Behavioral Research

Table of Contents
1 Description & Theoretical Background
2 Measurement and Methodological Issues
3 Type of Behavior as a Moderator of the Intention - Behavior Relation
4

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

5

Behavioral Intention vs. Behavioral Expectation vs. Behavioral Willingness

6 References
7 Measures Appendix
8 Published Examples

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Other Constructs
 

Barriers

 

Dispositional Optimism

 

Environments

 

Illness Representations

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

Intention, Expectation, and Willingness
Frederick X. Gibbons

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4

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

In an effort to reduce the "literal inconsistency" problem (the inconsistency between what people say and what they do) and therefore increase the observed relation between proximal antecedents and behavior, researchers have explored other types of proximal measures.

Implementation Intentions
One way to increase the predictive power of intentions is to make them more concrete; i.e., add items regarding the specific ways in which the behavior may be performed, or the goal attained. In other words, ask about when the behavior will be performed, as well as where and how it will take place, what Gollwitzer (1999) calls implementation intentions (see examples in Measures). Adding these specifics has been shown to increase the likelihood that intentions to engage in behaviors, such as maintaining a healthy diet (Verplanken & Faes, 1999), or engaging in breast self-examination (Orbell & Sheeran, 2000) will predict those behaviors—in part because it increases the likelihood that the behaviors will actually be performed (for a general review of implementation intention research, see Gollwitzer & Sheeran, in press). Forming these types of intentions is likely to be most important for health behaviors that are complex, and clearly linked with situational cues or prompts.

Behavioral Expectations
Intentions are defined as plans or goals. People oftentimes fall short of achieving their goals, however, which raises the question of whether respondents take this into account when stating their intentions. Assuming they often do not, Warshaw and Davis (1985) created the construct of behavioral expectation (BE), which they define as an estimate, or subjective probability, that a behavior will actually be performed (see Measures). Whereas BI is a plan, BE is a prediction. Theoretically, when answering BE items, people will take into account additional influential factors—circumstances, past behavior, anticipated change in intentions or circumstances—that might not enter into expressions of goals. Thus, BE should work better for behaviors that are undesirable and/or difficult; and there is some evidence of this (e.g., speeding; cf. Parker et al., 1992). Meta-analyses, however, have produced mixed support. Some have shown a slight, but significant superiority of BE for difficult or socially undesirable behaviors (Courneya & McAuley, 1994; Sheppard et al., 1988); others report no difference (Sheeran & Orbell, 1998; Webb & Sheeran, 2006). One reason for this is that people are not very good at estimating the impact of influential factors that are presumably considered when forming expectations: peer pressure and past behavior, for example; nor are they very good at estimating or anticipating changes in circumstances or in intentions. Thus, BE and BI often end up looking very similar (Conner & Sparks, 1996).

Many researchers have chosen to use BI and BE interchangeably. A meta-analysis of 154 TPB studies (Armitage & Conner, 2001) found that only 20 used straight BI measures; 40 used BE measures, and 88 used a combination of the two. Moreover, Davis and Warshaw (1992) present some evidence to suggest that people often report their expectations when answering BI questions. Clearly, there is a conceptual difference between behavioral goals and behavioral estimations—any smoker who has tried and failed to quit would attest to this. Similarly, asking a repeat DWI offender if s/he expects to drink and drive vs. whether s/he has a plan (or a goal) to drink and drive will result in very different responses. Empirically, however, the relative predictive validity of BE vs. BI measures for different types of behavior has not been clearly established (Webb & Sheeran, 2006); more research is needed.

Behavioral Willingness
When asked, most adolescents say they have no intention of engaging in behaviors that put their health at risk; and yet, when given the opportunity, many of them do (Gibbons, Gerrard, Reimer, & Pomery, 2006). This is one reason why intentions are less effective at predicting adolescent behavior (Albarracín et al., 2001; Sheeran & Orbell, 1998), or behavior that involves health risk (Webb & Sheeran, 2006). In an effort to improve this type of prediction, Gibbons and Gerrard (1997); Gibbons, Gerrard, & Lane, 2003; in press) developed the prototype / willingness (prototype) model of health behavior. The basic contention of the model is that much health risk behavior (binge drinking, risky sex), especially among adolescents, is not intentional, but rather a reaction to social circumstances.

To capture this unintentional, reactive component of risky behavior, Gibbons and Gerrard created the construct of behavioral willingness (BW), which they define as an openness to risk opportunity—what an individual would be willing to do under some circumstances. To assess BW ( see Measures), risk-conducive situations are described, along with the qualifier that no assumptions are being made about whether the respondent would ever be in (or seek out) these types of situations. The intent is to avoid implied internal attribution or "blame." After describing the situation, a series of possible responses is described, which increase in level of risk. The aggregated total provides an assessment of what kinds of risky behavior the respondent is capable of performing—if they encounter the opportunity.

BW is highly correlated with BI, but still consistently explains additional amounts of variance in behavior—from 2% to > 10% (see Gibbons et al., 2003, for reviews). Moreover, as might be expected, BW is usually a better predictor than BI of health risk behavior for adolescents (Gerrard Gibbons, Stock, Dykstra, & Houlihan, 2005; Gibbons, Gerrard, Ouellette, & Burzette, 1998; Gibbons et al., 2004); then, with age and experience, BE and BI eventually exceed BW (Pomery, Gibbons, Gerrard, & Reis-Bergan, 2005). Nonetheless, there are certain risky behaviors that, for many people remain "opportunistic" throughout life—adultery, for example, or risky sex, drunk driving, or recreational drug use.

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