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.
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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