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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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Sport Psychology (PSY407)
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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