The question of whether and how digital media use and digital communication affect people’s and particularly adolescents’ well-being has been investigated for several decades. Many studies have analyzed how different forms of digital communication influence loneliness and life satisfaction, two comparatively stable cognitive indicators of subjective well-being. Despite this large body of empirical work, the findings remain ambivalent, with studies resulting in positive, negative, or nonsignificant effects. Several meta-analyses suggest that the overall effect of digital communication on life satisfaction is probably too small to suggest a detrimental effect. The net effect of digital communication on loneliness, by contrast, is positive, but likewise small. Yet the studies on which these meta-analyses are based suffer from several limitations. They often adopt a limited perspective on the phenomenon of interest as a disproportionate amount of work focuses on interpersonal differences instead of intra-individual, contextual, and situational effects, as well as their interactions. Furthermore, studies are often based on cross-sectional data, use unvalidated and imprecise measurements, and differ greatly in how they conceptualize digital communication. The diversity in studied applications and forms of digital communication also suggests that effects are most likely bidirectional. Passive digital communication (e.g., browsing and lurking) is more likely to result in negative effects on well-being. Active and purposeful digital communication (e.g., posting, liking, conversating), by contrast, is more likely to result in positive effects. Future research should therefore investigate how the various levels of digital communication (including differences in devices, applications, features, interactions, and messages) interact in shaping individuals’ well-being. Instead of expecting long-term effects on comparatively stable cognitive indicators such as life satisfaction, scholars should rather study and identify the spatial and temporal boundaries of digital communication effects on the more fluctuating affective components of well-being.
Philipp K. Masur
Felix Reer and Thorsten Quandt
The study of addictive media use has a rather long tradition in media effects research and constitutes an interdisciplinary field that brings together scholars from communication science, psychology, psychiatry, and medicine. While older works focused on radio, film, or television addiction, newer studies have often examined the excessive use of interactive digital media and its consequences. Since the introduction of affordable home computer systems in the 1980s and 1990s, especially the pathological use of digital games (games addiction) has been discussed and investigated intensively. However, early research on the topic suffered from considerable methodological limitations, which made it difficult to assess the spread of the problem objectively. These limitations notwithstanding, the American Psychiatric Association (APA) decided to include the addictive use of digital games (Internet gaming disorder) as a “condition for further study” in its diagnostical manual, the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, 5th edition), in 2013. A few years later, the World Health Organization (WHO) officially acknowledged addictive game use as a diagnosable mental condition (gaming disorder) by listing it in the 11th edition of the International Classification of Diseases (ICD-11). Some scholars viewed the decisions of the APA and the WHO with skepticism, arguing that healthy players may be stigmatized, while others greeted them as important prerequisites to facilitate appropriate therapies. Despite the question of whether the inclusion of disordered game use in the manuals of the APA and the WHO has greater advantages than disadvantages, it definitely triggered a research boom. New scales testing the APA and the WHO criteria were developed and applied in international studies. Representative studies were conducted that indicated that at least a small percentage of players seemed to show playing patterns that indeed could be considered problematic. Further, the correlates of gaming disorder have been examined extensively, showing that the addictive use of digital games is associated with particular demographics, motivations, and personality aspects as well as with other diverse impairments, such as physical and psychological health issues and problems in the social and working lives of affected players. However, the debate about the accuracy of the definitions and diagnostic criteria postulated by the APA and the WHO has not ended, and more high-quality research is needed to further improve the understanding of the causes, consequences, and specifics of gaming disorder. In addition, new aspects and innovations, such as micropayments, loot boxes, and highly immersive technologies such as virtual reality or augmented reality systems, may expose gamers to new risks that future debates and research need to consider.
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.
Yvonnes Chen and Joseph Erba
Media literacy describes the ability to access, analyze, evaluate, and produce media messages. As media messages can influence audiences’ attitudes and behaviors toward various topics, such as attitudes toward others and risky behaviors, media literacy can counter potential negative media effects, a crucial task in today’s oversaturated media environment. Media literacy in the context of health promotion is addressed by analyzing the characteristics of 54 media literacy programs conducted in the United States and abroad that have successfully influenced audiences’ attitudes and behaviors toward six health topics: prevention of alcohol use, prevention of tobacco use, eating disorders and body image, sex education, nutrition education, and violent behavior. Because media literacy can change how audiences perceive the media industry and critique media messages, it could also reduce the potential harmful effects media can have on audiences’ health decision-making process. The majority of the interventions have focused on youth, likely because children’s and adolescents’ lack of cognitive sophistication may make them more vulnerable to potentially harmful media effects. The design of these health-related media literacy programs varied. Many studies’ interventions consisted of a one-course lesson, while others were multi-month, multi-lesson interventions. The majority of these programs’ content was developed and administered by a team of researchers affiliated with local universities and schools, and was focused on three main areas: reduction of media consumption, media analysis and evaluations, and media production and activism. Media literacy study designs almost always included a control group that did not take part in the intervention to confirm that potential changes in health and risk attitudes and behaviors among participants could be attributed to the intervention. Most programs were also designed to include at least one pre-intervention test and one post-intervention test, with the latter usually administered immediately following the intervention. Demographic variables, such as gender, age or grade level, and prior behavior pertaining to the health topic under study, were found to affect participants’ responses to media literacy interventions. In these 54 studies, a number of key media literacy components were clearly absent from the field. First, adults—especially those from historically underserved communities—were noticeably missing from these interventions. Second, media literacy interventions were often designed with a top-down approach, with little to no involvement from or collaboration with members of the target population. Third, the creation of counter media messages tailored to individuals’ needs and circumstances was rarely the focus of these interventions. Finally, these studies paid little attention to evaluating the development, process, and outcomes of media literacy interventions with participants’ sociodemographic characteristics in mind. Based on these findings, it is recommended that health-related media literacy programs fully engage community members at all steps, including in the critical analysis of current media messages and the production and dissemination of counter media messages. Health-related media literacy programs should also impart participants and community members with tools to advocate for their own causes and health behaviors.
Smita C. Banerjee and Kathryn Greene
Adolescent substance use remains a significant public health challenge, with recent approaches to address these problems including actively engaging adolescents in message planning and/or production as a prevention strategy. There are two benefits of this active involvement strategy. First, engaging adolescents in message planning or producing substance prevention messages is a form of participatory research that results in participant-generated messages for use in future intervention efforts. This participatory form of research is increasingly common in a wide range of topics and populations, particularly disenfranchised or stigmatized groups. It is important to focus on the second benefit of engaging adolescents in message planning and prevention: the effect of engaging in planning or producing substance prevention messages on the adolescents themselves. If done properly, the process of engaging adolescents in planning (or producing) anti-substance messages can provide longer-term benefits of delaying onset of substance use (strengthening resistance) as well as changing patterns for those already using. Some examples of this strategy exist with media literacy, although applied with a great deal of variability. The increased popularity of these planning/production approaches requires greater explication of how, when, and why they produce effects for participants. Two different theoretical perspectives address this active involvement intervention approach: narrative engagement theory and the theory of active involvement. Beyond these theories, sensation seeking is positioned as a moderator to explore for active involvement intervention effects.
Jannie Møller Hartley
The focus of news-audience research has shifted from investigating news audiences of single platforms—such as newspapers, television, or radio news—to audiences in an inherently cross-media context; and from examining the audience as passive, choosing between content made available for them; to investigating what audiences do with the news more actively, often coined by the term “news engagement.” News-audience studies can be divided into five approaches: (1) media-effect studies of news consumption; (2) studies of news-media use and motives; (3) cultural audience studies of news practices; (4) news audiences’ comprehension and recall of news; and (5) news engagement in the digital age. Due to changes in the media landscape, both technological and commercial, traditional analytical models in news-audience research have been challenged. The final discussion addresses how a tendency to focus on either reducing audiences to quantifiable aggregates in big-data research or labeling news audiences as a thing of the past can be observed—in both cases removing news-audience research from actual empirical audiences.