Social Influences and the Theory of Planned Behaviour: Evidence for a Direct Relationship Between...

Psychology and HealthOctober 2003, Vol. 18, No. 5, pp. 567–583

SOCIAL INFLUENCES AND THE THEORY OF

PLANNED BEHAVIOUR: EVIDENCE FOR A

DIRECT RELATIONSHIP BETWEEN PROTOTYPES

AND YOUNG PEOPLE’S EXERCISE BEHAVIOUR

AMANDA RIVIS* and PASCHAL SHEERAN*

Department of Psychology, University of Sheffield, Sheffield S10 2TP, UK

(Received 20 November 2001; In final form 3 October 2002)

This study employed a prospective questionnaire design to assess the predictive validity of prototypes anddescriptive norms in relation to young people’s exercise behaviour after variables from the theory of plannedbehaviour (TPB) and past behaviour had been controlled. Findings supported the utility of the TPB, descrip-tive norms, prototype similarity, and past behaviour in predicting intentions and behaviour. Importantly,prototype similarity was directly associated with behaviour, both on its own and through its relationshipwith descriptive norms, even after controlling for the TPB and past behaviour. Findings are discussedin relation to; (1) the role of social identification in motivating health-related decisions and behaviour,(2) the current conceptualisation of social influences in the TPB, and (3) recent research on the ‘‘percep-tion-behaviour expressway’’.

Keywords: Predictive validity; Theory of planned behaviour; Exercise behaviour

Engaging in regular physical activity has been linked with various long-term healthbenefits including a reduction in the risk of coronary heart disease (CHD) ( Oberman,1985; Cleroux et al., 1999), one of the primary causes of premature death in modernindustrial societies (Evans, 1991). Although the risks of developing CHD are greaterin middle age than early adulthood, the process which causes CHD—atherosclero-sis—occurs throughout life (Evans, 1991). Despite evidence that regular physical activ-ity reduces the risk of atherosclerosis as early as adolescence (Vasankari et al., 2000),exercise habits tend to dissipate as soon as individuals enter this developmental stage(U.S. Department of Health and Human Sciences, 1986). Given that one-third of18–19 year olds in the UK attend universities, investigation of the factors that underlieexercise behaviour among this population should prove beneficial in informing inter-ventions designed to increase exercise participation among young people. The presentresearch examined the roles of prototypes and descriptive norms in predicting exerciseamong UK university students and tested the utility of augmenting Ajzen’s (1991)theory of planned behaviour (TPB) with these constructs.

*Corresponding author. E-mail: [email protected] or [email protected]

ISSN 0887-0446 print: ISSN 1476-8321 online � 2003 Taylor & Francis Ltd

DOI: 10.1080/0887044032000069883

https://www.researchgate.net/publication/12395123_Reduced_mildly_oxidized_LDL_in_young_female_athletes?el=1_x_8&enrichId=rgreq-a639241c-8378-4b31-a7f4-6a9a715d033d&enrichSource=Y292ZXJQYWdlOzI0MDIzNjc1ODtBUzoxNzMzMzcxNDE1ODc5NjhAMTQxODMzODIwMzExNA==

The Theory of Planned Behaviour

The TPB is one of the most widely applied models of the cognitive determinants ofbehaviour and takes into account both social influences and personal factors. Socialinfluences are conceptualised in terms of the pressure that people perceive from import-ant others to perform, or not to perform, a behaviour (subjective norm). Subjectivenorm is determined by a person’s beliefs about the extent to which important otherswant them to perform a behaviour (normative beliefs; e.g., ‘‘My friends think that Ishould exercise at least six times over the next two weeks’’) multiplied by one’smotivation to comply with those people’s views (e.g., ‘‘I generally want to do whatmy friends think I should do’’). Subjective norms are proposed to influence behaviourthrough their impact upon intentions. The intention construct summarises the individ-ual’s motivation to act in a particular manner and indicates how hard the personis willing to try, and how much time or effort he/she is prepared to expend, in orderto perform a behaviour (Ajzen, 1991, p.199). Also important in the prediction ofintentions are people’s evaluations of a behaviour (attitudes; e.g., ‘‘For me, exercisingat least six times in the next two weeks would be wise/foolish’’), and the degree ofcontrol they believe they have over performing the behaviour, ( perceived behaviouralcontrol; e.g., ‘‘Exercising at least six times in the next two weeks is entirely under/outside my control’’). Attitudes are determined by beliefs about the likelihoodof outcomes of performing the behaviour (behavioural beliefs, e.g., ‘‘It is likely/unlikelythat I will feel fitter if I exercise at least six times in the next two weeks’’) multipliedby evaluations of those outcomes (outcome evaluations, e.g., ‘‘Feeling fitter is good/bad’’). Perceived behavioural control is determined by beliefs concerning the factorsthat may inhibit or facilitate performance of the behaviour multiplied by the perceivedpower of these factors (control beliefs; e.g., ‘‘Exercising at least six times in thenext two weeks requires time’’ and power, e.g., ‘‘Having time increases the likelihoodof my exercising at least six times in the next two weeks’’). According to theTPB, the more positive people’s attitudes and subjective norms, and the greatertheir perceived behavioural control regarding a behaviour, the more likely they areto intend to perform that behaviour. Similarly, the stronger people’s intentions,the more likely they are to perform the behaviour. To the extent that perceptionsof control accurately reflect the person’s actual control over behavioural performance,perceived behavioural control can also directly affect behaviour (Sheeran et al.,in press).The TPB has been successfully applied to the prediction of exercise intentions and

behaviour in a number of studies (see, e.g., Kimiecik, 1992; Godin et al., 1993;Courneya, 1995; Norman et al., 2000; Hagger et al., 2001). In a meta-analysis,Godin and Kok (1996) reported that TPB variables explain, on average, 42 and 36%of the variance in exercise intentions and behaviour, respectively, percentages whichcompare favourably with findings from applications of the TPB in other domains(for reviews see Sheeran and Taylor, 1997; Conner and Armitage, 1998; Sheeran,2002; Armitage and Conner, 2001). Although these effect sizes are impressive, (cf.Cohen, 1992), these percentages still mean that around 58% of the variance in inten-tions and 64% of the variance in behaviour is left unexplained. While some of the unex-plained variance can be attributed to methodological factors (cf. Sutton, 1998),conceptual factors should also be considered.

568 A. RIVIS AND P. SHEERAN

Descriptive Norms

The comparative weakness of the subjective norm–intention relation is of particularrelevance here. Personal factors (i.e., attitudes and perceived behavioural control)typically emerge as stronger predictors of exercise intentions than subjective norms(e.g., Kimiecik, 1992; van Ryn et al., 1996; Norman et al., 2000). In a meta-analysis,Hausenblas et al. (1997) reported an average correlation between attitude and intentionof 0.52, and an average correlation between perceived behavioural control and inten-tion of 0.43. In contrast, a much weaker coefficient of 0.27 was reported between sub-jective norms and intentions. Such evidence has led some researchers to conclude thatattitudes and perceived behavioural control are the most important variables and thatintention to exercise is not strongly influenced by social pressure (Godin, 1993; Blue,1995; Godin and Kok, 1996).An alternative explanation for the comparative weakness of the subjective norm–

intention relation concerns the conceptual status of the subjective norm construct.There is a long-standing distinction in the literature on social influence between theis (descriptive) and the ought (injunctive) meaning of social norms because theseare separate sources of motivation (Deutsch and Gerard, 1955). The subjective normcomponent of the TPB is an injunctive social norm since it is concerned with perceivedsocial pressure whether or not to engage in a behaviour (i.e., what other people thinkthat one ought to do). Subjective norms motivate behaviour through the possibilityof gaining approval or disapproval from significant others for one’s intentionsand actions. Descriptive norms, on the other hand, refer to perceptions of otherpeople’s behaviour in the domain. Here, the behaviour of significant others motivatesthe person by showing him or her what is the typical or normal thing to do, and whatis likely to be an effective and adaptive decision (‘‘If everyone is doing it, it must be asensible thing to do’’; cf. Cialdini et al., 1990).Factor analytic studies indicate that descriptive norm does not refer to the same con-

struct as subjective norm (e.g., Grube et al., 1986; White et al., 1994; Sheeran andOrbell, 1999). Moreover, a number of studies suggest that descriptive norm enhancesthe TPB’s capacity to predict behavioural intentions (e.g., Grube et al., 1986;Morgan and McGree, 1986; Conner and McMillan, 1999; Sheeran and Orbell, 1999;McMillan and Conner, 2003; Rivis and Sheeran, in press). In a recent meta-analyticreview, Rivis and Sheeran (in press) found that descriptive norms explained an incre-ment of 5% of the variance in intentions, over and above subjective norm, attitude,and perceived behavioural control.Notwithstanding the success of descriptive norms in applications to date, the import-

ance of this construct for exercise behaviour remains unclear—for two reasons. First,only a handful of studies have examined this construct in relation to health-promoting,as opposed to health-risk, behaviour (see Rivis and Sheeran, in press, for a review).Further tests are therefore warranted to determine generality. Second, previous studiesof descriptive norms did not control for the effects of past behaviour which has beenshown to make a significant contribution to the variance explained in intentions(e.g., Bagozzi, 1981; Ouelette and Wood, 1998; Fekadu and Kraft, 2001) and behaviour(e.g., Valois et al., 1988; Godin and Lepage, 1993; Bagozzi and Kimmel, 1995; Normanand Smith, 1995; Norman et al., 2000; Yzer et al., 2001; Abraham and Sheeran, inpress). There is also evidence to suggest that past behaviour might drive perceptionsof the norm. For example, people who engage in a particular behaviour tend to

SOCIAL INFLUENCES AND THE TPB 569

over-estimate the percentage of other people who perform that behaviour—the‘‘false consensus effect’’ (Ross et al., 1977). Hence, the predictive power of descriptivenorms might have been diminished had past behaviour been controlled in previousstudies. Controlling for past behaviour also has particular significance in the contextof exercise because people must exercise regularly for health benefits to accrue.

Prototypes

A further source of social influence that is currently neglected by the TPB is prototypeperception. Prototypes are the images that young adults have of the types of peoplewho engage in certain health behaviours (e.g., the typical smoker is ‘‘cool’’, or thetypical drinker is ‘‘one of the lads’’). The role of prototypes in young people’shealth-related decisions has been examined from the perspective of Gibbons and collea-gues’ prototype/willingness model of adolescent health-risk behaviour (PWM; Gibbonset al., 1998). According to the PWM, two aspects of prototype perception influencehealth-related decisions: the degree of liking one has for the risk image ( prototypeevaluation) and similarity of the image to oneself ( prototype similarity). Prototypeperceptions influence people’s behaviour through the process of social comparison(Festinger, 1954) whereby individuals compare themselves with the prototype andits attributes. The more positive people’s evaluations of the prototype, and the greatertheir perceived similarity to the prototype, the greater will be their inclination to engagein the health-risk behaviour described in the prototype.Support for the motivational power of prototypes has been obtained in studies

of young people’s health-risk behaviours. For example, Blanton et al. (1997) foundthat the more favourable were adolescents’ images of the typical drinker and typicalsmoker, the more willing they were to engage in drinking and smoking behaviourand the more likely they were to subsequently perform the behaviours if the oppor-tunity arose. Similarly, Gibbons et al. (1995) found that the more favourable adoles-cents’ images were of ‘‘the type of teenager who gets [a girl] pregnant’’, and the moresimilar they perceived themselves to be to that image, the greater was their willingnessto engage in unprotected sex. More recently, in an integration of the TPB and thePWM, Rivis and Sheeran (2003) found that undergraduate students’ evaluations of,and similarity to, the typical ‘‘binge drinker’’ contributed to the prediction of intentionsand behaviour even after TPB variables had been controlled.However, the ability of prototype similarity and prototype evaluation to predict

health-related decisions and behaviour over and above the TPB and descriptive normsis unclear since previous PWM studies have not controlled for the TPB and descriptivenorms. The importance of prototypes in relation to health-promoting behavioursis also unclear since, to date, the literature on prototypes has focused exclusivelyupon health-risk, as opposed to health-promoting, behaviours. However, we arguethat images may be equally important in motivating health-promoting behaviours, atleast among adolescents and young adults, for two reasons. First, research on youngpeople’s drinking and smoking behaviour suggests that acquiring the characteristicsof the prototype for their own self-images could be goals for young people whenthey engage in these behaviours (Leventhal and Cleary, 1980; Rivis and Sheeran,2003). Second, health-promoting images are likely to be associated with more positive(desirable) attributes than health-risk images, and people typically seek actions thatassociate them with positive images and avoid actions that associate them with negative


images (cf. Swann et al., 1987). Thus, there are grounds for expecting that prototypesimilarity and prototype evaluation will (positively) predict young people’s intentionsto engage in exercise.

Descriptive Norms as a Moderator of the Relationship between

Prototypes and Behaviour

Research examining the combination of social images and descriptive norms suggeststhat the impact that prototypes have upon health-related decisions and behaviourmight be moderated by descriptive norms. Blanton et al. (2001) showed that when par-ticipants believed their peers made healthy decisions (e.g., intended to get a flu shot),they were most influenced by a negatively framed communication that emphasisedthe undesirable attributes of people who made unhealthy decisions. In contrast, whenthey believed their peers made unhealthy decisions they were most influenced by a posi-tively framed communication that emphasised the desirable attributes of people whomade healthy decisions. Similarly, Gibbons and Eggleston (1996) found that people’simages of the ‘‘typical smoker’’ did not predict smoking status (e.g. cessation) amongpeople who had a lot of friends and family members who smoked. Thus, we further pre-dict that the relationship between prototypes and intentions relating to a health-pro-moting behaviour will be strongest among people who have a lot of friends whoengage in that health-promoting behaviour.

The Present Study

The foregoing discussion provides the following rationale for the present study: (a)few studies have assessed the role of descriptive norms in the context of the TPB inrelation to health-promoting behaviours, and none of these studies controlled forpast behaviour, and (b) the capacity of prototype evaluation and prototype similarityto predict health-promoting decisions and behaviour has not been tested. Thus, theaim of the current study is to assess the ability of prototype similarity, prototypeevaluation, and descriptive norms to enhance the prediction of exercise intentionsand behaviour after variables from the TPB and past behaviour have been taken intoaccount.

METHOD

Participants and Procedure

Three-hundred and thirty-three undergraduate students at a UK university volunteeredto take part in a prospective questionnaire survey concerning their ‘‘views about aspectsof students’ lifestyles’’. At Time 1, participants completed measures of TPB variables,prototypes, and past behaviour. Two weeks later (Time 2), N¼ 225 participants com-pleted a second questionnaire where they reported their exercise behaviour—a responserate of 68%.


Measures

Theory of Planned Behaviour variables and descriptive norms were measured withrespect to ‘‘exercising at least six times in the next two weeks’’. In order to reduce ambi-guity about the meaning of ‘‘exercise’’, and in line with previous researchers (Normanand Smith, 1995; Terry and O’Leary, 1995; Sheeran and Orbell, 2000), the followingdefinition of exercise was printed on the front of both questionnaires: ‘‘Exercise heremeans at least 20min of moderate/vigorous exercise. Exercise includes activities suchas aerobics, badminton, jogging, rugby, etc. It does not include activities such as walk-ing to the bus stop, dancing at clubs, etc.’’ Unless otherwise stated, responses to allitems were on 7-point bipolar scales.Attitudes were measured by responses to the stem ‘‘For me, engaging in exercise at

least 6 times over the next two weeks would be . . .’’ on six bipolar scales (pleasant-unpleasant, wise-foolish, healthy-unhealthy, beneficial-harmful, exciting-boring, andenjoyable-unenjoyable). Reliability was satisfactory (�¼ 0.77). Intentions to exercisewere measured by three items: ‘‘I will engage in exercise at least 6 times over the nexttwo weeks’’ (definitely yes-definitely no), and ‘‘I intend to exercise at least 6 times inthe next two weeks’’ (definitely do-definitely don’t and strongly agree-strongly disagree)(�¼ 0.92). Two items assessed subjective norms: ‘‘Most people who are important tome think I should exercise at least 6 times in the next two weeks’’ (strongly agree-strongly disagree and likely-unlikely) (�¼ 0.76). Perceived behavioural control wasmeasured by four items: ‘‘I feel in complete control of whether or not I exercise atleast 6 times over the next two weeks’’ (strongly agree-strongly disagree), ‘‘Howmuch control do you have over exercising at least 6 times in the next two weeks?’’ (com-plete control-no control), ‘‘If I wanted to, I could easily exercise at least 6 times in thenext two weeks’’ (strongly agree-strongly disagree), and ‘‘Engaging in exercise at least 6times over the next two weeks would be . . .’’ (very easy-very difficult). Reliabilityfor these items was satisfactory (�¼ 0.70). Descriptive norms were assessed by twoitems: ‘‘Of the people you know, how many exercise at least 3 times a week?’’ on a5-point scale ranging from 1 (none) to 5 (all) and ‘‘Of the four people you know bestof your age, how many exercise at least 3 times a week?’’ Scores on the two measureswere standardised and were reliably combined (�¼ 0.67).

Prototype

The following definition of a prototype taken from Gibbons et al. (1995, p. 85), waspresented to participants:‘‘The following question concerns your images of people. What we are interested in

here are your ideas about typical members of different groups. For example, we all haveideas about what typical movie stars are like or what the typical grandmother is like.When asked, we could describe one of these images – we might say we think the typicalmovie star is pretty or rich, or that the typical grandmother is sweet and frail. We arenot saying that all movie stars or all grandmothers are exactly alike, but rather thatmany of them share certain characteristics’’.Whereas previous studies have all supplied participants with an experimenter-defined

series of bipolar scales, the present study employed an open-ended measure.Participants were asked to write down at least three characteristics that they thoughtdescribed the type of person who exercises at least 3 times a week. Evaluation of the


prototype was assessed by the ‘‘evaluation thermometer’’ (e.g., Campbell, 1971;Stangor et al., 1991; Haddock and Zanna, 1994). Participants were asked to indicatetheir overall evaluation of the type of person who engages in exercise at least 3 timesa week on a 1–100 scale. Similarity to the prototype was assessed by two items: ‘‘Ingeneral, how similar are you to the type of person who exercises at least 3 times aweek?’’ (very similar-not at all similar) and ‘‘Do the characteristics that describethe type of person who exercises at least 3 times a week describe you?’’ (definitelyyes-definitely no) (�¼ 0.75).

Past Behaviour

Past behaviour was assessed by participants’ reports of the number of times they hadengaged in exercise in the last month.1

Exercise Behaviour

Exercise behaviour at Time 2 was assessed by one item on a seven-point scale: ‘‘Howoften did you engage in exercise over the last two weeks?’’ (not at all-every day).

RESULTS

Descriptive Findings

Table I shows the means, standard deviations, and intercorrelations for the studyvariables. Intentions to exercise, subjective norms, and perceived similarity to theexercise prototype were generally modest, with all means close to the scale midpoints.Attitudes towards exercise were generally positive (M¼ 5.57, SD¼ 0.90) andparticipants believed that exercise was under their control (M¼ 5.33, SD¼ 1.27).Descriptive norms were moderate with respondents reporting that, on average,

1Ajzen (1991) argued that measures of past and future behaviour are frequently more compatible thanmeasures of intention and behaviour which lead to overestimates of the strength of the past behaviour–future behaviour relation compared to the intention–behaviour relation (see also Conner et al., 1999). Wetherefore used a different time frame for our measures of past behaviour and future behaviour in an attemptto reduce shared method variance.

TABLE I Means, standard deviations, and intercorrelations for study variables

1 2 3 4 5 6 7 8 9 Mean SD

Behaviour 1.00 0.57*** 0.40*** 0.33*** 0.19** 0.28*** 0.19** 0.17* 0.71*** 2.81 1.57

Intention 1.00 0.57*** 0.40*** 0.35*** 0.40*** 0.55*** 0.31*** 0.61*** 4.06 1.78

Attitude 1.00 0.37*** 0.23*** 0.24*** 0.48*** 0.35*** 0.38*** 5.57 0.90

Subjective norm 1.00 0.12* 0.27*** 0.22*** 0.16** 0.26*** 4.02 1.48

PBC 1.00 0.19*** 0.23*** 0.05 0.24*** 5.33 1.27

Descriptive norm 1.00 0.23*** 0.15** 0.33*** 0.00 0.87

Prototype similarity 1.00 0.36*** 0.46*** 4.07 1.51

Prototype evaluation 1.00 0.16** 0.00 0.87

Past behaviour 1.00 6.35 7.74

Note: N¼ 225 for correlations with behaviour. N¼ 333 for all other correlations. Descriptive norm is the mean of twoZ-scores. PBC¼Perceived Behavioural Control. *p<0.05; **p<0.01; ***p<0.001.


‘some’ of the people they knew exercised at least 3 times a week. On average, partici-pants reported having engaged in exercise 6 to 7 times in the last month. Table IIshows the content and percentage endorsements of the exercise prototype (84% agree-ment between independent raters). Respondents’ images of the kind of person whoexercises at least three times a week were predominantly positive with the most fre-quently endorsed characteristic being ‘‘physically fit’’ (88.6% of cases) and aroundthree-quarters of the sample perceiving him/her as a ‘‘motivated’’ and ‘‘healthy’’ typeof person. Evaluations of the exercise prototype were generally favourable with respon-dents giving a mean rating of 66 (out of 100).

Predictors of Intention

All study variables were highly correlated with intentions to exercise (all ps<0.001).In order to determine how well the study variables predicted behavioural intentions,a three-step hierarchical regression was conducted. Attitudes, subjective norms, andperceived behavioural control were entered on the first step, past behaviour wasadded on the second step, and descriptive norms, prototype evaluation, and prototypesimilarity were added on the third step.

TABLE II Content and percentage endorsementsof exercise prototype

Item % Cases

Physically fit 88.6Motivated 75.9Healthy 72.0‘‘Sporty’’ 25.9Athletic 14.5Carefree 13.0Outgoing/popular 12.7Desirable physical attributes 10.8A ‘‘bore’’ 10.8Miscellaneous 7.8Attractive 5.7Intelligent 4.5Self-assured 3.6

TABLE III Hierarchical regression of intention on study variables (N¼ 333)

Step Variable(s) entered � � � �

1 Attitude 0.44*** 0.32*** 0.22*** 0.22***Subjective norm 0.21*** 0.16*** 0.13*** 0.13***PBC 0.22*** 0.15*** 0.13*** 0.13***

2 Past behaviour – 0.42*** 0.33*** 0.33***3 Descriptive norms – – 0.13*** 0.13***

Prototype evaluation – – 0.07 0.06Prototype similarity – – 0.18*** 0.18***

4 Prototype evaluation�descriptive norm – – – 0.00Prototype similarity�descriptive norm – – – 0.00

R2 0.41 0.55 0.60 0.60Model F 75.77*** 101.23*** 69.54*** 53.92***

Note. PBC¼ perceived behavioural control. *p<0.05 **p<0.01 ***p<0.001.


As Table III shows, all TPB variables had significant �s in the first equationand accounted for 41% of the variance. The addition of past behaviour led to a signif-icant increment in the variance explained in intentions (R2 change¼ 0.14, Fchange¼ 105.45, p<0.001). The addition of the two aspects of prototype perceptionand descriptive norms was also associated with a significant increment in the variance(R2 change¼ 0.05, F change¼ 12.76, p<0.001) and significant �s were obtained forprototype similarity and descriptive norms. At the third step, 60% of the variance inintentions was explained with significant �s obtaining for the TPB variables, past be-haviour, descriptive norms, and prototype similarity.2,3

Moderator Analysis

We hypothesised that there would be a significant interaction between the two aspectsof prototype perception and descriptive norms such that the prototype similarity–intention and prototype evaluation–intention relationships would be strongest amongpeople who have a lot of friends who exercise.To test this hypothesis, we conducted moderated (linear) regression. Variables

were mean-centred to minimize problems with multicollinearity (Aiken and West,1991). The final column of Table III shows the regression of intention on the TPBvariables, past behaviour, descriptive norms, the two aspects of prototype perception,and the two interaction terms. Contrary to predictions, adding the interaction termsat the final step of the equation did not produce significant �s for these variables(�s¼ 0.00, ns) and was not associated with a significant increase the variance explainedin intentions (R2 change¼ 0.00, F change¼ 0.31, ns).

Predictors of Behaviour

Intentions were significantly correlated with exercise behaviour (r¼ 0.57, p<0.001) aswere all other study variables. Hierarchical regression analysis was used to test theability of the study variables to predict behaviour. In the first equation, behaviourwas regressed on the TPB variables. Past behaviour was added at the second step,and descriptive norms, prototype evaluation, and prototype similarity were added onthe third step. The results are shown in Table IV.

2In the initial analysis, we also included a fourth step in the regression. Based upon Gibbons and colleagues’predictions that prototypes are most strongly related to health-related decisions when a person believes theyare similar to the type of person who engages in the behaviour and has a favourable impression of that type ofperson, we added the interaction between prototype similarity and prototype evaluation at the final (fourth)step. However, the interaction was non-significant (�¼�0.01, ns) and did not alter the results of the mainanalysis. Similar non-significant findings were obtained when we included the interaction in the regressionrelating to behaviour (�¼�0.04, ns). Again, the results of the main analysis remained unchanged.

3While we believe that hierarchical regression analysis was the correct approach to adopt here, it is possiblethat the TPB constructs would not have been significant had we controlled for the effect of past behaviour—the construct most highly correlated with intentions. We therefore re-ran the regression using the conventionalmultiple regression approach (Judd and McLelland, 1989) which tests the effects of each variable controllingfor all other variables in the model. Findings were identical to those of the original hierarchical regression.Similar findings emerged when we used conventional multiple regression to analyse the data relating to theprediction of behaviour (i.e., the same variables were significant). We are grateful to an anonymous reviewerfor raising this issue.


The regression of behaviour on the TPB variables revealed a significant �for intentions but not for the other predictors. Intentions alone explained 34% ofthe variance in exercise behaviour. At the second step, the addition of past behaviourproduced a significant increment in the variance explained in behaviour (R2

change¼ 0.20, F change¼ 92.35, p<0.001) and intentions remained significant. Theaddition of descriptive norms, prototype evaluation and prototype similarity at thethird step did not significantly enhance the variance explained in behaviour, althoughthe � for prototype similarity was marginally significant (�¼ 0.11, p¼ 0.063).

Moderator Analysis

While the prototype similarity–descriptive norm and prototype evaluation–descriptivenorm interaction terms did not significantly contribute to the variance explained inintentions, we wondered whether, in view of our finding of a marginally significantdirect relationship between prototype similarity and behaviour, the interactionsmight make a direct contribution to the variance explained in behaviour. Specifically,we hypothesised that the relationship between the two aspects of prototype perceptionand exercise behaviour would be strongest among people who have a lot of friendswho exercise.We again tested our hypothesis using moderated (linear) regression. The final column

of Table IV shows the regression of behaviour on TPB variables, past behaviour,descriptive norms, the two aspects of prototype perception, and the two interactionterms. The results partly confirmed predictions: The interaction between prototypeevaluation and behaviour was non-significant; however, the interaction betweenprototype similarity and descriptive norms was significant and accounted for anadditional 1% of the variance in behaviour. However, we were concerned that theprototype similarity–descriptive norm interaction term had a significant � in the finalequation (�¼ 0.13, p<0.05) but was associated with only a marginally significant incre-ment in the variance explained in behaviour (R2 change¼ 0.01, F change¼ 2.67,p¼ 0.071). We therefore re-ran the regression entering the interaction betweenprototype similarity and descriptive norm on its own at the fifth step of the

TABLE IV Hierarchical regression of behaviour on study variables (N ¼ 225)

Step Variable(s) entered � � � �

1 Intention 0.48*** 0.18** 0.15* 0.15*PBC 0.02 �0.01 �0.01 �0.01Attitude 0.09 0.05 0.02 0.02Subjective norm 0.07 0.03 0.02 0.02

2 Past behaviour – 0.57*** 0.54*** 0.53***

3 Descriptive norms – – 0.03 0.01Prototype evaluation – – �0.02 �0.01Prototype similarity – – 0.11y 0.12*

4 Prototype evaluation� – – – �0.09descriptive normPrototype similarity� – – – 0.13*descriptive norm

R2 0.34 0.54 0.54 0.55Model F 28.38*** 50.60*** 32.30*** 26.77***

Note: PBC¼Perceived behavioural control. yp<0.06; *p<0.05; **p<0.01; ***p<0.001.


equation. As anticipated, this produced a significant � for the prototype similarity–descriptive norm interaction (�¼ 0.13, p<0.05) and led to a significant increment inthe explained variance (F change¼ 5.22, p<0.05).4,5

We decomposed the interaction using simple slope analyses (Aiken and West, 1991).In particular, we examined the regression lines for prototype similarity at three levels ofthe moderator (descriptive norm); the mean level, one standard deviation above themean, and one standard deviation below the mean. The nature of the interaction wasin line with predictions (Fig. 1). Among participants who knew few people who exercise(low descriptive norm), their perceived similarity to the exercise prototype made littledifference to their future exercise behaviour. At moderate levels of descriptive normit made slightly more difference. However, the difference is greatest among peoplewho know a lot of people who engage in exercise: in this group, people who believethey are very similar to the ‘‘type of person who exercises’’ engage in significantlymore exercise than people who think they are not similar to this prototype.

DISCUSSION

The aim of the current study was to investigate the predictive validity of descriptivenorms and prototypes in relation to young people’s exercise intentions and behaviour

4We examined whether there were differences on any of our measures between participants who werepresent at behavioural follow-up and those who were absent. A multivariate ANOVA revealed no significantdifferences between the samples on any of the measures, F(8,324)¼ 1.46, ns. Hence, the possibility that ourresults were due to sample bias seems unlikely.

5It is unlikely that the failure of intentions to mediate the effect of prototype similarity upon behaviourin the present study was due to measurement artifact. The reliability of our intention measure was high(�¼ 0.92) and similar to that obtained in other TPB studies on health-promoting behaviours utilisingthree-item measures (e.g., Norman et al., 2000; Sheeran et al., 2001). Importantly, these studies also foundthat variables not included in the TPB (e.g., gender and past behaviour) directly predicted behaviour, overand above the TPB variables.

FIGURE 1 Interaction between descriptive norms and prototype similarity.


after variables from the TPB and past behaviour had been taken into account.Generally, our findings were consistent with expectations. The TPB successfullypredicted exercise intentions and behaviour and accounted for 41 and 34% of the vari-ance, respectively. These values are similar to the percentages of variance reported inGodin and Kok’s (1996) meta-analytic review of exercise and the TPB. Despite thisfact, descriptive norms and prototype similarity significantly enhanced the predictionof intentions over and above the TPB variables and past behaviour, capturing anadditional 5% of the variance. The augmented model also enhanced the predictionof behaviour. The interaction between prototype similarity and descriptive normsexplained an additional 1% of the variance in behaviour after the other variableshad been taken into account.

Evidence for Controlled and Automatic Processes in Young People’s

Exercise Behaviour

Our finding a direct relationship between prototype similarity and behaviour is particu-larly noteworthy for two reasons. First, it is extremely rare to obtain a significantassociation between a predictor variable and behaviour after intentions, perceivedbehavioural control, and past behaviour have been taken into account. The TPBassumes that intention and perceived behavioural control mediate the effects of ‘‘extra-neous variables’’ (variables not specified by the theory) on behaviour. While intentionswere predictive of behaviour, prototype similarity also directly predicted behaviour,on its own and through its relationship with descriptive norms, even after variablesfrom the TPB and past behaviour had been taken into account. The present findings,therefore, challenge the sufficiency assumption of the TPB (cf. Ajzen, 1985, 1991).However, because this study was correlational in nature, we can only speculate as tothe underlying mechanism for this relationship. One possibility is that young people’ssimilarity to the type of person who engages in regular exercise might automaticallylead to exercise behaviour.Experimental studies have shown that preconscious activation of knowledge struc-

tures such as stereotypes and traits affect behaviours such as social interaction(Bargh et al., 1996), helping behaviour (Macrae and Johnson, 1998) and intellectualperformance (Dijksterhuis et al., 1998) automatically, i.e., without participants beingaware of that influence. For example, Bargh et al. (1996, Study 1) found that partici-pants primed with the concept of ‘‘rudeness’’ were more likely to interrupt an experi-menter during a subsequent encounter, whereas participants primed with the conceptof ‘‘politeness’’ were less likely to interrupt the experimenter, compared to controls.Similarly, Dijksterhuis et al. (1998, Study 1) found that priming stereotypes of professoror supermodels led, respectively, to more and fewer correct answers on a knowledgetest (see also Chen and Bargh, 1997; Dijksterhuis and van Knippenberg, 2000, forsimilar demonstrations). Bargh and colleagues have also highlighted the processesunderlying direct perception–action effects. In particular, it has been noted that repre-sentations of types of people contain knowledge about these people’s goals. Thus,activation of these representations in the course of perception probably also activatethe associated goals among participants (Bargh et al., 2001). Although our resultsseem to support recent evidence suggesting that social comparisons are relativelyspontaneous, effortless, and unintentional (Gilbert et al., 1995), further experimental


research is warranted to determine whether the effects of prototypes are truly ‘‘auto-matic’’ (e.g., outside participants’ awareness) and the outcome of goal activation.

A Role for Social Identification in Motivating Young People’s Health Behaviour

Our findings for prototype similarity are important for another reason, namely,they support the evidence relating to the role of social identification in motivatinghealth-related decisions and behaviour. For example, research indicates that peoplewho strongly identify with a behaviourally relevant reference group are more likelyto act in accordance with the norms of that group compared to people who weaklyidentify with the group (e.g., Terry and Hogg, 1996; Terry et al., 1999; Astrom andRise, 2001). Importantly, however, the current study extends this research in twoways. First, the current findings suggest that peoples’ identification with the prototypi-cal member of the reference group is important in motivating health-related decisions,particularly when those people have a lot of friends who engage in a particular health-related behaviour. Second, the findings show that the influence of social identificationneed not depend upon its relationship with TPB variables or descriptive norms.Previous studies found that social identification played a moderating role in the predic-tion of health-related decisions, e.g., by increasing the strength of the relationshipbetween behavioural norms and intentions. The present study, on the other hand,showed that prototype similarity was a direct predictor of the criterion variables.Thus, the current findings suggest a more important role for social identificationin young people’s health-related decisions than previous research would indicate.

Expanding the Theory of Planned Behaviour to

Include Additional Sources of Social Influence

Our findings relating to descriptive norms are also worthy of mention. The fact thatdescriptive norms made a significant contribution to the variance in intentions, overand above subjective norms and the other TPB constructs, supports the evidencefor a distinction between subjective norms and descriptive norms (cf. Cialdini et al.,1990). Specifically, our findings suggest that young people’s exercise behaviour ismotivated not only through the possibility of gaining approval or disapproval fromsignificant others for one’s intentions, but also by significant others showing him orher what is the typical or normal thing to do. More generally, our findings for bothdescriptive norms and prototypes suggest that the TPB should be expanded to includeprototypes and descriptive norms as additional sources of social influence, at leastwhen trying to predict and explain young people’s health behaviours. Indeed, thefact that prototype similarity and descriptive norms were significant predictors ofintentions even after controlling for past behaviour strengthens this argument.

Theoretical and Practical Implications of the Present Study

Although further research is required to corroborate the findings from the current studyin relation to non-student populations, our findings have both theoretical and practicalimplications. At the practical level, the findings suggest that enhancing people’sperceived similarity to exercise role models, along with their estimations of numberof others who exercise, would help to increase exercise participation among young


people. Visits by famous sports personalities that emphasise similarities with targetaudiences of young people might represent a useful intervention strategy in thisregard. At the theoretical level, research that illuminates the processes by whichprototypes influence young people’s health behaviours is required. An examinationof individual differences should prove particularly fruitful. For example, Gibbonsand colleagues argue that prototypes are influential because of the greater ‘‘social orien-tation’’ of adolescents and young adults (Gibbons and Gerrard, 1997). Thus, people’sability to self-monitor (Snyder, 1974) and the frequency with which they comparethemselves with others (e.g., in terms of social skills and accomplishments) mightusefully be examined as potential moderators of the relationship between prototypeperception and health-related decisions. Finally, the findings for prototype similaritysuggest that young people’s exercise behaviour is driven, in part, by the desire to associ-ate themselves with the exercise prototype. However, an examination of the relativeimpact of the ‘‘type of person who does not exercise’’ versus the ‘‘type of personwho does exercise’’ upon young people’s exercise behaviour should enable moredefinitive conclusions to be reached concerning the type of goal-oriented motivationinfluencing exercise behaviour (cf. Blanton et al., 2001).

Conclusion

In conclusion, the present study has demonstrated the utility of augmenting the TPBwith prototype perception and descriptive norms in order to enhance the predictionof young people’s exercise behaviour. The present study also builds upon previousexperimental research on the ‘‘perception-behaviour expressway’’ and confirms thecorrelational evidence supporting a direct link between aspects of prototype perceptionand behaviour (cf. Rivis and Sheeran, 2003). More generally, the findings indicate howsocial influences might be better conceptualised in the TPB and underline the signifi-cance of social identification in motivating health-related decisions and behaviour.Further experimental and applied research will help both to confirm the generalityof these findings and further delineate the processes by which prototype perceptioninfluences young people’s health behaviours. In the meantime, the present findingssuggest a number of ways in which the prediction of, and participation in, a behaviourassociated with considerable long-term benefits—exercise—may be improved amongthe young adult population.

Acknowledgement

This research was funded by an ESRC award to the first author.

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