New Directions and Opportunities for Future Research
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The thousands of reasoned action studies now in existence address only a limited number of questions and use only a limited number of methodologies. For example, studies that explain intention far outnumber studies that prospectively examine behavior and studies that examine beliefs; and studies that use survey methodology far outnumber experimental studies. Although survey-based tests of intention usefully show whether in a particular population intention to perform a particular behavior is guided by attitude, perceived norm or perceived behavioral control, belief-based and behavioral analyses are at least as interesting to persuasion scholars. In addition, there are other questions that should appear more prominently on research agendas than they have thus far. Two of these have to do with developing hypotheses about when reasoned action variables will predict which behaviors, and how reasoned action can inform message design.
Predicting Prediction
Reasoned action theory proposes that to predict intention and behavior only a small number of variables need to be considered. Because each behavior is substantively unique, which of these variables most critically guide a particular behavior in a particular population is an empirical question. Clear research recommendations have been developed for identifying those critical variables (e.g., Fishbein & Ajzen, 2010; Fishbein & Yzer, 2003), and there is evidence that interventions that follow these recommendations can effectively change behavior (e.g., Albarracín et al., 2005).
Although the basic assumption of the uniqueness of each behavior is true in principle, the implication that identification of a behavior’s critical predictor is an empirical question is not altogether satisfactory. Both for scholarly and intervention purposes, it would be more advantageous if prediction could be predicted, that is, if it would be possible to hypothesize which reasoned action variable will predict a particular behavior in a particular population. There is some evidence that this is a realistic objective. For example, experimental work has corroborated behavior and population features that determine the predictive power of perceived norm (Jacobson, Mortensen, & Cialdini, 2011; Trafimow & Fishbein, 1994).
One can turn to other theory to derive principles that can help understand when specific reasoned action variables will explain behavior (Fishbein & Ajzen, 2010; Weinstein & Rothman, 2005). For example, Lutchyn and Yzer (2011) used construal level theory (Trope & Liberman, 2003) to test the implications of changing the time component of behavioral definitions for the relative importance of behavioral and control beliefs. Construal level theory proposes that people use abstract terms to construe behaviors that are to be performed some time in the future. Construals of such distant behaviors emphasize the “why” aspects of behavior, and describe behavior in terms of the value or desirability of a behavioral outcome, or in reasoned action terms, behavioral beliefs. In contrast, construals of near future behaviors are more concrete and represent the “how” aspect of the behavior. They reflect feasibility of the behavior, or in reasoned action terms, control beliefs. Lutchyn and Yzer (2011) found that the salience of beliefs is a function of time frame, such that when the time component in a behavioral definition moves from the near to the distant future, the salience of behavioral beliefs increases and the salience of control beliefs decreases. These findings have implications for message design. To motivate distant behavior, messages need to address behavioral consequences. For example, a message sent in September to motivate people to get a flu shot right before the flu season’s expected onset in December can emphasize the benefits of getting a flu shot. To affect near future behavior, for example, getting a flu shot this week, messages should include references to control beliefs, for example, information about where one can get free flu shots.
Moving Beyond Message Content
Interventionists can use reasoned action theory to identify the behavioral, normative, and/or control beliefs that guide people’s behavior. It is these beliefs that messages should address. The theory thus is a tool for informing message content. It was not designed to inform the next necessary question in the message design process; which audiovisual, narrative, duration, and other stylistic message features will change the beliefs addressed in the message? Fishbein and Ajzen (2010) commented thus on the boundaries of reasoned action theory: “Selection of appropriate primary beliefs is perhaps our theory’s most important contribution to behavior change interventions. The theory offers little guidance as to the specific strategies that will most effectively bring about the desired changes in behavioral, normative, or control beliefs. Such guidance must come from outside our theory” (p. 367).
Some guidance is available. The literature on communication campaigns, for example, offers excellent overviews of components and design steps of successful campaigns (Rice & Atkin, 2009). Similarly, scholars have addressed the complementary nature of behavior change and message effects theories for the purpose of improving cancer prevention (Cappella, 2006). Such work highlights that message development involves decisions about both content and creative design, and that different theories are to be used to inform each of these decisions. Which theories in particular complement reasoned action theory is a relatively unexplored question, but one that if answered can greatly advance understanding of persuasive messages.
Conclusion
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Seen through a reasoned action lens, persuasion is belief-based behavior change. Therefore, the better one understands which beliefs cause behavior by what process, the better able one is to design successful messages. The review presented in this chapter discussed that if used correctly, reasoned action theory can identify the beliefs that explain why people do or do not perform a particular behavior. It also identified a number of issues that if addressed can deepen our understanding of behavioral prediction. Akin to how reasoned action theory was first conceived, to address these issues, an outward-looking strategy that draws on complementary theory will generate greatest progress. The challenge for future research is twofold; more precise predictions about how and when reasoned action variables predict intention and behavior are needed, and in addition, message design strategies that can change these variables need to be identified. These are challenges that promise exciting research, significant theoretical advancement, and effective practical application.
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