Ellen A. Wartella, Alexis R. Lauricella, Leanne Beaudoin-Ryan, and Drew P. Cingel
This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Communication. Please check back later for the full article.
Children are and have been active media users for decades. Historically, the focus on children and media issues have centered on the concerns and consequences of media use, generally around violence. In the last 40 years, we have seen a shift to study children and media from a more holistic approach, to understand both the positive and negative relationships between children and media use. Further, the recognition of the very important developmental differences that exist between children of different ages and the use of grand developmental theories, including those by Piaget and Vygotsky, have supported the field’s understanding of the unique ways in which children use media and the effects it has on their lives. Three important constructs related to a more complete understanding of children’s media use are the ABCs (attention, behavior, and comprehension). The first construct, attention, focuses on the way in which children’s attention to screen media develops, how factors related to parents and children can direct or influence attention to media, and how media may distract attention. The second construct is the behavioral effect of media use, including the relationship between media use and aggressive behavior, but importantly, the positive effect of prosocial media on children’s behavior and moral development. Finally, the third construct is the important and dynamic relationship between media and comprehension and learning. Taken together, these constructs describe a wide range of experiences that occur within children’s media use.
Matthew W. Savage, Sarah E. Jones, Jenna E. Reno, and Shari Veil
University students, faculty, and staff are among those most vulnerable to cybersecurity risks due to their reliance on modern technologies, the nature of their online activities, and the open infrastructure of institutional networks. Furthermore, cyberbullying has emerged as a public health concern by the Centers for Disease Control and Prevention (CDC), which first warned of electronic aggression in 2008, or any type of harassment or bullying that occurs via email, chat, instant messaging, websites, blogs, or text messaging. Roberto and Eden emphasized the communicative nature of cyberbullying, defining it as the “deliberate and repeated misuse of communication technology by an individual or group to threaten or harm others” in 2010 (p. 201). In response to serious cybersecurity concerns and growing evidence of cyberbullying behavior, the national Stop.Think.Connect. (STC) campaign was developed to educate Americans on cybersecurity risks and equip citizens with tools for safe, respectful, and appropriate online behavior; however, it lacks targeted messaging for those on university campuses. Formative research is needed to ascertain the specific cybersecurity risks and challenges identified by those living and working on large university campuses. Research by Noar in 2006 demonstrates that formative evaluation leads to more successful campaigns. The process involves learning about target populations, discovering communicative determinants of behavior change, and testing message concepts. To that end, this case study is a first step in targeting STC campaign messages to university students, faculty, and staff. Specifically, we sought to identify the distinct cybersecurity needs faced by university students and personnel, their perceptions of the saliency of the problem, and potential motives for increasing their cybersecurity-enhancing behaviors. These activities are needed to implement the campaign on college campuses and to increase the likelihood of any future outcome evaluation efforts that yield evidence of campaign effectiveness. Currently, we are unaware of any outcome evaluation.
Focus group methodology was conducted to examine the target audiences’ knowledge, interests, needs, and attitudes regarding the management of cybersecurity threats. Additionally, practical recommendations for enhancing STC campaign implementation on university campuses were ascertained. Results emphasized key ways to improve the theoretical underpinnings of the campaign using the Integrated Behavioral Model (IBM). We identified how determinants of behavior change can be utilized to strengthen campaign messaging. Students displayed laissez-faire attitudes toward cybersecurity, while faculty and staff attitudes demonstrated a much higher level of concern. Social norms for personal cybersecurity action taking were notably low among students as well as faculty and staff. Students displayed limited personal agency in regards to enacting cybersecurity measures, while faculty and staff had greater knowledge of steps they could take, but little faith that these actions would be efficacious. Finally, thematic recommendations for implementing an effective cybersecurity campaign on a university campus were identified.
Kathryn Greene, Smita C. Banerjee, Anne E. Ray, and Michael L. Hecht
Results of national epidemiologic surveys indicate that substance use rates among adolescents remain relatively steady or even show slight declines; however, some substance use rates, such as electronic cigarettes, are actually rising. Thus, the need for efficacious drug prevention efforts in the United States remains high. Active Involvement (AI) interventions are a promising avenue for preventing and reducing adolescent substance use, and they create opportunities for adolescents to experience a core feature of engagement that is common to these interventions, such as producing videos, posters, or radio ads; or generating themes and images for messages such as posters.
Existing interventions grounded in theories of Active Involvement include programs delivered face-to-face and via e-learning platforms. Narrative Engagement Theory and the Theory of Active Involvement guide the components of change in AI interventions. Youth develop message content during participation in Active Involvement interventions. Advanced analytic models can be applied to address new research questions related to the measure of components of AI interventions.
Michael Mackert and Marie Guadagno
Advertising as a field and industry often has a contentious relationship with both health communication and public health due to legitimate concerns about how advertising for certain products, such as alcohol and tobacco, could contribute to less-healthy decisions and behaviors. While acknowledging such concerns, advertisers and their approach to solving communication problems could also provide valuable lessons to those working in health communication. Indeed, advertising agencies are designed to develop creative and effective messages that change consumer behavior—and health communication practitioners and scholars aim to change population-level behavior as well. The perspective and approach of the account planner in the advertising agency—a role whose chief responsibility is to bring the consumer perspective into every step of the advertising development process and inspire effective and creative campaigns—would be particularly valuable to those working in health communication. It was account planning work that shifted traditional milk advertising from promoting it as a healthy drink to the iconic “got milk?” campaign, which positioned milk as a complement that makes other food better—an approach that drove positive sales after years of declining milk consumption. Yet many who work in health communication and public health often know little of how advertising agencies work or their internal processes that might be productively adopted. This lack of understanding can also lead to misperceptions of advertisers’ work and intentions. As an example, one might assume dense medical language in prescription drug advertising is intended to add unnecessary complexity to the advertisements and obscure side effects; instead, advertising professionals who work on prescription drug advertising have often been trained on clear communication—but cannot fully utilize that training because of regulations that require medically accurate terminology that might not be comprehensible to most viewers. Improved understanding of how advertisers can act as agents of change, and increased dialogue between the fields of advertising and health communication, could contribute to improved health communication research, practice, and policy.
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.
Janice L. Krieger and Jordan M. Neil
Strategic communication is an essential component in the science and practice of recruiting participants to clinical research studies. Unfortunately, many clinical research studies do not consider the role of communication in the recruitment process until efforts to enroll patients in a timely manner have failed. The field of communication is rich with theory and research that can inform the development of an effective recruitment plan from the inception of a clinical research study through informed consent. The recruitment context is distinct from many other health contexts in that there is often not a behavioral response that can be universally promoted to patients. The appropriateness of a clinical research study for an individual is based on a number of medical, psychological, and contextual factors, making it impossible to recommend that everyone who is eligible for a clinical research study enroll. Instead, clinical research study recruitment efforts must utilize strategic communication principles to ensure that messages promote awareness of clinical research, maximize personal relevance, minimize information overload, and facilitate informed choice. This can be accomplished through careful consideration of various aspects of the communication context described in this chapter, including audience segmentation, message content, message channels, and formative, process, and outcome evaluation, as well as the enrollment encounter.
Andrew M. Ledbetter
Owing to advances in communication technology, the human race now possesses more opportunities to interact with interpersonal partners than ever before. Particularly in recent decades, such technology has become increasingly faster, mobile, and powerful. Although tablets, smartphones, and social media are relatively new, the impetus behind their development is old, as throughout history humans have developed mechanisms for communicating ideas that transcend inherent temporal and spatial limitations of face-to-face communication. In the ancient past, humans developed writing and the alphabet to preserve knowledge across time, with the later development of the printing press further facilitating the mass distribution of written ideas. Later, the telegraph was arguably the first technology to separate communication from transportation, and the telephone enabled people at a distance to hear the warmth and intimacy of the human voice. The development of the Internet consolidates and advances these technologies by facilitating pictorial and video interactions, and the mobility provided by cell phones and other technologies makes the potential for communication with interpersonal partners nearly ubiquitous. As such, these technologies reconfigure perception of time and space, creating the sense of a smaller world where people can begin and manage interpersonal relationships across geographic distance.
These developments in communication technology influence interpersonal processes in at least four ways. First, they introduce media choice as a salient question in interpersonal relationships. As recently as the late 20th century, people faced relatively few options for communicating with interpersonal partners; by the early years of the 21st century, people possessed a sometimes bewildering array of channel choices. Moreover, these choices matter because of the relational messages they send; for example, choosing to end a romantic relationship over the phone may communicate more sensitivity than choosing to do so via text messaging, or publicly on social media. Second, communication technology affords new opportunities to begin relationships and, through structural features of the media, shape how those meetings occur. The online dating industry generates over $1 billion in profit, with most Americans agreeing it is a good way to meet romantic partners; friendships also form online around shared interests and through connections on social media. Third, communication technology alters the practices people use to maintain interpersonal relationships. In addition to placing traditional forms of relational maintenance in more public spaces, social media facilitates passive browsing as a strategy for keeping up with interpersonal partners. Moreover, mobile technology affords partners increased geographic and temporal flexibility when keeping contact with partners, yet simultaneously, it may produce feelings of over-connectedness that hamper the desire for personal autonomy. Fourth, communication technology makes interpersonal networks more visibly manifest and preserves their continuity over time. This may provide an ongoing convoy of social support and, through increased efficiency, augment the size and diversity of social networks.
In recent years, organizations have greatly increased their use of communication technologies to support knowledge management initiatives. These technologies, commonly referred to as knowledge management systems, are adopted in the hope that they will bolster organizations’ access to, and utilization of, knowledge resources. Yet the relationship between communication technology and knowledge management is complicated by ambiguity regarding whether knowledge can be validly captured, stored, and transmitted in an explicit form (as an object) or only exists in applications (as an action). Many scholars argue that reliance on communication technologies for knowledge management aids the ability of organizations to process information, but it has limited benefits for helping individuals gain situated knowledge regarding how best to accomplish work. An alternative view explores the potential of communication technologies to facilitate interaction among knowledgeable actors, which can support ongoing organizational learning. In practice, the use of communication technologies enacts a duality whereby knowledge operates both as an object that organizations and individuals have, and as an applied action that is used to solve situated problems. Numerous theoretical frameworks have been applied to study the relationship between communication technologies and knowledge management, with three of the most prominent being public goods theory, communities of practice, and transactive memory systems theory. Extant research recognizes the diverse ways that communication technologies can support knowledge management practices aimed at either improving the utilization of information in organizations or bolstering opportunities for interpersonal knowledge sharing. Regardless of the position taken regarding the most appropriate and effective ways that communication technology can support knowledge management, organizations hoping to implement knowledge management systems face numerous challenges related to spurring the creation of organizational knowledge, motivating individuals to share knowledge, transferring knowledge among groups, and storing knowledge to allow future retrieval. Furthermore, the breadth and diversity of communication technologies used for knowledge management will continue to expand as organizations explore the potential applications of social media technologies and seek to gain value from increases in available data regarding individuals’ communication and behaviors.
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.