首页    期刊浏览 2025年02月28日 星期五
登录注册

文章基本信息

  • 标题:Achievement goals, thoughts about intense physical activity, and exerted effort: a mediational analysis.
  • 作者:Lochbaum, Marc ; Stevenson, Sarah ; Hilario, Daniel
  • 期刊名称:Journal of Sport Behavior
  • 印刷版ISSN:0162-7341
  • 出版年度:2009
  • 期号:March
  • 语种:English
  • 出版社:University of South Alabama
  • 关键词:Exercise;Goals (Psychology)

Achievement goals, thoughts about intense physical activity, and exerted effort: a mediational analysis.


Lochbaum, Marc ; Stevenson, Sarah ; Hilario, Daniel 等


Achievement behavior is defined as exerted effort or behavioral intensity, persistence of such effort, choice of actions (e.g., choosing task difficulty level), and performance-based outcomes (Ames, 1992; Dweck, 1986; Nicholls, 1984a; Roberts, 1992). Motivational theories attempt to explain achievement behaviors to infer a person's level of motivation (Maehr & Braskamp, 1986; Roberts, 1992). Effort exerted in response to perceived failure is an important factor that influences sport and physical activity achievement settings. Recent research has demonstrated that individuals differ in their levels of preference and tolerance for physical activity intensity (Ekkekakis, Hall, & Petruzzello, 2005). For example, though these preference and tolerance constructs are seemingly important, they are not theoretically derived. Achievement goals from social-cognitive models are examples of theoretically-derived variables that improve understanding of a person's preference and tolerance for exercise intensity.

Motivation Framework

The achievement goal framework (Duda, 1989; Dweck & Leggett, 1988; Nicholls, 1984a, 1984b, 1989; Roberts, 2001) has been helpful in understanding affect, cognitions, and behaviors as related to achievement motivation in both sport and exercise settings (Biddle, 1999; Duda & Whitehead, 1998; Whitehead, Andree, & Lee, 2004). Researchers (e.g., Elliot, 1997; Elliot & Church, 1997; Elliot & Harackiewicz, 1996) have suggested that the approach-avoidance goals distinction should be added to the achievement goal task-ego goals distinction. Although Smith, Duda, Allen, and Hall (2002) contend that differences between performance-approach and performance-avoidance are minimal, a substantial body of literature has demonstrated the importance of including the approach-avoidance distinction in understanding achievement behaviors (e.g., Conroy, Kaye, & Coatsworth, 2006; Cury, Elliot, Da Fonseca, & Moller, 2006; Elliot, Cury, Fryer, & Huguet, 2006; Moller & Elliot, 2006; Van Yperen, 2006; Wang, Biddle, & Elliot, 2007).

Elliot and his colleagues have suggested a two-factor achievement goal framework that includes the following goal orientations: mastery-approach, mastery-avoidance, performance-approach, and performance-avoidance (Elliot, 1997; 1999; Elliot & McGregor, 2001; Elliot & Thrash, 2002). The two goal orientations reflect how competence is valence and defined (Elliot & McGregor, 2001; Elliot & Thrash, 2001). The definition of competence is based on standards (i.e., absolute, intrapersonal, and normative) of reference. Competence, if based on the mastery-approach goal, is defined by task-based attainment, whereas competence, if based on the mastery-avoidance goal, consists of avoiding task-based attainment. The performance-approach goal defines competence based on normative achievements, whereas the performance-avoidance goal defines competence based on avoiding displays of normative incompetence (Elliot, 1999). Valence refers to approach-avoidance differences of goal orientations. Approach valence indicates behavior that is initiated by a positive or desirable event or possibility, whereas, avoidance valence consists of behavior that is initiated by a negative or undesirable event or possibility (Elliot, 1999).

One theoretical framework for understanding indicants of motivation (i.e., persistence, task choice and exerted effort) is Elliot's (1999) hierarchical model. His model offers a framework to better understand the importance of preference and tolerance as personal factors, or antecedent variables to achievement goals. Elliot proposed that achievement goals serve as process variables by which personal as well as environmental factors impact achievement goal adoption. He contends that need for achievement, fear of rejection, neurophysiological predispositions, as well as personality and self-esteem variables, are antecedent variables to achievement goals. Several of these antecedent variables have received empirical support (Conroy & Elliot, 2004; Conroy, Elliot, & Hofer, 2003; Heimpel, Elliot, & Wood, 2006). For instance, Conroy and his colleagues have demonstrated that fear of failure and achievement motivation are antecedents to achievement goals. Heimpel et al. (2006) has demonstrated that personality traits as well as self-esteem are antecedents to achievement goals. Interestingly, preference and tolerance for exercise intensity is similar to the neurophysiologic predispositions as discussed by Elliot. Tolerance for pain and discomfort, both associated with intense exercise or physical effort, are components of preference and tolerance for intense exercise. Ekkekakis et al. (2005) developed a scale to assess an individual's preference and tolerance for physical activity intensity as individual difference variables influencing exercise adherence and enjoyment of physical activity.

The purpose of this study, then, was to examine the extent to which a person's preference and tolerance for physical activity intensity as well as their strenuous (intense) exercise history are antecedent variables of achievement goals in explaining exerted effort as defined by performance on the shuttle run task. Therefore, achievement goals are process variables that reflect individual differences on effortful physical exertion. In the present study, the shuttle run that ranges in effort from very low to very high was completed in groups, which created normative comparisons. Thus, it was hypothesized that only the performance-approach goal would serve as a mediator of individual difference variables on shuttle run performance, whereas the performance-avoidance goal would suppress the influence of individual difference variables on performance. These hypotheses are consistent with past literature (Cury et al., 2006; Elliot & McGregor, 2001; Zusho, Pintrich, & Cortina, 2005). Last, it was hypothesized that sex differences would be present in the shuttle run performance data and strenuous physical activity variable given for decades men report participating more in strenuous physical activity compared to women. Given sex differences were hypothesized these variables, sex differences were examined in all variables.

Method

Participants

Participants were 286 volunteer, college-aged university students, 155 men and 131 women, who were recruited by personal communication from illness and wellness courses at a university in the southwestern U.S. Participants were categorized as moderately active based on their self-reported degree of strenuous (M = 2.92, SD = 1.91 ), moderate (M = 3.07, SD = 1.80), and mild exercise intensity (M = 3.33, SD = 2.59) per week.

Measures

Achievement Goal Questionnaire (AGQ). Achievement goals were assessed by adapting Elliot and McGregor's (2001) AGQ, a 12-item instrument that assesses the four achievement goals with respect to strenuous physical activity. Sample items include "It is important to me to exercise strenuously as well as I possibly can" (mastery-approach); "It is important for me to exercise strenuously well when compared to others" (performance-approach); "I worry that I may not exercise strenuously as well as I possibly can" (mastery-avoidance); and "I just want to avoid exercising strenuously worse than others" (performance-avoidance). The questionnaire required individuals to specify the extent to which each item was true on a scale from 1 (not at all) to 7 (completely) after reading the following statement: "Please think about your thoughts and feelings when engaging or thinking about engaging in strenuous exercise. Please read each question and respond as to how like the statement is about you." Three items assessed each of the achievement goals.

Elliot and McGregor (2001) have reported strong psychometric properties for their AGQ. The authors conducted an exploratory factor analysis (EFA) on their original version of the AGQ and reported four distinct factors corresponding to the four achievement goals. For the present study, a CFA was conducted on the achievement goal items to examine the psychometric properties of Elliot and McGregor's (2001) version of the AGQ. Changes in the questionnaire did not adversely affect the psychometric properties. This analysis was conducted on the covariance matrix. Using maximum likelihood estimation, the solution was generated. The four factor model again provided an acceptable fit for the data, [chi square] (48, N = 286) = 132.68, p < .001; CFI = .95; RMSEA = .07; all items displayed acceptable factor loadings ranging from .43 to .89. The internal consistencies (Cronbach's [alpha]) were .89, .87, .90, and .82 for mastery-approach, mastery-avoidance, performance-approach, and performance-avoidance, respectively.

Leisure Time Exercise Questionnaire (LTEQ). The LTEQ was used to assess participants' exercise behavior (Godin & Shepard, 1985). Participants were asked, "Considering a typical 7-day period (a week), how many times on average do you perform the following kinds of exercise for more than 20 minutes continuously or discontinuously during your free time?" Participants indicated their weekly frequencies of exercise for mild (e.g., yoga, easy walking), moderate (e.g., fast walking, volleyball), and strenuous intensity level (e.g., running, soccer). For the present investigation, the self-reported strenuous intensity participation was especially important because it is logical to speculate that participants who choose to engage in strenuous physical activity might be more adept at completing the shuttle run task as opposed to participants who participated in only moderate to mild exercise. Godin and Shephard (1985) demonstrated that the items have shown very good test-retest reliability (r = .94). In addition, concurrent validity has been examined using physiological surrogates of exercise participation with VO2 max (r = .38, p <.001).

Preference for and Tolerance of the Intensity of Exercise Questionnaire (PRETIE-Q). The 16-item PRETIE-Q (Ekkekakis, Hall, & Petruzzello, 2005) assesses self-reported in the preference for and tolerance of exercise intensity. Each statement is rated on the extent to which the participant agrees or disagrees with the statements such as "Feeling tired during exercise is my signal to slow down or stop," or "I would rather work out at low intensity levels for a long duration than at high-intensity levels for a short duration" to measure tolerance and preference, respectively. All items are scored on a Likert scale ranging from 1 (I totally disagree) to 5 (I totally agree). Ekkekakis et al. (2005) demonstrated acceptable psychometric properties with internal consistencies (Cronbach's [alpha]) ranging from .81 to .85 for preference, and from .82 to .87 for tolerance. In the present investigation, internal consistencies were .73 and .81 for preference and tolerance, respectively.

20-meter shuttle run. The 20-meter shuttle run, developed by Leger and Lambert (1982; 1988), is a field test used to predict VO2max and was used in this study to measure exerted effort. Participants were required to run 20 m then turn around and return. Each trial required that participants touch the 20 m line with either foot upon hearing a beeping signal. The signal was emitted from a recording on a compact disc and is its purpose it to dictate the time allotted for covering the run distance. As designed by Leger and Lambert (1982; 1988), the frequency of the signals was increased such that the run speed is increased by 0.5 km [h.sup.-1] each minute from a starting speed of 8.5 km [h.sup.-1]. For each participant, the test ended when he or she stopped running and stepped out of the designated shuttle run testing area and walked over to one of the research assistants to get his or her level recorded. The last level at which the participant successfully completed was recorded.

Procedures

Instructors of various physical activity courses granted permission to the researchers to approach potential participants. Participants were recruited in their classes at the start of their class. The instructors informed their students that this meeting would occur a week in advance. The students regardless of study participation would have completed the shuttle run as completion of fitness tests was a part of the course. At the meeting, students were informed that the study concerned whether individual difference variables such as need for achievement were associated with exercise participation and shuttle-run performance. Participants were told that refusal to participate in completing the questionnaires would not negatively affect their class standing. Their class instructor was present to confirm this statement. After participants agreed to volunteer for the study in this meeting, they were presented with the questionnaire packet that was approved by the University Human Subject's Institutional Review Board.

The packet contained the AGQ, LTEQ, PRETIE-Q, and questions to obtain sex and age. Then participants completed the shuttle run task in groups of approximately 25 students each in their respective fitness class as they would have whether or not they were in the study. The time between questionnaire administration and shuttle run completion was approximately 15-25 minutes. Participants were monitored by research assistants to accurately record shuttle run performance.

Results

Table 1 contains the means, standard deviations, and effect sizes for all variables. MANOVAs with univariate post hoc-tests for sex were conducted for the achievement goal variables, and preference and tolerance for strenuous physical activity. In addition, separate ANOVAs were conducted on self-reported strenuous physical activity participation and shuttle run performance. Separate process variable analyses were conducted for sex. Effect sizes (Hedges, 1981) represent differences between men and women. Men were significantly higher in the mastery-approach goal and preference for higher exercise intensity. In addition, the men performed significantly better on the shuttle run performance compared to the women participants. Table 2 lists the intercorrelations among all variables.

Multiple regressions were computed to examine the achievement goal process models. Mediation (Baron & Kenny, 1986) is a statistical process that produces a decrease in the beta for a direct relation (e.g., preference for strenuous exercise to shuttle run performance would be mediated by performance-approach goals). Conversely, suppression (Baron & Kenny, 1986) produces an increase in the beta for a direct relation (e.g., strenuous exercise participation to shuttle run performance would be suppressed by performance-avoidance goals).

The following steps based on Baron and Kenny's recommendations (1986) were examined for the process models: (a) an independent variable must directly predict a dependent variable; (b) an independent variable must predict a process variable; and (c) a process variable must predict a dependent variable, and the indirect relation between the independent variables and the dependent variable must increase or decrease when the process model is controlled. The basic regression model or the independent variables used in the analyses consisted of the following dependent variables: self-reported strenuous exercise participation, preference for strenuous physical activity, and tolerance for strenuous physical.

Basic Model Predicting Exercise Motivations

Self-reported strenuous exercise participation, preference for strenuous physical activity, and tolerance for strenuous physical variables were regressed on shuttle run performance. Because of the previously reported sex differences, separate analyses were conducted for both sexes. For the men, the analysis yielded an overall significant effect, F(3, 151 ) = 10.79, p < .001, [R.sup.2] =. 18. Both strenuous exercise, t = 4.74, p < .001, [beta] =. 37, and preference for strenuous exercise, t = 2.09, p < .05, [beta] = .18, were significant positive predictors of shuttle run performance. For the women, the analysis yielded an overall significant effect, F(3,127) = 6.32, p < .001, [R.sup.2] = .13. Both strenuous exercise, t = 3.16, p < .01, [beta] = .27, and tolerance for strenuous exercise, t = 2.28, p < .05, [beta] = .21, were significant positive predictors of level obtained on the shuttle run task.

Basic Model Predicting Achievement Goals

The two mastery goals were regressed individually on the basic model variables for both men and women. For men, the mastery-approach goal overall model was significant, F(2, 152) = 19.51,p < .001, [R.sup.2] = .18. Strenuous physical activity, t = 4.72,p < .001, [beta] = .35, and preference, t = 2.82, p < .001, [beta] = .21, were significant positive predictors of the mastery-approach goal. For the mastery-avoidance goal, the overall model was significant, F(2, 152) = 3.80, p < .05, [R.sup.2] = .05. Strenuous physical activity, t = -2.14, p < .05, [beta] = -.17, was a significant, negative predictor of the mastery-avoidance goal, whereas preference, t = 1.96, p < .05, [beta] = .16, was a significant, positive predictor of the mastery-avoidance goal.

For women, the mastery-approach goal overall model was significant, F(2, 128) = 9.06, p < .001, [R.sup.2] =. 12. Strenuous physical activity, t = 2.74, p < .01, [beta] = .23, and tolerance, t = 2.74, p < .001, [beta] = .23, were significant positive predictors of the mastery-approach goal. For the mastery-avoidance goal though the overall model was not significant, F(2, 128) = 3.80,p > .05, [R.sup.2] = .04, however strenuous physical activity, t = -2.24, p < .05, [beta] = -.20, was a significant negative predictor of the mastery-avoidance goal.

The two performance goals were regressed individually on the basic model. For men, the performance-approach goal overall model was significant, F(2, 152) = 9.09,p < .001, [R.sup.2] =. 11. Strenuous physical activity, t = 2.37, p < .05, [beta] = .18, and preference, t = 3.27, p < .01, [beta] = .25, were significant positive predictors of the performance-approach goal. For the performance-avoidance goal, the overall model was not significant and neither of the basic model variables were significant predictors of the performance-avoidance goal.

For the women, the performance-approach goal overall model was not significant, F(2, 128) = 2.86, p > .05, [R.sup.2] = .04, however, tolerance for strenuous physical activity was a significant positive predictors of the performance-approach goal, t = 2.38, p < .05, [beta] = .21. For the performance-avoidance goal, the overall model was not significant and neither of the basic model variables significantly predicted the performance-avoidance goal, F(3,127) = 1.09,p > .05, [R.sup.2] = . 03.

Achievement Goal Process Models

The last step in Baron and Kenny's (1986) process model is to determine the extent to which the achievement goals serve as process variables between the basic model variables and shuttle run performance. The variables chosen for the process analysis depend upon significance in the first two steps, as well as preliminary analyses. In this preliminary process analysis, the four goals were regressed on the shuttle run performance to determine which dimensions were significant and needed further analyses. For the men, the mastery and performance-approach goals were significant predictors of shuttle run performance. Subsequent analyses were for process variables related to men, but not women, as none of the goal orientations were significant predictors of shuttle run performance for women.

For the mastery-approach process analysis, a regression was computed to test whether the mastery-approach goal mediated the influence of strenuous exercise participation and preference for strenuous physical activity on shuttle run performance. The overall model was significant, F(3, 151) = 11.50, p < .001, [R.sup.2] = .19. In particular, strenuous exercise participation, t = 4.11, p < .001, [beta] = .33, and preference, t = 2.05, p < .05, [beta] = .15, were significant positive predictors of positive shuttle run performance. The mastery-approach goal beta was not a statistically significant predictor, t = 1.33, p > .05, [beta] = .15. The decrease in beta for strenuous exercise on shuttle run performance was .05 (14%).

To test the significance of the mediated effect, Kenny, Kashy, and Bolger's (1998) method to calculate a z score was followed. If the calculated z score is greater than 1.96, this value is significant at the p < .05 level. The z score for the model was 1.28, hence, the mastery-approach goal did not significantly mediate the influence of strenuous exercise participation on shuttle run performance. The decrease in beta for preference for strenuous exercise on shuttle run performance was .03 (17%). The z score for the model was 1.16, hence, the influence of preference for strenuous physical activity on shuttle run performance was not significantly mediated by the mastery-approach goal.

For the performance-approach process analysis, a regression was computed to test whether the performance-approach goal mediated the influence of strenuous exercise participation and preference for strenuous physical activity on shuttle run performance. The overall model was significant, F(3, 151) = 11.82, p < .001, [R.sup.2] = .19. Specifically, strenuous exercise participation, t = 4.54,p < .001, [beta] = .34, significantly predicted shuttle run performance, whereas preference for strenuous physical activity, t = 1.89, p > .05, [beta] = .15, and the performance-approach goal, t = 1.60, p > .05, [beta] = .12, were not significant. The decrease in beta for strenuous exercise participation on shuttle run performance was .03 (8%).

Kenny et al.'s (1998) method to calculate a z score was also followed to test the significance of the mediated effect. The z score for the model was 2.19, hence, the performance-approach goal significantly mediated the influence of the strenuous physical activity on shuttle run performance. The decrease in beta for preference for strenuous physical activity on shuttle run performance was .035 (19%). The z score for the model was 2.93, hence, the performance-approach goal significantly mediated the influence of preference for strenuous physical activity on shuttle run performance. Taken together the process model results suggested that for men the performance-approach goal fully mediated the influence of preference for strenuous physical activity and mediated the influence of self-reported strenuous exercise history. This significant mediation supported our hypothesis concerning the performance-approach goal. For the women, the process models were not supported. The influence of self-reported strenuous exercise history as well as tolerance for strenuous exercise was direct. As hypothesized, neither of the mastery goals served as process variables.

Discussion

The purpose of the present investigation was to test the hierarchical model of achievement motivation on exerted effort of a physically demanding task. Specifically, Elliot's (1997, 1999) hierarchical model with his two-factor achievement goal framework served as the theoretical foundation of this investigation. Preference and tolerance for exercise intensity, as well as typical strenuous physical exercise participation, served as the antecedent variables within the hierarchical model. The shuttle run task has a performance component, level achieved. In addition, the task was completed in groups ostensibly creating a strong normative assessment climate. Therefore, it was hypothesized that only the performance goal dimension (approach and avoidance) would serve as process variables as opposed to the two mastery goals.

The findings indicated partial support of our hypothesis. The results demonstrated that for men the performance-approach goal mediated preference for intense exercise as well as self-reported strenuous physical activity participation upon shuttle run performance. The performance-approach goal provided full mediation of the influence of preference for intense exercise. This result lends support for Elliot's (1999) hierarchical model of achievement motivation for individual difference variables. For instance, preference for exercise intensity was mediated in full by the performance-approach goal. In addition, based on follow-up mediation analyses, self-reported physical activity history influenced shuttle run performance (i.e., exerted effort) as a function of the performance-approach goal.

Several findings were in contrast to the primary hypothesis. For the women, self-reported physical activity history and tolerance for intense exercise directly influenced shuttle run performance. Performance goals did not mediate or suppress these variables as hypothesized. An examination of several investigations utilizing the two-factor goal framework (Conroy et al., 2006; Cury, Elliot, Sarrazin, Da Fonseca, & Rufo, 2002) suggested that women are similar to men on each achievement goal orientation. To date, only Cury et al. (2002) explicitly stated testing for sex differences in their data. Hence, because of these unexpected differences found in the present investigation, post-hoc examination of the data is discussed.

As shown in Table 2, the correlations among the achievement goals and the shuttle run performance were extremely low. Only the mastery-approach correlation was statistically significant, though it was still quite low. In contrast, the relationship between the achievement goals and the basic model variables in several instances were conceptually consistent, but small to moderate in magnitude. Examination of the data, however, suggests that the mastery goal orientation is conceptually related more often than the performance goal orientation among women participants. The mastery-approach goal was significantly and positively related to self-reported strenuous physical activity history and tolerance for intense exercise, whereas the mastery-avoidance goal was negative and significantly related to self-reported strenuous physical activity history. The mastery-avoidance goal was significantly and positively related to preference for intense exercise.

The performance-avoidance goal hypothesis was not supported for either sex, nor did it significantly predict exerted effort. The basic model variables were also not significantly related to this achievement goal. Given the normative comparison climate in which the shuttle run task was completed, this result is surprising. Classic goal orientation theory as well as Elliot's two-factor structure hypothesizes that any performance goal should exert influence under such environments. In a rare study that examined the effects of Elliot's (1997) two-factor achievement goals on performance, Elliot et al. (2006) examined performance on a basketball dribbling task in 11 to 13 year old French youths. The results indicated that the performance-avoidance goal led to significantly worse performance than did any other achievement goal. Saliency of the four achievement goals were manipulated by the participants reading a description of the dribbling task for both performance goals and both mastery goals. Next, the participants in one of the overall goal conditions (e.g., performance) read descriptions that highlighted the valence of the goal (i.e., approach or avoidance). Therefore, it appears that goal saliency is an important variable for future consideration. Achievement goal saliency was not manipulated in the present investigation. This omission could account for failure of the performance-avoidance goal to mediate or suppress the influence of our basic model variables upon outcome shuttle run performance. This suggests that goal saliency is important when examining achievement goals.

The present study included selected limitations. It appears that goal saliency is an important factor for determining Elliot's (1997) achievement goal model. Future researchers examining exerted effort should consider manipulating achievement goals to test Elliot's model, particularly for the women. The shuttle run task was completed in a highly performance-orientated environment, as the task was conducted in a group setting. Women exerted effort was predicted by tolerance for strenuous physical activity and self-reported engagement in strenuous physical activity.

The results for the men also indicated that the mastery-approach goal is a viable mediator of our basic model variables. This result is consistent with the previous literature (see Duda, 2005, & Elliot, 2005, for reviews in sport and education) suggesting that a mastery goal orientation especially that of an approach style is associated with adaptive achievement strategies. Future experimental research is needed that should yield greater insight into the importance of the mastery-approach goal. Perhaps performance-approach goals, as opposed to mastery-approach goals, are more important mediators of exerted effort or high intensity physical activity for men as opposed to women. Future research is needed to examine the psychological factors, such as goal orientations, that sustain physical effort.

References

Ames, C. (1992). Classrooms: Goals, structures, and student motivation. Journal of Educational Psychology, 84, 261-271.

Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychology research: Conceptual, strategic, and statistical considerations. Journal of Personality & Social Psychology, 51, 1173-1182.

Biddle, S. J. H. (1999). Motivation and perceptions of control: Tracing its development and plotting its future in exercise and sport psychology. Journal of Sport & Exercise Psychology, 21, 1-23.

Conroy, D. E., & Elliot, A. J. (2004). Fear of failure and achievement goals in sport: Addressing the issue of the chicken and the egg. Anxiety, Stress, & Coping, 17, 271-285.

Conroy, D. E., Elliot, A. J., & Hofer, S. M. (2003). A 2 x 2 achievement goal questionnaire for sport: Evidence for factorial invariance, temporal stability, and external validity. Journal of Sport & Exercise Psychology, 25, 456-476.

Conroy, D. E., Kaye, M. P., & Coatsworth, J. D. (2006). Coaching climates and the destructive effects of mastery-avoidance achievement goals on situational motivation. Journal of Sport & Exercise Psychology, 28, 69-92.

Cury, F., Elliot, A. J., Da Fonseca, D. D., & Moller, A. C. (2006). The social-cognitive model of achievement motivation and the 2 x 2 achievement goal framework. Journal of Personality & Social Psychology, 90, 666-679.

Cury, F., Elliot, A. J., Sarrazin, P., Da Fonseca, D., & Rufo, M. (2002). The trichotomous achievement goal model and intrinsic motivation: A sequential mediational analysis. Journal of Experimental Social Psychology, 38, 473-481.

Duda, J. L. (1989). Relationship between task and ego orientation and the perceived purpose of sport among high school athletes. Journal of Sport & Exercise Psychology, 11, 318-335.

Duda, J. L. (2005). Motivation in sport: The relevance of competence and achievement goals. In A. J. Elliot & C. S. Dweck (Eds.), Handbook of competence and motivation (pp. 318-335). New York: Guilford Press.

Duda, J. L., & Whitehead, J. (1998). Measurement of goal perspectives in the physical domain. In J. L. Duda (Ed.), Advances in sport and exercise psychology measurement (pp. 21-48). Morgantown, WV: Fitness Information Technology.

Dweck, C. S. (1986). Motivational processes affecting learning. American Psychologist, 41, 1040-1048.

Dweck, C. S., & Leggett, E. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95, 256-273.

Ekkekakis, P, Hall, E. E., & Petruzzello, S. J. (2005). Variation and homogeneity in affective responses to physical activity of varying intensities: An alternative perspective on dose-response based on evolutionary considerations. Journal of Sports Sciences, 23, 477-500.

Elliot, A. J. (1997). Integrating the "classic" and "contemporary" approaches to achievement motivation: A hierarchical model of approach and avoidance achievement motivation. In P. Pintrich & M. Maehr (Eds.), Advances in motivation and achievement (Vol. 10, pp. 143-179). Greenwich, CT: JAI Press.

Elliot, A. J. (1999). Approach and avoidance motivation and achievement goals. Educational Psychologist, 34, 169-189.

Elliot, A. J. (2005). A conceptual history of the achievement goal construct. In A. J. Elliot & C. S. Dweck (Eds.), Handbook of competence and motivation (pp. 52-72). New York: Guilford Press.

Elliot, A. J., & Church, M.A. (1997). A hierarchical model of approach and avoidance achievement motivation. Journal of Personality & Social Psychology, 72, 218-232.

Elliot, A. J., Cury, F., Fryer, J. W., & Huguet, P. (2006). Achievement goals, self-handicapping, and performance attainment: A mediational analysis. Journal of Sport & Exercise Psychology, 28, 344-361.

Elliot, A. J., & Harackiewicz, J. M. (1996). Approach and avoidance achievement goals and intrinsic motivation: A mediational analysis. Journal of Personality & Social Psychology, 70, 461-475.

Elliot, A. J., & McGregor, H. A. (2001). A 2 x 2 achievement goal framework. Journal of Personality & Social Psychology, 80, 501-519.

Elliot, A. J., & Thrash, T. M. (2001). Achievement goals and hierarchical model of achievement motivation. Educational Psychology Review, 13, 139-156.

Elliot, A. J., & Thrash, T. M. (2002). Approach-avoidance motivation in personality: Approach and avoidance temperaments and goals. Journal of Personality & Social Psychology, 82, 804-818.

Godin, G., & Shephard, R. J. (1985). A simple method to assess exercise behavior in the community. Canadian Journal of Applied Sport Science, 10, 141-146.

Hedges, L. V. (1981). Distribution theory for Glass's estimator of effect size and related estimators. Journal of Educational Statistics, 6, 107-128.

Heimpel, S. A., Elliot, A. J., & Wood, J. V. (2006). Basic personality dispositions, self-esteem, and personal goals: An approach-avoidance analysis. Journal of Personality, 74, 1293-1319.

Kenny, D. A., Kashy, D. A., Bolger, N. (1998). Data analysis in social psychology. In D. Gilbert, S. Fiske, & G. Lindzey (Eds.), The handbook of social psychology (Vol. 1, 4th ed., pp. 233-265). Boston, MA: McGraw-Hill.

Leger, L. A., & Lambert, J. (1982). A maximal multistage 20-m shuttle run test to predict VO2max. European Journal of Applied Physiology, 49, 1-12.

Leger, L. A., Mercier, D., Gadoury, C., & Lambert, J. (1988). The multistage 20 metre shuttle run test for aerobic fitness. Journal of Sports Sciences, 6, 93-101.

Maehr, M. L., & Braskamp, L. A. (1986). The motivation factor: A theory of personal investment. Lexington, MA: D. C. Heath.

Moller, A. C., & Elliot, A.J. (2006). The 2 x 2 achievement goal framework: An overview of empirical research. In A. Mittel (Ed.), Focus on educational psychology (pp. 307-326). Hauppauge, NY: Nova Science Publishers.

Nicholls, J. G. (1984a). Conceptions of ability and achievement motivation. In R. Ames & C. Ames (Eds.), Research on Motivation in Education: Student Motivation (Vol. 1, pp. 39-73). New York: Academic Press.

Nicholls, J. G. (1984b). Achievement motivation: Conceptions of ability, subjective experience, task choice, and performance. Psychological Review, 91, 328-346.

Nicholls, J. G. (1989). The competitive ethos and democratic education. Cambridge, MA: Harvard University.

Roberts, G. C. (1992). Motivation in sport and exercise: Conceptual constraints and convergence. In G. C. Roberts (Ed.), Motivation in sport and exercise (pp. 3-29). Champaign, IL: Human Kinetics.

Roberts, G. C. (2001). Understanding the dynamics of motivation in physical activity: The influence of achievement goals on motivational processes. In G. C. Roberts (Ed.), Advances in motivation in sport and exercise (pp. 1-50). Champaign, IL: Human Kinetics.

Smith, M., Duda, J., Allen, J., & Hall, H. (2002). Contemporary measures of approach and avoidance goal orientations: Similarities and differences. British Journal of Educational Psychology, 72, 155-190.

Van Yperen, N. W. (2006). A novel approach to assessing achievement goals in the context of the 2 x 2 framework: Identifying distinct profiles of individuals with different dominant achievement goals. Personality & Social Psychology Bulletin, 32, 1432-1445.

Wang, C. K. J., Biddle, S. J. H., & Elliot, A. J. (2007). The 2 x 2 achievement goal framework in a physical education context. Psychology of Sport & Exercise, 8, 147-168.

Whitehead, J., Andree, K. V., & Lee, M. J. (2004). Achievement perspectives and perceived ability: How far do interactions generalize in youth sport? Psychology of Sport & Exercise, 5, 291-317.

Zusho, A., Pintrich, P. R., & Cortina, K. S. (2005). Motives, goals, and adaptive patterns of performance in Asian American and Anglo American students. Learning & Individual Differences, 15, 141-158.

Marc Lochbaum, Sarah Stevenson, and Daniel Hilario

Texas Tech University

Address Correspondence To: Marc Lochbaum, Ph.D., Health, Exercise, and Sport Sciences, Box 4301 l, Texas Tech University, Lubbock, TX 79409-3011, Phone: (806) 742-3371, E-mail: [email protected]
Table 1. Means, standard deviation, effect sizes, and differences
statistics for men and women participants for all variables

 Men Women

 M SD M SD ES

Achievement Goal Questionnaire (A)

 Mastery-Approach (a) 5.28 1.18 4.89 1.10 .34
 Mastery-Avoid 3.95 1.57 4.19 1.50 -.16
 Performance-Approach 3.98 1.57 3.75 1.44 .15
 Performance-Avoid 3.19 1.29 3.21 1.39 -.01

Preference for and Tolerance of the Intensity of Exercise
Questionnaire (B)

 Preference (b) 26.23 5.57 24.93 4.82 .25
 Tolerance 26.13 4.59 25.40 4.57 .17

Leisure Time Exercise Questionnaire (C)

 Strenuous Physical Activity 3.24 2.03 2.65 1.59 .32

Shuttle Run

 Level (D) 7.34 2.23 5.22 1.42 1.12

Note: (A) Wilks' Lambda =.96, F(4,281) = 2.87, p <.05; (a) F(1,284) =
8.11, p < .01; (B) Wilks' Lambda = .98, F(2,283) = 2.25, p >.05; (b)
 F(l,284) = 4.37, p <.05; (C) F(1,283) = 7.29, p <.0l (D) F(1,284)
= 96.32, p<.001.

Table 2. Correlations among all variables with the top half of the
diagonal being only men and the bottom half of the diagonal being
only women.

Variables 1 2 3 4

Shuttle run performance 1.00 .38 ** .19 ** .22 **
Self-report strenous exercise .30 ** 1.00 .29 ** .11
Tolerance .24 ** .17 ** 1.00 .54 **
Preference .05 .01 .43 ** 1.00
Mastery-Approach .17 ** .27 ** .27 ** .07
Mastery-Avoidance -.05 .19 ** -.02 .24 **
Performance-Approach -.12 .01 .21 ** .19 *
Performance Avoidance .01 -.14 -.03 .06

Variables 5 6 7 8

Shuttle run performance .27 ** -.04 .24 ** .02
Self-report strenous exercise .37 ** -.15 .21 ** .02
Tolerance .42 ** .08 .21 ** .O1
Preference .25 ** .14 .27 ** .09
Mastery-Approach 1.00 .12 .41 ** .19 **
Mastery-Avoidance .19 ** 1.00 .16 ** .29 **
Performance-Approach .37 ** .35 ** 1.00 .50 **
Performance Avoidance .11 .35** .67 ** 1.00

Note. ** p < .01; * p < .5
联系我们|关于我们|网站声明
国家哲学社会科学文献中心版权所有