Behavioral Research

Table of Contents
1 Description & Theoretical Background
2 Measurement and Methodological Issues

Type of Behavior as a Moderator of the Intention - Behavior Relation


Other Proximal Antecedents: Implementation Intentions, Behavioral Expectation, and Behavioral Willingness


Behavioral Intention vs. Behavioral Expectation vs. Behavioral Willingness

6 References
7 Measures Appendix
8 Published Examples

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Other Constructs



Dispositional Optimism




Illness Representations

  Implementation Intentions
  Intention, Expectation, and Willingness
  Normative Beliefs
  Optimistic Bias
  Perceived Benefits
  Perceived Control
  Perceived Severity
  Perceived Vulnerability
  Self-Reported Behavior
  Social Influence
  Social Support

Intention, Expectation, and Willingness
Frederick X. Gibbons

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3 Type of Behavior as a Moderator of the Intention - Behavior Relation

Perhaps the most important moderator of the BI / behavior relation is the nature of the behavior involved. In particular, four dimensions of behavior influence the predictive power of the BI construct: a) perceived behavioral control, b) complexity, c) social desirability, and d) social involvement.

Perceived behavioral control. Recognizing that perceived ability to perform a particular behavior, or achieve a certain goal may influence whether the behavior actually occurs, Ajzen (1991) developed the TPB, which adds a self-efficacy component to the TRA, called perceived behavioral control (see Measures). When perceived and actual control are high, BI should relate directly to outcome. When the behavior is difficult, however—sticking to a diet, for example, or avoiding fatty foods—intentions may be high, but ability may be a step or two lower. Meta-analyses have suggested that this additional construct adds about 2% on average to the percentage of variance accounted for in behavior (Armitage & Conner, 2001). That amount does vary considerably, however, depending on the actual difficulty involved—up to a high of 12% for behaviors such as quitting smoking, which are very difficult (Godin, Valois, Lepage, & Desharnais, 1992).

Complexity. Multiple-act criteria, i.e., behaviors that require a series of actions to complete (e.g. fecal occult blood test or FOBT), are more difficult to predict than are less complex behaviors. One reason for this is that people tend to overestimate the likelihood that they will successfully complete all of the actions in the series, when failure to complete any one of them stops the behavior. Thus, intentions don't do as good a job (relatively speaking) in predicting complex behaviors like screening for cancer. For example, Godin and Kok (1996) and McEachan and Conner (2005) both found that BI explained about 16% of the variance in screening behavior, meaningfully lower than researchers typically observe for other (less complex) behaviors.

Social desirability. Ajzen and Fishbein (2005) refer to the issue of poor BI "performance" as "literal inconsistency" - the tendency for people to not do what they said they were going to do. This is especially likely when the behavior is very high or very low in social desirability. Most instances of poor BI prediction involve the former: reports of intentions to do appropriate behaviors that don't actually result in action. For example, Sheeran (2002) reported that people who say they do not intend to engage in cancer screening very seldom do (what he calls "behavioral inertia"); however, a significant percentage of those who give the socially desirable response—"I intend to screen"—do not follow through. More generally, Sheeran found across a variety of health behaviors, that the median percentage of people who said they did not intend to "do the right thing" and did not was 93%, whereas about half of those who said they had good intentions never acted on those intentions. Presumably, the same problem exists, in reverse, for undesirable behaviors—low reported BI, but performance nonetheless. A recent meta-analysis (Webb & Sheeran, 2006) addressed this issue, by looking at health risk as well as health promotion behaviors.

Social involvement. Webb and Sheeran (2006) conducted a meta-analysis of the BI / health behavior relation, examining only those studies (N = 47) that included longitudinal measures of BI and behavior, and involved an intervention intended to change the former (BI), in an effort to then change the latter. They concluded that changes in health intentions had a smaller impact on changes in health behavior (i.e., Δ BI / Δ behavior relations were weaker) when: a) the gap between measurement of BI and behavior was relatively long (greater than the median of 11.5 weeks), b) the behavior included a significant habitual component (e.g., seat belt use), c) perceived and actual control were low, and d) the behaviors involved health risk (as opposed to health promotion) and were performed in "social contexts" (e.g., smoking, condom use). The authors concluded that intentional control over health behavior is more limited than previously thought. They also recommend that future behavior change efforts give greater consideration to non-intentional routes to health behavior that include health images or prototypes (see Gibbons & Gerrard, 1997) and "automatic" (i.e., situationally-controlled) processes.

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