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Sport
Psychology (PSY407)
Lesson
17
SITUATIONAL
FACTORS RELATED TO ANXIETY AND
MOOD
We
have learned that
individuals bring to the athletic situation
certain traits or characteristics that
are relatively
stable
and that basic personality traits
were predictors of athletic performance.
The environment or the situation
is
believed to interact with the athlete's personality to
influence behavior and athletic
performance.
Mood
State and Athletic
Performance
A
personality trait is believed to be a relatively
permanent disposition. Conversely, a mood
state is believed to be
a
situation specific, somewhat
transient, psychological response to an
environmental stimulus. For
example, the
predisposition
to be tense in a wide variety of situations is a
personality trait, whereas the actual
manifestation of
tension
is situation-specific and is a mood
state. From a psychological
perspective, a mood state should
have a
stronger
influence on behavior than a personality
trait.
Just
as the effects of personality on athletic behavior
can be determined and measured, so
also can the effects
of
the
situation (environment) on athletic
behavior be determined. Mood
states fluctuate as the situation
changes.
In
this lecture we will discuss the
following topics:
·
Ways
in which sport psychologists measure
mood state
·
Morgan's
mental health model
·
Research
and the Profile of Mood
States
·
The
interactional model
·
The
mood profile of the elite disabled
athlete.
Ways
in Which Sport Psychologists
Measure Mood
State
The
Profile of Mood States (POMS) is by
far the most commonly used instrument
for measuring mood states
in
psychology.
LeUnes and Burger (1998)
noted that the POMS was
first used in sport in 1975.
Originally
developed
by McNair, Lorr and
Droppleman (1971, 1981,
1992), the POMS is composed of 65
items that
measure
six mood states:
1.
Tension
2.
Depressions
3.
Anger
4.
Vigor
(positive)
5.
Fatigue
6.
Confusion
Five
of these mood states are
negative in nature, while
one is positive (vigor).
Since the original development of
the
POMS in 1971, two additional
authorized versions of the POMS have
been developed. In addition to
the
three
authorized versions of the POMS, independent
researchers have developed four
other shortened
versions
(LeUnes
& Burger, 2000; Terry, 1995a).
Research has shown that
all of the shortened versions
are highly
correlated
with the original 65-item
POMS.
The
Profile of Mood States and
Mental Health
Model
Bill
Morgan (1979) was one of the
first to utilize the Profile of
Mood States (POMS) in sport-
and
exercise-related
research. Morgan noted that
elite athletes exhibited a mood
profile that was lower
in
negative
moods and higher in vigor
than a normative sample, and
elite athletes also exhibited a
more
mentally
healthy mood profile than
less successful athletes.
Morgan referred to the notion that
the
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Sport
Psychology (PSY407)
successful
athletes exhibits a more healthy mood
profile than less successful
athletes or a normative
population
as the mental health model. According to this model,
the successful athlete is viewed as
a
mentally
healthy individual relative to psychological mood.
When the standardized POMS
scores of the
elite
athlete are plotted, they
take the form of an iceberg,
with all of the negative
moods falling below
the
population norm and the
vigor score falling well
above the norm. This mood
profile has come to
be
referred
to as the iceberg profile.
Research
has been very supportive of the
notion that the successful
athlete exhibits an iceberg
profile
relative
to the population norm (average
population). Terry and Lane
(2000), however, found strong
support
for the notion that the
athlete exhibits a mood profile
that is superior to that of the
population
norm.
Consistent with the mental health model,
athletes exhibit lower
negative mood states and
a
higher
vigor score compared to a
POMS normative sample of a
similar age group.
Research
and the Profile of Mood
States
Investigators
have been interested in studying the
relationship between precompetitive mood
and
athletic
performance. One approach has
been to determine if athletes
belonging to different
achievement
levels can be differentiated
based on mood state
measures. A second approach
has been to
determine
if performance outcome can be predicted
based on precompetitive mood. We will
take a
look
at both of these approaches
and also look at a
conceptual model for studying the
relationship
between
mood and performance.
Mood
States and Achievement Levels
In
this line of research, investigators
attempted to show that scores on the
POMS could discriminate
among
groups of athletes of different
skill levels. This is a
situation in which athletes of
clearly different
skill
level are given the POMS to see if the
scores of the different skilled groups
differ.
Beedie,
Terry, and Lane (2000)
reported the results of a meta-analysis
such studies and found the
effect
size
was just .10, which is
considered to be very low. So it is not
possible to consistently
differentiate
between
athletes of differing skill
level.
Mood
States and Performance
Outcome
In
this line of research, investigators
try to see whether the performance
outcome of athletes of a
similar
skill level can be predicted based on
POMS scores. If I know an
athlete's percompetitive mood
profile,
can I use it to predict how
she will do in the competition?
Results
of a second meta-analysis by Beedie,
Terry, and Lane (2000)
shows the overall effect size
for
this
investigation was .35, which is
considered to be small to medium. In
addition, two moderating
variables
were identified. A moderating variable is a variable
that determines the relationship
between
two
other variables. They two
moderating variables were types of sport
and how performance
was
measured.
Type
of Sport
Effects
were slightly larger for
individual sports compared to
team sports, and effects
were larger for
short-duration
sports (rowing, wrestling) compared to
long-duration sports (e.g.,
basketball, volleyball).
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Sport
Psychology (PSY407)
Measuring
of Performance
Effects
were larger when performance
outcome was conceptualized as
subjective and self-referenced,
as
opposed
to objective. An objective outcome would be whether
you won or lost a contest, or
whether
you
recorded a better time than another
athlete in a contest. Examples of
subjective self-referenced
outcomes
include
(a) post-event self-rating of performance, (b)
percentage of personal best,
and (c) comparison to
expectations.
A
stronger relationship exists between
mood and performance when
performance is measured subjectively
than
when
it is measured objectively. If you
are simply trying to predict whether an
athlete wins or loses a
contest or
finishes
higher than another runner in a race,
mood is a relatively weak predictor of
performance.
A
Conceptual Model for Predicting
Performance
Lane
and Terry (2000) proposed a
conceptual model for explaining the
relationship between percompetitive
mood
and performance. They proposed
that depression is a moderator between
other manifestations of
mood
and
athletic performance. High levels of
depression are associated
with increased anger, tension confusion,
and
fatigue,
but with reduced vigor.
The increased levels of
negative mood have a
debilitative effect upon
performance,
while reduced vigor has a
reduced facilitative effect upon
performance. In the absence of
depression,
vigor will have a
facilitative effect on performance, fatigue,
and confusion will have a
debilitative
effect
upon performance, and anger
and tension will have a
curvilinear effect upon performance.
Anger and
tension,
in the absence of depression, can
actually facilitate performance up to a
point.
The
Interactional Model
The
notion that the personality interacts
with situation to predict performance is
known as the interactional
model.
Information about personality plus
information about the environment
(situation) plus the interaction
between
the two is a better predictor of athlete
behavior than personality or the
situation alone.
Utilizing
the interactional model, sport psychologists have
been able to identify a
psychological profile for
the
elite
athlete. A successful world-class
athlete is low in the trait
measures of anxiety and neuroticism,
and high in
extraversion.
In terms of psychological mood
states, the world-class athlete is
low in anxiety tension,
depression,
anger,
fatigue confusion, but high in vigor. In
total, the psychological profile of the
successful world-class
athlete
is consistent with positive
mental health.
Psychological
Profile of the Elite Disabled
Athlete
In
recent years attention has
been devoted to describing the
psychological characteristics of the elite
disabled or
physically
challenged athlete. Interestingly, the
elite disabled athlete exhibits a
psychological profile that is
very
similar
to the profile of the elite able-bodied athlete
(Asken, 1991; Shephard, 1990).
Wheelchair athletes
are
higher
in self-esteem and physical
orientation than disabled
nonathletes (Roeder & Aufsesser,
1986)
In
addition, the iceberg profile of the
elite able-bodied athlete is readily observed in elite
disabled wheelchair
athlete
(Greenwood, Dzewaltowski and French,
1990; Henschen, Horvat &
French, 1984). As with the
elite
able-bodied
athlete, the physically challenged elite
athlete is generally mentally healthy
individual who
displays
low
levels of tension, depression, anger,
fatigue, and confusion. The iceberg
profile of the elite athlete has
also
been
observed in elite visually impaired male
athletes.
In
summary, the psychological and
mood profile of the elite disabled
athlete is very similar to that of the
elite
able-bodied
athlete.
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VU
Sport
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References
Cox,
H. Richard. (2002). Sport Psychology:
Concepts and Applications.
(Fifth Edition). New
York:
McGraw-Hill
Companies
Lavallec.
D., Kremer, J., Moran,
A., & Williams. M. (2004)
Sports Psychology: Contemporary
Themes.
New
York: Palgrave Macmillan
Publishers
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