Using Implementation Intentions to Increase Attendance for Cervical Cancer Screening

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1 Health Psychology Vol. 19. No Copyright 2000 by the American Piychohjgical Allocution, Inc /00/S100 DOT: «0278-«133.I Using Implementation Intentions to Increase Attendance for Cervical Cancer Screening Paschal Sheeran and Sheina Orbell University of Sheffield This article evaluates an intervention based on P.. Gollwitzer's (1993) concept of implementation intentions. Women registered at a medical practice in rural England (N = 114) completed measures of the theory of planned behavior variables before a manipulation that induced one half of the sample to form implementation intentions specifying when, where, and how they would make the appointment Subsequent attendance was determined from medical records. Findings show that the theory of planned behavior variables and previous delay behavior provided good prediction of attendance. However, despite equivalent motivation to attend, participants who formed implementation intentions were much more likely to attend for screening compared with controls (92% vs. 69%). Evidence also suggests that implementation intentions attenuated the relationship between previous delay behavior and subsequent attendance. Key words: implementation intentions, cervical cancer, screening, intervention A primary concern for health psychologists is predicting and understanding people's health-related behaviors. An approach that has had a good deal of success in this task is the theory of reasoned action (Fishbein & Ajzen, 1975) and its successor, the theory of planned behavior (Ajzen, 198S, 1991). According to these models, a person's intention to perform a behavior is the key predictor of behavioral performance. Prospective studies indicate that intentions predict a wide variety of health behaviors, including attempts to quit smoking (e.g., Borland, Owen, Hill, & Schofield, 1991; Norman, Conner, & Bell, 1999), condom use (e.g., Fisher, Fisher, & Rye, 1995; White, Terry, & Hogg, 1994), and cancer screening (e.g., De Vellis, Blalock, & Sandier, 1990; ontano & Taplin, 1991). eta-analytic reviews show that measures of intention generally account for 20%-30% of the variance in behavior (Ajzen, 1991; Conner & Armitage, 1998; Godin & Kok, 1996; Randall & Wolff, 1994; Sheeran & Orbell, 1998; Sheppard, Hartwick, & Warshaw, 1988). Although explaining 20%-30% of the variance in behavior is impressive, this finding also means that many people with positive intentions do not succeed in performing their intended behavior. That is, there is often a gap between people's intentions and their actual behavior. For example, Orbell and Sheeran (1998) found Paschal Sheeran and Sheina Orbell, Department of Psychology, University of Sheffield, Sheffield, United Kingdom. Sheina Orbell is now at the Department of Psychology, University of Essex, Essex, United Kingdom. We thank Erin arshall for her help in conducting the study and Sharon Parker for helpful comments on a draft of the article. Correspondence concerning this article should be addressed to Paschal Sheeran, Department of Psychology, University of Sheffield, Sheffield S10 2TP. United Kingdom. Electronic mail may be sent to p.sheeran@shefiield.ac.uk or to sorbell@essex.ac.uk. that only 43% of women who intended to attend for cervical screening actually did so during the following year. The aim of the present study is to address this problem using Gollwitzer's (1993; Gollwitzer & Brandstatter, 1997) concept of implementation intentions. In particular, we examine whether intentions to attend for cervical screening that have been supplemented by implementation intentions specifying when, where, and how the appointment will be made improves the likelihood of attendance. According to the theory of reasoned action, intentions to perform a behavior are determined by attitudes toward the behavior and by subjective norms. Attitude toward the behavior refers to people's positive or negative evaluation of their performing the behavior. Subjective norm refers to people's perceptions of approval or disapproval from significant others for performing the behavior. The theory of planned behavior postulates an additional determinant of intentions and behavior termed perceived behavioral control. Perceived behavioral control refers to people's appraisals of their ability to perform a behavior and is closely related to Bandura's (1977, 1986) concept of self-efficacy. The more positive people's attitudes and subjective norms are regarding the behavior and the greater their perceived behavioral control, the more likely it is that people will intend to perform the behavior. Intentions to perform a behavior are conceptualized as the most immediate and important predictor of behavioral performance and mediate the effects of attitudes, subjective norms, and to a lesser extent, perceived behavioral control (Ajzen, 1991). Behavioral intentions are proposed to summarize people's motivation to perform a behavior. Ajzen (1991) states that "intentions are assumed to capture the motivational factors that influence a behavior, they are indicators of how hard people are willing to try, of how much effort they are planning to exert, in order to perform the behavior" (p. 181). A distinction between a motivational phase, during which a decision to perform a behavior is made, and a volitional phase, 283

2 284 SHEERAN AND ORBELL during which specific plans are made to ensure that one's decision is acted upon, is central to Gollwitzer's (1993) concept of implementation intentions. According to Gollwitzer (1990) and Heckhausen (1991), the motivational phase involves a subjective evaluation of the costs and benefits of performing the behavior which culminates in the development of a goal intention or decision to perform the behavior. This phase parallels the motivational emphasis in the theory of planned behavior, in which the decision to act (intention) is based upon attitudes, subjective norms, and perceived behavioral control. However, unlike the theory of planned behavior, Gollwitzer and Heckhausen also posit a volitional phase that follows intention formation. This phase is characterized by the development of implementation intentions which specify when and where one will enact one's intention. Thus, goal intentions involve propositions of the form "I intend to do X," whereas implementation intentions involve the prepositional form "I intend to do X at time Y and in location Z." Only four experimental studies have examined the utility of implementation intentions in health contexts (ilne, Orbell, & Sheeran, 1999; Orbell, Hodgkins, & Sheeran, 1997; Sheeran & Orbell, 1999; Verplanken & Faes, 1999). In Orbell et al.'s (1997) study, women completed measures of theory of planned behavior constructs concerning the performance of a breast self-examination in the next month. One half of the sample were also asked to form implementation intentions specifying where and when they would perform this behavior. Despite equivalent intentions to perform the behavior, all of the women who formed implementation intentions performed a breast self-examination in the subsequent month compared with 53% of the control group. Similarly, Sheeran and Orbell (1999), Verplanken and Faes (1999), and ilne et al. (1999) found that forming implementation intentions improved the likelihood of supplement use, eating a healthy diet, and exercise adherence. In sum, evidence suggests that implementation intentions can be effective in increasing the likelihood of successfully enacting one's intentions. Evidence suggests that implementation intentions are effective because they affect attentional and memorial processes relevant to successfully acting upon one's intentions. Implementation intentions are not proposed to alter people's motivation (goal intentions). Rather, "the underlying theory is that by forming implementation intentions people pass on control of goal-directed activities from the self to the environment The intended behavior is subject to external control through the environmental cues specified in one's implementation intention... when these cues... are encountered, they are expected to prompt the intended behavior" (p. 153). Implementation intentions, therefore, affect the volitional phase of performing a behavior: They ensure that one's intention to perform a behavior is specific with respect to the timing and location of its performance. They also ensure that one's intention to perform the behavior is not forgotten (Orbell et al., 1997; Sheeran & Orbell, 1999). Implementation intentions stand in marked contrast to the motivational emphasis of the theory of planned behavior and other traditional models of behavior. There were two reasons for conducting the present study. The first concerned the paucity of research on attendance for cervical screening. Cervical cancer is a significant cause of mortality among women and is almost invariably fatal when detected as an invasive carcinoma in situ (World Health Organization, 1986, 1987). However, it is estimated that if women were screened every 3 years, the cervical cancer mortality rate could be reduced by 70%-95% (Greenwald & Sondik, 1986). Evidence shows that attendance for cervical screening is less than optimal. For example, an authoritative survey in the United Kingdom indicated that between 10% and 32% of eligible women remain unscreened (National Audit Office, 1998). In the United States, estimates of the proportion of women who had not been screened in the last 3 years range from 13% to 30% (Hayward, Shapiro, Freeman, & Corey, 1988; Lantz, Weigers, & House, 1997; Ruchlin, 1997). Despite its importance for public health, a literature search revealed only one longitudinal study that examined psychological predictors of attendance for cervical screening (Orbell & Sheeran, 1998). Relatedly, we were unable to locate any psychological intervention studies that were designed to increase attendance for cervical screening. In sum, a longitudinal intervention study of cervical screening uptake is overdue. The second reason for conducting the study was to extend the scope of the implementation intention construct by applying implementation intentions among a representative sample and to a more complex behavior than has been examined heretofore. Previous studies have all employed undergraduate samples (see, however, Orbell & Sheeran, 2000, for a correlational study that employed an older adult sample). ore importantly, previous studies have all examined single actions (i.e., perform breast selfexamination, take vitamin supplements, etc.). In the case of these behaviors, manipulations of implementation intentions have all involved asking participants in the experimental group to specify where and when they will perform the focal behavior. The behavioral intention "I intend to do X" was simply supplemented by an implementation intention "I intend to do X at Time Y and in location Z." However, attending for a cervical smear test is more complex. It is not sufficient to specify where and when one will perform the behavior, since it is necessary both to make an appointment for the test and to attend that appointment. In other words, it is necessary to perform a behavior in the service of the focal intention (make an appointment) in order to successfully enact the behavioral intention of attending for a cervical screening. Thus, in the present study, we asked participants in the experimental group to form implementation intentions concerning when, where, and how they would make an appointment, and we examined whether this increased the likelihood of their attending for the test. ore formally, the present study examined whether the behavioral intention "I intend to do X" is more likely to be enacted if a person forms an implementation intention "I intend to do W at Time Y and in location Z in order to achieve goal X." The present study could, therefore, make an important theoretical contribution to the literature if it can be demonstrated that implementation intentions increase the likelihood of achieving a goal (i.e., an outcome that can be achieved by performing a variety of single actions), as opposed to performing a single action (cf. Fishbein, 1980). We tested the following hypotheses in the present study: (a) Attitudes, subjective norms, perceived behavioral control and intentions concerning attendance for cervical screening, and records of previous attendance will predict subsequent attendance for the test, and (b) despite equivalent intentions to attend, participants who form implementation intentions specifying when, where, and how they will make an appointment for attendance will be more

3 IPLEENTATION INTENTIONS 285 likely to attend compared with control participants who do not form implementation intentions. Participants and Procedure ethod Potential participants were all of the women registered at a single medical practice in rural England who were due for a cervical smear test during a 3-month period. Two hundred seventeen women were eligible to attend for testing over the 3 months. These women received a standard postal reminder from their medical practitioner indicating that they should attend for the cervical smear test within the next 3 months. They were then sent a confidential postal questionnaire concerning their views of the cervical smear test. One hundred fourteen questionnaires were returned, a response rate of 50%. This is similar to response rates obtained in previous studies (see Orbell & Sheeran. 1993). Participants' (N = 114) ages ranged from 20 to 67 years ( = 40.62, SO = 11.69). edical records indicated that participants had received an average of 5.39 smear tests ( = 2.78) and, on the basis of their age and other clinical indicators, should have received an average of 5.86 smear tests ( = 2.58). The period of delay between being offered the test and test uptake ranged from 0 to 4 months the last time a test was due ( = 0.75, SO ). Questionnaire Items assessing attitudes, subjective norms, perceived behavioral control, and intentions were all measured on 5-point scales. Attitude toward the cervical smear test was measured by responses to the stem "For me. going for a cervical smear within the next 3 months would be..." on eight scales (worthwhile, worrying, reassuring, embarrassing, wise, healthy, unpleasant, important). Response options ranged from not at all to extremely. Reliability was high (a =.82). The single item format recommended by Azjen and Fishbein (1980) was used to measure subjective norm ("ost people who are important to me think that I should go for a cervical smear within the next 3 months"; strongly agree-strongly disagree). Perceived behavioral control was measured by 3 items: "How easy or difficult would it be for you to go for a cervical smear within the next 3 months?" (very easy-very difficult), "How confident are you that you will be able to go for a cervical smear within the next 3 months?" (very confident-very unconfident), and "If I wanted to, I could easily go for a cervical smear within the next 3 months" (strongly agree-strongly disagree). The scale was moderately reliable (a =.67). Intention was measured by 2 items: "I intend to go for a cervical smear within the next 3 months" (strongly agree-strongly disagree) and "I will try to go for a cervical smear within the next 3 months" (strongly agree-strongly disagree). Reliability was high (a =.94). Behavior Uptake of the cervical smear test within the 3-month period following the invitation was reliably determined from participants' medical records. Previous screening behaviors were also recorded, namely, number of previous smears, number of smears that should have been obtained, and delay in attendance following the client's last invitation. Implementation Intention anipulation Participants were randomly assigned to the experimental or control condition. Participants in the experimental group were asked to form an implementation intention specifying when, where, and how they would make an appointment to go for a cervical smear test (cf. Gollwitzer, 1993). The following two lines were added to the postal questionnaire for the experimental group and were presented after the items assessing theory of planned behavior variables: "You are more likely to go for a cervical smear if you decide when and where you will go. Please write in below when, where, and how you will make an appointment-" Space was included to allow participants to write in their answers in each case. The questionnaire for the control group was identical in all respects to that of the experimental group except for the omission of this item. Representativeness Check Results Respondents versus nonrespondents were compared on background variables and previous screening behaviors using data from participants' medical records in order to gauge the representativeness of the final sample. ultivariate analysis of variance (ANOVA) showed a significant multivariate effect, F(4, 212) = S.62,p<.001. UnivariateF tests showed that respondents did not differ in age, number of previous smears, or the number of smears that should have been obtained (maximum F 1.84, p >.17). However, there was a significant difference between the groups regarding delay in attendance last time, F(l, 215) = 8.62, p <.001. Nonrespondents delayed longer than respondents (s = 2.00 vs. 0.75, respectively; s = 2.30 and 1.15). These findings indicate that the present sample probably overrepresents participants who promptly attend for cervical screening. We will return to the significance of this rinding in the discussion. Predictors of Attendance Of the 114 participants, 92 (81%) attended for screening within 3 months of being invited to attend. We first tested the ability of the theory of planned behavior variables, previous screening behaviors (number of previous smears, number of smears that should have been obtained, and delay in attendance following the last invitation), and age to predict attendance for the cervical smear test. Discriminant analysis employing a direct entry procedure produced a highly significant function, Canonical correlation =.68, Wilks's A = 0.53, ^(S, N = 114) = 67.67, p <.001. Overall, 87% of grouped cases were correctly classified. After we adjusted for group size (cf. Tabachnick & Fidell, 1989, p. 544), classification was 22% greater than would be expected by chance. Table 1 presents correlations between the independent variables and the discriminant function and comparisons of means for attendees and nonattendees. Delay in attendance was the strongest correlate of the discriminant function, followed by intentions, subjective norms, perceived behavioral control, and attitudes, respectively. Univariate analyses showed significant mean differences on all five of these variables for attendees versus nonattendees. Number of previous smears, number of smears that should have been obtained, and age were each modestly correlated with the discriminant function and did not distinguish attendees versus nonattendees in univariate analyses. Overall, the discriminant analysis indicates that theory of planned behavior variables and previous delay behavior provide good prediction of attendance for the cervical smear test. Participants who have not delayed in the past, who have strong intentions to attend, who feel social pressure to do so, who feel confident that they will be able to attend, and who positively evaluate attendance are likely to attend for the test.

4 286 SHEERAN AND ORBELL Table 1 Correlations Between Predictors and Discriminant Function, and Comparisons of eans for Attendees Versus Nonattendees Predictor Correlation with function Attendees Nonattendees F Delay in attendance last time Intention Subjective norm Perceived behavioral control Attitude No. of smears due No. of previous smears Age * 35.73* 29.67* 12.96* 9.36* **p <.01. ***;?<.001. Randomization Check In order to ensure that our randomization of participants to the experimental (n = 59) and control conditions (n 55) was successful, we compared the two groups on theory of planned behavior variables, previous screening behaviors, and age (see Table 2). A ANOVA comparing the two groups was nonsignificant, F(8, 105) = 1.51, p >.16, and univariate F tests confirmed that there were no differences between the groups on attitudes, subjective norms, perceived behavioral control, or intentions concerning the cervical smear test. Similarly, the groups did not differ in terms of the number of previous smear tests obtained, the number they should have obtained, how many months they had delayed before obtaining a test the last time they were invited to attend, or age. Table 2 shows that both groups had positive attitudes, subjective norms, perceived behavioral control, and intentions. Behavioral intentions were strong in both conditions, with mean scores greater than 4.5 on a 1-5 scale. We can conclude that both groups were highly motivated to attend for screening prior to the experimental manipulation. Table 2 Comparison of Experimental and Control Groups on Theory of Planned Behavior Variables, Previous Screening Behaviors, and Age Variable Attitude Subjective norm Perceived behavioral control Intention No. of previous smears No. of smears due Delay in attendance last time Age Experimental group Control group a Values do not meet p <.05 criterion for statistical significance. F" Intervention Findings Fifty-five women in the experimental group 99% completed the implementation intention items. To determine the efficacy of asking participants to form implementation intentions regarding when, where, and how they would make an appointment to attend for the cervical smear test on subsequent attendance, we crosstabulated condition (implementation intention vs. control) and attendance or nonattendance (see Table 3). A highly significant dependent relationship obtained, )?(l,n= 114) = 9.20, p <.002. Sixty-nine percent of the control group attended for screening which is a higher attendance rate than those obtained in many previous studies (see, e.g., Orbell & Sheeran, 1998). It is especially impressive, therefore, that 92% of the participants in the experimental condition subsequently attended for cervical screening. These findings provide convincing evidence that implementation intention formation makes it more likely that participants will succeed in keeping an important appointment. In a second analysis, we tested whether the implementation intention intervention improved discrimination of attendees versus nonattendees compared to the classification provided by the theory of planned behavior, previous screening behaviors, and age. The discriminant analysis described earlier was rerun including experimental condition as a predictor variable. The discriminant function was highly significant, Canonical correlation =.71, Wilks's A = 0.49, ^(9, N = 114) = 76.11,p <.001, and the experimental condition was significantly correlated with the function (r =.29, p <.05). Overall, 89% of grouped cases were correctly classified, which was 22% greater than would be expected by chance. Comparison of how well the two models fitted the data indicated that including experimental condition as a predictor provided better discrimination than the cognitive and background variables on their own, jf(\, N = 114) difference = 8.44, p <.005. Table 3 Cross-Tabulation of Experimental Condition by Attendance Group Experimental Control Attended Did not attend

5 IPLEENTATION INTENTIONS 287 Implementation Intentions and Previous Delay Behavior One intriguing finding that bears further examination is that previous delay behavior was the best predictor of subsequent attendance for a smear test in the discriminant analysis. This finding indicates that people's beliefs about the smear test and their intentions to attend have less influence on uptake of the cervical smear test than their previous delay behavior. Given that a person's previous screening behavior cannot be altered by educational interventions (unlike attitudes, intentions, etc.), it would be useful to determine whether our implementation intention intervention affected the importance of this variable. We, therefore, computed correlations between delay behavior and subsequent attendance separately for the two groups. Findings showed that while delay behavior was correlated with attendance for both groups, the correlation was significantly smaller for participants who formed implementation intentions (r = -.29, p <.05) compared with control participants (r = -.70, p <.001; Z = 2.95, p <.004, 2-tailed). These findings indicate that implementation intentions can reduce the habit of delay behavior. Discussion This is the first study we are aware of that evaluated a psychological intervention to increase attendance for cervical screening. Theory of planned behavior variables were used to measure participants' motivation to attend for cervical screening prior to a manipulation that asked one half of the sample to form implementation intentions specifying when, where, and how they would make an appointment to attend. Participants in the implementation intention and control conditions were highly motivated to attend. However, despite equivalent motivation to attend (and equivalent previous screening behaviors and ages), there were substantial differences in rates of attendance for the two groups. While 69% of controls subsequently attended for the test, 92% of participants who formed implementation intentions were screened. These findings demonstrate that forming an implementation intention to perform a behavior in the service of a goal intention (make an appointment to attend) increases the likelihood of action (subsequent attendance) even when participants strongly intend to achieve their goal. These findings are especially impressive when one considers that the theory of planned behavior variables, previous screening behaviors, and age provided good prediction of attendance. Discriminant analysis showed that previous delay behavior, intentions, subjective norms, perceived behavioral control, and attitudes were able to accurately distinguish between 89% of attendees versus nonattendees. These findings add to the substantial evidence that supports the utility of the theories of reasoned action and planned behavior in predicting people's health-related behavior (e.g., Conner & Sparks, 1996; Godin & Kok, 1996; Sheeran & Orbell, 1998; Sheeran & Taylor, 1999). ore importantly, findings from a second discriminant analysis that included experimental condition as a predictor indicated that an intervention based on the volitional phase of action (cf. Gollwitzer, 1990; Heckhausen, 1991) significantly enhanced the prediction of attendance behavior provided by one of the most extensively researched accounts of motivation the theory of planned behavior. It would be valuable to explore whether implementation intentions could similarly enhance the predictive validity of other models of health behavior, such as the transtheoretical model (Prochaska & DiClemente, 1983, 1984; Prochaska, DiClemente, & Norcross, 1992). Findings from the present study also speak to the utility of implementation intentions in reducing the impact of habit, that is, in attenuating the relationship between past behavior and future behavior. The correlation between previous delay behavior and attendance for the test within 3 months was negative and statistically significant for both experimental and control participants, indicating that having delayed in the past was associated with failure to attend promptly on this occasion. Importantly, however, the correlation between previous delay and subsequent attendance was significantly lower for participants who formed implementation intentions compared to controls. Orbell et al. (1997) proposed (and obtained supporting evidence) that past behavior should have less influence on future behavior for participants who form implementation intentions, because implementation intentions involve cognitive rehearsal of the link between a behavior and the context of its enactment This cognitive rehearsal parallels the behavioral rehearsal of the link between an action and the context of its enactment that is the defining feature of habits (cf. Gollwitzer, 1993). Thus, forming an implementation intention and possessing a habit have similar cognitive underpinnings. In both cases there is an association in memory between an action schema and certain environmental cues. However, because an implementation intention involves specifying that one will perform a new behavior when specified environmental cues are encountered, previous action tendencies associated with these cues will be suppressed, and the new behavior will be automatically activated (Gollwitzer & Brandstatter, 1997). Thus, implementation intentions can be effective in helping to replace a previous action tendency with a new behavior whose performance is desired by the actor. A number of potential criticisms of our study should be discussed. First, it is important to acknowledge that although the response rate to our postal questionnaire was 50% (similar to rates obtained in previous studies of this behavior; see Orbell & Sheeran, 1993), there was, nonetheless, a significant difference between respondents and nonrespondents regarding delay in attendance the last time they were due for cervical screening. In particular, nonrespondents delayed longer than respondents, which suggests that the present sample overrepresents women who attend promptly. The significance of this finding is difficult to clarify, because we have been unable to locate any studies that have compared prompt versus late attendees on psychological,' demographic, or clinical variables. Kowalski and Brown (1994) have suggested that cervical cancer screening is associated with heightened concerns about evaluations of others and with increased anxiety and embarrassment. It is possible, therefore, that differences in previous delay behavior reflect individual differences in fear of negative evaluation (Leary, 1983), public selfconsciousness (Fenigstein, Scheier, & Buss, 1975), or social anxiety (Schlenker & Leary, 1982). However, this analysis is speculative and will need to be tested in future research. Overall, we do not believe that the differences in delay in previous attendance between respondents and nonrespondents seriously compromises the validity of our analyses for two reasons. First, the amount of delay was relatively modest since respondents and nonrespondents did not differ on the two key screening be-

6 288 SHEERAN AND ORBELL havior measures (number of smears obtained and number of smears that should have been obtained) or age. Thus, it seems likely that the final sample adequately represents the population from which it was drawn in terms of risk of cervical cancer (see Orbell & Sheeran, 1993). Second, it is important to acknowledge that this was an experimental study. Because there were 55 participants, at least, in both conditions, the present sample is sufficiently large (i.e., possesses adequate statistical power) to test the hypothesis that forming an implementation intention increases the likelihood of attendance for cervical screening. A second potential limitation concerns the time frame for collection of the attendance data. Our measures of theory of planned behavior variables all specified attendance "within the next 3 months," because this time frame was the standard administrative procedure in the medical practice that invited us to conduct the study. However, it is possible that participants did subsequently attend for testing after the 3-month period. Again, this consideration should not unduly bias our findings, since there are no grounds for supposing that rates of attendance after the 3-month study period should differ for experimental versus control participants. A final potential objection that should be addressed is that the implementation intention manipulation employed here did not affect participants' volition, as we propose, but rather increased intentions to attend (or attitudes, subjective norms, or perceived behavioral control). Although we are unable to test this possibility using the present data, accumulated evidence does not support this hypothesis. Several studies have measured intentions (and the other theory of planned behavior variables) both before and after implementation intention formation and found no evidence that implementation intentions affect participants' motivation to perform the behavior (ilne et al., 1999; Orbell et al., 1997; Sheeran & Orbell, 1999). In sum, there are good grounds to suppose that our manipulation affected participants' ability to enact their intentions to attend for cervical screening rather than the strength of their intentions to attend. Notwithstanding these potential limitations, the present study has important theoretical and applied implications. At the theoretical level, this is one of the first studies to demonstrate that implementation intentions can enhance the likelihood of achieving a goal as well as increasing the likelihood of performing single actions. Our findings indicate that forming an implementation intention to perform a behavior in the service of a goal intention in this case, make an appointment to attend for a cervical smear test increased the likelihood of achieving the goal of attendance. This relates to research by Sheeran, Orbell, and Norman (1999) who pointed to the role of "conflicting" and "complementary" intentions in explaining the consistency between intentions and behavior. They defined a complementary intention as an intention to perform a behavior which, if performed, is likely to facilitate performance of the focal behavior. Sheeran, Orbell, and Norman (1999) speculated that forming an implementation intention to perform a complementary behavior might enhance the likelihood of performance of the focal behavior. Since the intention to make an appointment for a cervical smear test can be construed as a complementary intention to the focal intention of attending for the test, findings obtained here are consistent with this speculation. It would be valuable to determine whether implementation intentions could be used similarly in the context of other health goals, for example, using implementation intentions to increase the likelihood of carrying condoms (a complementary behavior) in order to increase the likelihood of condom use (cf. Sheeran, Abraham, & Orbell, 1999). Relatedly, future research could examine whether forming implementation intentions to suppress "conflicting intentions" might also be effective in enhancing the likelihood of performing particular health behaviors. There are also several potential applications of our findings. The present study shows that participants can be induced to form implementation intentions by means of an extremely simple manipulation (just two lines of text at the end of a questionnaire in the present case). One implication for increasing cervical screening uptake is that the postcard reminder that is sent to women to invite them to attend for the test could usefully be amended to include the implementation intention manipulation described here. It would also be valuable to examine the utility of the implementation intention intervention employed here among other populations where economic and access barriers to cervical screening may be more compelling than in the United Kingdom (cf. Orbell, Crombie, & Johnston, 1996). issed appointments are also likely to be a serious issue in the context of many other medical conditions, and implementation intention interventions could prove useful for medical practice in those areas. ore generally, implementation intentions could be applied to a wide variety of health behaviors where the timing and location for performing the behavior is uncertain or where the specific behavior to be performed is unclear (cf. Bargh, 1990), including, for example, medication adherence or eating a healthy diet, hi sum, there are numerous possible applications of implementation intentions that can, and should, be tested by health psychologists in future research. References Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckmann (Eds.), Action control: From cognition to behavior (pp ). Berlin, Germany: Springer-Verlag. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, Ajzen, I., & Fishbein,. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall. Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall. Bargh, J. A. (1990). Auto-motives: Preconscious determinants of social interaction. In E. T. Higgins & R.. Sorrentino (Eds.). Handbook of motivation and cognition: Foundations of social behavior (pp ). New York: Guilford Press. Borland, R., Owen, N., Hill, D., & Schofield. P. (1991). Predicting attempts and sustained cessation of smoking after the introduction of workplace smoking bans. Health Psychology, 10, Conner,., & Armilagc, C. J. (1998). The theory of planned behavior: A review and avenues for further research. Journal of Applied Social Psychology, 28, Conner,., & Sparks, P. (1996). The theory of planned behaviour and health behaviours. In. Conner & P. Norman (Eds.), Predicting health behaviour (pp ). Buckingham, England: Open University Press. De Vellis, B., Blalock, S., & Sandier, R. (1990). Predicting participation in cancer screening: The role of perceived behavioral control. Journal of Applied Social Psychology, 20, Fenigstein, A., Scheier,. F., & Buss, A. H. (1975). Public and private

7 IPLEENTATION INTENTIONS 289 self-consciousness: Assessment and theory. Journal of Consulting and Clinical Psychology, 37, Fishbein.. (1980). Theory of reasoned action: Some applications and implications. In H. Howe &. Page (Eds.), Nebraska symposium on motivation 2979 (pp ). Lincoln: University of Nebraska Press. Fishbein,., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, A: Addison-Wesley. Fisher, W. A., Fisher, J. D., & Rye, B. (1995). Understanding and promoting AIDS preventive behavior: Insights form the theory of reasoned action. Health Psychology, 14, Godin, G., & Kok, G. (1996). The theory of planned behavior: A review of its applications to health-related behaviors. American Journal of Health Promotion, 11, Gollwitzer, P.. (1990). Action phases and mind-sets. In E. T. Higgins & R.. Sorrentino (Eds.), Handbook of motivation and cognition: Foundations of social behavior (pp ). New York: Guilford Press. Gollwitzer, P.. (1993). Goal achievement: The role of intentions. European Review of Social Psychology, 4, Gollwitzer, P.., & Brandstmter, V. (1997). Implementation intentions and effective goal pursuit. Journal of Personality and Social Psychology, 73, Greenwald, P., & Sondik, E. J. (1986). Cancer control objectives for the nation: Bethesda, D: National Cancer Institute. Hayward, R. A., Shapiro,. F., Freeman, H. E., & Corey, R. (1988). Who gets screened for cervical and breast cancer? Results from a national survey. Archives of Internal edicine, 148, Heckhausen, H. (1991). otivation andaction. Berlin, Germany: Springer- Verlag. Kowalski, R.., & Brown, K. J. (1994). Psychosocial barriers to cervical cancer screening: Concerns with self-presentation and social evaluation. Journal of Applied Social Psychology, 24, Lantz, P.., Weigers,. E., & House, J. S. (1997). Education and income differentials in breast and cervical cancer screening. edical Care, 35, Leary,. R. (1983). A brief version of the Fear of Negative Evaluation Scale. Personality and Social Psychology Bulletin, 9, ilne, S., Orbell, S., & Sheeran, P. (1999). Combining motivational and volitional interventions to promote exercise participation: Protection motivation theory and implementation intentions. anuscript submitted for publication. ontano, D., & Taplin, S. (1991). A test of an expanded theory of reasoned action to predict mammography screening. Social Science and edicine, 32, National Audit Office. (1998). The performance of the National Health Service cervical screening programme in England. London: Author. Norman, P., Conner,., & Bell, R. (1999). The theory of planned behavior and smoking cessation. Health Psychology, 18, Orbell, S., Crombie, I., & Johnston, G. (1996). Social cognition and social structure in the prediction of cervical screening uptake. British Journal of Health Psychology, 1, Orbell, S., Hodgkins, S., & Sheeran, P. (1997). Implementation intentions and the theory of planned behavior. Personality and Social Psychology Bulletin, 23, Orbell, S., & Sheeran, P. (1993). Health psychology and the uptake of preventive health services: A review of thirty years research on cervical screening. Psychology and Health, 8, Orbell, S., & Sheeran, P. (1998). 'Inclined abstainers": A problem for predicting health behaviour. British Journal of Social Psychology, 37, Orbell, S., & Sheeran, P. (2000). otivational and volitional processes in action initiation: A field study of the role of implementation intentions. Journal of Applied Social Psychology, 30, Prochaska, I. O., & DiClememe, C. C. (1983). Stages and processes of self-change in smoking: Towards an integrative model of change. Journal of Consulting and Clinical Psychology, 5, Prochaska, J. O., & DiClemente, C. C. (1984). The transtheoretical approach: Crossing traditional boundaries of change. Homewood, IL: Dorsey Press. Prochaska, J. O., DiClememe, C. C., & Norcross, J. C. (1992). In search of how people change: Applications to addictive behaviors. American Psychologist, 47, Randall, D.., & Wolff, J. A. (1994). The time interval in the intentionbehaviour relationship: eta-analysis. British Journal of Social Psychology, 33, Ruchlin, H. S. (1997). Prevalence and correlates of breast and cervical screening among older women. Obstetrics and Gynecology, 90, Schlenker, B. R., & Leary,. R. (1982). Social anxiety and self-presentation: A conceptualization and model. Psychological Bulletin, 92, Sheeran, P., Abraham, C. S., & Orbell, S. (1999). Psychosocial correlates of heterosexual condom use: eta-analysis. Psychological Bulletin, 125, Sheeran, P., & Orbell, S. (1998). Do intentions predict condom use? eta-analysis and examination of six moderator variables. British Journal of Social Psychology, 37, Sheeran, P., & Orbell, S. (1999). Implementation intentions and repeated behaviour: Augmenting the predictive validity of the theory of planned behavior. European Journal of Social Psychology, 37, Sheeran, P., Orbell, S., & Norman, P. (1999). Theory of planned behavior and intention-behavior relations: Significance of conflicting and complementary intentions. anuscript submitted for publication. Sheeran, P., & Taylor, S. (1999). Predicting intentions to use condoms: eta-analysis and comparison of the theories of reasoned action and planned behavior. Journal of Applied Social Psychology, 29, 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, Tabachnick, B. G., & Fidell, L. S. (1989). Using multivariate statistics (2nd ed.), New York: Harper & Row. Verplanken, B., & Faes, S. (1999). Good intentions, bad habits and the effects of forming implementation intentions on behavior and cognition. European Journal of Social Psychology, 29, White, K., Terry, D., & Hogg,. A. (1994). Safer sex behavior The role of attitudes, norms, and control factors. Journal of Applied Social Psychology, 24, World Health Organization. (1986). Control of cancer of the cervix uteri. Bulletin of the World Health Organization, 64, World Health Organization. (1987). Genital human papillomavirns infections and cancer: emorandum from a WHO meeting. Bulletin of the World Health Organization, 65,