Advances in Physical Education
2011. Vol.1, No.2, 16-22
Copyright © 2011 SciRes. DOI:10.4236/ape.2011.12004
Measured and Perceived Physical Fitness, Intention, and
Self-Reported Physical Activity in Adolescence
Timo Jaakkola1, Tracy L. Washington2
1Department of Sport Sciences, University of Jyväskylä, Jyväskylä, Finland;
2School of Exercise and Nutrition Sciences, IHBI, Faculty of Health, Queensland University of Technology,
Brisbane, Australia.
Received September 16th, 2011; revised October 19th, 2011; accepted October 29th, 2011.
Objective: The aim of this study was to investigate the associations among measured physical fitness, perceived
fitness, intention towards future physical activity and self-reported physical activity through junior high school
years. Methods: Study participants included 122 Finnish students who were 13 years old during Grade 7. The
sample was comprised of 80 girls and 42 boys from 3 junior high schools (Grades 7 - 9). During the autumn se-
mester of Grade 7, students completed fitness tests and a questionnaire analyzing self-perception of their physical
fitness. The questionnaire delivered at Grade 8 included intention towards future physical activity. At Grade 9
students’ self-reported physical activity levels. Results: Structural Equation Modelling revealed an indirect path
from physical fitness to self-reported physical activity via perceived physical fitness and intention towards future
physical activity. The model also demonstrated a correlation between perceived physical fitness and physical ac-
tivity. Squared multiple correlations revealed that perceived physical fitness explained 33 % of the actual physical
fitness. Conclusions: The results of this study highlight the role of physical and cognitive variables in the process
of adoption of physical activity in adolescence.
Keywords: Physical Activity, Fitness, Self-Perceptions, Adolescents
Childhood and adolescence is a critical time period for
adopting a physically active lifestyle. Evidence exists to dem-
onstrate that childhood and adolescence patterns of physical
activity (PA) moderately track into adulthood which means that
active children and adolescents are more likely to become active
adults (Telama et al., 2005). Additionally, previous studies have
shown that PA declines markedly during the transition from
elementary school to secondary school and the decrease con-
tinues throughout secondary school (Telama & Yang, 2000;
Nader, Bradley, & Houts, 2008). This decline is suggested to be
related with different physical, psychological, and social factors
(Sallis, Prochaska, & Taylor, 2000). Aforementioned studies
demonstrate that investigating the antecedents of youth PA
patterns remain one of the most important topics in the sport
The concept of physical fitness can be divided into health-
related fitness and skill related fitness (Caspersen, Powell, &
Christenson, 1985). Health related fitness includes the compo-
nents of cardiorespiratory endurance, muscular endurance,
muscular strength, body composition, and flexibility. Skill-
related fitness includes factors such as agility, balance, coordi-
nation, speed, power, and reaction time. Methods analyzing
physical fitness within children and adolescents typically in-
volve both fitness themes (Safrit, 1990). It has been suggested
that physical fitness in childhood and adolescence is an impor-
tant factor influencing engagement of PA in adulthood (Malina,
2001). More specifically, research has shown that youth who are
more active, obtain higher scores on cardiovascular tests than
inactive youth when compared with inactive youths. However,
the associations between other health-related fitness variables
and PA are more inconsistent (Huotari, Nupponen, Laakso, &
Kujala, 2009; Huotari, Nupponen, Laakso, & Kujala, 2010).
A number of social-cognitive models hypothesize that dif-
ferent cognitive variables are involved in the process of adopting
behaviors such as .PA engagement (Ajzen, 1991; Bandura, 1997;
Hagger & Chatzisarantis, 2007). These cognitive attributes
include physical self-perceptions and intention towards future
activity. More specifically, studies have shown that self-percep-
tions such as perceived physical competence (Bagoien & Halvari,
2005), self-efficacy (Dishman et al., 2005), and self-esteem
(Tremblay, 2000) have been positively associated with PA in
school aged participant groups. Additionally, many social-
cognitive theories have suggested that there are cognitive proc-
esses determining behavior. One of the most utilized social
cognitive theories in the field of PA research is the theory of
planned behavior (TPB), which postulates that belief-based
social cognitive constructs, namely attitudes, subjective norms
and perceived behavioral control, are antecedents of behavior
such as PA (Ajzen, 1991). Attitudes in TPB are defined as a
person’s belief that the target behavior will result in certain
desirable outcomes. Subsequently, subjective norms are defined
as a person’s belief that others desire them to perform the target
behavior. Perceived behavioral control in TPB represents a
person’s belief that they have capacities, faculties, abilities, and
resources to engage in the target behavior. Conceptually per-
ceived behavioral control of the theory of planned behavior
represents a rather similar construct than self-efficacy (Bandura,
1997) and perceived competence (Harter, 1978) in other so-
cial-cognitive models. All of these constructs assume that the
belief a person has on their abilities and capacities effects their
subsequent behavior. The link between physical self-perceptions
and PA has been shown in many studies using the samples of
schoolchildren (Hagger & Chatzisarantis, 2009; Hagger, Chat-
zisarantis, Biddle, & Orbell, 2001; Hagger, Chatzisarantis,
Culverhouse, & Biddle, 2003; Sallis et al., 2000). In the present
study, we use the variable of perceived physical fitness to rep-
resent perceived competence related to the person’s actual
physical fitness (see Figure 1). Theoretically, we assume that the
variable of perceived physical fitness represents a similar con-
struct rather than perceived behavioral control in the theory of
planned behavior.
Interestingly, previous studies have shown that children and
adolescents have rather reliable perceptions of their measured
physical fitness (Huotari, Sääkslahti, & Watt, 2009). For exam-
ple, Huotari et al. (2009) reported high correlations between
measured and perceived fitness in a sample of 48 Finnish 12
year-old children. Specifically, the correlations between meas-
ured and perceived endurance and strength was .69 and .71
respectively. These results indicate that Finnish children per-
ceive his/her own physical fitness as a reliable representation of
actual fitness. In the other words, the objective measure of fit-
ness seems to determine whether children perceive themselves
competent in situations related to physical fitness. Although the
evidence on the association among measured physical fitness,
physical self-perceptions, and PA exist, there are no studies
analyzing the interaction between measured and perceived fit-
ness in the process of adopting PA.
Social-cognitive models suggest that intention mediates the
association between self-perceptions and behavior (Ajzen, 1991;
Hagger & Chatzisarantis, 2007). Therefore, intention is observed
as the most reliable and proximal predictor of behavior. Con-
ceptually, intention is intended to summarize a person’s general
affective and cognitive orientation toward the behavior, the
perceived pressure placed on them by significant others to par-
ticipate in the target behavior and their competence-related
evaluation of their faculties and capacities toward the behavior
(Hagger et al., 2003). According to the TPB and the trans-
contextual model, intention is a direct predictor of behavior,
whereas physical self-perceptions represent indirect predictors
(Hagger et al., 2003; Hagger, Chatzisarantis, & Harris, 2006).
The studies within the context of PA have supported this as-
sumption of the mediating role of intention between self-perce-
ptions and behavior (Hagger & Chatzisarantis, 2009; Lippke,
Ziegelmann, & Schwarzer, 2004). Intention is considered to be
an important factor in the process of adopting the habit of PA.
However, there are only a few studies to investigate the rela-
tionship between intention toward activity and PA within ado-
lescent groups (Hagger et al., 2001; Hagger et al., 2003; Hagger
et al., 2007). Furthermore, the observed studies were longitudi-
nal where only a few weeks time interval was allowed to inves-
tigate how cognitive variables would translate into behavior.
Behavioral change is a complex process and therefore we can
assume that the process takes more time (Booth et al., 2010).
The rationale of the current study stems from the theoretical
predictions and empirical results presented above. We assume
that the measured physical fitness variables will result in per-
ceived physical fitness, which subsequently fall within the in-
tention to be physically active. The intention would then result
in physical activity later. In the other words, we suggest that
there are sequential associations among measured and perceived
physical fitness, intention toward PA, and self-reported PA. In
this study, we test these associations through junior high school
years by measuring fitness and perceived physical fitness vari-
ables at Grade 7 as the first variables in the model. Intention
toward future activity is gathered at Grade 8 and is set as the
second variable in the model, and the last variable located in the
model is self-reported PA which is collected and analyzed at
Grade 9. To our knowledge, this is the first study to analyze the
relationship among these four variables in the same model
through the adolescent years. Research is needed in this area as
previous studies have demonstrated that PA clearly declines
within the adolescent years (Telama & Yang, 2000; Nader et al.,
2008) and that PA adopted in childhood and adolescence is
known to track into adulthood (Telama et al., 2005).
Hence, the primary aim of this study was to investigate the
associations among measured physical fitness, perceived fitness,
intention towards future PA, and self-reported PA during the
junior high school years. We hypothesized that physical fitness
would be positively associated with perceived physical fitness at
Grade 7. Additionally, we assumed that perceived physical
fitness would positively and sequentially predict intention to-
wards PA at Grade 8 and self-reported PA at Grade 9. The se-
quential pattern of study variables is presented in Figure 1.
Participants a nd Desi gn of the Study
Study participants included 122 Finnish students who were 13
years old during their Grade 7. The sample was comprised of 80
girls and 42 boys from 3 junior high schools (grades 7 - 9).
During the autumn semester of Grade 7 students implemented
the fitness tests and completed the questionnaire analyzing
self-perception of their physical fitness. The questionnaire de-
livered at Grade 8 included intention towards future PA. Within
Grade 9 students’ self-reported PA engagement was collected.
Fitness tests. The physical fitness tests package is a widely
used instrument in Finnish physical education (Nupponen, Soini,
& Telama, 1999). Throughout junior high school, the test
package is typically implemented one or two times every aca-
Fitness index
Stre nght
Grade 7 Grade 8Grade 9
Grade 7
Figure 1.
The hypothesized sequential pattern of associations among the study variables.
demic year. The primary aim of the fitness tests is to give stu-
dents information on their physical fitness levels and to motivate
them to exercise during their leisure time. The Finnish test
package includes items analyzing students’ strength, speed,
aerobic fitness, flexibility, and fundamental movement skills.
For the purpose of this study, we used only the items pertaining
to strength, speed, aerobic fitness, and flexibility. It should be
noted that there are two parallel aerobic fitness and abdominal
muscle endurance tests in the Finnish physical education fitness
test package. Girls typically run 1500 meters for the aerobic
fitness test, whereas boys favor the12 minute Cooper test. In this
study, all girls participated in the 1500 meter test and most of the
boys (76%) completed the Cooper test. The manual also includes
two abdominal tests analyzing abdominal muscle endurance.
The first is a 30 seconds sit up test and the second is a Curl-up
test.. All physical fitness tests in this study were implemented
according to the international and Finnish standards for the
assessment of physical fitness (Eurofit, 1988; Larson, 1974;
Nupponen et al., 1999; Safrit 1990). These tests are valid and
reliable tools in measuring junior high school aged children’s’
physical fitness.
The instruments analyzing perceived physical fitness, inten-
tion towards future PA, and self-reported PA were adopted from
the Health Behavior in School-aged Children survey, which was
developed by the World Health Organization and is conducted in
North America and many countries within Europe. Prochaska,
Sallis and Long (2001) reported adequate factorial validity and
reliability of these two PA engagement items in a sample of 148
Abdominal muscle endurance tests. The goal of the 30 sec.
abdominal muscle test is to complete as many sit-ups in 30
seconds as possible. In the Curl-up test participants are required
to perform the task at a given pace at five second intervals and
effectively complete as many repetitions as possible. In the 30
sec. test, the participant’s hands are crossed behind their head,
whereas in the Curl-up test, hands are crossed in front of the
trunk fingers being on shoulders. In 30 sec. test, the result is the
amount of proper repetitions within 30 second time. In the latter
abdominal test, the result is the number of proper repetitions
which the person can perform on pace.
Speed test. In the speed test, the purpose was to run 50 meters
as quick as possible. The student started running from ready – go
signals and a teacher recorded the running time by stopwatch.
The result is the total running time from the start signal to the
crossing of the finish line.
Aerobic fitness tests. Aerobic fitness was assessed by the
1500 meters running test and 12 min. Cooper test. The result of
the 1500 meters test is the total time for running the distance. In
the Cooper test, the result is the amount of meters, which a
person was able to run within 12 minutes.
Flexibility test. Sit and reach test was used in analyzing stu-
dents’ flexibility. In the test, the task is to sit on the floor both
legs straight against a bench and reach forward. The meter is
spread out on the bench so that the result is 50 cm if the student is
able to reach fingertips at the level of his/her soles.
Perceived physical fitness. Perceived physical fitness was
measured by a one item question, “How do you consider your
physical fitness?” The item is presented using a 4-point response
scale (1 = Poor, 2 = Moderate, 3 = Good, 4 = Excellent).
Intention towards future physical activity. Intention towards
future PA was analyzed by the question: “How likely are you to
participate in regular PA after one year”. The item is rated on a
five point Likert scale (1 = strongly unlikely to 5 = strongly
Self-reported physical activity. PA engagement was analyzed
by a self-report questionnaire. The introduction for the questions
is: “In the next two questions PA means all activities which raise
your heart rate or momentarily gets you out of breath, for ex-
ample, in doing exercise, playing with your friends, going to
school, or in school physical education. PA also includes for
example jogging, intensive walking, roller skating, cycling,
dancing, skating, skiing, soccer, basketball and baseball.” The
items are “Think about your typical week. How many days did
you exercise for at least 60 min. during which you got out of
breath” and “Think about your last 7 days. How many days did
you exercise for at least 60 min during which you get out of
breath?” Both items are presented using an 8-point response
scale, 0 to 7 days in a week. A sum scale of PA engagement was
formulated by adding the response scores for the two items to
assess students’ self-reported engagement in both moderate to
vigorous and vigorous PA.
Data Preparation
Numerous steps were taken to prepare for the data analysis. It
should be noted that the scales in this study were originally in the
reverse direction when compared with the other instruments.
Therefore, for the clarity of results in correlation and structural
equation modelling (SEM) analyses we transformed the two
scales to be comparable with the other measures. Additionally,
before SEM analysis was conducted, the abdominal test (the 30
sec. sit-up and Curl-up test) scores were summed together to
create a sumscale. Furthermore, the same procedure was fol-
lowed for the two aerobic fitness test scores. Subsequently,
actual scores were then translated as standardized Z-scores for
further statistical analyses. Finally, exogenous or indirectly
observed variables of strength, speed, aerobic fitness, and flexi-
bility were identified as a latent variable of fitness for the SEM
Data Analysis
The participants’ scores for both the fitness tests and the
self-report questionnaires were summarized using descriptive
statistics. Pearson’s correlation coefficients and structural equa-
tion modelling were used to examine the relationships between
variables. Statistical analyses were conducted using PASW for
Windows 18 (yr) and LISREL 8.30 (yr) software. In the fitness
data, altogether 96 students completed the 30 sec. abdominal
muscle endurance test, and twenty-five students completed the
abdominal curl up muscle test. For the aerobic fitness tests 90
students ran the timed 1500 meters and 32 students completed
the Cooper test.
The descriptive data of measured variables are shown in Table
1. Pearson’s correlation coefficients are shown in Table 2 indi-
cate that significant moderate correlations exist among strength,
speed, and aerobic fitness. The correlations between flexibility
and other physical fitness variables were weak. Additionally,
perceived physical fitness, intention towards, future activity,
strength, speed, and aerobic fitness had weak to moderate in-
tercorrelations. PA correlated significantly only with strength,
perceived physical fitness, and intention towards future activity;
however, these correlations were weak.
The adequacy of the hypothesized model of study variables
were analyzed via structural equation modelling (SEM). Firstly,
descriptive statistics were analyzed and results indicated that the
scales were approximately normally distributed. Therefore, the
maximum likelihood method was applied. The overall fit of the
analyzed model to the data was investigated using the chi-square
test (x²). A non-significant result shows that the proposed model
has an acceptable fit to the data. Additionally, the Root Mean
Square Error of Approximation (RMSEA), the Non Normed Fit
Index (NNFI), the Goodness of Fit Index (GFI), and the Ad-
justed Goodness of Fit Index (AGFI) were examined. The NNFI,
GFI, and AGFI indices vary from 0 to 1. Fit indices greater than
0.90 are indicative of acceptable model fit. In addition, the
p-value associated with a hypothesis test of RMSEA of 0.05 is
indicative of a representative model. Additionally, the propor-
tion of variance predicted by independent variables for the de-
pendent variables were investigated using squared multiple
correlations (r²).
The results of the proposed model demonstrated poor fit to the
data. The next phase was to examine the modification indices
and remove all insignificant path coefficients from the model.
After this procedure SEM analysis revealed that the final model
had a good fit to the data (x² = [12] = 9.78, p > 0.71; NNFI =
1.00; GFI = 0.98; AGFI = 95; RMSEA = 0.000).
The model reveals an indirect path from physical fitness index
to self-reported PA via perceived physical fitness and intention
towards future PA. The model also demonstrated a correlation
between perceived physical fitness and PA. Squared multiple
correlations revealed actual physical fitness explained rather
highly perceived physical fitness (33%). All other squared mul-
tiple correlations are low. The final model is presented in Figure
Table 1.
Variables of the study (Grades 7 - 9).
Variable n Grade M SD Min Max
30 sec. abdom. test (repetitions) 97 7 23.04 6.43 9 43
Curl up abdom. test (repetitions) 25 7 123.8569.36 33 220
50 m speed test (sec.) 122 7 8.48 0.76 7.22 10.03
Cooper test (meters) 32 7 2196.72362.051540 2650
1500 m test (min. sec.) 90 7 8.14 1.17 6.00 13.17
Reaching test (cm) 122 7 61.38 8.39 30 78
Perceived fitness 122 7 2.90 0.66 1 4
Intention 122 8 4.43 0.87 1 5
Physical activity 122 9 3.96 1.71 0 7
Table 2.
Correlations among the study variables.
1. 2. 3. 4. 5. 6.
1. Strength
2. Speed 0.39***
3. Aerobic fitness 0.40*** 0.62***
4. Flexibility 0.09 0.17 0.19*
5. Perceived fitness 0.30*** 0.34*** 0.38*** 0.10
6. Intention 0.31*** 0.20* 0.32*** 0.07 0.35***
7. Physical activity 0.23** 0.02 0.13 0.01 0.32*** 0.26**
p < 0.05*, p < 0.01**, p < 0.001***
(13) = 18.21, p = .15
MSEA = .058
GFI = .96
GFI = .91
NFI = .92
Grade 7
Grade 9
Grade 8
Grade 7
Intention Physical
Stre nght
Fitness index Perceived
Figure 2.
The results of the Structural Equation Modelling.
The main purpose of the present study was to investigate the
associations among measured physical fitness, perceived fitness,
intention towards future PA, and self-reported PA during junior
high school years. We hypothesized that actual physical fitness
is positively associated with perceived physical fitness at Grade
7. Additionally, we assumed that perceived physical fitness
positively and sequentially predicted intention towards PA at
Grade 8 and self-reported PA at Grade 9. To our knowledge, this
is the first attempt to analyze measured and perceived physical
fitness, intention, and self-reported PA through junior high
Path analysis revealed an indirect path from physical fitness
index to self-reported PA via perceived physical fitness and
intention towards future PA. Additionally, analysis indicates a
correlation between perceived physical fitness and PA. Although
squared multiple correlations among study variables are rather
low, the results of the study indicate that both physical and
cognitive variables are involved in the process in which ado-
lescents adopt PA.
In this study, physical fitness was associated with later PA as
earlier studies have suggested (Malina, 2001). However, physi-
cal fitness measured at Grade 7 did not have a direct effect on PA
at Grade 9. The path from physical fitness to future PA is
through perceived fitness and intention towards future PA. The
results of this study highlight the important roles that cognitive
factors serve in the process of PA adoption (Hagger & Chat-
zisarantis, 2009; Sallis et al., 2000). These results may also
explain earlier contradictory findings on the associations be-
tween physical fitness and PA, where students with good re-
sults in muscular endurance, muscular strength, body composi-
tion, and flexibility are not necessarily the most active (Huotari
et al., 2009; Huotari et al., 2010; Malina, 2001). The results of
this study suggest that cognitive attributes exist between meas-
ured physical fitness and PA. Students who score high on fit-
ness tests do not necessarily perceive themselves as competent
in the PA domain or have not developed intention towards PA.
According to the social cognitive models of behavior, these
constructs are crucial for targeting behaviors such as PA (Ajzen,
1991; Bandura, 1997; Hagger et al., 2007). The lack of these
cognitive variables is evidenced by students’ lower level of
engagement in PA.
This study reveals that the perception of one’s fitness is a
crucial factor shaping a student’s intention towards future ac-
tivity and subsequent PA patterns. This finding is in agreement
with many sport psychology studies, which have found positive
associations between physical self-perceptions and PA within
adolescent groups (Bagoien & Halvari, 2005; Dishman et al.,
2005; Hagger et al., 2003; Sallis et al., 2000; Tremblay, 2000).
The results of this study also further support social cognitive
models, which propose that intention mediates between
self-perception and behavior (Ajzen, 1991; Hagger & Chatzis-
arantis, 2007). Earlier empirical studies in adolescents’ PA con-
text have shown contradictory results of these associations. Most
studies have supported social cognitive models (Hagger, 2001;
Hagger et al., 2003; Hagger et al., 2007; Rhodes, Macdonald, &
McKay, 2006) whereas some have not given support to the
models (Motl, 2002). The possible reason for these contradictory
results may be that the studies pertaining to social cognitive
models were cross-sectional designs or the time interval between
measurement points was only few weeks. It is evident that the
behavioral change especially in adolescence, where many psy-
chological, social, and physical changes exist, takes more time
(Booth et al., 2010). In this study, we followed students through
their 3-year junior high school period, which provides reliable
information on the associations among perceived physical fit-
ness, intention, and self-reported PA. Additionally, knowing that
PA levels typically decreases during junior high school (Telama
& Yang, 2000; Nader et al., 2008), it was important to investi-
gate the associations among physical, cognitive, and behavioral
variables within the junior high school period.
The results of this study highlight the role of measured and
perceived physical fitness in the process of adoption of PA in
adolescence. Schools and particularly physical education are the
obvious possible channels to support engagement in PA as they
reach the entire age cohort of adolescents. However, in many
countries, the students have only one session of obligatory
physical education weekly. Clearly, a single class is not suffi-
cient to develop a students’ actual fitness. Therefore, the em-
phasis concerning physical fitness training in physical education
curriculum should include an educational component to address
leisure time fitness opportunities. The physical education cur-
riculum could include information on FIT (intensity, time, and
frequency) principles, and the benefits of physical fitness train-
ing. Earlier studies in adolescents’ in PA context have shown
that a teacher can contribute to a child’s attitude and intention
towards PA. For example in 2005, Chatzisarantis and Hagger
performed an intervention with schoolchildren that demon-
strated children that were in a salient belief-based persuasive
communication group reported more positive attitudes and
stronger intentions towards future PA than those who were in
nonsalient behavioral belief group. These findings suggest that
even little investments in physical education curriculum might
positively affect the possibility for adolescents PA engagement.
Motivation research in the area of sport and exercise psy-
chology has revealed that self-referenced rather than normative
social climate of the PA participation groups have been associ-
ated with positive development of physical self-perceptions, PA
intentions, and actual PA. In other words, by emphasizing a
task-involving motivational climate practitioners are able to
positively affect all cognitive and behavioral variables adopted
in our study (Standage, Duda, & Ntoumanis, 2003a; Standage,
Duda, & Ntoumanis, 2003b; Standage, Duda, & Ntoumanis,
2005; Wallhead & Ntoumanis, 2004). These results emphasize
that when implementing physical fitness training, practitioners
should utilize a task-involving motivational climate for example
by adopting didactical principles of the TARGET model (Ep-
stein, 1989). In this way he/she is able to support the cognitive
and behavioral process where adolescents adopt PA.
The use of self-reports in measuring PA engagement is one of
the limitations of this study. In some studies self-report measures
of PA have had limited reliability and validity particularly in
samples of children and adolescents (Shephard, 2003). Another
limitation of this study is a relatively small number of partici-
pants. The sample size did not allow for us to compare the boys’
and the girls’ models with each other. Earlier studies have in-
dicated that there are differences in physical self-perceptions
between boys and the girls. For example, Lintunen (1995) rec-
ognized that between ages 11 and 15 girls’ physical self-
perceptions became more realistic compared with the boys
perceptions. These differences might also relate to the gender
differences in the process of adoption PA. Finally, there are
limitations to the study as it is cross sectional in nature with
measures taken at three different time points over a span of three
years. Therefore, the results can only be interpreted as observed
associations between the main variables over a three-year pe-
Future studies should investigate whether gender differences
affect the outcome measures. In addition, it will be important for
future interventions to implement measures that affect students’
intention towards PA through the school years. Such interven-
tions would help inform researchers to understand just how
physical and cognitive variables interact while school aged
students adopt habitual or lifelong PA.
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