Modern research methods for communication and social change reflect a tension between collecting data at the individual level while making inferences at macro-levels such as health-care systems, communities, and nations. This tension becomes more palpable when measuring the concerns of historically underserved, difficult-to-reach populations, those suffering the greatest inequalities in access to information, civic participation, and, in particular, health-care. Research questions are explored by focusing on multiple levels of analysis, multidisciplinary approaches, targeted methods/measures, flexible measures of “community,” and converging methodologies for maximizing evaluation validity.
Communication studies often rely on national samples of self-reports on personal attitudes and values, drawing conclusions at the individual level. Despite the risk of “ecological” or “atomistic” fallacies, creative comparisons of different levels of analysis, especially at the city level, can illuminate previously unconfirmed connections between communication and social change. For example, differences in community-level demographics or social structure have been linked to variations in major newspaper coverage, often called a “community structure” approach, sometimes revealing a “guard dog” relationship, in which media perpetuate existing social and political arrangements, as opposed to functioning as “watchdogs” on abuses of power (Tichenor et al. 1980; Donohue et al. 1995; Demers & Viswanath 1999).
Combining article “prominence” and article “direction” into a single score, Pollock’s “media vector” measure used a community structure model to link community/ demographic characteristics or “stakeholders” at the metropolitan level – such as poverty level and educational or income privilege – to newspaper coverage supporting social change or human rights claims, sometimes mirroring the concerns of more “vulnerable” groups (Pollock 2007). Other community analyses use hierarchical linear modeling to compare aggregate and individual levels of analysis regarding the positive contribution of local print media consumption directly (and indirectly, through increased social interaction) to community participation (Paek et al. 2005).
Rationale For Multi-Method Multidisciplinary Approaches
Given the complexity of human communications and the consequences attendant with the flow of information, it is not surprising that communication both draws from and contributes to other disciplines. By extension, documenting and measuring communication processes and effects demand a variety of approaches.
For example, journalism “gatekeeping” studies illuminate editorial decisions to omit some issues, “agenda-setting” studies enhance audience salience for selected issues, and “diffusion” studies underscore uneven flows of new information to different audiences. All draw attention to audience or population inequalities in information. Dependent variables such as community participation, civic engagement, collective action, and social capital – community interaction and solidarity (Putnam 2000) – borrowed from political science and sociology illustrate the use of multidisciplinary approaches and concerns. “Framing,” drawing from sociology and psychology, refers to the way journalists organize news stories to provide meaning to related events, indicating the advocacy of certain ideas (Reese 2001), and helping social movements foster mobilization (Johnston & Noakes 2005).
These diverse phenomena in a variety of media and multiple settings call for broadening the scope of research designs beyond traditional random samples of individuals to employing a variety of research designs and data collection tools, including surveys or quasi-experimental designs; analysis of communication and media content, including conversations, Internet postings, and exchanges; interpersonal exchanges (e.g., between physicians and patients); and exploring internal messages to improve self-monitoring of compliance with healthy behavior (Parrott 2004).
In addition, recent interest in the effects of health disparities, communication inequalities, and the role of “social contextual” factors like social class, social organizations, and social capital, on communication phenomena that affect health warrant measures at social level (Viswanath 2006; Viswanath & Emmons 2006).
Special attention is increasingly paid to different types of “communities” in reducing health knowledge gaps, whether communities with different levels of “community-boundedness” (relevance of a topic for a specific community) or “communities without propinquity” (Viswanath et al. 2000). “Community” as both a definition and unit of analysis is becoming elastic as researchers seek hard-to-reach and high-risk populations less through traditional telephone or residential interviews, more through intersecting respondents in the community contexts and venues they inhabit: in the workplace, meeting places, grocery stores, or recreational locations. Examining the role of “community norms” for college-age drinking, for example, requires exploring multiple norm sources: parents, social peers, close friends, etc. Modern research on breast cancer, for example, sometimes focuses on the roles that partners/spouses and workplaces can play in accelerating cancer recovery rates. In addition, some studies suggest training those in high-risk or difficult-to-reach communities themselves to promote risk reduction, suggesting that identification can play a role in behavior change. In general, traditional onsite geographic research engagement is expanding to “onsite” measurement in a wide range of venues, from residence to workplace and Internet sites of all kinds: blogs, bulletin boards, chatrooms, or websites themselves (Sundar et al. 2007), including the use of online deliberation to discuss health policy and medical ethics (Price et al. 2006).
Evaluating Health Communication Effectiveness: Maximizing Validity
The experiences with major lifestyle campaigns such as the Stanford Heart Disease Prevention Program and the Minnesota Heart Health Program, among others, highlight the difficulty of measuring the impact of community-based health campaigns (Hornik 2002). These include (1) the problem of finding legitimate “control” groups or segments when long-term secular trends (such as changes in social norms regarding balanced diets and tobacco consumption) outpace the pristine designs of investigators; (2) the need to search for appropriate (especially longer) effect lag times and magnitudes of expected effects (much smaller) that may differ from traditional research expectations (e.g., reduction in tobacco use has been gradual over several decades, but efforts to measure the effects of reduction campaigns within oneor two-year spans would have encountered few significant results); and (3) the importance of flexibility in accounting for effects across multiple (individual, institutional, and social) units of analysis. These dilemmas could be addressed by more creative approaches to research designs, including longitudinal designs with multiple time points, comparing different levels of exposure to campaigns rather than assuming no exposure, and measuring intermediate outcomes that are amenable to change through communications rather than limited to final health outcomes, among others (Hornik 2002; Glasgow et al. 2004).
These challenges are not unique to communication, and, in fact, are common in medicine, where randomized control trials (RCT) remain the gold standard. Given the practical difficulty in conducting RCTs, and the fact that evidence is accumulated through a variety of observational methods such as surveys, experiments and quasi-experiments, perusal of medical records, literature reviews, and meta-analyses, among others, some have argued that one must look at the total “weight of evidence” from the multiple methods to reach inferences rather than rely on one single method (Weed 2005). The latter is a reasonable and viable alternative, given the complexity in studying the impact of communication in social change.
Employing multiple methods is not unusual in health communication research. Researchers have used textual analyses to study physician–patient interactions, and narrative and discourse analyses to examine the impact of social movements on health policies (Sharf 2001). Further, ethnographic critical incident interviews were combined with online and paper questionnaires to examine relationships among social support, communication competence, and perceived stress in a study of well elders, seniors with cancer, and their lay caregivers (Query & Wright 2003). In addition, meta-analysis pools and statistically analyzes data from similar studies with similar measures, combining findings to reach larger conclusions (see, e.g., Witte & Allen 2000).
To mitigate inequalities and health disparities, scholars use imaginative levels of analysis, measures and definitions of community, and converging methodologies to improve research validity and (for health communication) effectiveness, exploring how much communication exposure measures add to income, education, gender, and age in their collective power to improve prevention behavior and reduce differential risk behaviors among different social groups.
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