does state versus action orientation moderate the intention-behavior relationship?

Does State Versus Action Orientation Moderate the Intention-Behavior Relationship?

PAUL NORMAN] AND PASCHAL SHEERAN University of Shefield, UK Shefield, United Kingdom

SHEINA ORBELL University of Essex, UK

Colchester; United Kingdom

According to Kuhl’s (1 985) theory of action control, action-oriented individuals should be more likely to translate their intentions into action than state-oriented individuals. The present study considered the moderating role of state vs. action orientation on intention- behavior relations across 30 behaviors. Respondents ( N = 2 11) completed questionnaires assessing their intentions to perform each of the 30 behaviors and state vs. action orientation. Two weeks later, respondents completed a second questionnaire to assess performance of the 30 behaviors. Between-subjects and within-subjects analyses both failed to provide support for the moderating role of state vs. action orientation, although a more detailed analysis revealed that state-oriented individuals were more likely to act on their intentions in the case of behaviors that were under nonnative control. The results are dis- cussed in relation to Kuhl’s theory of action control and the need to focus on a range of volitional processes when addressing the intention-behavior gap.

The theory of reasoned action (TRA; Ajzen & Fishbein, 1980) has been used extensively to predict intentions and behavior. According to Ajzen and Fishbein, the proximal determinant of behavior is the person’s intention to perform the behavior (e.g., “I intend to go to the gym next week”). This construct represents a person’s motivation to perform the behavior, and those with strong intentions are likely to expend more effort to enact their intention. Intention, in turn, is determined by two constructs; first, the person’s attitude toward the behavior, which refers to the person’s evaluation of performing the behavior (e.g., “My going to the gym next week would be good/bad”), and second, subjective norm, which refers to the perceived social pressure to perform or not perform the behavior (e.g., “People who are important to me think I should/should not go to the gym next week”). The relative weights attached to these two constructs are likely to

]Correspondence concerning this article should be addressed to Paul Norman, Department of Psychology, University of Sheffield Sheffield S10 ZTP, United Kingdom. E-mail: p.norman@sheffield.ac.uk

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Journal of Applied Social Psychology, 2003, 33, 3, pp. 536-553. Copyright 0 2003 by V. H. Winston & Son, Inc. All rights reSeNed.

STATE VERSUS ACTION ORIENTATION 537

vary for different intended behaviors. Thus, it is possible to distinguish between those behaviors that are under attitudinal control (i.e., behaviors for which attitude predicts intention better than does subjective norm) and those that are under normative control (i.e., behaviors for which subjective norm predicts intention better than does attitude; cf. Trafimow & Finlay, 1996).

A number of meta-analyses have attested to the predictive validity of the TRA. The attitude and subjective norm constructs have been found to explain between 40% and 50% of the variance in intention (Farley, Lehmann, & Ryan, 1981; Sheeran & Taylor, 1999; Sheppard, Hartwick, & Warshaw, 1988; Sutton, 1998; van den Putte, 1993). Intention, in turn, has been found to be a consistent, though moderate, predictor of behavior explaining between 19% and 38% of the variance in behavior (Ajzen, 1991; Conner & Armitage, 1998; Godin & Kok, 1996; Randall & Wolff, 1994; Sheeran & Orbell, 1998; Sheppard et al., 1988; van den Putte, 1993). However, despite these encouraging findings, a number of observations can be made about the strength and nature of the intention-behavior relationship (Sheeran, Orbell, & Trafimow, 1999). First, there is considerable het- erogeneity in the strength of the intention-behavior relationship across behaviors. For example, in their meta-analysis of research with the TRA, Sheppard et al. reported a large range of intention-behavior correlations, from . 10 (for being absent from work) to .96 (for having an abortion). Second, when past behavior is also measured, it typically adds to the amount of variance explained in behavior over and above intention (e.g., Yzer, Siero, & Buunk, 2001), thus questioning the sufficiency of the TRA (cf. Ajzen, 1991). Third, Sutton (1998) outlined a number of methodological factors (e.g., violation of scale correspondence, random measurement error, restricted variance) that might attenuate the strength of the intention-behavior relationship, although it is unlikely that in excess of 60% of the variance can be attributed to these factors.

Ajzen (1 985) noted that the TRA was only intended to be applied to the prediction of volitional behavior. However, the performance of many behaviors is not under complete volitional control, and this might serve to undermine the strength of the intention-behavior relationship. Ajzen therefore extended the TRA to include perceived behavioral control as an additional predictor of intention and behavior. Perceived behavioral control (PBC) refers to a person’s per- ception of the amount of control he or she has over performing the behavior (e.g., “My going to the gym next week would be easy/difficult”). When people’s per- ceptions of control are accurate, PBC should add to the prediction of behavior after controlling for intention. Ajzen and Madden (1986) presented evidence to support this proposition, and subsequent research has confirmed that PBC adds to the variance explained in behavior (e.g., Norman, Conner, & Bell, 2000). Nev- ertheless, meta-analyses indicate that intention and PBC together still only explain between 23% and 34% of the variance in behavior (Ajzen, 1991; Conner & Armitage, 1998; Godin & Kok, 1996).

538 NORMAN ET AL.

Another approach to the intention-behavior relationship has been the devel- opment of a number of models that distinguish between different stages in the ini- tiation, adoption, and maintenance of behavior (Heckhausen, 1991 ; Prochaska & DiClemente, 1984; Schwarzer, 1992; Weinstein, 1988). These models state that different cognitions should be important in the progression from one stage to another. While the number of stages outlined in the various stage models vary, it is possible to make a broad distinction between a motivational phase (i.e., intention formation) and a volitional phase (i.e., intention enactment; Armitage & Conner, 2000; Bagozzi, 1993; Gollwitzer, 1993; Kuhl, 1985). Models such as the TRA have been found to provide a strong prediction of people’s intentions (i.e., the motivational phase), but only a modest prediction of people’s behavior (i.e., the volitional phase). As Bagozzi argued, this suggests that intention is a necessary but not sufficient determinant of behavior. Therefore, other variables are required to predict the enactment of intentions, and recent theoretical work has addressed the cognitive mechanisms through which intentions are translated into action.

Important among these recent approaches is Kuhl’s (1 985) theory of action control. Kuhl outlined a number of volitional processes that can be used to initiate and maintain the performance of goal-directed behavior. When an intention is formed, it is subject to various internal and external influences that might encourage alternative action tendencies. For an intention to be translated into action, it must be strengthened and protected from these alternative action tendencies, and this might be achieved through the employment of a number of action control processes (i.e., active attentional selectivity, encoding control, emotion control, motivation control, environment control, parsimony of informa- tion processing). The efficiency of the action control processes in ensuring that an intention is translated into action is a function of whether the individual is action oriented versus state oriented. Individuals are action oriented when they simultaneously focus on their present state, their intended future state, the dis- crepancy between the two states, and possible action alternatives to reach the intended future state. Thus, action-oriented individuals engage in rapid decision making and focus on actions. Such activities are likely to facilitate goal achievement. In contrast, individuals who are state oriented focus exclusively on their present state or their intended future state and thereby fail to consider possible action alternatives to reach their intended future state. State-oriented individuals therefore hesitate before deciding to act and focus on goals. Such activities are likely to impair goal achievement.

Whether an individual is action oriented or state oriented is dependent on situational and dispositional factors. To measure the dispositional component of state orientation versus action orientation, Kuhl (1 985) developed the Action Control scale (ACS). State Orientation is characterized by an inability to initiate intended behavior because of preoccupation or hesitation, while action orientation is


characterized by a high capacity to engage the self-regulatory mechanisms necessary to enact one’s intentions. According to Kuhl, individuals who are action oriented are more likely to translate their intentions into action as a consequence of their greater self-regulatory capacities. Scores on the ACS, therefore, should moderate the relationship between intention and behavior such that stronger intention-behavior correlations should be obtained among action-oriented than among state-oriented individuals.

Kuhl (1 982) presented data to support this claim. German school children ( N = 48) were asked to rate their intentions to perform a list of 22 after-school activities. The following day, they reported how much time they had actually spent performing each activity. In line with predictions, it was found that the intention-behavior correlations for action-oriented subjects were higher (.40 < r < 3 0 ) than were those obtained for state-oriented subjects (.30 < r < .40).

A number of other researchers also have tested the moderating role of state versus action orientation on intention-behavior relations. Kendzierski (1 990) considered the moderating role of state versus action orientation in two studies on exercise behavior. In the first study on exercise adoption, a significant intention- behavior correlation was found among action-oriented subjects (Y = .54, p < .Ol), whereas the same correlation among state-oriented subjects was nonsignificant (Y = .24, ns). A similar pattern of results was found in the second study on aerobic class attendance, with a stronger intention-behavior correlation found among action-oriented subjects (Y = .43, p < .05) than among state-oriented subjects (r =

.15, ns). However, while offering some support for the assertion that the intention- behavior correlation should be moderated by state versus action orientation, it is important to note that the difference between the intention-behavior correlations obtained for action- and state-oriented subjects was not statistically reliable in either study (Zs = 1.50 and 1.24, respectively, ns). Schifter and Ajzen (1985), in their study of weight loss, found that the interaction between intention and scores on the ACS (Kuhl, 1985) correlated with weight loss (r = .22, p < .05), indicating that the relationship between intentions and weight loss was stronger among action-oriented respondents.

It can be argued that previous tests of the moderating role of state versus action orientation have been less than optimal. For example, comparing the strength of intention-behavior correlation coefficients for state- and action- oriented subjects might confound group differences in variance or reliability of measures with true moderator effects (Baron & Kenny, 1986). A more appropriate test of the moderation hypothesis would involve the use of moderated regression analysis. Bagozzi, Baumgartner, and Yi (1992) used this technique to test the moderating role of state versus action orientation in relation to coupon use in the United States. They reported a nonsignificant beta weight for the interaction between intention and scores on the ACS (Kuhl, 1985), indicating that state versus action orientation did not moderate the intention-behavior relationship.

540 NORMAN ET AL.

The evidence for the moderating role of state versus action orientation on intention-behavior relations, therefore, is equivocal at best. However, all tests of the moderating role of state versus action orientation to date have been conducted using between-subjects analyses focusing on single behaviors. Given the principle of compatibility in measurement (Fishbein & Ajzen, 1975), it is not surpris- ing that a personality variable such as state versus action orientation is unable to predict the translation of intentions into action for specific behaviors. Rather, one might expect action-oriented subjects to exhibit stronger intention-behavior correlations across a range of behaviors, and this might be tested by utilizing within- subjects analyses (cf. Trafimow & Finlay, 1996). In other words, if action- oriented individuals have greater self-regulatory capacities, then one might expect to find a close correspondence between their intentions and behaviors across a range of behaviors. When individuals’ intentions and behaviors are assessed across a large number of behaviors, it is possible to compute an intention-behavior correlation for each individual (i.e., within-subjects correlation). The strength of this within-subjects correlation would be expected to correlate with scores on the ACS (Kuhl, 1985).

Another issue that needs to be considered is whether the influence of state versus action orientation is consistent across all behaviors. Kuhl (I 982) noted that while intention-behavior correlations were generally higher among action- oriented subjects, there were a number of after-school activities for which intention-behavior correlations were actually higher among state-oriented subjects. These behaviors tended to be socially prescribed behaviors, such as brushing one’s teeth and shining one’s shoes. Kuhl explained this contradictory finding by noting that such behaviors require little self-regulatory support and suggested that state-oriented individuals might have an increased tendency to engage in such externally controlled behaviors in order to compensate for their low self- regulatory capacities. This means that stronger intention-behavior correlations might be expected for state-oriented individuals for behaviors that are socially prescribed (i.e., under normative control), whereas stronger intention-behavior correlations might be expected for action-oriented individuals for behaviors that are self-determined (i.e., under attitudinal control). Fuhrmann and Kuhl (1 998) presented data that are consistent with these predictions. In a longitudinal study of compliance with nutritional recommendations, state-oriented individuals exhibited better compliance when an external authority made the recommendations, whereas action-oriented individuals exhibited better compliance when the recommendations were self-chosen. Kuhl and Kazen (1 994) presented similar findings for simulated office tasks.

A number of points can be drawn from the foregoing discussion. First, previous tests of the moderating role of state versus action orientation on the intention-behavior relationship have produced mixed findings. Second, tests of the moderator hypothesis to date have been conducted using between-subjects


analyses focusing on single behaviors. An alternative test of the moderating role of state versus action orientation would utilize within-subjects analyses in which the strength of the intention-behavior relationship is assessed across a range of behaviors. Third, no studies have tested Kuhl’s (1982) suggestion that the nature of the moderating effect of state versus action orientation might differ for behaviors that are under normative versus attitudinal control. The present study, therefore, seeks to test the moderating role of state versus action orientation on intention-behavior relations in a more comprehensive and rigorous manner than has been the case heretofore.

Participants were asked to indicate their intentions to perform 30 behaviors over the next 2 weeks and were followed up 2 weeks later. In line with Kuhl’s (1985) theory of action control, it is hypothesized that state versus action orientation will moderate intention-behavior relations for each of the 30 behaviors such that stronger intention-behavior relations will be found among action-oriented individuals than among state-oriented individuals. Moreover, it is hypothesized that within-subjects, intention-behavior correlations will correlate positively with scores on the ACS (Kuhl, 1985). Kuhl’s (1982) suggestion that the moderating role of state versus action orientation might vary according to whether the behavior is under normative or attitudinal control is examined also. It is hypothesized that for behaviors under attitudinal control, stronger intention-behavior relations will be found among action-oriented individuals than among state-oriented individuals, whereas for behaviors under normative control, stronger intention-behavior relations will be found among state-oriented individuals than among action-oriented individuals. Finally, it is hypothesized that when within- subjects intention-behavior correlations are computed separately for behaviors under attitudinal and normative control, a positive correlation will be obtained between the within-subjects correlations for attitudinally controlled behaviors and scores on the ACS, whereas a negative correlation will be obtained for normatively controlled behaviors.

Method

Participants and Procedure

A pilot study was conducted with a sample of 3 1 undergraduates at a United Kingdom university in order to identify a range of behaviors to be used in the main study and to identify the median level of performance of these behaviors over a 2-week period. On the basis of this work, 30 behaviors were chosen (Table 1).

For the main study, the participants were 21 1 (145 females and 66 males) undergraduates at the same university who completed a questionnaire as part of a larger research project measuring TRA constructs in relation to the 30 behaviors

542 NORMAN ET AL.

Table 1

Multiple Linear Regression Analyses Predicting Intention (Beta Coeficients) and Moderated Logistic Regression Analyses Predicting Behavior (Regression Coefficients)

Predicting intention Predicting behavior

INT X

Behavior ATT SN INT AOD AOD

Attitudinally controlled behaviors 1. 2. 3. 4. 5. 6. 7.

8.

9. 10.

11.

12. 13.

14. 15.

16. 17.

18.

19.

Avoid eating meat 0.66*** 0.12* Eat fruit on at least 7 days 0.53*** 0.07 Go to the sports centre 0.58*** 0.18** Tidy room at least 3 times 0.53*** 0.21*** Go for a walk 0.55*** 0.25*** Avoid eating fast food 0.40*** 0.11 Read for pleasure for at least 3 hours 0.48*** 0.22*** Avoid getting drunk more than 2 times 0.46*** 0.21*** Buy a magazine 0.47*** 0.24*** Go to a nightclub at least 2 times 0.54*** 0.34*** Write at least 2 letters to family/friends 0.52*** 0.32*** Go shopping with a friend 0.42*** 0.22*** Do at least 20 hours of independent study 0.50*** 0.3 1 *** Buy a newspaper 0.46*** 0.27*** Avoid sleeping in past 9:OO a.m. on more than 2 weekdays 0.36*** 0.21** Rent a video 0.36*** 0.22*** Go to the library to study at least 4 times 0.47*** 0.34*** Exercise at least 6 times 0.46*** 0.37*** Take bottles to bottle bank 0.36*** 0.27***

1.08*** -0.22 0.02 1.13*** 0.02 0.11 0.67*** 0.12 -0.04 0.73*** 0.07 0.05 0.87*** -0.09 -0.02 0.57*** -0.04 0.06

0.64*** 0.19** -0.01

0.45*** 0.03 0.00 0.53*** 0.05 0.02

0.77*** -0.05 -0.05

0.86*** 0.14 -0.04 0.71*** 0.10 -0.02

0.72*** 0.09 -0.04 0.79*** 0.08 -0.06

0.22*** 0.01 0.00 0.44*** 0.01 0.01

0.63*** 0.07 -0.07 0.63*** 0.20"" -0.03 0.83*** -0.18, 0.12

(table continues)


Table 1 (Continued)

Predicting intention Predicting behavior

INT X

Behavior ATT SN INT AOD AOD

Normatively controlled behaviors 20. 21.

22. 23. 24. 25. 26. 27. 28.

29. 30.

Avoid smoking cigarettes 0.35*** 0.29*** Go to the pub at least 4 times 0.39*** 0.40*** Attend all lectures 0.25*** 0.26*** Visit the countryside 0.33*** 0.39*** Buy new clothes 0.22*** 0.31*** Take vitamin pills 0.31*** 0.45*** Go to the cinema 0.22*** 0.39*** Go out for a meal 0.24*** 0.43*** Get at least 7 hours sleep on every weekday 0.08 0.30*** Visit friends at least 3 times 0.24*** 0.47*** Go home to visit parents 0.15* 0.47***

0.54*** 0.04 -0.04

0.84*** -0.11 -0.07 0.96*** -0.08 0.13 0.68*** 0.06 -0.06 0.32*** 0.03 -0.03 1.09*** 0.06 -0.10* 0.35*** 0.08 -0.02 0.39*** 0.04 0.03

0.75*** 0.10 -0.03 0.69*** -0.05 0.01 0.68*** 0.00 0.03

Note. ATT = attitude, SN = subjective norm, INT = intention, AOD = decision-related action versus state orientation. *p < .05. **p < .01. ***p < .001.

and state versus action orientation. The participants completed a second questionnaire 2 weeks later in which they reported their behavior.

Measures

Responses to all of the TRA items were on 7-point scales. For each of the 30 behaviors, intention to perform the behavior was assessed using an item stem with two response formats: “I intend to perform the behavior the next 2 weeks . . . strongly disagreelstrongly agree; definitely don ’tldefinitely do.” Internal reliabili- ties for the measures of intention were high (Mdn a = .97). Three semantic differ- ential scales were used to provide a direct measure of attitude toward each of the 30 behaviors: “Performing the behavior over the next 2 weeks would be . . . men- joyablelenjoyable, badlgood, unpleasantlpleasant” (Mdn a = .92). To provide a direct measure of subjective norm for each of the 30 behaviors, an item stem was presented with two response formats: “Most people who are important to me think I should perform the behavior over the next 2 weeks . . . strongly disagree1 strongly agree, unfikelyllikely” (Mdn a = .92).

544 NORMAN ET AL.

Action Orientation versus state orientation was measured using the AOD (prospective and decision-related action orientation vs. hesitation) subscale of the ACS (Kuhl, 1994). The scale consists of 12 forced-choice items with one response reflecting state orientation (SO) and the other reflecting action orientation (AO). For example, “When I am facing a big project that has to be done: (a) I often spend too long thinking about where I should begin (SO); or (b) I don’t have any problems getting started (AO).” Responses to the 12 items are summed, with high scores indicating action orientation. The scale was found to have satis- factory internal reliability (a = .74).

Future behavior was measured in the Time 2 questionnaire. For each of the 30 behaviors, participants were asked to indicate whether or not they had performed the behavior over the previous 2 weeks.

Results

Between-Subjects Analyses: All Behaviors

We first employed moderated regression analyses to test the hypothesis that state versus action orientation would moderate intention-behavior relations for each of the 30 behaviors (Baron & Kenny, 1986). Logistic regressions were used since the behavior measures were dichotomous and therefore violated the assumption of normally distributed errors made by multiple linear regression. For each behavior, future behavior was regressed onto intention, AOD scores (Kuhl, 1994), and the interaction between intention and AOD scores. The measures were mean-centered before computing interaction terms in order to minimize any problems with multicollinearity and to aid the interpretation of significant interaction terms (Aiken & West, 1991). Significant regression coefficients for the Intention x AOD interaction terms would indicate a moderating role for state versus action orientation, with positive regression coefficients indicating that high AOD scores (i.e., action orientation) tend to increase the strength of intention- behavior relationships.

The regression coefficients from the moderated logistic regression analyses for the 30 behaviors are presented in Table 1. In line with the TRA, the intention measure was found to be a significant predictor of hture behavior for each of the 30 behaviors. Point biserial correlations between the intention and behavior measures indicate that intention explained between 6% and 60% of the variance in behavior (Mdn r2 = .23). AOD scores were found to be predictive of future behavior in two cases, with action-oriented individuals being more likely to perform the behaviors under consideration. Contrary to predictions, only 1 of the 30 Intention x AOD interactions emerged as a significant predictor of behavior. Moreover, the regression coefficient was negative, indicating that for taking vitamin pills, low AOD scores (i.e., state orientation) tended to increase the strength of the intention-behavior relationship.


Within-Subjects Analyses: All Behaviors

The moderating role of state versus action orientation on the intention- behavior relationship was examined further using within-subjects analyses. A within-subjects correlation was first computed between intention scores and future behavior across the 30 behaviors for each subject. The median within- subjects correlation between intention and behavior was .56. The correlation between the r-to-Z transformations of the intention-behavior correlations and AOD scores was then computed. A significant positive correlation would indicate that participants with high AOD scores (i.e., action oriented) exhibit a stronger relationship between their intentions and future behavior. However, contrary to predictions, the correlation was nonsignificant (r = -.02, ns).

Between-Subjects Analyses: Attitudinally Versus Normatively Controlled Behaviors

In order to test the hypothesis that the moderating role of state versus action orientation on intention-behavior relations should vary according to whether behavior is under attitudinal or normative control, we first conducted between- subjects regressions of intention onto attitude and subjective norm for each of the 30 behaviors. Behaviors for which the attitude beta weight was higher than the subjective norm beta weight were deemed to be under attitudinal control, whereas behaviors for which the subjective norm beta weight was higher than the attitude beta weight were deemed to be under normative control (cf. Trafimow & Finlay, 1996).

The 30 behaviors are presented in Table 1 in order of the size of the difference between the beta coefficient for attitudes and subjective norms. The first 20 behaviors were deemed to be under attitudinal control, whereas the last 10 behaviors were deemed to be under normative control. Further analyses confirmed this classification procedure. The mean attitude beta weight for attitudinally controlled behaviors was significantly stronger than that for normatively controlled behaviors (.47 vs. .24), t(28) = 7 . 0 5 , ~ < .001; whereas the mean subjective norm beta weight for normatively controlled behaviors was significantly stronger than that for attitudinally controlled behaviors (.39 vs. .24), t(28) = 4 . 9 3 , ~ < ,001. In addition, the size of the difference between attitude and subjective norm beta weights for attitudinally and normatively controlled behaviors was statistically reliable (.23 vs. -.14), t(28) = 8 . 3 2 , ~ < .001. Considering the prediction of behavior, only one of the Intention x AOD interaction terms was significant. This was for taking vitamin pills, and the regression coefficient was negative, indicating that low AOD scores (i.e., state orientation) tended to increase the strength of the intention-behavior relationship. This finding is in line with predictions, since taking vitamin pills is a normatively controlled behavior.

546 NORMAN ET AL.

Within-Subjects Analyses: Attitudinally Ersus Normatively Controlled Behaviors

The moderating role of state versus action orientation on intention-behavior relations for attitudinally and normatively controlled behaviors was then tested using within-subjects analyses. For each participant, a within-subjects correlation was computed between their intention scores and future behavior for the 20 behaviors under attitudinal control and for the 10 behaviors under normative control. The median within-subjects intention-behavior correlation was .57 for attitudinally controlled behaviors and .52 for normatively controlled behaviors. The correlation between the r-to-Z transformations of the intention-behavior correlations and AOD (Kuhl, 1994) scores was then computed separately for behaviors under attitudinal and normative control. It was hypothesized that a positive correlation would be found between the within-subject intention-behavior correlations for attitudinally controlled behaviors and AOD scores, while a negative correlation would be found for normatively controlled behaviors. The correlation for attitudinally controlled behaviors was positive but nonsignificant (r = .03, ns). In contrast, the correlation for normatively controlled behaviors was negative and statistically significant ( r = -.13, p < .05, one-tailed), indicating that those with low AOD scores (i.e., state oriented) exhibited a stronger intention-behavior relationship for normatively controlled behaviors. The difference between the size of the correlation coefficients obtained for attitudinally versus normatively controlled behaviors was statistically reliable, t(208) = 1.72, p < .05, one-tailed.2

Discussion

The present study sought to assess the moderating role of state versus action orientation on intention-behavior relations across 30 behaviors. According to Kuhl’s (1985) theory of action control, individuals who are action oriented should

*Most previous tests of the moderating role of state versus action orientation on the intention- behavior relationship have used the AOD subscale (Kuhl, 1994) of the Action Control scale (ACS). However, we also analyzed the data using both the AOD (prospective and decision-related action orientation vs. hesitation) and AOF (action orientation subsequent to failure vs. preoccupation) sub- scales, as suggested by Kuhl. The pattern of results remained unchanged. Only one of the interactions in the between-subjects moderated regression analyses was significant (0 = -.05, p < .05), indicating that for taking vitamin pills, low ACS scores (i.e., state orientation) tended to increase the strength of the intention-behavior relationship. Considering the within-subjects analyses, the correlation between the strength of the intention-behavior correlation and ACS scores was nonsignificant ( r = -.04, ns). When within-subjects correlations were computed separately for attitudinal and normative behaviors and correlated with ACS scores, the correlation for attitudinally controlled behaviors was nonsignificant (Y = .04, as), whereas the correlation for normatively controlled behaviors was statistically significant (r = -.13, p < .05, one-tailed). The difference between the size of the correlation coefficients obtained for attitudinal and normative behaviors was statistically reliable, t(208) = I .79,p < .05, one- tailed.


be more likely to translate their intentions into action. This proposition was tested using a series of between-subjects moderated regression analyses in which behavior was regressed onto intention, AOD (Kuhl, 1994) scores, and the interaction between intention and AOD scores. The results of the 30 analyses provided little support for the moderating role of state versus action orientation. Only one interaction term was found to be significant, and this indicated that the intention- behavior relationship was stronger among state-oriented individuals. Moreover, given the number of tests conducted, it is possible that even this finding might be a chance result. The present results, therefore, are in line with a number of previous studies that have failed to find strong evidence for the moderating role of state versus action orientation on the intention-behavior relationship for specific behaviors (Bagozzi et al., 1992; Kendzierski, 1990; Schifter & Ajzen, 1985).

One difficulty with previous tests of the moderating role of state versus action orientation is that they have attempted to use a personality variable as a moderator of intention-behavior relationships for specific behaviors. Such analyses might underestimate the moderating role of state versus action orientation, given the principle of compatibility in measurement. Therefore, we conducted a within- subjects analysis in which intention-behavior correlations were computed across the 30 behaviors for each individual. If action-oriented individuals have greater self-regulatory capacities, one would expect a close correspondence between their intentions and behavior across a range of behaviors. However, contrary to predictions, the correlation between the strength of the within-subjects intention- behavior correlation and AOD scores was close to 0 and nonsignificant. Overall, the results of both between-subjects and within-subjects analyses failed to support Kuhl’s (1 985) proposition that state versus action orientation moderates the intention-behavior relationship.

It was hypothesized further that for behaviors that are under attitudinal control, strong intention-behavior relations might be expected only among action-oriented individuals. In contrast, for behaviors that are under normative control, stronger intention-behavior relations might be expected among state-oriented individuals. For the 20 behaviors that were identified as being under attitudinal control, moderated regression analyses reveal that only 9 had positive interaction terms, and none were statistically significant. For the 10 normatively controlled behaviors, 6 had negative interaction terms, only 1 of which was significant. Kuhl’s (1 982) proposition was tested hrther using within-subjects analyses. The strength of the intention-behavior correlation was computed separately for attitudinally and normatively controlled behaviors for each subject. These within-subjects correlations were then correlated with AOD (Kuhl, 1994) scores. Whereas the correlation was positive but nonsignificant for attitudinally controlled behaviors, the correlation for normatively controlled behaviors was significant and negative. Importantly, the difference in the size of the correlations obtained for attitudinally versus normatively behaviors was statistically reliable. However, it should be noted that this

548 NORMAN ET AL.

is a weak effect, with the difference between the size of the two correlations only becoming statistically reliable when a one-tailed test is used. Nevertheless, the present results indicate that the within-subjects intention-behavior correlation tends to be stronger among state-oriented individuals in the case of normatively controlled behaviors, thus providing some preliminary support for Kuhl’s (1982) suggestion that state-oriented individuals engage in such behaviors as a way of overcoming deficits in self-regulatory capacity.

It is possible to speculate further that state-oriented individuals might be particularly responsive to normative influences. For example, Bagozzi et al. (1992) reported that the subjective norm-intention relationship was stronger among state-oriented individuals than among action-oriented individuals. In addition, both the present results and previous research findings suggest that state-oriented individuals might exhibit enhanced enactment of goals recommended by others (Fuhrmann & Kuhl, 1998; Kuhl & Kazen, 1994). State-oriented individuals might regulate their behavior through a controlled (Ryan, Sheldon, Kasser, & Deci, 1996) or social reaction (Gibbons, Gerrard, Ouellette, & Burzette, 1998) pathway in which they respond to immediate situational demands rather than attempt to integrate socially prescribed goals into their self-representations (Kuhl & Kazin, 1994). In this way, state orientation might have some overlap with Synder’s (1 974) concept of self-monitoring (i.e., the extent to which individuals regulate their behavior to correspond with immediate situational or social cues). Indeed, Bagozzi et al. reported a moderate negative correlation (Y = -.37, p < .01) between scores on the ACS (Kuhl, 1985) and self-monitoring.

Interestingly, Prislin and Kovrlija (1992) found that the intentions of high self-monitors were predicted best by subjective norms, whereas the intentions of low self-monitors were predicted best by attitudes. In addition, Miller and Grush (1986) presented evidence to suggest that whereas individuals low in self- monitoring and high in private self-consciousness exhibit greater attitude- behavior correspondence, individuals with other combinations of these traits exhibit greater subjective-norm-behavior correspondence. Given the relatively weak impact on state versus action orientation on intention-behavior relations, it might be necessary to explore the moderating role of other personality traits (Abraham, Norman, & Conner, 2000). In addition to self-monitoring and self- consciousness, future work could focus on individual differences in conscien- tiousness (McCrae & Costa, 1987), as well as assessment and locomotion aspects of self-regulation (Kruglanski et al., 2000).

The present study has a number of limitations indicating that conclusions must be drawn with some caution. First, the follow-up period in the present study was only 2 weeks. It might be the case that longer periods of time are required to assess the impact of action versus state orientation on intention-behavior relations. For example, over longer periods of time, intentions are more likely to need to be protected from competing action tendencies. In addition, initiative might be


needed to overcome the inertia and inhibition that could result from waiting to identify appropriate opportunities for the enactment of uncompleted intentions. As these are tasks that require high self-regulatory capacities, one would expect the impact of action versus state orientation on intention-behavior relations to increase with the length of time between intention formation and action initia- tion. However, it should be noted that Kendzierski (1 990) failed to find evidence for the moderating role of action versus state orientation on intention-behavior relations for exercise adoption and aerobic class attendance that were measured over 8-week and 1 l-week periods, respectively.

Second, the present results suggest that action versus state orientation has only a weak influence on intention-behavior relations. However, this personality variable might have an indirect influence through the action control processes identified in Kuhl’s (1985) theory of action control. In short, Kuhl proposes that action-oriented individuals are more likely to engage in various action control processes that might be required to strengthen and protect intentions from alternative action tendencies and to aid the translation of intentions into action. There- fore, a more complete test of Kuhl’s theory of action control would need to measure the extent to which individuals engage in various action control processes when attempting to attain a goal in addition to the personality disposition of state versus action orientation. Fuhrmann and Kuhl (1 998) assessed a range of action control process and found that a number (i.e., attentional control, impulse control, motivational control and decision control) were related to enhanced enactment of nutritional intentions in response to potential opportunities. These findings are consistent with other theoretical and empirical work that has highlighted the importance of volitional processes and cognitions in bridging the intention-behavior gap (e.g., Bagozzi & Warshaw, 1990; Gollwitzer, 1993; Jones, Abraham, Harris, Schulz, & Chrispin, 2001). For example, a number of studies have demonstrated that forming an implementation intention (Gollwitzer, 1993) specifying when, where, and how the behavior is going to be performed is a pow- erful technique for translating intentions into action (Orbell, Hodgkins, & Sheeran, 1997; Sheeran & Orbell, 1999,2000).

Third, future behavior was measured by asking respondents to indicate whether or not they had performed the target behavior over the previous 2 weeks. For relatively frequent actions (e.g., exercise), a median level of performance was specified (e.g., 6 times) on the basis of pilot work. Sutton (1998) highlighted that under such circumstances, the marginal distributions of the predictor (i.e., intention) and criterion (i.e., future behavior) measures might be unequal, thereby reducing the amount of variance that can be explained in behavior. It is possible, therefore, that the present study provided a rather conservative test of the hypothe- ses under investigation, although further research is required to test this possibility.

Notwithstanding the aforementioned limitations, the present study has theoretical importance. First, the present study provides the only test to date of

550 NORMAN ET AL.

the moderating role of state versus action orientation on the intention-behavior relationship using within-subjects analyses. Second, the present study highlights the importance of distinguishing between behaviors that are under attitudinal versus normative control. Within-subjects analyses reveal that state versus action orientation moderated the intention-behavior relationship for normative behaviors such that state-oriented individuals were more likely to act on their intentions in the case of behaviors that were under normative control. However, further research is required to outline the various volitional processes that individuals engage in when enacting their intentions, particularly among state-oriented individuals with regard to the performance of normatively controlled behaviors.

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