Achievement goal profiles for self-report physical activity participation: differences in personality.

Lochbaum, Marc R. ; Bixby, Walter R. ; Wang, C.K. John 等

Estimated levels of physical inactivity are staggering in the light of the multitude of much publicized physical and mental benefits of regular physical activity (US Department of Health and Human Services, 2000). To better understand physical inactivity, two approaches have received a great deal of research attention. One approach has attempted to identify constructs associated with motivation (e.g., self-efficacy, goal orientations, self-determination). Though this approach is certainly worthy (Sallis, Prochaska, & Taylor, 2000), examination of these constructs in isolation provide little insight into a broader view of additional constructs that influence exercise motivation. The other approach has related personality with exercise behaviors (e.g., Courneya & Hellsten, 1998). This approach has provided useful information, but to date how personality differs across motivation profiles for strenuous and moderate intensity physical exercise has not been investigated. Hence, the purpose of the present investigation was to integrate both approaches by identifying a range of motivated subgroups for strenuous and moderate intensity exercise and by doing so determine whether personalities of these subgroups differed. By identifying subgroups, appropriate interventions may be formulated based on a personality framework.

Motivation Framework

Social-cognitive models have dominated the exercise psychology literature. The achievement goal approach (Duda, 1989; Dweck & Leggett, 1988; Nicholls, 1984a, 1984b, 1989; Roberts, 2001) has been tremendously helpful in understanding affect, cognitions, and behaviors as related to achievement motivation in both sport and exercise settings (see Biddle, 1999; Duda & Whitehead, 1998; Whitehead, Andree, & Lee, 2004). The achievement goal approach is concerned with the individuals' subjective interpretation of success as they correspond to the task and ego orientated achievement goals. Some researchers (Elliot, 1997; Elliot & Church, 1997; Elliot & Harackiewicz, 1996) have suggested that the approach-avoidance goals distinction should be included in addition to the task-ego goals distinction. Approach goals focus on attaining competence, whereas avoidance goals focus on avoiding incompetence. Elliot and his colleagues view perceived competence as the predictor of achievement goals (see Elliot & Church, 1997), and not as a moderator of goal adoption. Recently, Smith, Duda, Allen, and Hall (2002) revealed that differences between performance-approach and performance-avoidance are minimal. Therefore, we adopted Nicholls' (1989) classic achievement goal theory approach whereby the motivational effects of achievement goals are moderated by levels of perceived competence.

Based on this classic achievement goal approach, a task orientated individual's action is primarily motivated by personal mastery or improvement. Success and failure in achieving personal mastery is subjectively defined by self-referenced perceptions of his or her performance. A task orientation has been consistently related to a variety of motivation indicators such as endorsing effort and persistence as achievement strategies (Lochbaum & Roberts, 1993) and higher levels of intrinsic motivation (Duda, Chi, Newton, Walling, & Catley, 1995; Wang & Biddle, 2001; Wang, Chatzisarantis, Spray, & Biddle, 2002). Task oriented individuals, regardless of perceived ability or competence, are hypothesized to be motivationally adaptive.

An ego orientated person strives to win and demonstrate high normative ability. These individuals judge success and failure on other-referenced standards. Research predictions, typically, propose that ego oriented individuals will be motivationally fragile when they doubt their own competence (Nicholls, 1989, Roberts, 1992). This relationship has generally been verified in physical education contexts (Cury, Biddle, Sarrazin, & Famose, 1997; Wang et al., 2002; Wang & Biddle, 2001) though research exists that does not support this relationship (Vlachopoulos & Biddle, 1997).

Given that researchers have established that the two orientations are not mutually exclusive, they have begun 'goal profiling' or examining both goals simultaneously (Fox, Goudas, Biddle, Duda, & Armstrong, 1994). Given the importance of perceived ability to Nicholls' theory, researchers have begun to use both orientations as well as the levels of perceived ability in the process of 'goal profiling' (Wang et al., 2002). For example, Wang and colleagues profiled 818 youths using cluster analysis on the two orientations and perceived competence in order to examine differences in the profiles groups in self-determination, sport ability beliefs, and self-reported physical activity. Three distinct groups emerged from the cluster analysis that corresponded to theoretically consistent differences in the measured variables, thus justifying the use of goal profiling. Several important constructs in addition to self-determination and sport ability beliefs exist that have yet to be examined with 'goal profiling'. Personality is one such construct.

Personality and Exercise

Researchers have examined the relationship between personality and exercise for over 50 years (e.g., Weber, 1953). Investigations have focused on a variety of issues ranging from whether or not exercise participation impacts personality (e.g., Mikel, 1983), how personality relates to exercise motives and barriers (e.g., Courneya & Hellsten, 1998), and how personality influences exercise feeling states (Lochbaum & Lutz, 2005). Pertinent to the present investigation, researchers have investigated whether or not personality is a determinant or correlate of exercise participation. These investigations have used personality as a predictor of adherence to fitness programs (Courneya, Friedenreich, Sela, Quinney, & Rhodes, 2002; Potgieter & Venter, 1995; Rhodes, Courneya, & Jones, 2005; Rhodes, Courneya, & Jones, 2002; Welsh, Labbe, & Delaney, 1991) or the relationship among personality to various measures of exercise behavior (Arai, 1998; Courneya, Bobick, & Schinke, 1999; Rhodes & Courneya, 2003; Rhodes, Courneya, & Bobick, 2001; Rhodes, Courneya, & Jones, 2002; Sale, Guppy, & El-Sayed, 2000; Szabo, 1992; Yeung & Hemsley, 1997).

These investigations have been consistent in that extraversion is a predictor or positively related to exercise behavior in all but one investigation (Yeung & Hemsley, 1997). Also, conscientiousness and openness to experience have been positively related to exercise behavior (Courneya et al., 2002; Courneya & Hellsten, 1998). Less consistent has been the inverse relationship between neuroticism and exercise behavior in nonclinical populations. It is important to note that the correlations among personality and exercise behavior are moderate to weak in nature. Personality (neuroticism) has explained approximately 8% of the variance in exercise adherence, 3% of the variance in strenuous exercise participation (extraversion), and 3% of the variance in moderate exercise participation (openness to experience).

Given the low amounts of explained variance, justification of personality as a topic of study is required. Rhodes and colleagues (2001) suggested that the relationship among individual personality traits is best understood by multivariate examination. Rhodes et al. (2001) examined differences in personality based on stages of exercise change (i.e., from not even considering exercise in their life to those who exercise regularly). The results revealed that neuroticism, extraversion, and conscientiousness varied in their importance across the stages of change for exercise. Neuroticism was found to be a more critical variable with regards to earlier stages of exercise change, whereas extraversion and conscientiousness were found to be more important in the later stages of change. Based on these results, it would appear that a correlation examination of the personality/exercise relationship is not appropriate. Last, Rhodes and Courneya (2003) have suggested that researchers examine the entire Five Factor Model (FFM) to gain a better understanding of the exercise personality. Examining the entire FFM is important because it provides a comprehensive taxonomy of personality (Digman, 1990) and research has provided several examples as previously discussed demonstrating that more than just extraversion and neuroticism impact exercise behaviors and outcomes.

In summary, enhancing exercise participation rates is a public health priority. Increasing participation rates of all persons is a major goal of our nation (US Department of Health and Human Services, 2000). Motivation for exercise is an obvious determinant of physical activity participation. It has been suggested that a simple correlational analysis of the relationships among personality traits and self-reported exercise participation are not appropriate. Therefore, the purpose of the present investigation was to determine whether personality differences exist based on differing motivation profiles for exercise. In addition, self-reported strenuous and moderate intensity exercise participation was reported to verify motivation subgroups. Given that we have no prior knowledge of the characteristics of the participants, no specific hypotheses regards to the cluster profiles were forwarded. Because gender differences have been reported in the goal orientation literature, we hypothesized that men and women would differ on their responses to mean averages on task and ego orientations and, therefore, separate analyses would be required for each gender.

Method

Participants

Participants were 670 volunteer, university students (293 male, 316 female, 61 genders not indicated). All participants were recruited via personal communications from physical fitness courses at a large southwestern university. Participants were primarily college-aged with 33.3% reporting being between 18-19 years, 29.4% between 20-21 years, 18.4% between 22-23 years, and the remaining 18.9% being 24 years of age or older.

Measures

Goal Orientation in Exercise Scale (GOES). The GOES developed by Kilpatrick, Bartholomew, and Riemer (2003) is a 10-item scale that measures task and ego orientation in an exercise motivation context. Each item was rated after reading the following statement stem, "I feel most successful in a health/exercise setting when ... " Example task items include "I learn something while exercising and it makes me want to participate more" and "An exercise skill I learn really feels right." Example ego items include "Others can not do as well as me" and" I am the only one who can exercise at some high intensity." The GOES has adequate psychometric properties (Kilpatrick et al., 2003) and the internal consistencies for the present investigation (Cronbach's a) were .73 and .78 for task and ego orientation, respectively. A score for task and ego is computed with five items being summed. All 10-items were scored on a Likert scale ranging from 1 strongly disagree to 5 strongly agree.

Perceived Physical Ability (PPA). PPA, developed by Ryckman, Robbins, Thornton, and Cantrell (1982), is a 10-item scale that measured participants' perceptions of their physical ability. Each item is rated after reading the following statement stem, "Read each of the statements listed below and indicate how strongly you agree or disagree with each statement." Example statements include "I have excellent reflexes" and "I am not agile and graceful." The PPA has adequate psychometric properties (Ryckman et al., 2003) and the internal consistency for the present investigation (Cronbach's a) was .75. All l0 items were scored on a Likert-type scale ranging from I strongly disagree to 6 strongly agree and were summed for a total score. NEO-Five Factor Inventory. The NEO-FFI is a 60-item measure developed to fit the Five Factor Model of personality (Costa & McCrae, 1992). The NEO-FFI yields scores for neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness, and this measure has demonstrated good psychometric properties across diverse samples. For the present investigation the internal consistencies were .58, .72, .57, .75, and .77 for neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness, respectively. Participants were asked to respond to the series of questions concerning how one behaves, feels, and acts. Example questions are "I am not a worrier" (neuroticism question) and "I don't like to waste my time daydreaming" (openness to experience question). Each of these five personality dimensions is scored by summing 12-items that are scored on a Likert scale ranging from 0 strongly disagree to 4 strongly agree though many of the items are reversed scored.

Leisure Time Exercise Questionnaire (LTEQ). The LTEQ (Godin & Shepard, 1985) was used to assess participants' exercise behavior. Participants were asked "Considering a typical 7-day period (a week), how many times on average do you do the following kinds of exercise for more than 15 minutes during your free time?" Participants indicated their weekly frequencies of exercise in light, moderate, and strenuous exercise. These frequencies were rated on a 9-point scale ranging from 0 never to 88 times or more a week. For the present investigation, the strenuous and moderate intensity exercise questions were analyzed. Godin and Shephard (1985) demonstrated that the items have shown very good test-retest reliability (r = .94) and concurrent validity has been examined using physiological surrogates of exercise participation (r = .38 with V[O.sub.2] max).

Procedures

Permission was granted from instructors of a variety of physical activity courses such as weight training, basketball, volleyball, and jogging to approach potential participants. The primary author and several research assistants recruited participation by coordinating with the activity instructor a class meeting time in which the study could be presented. The study explanation to the potential participants was that the primary author was interested in understanding the whether or not personality was associated with exercise participation based on motivation. Participants were told that no rewards or punishment would occur for refusal to participate. Those who agreed to participate (neither the primary author or research assistants reported any refusals) were presented with the questionnaire packet that was approved by the first author's University Human Subject's Institutional Review Board. The packet contained the GOES, PPA, NEO-FFI, LTEQ, and questions to obtain gender and age.

Data Analyses

Cluster analysis was conducted to identify subgroups of individuals sharing similar responses to our two motivational constructs and perceived ability. More specifically, a two-stage clustering method was used (Hair, Anderson, Tatham, & Black, 1998; Wang et al., 2002). First, a hierarchical clustering method was used to determine the number of clusters and initial cluster centers. Second, using the cluster centers found in the first stage, a k-means clustering method was used to refine the clusters (Punj & Stewart, 1983). The cluster analyses were conducted using the following three variables: task orientation, ego orientation, and perceived physical ability. As the scales of the questionnaires were different, it was necessary to standardize all the scores to a mean of 0 and a standard deviation of 1 using Z-scores (see Spray & Wang, 2001). Four outliers were removed using the criteria of [+ or -] 3 standard deviations on the Zscores. To examine potential cluster differences in terms of their personality traits, two Multivariate Analysis of Variance (MANOVAs) were conducted with the cluster as independent variable and the five personality factors as dependent variables. We use Pillai's Trace as the tests of significance within MANOVAs as there may be unequal number or small sample size in each cluster. Pillai's trace provides maximum protection against finding a statistical significance when there is none (Hair et al., 1998). Prior to conducting the cluster analysis, a MANOVA was conducted with univariate follow-up to determine specific gender differences existed on the measured variables with specific attention being paid to the GOES and PPA. Last, effect size (ES) estimates (Hedges, 1981) were calculated to determine the meaningfulness of differences between clusters. Cohen's (1988) interpretation guidelines were followed for the social sciences that an effect of .2 is small, .5 is medium, and .8 is large. Given the number of comparisons, specific effect sizes are mentioned where appropriate in the discussion section.

Results

Descriptive Statistics and Gender Differences

Table l contains the means and standard deviations for all measured variables for the entire sample as well as for both genders. The MANOVA with univariate follow-ups for gender revealed that significant differences emerged on seven out of the l0 variables. Concerning the goal profiling variables and consistent with past research, men scored significantly higher on ego orientation and perceptions of physical ability. Men also reported greater strenuous physical activity participation over the course of a typical 7-day period. Men and women also differed on all but one (i.e., openness to experience) of the NEO-FFI variables. It is important to note that the meaning of the raw scores for these variables differs by gender (i.e., percentile classification). With this in mind, both genders were similar in percentile classification interpretation based on published standards (Costa & McCrae, 1992); hence, the most important and significant gender differences occurred with the motivational and self-reported exercise variables.

Cluster Analysis

In view of the significant differences between the two genders, cluster analyses were conducted separately for men and women. For the male sample, a four-cluster solution was found to be suitable from the agglomeration coefficients and dendrogram. The dendrogram is a graphical representation of the clusters scaled on a 0 to 25 scale and agglomeration coefficient is defined as the average height of the mergers in a dendrogram (Hair et al., 1998). On the other hand, the female sample could be categorized into three homogenous clusters. Using the cluster means identified from the hierarchical clustering method as the initial centres for k-means cluster analysis, the final clusters centres for the men and women are presented in Table 2.

Using Z scores [+ or -] 0.5 as criteria for classifying high (>.5) or low scores (<.5), cluster 1 of the male sample (n = 73) had a "high task/low ego/high competence" goal profile. The second male cluster had a "moderate/high/moderate" goal profile (n = 90). The third cluster consisted of participants (n = 65) with a "low/low/low" profile and the last cluster had men (n = 65) with a distinctly "high/high/high" goal profile. In terms of their female counterpart, the first cluster had a "high/high/moderate" goal profile with more than 50% of the women (n = 163). The second cluster had a "high/low/low" profile (n = 89). The last cluster was a "low/low/low" profile of women (n = 64) similar to the third cluster of the male sample.

Separate Gender Analyses for Personality and Physical Activity

To examine the cluster differences in terms of their personality traits and physical activity, separate Multivariate Analysis of Variance (MANOVAs) were conducted for the two genders for both sets of variables (personality and physical activity). The MANOVA results for both genders showed significant differences between the clusters on the dependent measures, Pillai's Trace = .24, F (15, 861) = 5.08,p <.001, [h.sup.2] = .08 for men, and Pillai's Trace = .268, F (10, 620) = 9.28, p < .001, [h.sup.2] =. 13, for women. Tables 3 and 4 contain the means, standard deviations and z scores of the dependent variables for the clusters among the male and female participants, respectively. ANOVAs on each dependent variable were conducted as follow-up tests to the MANOVAs. For the male sample, significant differences were found on four out of the five dependent variables (i.e., neuroticism, extraversion, agreeableness, and conscientiousness; see Table 3). For the female sample, significant differences were found on three out of the five dependent variables (i.e., extraversion, agreeableness, and conscientiousness; see Table 4). Post-hoc Tukey's Honestly Significant Difference (HSD) tests were conducted to examine the pairwise comparison between the clusters for each gender (see tables 3 and 4).

Two separate MANOVAs were conducted for each gender with two self-reported physical activity levels (strenuous and moderate) as dependent variables. The multivariate effects were significant, Pillai's Trace =. 12, F (6, 578) = 6.12,p < .001, [h.sup.2] = .06 for men, and Pillai's Trace = .084, F (4,626) = 6.88,p < .001, [h.sup.2] = .04, for women. The results of the follow-up tests are presented in Tables 3 and 4.

Profiles of Cluster Groups

In terms of the personality profiles, Cluster 1 of the male participants ("high/low/high') had the highest scores in agreeableness (ES difference range .39 to .78) and conscientiousness (ES's = .60 and .69, respectively for Cluster 2 and Cluster 3). They also participated in moderate to high levels of both strenuous (ES's = .43 and .74, respectively compared to Cluster 2 and Cluster 3) and moderate (ES = .73 for Cluster 3) exercise. Contrastingly, Cluster 2, with a "moderate/high/moderate" goal profile scored lowest in agreeableness (ES = -.78) and conscientiousness (ES = -.69), compared to the first cluster. This cluster reported average participation in strenuous and moderate physical activity. Cluster 3 consisted of a "low/low/low" goal profile. The men in this cluster had highest score in neuroticism (ES's = -.54 and -.55, respectively compared to Cluster 2 and 3), and lowest scores in extraversion, openness, agreeableness, and conscientiousness. Finally, the "high/high/high" goal profile (Cluster 4) scored lowest in neuroticism, but highest in extraversion (ES difference range .67 to .92 compared to the other clusters), as well as physical activity participation (ES difference range .33 to 1.03).

For the female sample, Cluster 1 ("high/high/moderate" goal profile) had the highest score in extraversion (ES's = .56 and .82, respectively compared to Cluster 2 and 1). This profile is similar to the Cluster 1 of the male sample. In terms of physical activity participation, this group of women reported highest level of strenuous exercise (ES's = .52 and .49, respectively compared to Cluster 1 and 2). The second female cluster, with a "high/low/low" profile, had the highest score in agreeableness (ES's.= .54 and 1.04, respectively compared to Cluster 1 and 2) and conscientiousness (ES's = .86 and .84, respectively compared to Cluster 1 and 2). They participated in low level of strenuous exercise but higher in moderate intensity exercise (ES's = .03 and .36, respectively compared to Cluster 1 and 2). The last female cluster with a "low/low/ low" profile had significantly lower scores in extraversion, agreeableness, and conscientiousness that were verified with the already mentioned ES's. They also had the lowest levels of physical activity participation in both intensities.

Discussion

The purpose of the present investigation was to ascertain whether personality differed based on differing motivation profiles for physical exercise. Personality has been linked to exercise behavior though it has been suggested that this relationship has been investigated incorrectly and has been mainly limited to extraversion and neuroticism. Therefore, we specifically profiled participants based on their self-reported degrees of task and ego orientations to physical exercise as well as their perceptions of physical ability as opposed to simply correlating personality traits with self-reported exercise behavior. Past research has suggested that it is too simplistic to label individuals as high or low in motivation (e.g., Ntoumanis, 2001; Wang & Biddle, 2001); hence, cluster analysis was conducted to determine the most appropriate motivational grouping for the present sample. Given significant differences between genders in goal orientations and perceptions of ability, separate cluster analyses were conducted. The results of our cluster analyses clearly supported this notion in that the clusters produced more than two groupings.

For the male participants, four clusters emerged. Cluster 1 had a "high task/low ego/high competence" profile, Cluster 2 had a moderate "task/high ego/moderate competence" profile, cluster 3 had a low task/low ego/low competence profile, and cluster 4 had a "high task/high ego/high competence" profile. These participants were nearly equally distributed across the four clusters (24.9%, 30.7%, 22.1% and 22.1%, respectively for Cluster I to 4). The differences in motivational profiles of the most motivated groups and lowest motivated group were confirmed with significant differences in self-reported strenuous and moderate intensity physical activity. Cluster 3 clearly self-reported the least amount of strenuous and moderate intensity physical activity compared to Clusters 1 and 4. Cluster 2 differed from Cluster 3 with regards to self-reported strenuous physical activity participation.

Pertinent to our purpose, differences in personality profiles were examined across the four clusters. It is first important to note that openness to experience did not differ amongst the four clusters. Lochbaum, Karoly, and Landers (2002) reported significant differences in this personality trait between participants who were very active and those who reported no physical activity participation six months prior to their participation in the investigation. In the present sample of participants based on the motivational profiles, no one group exists that reported no physical activity participation in typical 7-day period. Hence, it appears in participants who report on average at least three days of physical activity (see Cluster 3, Table 3) openness to experience is similar to that of more active individuals. Given the main public health interest is to enhance physical activity participation, examining the lowest motivated group's personality profile compared to the more motivated groups (Clusters 1 and 4) will best lend insight into structuring physical activity interventions.

The lowest motivated group reported lower levels of extraversion, conscientiousness, and greater neuroticism than the two most motivated groups (Clusters 1 and 2). Interestingly, this lowest motivated group was similar to Cluster 2's personality profile. Cluster 2 had moderate levels of task orientation as well as perception of physical competence and a high ego orientation. These two Clusters (2 and 3) reported significantly similar levels of moderate physical activity though and, importantly, Cluster 2 reported greater levels of strenuous exercise participation over a typical 7-day period.

For the female participants, three clusters emerged. Cluster I had a "high task/high ego/ moderate competence" profile, Cluster 2 had a "high task/low ego/low competence profile, and cluster 3 had a low task/low ego/low competence" profile. Unlike the results for the men, the women were distributed unequally across the three clusters (51.5%, 28.1%, and 20.2%, respectively for the Clusters I to 3). But similar to the men and fortunate for the health of the present female sample, over half of the participants were very motivated for physical activity (Cluster 1) and this was verified by their self-reported significantly more strenuous intensity exercise engagement compared to the other two clusters and significantly more moderate intensity exercise than the participants in Cluster 3 (lowest motivation).

Concerning personality, the differences between the lowest motivated group and the more motivated groups were much clearer compared to the male results. First, openness to experience as well as neuroticism did not differ amongst the three groups. The lowest motivated group (see Cluster 3, Figure 2) scores for extraversion, agreeableness, and conscientiousness were the lowest when compared to the other two clusters (see Figure 2). Clusters 1 and 2 differed only in agreeableness whereby Cluster 2 participants reported a higher score compared to participants in Cluster 1 and Cluster 3 participants.

As a whole, several observations are clear and merit attention. Lower motivated groups of male and female participants score lower compared to more motivated groups for physical activity on extraversion and conscientiousness. These findings support past research investigating exercise behavior and the FFM (Courneya et al., 2002; Courneya & Hellsten, 1998). But, again, past research using correlational methods has been criticized (Rhodes et al., 2001). The correlations in the present investigation are similar to past research in that several significant correlations between personality and exercise behavior exist, but the correlations are weak in nature and explain no more than 3.2% of the variance in either strenuous or moderate intensity exercise. Also supportive of the inconsistent nature of neuroticism and exercise behavior, the lowest motivated groups of men reported the highest levels of neuroticism. This finding was not supported in the female sample. The lowest motivated female cluster reported the lowest level of agreeableness.

Based on the results, one clear line of research with the goal of moderate and strenuous exercise participation enhancement is evident. The present research demonstrates that goals, perceived competence, and personality should be measured prior to conducting an exercise program in order to identify groups that may be susceptible to lower motivations for strenuous and moderate intensity physical activity. By measuring these variables several different interventions to enhance exercise participation could be identified. For instance, one intervention could focus on eliminating perceived barriers based on personality (i.e., those participants scoring low in extraversion and conscientiousness). Low extraverted individuals would be hypothesized to perceive large group or social settings as a barrier. Thus, these individuals could be given an individualized exercise program. In addition, given that these individuals will most likely be low in conscientiousness, these participants could be assigned an exercise leader to assist given that they are less determined in nature.

Last, though the present research is very unique and provides direction for future research, limitations existed. One limitation was the design. The cross-sectional design does not allow for causation to be determined. Another limitation is that the participants self-reported their exercise behaviors. Though it is unknown whether or not the participant over or underestimated their behaviors, future prospective research would be well served to measure exercise attendance and changes in fitness over time (e.g., maximal oxygen consumption) as well as self-reported exercise behavior. Another potential limitation was the assessment of goal orientation. We specifically asked the participants questions reference to exercise as opposed to sport or physical activity. It is possible that some participants may have been more motivated for sport participation (e.g., playing recreational basketball) than exercise per se (e.g., lifting weighs). Future research should allow participants to identify their main motivation, exercise or sport, and then answer an appropriate goal orientation scale. The last limitation was that the sample was comprised mainly of undergraduate students. The present study conducted in a non college-aged sample would be beneficial in order to identify the personality profiles of adults who engage in no moderate or strenuous physical activity. In the present sample, all groups on average reported participating in both intensities in a typical 7-day period. Despite the mentioned limitations, the present study has extended personality research in the domain of exercise participation. The FFM within the framework of goal profiling appears to be a useful framework for future research aimed at enhancing a major public health concern.

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Marc R. Lochbaum

Texas Tech University

Walter R. Bixby

Elon University

C.K. John Wang

National Institute of Education, National Technological University

Address Correspondence To: Marc Lochbaum, Ph.D., Department of HESS, Box 43011 Texas Tech University, Lubbock, TX 79409-3011, Phone: (806) 742-3371, Fax: (806) 742-1688, Email: Marc.Lochbaum@ttu.edu

Table 1. Descriptive statistics for the entire sample
(N = 609) and male (n= 296) and female (n = 316)

 Overall Male

 Mean SD Mean SD
GOES
 Task 17.77 3.30 17.74 3.10
 Ego 14.37 4.01 15.07 3.98
Perceived
Physical Ability 38.47 6.99 40.30 7.16
NEO-FFI
 Neuroticism 22.89 5.76 22.07 5.78
 Extraversion 30.43 5.87 29.66 5.72
 Openness 23.91 5.52 23.64 5.74
 Agreeableness 28.16 6.51 26.88 6.09
 Conscien-
 tiousness 30.55 6.26 29.85 6.14
Self-Reported Exercise
 Strenuous 2.64 1.91 2.85 1.92
 Moderate 3.21 1.99 3.25 2.02

 Gender
 Female Differences

 Mean SD p ES
GOES
 Task 17.80 3.48 n.s. -.02
 Ego 13.71 3.93 <.001 .34
Perceived
Physical Ability 36.76 6.39 <.001 .51
NEO-FFI
 Neuroticism 23.66 5.65 <.001 -.27
 Extraversion 31.15 5.93 <.01 -.25
 Openness 24.16 5.30 n.s. -.09
 Agreeableness 29.35 6.68 <.001 -.38
 Conscien-
 tiousness 31.19 6.30 <.01 -.21
Self-Reported Exercise
 Strenuous 2.46 1.89 <.05 .20
 Moderate 3.17 1.96 n.s. .04

Table 2 Goal profile clusters far nun aril women

 Cluster 1 Cluster 2

Men n 73 90
Women n 163 89

 Mean SD Z Mean SD Z
Man only
 Task 19.31 2.22 .46 17.52 2.15 -.08
 Ego 11.80 2.85 -.64 17.18 2.37 .70
 Perceived Competence 42.41 4.38 .56 36.29 3.31 -.31
Women only
 Task 19.21 2.48 .43 18.86 2.26 .45
 Ego 16.36 2.76 .50 9.81 2.12 -1.14
 Perceived Competence 38.96 5.95 .07 35.29 6.44 -.45

 Cluster 3 Cluster 4

Men n 65 65
Women n 64

 Mean SD Z Mean SD Z

Man only
 Task 14.21 2.33 -1.08 19.54 2.53 .53
 Ego 11.92 2.07 -.61 18.66 2.72 1.07
 Perceived Competence 34.21 4.21 -.61 48.69 5.18 1.46
Women only
 Task 12.95 2.28 -1.46
 Ego 12.27 3.00 -.52
 Perceived Competence 33.12 5.12 -.76

Table 3. Means. Standard Deviations, and Z Scores of the
Dependent Variables by Cluster for the Male Participants

 Cluster 1

Variable Mean SD Z

Personality Traits
 Neuroticism 21.34 (a)(b)(c) 5.69 -.27
 Extraversion 31.38 (a) 4.92 .16
 Openness to 23.96 (a) 6.61 .01
 Experience
 Agreeableness 29.34 (a) 6.15 .18
 Conscientiousness 31.85 (a) 6.48 .21

Physical Activity Levels
 Strenuous Exercise 3.12 (a) 1.71 .25
 Moderate Exercise 3.37 (a) 2.18 .08

 Cluster 2

Variable Mean SD Z

Personality Traits
 Neuroticism 23.26 (a)(c) 5.28 .06
 Extraversion 28.30 (b) 5.03 -.36
 Openness to 23.45 (a) 5.45 -.08
 Experience
 Agreeableness 24.84 (b) 5.49 -.51
 Conscientiousness 27.98 (b) 4.75 -.41

Physical Activity Levels
 Strenuous Exercise 2.62 (a)(b) 1.84 -.01
 Moderate Exercise 3.14 (a)(b) 1.81 -.03

 Cluster 3

Variable Mean SD Z

Personality Traits
 Neuroticism 23.37 (a)(c) 5.46 .08
 Extraversion 26.88 (b) 4.95 -.60
 Openness to 22.73 (a) 5.24 -.21
 Experience
 Agreeableness 26.91 (a)(b) 6.24 -.19
 Conscientiousness 28.14 (b) 5.83 -.38

Physical Activity Levels
 Strenuous Exercise 1.85 (c) 1.71 -.42
 Moderate Exercise 2.61 (b) 1.92 -.30

 Cluster 4

Variable Mean SD Z

Personality Traits
 Neuroticism 20.16 (a)(b) 6.29 -.47
 Extraversion 32.01 (a) 6.11 .27
 Openness to 24.61 (a) 5.55 .12
 Experience
 Agreeableness 26.94 (a)(b) 5.67 -.19
 Conscientiousness 31.68 (a)(b) 6.59 .18

Physical Activity Levels
 Strenuous Exercise 3.71 (a) 1.89 .55
 Moderate Exercise 3.71 (a) 1.97 .25

Variable F p [[eta].sup.2]

Personality Traits
 Neuroticism 5.31 <.01 .05
 Extraversion 15.01 <.01 .13
 Openness to 1.27 ns .01
 Experience
 Agreeableness 7.89 <.01 .08
 Conscientiousness 9.75 <.01 .09

Physical Activity Levels
 Strenuous Exercise 12.79 <.01 .12
 Moderate Exercise 3.56 <.05 .04

Note. Means in the same row that do not share superscripts
differ at p <.01 using Tukey's HSD

Table 4. Means, Standard Deviations, and Z Scores of the Dependent
Variables by Cluster for the Female Participants

 Cluster 1 Cluster 2

Variable Mean SD Z Mean SD Z

Personality Traits
 Neuroticism 23.11 (a) 5.83 .04 24.17 (a) 6.21 .22
 Extraversion 32.50 (a) 5.85 .35 31.08 (a) 6.06 .11
 Openness to 23.90 (a) 5.05 .00 24.41 (a) 6.25 .09
 Experience
 Agreeableness 29.00 (a) 6.46 .13 32.46 (b) 6.17 .25
 Conscientiousness 32.28 (a) 6.04 .28 32.14 (a) 6.13 .25
Physical Activity Level
 Strenuous Exercise 2.92 (a) 1.96 .14 1.95 (b) 1.64 -.36
 Moderate Exercise 3.29 (a) 1.94 .04 3.35 (a) 2.06 .07

 Cluster 3

Variable Mean SD Z F p

Personality Traits
 Neuroticism 24.41 (a) 4.14 .26 1.72 >.05
 Extraversion 27.97 (b) 4.65 -.42 14.58 <.01
 Openness to 24.43 (a) 4.51 .09 .37 >.05
 Experience
 Agreeableness 26.03 (c) 6.20 -.33 19.83 <.01
 Conscientiousness 27.17 (b) 5.68 -.54 18.17 <.01
Physical Activity Level
 Strenuous Exercise 1.98 (b) 1.80 -.35 10.56 <.01
 Moderate Exercise 2.64 (b) 1.82 -.29 3.02 <.05

Variable [[eta].sup.2]

Personality Traits
 Neuroticism .01
 Extraversion .08
 Openness to .00
 Experience
 Agreeableness .11
 Conscientiousness .10
Physical Activity Level
 Strenuous Exercise .06
 Moderate Exercise .02

Note. Means in the same row that do not share superscripts
differ at p <.01 using Tukey's HSD