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When individuals are asked whether they will someday own their own home, enjoy a productive career, or develop a myriad of diseases, many are optimistic. Generally, they think they will experience more good than bad outcomes in life and they view themselves as more likely than similar others to experience the good things and less likely than others to experience the bad things. In the area of health behavior and communication, there are three primary types of optimism that have been defined and operationalized: (1) Dispositional optimism is the generalized positive expectancy that one will experience good outcomes. (2) Comparative optimism refers to the belief that one is either more likely than others to experience positive events or less likely than others to experience negative events. (3) Unrealistic optimism refers to an underestimation of one’s actual risk of experiencing some negative event. Although the three types of optimism may be correlated, their associations may be modest. Also, unlike dispositional optimism, which is an individual difference, comparative and unrealistic optimism are often risk perceptions about specific events and therefore can be defined as accurate or inaccurate. For this reason, the latter two types of optimism have sometimes been labeled the optimistic bias. Research on all three varieties of optimism affords opportunities to understand how optimism influences information processing in a health message or one’s behavioral intentions following the message.


Hye-Jin Paek and Thomas Hove

Risk perception refers to people’s subjective judgments about the likelihood of negative occurrences such as injury, illness, disease, and death. Risk perception is important in health and risk communication because it determines which hazards people care about and how they deal with them. Risk perception has two main dimensions: the cognitive dimension, which relates to how much people know about and understand risks, and the emotional dimension, which relates to how they feel about them. Several theoretical models have been developed to explain how people perceive risks, how they process risk information, and how they make decisions about them: the psychometric paradigm, the risk perception model, the mental noise model, the negative dominance model, the trust determination model, and the social amplification of risk framework. Laypeople have been found to evaluate risks mostly according to subjective perceptions, intuitive judgments, and inferences made from media coverage and limited information. Experts try to base their risk perceptions more on research findings and statistical evidence. Risk perceptions are important precursors to health-related behaviors and other behaviors that experts recommend for either dealing with or preventing risks. Models of behavior change that incorporate the concept of risk perception include the Health Belief Model, Protection Motivation Theory, the Extended Parallel Process Model, and the Risk Perception Attitude framework. Public awareness and perceptions of a risk can be influenced by how the media cover it. A variety of media factors have been found to affect the public’s risk perceptions, including the following: (1) amount of media coverage; (2) frames used for describing risks; (3) valence and tone of media coverage; (4) media sources and their perceived trustworthiness; (5) formats in which risks are presented; and (6) media channels and types. For all of these media factors, albeit to varying degrees, there is theoretical and empirical support for their relevance to risk perceptions. Particularly related to media channels and genres, two hypotheses have emerged that specify different kinds of media influences. The impersonal impact hypothesis predicts that news media mainly influence how people see risks as affecting other individuals, groups, nations, or the world population in general (societal-level risk perceptions). By contrast, the differential impact hypothesis predicts that, while news media influence people’s societal-level risk perceptions, entertainment media have stronger effects on how people see risks as affecting themselves (personal-level risk perceptions). As the media environment become increasingly diverse and fragmented, future research on risk perception needs to examine more of the influences that various media, including social media, have on risk perception. Also, the accounts of how those influences work need to be further refined. Finally, since people’s risk perceptions lead them to either adopt or reject recommended health behaviors, more research needs to examine how risk perceptions are jointly affected by media, audience characteristics, and risk characteristics.


Simon Zebregs and Gert-Jan de Bruijn

Meta-analyses are becoming increasingly popular in the field of health and risk communication—meta-analyses allow for more precise estimations of the magnitude of effects and the robustness of those effects across empirical studies in a particular domain. Despite its popularity, most scholars are not trained in the basic methods involved with meta-analyses. There are advantages to meta-analysis in comparison to other forms of research synthesis. An overview of the methods involved in conducting and reporting meta-analytical research is helpful. However, the methods involved with meta-analyses are not as clear-cut as they may first appear. Numerous issues must be considered and various arbitrary decisions are required during the process. These issues and decisions relate to various topics such as inclusion criteria, the selection of sources, quality assessments for eligible studies, and publication bias. Basic knowledge of these issues and decisions is important for interpreting the outcomes of a meta-analysis correctly.