Health and Risk Communication

Since McCombs and Shaw first introduced the theory in 1972, agenda setting has emerged as one of the most influential perspectives in the study of the effects of mass media. Broadly defined, “agenda setting” refers to the ability of mass media sources to identify the most salient topics, thereby “setting the agendas” for audiences. In telling us what to think about, then, mass media sources are perceived to play an influential role in determining priorities related to policies, values, and knowledge on a given topic or issue.

Scholars have studied this phenomenon according to both object (issue) salience and attribute salience and along aggregate and individual audience responses. The audience characteristics of need for orientation, uncertainty, relevance, and involvement are advanced as moderating and predicting agenda-setting effects. When agenda-setting theory is applied to the study of messaging related to health and risk communication, scholars have reviewed and identified common themes and topics that generally include media’s role in educating and informing the public about specific health conditions as well as public health priorities and administrative policies.

Agenda setting is often examined in terms of measuring mass media effects on audiences. Looking at interpersonal communication, such as that coming from medical providers, opinion leaders, or peer networks, in studies will allow research to examine the combined effects of interpersonal and mass communication. Testing possible interactions among differing sources of information along with assessment of issue and attribute salience among audiences according to an agenda-setting framework serves to document audience trends and lived experiences with regard to mass media, health, and risk communication.

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.

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.

A community of practice (CoP) situated in a health and risk context is an approach to collaboration among members that promotes learning and development. In a CoP, individuals come together virtually or physically and coalesce around a common purpose. CoPs are defined by knowledge, rather than task, and encourage novices and experienced practitioners to work together to co-create and embed sustainable outputs that impact on theory and practice development. As a result, CoPs provide an innovative approach to incorporating evidence-based research associated with health and risk into systems and organizations aligned with public well-being.

CoPs provide a framework for constructing authentic and collaborative learning. Jeanne Lave and Etienne Wenger are credited with the original description of a CoP as an approach to learning that encompasses elements of identity, situation, and active participation. CoPs blend a constructivist view of learning, where meaningful experience is set in the context of “self” and the relationship of “self” with the wider professional community. The result is an integrated approach to learning and development achieved through a combination of social engagement and collaborative working in an authentic practice environment. CoPs therefore provide a strategic approach to acknowledging cultural differences related to translating health and risk theory into practice.

In health and risk settings, CoPs situate and blend theory and practice to create a portal for practitioners to generate, shape, test, and evaluate new ideas and innovations. Membership of a CoP supports the development of professional identity within a wider professional sphere and may support community members to attain long range goals.

Building and sustaining relationships fundamentally requires mutual trust based on authentic and reciprocal communication. Successful academic and community partnerships require a deep understanding of the needs of all stakeholders facilitated through dialogue and ongoing communication strategies. This dialogue is especially crucial to address health disparities and bridge the divide between academics and other professionals and the communities they serve. Innovative and sound health communications and community engagement approaches can help to address this divide. For those working with communities to improve health, Community Based Participatory Research (CBPR) principles can serve as a compass to guide those efforts of building on the strengths and resources within the community and ensuring co-learning to address social inequities. Moreover, using innovative and interactive health communication strategies, such as community forums, photovoice projects, and the development of culturally sensitive and relevant messaging, can empower and engage the community, facilitating long-lasting relationships between the academic institutions and communities that ultimately address the unique concerns and values of those most in need.

Embarrassment, according to Fischer and Tangney, is an “aversive state of mortification, abashment, and chagrin that follows public social predicaments.” It is usually related to our perceptions of how others perceive us as well as their judgments of us, and it is associated with a loss of self-esteem when we perceive that others have judged us as inadequate or incompetent. However, even mere exposure or attention publicly placed on someone can elicit embarrassment (think of someone pointing at you and laughing).

Embarrassment is considered a self-conscious emotion. Self-conscious emotions include those that are evoked by self-reflection and self-evaluation: embarrassment, shame, guilt, and pride. Shame, an intense form of embarrassment, also has structural and larger social contexts, while embarrassment is more individually experienced. Self-conscious emotions play an important role in regulating behavior; they assist us in behaving according to social standards and guide us in responding when those rules are broken. While these emotions provide feedback in social situations, they also provide feedback for anticipated outcomes.

Embarrassment can play an important role in health, both in communication and behavior, and occurs through different forms. Primary embarrassment is the first rush of blood to the face and increased heart rate that usually lasts a few moments. Secondary embarrassment is the after-effect that shapes future behavior. Anticipatory embarrassment is the emotion surrounding the potential for embarrassment in an upcoming situation. Solitary embarrassment is the one that no one actually observes.

Three stigmatized areas of health—mental health, healthcare, and sexual health—may be assessed as case studies through which to understand the literature around embarrassment, as both an affect and an emotion.

Research on forgiveness and its health-related effects has steadily increased since the late 20th century. Most of the forgiveness-health literature demonstrates that forgiveness indirectly influences health through a variety of psychosocial affective factors. Common distinctions in this research are reflected in studies focused on reduction of negative affect and, thus, negative health effects, and studies focused on preventative and health-promoting implications of forgiveness (e.g., increased positive affect). While a lack of clarity exists regarding health implications stemming from reductions in unforgiveness (as distinct from increases in forgiving responses), current research supports the notion that forgiveness, as opposed to unforgiveness, affects psychological, physical, and relational health in overridingly beneficial ways. More specifically, forgiveness, and/or the moderation of unforgiveness, is associated with the exhibition of positive affect (e.g., sympathy, empathy, and optimism), improved self-esteem, higher life satisfaction, and better mental health ratings. Physical health effects of forgiveness include enhanced bioregulation in response to transgression stressors, as well as better self-rated health status and the exhibition of positive health behaviors. Limitations in the current literature most commonly relate to disparate definitional, methodological, and interpretative issues typical of transdisciplinary forgiveness and health research. Current trends and future directions for forgiveness-health research include consideration of additional variables thought to be associated with forgiveness processes, including religiosity, empathy, and social support. Additionally, research that focuses on communicative and relational aspects of health and well-being is warranted. Suggestions for research opportunities in forgiveness-health research framed by a communicative lens are offered.