An empirical content analysis of a decade of coverage of climate change in five national newspapers in the US is presented. The analysis is based on the perspective, drawn from social problems theory, that the content of news discourse can be understood in terms of claims-making and framing. Climate change is also discussed in terms of Downs' issue-attention cycle, a five-stage model describing the rise and fall of social attention to important issues. Climate change, as a news story, is described as exhibiting three phases that are related to the sources quoted and the frames presented in the news coverage. Results of the analysis show that scientists tend to be associated with frames emphasizing problems and causes, while politicians and special interests tend to be associated with frames emphasizing judgments and remedies. Results also show how scientists declined as news sources as the issue became increasingly politicized.

Recent developments in communication technologies have created alternative survey methods through e‐mail and Web sites. Both methods use electronic text communication, require fewer resources, and provide faster responses than traditional paper and pencil methods. However, new survey methodologies also generate problems involving sampling, response consistency and participant motivation. Empirical studies need to be done to address these issues as researchers implement electronic survey methods. In this study we conduct an analysis of the characteristics of three survey response modes: post, e‐mail, and Web site. Data are from a survey of the National Association of Science Writers (NASW), in which science writers' professional use of e‐mail and the Web is evaluated. Our analysis offers two lessons. First, a caution. We detect a number of potentially important differences in the response characteristics of these three groups. Researchers using multi‐mode survey techniques should keep in mind that subtle effects might be at play in their analyses. Second, an encouragement. We do not observe significant influences of survey mode in our substantive analyses. We feel, at least in this case, that the differences detected in the response groups indicate that using multi‐mode survey techniques improved the representativeness of the sample without biasing other results.

The heuristic-systematic information processing model (HSM) holds that individuals will use one or both of these modes of information processing when attempting to evaluate information in order to arrive at a judgment. Systematic processing is defined by effortful scrutiny and comparison of information, whereas heuristic processing is defined by the use of cues to arrive more easily at a judgment. Antecedents to the two processing modes include information sufficiency, motivation, and self-efficacy. Structural equation modeling is used to examine competing configuration of this model and to evaluate the model as appropriate for predicting risk judgment. The model also is evaluated across three groups that vary with respect to their level of concern. These analyses are executed within a case study involving an epidemiological investigation of a suspected cancer cluster. The analysis confirms the HSM's theoretically proposed structure and shows it to be a useful vehicle for evaluating risk judgment. In the overall analysis, antecedent variables generally function as specified by theory. Systematic processing is predicted by greater motivation. Heuristic processing is predicted by information sufficiency. Self-efficacy is a significant predictor of both processing modes. And heuristic processing is shown to be associated with judgment of less risk. However, when the analysis is contrasted across three groups (those concerned about cancer, not concerned and uncertain) it is shown that the model is significantly more robust for the uncertain group. This finding may have implications for the use of the HSM in risk research specifically, and in field research generally.

This study examines how credibility affects the way people process information and how they subsequently perceive risk. Three conceptual areas are brought together in this analysis: the psychometric model of risk perception, Eagly and Chaiken's heuristic-systematic information processing model, and Meyer's credibility index. Data come from a study of risk communication in the circumstance of state health department investigations of suspected cancer clusters (five cases, N = 696). Credibility is assessed for three information sources: state health departments, citizen groups, and industries involved in each case. Higher credibility for industry and the state directly predicts lower risk perception, whereas high credibility for citizen groups predicts greater risk perception. A path model shows that perceiving high credibility for industry and state-and perceiving low credibility for citizen groups-promotes heuristic processing, which in turn is a strong predictor of lower risk perception. Alternately, perceiving industry and the state to have low credibility also promotes greater systematic processing, which consistently leads to perception of greater risk. Between a one-fifth and one-third of the effect of credibility on risk perception is shown to be indirectly transmitted through information processing.

The heuristic-systematic information-processing model (HSM) holds that individuals will use 1 or both of these modes of information processing when attempting to evaluate information in order to arrive at a judgment. Using survey data, an adaptation of this model is evaluated across a series of 3 cases in which epidemiological information is communicated to communities concerned about cancer rates. This adaptation of the HSM proves to be a potentially useful model for understanding how individuals perceive risk. Although the model does vary across the 3 applications enough to justify inclusion of the case as a control variable, relationships among the model's most important constituent variables are generally consistent and strong. A quarter to a third of the variance in risk perception is predicted by information processing in a structural model having an acceptably close fit to the data.A significant literature has developed during the past dozen years that attends to the processes and effects of communication involving risk-frequently the perceived health risks associated with environmental hazards or the hazards of new technologies (Trumbo, 2001). One area of effort that is gaining a foothold in this line of research involves a popular information-processing theory that hails from experimental social psychology: Eagly and Chaiken's heuristic-systematic model, or simply the HSM (Chaiken, 1980, Eagly & Chaiken, 1993. This article reports the results of a series of three replicated investigations using the experimentally developed HSM as the basis for an adaptation of the model to predict risk perception in data gathered by survey methods.The results of this investigation are significant in three ways: First, they examine measurement issues involving the adaptation of the HSM for survey data; second, they evaluate the consistency of the performance of an adapted model; and third, they reveal interesting, consistent, and potentially important relationships between information processing and reactions to risk. 368 This article describes HSM and risk perception-the two major conceptual areas of the analysis-and discusses the proposed model, describing the context of the data collections (public health communication involving cancer epidemiology) and providing the results of a set of three replications using the proposed model.

The heuristic-systematic information-processing model (HSM) holds that individuals will use 1 or both of these modes of information processing when attempting to evaluate information in order to arrive at a judgment. Using survey data, an adaptation of this model is evaluated across a series of 3 cases in which epidemiological information is communicated to communities concerned about cancer rates. This adaptation of the HSM proves to be a potentially useful model for understanding how individuals perceive risk. Although the model does vary across the 3 applications enough to justify inclusion of the case as a control variable, relationships among the model's most important constituent variables are generally consistent and strong. A quarter to a third of the variance in risk perception is predicted by information processing in a structural model having an acceptably close fit to the data.A significant literature has developed during the past dozen years that attends to the processes and effects of communication involving risk-frequently the perceived health risks associated with environmental hazards or the hazards of new technologies (Trumbo, 2001). One area of effort that is gaining a foothold in this line of research involves a popular information-processing theory that hails from experimental social psychology: Eagly and Chaiken's heuristic-systematic model, or simply the HSM (Chaiken, 1980, Eagly & Chaiken, 1993. This article reports the results of a series of three replicated investigations using the experimentally developed HSM as the basis for an adaptation of the model to predict risk perception in data gathered by survey methods.The results of this investigation are significant in three ways: First, they examine measurement issues involving the adaptation of the HSM for survey data; second, they evaluate the consistency of the performance of an adapted model; and third, they reveal interesting, consistent, and potentially important relationships between information processing and reactions to risk. 368 This article describes HSM and risk perception-the two major conceptual areas of the analysis-and discusses the proposed model, describing the context of the data collections (public health communication involving cancer epidemiology) and providing the results of a set of three replications using the proposed model. The Heuristic-Systematic ModelThe heuristic-systematic model examines information processing as an antecedent to attitude formation. As a process theory, it is based on the assumption that "attitudes are formed and modified as people gain information about attitude objects" (Eagly & Chaiken, 1993, p. 257). As such, it is well suited for use in studies of risk communication because it can form effective links among the questions of where people get risk information, how they deal with it, and how this influences their subsequent risk perceptions. The HSM may be especially appropriate to this task because "the heuristic-systematic model was developed to apply to validity-seeking persuasion ...

Individuals’ past experiences with a hazard can encompass many different aspects, which can influence how they judge and respond to a future hurricane risk. This study, which utilizes survey data from coastal residents who are at risk from hurricanes, adds to understanding of past hazard experience in two ways. First, it examines six different aspects of people’s past hurricane experiences and the relationships among them. Then, it draws on risk theories of behavioral responses to explore how these different experiences influence people’s evacuation intentions for a hypothetical hurricane as mediated through multiple dimensions of risk perception (cognitive, negative affective) and efficacy beliefs (self efficacy, response efficacy). The results suggest that people can experience emotional or otherwise severe impacts from a hurricane even if they do not have experiences with evacuation, property damage, or financial loss. The results also reveal that different past hurricane experiences operated through different combinations of mediating variables to influence evacuation intentions. Some of these processes enhanced intentions; for instance, experience with evacuation, financial loss, or emotional impacts heightened negative affective risk perceptions, which increased evacuation intentions. Other processes dampened evacuation intentions; for instance, people with past hurricane-related emotional impacts had lower self efficacy, which decreased evacuation intentions. In some cases, these enhancing and dampening processes competed. Exploring people’s different past weather experiences and the mechanisms by which they can influence future behaviors is important for more deeply understanding populations at risk and how they respond to weather threats.

This study evaluated how individuals living on the Gulf Coast perceived hurricane risk after Hurricanes Katrina and Rita. It was hypothesized that hurricane outlook and optimistic bias for hurricane risk would be associated positively with distance from the Katrina-Rita landfall (more optimism at greater distance), controlling for historically based hurricane risk and county population density, demographics, individual hurricane experience, and dispositional optimism. Data were collected in January 2006 through a mail survey sent to 1,375 households in 41 counties on the coast (n = 824, 60% response). The analysis used hierarchal regression to test hypotheses. Hurricane history and population density had no effect on outlook; individuals who were male, older, and with higher household incomes were associated with lower risk perception; individual hurricane experience and personal impacts from Katrina and Rita predicted greater risk perception; greater dispositional optimism predicted more optimistic outlook; distance had a small effect but predicted less optimistic outlook at greater distance (model R(2) = 0.21). The model for optimistic bias had fewer effects: age and community tenure were significant; dispositional optimism had a positive effect on optimistic bias; distance variables were not significant (model R(2) = 0.05). The study shows that an existing measure of hurricane outlook has utility, hurricane outlook appears to be a unique concept from hurricane optimistic bias, and proximity has at most small effects. Future extension of this research will include improved conceptualization and measurement of hurricane risk perception and will bring to focus several concepts involving risk communication.