance decision support tools that personalize plan displays based on cost estimates.

Background: Despite recently expanded access to health insurance, consumers still face barriers to using their coverage to obtain needed health care. Objective: To examine the characteristics of those who delay or avoid health care due to costs. Methods: Participants were recruited via Amazon MTurk and completed a survey assessing demographic characteristics, financial toxicity, health care minimizer-maximizer tendencies, health insurance knowledge, numeracy, delaying/avoiding any care, and delaying/avoiding six common health care services (three preventive and three nonpreventive services). Validated measures were used when available. Delay/avoidance behaviors were categorized into delaying/avoiding any care, preventive care, and nonpreventive care. Logistic regression models examined 1) financial toxicity, 2) minimizer-maximizer tendencies, 3) numeracy, 4) health insurance knowledge, and 5) knowledge of preventive care coverage separately on three forms of delay/avoidance behaviors, controlling for chronic conditions, insurance status, and/or income where appropriate. Results: Of 518 respondents, 470 did not fail attention-check questions and were used in analyses. Forty-five percent of respondents reported delaying/avoiding care due to cost. Multivariable analyses found that financial toxicity was related to delaying/avoiding any care (odds ratio [OR] = 0.884, P < 0.001), preventive care (OR = 0.906, P < 0.001), and nonpreventive care (OR = 0.901, P < 0.001). A tendency to minimize seeking health care (OR = 0.734, P < 0.001) and lower subjective numeracy (OR = 0.794, P = 0.023) were related to delaying/avoiding any care. General health insurance knowledge (OR = 0.989, P = 0.023) and knowledge of preventive care coverage (OR = 0.422, P < 0.001) were related to delaying/avoiding preventive care. Conclusions: Many people delay or avoid health care due to costs, even when insured. Results suggest that there may be different reasons individuals delay or avoid preventive and nonpreventive care. Findings may inform interventions to educate consumers and support discussions about health care costs to facilitate appropriate health care utilization.

Greater numeracy has been correlated with better health and financial outcomes in past studies, but causal effects in adults are unknown. In a 9-week longitudinal study, undergraduate students, all taking a psychology statistics course, were randomly assigned to a control condition or a values-affirmation manipulation intended to improve numeracy. By the final week in the course, the numeracy intervention (statistics-course enrollment combined with values affirmation) enhanced objective numeracy, subjective numeracy, and two decision-related outcomes (financial literacy and health-related behaviors). It also showed positive indirect-only effects on financial outcomes and a series of STEM-related outcomes (course grades, intentions to take more math-intensive courses, later math-intensive courses taken based on academic transcripts). All decision and STEM-related outcome effects were mediated by the changes in objective and/or subjective numeracy and demonstrated similar and robust enhancements. Improvements to abstract numeric reasoning can improve everyday outcomes.

Introduction: Since the Affordable Care Act was passed, more than 12 million individuals have enrolled in the health insurance marketplace. Without support, many struggle to make an informed plan choice that meets their health and financial needs. Methods: We designed and evaluated a decision aid, Show Me My Health Plans (SMHP), that provides education, preference assessment, and an annual out-of-pocket cost calculator with plan recommendations produced by a tailored, risk-adjusted algorithm incorporating age, gender, and health status. We evaluated whether SMHP compared to HealthCare.gov improved health insurance decision quality and the match between plan choice, needs, and preferences among 328 Missourians enrolling in the marketplace. Results: Participants who used SMHP had higher health insurance knowledge (LS-Mean = 78 vs. 62; P < 0.001), decision self-efficacy (LS-Mean = 83 vs. 75; P < 0.002), confidence in their choice (LS-Mean = 3.5 vs. 2.9; P < 0.001), and improved health insurance literacy (odds ratio = 2.52, P < 0.001) compared to participants using HealthCare.gov . Those using SMHP were 10.3 times more likely to select a silver- or gold-tier plan (P < 0.0001). Discussion: SMHP can improve health insurance decision quality and the odds that consumers select an insurance plan with coverage likely needed to meet their health needs. This study represents a unique context through which to apply principles of decision support to improve health insurance choices.

Donation requests often convey numerical information about the people in need. In two studies we investigated the effects of numeracy and presentation format on the underlying affective and cognitive mechanisms of donation decisions. In Study 1, participants were presented with information about a victim in need, either in a frequency format or in a percentage format. In Study 2, we manipulated the identifiability and number of target victims. Our results demonstrate that donations of individuals lower in numeracy were more susceptible to changes in numeric presentation format than those higher in numeracy. Importantly, the underlying mechanisms for donations differed by numeracy. Whereas the mental image of the victim influenced donation decisions of less numerate people only, the estimated impact of a donation was positively correlated with donation amounts for both more and less numerate individuals.

Measuring reaction times to number comparisons is thought to reveal a processing stage in elementary numerical cognition linked to internal, imprecise representations of number magnitudes. These intuitive representations of the mental number line have been demonstrated across species and human development but have been little explored in decision making. This paper develops and tests hypotheses about the influence of such evolutionarily ancient, intuitive numbers on human decisions. We demonstrate that individuals with more precise mental-number-line representations are higher in numeracy (number skills) consistent with previous research with children. Individuals with more precise representations (compared to those with less precise representations) also were more likely to choose larger, later amounts over smaller, immediate amounts, particularly with a larger proportional difference between the two monetary outcomes. In addition, they were more likely to choose an option with a larger proportional but smaller absolute difference compared to those with less precise representations. These results are consistent with intuitive number representations underlying: a) perceived differences between numbers, b) the extent to which proportional differences are weighed in decisions, and, ultimately, c) the valuation of decision options. Human decision processes involving numbers important to health and financial matters may be rooted in elementary, biological processes shared with other species.

Using five variants of the Asian Disease Problem, we dissected the risky-choice framing effect by requiring each participant to provide preference ratings for the full decision problem and also to provide attractiveness ratings for each of the component parts, i.e., the sure-thing option and the risky option. Consistent with previous research, more risky choices were made by respondents receiving negatively framed versions of the decision problems than by those receiving positively framed versions. However, different processes were evident for those scoring high and low on numeracy. Whereas the choices of the less numerate showed a large effect of frame above and beyond any influence of their evaluations of the separate options, the choices of the highly numerate were almost completely accounted for by their attractiveness ratings of the separate options. These results are consistent with an increased tendency of the highly numerate to integrate complex numeric information in the construction of their preferences and a tendency for the less numerate to respond more superficially to non-numeric sources of information.

Environmental events such as natural disasters may influence the public's affective reactions and decisions. Shortly after the 2004 Tsunami disaster we assessed how affect elicited by thinking about this disaster influenced risk perceptions and future time perspective in Swedish undergraduates not directly affected by the disaster. An experimental manipulation was used to increase the salience of affect associated with the disaster. In Study 1 we found that participants reminded about the tsunami had a sense that their life was more finite and included fewer opportunities than participants in the control condition (not reminded about the tsunami). In Study 2 we found similar effects for risk perceptions. In addition, we showed that manipulations of ease-of-thought influenced the extent to which affect influenced these risk perceptions, with greater ease of thoughts being associated with greater perceived risks.

Researchers in the decision making tradition usually analyze multiple decisions within experiments by aggregating choices across individuals and using the individual subject as the unit of analysis. This approach can mask important variations and patterns within the data. Specifically, it ignores variations in decisions across a task or game and possible influences of characteristics of the subject or the experiment on these variations. We demonstrate, by reanalyzing data from two previously published articles, how a mixed model analysis addresses these limitations. Our results, with a modified Iowa gambling task and a prisoner's dilemma game, illustrate the ways in which such an analysis can test hypotheses not possible with other techniques, is more parsimonious, and is more likely to be faithful to theoretical models.

Human-caused climate change is happening; nearly all climate scientists are convinced of this basic fact according to surveys of experts and reviews of the peer-reviewed literature. Yet, among the American public, there is widespread misunderstanding of this scientific consensus. In this paper, we report results from two experiments, conducted with national samples of American adults, that tested messages designed to convey the high level of agreement in the climate science community about human-caused climate change. The first experiment tested hypotheses about providing numeric versus non-numeric assertions concerning the level of scientific agreement. We found that numeric statements resulted in higher estimates of the scientific agreement. The second experiment tested the effect of eliciting respondents' estimates of scientific agreement prior to presenting them with a statement about the level of scientific agreement. Participants who estimated the level of agreement prior to being shown the corrective statement gave higher estimates of the scientific consensus than respondents who were not asked to estimate in advance, indicating that incorporating an "estimation and reveal" technique into public communication about scientific consensus may be effective. The interaction of messages with political ideology was also tested, and demonstrated that messages were approximately equally effective among liberals and conservatives. Implications for theory and practice are discussed.

OBJECTIVE:Observational research suggests that placing graphic images on cigarette warning labels can reduce smoking rates, but field studies lack experimental control. Our primary objective was to determine the psychological processes set in motion by naturalistic exposure to graphic vs. text-only warnings in a randomized clinical trial involving exposure to modified cigarette packs over a 4-week period. Theories of graphic-warning impact were tested by examining affect toward smoking, credibility of warning information, risk perceptions, quit intentions, warning label memory, and smoking risk knowledge. METHODS:Adults who smoked between 5 and 40 cigarettes daily (N = 293; mean age = 33.7), did not have a contra-indicated medical condition, and did not intend to quit were recruited from Philadelphia, PA and Columbus, OH. Smokers were randomly assigned to receive their own brand of cigarettes for four weeks in one of three warning conditions: text only, graphic images plus text, or graphic images with elaborated text. RESULTS:Data from 244 participants who completed the trial were analyzed in structural-equation models. The presence of graphic images (compared to text-only) caused more negative affect toward smoking, a process that indirectly influenced risk perceptions and quit intentions (e.g., image->negative affect->risk perception->quit intention). Negative affect from graphic images also enhanced warning credibility including through increased scrutiny of the warnings, a process that also indirectly affected risk perceptions and quit intentions (e.g., image->negative affect->risk scrutiny->warning credibility->risk perception->quit intention). Unexpectedly, elaborated text reduced warning credibility. Finally, graphic warnings increased warning-information recall and indirectly increased smoking-risk knowledge at the end of the trial and one month later. CONCLUSIONS:In the first naturalistic clinical trial conducted, graphic warning labels are more effective than text-only warnings in encouraging smokers to consider quitting and in educating them about smoking's risks. Negative affective reactions to smoking, thinking about risks, and perceptions of credibility are mediators of their impact. TRIAL REGISTRATION:Clinicaltrials.gov NCT01782053.

Charitable giving in 2013 exceeded $300 billion, but why do we respond to some life-saving causes while ignoring others? In our first two studies, we demonstrated that valuation of lives is associated with affective feelings (self-reported and psychophysiological) and that a decline in compassion may begin with the second endangered life. In Study 3, this fading of compassion was reversed by describing multiple lives in a more unitary fashion. Study 4 extended our findings to loss-frame scenarios. Our capacity to feel sympathy for people in need appears limited, and this form of compassion fatigue can lead to apathy and inaction, consistent with what is seen repeatedly in response to many large-scale human and environmental catastrophes.