The SAGE Handbook of Persuasion

by James Price Dillard

  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.

  References

  * * *

  Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckman (Eds.), Action-control: From cognition to behavior (pp. 11–39). Heidelberg, Germany: Springer.

  Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211.

  Ajzen, I., & Fishbein, M. (1973). Attitudinal and normative variables as predictors of specific behavior. Journal of Personality and Social Psychology, 27, 41–57.

  Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall.

  Ajzen, I., & Fishbein, M. (2008). Scaling and testing multiplicative combinations in the expectancy-value model of attitudes. Journal of Applied Social Psychology, 38, 2222–2247.

  Albarracín, D., Gillette, J. C., Earl, A. N., Glasman, L. R., Durantini, M. R., & Ho, M. H. (2005). A test of major assumptions about behavior change: A comprehensive look at HIV prevention interventions since the beginning of the epidemic. Psychological Bulletin, 131, 856–897.

  Albarracín, D., Johnson, B. T., Fishbein, M., & Muellerleile, P. (2001). Theories of reasoned action and planned behavior as models of condom use: A meta-analysis. Psychological Bulletin, 127, 142–161.

  Albarracín, D., Kumkale, G. T., & Johnson, B. T. (2004). Influences of social power and resources on condom use decisions: A research synthesis. AIDS Care, 16, 700–723.

  Allport, G. W. (1935). Attitudes. In C. Murchison (Ed.), Handbook of social psychology (pp. 798–844). Worcester, MA: Clark University Press.

  Armitage, C. J. (2005). Can th
e theory of planned behavior predict the maintenance of physical activity? Health Psychology, 24, 235–245.

  Armitage, C. J., & Conner, M. (1999). Distinguishing perceptions of control from self-efficacy: Predicting consumption of a low fat diet using the theory of planned behavior. Journal of Applied Social Psychology, 29, 72–90.

  Armitage, C. J., & Conner, M. (2001). Efficacy of the theory of planned behavior: A meta-analytic review. British Journal of Social Psychology, 40, 471–499.

  Armitage, C. J., Conner, M., Loach, J., & Willetts, D. (1999). Different perceptions of control: Applying an extended theory of planned behavior to legal and illegal drug use. Basic and Applied Social Psychology, 21, 301–316.

  Bandura, A. (1997). Self-efficacy: The exercise of control. New York, NY: Freeman.

  Blank, M., & Hennessy, M. (2012). A reasoned action approach to HIV prevention for persons with serious mental illness. The Annals of the American Academy of Political and Social Science, 640, 173–188.

  Brown, N. R., & Sinclair, R. C. (1999). Estimating number of lifetime sexual partners: Men and women do it differently. Journal of Sex Research, 36, 292–297.

  Budden, J. S., & Sagarin, B. J. (2007). Implementation intentions, occupational stress, and the exercise intention-behavior relationship. Journal of Occupational Health Psychology, 12, 391–401.

  Cappella, J. N. (2006). Integrating message effects and behavior change theories: Organizing comments and unanswered questions. Journal of Communication, 56, S265–S279.

  Cialdini, R. B., Reno, R. R., & Kallgren, C. A. (1990). A focus theory of normative conduct: Recycling the concept of norms to reduce littering in public places. Journal of Personality and Social Psychology, 58, 1015–1026.

  Cooke, R., & French, D. P. (2008). How well do the theory of reasoned action and theory of planned behaviour predict intentions and attendance at screening programmes? A meta-analysis. Psychology & Health, 23, 745–765.

  Cooke, R., & Sheeran, P. (2004). Moderation of cognition-intention and cognition-behaviour relations: A meta-analysis of properties of variables from the theory of planned behavior. British Journal of Social Psychology, 43, 159–186.

  Courneya, K. S., & McAuley, E. (1993). Predicting physical activity from intention: Conceptual and methodological issues. Journal of Sport and Exercise Psychology, 15, 50–62.

  De Bruijn, G. J., Kremers, S. P. J., Schaalma, H., van Mechelen, W., & Brug, J. (2005). Determinants of adolescent bicycle use for transportation and snacking behaviour. Preventive Medicine, 40, 658–667.

  Dulany, D. E. (1968). Awareness, rules, and prepositional control: A confrontation with S-R behavior theory. In D. Horton & T. Dixon (Eds.), Verbal behavior and general behavior theory (pp. 340–387). Englewood Cliffs, NJ: Prentice-Hall.

  Falk, E. B., Berkman, E. T., Whalen, D., & Lieberman, M. D. (2011). Neural activity during health messaging predicts reductions in smoking above and beyond self-report. Health Psychology, 30, 177–185.

  Fielding, K. S., McDonald, R., & Louis, W. R. (2008). Theory of planned behaviour, identity and intentions to engage in environmental activism. Journal of Environmental Psychology, 28, 318–326.

  Finlay, K. A., Trafimow, D., & Moroi, E. (1999). The importance of subjective norms on intentions to perform health behaviors. Journal of Applied Social Psychology, 29, 2381–2393.

  Fishbein, M. (1963). An investigation of the relationships between beliefs about an object and the attitude toward that object. Human Relations, 16, 233–240.

  Fishbein, M. (1967). Attitude and the prediction of behavior. In M. Fishbein (Ed.), Readings in attitude theory and measurement (pp. 477–492). New York, NY: Wiley.

  Fishbein, M. (2000). The role of theory in HIV prevention. AIDS Care, 12, 273–278.

  Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.

  Fishbein, M., & Ajzen, I. (2010). Predicting and changing behavior: The reasoned action approach. New York, NY: Psychology Press.

  Fishbein, M., & Stasson, M. (1990). The role of desires, self-predictions, and perceived control in the prediction of training session attendance. Journal of Applied Social Psychology, 20, 173–198.

  Fishbein, M., & Yzer, M. C. (2003). Using theory to design effective health behavior interventions. Communication Theory, 13, 164–183.

  Gibbons, F. X., Gerrard, M., Blanton, H., & Russell, D. W. (1998). Reasoned action and social reaction: Willingness and intention as independent predictors of health risk. Journal of Personality and Social Psychology, 74, 1164–1180.

  Giles, M., Liddell, C., & Bydawell, M. (2005). Condom use in African adolescents: The role of individual and group factors. AIDS Care, 17, 729–739.

  Gollwitzer, P. M. (1999). Implementation intentions: Strong effects of simple plans. American Psychologist, 54, 493–503.

  Gollwitzer, P. M., & Sheeran, P. (2006). Implementation intentions and goal achievement: A meta-analysis of effects and processes. Advances in Experimental Social Psychology, 38, 69–119.

  Hagger, M. S., Chatzisarantis, N. L. D., & Biddle, S. J. H. (2002). A meta-analytic review of the theories of reasoned action and planned behavior in physical activity: Predictive validity and the contribution of additional variables. Journal of Sport and Exercise Psychology, 24, 3–32.

  Hale, J. L., Householder, B. J., & Greene, K. L. (2002). The theory of reasoned action. In J. P. Dillard & M. Pfau (Eds.), The persuasion handbook: Developments in theory and practice (pp. 259–286). Thousand Oaks, CA: Sage.

  Huebner, D. M., Neilands, T. B., Rebchook, G. M., & Kegeles, S. M. (2011). Sorting through chickens and eggs: A longitudinal examination of the associations between attitudes, norms, and sexual risk behavior. Health Psychology, 30, 110–118.

  Jacobson, R. P., Mortensen, C. R., & Cialdini, R. B. (2011). Bodies obliged and unbound: Differentiated response tendencies for injunctive and descriptive social norms. Journal of Personality and Social Psychology, 100, 433–448.

  Keats, M. R., Culos-Reed, S. N., Courneya, K. S., & McBride, M. (2007). Understanding physical activity in adolescent cancer survivors: An application of the theory of planned behavior. Psycho-oncology, 16, 448–457.

  Kiviniemi, M. T., Voss-Humke, A. M., & Seifert, A. L. (2007). How do I feel about the behavior? The interplay of affective associations with behaviors and cognitive beliefs as influences on physical activity behavior. Health Psychology, 26, 152–158.

  Kraft, P., Rise, J., Sutton, S., & Røysamb, E. (2005). Perceived difficulty in the theory of planned behaviour: Perceived behavioural control or affective attitude? British Journal of Social Psychology, 44, 479–496.

  Larimer, M. E., Turner, A. P., Mallett, K. A., & Geisner, I. M. (2004). Predicting drinking behavior and alcohol-related problems among fraternity and sorority members: Examining the role of descriptive and injunctive norms. Psychology of Addictive Behaviors, 18, 203–212.

  Lee, C., & Green, R. T. (1990). A cross-cultural examination of the Fishbein behavioral intention model. Journal of International Business Studies, 22, 289–305.

  Lutchyn, Y., & Yzer, M. (2011). Applying Temporal Construal Theory to the Theory of Planned Behavior to examine time frame effects on belief generation. Journal of Health Communication, 16, 595–606.

  Newell, S., Girgis, A., Sanson-Fisher, R. W., & Savolainen, N. J. (1999). The accuracy of self-reported health behaviors and risk factors relating to cancer and cardiovascular disease in the general population: A critical review. American Journal of Preventive Medicine, 17, 211–229.

  Norman, P., & Conner, M. (2005). The Theory of Planned Behavior and exercise: Evidence for the mediating and moderating roles of planning on intention-behavior relationships. Journal of Sport and Exercise Psychology, 27, 488–504.

  Norman, P., & Hoyle, S. (2004). The theory of planned behavior and breast self-examination: Distinguishing between perceived control and self-efficacy. Journal of Applied Social Psychology, 34, 694–708.

  Pertl, M., Hevey, D.,
Thomas, K., Craig, A., Ni Chuinneagain, S., & Maher, L. (2010). Differential effects of self-efficacy and perceived behavioral control on intention to perform skin cancer related health behaviors. Health Education Research, 25, 769–779.

  Rhodes, R. E., & Courneya, K. S. (2003). Investigating multiple components of attitude, subjective norm, and perceived control: An examination of the theory of planned behaviour in the exercise domain. British Journal of Social Psychology, 42, 129–146.

  Rice, R. E., & Atkin, C. K. (2009). Public communication campaigns: Theoretical principles and practical applications. In J. Bryant & M. B. Oliver (Eds.), Media effects: Advances in theory and research (3rd ed., pp. 436–468). New York, NY: Routledge.

  Rivis, A., & Sheeran, P. (2003). Descriptive norms as an additional predictor in the theory of planned behaviour: A meta-analysis. Current Psychology, 22, 218–233.

  Rodgers, W. M., Conner, M., & Murray, T. C. (2008). Distinguishing among perceived control, perceived difficulty, and self-efficacy as determinants of intentions and behaviours. British Journal of Social Psychology, 47, 607–630.

  Sheeran, P., & Orbell, S. (1998). Do intentions predict condom use? Meta-analysis and examination of six moderator variables. British Journal of Social Psychology, 37, 231–250.

  Sheeran, P., Orbell, S., & Trafimow, D. (1999). Does the temporal stability of behavioral intentions moderate intention-behavior and past behavior-future behavior relations? Personality and Social Psychology Bulletin, 25, 721–730.

  Sheeran, P., & Taylor, S. (1999). Predicting intentions to use condoms: A meta-analysis and comparison of the theories of reasoned action and planned behavior. Journal of Applied Social Psychology, 29, 1624–1675.

  Sheppard, B. H., Hartwick, J., & Warshaw, P. R. (1988). The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. Journal of Consumer Research, 15, 325–342.