The Value of the Theory of Planned Behavior, Perceived Control, and Self-Efficacy Expectations for Predicting Health-Protective Behaviors

Transcription

1 BASIC AND APPLIED SOCIAL PSYCHOLOGY, 1993, 14(2), Copyright 1993, Lawrence Erlbaum Associates, Inc. The Value of the Theory of Planned Behavior, Perceived Control, and Self-Efficacy Expectations for Predicting Health-Protective Behaviors Kevin D. McCaul, Ann K. Sandgren, H. Katherine O'Neill, and Verlin B. Hinsz North Dakota State University In two studies we asked whether self-efficacy expectations and perceived control predict intentions to act and the performance of health-protective behaviors. Young adults took part in treatments intended to increase adherence to either a regimen of breast self-exam or testicular self-exam (Experiment 1) or to a dental regime (Experiment 2). We gathered measures of attitudes subjective norms, self-efficacy, perceived control, behavioral intentions, and, at follow-up, self-reported behavior. Regression analyses demonstrated that attitudes and subjective norms predicted intentions to perform breast and testicular self-exams (R^s =.34 and.43, respectively) and intentions to brush and floss one's teeth (R^s =.11 and.15, respectively). Perceived control added significantly to the prediction of these healthprotective behavioral intentions and was a better predictor than self-efficacy, which was defined as perceived ability. Both studies clearly support the predictive value of the theory of planned behavior, which included perceived control, in the realm of health behavior. The studies also suggest the need for more research to elucidate the meaning of the perceived control construct. Ajzen and Fishbein (1980) proposed the theory of reasoned action to explain when attitudes will likely predict behavior. The crucial aspects of the theory (see also Fishbein & Ajzen, 1975) are that intentions causally determine behavior and that intentions in turn are caused by the joint influences of attitudes toward the behavior and subjective norms. In Requests for reprints should be sent to Kevin D. McCaul, Department of Psychology, North Dakota State University, Fargo, ND

2 232 McCAUL, SANDGREN, O'NEILL, HINSZ general, tests of the model support these causal connections. There is much evidence that intentions predict behavior (see Ajzen & Fishbein, 1977) and that attitudes and subjective norms predict intentions (e.g., Brinberg, 1979; Pagel & Davidson, 1984). Although tests of the theory of reasoned action have produced much supportive data, the theory has not gone uncriticized. Writers have attacked the theory in three ways. First, some authors have argued that various factors moderate the predicted causal relations. It is now well known, for example, that attitude-behavior correspondence is higher when one has previous experience with the attitudinal object (Fazio & Zanna, 1978; Regan & Fazio, 1977). A second type of criticism includes disagreements with the hypothesized causal paths in the model (see Liska, 1984). For example, although the model posits that attitudes influence behavior only through the mediating variable of intentions, data show that attitudes sometimes influence behavior directly (e.g., Bentler & Speckart, 1979; Zuckerman & Reis, 1978). Finally, a few theorists have noted that the theory of reasoned action needs additional causal elements. Triandis (1980), for example, emphasized the importance of emotional reactions to performing the behavior. In this article, we consider whether self-efficacy and perceived control should be added to the theory of reasoned action. We selected these variables because Ajzen recently proposed that the theory of reasoned action needs an additional element in certain circumstances (Ajzen, 1985, 1991; Ajzen & Madden, 1986; Schifter & Ajzen, 1985). Specifically, Ajzen noted that the original model dealt exclusively with volitional behaviors and that the model fails to sufficiently predict behaviors that are not under complete volitional control. Ajzen further suggested that many (if not most) behaviors that seemingly are controllable may actually be only more or less controllable. Ajzen proposed that, whenever a behavior is less than completely uncontrollable, the theory of planned behavior is superior to the theory of reasoned action. This theory of planned behavior adds one causal element: perceived behavioral control or the "person's belief as to how easy or difficult performance of the behavior is likely to be" (Ajzen & Madden, 1986, p. 457). Perceived control, together with attitudes and one's subjective norms, theoretically adds to the prediction of intentions. Further, when perceptions of control closely match reality, perceived control can also directly predict behavior. For example, Ajzen and Madden (1986) showed that perceived control predicted intentions to attend class beyond what was predicted by attitudes and subjective norms. They also demonstrated that perceived control added to the prediction of the behavioral goal of receiving an "A" beyond what was predicted by intentions alone.

3 THEORY OF PLANNED BEHAVIOR AND SELF-EFFICACY 233 SELF-EFFICACY AND THE THEORY OF REASONED ACTION Recently, McCaul, O'Neill, and Glasgow (1988) proposed an extension to the theory of reasoned action in the context of predicting health-promoting behaviors. McCaul et al. drew on theory and research regarding selfefficacy expectations, or a person's belief that he or she is capable of performing the requisite behavior (see Bandura, 1982). McCaul et al. argued that one's self-efficacy for performing a health-protective behavior should predict intentions and, in a prospective examination of dental health behaviors (i.e., brushing and fiossing), they discovered that self-efficacy predicted intentions after controlling for the infiuence of attitudes and subjective norms. In a similar study, Tedesco, Keffer, and Fleck-Kandath (1991) showed that self-efficacy also predicted brushing and fiossing behavior after controlling for intentions. McCaul et al.'s (1988) arguments, though originally restricted to healthprotective behaviors, fit neatly within Ajzen's more general model of planned behavior. That is, health-protective behaviors such as fiossing probably fall within the class of behaviors that Ajzen considered not under complete behavioral control. Breaking unhealthy habits (e.g., smoking, consuming alcohol) and instituting health-protective ones (e.g., daily blood pressure checks, using safety belts) are difficult goals. Indeed, most persons who initially break a habit will resume it (Brownell, Marlatt, Lichtenstein, & Wilson, 1986); most persons attempting to begin a regimen fail to adhere consistently (Belisle, Roskies, & Levesque, 1987; Lund & Kegeles, 1984). In summary, McCaul et al. (1988) proposed that self-efficacy adds to the theory of reasoned action in understanding health-protective behaviors. More generally, Ajzen (1985) theorized that perceived behavioral control adds to the theory of reasoned action in understanding any behavior whose enactment requires control including health-protective behaviors. In this article, we examine the predictive value of the theory of planned behavior across four different health-protective behaviors. Further, we evaluate measures of both self-efficacy expectations and perceived behavioral control for the four health behaviors, and consider the relative predictive power of each. To compare self-efficacy expectations and perceived behavioral control, we needed to differentiate them. The interpretation of self-efficacy varies as a function of the behavior to be performed and the context in which the behavior will be performed (Bandura, 1986). For example, for social skills (e.g., assertiveness; Lee, 1984) self-efficacy primarily refiects the perceived ability of the individual (i.e., knowing how to perform the behavior successfully). For performance goals, self-efficacy has been defined as the

4 234 McCAUL, SANDGREN, O'NEILL, HINSZ perceived likelihood of attaining specific levels of performance (Locke, Motowidlo, & Bobko, 1986). In this study, to assess self-efficacy separately from perceived control and behavioral intention measures, we emphasized the perceived ability aspect of self-efficacy. This approach, which has been used previously in the context of health-protective behaviors (Brubaker & Fowler, 1990; Brubaker & Wickersham, 1990), reduces the likelihood of confounding self-efficacy expectations with beliefs about the outcomes of the behavior (cf. Eastman & Marzillier, 1984). No one seems to doubt that perceived ability is a central part of the self-efficacy construct, although whether it captures all the meaning of the construct is still controversial (see, e.g., Bandura, 1984, 1986; Corcoran, 1991; Kazdin, 1978; Kirsch, 1986). Thus, we chose an ability conception of self-efficacy although recognizing that such a definition might limit our conclusions. Perceived behavioral control was operationalized for these health-related behaviors as the performance of a regimen over time (i.e., consistently performing the behaviors over the next several months). These measures followed directly from earlier measures of perceived control for a healthrelated behavior (Schifter & Ajzen, 1985). Thus, in this article we describe two studies that tested the theory of planned behavior and that compared a measure of self-efficacy to a measure of perceived control in the context of health-protective behaviors. In each study, subjects participated in programs intended to encourage the performance of health-protective behaviors (cancer detection and dental hygiene). Measures of attitudes, subjective norms, self-efficacy, perceived control, and behavioral intentions were taken after intervention, and self-reports of behavior were taken at follow-up sessions. Regression analyses were used to test whether: 1. Attitudes, subjective norms, perceived control, and self-efficacy expectations predicted intentions. 2. Perceived control and self-efficacy each predicted intentions after controlling for attitudes and subjective norms. 3. Perceived control and self-efficacy expectations each contributed significantly to the prediction of intentions after controlling for the other. EXPERIMENT 1 In the first experiment, we examined the theory of planned behavior in the context of self-exams for cancer detection. Male and female college students took part in a one-session intervention intended to promote selfexamination for either breast or testicular cancer. The suggested regimens

5 THEORY OF PLANNED BEHAVIOR AND SELF-EFFICACY 235 involved monthly self-examinations to search for lumps that might indicate cancer. One week after the intervention, participants completed measures of each element of the theory of planned behavior and self-efficacy; 3 months later, they reported adherence behavior. Subjects One hundred thirty-eight college students (66 women, 72 men) participated in small groups to earn extra credit for introductory psychology classes. Eight women were excluded because they had conducted a breast selfexamination in the previous month and they reported that they "usually" conducted examinations at least once a month. Of the 138 students who began the experiment, 3 women and 14 men failed to attend the second session, largely due to scheduling difficulties. Participants did not differ from dropouts on age or reported frequency of previous self-examination behavior. Procedure At the first of two sessions, participants completed pretest measures and then received an educational message describing the importance of selfexamination and how to perform such exams.* Brochures from the American Cancer Society were also provided. Participants were asked to complete a single exam during the subsequent week (all reported that they did). The men and women were also randomly assigned to three treatments: (a) a group in which subjects were publicly committed to performing self-exams, (b) a group in which subjects signed contracts to complete self-exams, and (c) a control group in which subjects received health education only. No reliable differences for intentions or behavior emerged among these three conditions during the study (see Sandgren, 1986). After 1 week, participants returned and completed measures representing elements of the theory of planned behavior and self-efficacy (see Measures section). They were asked to continue to examine themselves once a month and then were dismissed from the study. Three months later, we contacted 97^0 of the participants by phone and asked how many times they had conducted a self-exam since the last session. 'We included pretest measures in part to exclude participants who were already performing self-exams and also to look at changes in processes (e.g., attitudes) that were caused by the treatment manipulations. It is worth nothing that in Experiment 1, reported behavior at pretest was uncorrelated with any of the measures taken later, probably because of restricted variability (e.g., at pretest, none of the men reported performing testicular self-examination).

6 236 McCAUL, SANDGREN, O'NEILL, HINSZ Measures Using the procedures suggested by Ajzen and Fishbein (1980), we constructed measures of attitude, subjective norm, and intentions for both breast self-exam (BSE) and testicular self-exam (TSE) behaviors. Attitudes. Attitudes toward self-exams were collected on ten 7-point semantic-differential scales with endpoints labeled good-bad, harmfulbeneficial, pleasant-unpleasant, wise-foolish, worthless-valuable, assuringtroubling, soothing-distressing, comforting-annoying, healthy-unhealthy, and favorable-unfavorable. These scales showed high internal consistency, with alphas of.78 for BSE and.85 for TSE; thus, the items were averaged to form single scales for breast and testicular exams. For the entire sample, attitudes toward BSE were slightly positive {M = 4.83, SD = 0.55) and attitudes toward TSE were neutral (M = 4.01, SD = 0.61). Subjective norm. The subjective norm was measured using a single item that read "Most people important to me think that I should conduct a self-exam once a month." Responses were measured on a 7-point scale ranging from extremely unlikely (1) to extremely likely (7). The average sample values were 5.40 {SD = 1.14) for BSE and 4.37 {SD = 1.26) for TSE. Intentions. Intentions were assessed by responses to a single item: "I intend to conduct breast (testicular) self-examination at least once each month over the next six months." Responses were measured on a 7-point scale ranging from extremely unlikely (1) to extremely likely (7). Average intentions for BSE were 6.27 {SD = 0.60), and for TSE they were 5.57 {SD = 1.27). Perceived control. Participants were asked two questions to measure perceived control: "What is the likelihood that if you try you will manage to conduct breast (testicular) self-examination once a month over the next six months?" and "What is your best estimate that an attempt on your part to conduct breast (testicular) self-examination over the next 6 months would be successful?" These questions, which precisely follow those used by Schifter and Ajzen (1985), were answered using 7-point scales ranging from extremely unlikely (1) to extremely likely (7). We combined these two items into a single score (alpha levels =.87 and.86 for BSE and TSE, respectively). Average perceived control for BSE was 6.21 {SD = 0.59), and for TSE it was 5.56 {SD = 1.09).

7 THEORY OF PLANNED BEHAVIOR AND SELF-EFFICACY 237 Self-efficacy. Self-efficacy was assessed with a single item, reading "I could conduct a breast (testicular) self-examination at least once a month." The response scale used the same unlikely-likely endpoints as those used for perceived control, and self-efficacy averaged 6.56 (SD = 0.53) for BSE and 6.11 {SD = 0.70) for TSE. Reported behavior. A the 3-month follow-up, participants estimated the number of times during the previous 3 months that they had performed a cancer self-exam. These reports averaged 2.18 for BSE {SD = 0.83) and 2.80 for TSE (S > = 1.77). Results Table 1 shows the intercorrelations among all variables from the theory of planned behavior plus self-efficacy expectations and reported behavior. As the table reveals, nearly all intercorrelations among these variables were statistically significant for both BSE and TSE (the exceptions were primarily correlations of model components with reported behavior). In predicting intentions, attitudes toward higher correlations than subjective norms, but perceived control showed the highest relationship to intentions; perceived control was also a stronger predictor than self-efficacy for both behavioral intentions. Thus, the first hypothesis was supported: Attitudes, TABLE 1 Correlations Among Planned Behavior Variables, Self-Efficacy Expectations, and Reported Behavior for Cancer Self-Examinations Subjective Perceived Self- Attitude Norm Control Efficacy Intentions Behavior Breast self-exam Attitude -.60* Subjective norm Perceived control Self-efficacy Intentions Behavior Testicular self-exam Attitude -.42* Subjective norm Perceived control Self-efficacy Intentions Behavior 53* 33* 64* 30*.31*.32*.67*.56*.21.49*.58*.38*.63*.38*.65*.31*.89*.46* _ *.30*.30*.36*.12.41*.24.34* *p <.05.

8 238 McCAUL, SANDGREN, O'NEILL, HINSZ subjective norms, perceived control, and self-efficacy each predicted intentions individually. Predicting intentions. Regression analyses were used to test the theory of planned behavior against the theory of reasoned action. (For all analyses reported as significant, we usedp <.05). The regression results are presented in Table 2. Based on the theory of reasoned action, to predict behavioral intentions we first entered attitudes and subjective norms; TABLE 2 Results of Regression Analyses Predicting Intentions to Perform Cancer Self-Examinations Breast Self-Exam Predictive Variables Beta Multiple R R^s Change Step 1. Attitudes + Subjective norm Step 2. Perceived control Step 1. Attitudes -I- Subjective norm Step 2. Self-efficacy Step 1. Attitude + Subjective norm + Self-efficacy Step 2. Perceived control Step 1. Attitude + Subjective norm -1- Perceived control Step 2. Self-efficacy Testicular Self-Exam Predictive Variables Beta Multiple R R^ Change Step 1. Additudes + Subjective norm Step 2. Perceived control Step 1. Attitude + Subjective norm Step 2. Self-efficacy Step 1. Attitude -I- Subjective norm -I- Self-efficacy Step 2. Perceived control Step I. Attitude -1- Subjective norm -I- Perceived control Step 2. Self-efficacy ^Indicates that the R increment is not statistically significant.

9 THEORY OF PLANNED BEHAVIOR AND SELF-EFFICACY 239 together, these variables accounted for a significant proportion of variability in intentions to perform BSE {R^ =.34) and TSE {R^ =.43). Then, in accord with the theory of planned behavior, perceived control was entered into the regression equation. Perceived control predicted an additional 14<7o of the variance in BSE intentions and 39% of the variance in TSE intentions, and both increments were significant. In a second set of analyses, we similarly tested the contribution of self-efficacy after attitudes and the subjective norm had been entered in the regression equation. Although self-efficacy produced a significant increment in intentions to perform BSE {R^ change =.044, p =.045), it failed to predict a significant increase in intentions to perform TSE {R^ change =.012, /? >.1). With one exception, then, these data support Hypothesis 2: Perceived control and self-efficacy predicted intentions to perform cancer self-examinations. Perceived control versus self-efficacy. Two multiple-regression analyses were conducted to test the comparative contributions of perceived control and self-efficacy expectations (Hypothesis 3). Perceived control was a significant contributor to the prediction of intentions after attitude, subjective norm, and self-efficacy had been entered into the equation with F(l, 58) = 12.22, p <.01, for BSE, and F(l, 52) = 108.6, p <.01, for TSE. However, self-efficacy failed to add to the equation predicting intentions for either BSE or TSE after all variables from the theory of planned behavior had been entered {ps >.1). Predicting reported behavior. One reason that perceived control might predict intentions so well is that the items making up the scale could be simply measuring intentions in a different way. If this were the case, we would not expect perceived control to predict behavior after controlling for intentions. But Ajzen and Madden (1986) suggested that perceived control should predict behavior, at least to the extent that such perceptions mirror actual controllability. Regression analyses demonstrated that intentions predicted reported behavior, accounting for 9.O<7o of the variance for BSE and 11.5<^o of the variance for TSE (both ps <.01). For BSE, adding perceived control to the regression equation failed to increase the variance accounted for. However, for TSE, adding perceived control increased the total R^ by 5O<^o (from 11.7% to 17.5%), an increment that was nearly significant, F(l, 53) = 3.71,p =.06. These data suggest though weakly that intention and perceived control are not identical measures. Although perceived control and intentions may not be identical measures, they nevertheless shared a great deal of common variance (rs of.63 for BSE and.89 for TSE). One could conceive of perceived control as a two-part construct, with one part refiecting motivation (i.e., intentions) and a second part refiecting perceived competence (i.e., self-efficacy). To explore this

10 240 McCAUL, SANDGREN, O'NEILL, HINSZ possibility, we conducted a regression analysis that tested whether perceived control added to the prediction of reported behavior after intentions and self-efficacy had entered the equation. If perceived control should fail to contribute to the equation, our speculation regarding the two components of perceived control would have some empirical support. Unfortunately, the results of these analyses were not uniform across BSE and TSE. For TSE, perceived control still tended to predict behavior after both intentions and self-efficacy had been entered {p <.08), whereas for BSE, perceived control did not. Discussion The following conclusions can tentatively be drawn from the data in Experiment 1: 1. As predicted by the theory of planned behavior, attitudes, subjective norm, and perceived control each predicted intentions to conduct BSE and TSE. In addition, self-efficacy predicted intentions. These findings complement those of Brubaker and colleagues (Brubaker & Fowler, 1990; Brubaker & Wickersham, 1990; Murphy & Brubaker, 1990), who also found support for the theory of planned behavior and the additional role of self-efficacy in the performance of TSE. 2. As predicted by the theory of planned behavior, perceived control predicted intentions after attitudes and subjective norm had been entered into the equation. At least for these health-related behaviors, perceived control was an important predictor. On the other hand, self-efficacy predicted intentions over and above attitudes and subjective norm only for BSE-not for TSE. It should be noted that Brubaker and Fowler (1990) discovered that self-efficacy for performing TSE did add significantly to the prediction of intentions. Thus, the usefulness of self-efficacy in predicting health-protective behaviors requires further study. 3. Contrary to expectations, we observed differences between the predictive power of our measures of perceived control and self-efficacy. Specifically, whereas perceived control uniquely predicted intentions, selfefficacy failed to do so once perceived control was entered into the regression equations. Participants apparently perceived a difference in these two measures, and that difference was reflected in their relative predictive power. In general, these data fit well with expectations drawn from the theory of planned behavior. The construct of perceived control adds to the theory of reasoned action as an important predictor of intentions to behave. Moreover, perceived control appears to be more important than self-efficacy for

11 THEORY OF PLANNED BEHAVIOR AND SELF-EFFICACY 241 cancer self-examination behaviors. It is important to recognize the replicability of these findings across two related but distinct behaviors for women and men: BSE and TSE. Still, confidence in the generality of the data would be much improved with a replication of another area of self-protective health actions. To that end, we describe a second experiment. EXPERIMENT 2 Although the Experiment 1 data were generally consistent with the theory of planned behavior, some questions remain. First, it is unclear whether our measure of perceived control was actually tapping a different construct than our measure of intentions. We asked whether perceived control would predict reported behavior after controlling for intentions and discovered a mixed answer: Perceived control failed to predict BSE behavior but did predict TSE behavior. Second, it was unclear whether perceived control emerged as a better predictor than self-efficacy because of the nature of the different theoretical constructs or because the self-efficacy measure was less reliable (i.e., it consisted of a single item). Third, we explored whether perceived control might actually be tapping both intentions and perceived competence (self-efficacy), but perhaps because of the measurement issue just alluded to, the data from Experiment 1 did not provide a satisfactory answer. In the second experiment, we examined the theory of planned behavior in the context of a regimen to prevent periodontal (gum) disease. Participants were identified as "at risk" for the development of periodontal disease and were invited to enter a treatment program intended to facilitate adherence to a plaque prevention regimen. The regimen involved daily brushing and fiossing self-care skills that may prevent peridontal disease (e.g., Lobene, Soparkar, & Newman, 1982). At the conclusion of treatment, participants completed measures of each element of the theory of planned behavior and a self-efficacy measure, and they reported their brushing and fiossing behaviors at a 2-month follow-up. Subjects Eighty-one college students (49 men, 32 women) were recruited from introductory psychology classes {n = 18) and from a campus organization for older-than-average students {n = 63). All participants were screened and then selected because they showed periodontal bleeding (an early sign of periodontal disease) and reported fiossing less than three times per week. Participants averaged 30.2 years of age.

12 242 McCAUL, SANDGREN, O'NEILL, HINSZ Procedure Participants took part in three treatment sessions over a 1-month period in which they learned how to remove plaque and were given assistance, based on social learning theory, to aid regimen adherence. After the 1-month treatment, an 8-week maintenance phase ensued during which minimal contact with the experimenters occurred. All participants returned to the laboratory at the end of this phase to complete measures taken from the theory of planned behavior and a measure of self-efficacy expectations (see Measures section). At 2 months following this session, participants were interviewed by phone about the frequency of their recent dental hygiene behavior. Participants were randomly assigned to one of three conditions. In a control condition, participants were exposed to educational messages, skills training, and 3 weeks of self-monitoring. In two experimental conditions, participants engaged in additional treatment components and continued self-monitoring over the 2-month maintenance period. For one of the experimental groups, plaque removal goals were reset such that they were asked to remove plaque thoroughly every other (rather than every) day. Two months after treatment, the daily goal group showed greater adherence to flossing behavior than the less frequent goal and control conditions, but this difference disappeared by 6 months posttreatment. The data presented here are collapsed over conditions. Measures A specific description of each measure for flossing is provided here; we collected parallel measures related to brushing. As in Experiment 1, our measures were constructed whenever possible using established procedures (e.g., Ajzen & Fishbein, 1980). Attitudes. Attitudes toward flossing were collected from five 7-point semantic-differential scales with endpoints labeled good-bad, harmfulbeneficial, pleasant-unpleasant, wise-foolish, and worthless-valuable. The specific attitudinal stem was "My flossing once a day would be..." The five items were all intercorrelated so they were summed to form a single attitudinal index (alpha levels =.78 for flossing and.87 for brushing). For the entire sample, the average attitudes were strongly positive (brushing, M = 31.5, SD = 3.1; flossing, M = 29.9, SD = 3.0). Subjective norm. The subjective norm was measured using a single item that read "Most people who are important to me think that I should floss my teeth once a day." Responses were measured on a 7-point scale

13 THEORY OF PLANNED BEHAVIOR AND SELF-EFFICACY 243 ranging from strongly disagree (1) to strongly agree {!). The average score was 4.76 {SD = 1.29) for flossing and 5.23 {SD = 1.22) for brushing. Intentions. Intentions were measured using two items: "I intend to fioss my teeth at least once a day over the next 3 months" and "I intend to floss my teeth at least every other day over the next 3 months." These items were highly intercorrelated {r =.71) and were averaged for all analyses. Intentions to brush were measured by a single item: "I intend to brush my teeth twice a day over the next 3 months." Average intentions for fiossing were 5.94 {SD = 1.13) and for brushing they were 6.35 {SD = 0.86). Perceived control. perceived control: Participants were asked four questions to measure 1. What is the likelihood that if you try you will manage to fioss your teeth once a day over the next 3 months? 2. What is your best estimate that an attempt on your part to fioss your teeth in a correct manner each time over the next 3 months would be successful? 3. What is the likelihood that if you try you will manage to spend the time to fioss your teeth thoroughly each time over the next 3 months? 4. What is your best estimate that an attempt on your part to spend the time to fioss your teeth in a correct manner each time over the next 3 months would be successful? These questions were answered using a 100-point scale ranging from not at all likely (1) to extremely likely (100). Responses to the four items were averaged (alpha values =.94 for fiossing and.78 for brushing). Average perceived control for fiossing was 79.3 {SD = 19.3) and for brushing it was {SD = 11.27). Self-efficacy. The self-efficacy scale included four items that measured expectations about successful performance ("I could fioss in the correct marmer," "I could fioss all of my teeth," "I could take the time to fioss my teeth well," and "I could floss my back teeth as well as my front teeth"). These items, measured on 100-point scales, were averaged to form a single scale (alphas =.93 for fiossing and.94 for brushing). Average self-efficacy for fiossing was 89.4 {SD = 13.22) and for brushing it was 95.6 {SD = 7.1). Reported behavior. At the 2-month follow-up, participants estimated the number of times during the previous week that they had fiossed and

14 244 McCAUL, SANDGREN, O'NEILL, HINSZ TABLE 3 Correlations Among Planned Behavior Variables, Self-Efficacy Expectations, and Reported Behavior for Dental Hygiene Behaviors Subjective Perceived Self- Attitude Norm Control Efficacy Intentions Behavior Brushing Attitude Subjective norm Perceived control Self-efficacy Intentions Behavior * 21*.17* *.16.58*.04 Flossing Attitude Subjective norm Perceived control Self-efficacy -.45* 22* 27* *.22*.37*.71*.36* Intentions Behavior *p < * *.00.31*.31*.37*.33* brushed their teeth.^ Average flossing score was 3.92 {SD = 2.02) and average brushing scores were 13.2 {SD = 4.72). Results Table 3 presents the intercorrelations among all variables from the theory of planned behavior as well as self-efficacy expectations and reported behavior. As the table reveals, most of these correlations were in the expected direction and were statistically significant {ps <.05, two-tailed). Predicting intentions. The results of regression analyses used to test the theory of planned behavior are presented in Table 4. As in Experiment 1, attitudes toward the behavior and the subjective norm were first entered into the equation to predict intentions to brush or intentions to floss. In each case, these two variables predicted a significant proportion of the variance in intentions {R^ =.11 for brushing and.15 for flossing). Following the introduction of attitudes and subjective norms into the regression equation, perceived control was entered. As Table 4 shows. ^Although the phone caller pleaded for honesty, there is nevertheless reason for caution in trusting the self-reported behavioral data. However, a similar phone measure was taken earlier in the study when some of the participants were self-monitoring daily. The correlations between the self-monitoring data and the phone-call data were strong (rs =.70 and.85 for brushing and flossing behaviors, respectively).

15 THEORY OF PLANNED BEHAVIOR AND SELF-EFFICACY 245 TABLE 4 Results of Regression Analyses Predicting Intentions to Perform Dental Hygiene Brushing Predictive Variables Beta Multiple R R^ Change Step 1. Attitudes + Subjective norm Step 2. Perceived control Step 1. Attitudes -I- Subjective norm Step 2. Self-efficacy Step 1. Attitudes -f- Subjective norm -1- Self-efficacy Step 2. Perceived control Step 1. Attitude -1- Subjective norm -1- Perceived control Step 2. Self-efficacy ^ ^ Flossing Predictive Variables Beta Multiple R R^ Change Step 1. Attitudes -1- Subjective norm Step 2. Perceived control Step 1. Attitudes -l- Subjective norm Step 2. Self-efficacy Step 1. Attitudes -1- Subjective norm -\- Self-efficacy Step 2. Perceived control Step 1. Attitudes -1- Subjective norm + Perceived control Step 2. Self-efficacy ^ ^Indicates that the R^ increment is not statistically significant. perceived control added significantly to the prediction of intention for brushing, F{\, 75) = 29.3, p <.001, and for flossing, F(l, 74) = 80.8, p <.001. Perceived control predicted a great deal of the remaining variance, an increase of 25*^0 for brushing and 45 Vo for flossing. The results were less consistent when self-efficacy was entered into the regression equation following the introduction of attitudes and subjective norms. Self-efficacy failed to predict brushing intentions (F < 1) but was a significant predictor of flossing intentions, F{1, 74) = 9.42, p <.01, R^ change =.10.

16 246 McCAUL, SANDGREN, O'NEILL, HINSZ Perceived control versus self-efficacy. Two multiple regression analyses for each behavior were used to test the comparative contributions of perceived control and self-efficacy expectations. First, we examined whether self-efficacy contributed to the prediction of intentions after attitude, subjective norm, and perceived control had been entered. Selfefficacy failed to contribute to the equation in either case {ps >.1). We also asked whether perceived control would predict intentions after self-efficacy had been added to the equation together with attitude and subjective norm. In these analyses, perceived control did contribute significantly, with F(l, 74) = 29.4, p <.001, for brushing, and F{1, 73) = 63.5, p <.001, for fiossing. Thus, whereas perceived control appeared to play a unique role in predicting intentions to bru^)h and fioss, self-efficacy failed to predict intentions once the level of perceived control was known. Predicting reported behavior. Similar to Experiment 1, perceived control was again a strong predictor of intentions in Experiment 2. Still, it is conceivable that the strong control-intentions relation arose because the items measuring control were actually measuring intentions or some combination of intentions and self-efficacy. If the first case were true, we would not expect perceived control to predict reported behavior after controuing for intentions. Regression analyses predicting fiossing and brushing behaviors showed that intentions predicted each behavior (/^ =.11 for brushing and R^ =.09 for fiossing). Perceived control added significantly to the prediction of brushing {R^ increment =.06) and fiossing {R^ increment =.02), suggesting that the intention and perceived control measures were not identical. We again performed an additional analysis to see whether perceived control might be best described as a measure combining intentions and self-efficacy, we found that for fiossing, once intentions and self-efficacy had entered the equation predicting reported behavior, perceived control no longer did so (Fto enter < 1). For brushing, however, perceived control remained a reliable predictor {R^ increment =.06, /? =.02). GENERAL DISCUSSION Although we describe two studies in this article, those studies actually addressed four separate health-protective behaviors: breast and testicular self-exam, and tooth brushing and fiossing. Thus, the consistent findings across these four behaviors indicate strong generalizability for the performance of health-protective behaviors. One such finding supports the theoretical predictions of both the theory of reasoned action and the theory of planned behavior. Specifically, attitudes and subjective norms routinely

17 THEORY OF PLANNED BEHAVIOR AND SELF-EFFICACY 247 predicted intentions to perform self-protective health behaviors, supporting the value of these theories in the health area. More important, perceived control was a powerful predictor of intentions across all four healthprotective behaviors; indeed, perceived control was the best predictor of intentions. These findings complement those of Madden, Ellen, and Ajzen (1992), who showed that perceived control enhanced the prediction of behavioral intentions across a wide variety of activities. Together, these studies provide strong support for Ajzen's theoretical emphasis on perceived control. The importance of perceived control grows when one considers that researchers have frequently used other plausible predictors and have failed to improve on the theory of reasoned action. In a recent study in a similar context, for example, Timko (1987) examined determinants of the intentions of women to delay seeking medical care for a breast cancer symptom. A variety of variables external to the theory of reasoned action, including emotional reactions, judgments of seriousness, and the "powerful others" health locus of control scale correlated with intentions. But none of these variables, including health locus of control, predicted intentions after controlling for attitudes and subjective norms. In our studies, the pattern of results involving perceived control was generally consistent across the four behaviors studied. However, a subtle difference emerged. When self-efficacy by itself (i.e., ignoring perceived control) was used to predict intentions, it added to the regression equation for BSE and flossing but not for TSE and brushing. One might be tempted to argue that self-efficacy was unimportant for brushing because everyone should feel that they have the competence to perform that behavior (and, indeed, the mean self-efficacy levels for brushing were very high). However, this notion would not explain the BSE-TSE difference, as self-efficacy was higher for BSE than TSE but was nevertheless more predictive of BSE intentions. Although we have no ready explanation for these differences across behaviors, perhaps the most important point is that the self-efficacy measure was invariably the weakest variable in the regression equations.^ In contrast to the self-efficacy findings, the data clearly point to an important theoretical role for perceived control. But the studies also raise of the inconsistent findings in these studies could be attributed in part to problems with the data; some of the variables had nonnormal distributions, and there were sometimes extremely high intercorrelations among predictor variables. We conducted one additional set of analyses that reduced the impact of these problems, thereby lending confidence to our conclusions. Specifically, we standardized all individual variables and then conducted our major analyses on the entire data set, across all four behaviors. These analyses, which were based on approximately 280 observations, produced normalized distributions and reduced the maximum intercorrelation to.58. The analyses also confirmed each of the major conclusions noted in our discussion.

18 248 McCAUL, SANDGREN, O'NEILL, HINSZ issues regarding the nature of this theoretical construct. We created perceived control measures in each study that closely resembled measures Ajzen used in a study of weight loss (Schifter & Ajzen, 1985). For example, in Experiment 1, we asked, "What is the likelihood that if you try you will manage to conduct breast self-examination once a month over the next six months?" We need to know, however, how this particular notion of perceived control differs from self-efficacy and how it differs from intentions. Perceived Control and Self-Efficacy In these studies, perceived control produced results different from those produced by self-efficacy, a finding that disputes Ajzen's suggestion that the two constructs are equivalent (Ajzen & Madden, 1986). In particular, after taking into account perceived control, self-efficacy failed to predict intentions, but after controlling for self-efficacy, perceived control continued to add strongly to the prediction of intentions. We suspect that these results were partly produced by our decision to operationalize self-efficacy as one's perceived ability to perform the protective health behaviors (particularly in Experiment 2). Early on, Bandura (1977) defined an efficacy expectation as "the conviction that one can successfully execute the behavior required to produce the outcomes" (p. 193). Depending on the outcome one selects, our emphasis on perceived ability could be seen as either perfectly reasonable or an unfair test of Bandura's notions. If the outcome in Experiment 2, for example, is "thoroughly removing plaque," then our measure of fiossing efficacy seems appropriate. If the outcome is "preventing periodontal disease," then one must measure efficacy not only for the ability to execute the behavior successfully once, but also for the ability to succeed in one's performance repeatedly. Although our emphasis on the more limited outcome fits with some authors' view of self-efficacy (e.g., Kirsch, 1986), Bandura would probably prefer a much more liberal measure, one "concerned not with the skills one has, but with beliefs about what one can do with the subskills one possesses in dealing with continuously changing realities, most of which contain ambiguous, unpredictable, and stressful elements" (Bandura, 1986, p. 368). A broader measure of self-efficacy might well eliminate the apparent differences between self-efficacy and perceived control. It is nonetheless important to learn that if we equate self-efficacy with perceived skills (i.e., "Do I have the ability to perform this behavior"?), it is a poorer predictor of intentions than perceived control. Moreover, if we were to increase the scope of the measure of self-efficacy so that it became identical to perceived control, we would still be left with a more general issue: What exactly are these variables measuring?

19 THEORY OF PLANNED BEHAVIOR AND SELF-EFFICACY 249 Perceived Control and Intentions Consider our measure of iiitentions in Experiment 2 as compared to the measure of perceived control. To measure intentions, participants responded to the statement "I intend to floss my teeth at least once a day over the next 3 months," whereas to measure perceived control participants answered the question "What is the likelihood that if you try you will manage to floss your teeth once a day over the next 3 months?" These measures seem similar and, as noted earlier, intentions and perceived control were closely correlated (the average r across all four behaviors in the two experiments was.70). But regression analyses suggested that control and intent were not identical measures. Specifically, we discovered that perceived control sometimes predicted behavior after controlling for brushing and flossing intentions, suggesting that perceived control is not the same construct as intention. Rather than measuring intentions alone, perceived control may actually have two components: one measuring intentions and a second measuring something like perceived competence. Although our data were not wholly in line with this possibility, they left the question open. In particular, when predicting reported flossing and BSE behaviors, perceived control no longer entered the equation after intentions and self-efficacy (perceived competence) had been entered. Summary Additional theoretical and measurement efforts are obviously needed to define precisely what is meant by perceived control and to specify exactly how this construct differs from self-efficacy and intentions to act. Such measurement questions have surrounded the notion of self-efficacy since its inception (see Corcoran, 1991; Eastman & Marzillier, 1984; Kazdin, 1978) and, because perceived control is a critical component of the theory of planned behavior, important questions about the nature of that construct as well will probably become an issue (Netemeyer, Burton, & Johnston, 1991). The distinction (or lack of distinction) between intentions and perceived control, for example, reminds one of Kirsch's charge that measures of self-efficacy in phobic contexts correspond exactly to measures of intentions (Kirsch, 1982). Regardless of the eventual outcome of such research, it is now clear that some construct such as perceived control must be added to the theory of reasoned action, as Ajzen (1985, 1991) has proposed. Our data show the importance of perceived control across four separate behaviors, and, therefore, the results also have implications for understanding and controlling self-protective health behaviors. Three constructs contribute indepen-

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