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In an ideal world, people would adopt a positive attitude toward a healthy lifestyle as a result of carefully considering relevant and strong arguments. Attitudes based upon such considerations are believed to be stable and good predictors of related behavior, and less vulnerable to counterattitudinal messages. However, carefully evaluating arguments in such messages is difficult. First, people need to identify what information can serve as an argument and construe the argumentative relation between the information and the advocated claim. Next, they need to assess the extent to which the argument satisfies the criteria for a strong argument. What these criteria are depends on the type of argument at hand: an argument from analogy, for instance, should be evaluated with different criteria than an argument from authority. Argument scrutiny thus entails reconstruction, identification, and evaluation.
The good news is that even though argument scrutiny is a complex task, it seems that people are pretty well equipped to carry it out. Meta-analyses have shown that messages containing strong arguments are more persuasive than those containing weak arguments. In addition, there is evidence that people are sensitive to what extent a specific argument satisfies relevant criteria when evaluating arguments. The bad news is that people may use these skills not so much to make objective evaluations to reach a better decision, but rather to defend the type of behavior that they already feel they want to perform. That is, they use their argument evaluation skills to reason why the arguments in support of the behavior that they favor are stronger than the arguments against that behavior.
Rachel A. Smith
A premise in health promotion and disease prevention is that exposure to and consequences of illness and injury can be minimized through people’s actions. Health campaigns, broadly defined as communication strategies intentionally designed to encourage people to engage in the actions that prevent illness and injury and promote wellbeing, typically try to inspire more than one person to change. No two people are exactly alike with respect to their risk for illness and injury or their reactions to a campaign attempting to lower their risk. These variations between people are important for health messaging. Effective campaigns provide a target audience with the right persuasive strategy to inspire change based on their initial state and psychosocial predictors for change. It is often financially and logistically unreasonable to create campaigns for each individual within a population; it is even unnecessary to the extent to which people exist in similar states and share psychosocial predictors for change. A challenging problem for health campaigns is to define those who need to be reached, and then intelligently group people based on a complex set of variables in order to identify groups with similar needs who will respond similarly to a particular persuasive strategy. The premise of this chapter is that segmentation at its best is a systematic and explicit process of research to make informed decisions about how many audiences to consider, why the audience is doing what they are doing, and how to reach that audience effectively.
Abigail R. Corrington, Mikki Hebl, and Jo-Ann Tsang
A growing number of studies are utilizing different sorts of behavioral indicators as measures of prejudice and discrimination. Although there are few foolproof behavioral indicators of discrimination (cf. verbal articulations of overt discrimination), patterns of behaviors can often be reliable indicators of discrimination. There are three sets of behavioral indicators. First, there are verbal behaviors such as overt insults or the use of pejorative words to describe stigmatized individuals. Such verbal statements, particularly when overt, make attributions of perceiver prejudice very straightforward. Such exchanges appear to be on the rise and are particularly worthy of study following the apparent 2016 “whitelash” and resistance to acting in ways deemed to be “politically correct.” Other forms of verbal behaviors involve more indirect expressions of prejudice, such as ambiguous comments and subjective references. Second, there are paraverbal behaviors that may index discrimination. For instance, individuals’ tone and pacing of speech may intentionally or unintentionally signal their disapproval or dislike of a stigmatized target. These behaviors are less commonly studied by social scientists but provide indicators about an individual’s intentions toward a stigmatized target. Third and finally, there are both nonverbal microbehaviors (e.g., gestures, eye contact) and macrobehaviors (e.g., avoidance, helping behavior). Behavioral measures—both classic and more state-of-the-art—that might serve as indicators of discrimination have been identified in recent research, and researchers should continue to learn more about them and use them.
Behavioral journalism is a term used to describe a theory-based health communication messaging strategy that is based on conveying “role model stories” about real people and how they achieve healthy behavior changes. The aim is to stimulate imitation of these models by audiences of their peers. Theoretical foundations for the strategy itself are in Albert Bandura’s social cognitive theory and Everett Rogers’s model of diffusion of innovations, but it can be used flexibly to convey various kinds of theory-driven message content. Behavioral journalism emerged as an explicit health communication technique in the late 1970s and was developed as a distinct alternative to the social marketing approach and its focus on centrally generated messages devised by experts. It has been used subsequently to promote smoking cessation, improvements in nutrition and physical activity, avoidance of sexually transmitted diseases and unplanned pregnancy, reduced intergroup hostility, advocacy for healthy policy and environmental changes, and many other diverse health promotion objectives. Formats used for behavioral journalism include reality television programs, broadcast and print news media, printed newsletters for special audiences, documentary film and video, digital and mobile communication, and new social media. Behavioral journalism is intended for use in concert with community organization and actions to prompt and reinforce the imitation of role models and to facilitate and enable behavior change, and its use in that context has yielded many reports of significant impact on behavior. With citations of use growing steadily in the past two decades, behavioral journalism has proven to be readily adaptable to new and emerging communication technologies.
Communication research has recently had an influx of groundbreaking findings based on big data. Examples include not only analyses of Twitter, Wikipedia, and Facebook, but also of search engine and smartphone uses. These can be put together under the label “digital media.” This article reviews some of the main findings of this research, emphasizing how big data findings contribute to existing theories and findings in communication research, which have so far been lacking. To do this, an analytical framework will be developed concerning the sources of digital data and how they relate to the pertinent media. This framework shows how data sources support making statements about the relation between digital media and social change. It is also possible to distinguish between a number of subfields that big data studies contribute to, including political communication, social network analysis, and mobile communication.
One of the major challenges is that most of this research does not fall into the two main traditions in the study of communication, mass and interpersonal communication. This is readily apparent for media like Twitter and Facebook, where messages are often distributed in groups rather than broadcast or shared between only two people. This challenge also applies, for example, to the use of search engines, where the technology can tailor results to particular users or groups (this has been labeled the “filter bubble” effect). The framework is used to locate and integrate big data findings in the landscape of communication research, and thus to provide a guide to this emerging area.
Bradford William Hesse
The presence of large-scale data systems can be felt, consciously or not, in almost every facet of modern life, whether through the simple act of selecting travel options online, purchasing products from online retailers, or navigating through the streets of an unfamiliar neighborhood using global positioning system (GPS) mapping. These systems operate through the momentum of big data, a term introduced by data scientists to describe a data-rich environment enabled by a superconvergence of advanced computer-processing speeds and storage capacities; advanced connectivity between people and devices through the Internet; the ubiquity of smart, mobile devices and wireless sensors; and the creation of accelerated data flows among systems in the global economy. Some researchers have suggested that big data represents the so-called fourth paradigm in science, wherein the first paradigm was marked by the evolution of the experimental method, the second was brought about by the maturation of theory, the third was marked by an evolution of statistical methodology as enabled by computational technology, while the fourth extended the benefits of the first three, but also enabled the application of novel machine-learning approaches to an evidence stream that exists in high volume, high velocity, high variety, and differing levels of veracity.
In public health and medicine, the emergence of big data capabilities has followed naturally from the expansion of data streams from genome sequencing, protein identification, environmental surveillance, and passive patient sensing. In 2001, the National Committee on Vital and Health Statistics published a road map for connecting these evidence streams to each other through a national health information infrastructure. Since then, the road map has spurred national investments in electronic health records (EHRs) and motivated the integration of public surveillance data into analytic platforms for health situational awareness. More recently, the boom in consumer-oriented mobile applications and wireless medical sensing devices has opened up the possibility for mining new data flows directly from altruistic patients. In the broader public communication sphere, the ability to mine the digital traces of conversation on social media presents an opportunity to apply advanced machine learning algorithms as a way of tracking the diffusion of risk communication messages. In addition to utilizing big data for improving the scientific knowledge base in risk communication, there will be a need for health communication scientists and practitioners to work as part of interdisciplinary teams to improve the interfaces to these data for professionals and the public. Too much data, presented in disorganized ways, can lead to what some have referred to as “data smog.” Much work will be needed for understanding how to turn big data into knowledge, and just as important, how to turn data-informed knowledge into action.
Kory Floyd and Colter D. Ray
Affectionate communication comprises the verbal and nonverbal behaviors people use to express messages of love, appreciation, fondness, and commitment to others in close relationships. Like all interpersonal behaviors, affectionate communication has biological and physiological antecedents, consequences, and correlates, many of which have implications for physical health and wellness. Investigating these factors within a biological framework allows for the adjudication of influences beyond those attributable to the environment. In particular, there are observable genetic and neurological differences between individuals with a highly affectionate disposition and those less prone to communicating affection, suggesting that variance in the tendency to engage in affectionate behavior is not entirely the result of environmental influences such as enculturation, parenting, and media exposure. In addition, the expression of affection is associated with markers of immune system competence and appears to help the body to relax and remain calm. The biological effects of affectionate communication are perhaps most pronounced in situations involving either acute or chronic stress. Specifically, highly affectionate individuals are less likely than others to overreact physiologically to stress-inducing events. Whatever stress reaction they do mount is better regulated than among their less affectionate counterparts. Moreover, highly affectionate individuals—or simply those who receive expressions of affection prior to or immediately following a stressful situation—exhibit faster physiological recovery from their elevated stress. Perhaps unsurprisingly, therefore, being deprived of adequate affectionate communication is predictive of multiple physical and psychological detriments, including elevated stress and exacerbated depression, social and relational problems, insecure attachment, susceptibility to diagnosed anxiety and mood disorders, susceptibility to diagnosed secondary immune disorders, chronic pain, and sleep disturbances.
Stephen A. Rains
The widespread diffusion of social media in recent years has created a number of opportunities and challenges for health and risk communication. Blogs and microblogs are specific forms of social media that appear to be particularly important. Blogs are webpages authored by an individual or group in which entries are published in reverse chronological order; microblogs are largely similar, but limited in the total number of characters that may be published per entry. Researchers have begun exploring the use and consequences of blogs and microblogs among individuals coping with illness as well as for health promotion. Much of this work has focused on better understanding people’s motivations for blogging about illness and the content of illness blogs. Coping with the challenges of illness and connecting with others are two primary motivations for authoring an illness blog, and blogs typically address medical issues (e.g., treatment options) and the author’s thoughts and feelings about experiencing illness. Although less prevalent, there is also evidence that illness blogging can be a resource for social support and facilitate coping efforts. Researchers studying the implications of blogs and microblogs for health promotion and risk communication have tended to focus on the use of these technologies by health professionals and for medical surveillance. Medical professionals appear to compose a noteworthy proportion of all health bloggers. Moreover, blogs and microblogs have been shown to serve a range of surveillance functions. In addition to being used to follow illness outbreaks in real-time, blogs and microblogs have offered a means for understanding public perceptions of health and risk-related issues including medical controversies. Taken as whole, contemporary research on health blogs and microblogs underscores the varied and important functions of these forms of social media for health and risk communication.
Davi Johnson Thornton
Communication studies identifies bodies as both objects of communication and producers (or sites) of communication. Communication about bodies—for example, gendered bodies, disabled bodies, obese bodies, and surgically modified bodies—influences bodies at the physical, material level by determining how they are treated in social interactions, in medical settings, and in public institutions. Communication about bodies also forges cultural consensus about what types of bodies fit in particular roles and settings. In addition to analyzing the stakes of communication about bodies, communication studies identifies bodies as communicating forces that cannot be accounted for by standards of reason, meaning, and decorum. Bodies are physical, material, affective beings that communicate because of, not in spite of, their messy, ineffable status. Moreover, communication is an embodied process that involves a range of material supports, including human bodies, technological bodies, and other nonhuman physical and biological bodies. Investigating bodies as communicating forces compels an understanding of communication that is not exclusively rational, meaning-oriented, and nonviolent.
Evan K. Perrault
Due to their sheer scope in trying to reach large sections of a population, and the costs necessary to implement them, evaluation is vital at every stage of the health communication campaign process. No stage is more important than the formative evaluation stage. At the formative stage, campaign designers must determine if a campaign is even necessary, and if so, determine what the campaign’s focus needs to be. Clear, measurable, and realistically attainable objectives need to be a primary output of formative evaluation, as these objectives help to guide the creation of all future campaign efforts. The formative stage also includes pilot testing any messages and strategies with the target audience prior to full-scale implementation. Once the campaign is implemented, process evaluation should be performed to determine if the campaign is being implemented as planned (i.e., fidelity), and also to document the dose of campaign exposure. Identifying problem areas during process evaluation can ensure they get fixed prior to the completion of the campaign. Detailed process evaluation also allows for greater ease in replicating a successful campaign attempt in the future, but additionally can provide potential reasons for why a campaign was not successful. The last stage is outcome evaluation—determining if the objectives of the campaign were achieved. While it is the last stage of campaign evaluation, campaign designers need to ensure they have planned for it in the formative stages. If even just one of these stages of evaluation is minimized in campaign design, or relegated to an after-thought, developers need to realize that the ultimate effectiveness of their campaigns is likely to be minimized as well.