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Motivational orientations and imagery use: agoal profiling analysisJennifer Cumming , Craig Hall , Chris Harwood & Kimberley GammagePublished online: 09 Dec 2010.

To cite this article: Jennifer Cumming , Craig Hall , Chris Harwood & Kimberley Gammage (2002) Motivationalorientations and imagery use: a goal profiling analysis, Journal of Sports Sciences, 20:2, 127-136, DOI:10.1080/026404102317200837

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Motivational orientations and imagery use: a goalpro® ling analysis

JENNIFER CUMMING,1* CRAIG HALL,1 CHRIS HARWOOD2 andKIMBERLEY GAMMAGE1

1School of Kinesiology, University of Western Ontario, London, Ontario N6A 3K7, Canada and 2Department of Physical

Education, Sports Science and Recreation Management, Loughborough University, Loughborough LE11 3TU, UK

Accepted 12 September 2001

The aim of this study was to establish whether diþ erent motivational pro® les that result from performing acluster analysis re¯ ect the use of diþ erent functions and amounts of imagery. One hundred and ® ve competitiveswimmers were recruited to participate in the study. They were asked to complete both the Task and EgoOrientation in Sport Questionnaire (TEOSQ) and the Sport Imagery Questionnaire. The results of a K-meanscluster analysis on the TEOSQ scores resulted in a three-cluster solution that maximized between-groupdiþ erences and minimized within-group diþ erences. A multivariate analysis of variance revealed that the threecluster groups could be distinguished by their use of imagery. Speci® cally, the results indicated that individualswith a `complementary balance’ between task and ego orientations were more motivated to perform thefunctions of imagery that would help them to maximize their performance.

Keywords: goal pro® les, goal orientation, mental imagery.

Introduction

Advances in our understanding of achievement moti-vation over the past 15 years have provided sportpsychologists with a much greater appreciation ofwhy individuals behave in certain manners within cer-tain sporting contexts. Adapted from educationalpsychology, Nicholls’ achievement goal theory(Nicholls, 1984, 1989) has been a popular method ofexplaining an individual’ s beliefs, thoughts, feelings,actions and reactions in achievement settings such assport (for detailed reviews, see Duda and Whitehead,1998; Duda and Hall, 2001; Roberts, 2001). Achieve-ment goal theory holds that achievement behaviour isa function of the view that an individual subjectivelyassigns to perceived success or failure. In turn, the viewor meaning that an individual attaches to achievementwill in¯ uence behaviours such as the choice to investin a speci® c activity, the eþ ort expended in the activityand the persistence shown when met by a challenge toperform that activity (Duda and Hall, 2001).

Such variations in achievement behaviour essentially

* Author to whom all correspondence should be addressed. e-mail:jennifercumming@aol.com

stem from the goal states operating within the individualat a certain moment in time. These goal states re¯ ect theview of achievement that is held by the individualfor that speci® c activity or task. Nicholls (1984, 1989)focused on two speci® c achievement goal states, whichhe referred to as `task involvement’ and `ego involve-ment’ . When an athlete is high in task involvement,a sense of achievement is subjectively associatedwith mastery, progress and self-improvement. Successor failure would be determined by applying a self-referencing mechanism to evaluate whether mastery orpersonal improvement had been achieved. Conversely,when high in ego involvement, the athlete construesachievement in norm-referenced terms, placing theemphasis on demonstrating superior ability to others tooccasion feelings of success and satisfaction.

In sport, empirical attention to states of task and egoinvolvement has been limited (see Swain and Harwood,1996; Hall and Kerr, 1997; Harwood and Swain, 1998).Instead, achievement goal theorists have generallyinvestigated the two dispositional goal orientations thatrepresent a trait-like proneness or tendency to becometask or ego involved in a particular achievement setting,such as competitive sport (for reviews, see Duda andWhitehead, 1998; Duda, 2001; Roberts, 2001). In

Journal of Sports Sciences ISSN 0264-0414 print/ISSN 1466-447X online Ó 2002 Taylor & Francis Ltdhttp://www.tandf.co.uk/journals

Journal of Sports Sciences, 2002, 20, 127± 136

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support of Nicholls’ (1984) predictions that a taskorientation, but not an ego orientation, would be associ-ated with adaptive patterns of behaviour, this body ofresearch has found that a high task orientation ispositively associated with high enjoyment (Hom et al.,1993; Kim and Gill, 1997), intrinsic motivation (Dudaet al., 1995; Ntoumanis, 2001) and adaptive moralvalues and behaviours (Duda et al., 1991; Carpenterand Yates, 1997; Dunn and Dunn, 1999). As a result,one consistent message from this literature is that `weshould do whatever is possible to make sure an athlete’ stask orientation is robust’ (Duda, 2001).

The negative relationships emerging in these studiesfor an ego orientation also support the maladaptivepatterns of behaviour that were predicted by Nicholls(1984). For example, research has shown that a highego orientation is associated with feelings of successwhen evidence of high ability is demonstrated, butfeelings of failure and other negative emotions whenone’ s ability is evaluated as being lower than thatof others (Papaioannou and Kouli, 1999). As a result,individuals with a high ego orientation tend to withdrawfrom tasks or reduce their eþ ort when faced with dif-® culty or defeat. Because their goal is to demonstratesuperior ability, circumstances in which they cannot out-perform others or gain favourable judgements regardingability have been linked to feelings of incompetence,less persistence and decreased behavioural intensity(Duda et al., 1995).

Much of this early research (e.g. Duda et al., 1991)tended to report the main eþ ects of each goal orienta-tion separately without fully considering the interactionof task and ego orientation constructs within a trueorthogonal model (Harwood and Treasure, 2000). Astask and ego orientations are orthogonal constructs(Nicholls, 1989), performers are capable of being highin both orientations, low in both or high in one andlow in the other (i.e. high-task/high-ego, low-task/low-ego, high-task/low-ego, low-task/high-ego). Thesecombinations have been referred to as `goal pro® les’and they re¯ ect the relative tendencies of task andego involvement that have been socialized within theindividual.

The results of studies adopting a goal pro® linganalysis have changed the somewhat negative s̀pin’ thathas previously characterized an ego orientation (Foxet al., 1994; Walling and Duda, 1995; Roberts et al.,1996; White, 1998; Hodge and Petlichkoþ , 2000).Corroborating anecdotal evidence from coaches andperformers that a high ego orientation is a necessaryquality in competitive sport, all of these studies supportthe cognitive-behavioural merits of high ego orientationwhen it is combined with a moderate to high taskorientation (i.e. a high-task/high-ego goal pro® le).Furthermore, Hodge and Petlichkoþ (2000) suggest

that adaptive goal pro® les are those that achieve a `com-plementary balance’ between a moderate to high taskorientation and a moderate to high ego orientation. As aresult, this complementary balance would representboth a focus on demonstrating superior skills whencompared to others (ego orientation) and a focus onmaximizing personal mastery (task orientation), eachof which is necessary for success in athletic competition.In other words, athletes are motivated by both the desireto demonstrate normatively superior abilities in athleticcompetition as well as the desire to develop and mastertheir abilities further.

Analytically, the typical procedure used for develop-ing goal pro® le groups has been to perform a meanor median split of the sample data (see Fox et al.,1994; Roberts et al., 1996). It is worth noting, however,that caveats to this technique have recently beendocumented (Harwood and Treasure, 2000; Hodge andPetlichkoþ , 2000). Namely, that such analyses forcethe data into `high’ or l̀ow’ groupings, subsequentlyeliminating the possibility of examining the eþ ects of`average’ responses. Furthermore, misleading ® ndingsmay result because of the arbitrary creation of groups inthe analysis and the task and ego labels (i.e. high, low)assigned to those groups.

A more recent method of creating goal pro® le groupsin goal orientation has been to use cluster analysis(Hodge and Petlichkoþ , 2000; Wang and Biddle, 2001).This procedure is designed to create subgroups from asample of respondents that represent genuine within-cluster homogeneity while maximizing between-clusterdiþ erences (Hair et al., 1995). An advantage of usingcluster analysis is that it will provide the researcher withthe opportunity to examine diþ erent solutions and thenselect the solution that best ® ts the data, based onthe number of participants in each cluster and the sig-ni® cant diþ erences between cluster groups (Hodge andPetlichkoþ , 2000).

Bearing in mind this trend for using cluster analysisto create goal pro® le groups, further examination ofthe relationships between goal pro® les and motivation-related behaviours is merited. The key motivation-related behaviours associated with sport participationinclude the choices made to engage in speci® c tasks, theintensity of eþ ort or mental and physical engagementin achieving the task, and the persistence demonstratedin performing a task in the face of objective failure.Recall that early work in this area favoured task orienta-tion over ego orientation without a close examinationof goal pro® les. These ® ndings corroborated Nicholls’(1989) theoretical predictions in revealing how a hightask orientation was positively related to eþ ortfulbehaviours or `behavioural intensity’ (Duda, 1992).Nevertheless, indicators of behavioural intensity havebeen diý cult to de® ne operationally and, as a result,

128 Cumming et al.

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research on task choice, eþ ort investment and per-sistence has been limited. For example, Duda et al.(1989) conceptualized adherence to athletic injuryrehabilitation as an eþ ortful achievement behaviour;these authors found that high task orientation dis-tinguished those athletes who completed their pre-scribed exercises while pushing themselves and workingat their limits from athletes more prone to simply`walking through’ their exercise protocol.

Despite Duda’ s (1992) call for more work examiningthe interdependence between achievement goals andmotivation-related behaviours, this area of researchhas essentially been limited to the links between goalorientations and the eþ ort invested in physical tasks.Little or no research, however, has conceptualizedbehavioural intensity in terms of the active engagementand personal investment in the use of mental skillsand strategies that are perceived to be associated withsuccessful achievement striving. The premise here isthat the choice to invest in achievement-related mentalskills training represents a motivated behaviour thatremains overlooked and under-investigated from anachievement goal perspective. More speci® cally, thein¯ uence of task and ego goal orientation pro® les on theuse or application of those mental skills and strategiesremains to be investigated.

The related research literature on links betweenindividual diþ erences in goal orientation and achieve-ment-related psychological responses is impressive.Relationships between achievement goals and multi-dimensional anxiety (White and Zellner, 1996; Halland Kerr, 1997; Ntoumanis and Biddle, 1998; White,1998), cognitive interference (Newton and Duda,1993; Hatzigeorgiadis and Biddle, 1999) and coping(Ntoumanis et al., 1999) are well documented. How-ever, a need remains to determine whether certain taskand ego goal orientation pro® les in¯ uence the use orapplication of those mental skills and strategies that cancontrol such psychological responses. Mental imageryis one such psychological skill or strategy that can bemeasured by behavioural intensity. Given that imageryis an activity that requires the athlete to concentratefully to create and control images (Orlick, 1990), anathlete’ s frequency of imagery use could be used to indi-cate varying motivated behaviour, with higher frequen-cies indicating increased investment on the athlete’ spart to perform the behaviour. Furthermore, an investi-gation that would provide a better understanding of thein¯ uence of goal orientations on motivation to performthis strategy is warranted, because using imagery hasbeen found to improve skill learning and performance,modify cognitions and regulate arousal and anxiety (fora review, see Hall, 2001).

Paivio (1985) proposed that imagery serves bothcognitive and motivational functions, each operating

speci® cally or generally. The cognitive functions involvethe rehearsal of speci® c sport skills (cognitive speci® cimagery) and general strategies or routines (cognitivegeneral imagery). The motivational function involvesimaging speci® c goals and the activities necessary forachieving those goals (motivational speci® c imagery),or imagery related to general physiological arousaland aþ ect (motivational general imagery). Hall et al.(1998) found that motivational general imagery couldbe further subdivided into two speci® c components:motivational general-arousal imagery is associatedwith arousal and stress, whereas motivational general-mastery imagery is associated with being in control,mentally tough and self-con® dent.

Achievement goal theory would predict that, forbehavioural intensity, athletes low in task orientationwould invest less time engaging in imagery than athleteswho are high in task orientation and focused onmaximizing their mastery opportunities. The predictionfor ego orientation is a little more complex. Someresearchers might argue that athletes with a high egoorientation would invest less time and eþ ort in mentalskills training such as imagery to reinforce their superiorinnate ability without the need for `extra preparation’ .However, a high ego orientation component primarilyequates with the need to achieve a normative goal and,if imagery functions to facilitate that goal, then it ispossible that an athlete with a high ego orientationwould invest in imagery.

From a goal pro® ling perspective, one would predictthat an athlete with both high task and ego orienta-tion would engage in more frequent use of imagerythat focuses both on the demonstration of superiorskills when compared to others (motivational speci® cimagery) and personal mastery (cognitive speci® cimagery, cognitive general imagery and motivationalgeneral-mastery imagery), each of which is necessary forsuccess in athletic competition. For athletes high in onegoal orientation and low in the other, the use of imagerymight correspond with the particular imagery functionsthat service their goal orientation. More speci® cally,high-task/low-ego oriented athletes might use both cog-nitive speci® c imagery and cognitive general imagery,the functions of imagery that involve them imagingthemselves performing speci® c skills and strategies. Inaddition, given the problem-solving characteristic ofa high task orientation, such athletes might also engagein motivational general-mastery imagery, the functionof imagery that involves them imaging eþ ective copingand mastery of challenging circumstances. In com-parison, athletes with a low-task/high-ego orientationpro® le might use more motivational speci® c imagery,the function of imagery that involves them imagingthemselves winning and beating opponents. Athleteswith this pro® le might also be using more motivational

Goal pro® ling and imagery use 129

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general-arousal imagery, the function of imagery associ-ated with arousal and anxiety, given that research hasshown that a high ego orientation paired with a lowtask orientation is predictive of a stronger dispositionaltendency for athletes to experience cognitive anxietyin competition (White and Zellner, 1996) and to havehigher trait anxiety scores (White, 1998). Moreover,both cognitive anxiety in competition and high traitanxiety scores have been linked with greater use ofmotivational general-arousal imagery (Vadocz et al.,1997; J. Cumming, C. Harwood, C. Hall and S. Hanton,in prep.). However, the relationships between goalorientation, anxiety and the use of motivational general-arousal imagery have yet to be examined.

In summary, little research has examined the relation-ship between individual diþ erences in goal orientationpro® les and the personal investment and engage-ment in mental strategies, such as imagery. The aim ofthe present study was to bring two applied researchareas together and examine such relationships usingan up-to-date analytical method. More speci® cally,we wished to determine whether diþ erent motivationalpro® les that result from performing a cluster analysisre¯ ect the use of diþ erent functions and amounts ofimagery.

Methods

Participants

The volunteer participants were female (n = 64) andmale (n = 41) competitive swimmers. They competedat three diþ erent standards at a provincial swimmingchampionship: `A’ (n = 35), `AA’ (n = 35) or `AAA’(n = 35), with `A’ swimmers having the slowest timesand `AAA’ swimmers having the fastest times. Theswimmers quali® ed to compete at a particular standardby meeting the time for that standard in at least oneevent (e.g. 100 m freestyle), as set by the governingassociation. The mean age of the swimmers was 14.2years (s = 2.46).

Measures

Demographics. The participants supplied relevantdemographic information, including age, sex and com-petitive standard.

Task and Ego Orientation in Sport Questionnaire(TEOSQ). This questionnaire is designed to measurean individual’ s proneness to being task- or ego-orientedin sport (Duda, 1992; Duda and Nicholls, 1992).Both the task and ego subscales have been found to beinternally consistent, with Duda (1992) reporting alpha

coeý cients of 0.81± 0.86 and 0.79± 0.90, respectively,for a summary of studies. The questionnaire consists of13 items, seven of which correspond to a task orienta-tion and six to an ego orientation. Item responses areindicated on a 5-point scale ranging from 1 = `stronglydisagree’ to 5 = s̀trongly agree’ .

Sport Imagery Questionnaire (SIQ). The SIQ (Hall et al.,1998) is a 30-item self-report instrument that asksathletes to rate on a 7-point scale (1 = r̀arely’ and7 = `often’ ) how often they use ® ve functions of imagery:cognitive speci® c, cognitive general, motivation speci® c,motivation general-mastery and motivation general-arousal. Thus, the SIQ consists of ® ve subscales with sixitems representing each subscale. Factor analyses havesupported the ® ve-factor structure of the instrumentand inter-scale correlations have been shown to be lowto moderate (-0.45 to 0.32), indicating that the variousfunctions of imagery use are related but independent(Hall et al., 1998). In addition, Hall et al. (1998) foundthat the SIQ has acceptable internal consistencyestimates for each subscale (alpha coeý cients of 0.70and above).

Procedure

The questionnaires were administered in one of twoways. Some swimmers were contacted directly by one ofthe investigators before a regular practice session orafter a regional swim meet. They were informed of thenature of the study and their participation wasrequested. Those participants who volunteered weregiven a letter of information, a consent form and the twoquestionnaires. Other swimmers received the question-naires from their coaches. In such instances, the investi-gators ® rst instructed the coaches on the properadministration of the questionnaires. Then the coacheshad their swimmers read the letter of information,complete a consent form and answer the two question-naires. They then returned the completed materialto the investigators. In the case of swimmers under theage of 16, informed consent was obtained from theirparents or guardians before administration of thequestionnaires.

Results

Preliminary analysis

Reliability analysis. Internal consistency reliabilitywas adequate for each subscale of the TEOSQ andthe SIQ. The coeý cient alphas (Cronbach, 1951) forthe TEOSQ task and ego subscales were 0.77 and0.81, respectively. Those for the cognitive speci® c,

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cognitive general, motivational speci® c, motivationalgeneral-mastery and motivational general-arousaldimensions were 0.75, 0.73, 0.83, 0.72 and 0.76,respectively.

Descriptive statistics. Means and standard deviationswere calculated for each subscale (i.e. task, ego, cog-nitive general, cognitive speci® c, motivational general-mastery, motivational general-arousal and motivationalspeci® c) and are presented in Table 1 for the entiresample, by age, sex and competitive standard. Ananalysis of variance (ANOVA) revealed signi® cantdiþ erences in the participants’ goal orientation(F1,104 = 83.0, P < 0.001, g2 = 0.44). More speci® cally,the participants reported having a signi® cantly highertask orientation (4.08 ± 0.59; mean ± s) than egoorientation (3.12 ± 0.83). Furthermore, an ANOVArevealed signi® cant diþ erences in the participants’ useof imagery (F4,416 = 12.9, P < 0.001, g2 = 0.11). A Tukeypost-hoc test indicated that the participants used sig-ni® cantly more motivational general-mastery imagery(4.90 ± 1.15) than cognitive speci® c imagery (4.40 ±1.17), motivational general-arousal imagery (4.36 ±1.26), motivational speci® c imagery (4.20 ± 1.47) orcognitive general imagery (4.13 ± 1.18).

Diþ erences in age, sex and competitive standard. Giventhat previous research has indicated that diþ erences ingoal orientation exist between the sexes and betweenindividuals of diþ erent ages (e.g. Newton and Duda,1993; Petlichkoþ , 1993; White and Zellner, 1996), andthat there are diþ erences in the use of imagery betweenathletes of diþ erent standards (e.g. Barr and Hall,1992; Salmon et al., 1994; Vadocz et al., 1997), separatemultivariate analyses of variance were conducted todetermine whether any such diþ erences were present inthis study. Age, sex and competitive standard servedas the independent variables; the subscale scores of theTEOSQ (i.e. task and ego) and the SIQ (i.e. cognitivespeci® c, cognitive general, motivational speci® c, moti-vational general-mastery and motivational general-arousal) were the dependent variables. To assess agediþ erences, the sample was ® rst dichotomized basedon a median-split procedure (median = 14 years). Theoldest age group consisted of 42 swimmers (age = 16.5 ±2.1 years) and the youngest age group consisted of 40swimmers (age 12.0 ± 0.75 years). No age diþ erenceswere found (Pillai’ s Trace = 0.077, F7,74 = 0.879, P >0.05). Furthermore, there were no diþ erences betweenthe sexes (Pillai’ s Trace = 0.132, F7,74 = 1.60, P > 0.05)or between competitive standards (Pillai’ s Trace =0.153, F14,148 = 0.878, P > 0.05). Therefore, the datawere collapsed across age, sex and competitive standardfor further analysis.

Goal pro® les

Like Hodge and Petlichkoþ (2000), we generated goalpro® le groups using cluster analysis. More speci® cally,we used K-means cluster analysis to classify participantsbased on their task and ego orientation scores. A three-cluster solution was considered to be the best ® t,based on the number of participants in each cluster andthe signi® cant diþ erence between cluster groups onboth the task orientation (F2,102 = 52.1, P = 0.00) andego orientation (F2,102 = 104, P = 0.00) subscales. Incomparison, four-, ® ve- and six-cluster solutions lackedparticipants in some of the clusters or failed to show asigni® cant diþ erence among cluster groups. We thentested the stability of a three-cluster solution using atwo-thirds random sample (Hair et al., 1995) to re-cluster the data. Approximately 99% of the participantsretained their original cluster membership, indicating astable cluster pattern. The means, standard deviationsand standardized scores for the three clusters are pre-sented in Table 2.

To establish whether the goal pro® le groups were highor low on the two goal orientations, a criterion z-scoreof ± 0.5 was adopted (Hodge and Petlichkoþ , 2000).The z-scores of each cluster group were then examinedand classi® ed accordingly. The results of this classi® ca-tion indicated that participants in cluster 1 had a low-task/moderate-ego pro® le, participants in cluster 2had a moderate-task/low-ego pro® le and participantsin cluster 3 had a moderate-task/high-ego pro® le. Asnoted by Hodge and Petlichkoþ (2000), however,these labels are created in relation to the z-score andmight not represent the true strength of the goalorientation that might account for signi® cant dif-ferences in achievement behaviour. Therefore, we alsoadopt the same recommendation for the reader toexamine both relative diþ erences (i.e. how standardizedscores compare to one another) and absolute diþ erences(i.e. based on examining unstandardized means andstandard deviations) when examining cluster grouplabels.

Goal pro® le diþ erences in imagery use

To examine group diþ erences in imagery use, we con-ducted a multivariate analysis of variance with the goalpro® le groups serving as the independent variable andthe SIQ subscales as the dependent variables. Theresults indicated a signi® cant multivariate eþ ect (Pillai’ sTrace = 0.245, F10,198 = 2.77, P = 0.003, g2 = 12.3%).Further univariate analyses revealed signi® cant resultsfor the cognitive general (F2,105 = 4.55, P = 0.013,g2 = 8.2%), motivational speci® c (F2,105 = 4.33, P =0.016, g2 = 7.8%), motivational general-arousal(F2,105 = 3.58, P = 0.031, g2 = 6.6%) and motivational

Goal pro® ling and imagery use 131

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Table 2. Scores for goal pro® le groups on the Task and Ego Orientation in SportQuestionnaire

Task Ego

Clusters n mean ± s z mean ± s z

1. Low-task/moderate-ego 28 3.39 ± 0.45 -1.17 3.41 ± 0.48 0.352. Moderate-task/low-ego 44 4.31 ± 0.43 0.39 2.36 ± 0.50 -0.923. Moderate-task/high-ego 33 4.36 ± 0.59 0.47 3.90 ± 0.83 0.94

Table 3. Scores for goal pro® le groups on the Sport Imagery Questionnaire

Low-task/moderate-ego Moderate-task/low-ego Moderate-task/high-ego

Measure mean ± s z mean ± s z mean ± s z

Cognitive speci® c 4.01 ± 0.99 -0.19 4.67 ± 1.24 0.32 4.38 ± 1.15 -0.06Cognitive general 3.60 ± 1.05 -0.44 4.42 ± 1.22 0.34 4.19 ± 1.11 0.08Motivational speci® c 3.91 ± 1.54 -0.06 3.93 ± 1.45 -0.03 4.80 ± 1.29 0.39Motivational general-arousal 3.84 ± 1.32 -0.47 4.48 ± 1.22 0.08 4.65 ± 1.18 0.20Motivational general-mastery 4.28 ± 1.00 -0.42 5.21 ± 1.09 0.28 5.02 ± 1.18 -0.01

general-mastery (F2,105 = 6.47, P = 0.013, g2 = 11.3%)subscales. Tukey post-hoc tests indicated that swimmersin cluster 2 (moderate-task/low-ego) used signi® cantlymore cognitive speci® c imagery, cognitive generalimagery and motivational general-mastery imagerythan swimmers in cluster 1 (low-task/moderate-ego).Furthermore, swimmers in cluster 3 (moderate-task/high-ego) used signi® cantly more motivational speci® cimagery than swimmers in cluster 2 (moderate-task/low-ego) and more motivational speci® c imagery,motivational general-arousal imagery and motivationalgeneral-mastery imagery than swimmers in cluster 1(low-task/moderate-ego). The unstandardized means,standard deviations and z-scores for the three clusterson each of the SIQ subscales are presented in Table 3.

Discussion

In this study, we assessed the relationship between indi-vidual diþ erences in goal orientations and the use ofimagery. More speci® cally, we wished to determinewhether diþ erent motivational pro® les that result fromperforming a cluster analysis re¯ ect the use of diþ erentfunctions and amounts of imagery. By using a clusteranalysis, task and ego orientations were treated asorthogonal and in a manner that avoided the arbitraryattachment of `high’ and `low’ labels (Hodge andPetlichkoþ , 2000). Unlike the mean/median split pro-cedure, which dictates that there will be four goal pro® legroups, the cluster analysis allowed the number of goal

pro® le groups to be determined by the `best ® t’ with thedata.

We found three diþ erent cluster groups emerged fromthe data that maximized between-group variance andminimized within-group variance. Each of these clustergroups represented diþ erent combinations of low tomoderate task orientation and low to high ego orienta-tion as re¯ ected in the resultant z-scores. This analysis,therefore, identi® ed groups with moderate task or egoorientation, allowing us to better tap into the `average’responses of the sample. It must be noted, however,that these `low’ , `moderate’ and `high’ labels representrelative diþ erences (i.e. how standardized scorescompare to one another) in goal orientations thatexist between cluster groups and not the strength ofthe goal orientation that might account for signi® cantdiþ erences in imagery use. To examine the strengthof the goal orientations, absolute diþ erences (i.e. basedon examining unstandardized means and standarddeviations) must be considered (see Table 3). Forexample, the `moderate’ label given to task orientationin cluster 3 re¯ ects a very high task orientation in anabsolute sense (4.36 ± 0.59).

In general, our ® ndings provide support for thepredictions that could be put forward. Recall thatswimmers with both high ego and task orientationwere predicted to engage in more frequent use ofimagery that would focus both on the demonstration ofsuperior skills when compared to others (motivationalspeci® c imagery) and imaging personal mastery (cog-nitive speci® c imagery, cognitive general imagery and

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motivational general-mastery imagery), each of which isnecessary for success in athletic competition. However,the results of the cluster analysis did not produce agroup with that speci® c pro® le. Instead, those with theclosest pro® le were the swimmers in cluster 3, who werecharacterized by moderate task orientation and highego orientation.

We found that these swimmers used more moti-vational speci® c imagery than those swimmers charac-terized by moderate-task/low-ego (cluster 2) or low-task/moderate-ego (cluster 1) orientations. In other words,swimmers in cluster 3 (moderate-task/high-ego)focused more of their mental resources on imagingthemselves being normatively successful in swimmingand would probably bene® t from the more extensiveuse of this function by increasing their motivation toattain their goals. Callow and Hardy (2001) recentlyargued for this bene® t of using motivational speci® cimagery based on their research with skilled netballplayers. Furthermore, this group also used more moti-vational general-mastery imagery than their low-task/moderate-ego (cluster 1) counterparts, indicating thatthey also invested more eþ ort imaging some of thecharacteristics that are necessary for being successful intraining and competition. Bene® ts from the use of thisfunction would include the enhanced ability of modify-ing cognitions such as self-eý cacy (Feltz and Riess-inger, 1990) and self-con® dence (Callow et al., inpress).

The swimmers in cluster 2, who were characterizedby moderate task orientation and low ego orientation,did not devote as much time to imaging themselveswinning (i.e. motivational speci® c), which is consistentwith the prediction that the use of imagery mightcorrespond with the particular imagery functions thatservice their goal perspective. The swimmers in cluster 2used more cognitive speci® c imagery, cognitive generalimagery and motivational general-mastery imagerythan swimmers in cluster 1 (low-task/moderate-ego).Therefore, although the swimmers in cluster 2(moderate-task/low-ego) were not as focused onimaging themselves being normatively successful intraining and competition, they would still probablybene® t from their greater imagery use when comparedwith the swimmers in cluster 1 (low-task/moderate-ego) by being better able to execute skills, plans andstrategies (Hall et al., 1994; Munroe et al., 2000) andto modify cognitions such as self-eý cacy (Feltz andRiessinger, 1990) and self-con® dence (Callow et al., inpress).

Our ® ndings show that the swimmers in cluster 1,characterized by a low task orientation and a moderateego orientation, perhaps represented the least adaptivegroup of swimmers with respect to their imagery use.Unlike our prediction that swimmers higher in ego

orientation and lower in task orientation would usemore motivational speci® c imagery and motivationalgeneral-arousal imagery, the swimmers in cluster 1reported the least use of mental imagery across the threegroups, regardless of the function. As a result, theseswimmers would be less likely to experience the bene® tsthat are associated with imagery than the other clustergroups. One possible explanation for the swimmers incluster 1 (low-task/moderate-ego) engaging in lessmental imagery may be their lower task orientation andthe fact that they were simply less interested in personalimprovement and mastery. Speci® cally, this explanationstems from the theoretical prediction that a low taskorientation suppresses adaptive achievement behaviours(i.e. low behavioural intensity) (Nicholls, 1989; Duda,1992). Furthermore, this lack of investment in imageryuse also appears to supersede the role of ego orientation,since the swimmers in cluster 1 did not engage inmotivational-speci ® c imagery that re¯ ected theirmoderate ego orientation, given the trends emergingfrom the other clusters.

Consistent with the ® ndings of Roberts et al. (1996)and Hodge and Petlichkoþ (2000), therefore, the mostadaptive goal pro® le, or the pro® le that resulted inbehaviours that would appear more likely to maximizeachievement in the present study, demonstrated a`complementary balance’ between moderate taskorientation and high ego orientation (cluster 3). In thepresent study, this `complementary balance’ wasre¯ ected by the swimmers’ tendencies to image them-selves demonstrating superior abilities than otherscombined with imaging the development of theirabilities. One further noteworthy ® nding in the presentstudy is the greater use of motivational general-arousalimagery by swimmers in cluster 3 (moderate-task/high-ego). Although the speci® c relationships between goalorientations, the intensity of anxiety experienced andthe use of motivational general-arousal imagery hasnot previously been examined, some predictions wereoþ ered based on research in the diþ erent areas. Forexample, research showing that a high ego orientationand a low task orientation goal pro® le are associatedwith higher cognitive anxiety in competition and highertrait anxiety (White and Zellner, 1996; White, 1998),led us to predict that swimmers with that same pro® lewould engage in more motivational general-arousalimagery, because higher cognitive anxiety in com-petition and trait anxiety have been associated withgreater use of motivational general-arousal imagery(Vadocz et al., 1997; Cumming et al., in prep.). Con-sistent with our predictions, we found that swimmerswith a moderate-task/high-ego pro® le (cluster 3)engaged in more motivational general-arousal imagerythan swimmers with a low-task/moderate-ego pro® le(cluster 1).

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Conclusions

The link between individual diþ erences in achievementmotivation and behavioural investment in mentalstrategies has been an understudied area of motivatedbehaviour research in achievement goal theory. Thisstudy reinforces the need for further research to investi-gate whether athletes, driven by diþ erential achieve-ment goal orientations, apply themselves to mentalskills training and preparation to diþ ering extents. Themeasurement of imagery use lends itself well to thisparticular area of study in that observations could bemade not only of the frequency of imagery use reportedby swimmers, but also of the functions of imagery used.Nevertheless, similar research is required with largersamples across a variety of sports and considerationneeds to be taken of other cognitive skills and strategiesthat are relevant to performance.

Early achievement goal research often concludedthat a high task orientation was more desirable than ahigh ego orientation because it led to more adaptivepatterns of achievement. Individuals with a high taskorientation were considered the ones most likely to tryharder and develop eþ ective strategies for improvingtheir performance. Such a behavioural pattern seldomemerged for a dominant ego orientation within earlycorrelational research. However, by using goal pro® lingwith an analytical method that appropriately upholdsthe principle of orthogonality, the present ® ndings dolend support to other recent research that having amoderate to high ego orientation is a desirable charac-teristic for athletes. Those individuals with a balanceof moderate to high task and ego orientations aremore motivated to engage in tasks that maximizeachievement.

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