The Effects of Perceived Performance on Mood States and Attribution in a Competitive Virtual Reality Environment


Elizabeth Anne Murphy



 

Abstract
Introduction
Methods
Results
Discussion
References
Tables
Appendices
Relevant Links

 

Abstract

The purpose of this study was to examine shifts of mood following the implementation of false feedback in a competitive virtual reality environment.  The study systematically replicated that of Turnbull & Wolfson (2002), which hypothesized participants engaging in a competitive cognitive task would exhibit increased positive mood states if they exercised during the task and subsequently given positive false feedback on their performance. Turnbull & Wolfson (2002) also predicted that if given negative feedback, the exercise group would react with more tension, depression, anger, fatigue, and confusion relative to the control group of non-exercisers.   Thus, it was predicted the current study would establish similar results when positive and negative false feedback is given to participants in a competitive virtual reality setting.  The study assessed differences in tension, depression, anger, fatigue, confusion and vigor utilizing pre and post-test POMS questionnaires.  Results indicated an overall change in POMS scores pre to post, yet only significant between-group differences in tension.  Further analysis suggested the positive feedback group (N=13) accounted for the most change, as depression, fatigue, and total mood disturbance decreased significantly while vigor increased.  Contrary to the hypothesis, the negative feedback group (N=10) only experienced a moderately significant decrease in fatigue following feedback.  In addition, it was predicted that because the administrator had control over participants effort and hertz output, competitive individuals would attribute their performance to unstable, external factors.  Results were marginally consistent with the hypothesis, as 10 participants strongly agreed they could have beaten the virtual competitor if the examiner did not make them control their workload.

Keywords:  mood, mood state, athlete, competitiveness, attributional style, athletic performance

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Introduction

    According to Smith, Nolen-Hoeksema, Frederickson & Loftus (2003), emotion is a complex, multicomponent episode that creates a readiness to act.  Emotions have been classified with six components, including cognitive appraisal, subjective experience of the emotion, thought and action tendencies, an autonomic nervous system response, facial expressions, and responses to emotions.  Proposed by Buck (1984), the General Model of Emotion states when one encounters stimuli that elicit an external affective stimulus, the external stimulus becomes internal if it encompasses significant meaning to the person.  The internal affective stimulus is comprised of relevant learning and primes.  In essence, the degree to which one will become aroused to an external stimulus greatly depends on the meaning of the stimulus to the individual.  Stimuli that evoke emotion in one person may not have the same emotional effect in another.  Therefore, in order to provoke emotion, one must interpret the stimulus as being either beneficial or harmful to his or her goals.  Responses to affective stimuli can also be conditioned. For example, one who has previously had a negative experience of high places may then experience a fear of heights or flying.
    Buck (1984) believed affective stimuli are filtered by relevant learning stimuli so as to determine both cognitive and emotional impact.  Adaptive and homeostatic mechanisms are activated, as well as spontaneous expressive tendencies and one’s subjective experience.  One’s subjective experience is in part determined by physiological responses such as feedback from visceral and skeletal muscle systems, the activation of neurochemical systems, and a variety of facial expressions.  Cognitively, one may then label his or her emotional state from past emotional experiences or the current situation itself.  Once the stimulus has been labeled, one can then elicit goal-directed behavior and derive coping methods to control negative feelings.  Self-reports may be utilized to describe subjective response.  Consequently, the labeled emotional state may become an internal affective stimulus itself, eliciting another cycle of emotional response, while spontaneous expressive tendencies may be influenced by display rules.  That is, the individual only responds in a way conducive to the situation instead of how he or she truly feels.
In contrast with emotion, moods are free-floating and diffuse affective states (Smith, Nolen-Hoeksema, Frederickson & Loftus, 2003).  While an emotion is typically brief, lasting a relatively short period of time, moods endure for longer time periods, and are often salient only at the level of subjective experience.  Emotions are often conceptualized as varying along discrete categories, such as happiness, fear, and anger. However, moods vary along dimensions of arousal and pleasantness (Smith, Nolen-Hoeksema, Frederickson & Loftus, 2003).
    In 1884, William James derived the notion that emotion is associated with coarse feelings that elicit physiological changes within the body, namely anger and fear (Pluchik, 1994).  Thus, emotion entails recognition of these changes, as the perception of bodily changes is the subjective experience of emotion.  This idea is called the “commonsense viewpoint.”  However, after rethinking his initial argument, James hypothesized one’s perception of a stimulus gives rise to the feeling of an emotion, leading to physiological changes.  Therefore, emotions follow one’s perception of a given situation.  “....we feel sorry because we cry, angry because we strike, afraid because we tremble...” (James, 1890).  Essentially, the subjective feeling of an emotion arises from the perception of situations that produce physiological changes  (Plutchik, 1994).
    Walter Cannon (1927) strongly criticized the James-Lange theory of emotion. His rationale was grounded in three main criticisms.  First, Cannon revisited Charles Sherrington’s experiment in which he cut the spinal cord of the vague nerves of dogs so that no sensory impulse could reach the brain from various organs.  Likewise, he also removed the sympathetic portions of the autonomic nervous system in cats.  Surprisingly, both sets of animals displayed emotional reactions such as anger, fear, and pleasure while interacting with other animals and being handled.  The James-Lange theory was contradicted, as there were no visceral changes in the animals.  Internal organs are not supplied with an abundance of nerves, so internal changes occur too slowly to inflict emotion (Plutchik, 1994).
Next, Cannon acknowledged the fact that stressful situations provoke the same kind of physiological response, such as increased heart rate, pupil dilation, and erection of body hair.  However, it is difficult to distinguish between strong emotions and nonemotional factors that create physiological arousal such as exercise (Plutchik, 1994).  In addition, two completely different emotions can elicit the same physiological response in that body.  For example, anger makes the heart beat faster, as does the sight of a loved one (Smith, Nolen-Hoeksema, Frederickson & Loftus, 2003).
Finally, Cannon recognized when injected with epinephrine, individuals experienced physiological bodily changes such as increased heart rate, tightness in chest and throat, trembling, chills, dry mouth, and weakness.  However, the implementation of adrenaline did not instill fear or any other emotion in participants.  At most, the injection produced “as if” emotions, such as “I feel as if I am angry.” Therefore, Cannon believed that visceral changes do not encompass a significant role in emotion (Plutchik, 1994).  Instead, the Cannon-Bard theory proposes one’s perception of a stimulus is first registered in the thalamus.  Thalamic discharge is then released into sub-cortical structures that activate the autonomic nervous system and the cortex, evaluating the incoming stimulus.  This theory also explains how the same physiological response can occur with more than one emotion.  Lastly, the Cannon-Bard theory suggests that one’s interpretations of physiological response of a stimulus can be influenced by cognitive interpretations, while both cognitive and physiological aspects can influence our emotions and how we experience them (Plutchik, 1994).
    In 1962, Schacter & Singer established monumental research concerning the effects of the environment on affective states.  The two-factor theory states emotions are the product of both an unexplained arousal plus a cognitive explanation for that arousal.  Thus, a study was conducted in which participants were induced to be in a state of autonomic arousal.  The investigators hypothesized these individuals would react in ways dependent on the situation in which they were placed.   In their study, Schachter & Singer (1962) divided participants into two groups.  The experimental group was given an injection of epinephrine, a substance that induces autonomic arousal, whereas the control group did not receive an injection.  While some of the participants in the experimental group were correctly informed about the consequences of the injection, others were given no such information on the drug’s effect.  It was predicted those participants uninformed of the drug effect would display emotions similar to the situational context.  For example, if a participant was left in the waiting room with a confederate appearing seemingly happy, it was predicted he would demonstrate similar emotions.  However, if the confederate appeared angry, it was predicted he would display anger as well.
    The results of Shachter & Singer’s (1962) study were complementary to their hypothesis.  Findings illustrated uninformed individuals injected with epinephrine rated their emotions more intensely compared to informed participants.  In addition, the participants who received a physiological explanation for their emotions were less influenced by the situation compared to the control group.  In essence, increased ratings of arousal for uninformed participants were due not simply from the drug alone, but from the context of the situation as well.
Schachter & Singer’s (1962) renowned study has led to a cascade of cognitive appraisal research in recent years, including attributional style.  Zillman & Bryant (1974) derived the misattribution of arousal theory, which states that lingering physiological arousal can be mistakenly attributed to subsequent circumstances, and intensify our emotional reactions to those circumstances.  For example, in Zillman & Bryant’s (1974) study, participants engaged in rigorous exercise, and were then provoked by a confederate.  Findings suggested participants who had engaged in prior physical activity responded to the provocation with more anger compared to those who had not exercised.  Therefore, when previous physiological arousal is paired with a provocation by a confederate, responses are typically more exaggerated and hostile.
    In Zillman’s (1974) study, participants misattributed their emotions, as they believed their anger was the result of simply the provocation, whereas previous physiological arousal from rigorous exercise led to increased anger.  This concept was later coined “excitation transfer,” in which residual arousal following exercise can be misattributed to a subsequent environmental stimulus, resulting in the intensification of mood (Zillman, 1974).  Therefore, when considering aspects of emotion, it is imperative to not only acknowledge physiological aspects and situational context, but also how an individual perceives the situation that elicited the emotion.  The Attributional theory suggests that individuals attempt to understand, explain, and predict events based upon their perceptions of the event (Cox, 2002).  Derived from the theories of Fritz Heider (1958) and Bernard Weiner (1972), attributional style is composed of both locus of control and stability.  In 1958, Heider formulated the notion that behavioral outcome was the result of personal force in conjunction with environmental force.  Later, Weiner (1972) constructed two main dimensions to describe achievement situations that he referred to as locus of control and stability (Cox, 2002).
    Weiner (1972) suggested one’s outcome was the product of either internal or external forces, along with stable or unstable attributes.  When individuals attribute an outcome internally, they recognize it is the product of their own actions.  Thus, when people attribute a situation internally, they essentially believe their behaviors and actions influence their outcomes.  Conversely, when people recognize the idea that outcomes are based solely on luck or chance, and that they have no input on the result, these individuals are said to exhibit external control (Weiner, 1972).  In other words, results are the product of the environment instead of the individual.  Along with locus of control, stability is the second factor Weiner (1972) developed to classify attributional style.  Unstable individuals, he believed, acknowledge the idea their performance is often fleeting, and if given another chance they may perform differently.  In contrast, individuals who demonstrate stable characteristics believe that outcomes are fixed, and will not change, despite effort (Weiner, 1972).
    In the athletic environment, Cox (2002) believes it is better to attribute causation as internal and unstable, as athletes should view themselves in control of the situation, regardless of the outcome.  In contrast with the less-motivated athlete, the highly competitive individual is more likely to attribute behaviors internally, as outcome is the result of one’s actions, not simply due to outside forces such as fate or luck (Cox, 2002).
    Unlike Cox (2002), Frederick (2000) discovered a high correlation between competitiveness and external locus of control.  53 men and 84 women completed a packet of surveys containing a measure of competitiveness, a locus of control scale, and a demographic questionnaire.  Thus, results suggested that rather than attributing outcomes to their own behavior, participants were more likely to attribute success or failure to external factors, such as chance, luck, or powerful other.  The study also found that men are more apt then women to score higher on competitiveness scales, making them more susceptible to negative attributional styles, such as decreased internal control (Frederick, 2000).
To expand upon the effects of disappointment on competitive performance, Davis & Zaichkowsky IV (1998) studied the explanatory styles of elite hockey players.  While David & Pargman (1990) utilized the Profile of Moods States questionnaire to evaluate the effects of disappointment in athletes after a competitive event, Davis & Zaichkowsky IV (1998) presented hypothetical yet realistic disappointments to hockey players, consequently distinguishing between “mentally tough” players with those who were not.  In contrast with Peterson & Seligman (1984), the study hypothesized those who exhibited a “mentally tough” attitude would have an optimistic explanatory style when speculating the cause of negative events.   Mental toughness was defined as displaying resistance to adverse situations and showing minimal performance decrements (Davis & Zaichkowsky IV, 1998).  Criteria for mental toughness includes adversity response, over-achievement, effort, enthusiasm, and skill.  However, Peterson & Seligman (1984) proposed those who exhibit an internal, stable, and global cause for negative events are at a greater risk for depression.  Surprisingly, results of this study suggested those who exhibited mental toughness were more inclined to demonstrate pessimistic explanatory styles compared to those who did not.  Therefore, the findings appear consistent with that of Peterson & Seligman (1984), although the athletes did not exhibit depressive symptoms.
    Zillman’s (1974) study of the misattribution of arousal, has greatly increased interest pertaining to the effects of deception in the athletic environment, along with how individuals account for their performance.  A vast amount of research has been performed in the past twelve years studying the effects of false feedback in the athletic environment. (e.g., Silva, Cornelius, & Finch, 1992; Taylor & Demick, 1994; Fitzsimmons, Landers, Thomas, & van der Mars, 1991; Turnbull & Wolfson, 2002).    First, in 1992, Silva, Cornelius, & Finch examined the effects of false feedback on psychological momentum.  Taylor & Demick (1994) defined psychological momentum as a positive or negative change in cognition, affect, physiology, and behavior caused by an event or series of events that will result in a commensurate shift in performance and competitive outcome.  Thus, Silva, Cornelius & Finch (1992) had 116 participants compete in a novel motor task, after which they were given false feedback on the outcome of the task.  Results suggested those given positive feedback acknowledged a high frequency of positive psychological momentum, while those who were given negative feedback reported a high frequency of negative psychological momentum.  More importantly, false feedback was implemented in research by Fitzsimmons, Landers, Thomas, & van der Mars (1991), in which they determined whether self-efficacy predicted performance in experienced weightlifters.  36 male weightlifters completed six performance sessions, comprised of a one-repetition-maximum bench press.  Prior to the competition, participants stated the amount of weight they were 100%, 75%, and 50% confident they could lift.   Feedback was given under three conditions: accurate performance feedback, false feedback that they lifted more then they actually did, and false feedback stating they lifted less than they actually did.  Results reaffirmed pre-existing research that when given false-positive feedback, participants increased their future bench press abilities.
   Likewise, an influential study by Turnbull & Wolfson (2002) determined whether participants experienced a shift of mood, or intensity of mood depending on the type of feedback they were administered following a competitive event.  It was hypothesized that participants given a cognitive task in conjunction with exercise would exhibit intensified elatedness if given positive feedback relative to those that had not exercised.  Conversely, when given negative feedback, it was predicted the exercisers would report more negative affective states than those who had not exercised during the course of the task.
    Turnbull and Wolfson’s (2002) study consisted of 26 female and 28 male undergraduate students.  After completing the POMS-BI questionnaire, each participant was given a 20-minute cognitive task.  Half the participants performed the task in conjunction with exercise on an aerobic step while half did not perform such physical activity.  Cognitive tasks similar to those found on the WAIS-R were utilized, namely the digit span scale.  Once the task was completed, participants rested for five minutes in order to decrease residual arousal and the chance for excitation transfer.   Results revealed that participants who exercised during the rehearsal of the cognitive task and then given positive feedback displayed higher mood scores compared to those who did not exercise.  Conversely, as predicted, those who exercised and given negative feedback experienced a significant mood decrease compared to those who did not.  Also, exercisers who received neutral feedback tended to sustain heightened mood compared to others.   Thus, participants who exercised reacted more intensely to either positive or negative feedback relative to the control group of non-exercisers.

Rationale
    Turnbull & Wolfson’s (2002) study was a variation of Zillman’s (1974) experiment, as the pairing of previous physiological arousal with false feedback elicits greater intensity of emotion compared to the normative sample.  Thus, Turnbull & Wolfson (2002) suggested the type of feedback given to an individual following periods of increased physiological arousal in a competitive environment elicit stronger reactions compared to those who did not exercise in conjunction with performing a competitive cognitive task.  In addition, those who received positive and neutral false feedback reported less negative affective states with increased vigor.  Conversely, those who were administered negative false feedback reported increased tension, depression, anger, fatigue, and confusion compared to those that did not exercise.  Therefore, emphasis is placed on whether false feedback would have the same effect on those who have just completed a race in a virtual reality environment.
    The current study was a systematic replication of the research conducted by Turnbull & Wolfson (2002).  It was predicted that if individuals were administered positive feedback following a competitive virtual race, they would experience decreased states of tension, depression, anger, fatigue, confusion, and total mood disturbance, with increased vigor.  Likewise, if given negative feedback it was predicted they would report decreased vigor and increased negative affective states.  Finally, it was also hypothesized participants’ perceived interpersonal competitiveness, determined by a 5 point Likert-type competitiveness questionnaire derived by Griffin-Pierson (1990), would correlate with how they attribute the outcome of the race in the virtual world.   That is, did they believe their performance on the track was under their control, or under that of the administrator?  If the administrator did not control their effort and hertz output throughout the course of the study would they still believe they could beat the competitor?  Since the administrator made participants keep their effort and hertz output within a certain range, the study predicted results similar to that of Frederick (2000), as competitive athletes will attribute the outcome of the race as external and unstable in the given situation, independent of their control.
 
 

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Methodology

Participants
    Eighteen student athletes (8 male, 15 female) from a small Catholic liberal arts college in New England were used in the current study.  More specifically, there were 6 seniors, 3 juniors, 10 sophomores, and 4 freshmen.  17 out of the 23 subjects reported participating in a varsity sport in the past year, while 14 and 16 reported engaging in intramural or other exercise activities, respectively.   Each subject participated in a one-hour monitoring session in the Virtual Reality laboratory at Saint Anselm College.  Participants were randomly assigned to receive either positive or negative feedback.  Each participant was protected under the APA code of ethics and was approved by the institution’s International Review Board.

Materials
    The Profile of Mood States (McNair, Lorr & Droppelman, 1971) is a 65 item, Likert-type questionnaire ranging from not at all to extremely.  Subscales of the POMS include depression, anger, tension, fatigue, vigor, confusion, and total mood disturbance.   The internal consistency of the POMS ranges from .84 to .95 while test-retest reliability coefficients range from .65 to .74 (Hansen, Stevens & Coast, 2001).
The Competitiveness Questionnaire, derived by Griffin-Pierson (1990) measures both interpersonal and goal competitiveness.  For the purpose of the current study, only the interpersonal competitiveness scale was utilized as participants competed against a virtual runner.  The reliability of the interpersonal competitiveness scale was .76, while the validity was .62.

Apparatus
    In order to obtain an accurate reading of heart rate, a Polarâ Heart Rate Monitor was utilized in the current study.  Model A-1 allows users to track heart rate and workout time continuously.  It also provides users with their average heart rate at the end of their workout session.
    The Vivometrics Lifeshirtâ was implemented to record physiological responses, such as respiration during the course of the study.  The Lifeshirtâ allowed investigators to pinpoint physiological responses at a given point during the study, such as when a competitor came into view.  A useful tool, the Lifeshirtâ combined with Vivologicâ software was used in an ongoing study at Saint Anselm College pertaining to arousal.
    The Scifitâ elliptical trainer was combined with the 5DT head mounted display in order to simulate a real word environment.  The SXT7000 elliptical machine was purchased May 6, 2003 from Precision Fitness Equipment in Natick, Massachusetts.  The machine allows users to monitor their heart rate while shifting between 5 and 2000 watts of  resistance.  The use of bi-directional resistance allows for reverse walking, along with isokinetic resistance, ensuring the user does not go beyond a certain RPM during advanced workouts.  Handrails may also be used to ensure proper body positioning and comfort while on the machine.  There is no minimum RPM as it is beneficial for rehabilitated patients and deconditioned users.
    The 5DT head-mounted display 800 system allows users to configure their own immersion environment while providing high resolution (800x600x3 pixels-Full SVGA)
 and superior sound quality.  The 5DT HMD 800 includes adjustable top/back ratchets, a mounting base for head trackers, and a flip-up mode for reality checks.  The optical field of view is approximately 28 inches in height x 21 degrees.  The frequency response is 16Hz-22Hz (3dB), while the sound pressure level is 120dB (1KHz).
    Finally, a Dellâ computer system equipped with 1024 MB, a Quadro4XGL 64MB video card, and a 16x DVD ROM drive was utilized to project the DVD of the virtual runner onto the 5DT head-mounted display.  The computer system was purchased in April, 2002 from 5DT, Inc.

Procedure
    Initially, subjects entered the virtual reality laboratory and filled out a consent agreement as well as an informational form of one’s medical history.  The experimenter administered a demographic questionnaire, the Profile of Mood States, and Griffin-Pierson’s (1990) competitiveness questionnaire to participants.  The Polarâ Heart Rate monitor (Model A-1) was utilized to derive 60-70% of their max heart rate.  The participants were fitted to the Vivometrics Lifeshirt®, measuring physiological responses such as heart rate and respiration.  They were then calibrated to the Lifeshirt® using a breathing calibration bag and nose clip, and were asked to take seven breaths in rapid succession while both sitting and standing.
    The Scifit®  SXT7000 elliptical trainer in conjunction with the 5DT 800 head-mounted display was implemented to simulate a real-world environment.  Participants  warmed up for ten minutes on the elliptical until they reached 60-70% of their max heart rate, and continued to practice their standard hertz output at this rate for four minutes.  When their heart rate reached 60-70% max, the screen on the head-mounted display was turned on, displaying a virtual track at a local high school.  Participants were notified that if their workload was modified from 65-70% max heart rate, a competitor would appear on the 1600-meter track (mild deception).  If a competitor was to appear, they were given strict instruction not to increase their wattage and workload.  Since some people may become dizzy in the midst of a virtual environment, participants were told to notify the investigator if that should occur, and the study would be terminated for that participant.
    Once participants completed 1600 meters on the virtual track, a preprogrammed athlete appeared within competitive view.  Both before and after the athlete appeared within view, participants were given questions regarding comfort, anxiety, and effort, which were then recorded on the Lifeshirtâ diary.  The competitor remained approximately 400 yards in front of the participant regardless of workload, then dropped back and moved ahead once again.  A track coach remained stationed at the finish line (visible during the final 100 meters) indicating laps remaining.  Once completed, there was a four-minute cool-down period.  During the cool-down, the investigator pretended to print out the results of the race, and went into an adjacent room to obtain them.  Whether the participant beat the competitor or was defeated was determined by a flip of a coin prior to the study.  In order to have an even number of participants in each group, the coin was flipped and then yoked for the next subject.  False feedback was given, as participants either beat the virtual reality runner by 0:06 seconds or lost to the VR runner by the aforementioned time.
    Once the printout was received by the subject, the investigator presented the Profile of Mood States once again in order  to determine whether they displayed a shift in mood or intensity of mood following the administration false information. They were also interviewed regarding reactions to being passed, how they viewed the competitor and situation, and if they experienced anxiety while being passed or if it had little effect on them.  Finally, participants were given a debriefing form and a request to follow up if necessary.
 
 

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Results

    The dependent variables in this study included tension, depression, anger, fatigue, confusion, vigor, and total mood disturbance.  A paired-samples t-test was implemented to determine whether there was an overall change in the dependent measures based on the type of feedback administered to participants.  The test suggested an overall marginal significance for tension, while vigor, depression, fatigue, confusion, and total mood disturbance all revealed overall significant interactions.  Please refer to Table 1 for the mean scores.
    An independent-samples t-test was utilized to analyze differences in positive and negative feedback groups.  Results suggest significance in tension scores, t(21)=2.34, p=.029, while the other dependent measures (i.e.depression, anger, fatigue, confusion, vigor, tmd) did not display significant changes.  Please see Table 2.
    In order to account for the directionality and strength for the overall change in pre to post subscale scores, a paired-samples t-test was implemented.  Results of the test suggest the positive feedback group experienced the greatest amount of mood state change throughout the course of the study.  In essence, scores in depression, fatigue, and total mood disturbance decreased significantly, while vigor increased as predicted.  Please refer to Table 3.
    Finally, an independent-samples t-test was conducted between groups based on participants’ level of competitiveness and locus of control.  Results indicated a  marginally significant difference between highly interpersonal competitive individuals and external locus of control, based on their perceived performance in the virtual environment, t(14)= -1.819, p=.090.  Another independent-samples t-test was conducted to measure level of competitiveness and locus of control in real-life competitive environments, t(18)= -2.511, p= .022.  In this instance, results illustrated that in real-life competition, participants generally perceived their performance to be highly internal, under their control instead of under the influence of an external force.
 
 

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Discussion

    The current investigation attempted to systematically replicate Turnbull & Wolfson’s (2002) study and to illustrate similar results when immersed in a competitive virtual reality environment.  It was predicted that two feedback groups would display different POMS subscale scores following a competitive VR race.  More specifically, it was predicted individuals in the positive feedback group would report less intense negative affective states, namely tension, depression, anger, fatigue, and confusion.  The reduction of negative POMS subscale scores would thus decrease total mood disturbance in these individuals.  In contrast, individuals who received negative feedback were predicted to report decreased vigor, along with increased tension, depression, anger, fatigue, and confusion, promoting a higher total mood disturbance score.   Results were not consistent with the hypothesis, as there were no significant changes pre to post with the implementation of negative feedback.  Instead, there was only marginal significance for fatigue subscale scores; however, not in the predicted direction.  After the competitive event, individuals in the negative feedback group reported less fatigue compared to their initial pretest.  Thus, the hypothesis was supported in the positive feedback group, but not for the negative.
    With positive and negative groups combined, there was an overall change pretest to posttest.  The change was accounted for by the positive feedback group, as depression, anger, and total mood disturbance significantly decreased while vigor increased.  These results are consistent with Turnbull & Wolfson’s (2002) study as participants who were given positive false feedback generally reported increased vigor subscale scores along with decreased negative affective subscale scores.  Along with Turnbull & Wolfson (2002), other studies have demonstrated how exercise can have a significant positive impact on mood states.  For example,   Steptoe, Kimball & Basford (1998) studied the effects of exercise on the experiences and appraisal of daily stressors.  In their study, investigators administered diaries of exercise, mood, and the experience of daily stressors to 38 men and 34 women over a period twelve consecutive days.  Findings showed participants reported positive moods more frequently along with decreased depression on days they exercised compared with non-exercise days.  Also, results gathered from the State-Trait Anxiety Scale illustrated that individuals low in trait anxiety reported fewer stressful events on the days they exercised compared with days they did not exercise.
 Lichtman & Poser’s (1983) investigation is another study that displayed the beneficial aspects of exercise on mood states.  In their study, researchers administered the Nowlis Mood Scale, the Profile of Mood States and the Stroop Color-Word test to 64 participants aged between 16 and 54 years.  Participants were randomly assigned to either vigorous exercise or a hobby class.  In essence, those who engaged in the vigorous exercise activity reported less fatigue and depression, along with increased elatedness compared to the non-exercise, hobby group.  This study supported the notion that physical activity is related to incremental positive changes in mood states.
    Combining the positive and negative feedback groups in order to illustrate average individual subscale scores showed that between groups, only tension decreased significantly.  The reason for the significant decreases in tension is not clear, however, apprehension concerning the instrumentation and procedure of the study may have contributed to initial uneasiness that decreased throughout the course of the study.
    As predicted, there was evidence for a decrease in negative affective states with increased vigor in the positive feedback group.  There are many possibilities as to why this may have occurred.  From a physiological standpoint, there is a possibility exercise increases endorphin and serotonin synthesis and metabolism (e.g., Yeung, 1996; Chaouloff, 1997; Wiley, 2000).  More specifically, physical activity increases the entry of tryptophan, the precursor to 5-HT synthesis, into the brain (Chaouloff, 1997).  It can also be argued that for the competitive athlete, a win promotes increased vigor, along with decreased negative affective states, as shown by the “iceberg profile.”  Proposed by Morgan (1979), the profile argues competitive athletes exhibit a mood profile that is lower in negative moods and higher in vigor scores compared to the normative psychological sample.
Since 1979, many studies have been conducted to test the validity of the iceberg profile in competitive athletes.  Fuchs & Zaichkowsky (1983) investigated whether the iceberg profile was relevant to male and female bodybuilders.  31 competitive bodybuilders were given both the Profile of Mood States along with the Eysenck Personality Inventory to determine whether their mood characteristics resembled Morgan’s (1979) profile.  In essence, results indicated that both male and female bodybuilders had a similar iceberg profile compared with competitive runners, wrestlers, and oarsmen.  Also, Gat & McWhirter (1998) examined competitive and recreational cyclists vs. non-athletes in terms of their mood profile.  Surprisingly, both the competitive and recreational cyclist exhibited mood profiles similar to Morgan’s (1979) iceberg profile.  Therefore, there is a possibility that regardless of the feedback administered and the relative competitiveness of the athlete, athletes will exhibit a more positive mood compared to non-athletes.  Finally, another reason for the overall decrease in negative affective states is that participants may have simply been happy to complete the study and receive course credit.
    Along with depression, fatigue decreased significantly in the positive feedback group.  This appears viable, as vigor increased significantly for that particular group as well.  Again, this may be due to the nature of the competitive athlete.  Another possibility relates to studies performed with chronic fatigue patients, in which moderate exercise is a valid treatment option.  Freidberg (2002) conducted a case study on a 52-yr-old man suffering from chronic fatigue syndrome, and found the implementation of a 26-step graded activity program increase walk time from 0 to 155 minutes a week.  Follow-up assessments revealed a heightened global mood rating and substantial increases in walk time.  Therefore, evidence exists that exercise may reduce fatigue rather than exacerbate it.
 Vigor and total mood disturbance significantly increased in the positive feedback group, thus supporting the hypothesis.  Reasons for the increase are most likely due to the type of feedback administered and the effect of exercise as previously stated.   Tension, anger, and confusion did not result in significant changes pre to post, for reasons that are unclear.  Possible explanations include the small sample size of the group and a lack of threat posed by the virtual runner, to be discussed later.
    Another possibility pertains to Lane & Terry’s (2000) conceptual model, which explains the relationship between precompetitive mood and performance.  Lane & Terry (2000) believed that in the absence of depression, tension and anger have a curvilinear effect on performance.  Because there was a significant decrease in depression yet no significant changes in tension or anger during the course of the study, possibilities exist that if the participants were optimally aroused, their performance may have actually been facilitated by the presence of tension and anger.  Still, there is no evidence that the feedback administered should not have a significant effect on tension, anger, or confusion.
 Unlike the positive feedback group, the negative group showed only marginal decreases in fatigue.  Although there were decreases in negative affective states and an increase in vigor, the results for these subscales were not significant.  Thus, the hypothesis was not supported for the negative feedback group.  Because there were only ten participants in this group, a strong possibility exists the sample size was not large enough, as a group of ten participants cannot easily represent a given population.  Because many of the participants were selected from the same sports psychology class and appeared at different dates and times, it is possible there was a violation of confidentiality, despite debriefing.
    Another possibility for the lack of significance in the negative feedback group pertains to the legitimacy of the virtual competition.  That is, there were concerns as to whether participants believed their performance against the VR competitor was actually monitored and recorded by the computer.  Testimonial evidence at the time of debriefing confirmed that some participants knew the print out of their results did not apply to their overall performance on the track.  In some cases, the virtual runner on the track appeared too slow and out of breath, prompting participants to believe they were in better shape than the virtual runner.  Although it was not consistent with anger subscale scores, verbal evidence of frustration arose when the seemingly exhausted virtual runner beat certain participants.  Nevertheless, there was not enough change pre to post to make anger increase significantly for the negative feedback group.
    Finally, the hypothesis that highly competitive individuals would exhibit characteristics of an unstable attributional style and external locus of control, exhibited by Frederick (2000) was marginally significant.  Therefore, the hypothesis was supported, as 10 participants strongly agreed and 6 participants agreed their performance was not under their control, and instead was influenced by the administrator.  They generally believed that if the administrator did not have them control their workload, they could have beaten the virtual runner.  However, consistent with Cox (2002), in real-life competitive situations, participants demonstrated an internal locus of control, as they strongly believed themselves to be in control of their performance and success.  Because of these differences, the participants in the current study exhibited an unstable attributional style, recognizing their performance has the ability to change given the context of the situation.  Therefore, it is possible participants in the negative feedback group did not report significant decreases in negative affective states because they believed their performance was totally controlled by the administrator, and not due to their own effort and abilities.
    There are many ways in which this study could have been improved.  First, the sample size should have been greater, as 23 of participants cannot easily represent a population.  Since there was no significance in the negative feedback group, better results may have been obtained if there were thirteen participants instead of only ten, making the groups even in number.   Also, the study may have been more believable if participants were matched with a virtual runner based on their running experience and capabilities.  Based on the level of exertion the virtual runner exhibited, negative feedback did not seem valid to some participants.  Therefore, at least four other films (two male and two female) should have been utilized for novice, intermediate, and advanced runners.  Finally, since virtual environments may provoke sickness, nausea and dizziness were a problem for at least four people in the study.  Despite the fact some are predisposed to motion sickness, there is a possibility it could have been alleviated given more suitable technology.  For instance, the video recorder was attached to a confederate’s head as she rode a bicycle around the track.  Thus, the recording was not steady, as the picture bounced up and down and side to side.  Therefore, a computer program with a simulated track may not induce as much dizziness, however costly.
    The current investigation was a part of a larger ongoing experiment investigating physiological arousal when a competitor comes into view.   Since some participants became dizzy and ill during the course of the study, future research may focus upon characteristics of individuals who have a tendency to suffer from motion sickness compared to those who do not.  It would also be interesting to compare adults to children to determine whether there is an age difference in how individuals rate their mood after a competitive event.
 
 

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References

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Chaouloff, F. (1997).  Effects of Acute Physical Exercise on Central Serotonergic Systems.  Medicine & Science in
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Cox, R. (2002).  Sports Psychology Concepts and Applications.  New York, NY: McGraw-Hill.

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Davis, K. & Pargman, D.  Emotional Responses Following a Disappointing Competitive Sport in High Level Athletes.
     Journal of Applied Sport Psychology.

Frederick, C. (2000).  Competitiveness: Relations with GPA, Locus of Control, Sex, and Athletic Status.  Journal of
     Perceptual and Motor Skills.  Vol. 90.

Friedberg, F. (2002).  Does Graded Activity Increase Activity?  A Case Study of chronic Fatigue Syndrome. Journal of
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Fuchs, C. & Zaichkowsky, L. (1983).  Psychological Characteristics of Male and Female Bodybuilders: The Iceberg
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Gat, I. & McWhirter, B. (1998).  Personality Characteristics of Competitive and Recreational Cyclists.  Journal of Sport
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Griffin-Pierson, S. (1990).  The Competitiveness Questionnaire: A Measure of two Components of Competitiveness.
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Hale, B. (1993).  Explanatory Style as a Predictor of Academic and Athletic Achievement in College Athletes. Journal of
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Hansen, C.,  Stevens, L., & Coast, J. (2001).  Exercise Duration and Mood State: How Much is Enough to Feel Better?
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Heider, F. (1944).  Social Perception and Phenomenal Causality.  Psychological Review.  Vol. 51.

Lichtman, S. & Poser, E. (1983).  The Effects of Exercise on Mood and Cognitive Functioning.  Journal of
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McNair, D., Lorr, M. & Droppelman, L. (1971).  Manual for the Profile of Moods States.  San Diego: Education and
     Industrial Testing Service.

Peterson, C. & Seligman, M. (1984).  Causal Explanations as a Risk Factor for Depression:  Theory and Evidence.
     Psychological Review.  Vol. 91, Issue 3.

Plutchik, R. (1994).  The Psychology and Biology of Emotion.  New York, NY : Harper Collins College Publishers.

Schacter, S. & Singer, J. (1962).  Cognitive, Social, and Physiological Determinants of Emotional State.  Psychological
    Review.  Vol. 69.

Smith, E.,  Nolen-Hoeksema, S.,  Frederickson, B.,  & Loftus, G. (2003)  Atkinson & Hilgard’s Introduction to
    Psychology.  Belmont, CA: Wadsworth/Thomson Publishing.

Steptoe, A., Kimball, J, & Basford, P. (1998).  Exercise and the Experience and Appraisal of Daily Stressors: A
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Taylor, J. & Demick, A. (1994).  A Multidimensional Model of Momentum in Sports.  Journal of Applied Sports
     Psychology. Vol. 6.

Turnbull, M. & Wolfson, S. (2002).  Effects of Exercise and Outcome Feedback on Mood: Evidence for Missattribution.
     Journal of Sport Behavior.  Vol. 25, Issue 4.

Weiner, B. (1972).  Theories of Motivation: From Mechanism to Cognition.  Chicago: Rand McNally Publishers.

Yeung, R. (1996).  The Acute Effects of Exercise on Mood State.  Journal of Psychosomatic Research.  Vol. 40, Issue 2.

Zillman, D. & Bryant, J.  Effect of Residual Excitation on the Emotional Response to Provocation and Delayed
     Aggressive Behavior. Journal of Personality and Social Psychology.  Vol. 30.
 
 

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Tables

Table 1
_____________________________________________________
                        Pre              Post                        t                      p
Tension            6.43              4.96                   1.79                 .088
Depression       4.13              1.61                   2.83                 .010**
Anger               3.04              2.35                   0.65                 .521
Fatigue             7.26              3.70                   3.72                 .001**
Confusion        5.17               3.78                   2.08                 .050*
Vigor             13.78             16.09                 -1.90                 .070
TMD             12.26               0.04                  3.73                  .001**
_____________________________________________________
Note *p  .05  **p .01

Table 1 represents overall means for POMS scores pre to post and displays significant overall differences in depression, fatigue, confusion, and total mood disturbance.
 

Table 2
 __________________________________________________________________
                      Positive Feedback           Negative Feedback           t                 p

POMS
Post Score
Tension              6.08(2.8)                          3.50(2.4)                   2.39           .027*
Depression         1.77(3.0)                          1.40(1.9)                     .36           .723
Anger                 2.23(2.2)                          2.50(4.7)                   -.168         .87
Fatigue               3.62(4.0)                          3.80(3.0)                   -.127         .900
Confusion           3.69(2.1)                          3.90(3.1)                   -.181         .859
Vigor                17.00(4.9)                        14.90(6.4)                    .858         .403
TMD                    .31(11.7)                        -.30(11.4)                   .125         .952
___________________________________________________________________
Note *p .05

Table 2 represents between-group POMS means for the positive and negative feedback groups, with tension as significant.
 

Table 3
_____________________________________________
Group               Pre           Post            t             p
Positive
Tension            7.62          6.08         1.126       .282
Depression       4.69          1.77         2.526       .027*
Anger               3.62          2.23         1.091       .297
Fatigue             8.00          3.62         3.167       .008**
Confusion         4.62          3.69         1.171       .264
Vigor              13.46        17.00       -2.684       .020*
TMD              15.08           .31          3.448       .005**

Negative
Tension            4.90          3.50         1.801       .105
Depression       3.40          1.40         1.384       .200
Anger               2.30          2.50         -.108       .916
Fatigue             6.30          3.80         1.959       .082
Confusion         5.90          3.90         1.704       .123
Vigor              14.20       14.90          -.322       .754
TMD                8.60          -.30         1.741       .116
_____________________________________________
Note *p .05 **p .01

Table 3 represents mean subscale scores pre to post in both the positive and negative feedback groups.  Notice the positive feedback group accounted for the most change pre to post, as depression, fatigue, and total mood disturbance significantly decreased as vigor significantly increased.
 
 

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Appendices

Appendix A

                                                                                                            Identification #_____
 
 

Consent to Participate

This study investigates the relationship of mood to physiological functioning (heart rate, respiratory functioning, and skin conductance) within the context of the activity of running in a virtual environment. You may discontinue participation at any time during this study. In this study you will complete demographic information, questionnaires related to mood and exercise, and participate in a run in a virtual environment.  Some subjects may be invited to participate in an additional study that will investigate the ability to manage the relationship of mood to activity in the virtual environment.
Your completion of this study is fully voluntary. Participation in this study is not mandatory.  Should you decide not to participate at any time, please let your evaluator know and the procedure will be discontinued.  As part of participation in this study, we will videotape the activity component for analysis.  Once analyses are completed the video will be erased. Please initial here to indicate consent to videotape you during the activity component of this study.
(  ) yes videotape (  ) no don’t videotape  Initial here _____.If you have questions about this study, please feel free to speak to the researcher. After reading this description/ informed consent form, I (sign here) _________________________________agree to participate in this study. Date  ___/___/___.  Please print your name________________________________    Date of Birth: ____/____/____
I am at least 18 years old and am my own legal guardian  ___yes        no
Please print your name______________________________
Again, should you have any questions about this study or would like to learn more about this area of research, please contact
 Paul Finn, PhD                                                                                       Kathy FlanneryPaul Finn, PhD                                                                                                        Kathy Flannery, PhD
Department of Psychology                                                                       Department of Psychology
Saint Anselm College                                                                               Saint Anselm College
(603) 641-7131                                                                                      (603) 641-7254
Paulfinn@anselm.edu                                                                               Kflanner@anselm.edu
 
 
 
 

Appendix B

                                                                                                    Id _____

Demographic Questionnaire





Age: _______  Date of Birth: ___/___/______ Sex: (   ) male (    ) female

Year: (    ) Freshman   (    ) Sophomore   (    ) Junior   (    ) Senior

G.P.A. (Freshmen leave blank): _______    Major:___________________
 

During this past year did you/are you  participating in a sport as a student athlete? _______

If so, which sport(s)? ________________________________

During this past year did you/are you participating in an intramural sport? ________

If so, which sport(s)? ________________________________

During this past year did you/are you participating in exercise activities on your own? ___

If so, which activities(s)? ________________________________

During the last 3 months on average, how many times a week did you run? _______On average, how long (time) for each
run?_________  How many miles did you typically run each time? _______

During the last week, how many times did you run? _______ On average, how long (time) for each run?_________  How many miles did you typically run each time? _______

How many times a week do you ride a bike?  ________   Swim? ______ Other aerobic activity_______ (please specify)? ____________________________________

Did you work out today ()yes  ()no  If yes, what did you do_________how long______
What intensity (rate from 0=none 4=highest _____

Do you smoke cigarettes?   (   ) yes    (    ) no

Have you consumed alcoholic beverage(s) in today?   (   ) yes   (    ) no if yes, what type____________ about how many ounces__________

Have you consumed alcoholic beverage(s) in the last 24 hours?   (   ) yes   (    ) no if yes, what type____________ about how many ounces__________

Have you consumed acaffeinated beverage(s) in today?   (   ) yes   (    ) no if yes, what type____________ about how many ounces__________

Have you consumed caffeinated beverage(s) in the last 24 hours?   (   ) yes   (   ) no if yes, what type____________ about how many ounces__________

Are you currently taking prescriptive medications (today)?    (    )  yes      (    ) no
If so, what type? ___________________________________________

Do you take over the counter medications (today)?   (    ) yes    (    ) no
If so, specify type __________________________________

Has a health care provider placed you on exercise restrictions that could limit your participation in this study?  ()yes   ()no   If you are not sure, please ask.

Current height ______   Current weight ______
 
 
 

Appendix C

Strongly Disagree    1 2 3 4 5     Strongly Agree
 

1. I would want to get first place because that is the best place a runner can get.

                                               1     2     3     4     5

2. I perform better when I am competing against someone rather than when I am the only one striving for a goal.

                                               1     2     3     4     5

3. I do not care to be the best that I can be.

                                               1     2     3     4     5

4. If I receive a sports reward it is because I did well, and not because others weren’t as good as me.

                                               1     2     3     4     5

5. I do not feel that winning is important in both practice and competition.

                                               1     2     3     4     5

6. When I win an award or race it means that I am the best compared to everyone else that was running. It is only fair that the best person win the race.

                                               1     2     3     4     5

7. I always like to be the first one to finish a workout.

                                               1     2     3     4     5

8. I am not disappointed if I do not reach a goal that I have set for myself.

                                               1     2     3     4     5

9. I have always wanted to be better than others.

                                               1     2     3     4     5

10. Achieving excellence is not important to me.

                                               1     2     3     4     5
11. If I win an award it is because I did better than everyone else.

                                               1     2     3     4     5

12. I would want to win a race because that means I did better than other people.

                                               1     2     3     4     5

13. I would rather play a sport I could excel at than one which was more fun but I was average at.

                                               1     2     3     4     5

14. Because it is important that a winner be decided, I do not like to leave a race unfinished.

                                               1     2     3     4     5

15. I would rather run a difficult course and excel than run an easier course and excel.

                                               1     2     3     4     5
 
 
 

Appendix D

                                                                                        ID#_______

Post Eliptical/VR Interview

How competitive did you feel during the run you just completed
 Not at all competitive  1      2     3     4     5   very highly competitive

I would rather compete in a difficult event and win than win and excel in an event that is easier
  Strongly Disagree   1     2     3     4     5   Strongly Agree

My competitive performance and success in competition is mostly under my control
  Strongly Disagree   1     2     3     4     5   Strongly Agree

When running in an event at goal pace, if during the middle of the race  I come upon a competitor, the presence of the competitor would:
have no effect on me               1     2     3     4     5
motivate me to push harder     1     2     3     4     5
discourage  me – slow down   1     2     3     4     5

When running in an event at goal pace, if during the middle of the race  a competitor passes me, the presence of the competitor would:
have no effect on me               1      2    3     4     5
motivate me to push harder     1      2    3     4     5
discourage  me – slow down   1      2    3     4     5
 

During the study I just completed – The main goal of this study was to
_______________________________________________________

      _______________________________________________________

The level of workout intensity during this exercise was (please rate from 0=none to 4=highest)_______

If the examiner did not have me voluntarily control my level of activity by having me control my work load I could have passed the competitor when first seen on the track (circle one)
    Strongly Disagree   1 2 3 4 5   Strongly Agree
Why or why not? _______________________________

If the examiner did not have me voluntarily control my level of activity by having me control my work load I could have passed the competitor when first seen on the track (circle one)
    Strongly Disagree   1 2 3 4 5   Strongly Agree
Why or why not? _______________________________
 
 
 

Appendix E

                                                                                            Identification #_____

Debriefing Participants

    Thank you for your participation in the current study.  This study investigated competitive anxiety in sport for both goal oriented and competitive runners.  Measures of goal orientation and competitiveness were given in order to place participants into groups.  While running on the elliptical machine in the virtual reality dome, eye movement and bodily functions, such as heart rate, respiratory rate and skin conductance, were measured to determine how the bodies of competitive and goal oriented athletes react to being passed by a competitor. The competitor passing you was not another subject in the study, this was videotaped to happen at a predetermined time, completely independent of you.  The information acquired will be held confidential.  Individual results will not be available to you; however, group results of the research will be accessible to you as participants.
    Also, if you participated in the second component of this study, you received a “Mental Trainng Package” that was used to assess ability to reduce arousal among those participants who report sympathetic arousal as impeding competitive performance
    Please sign the debriefing form to indicate your knowledge and understanding of this study.  Should you have any further questions, please do not hesitate to contact me.
Today’s Date:  ___/___/___   Signature ____________________
Witness:     Signature ____________________
Today’s Date: ___/___/___
 Again, should you have any questions about this study or would like to learn more about this area of research, please contact

Paul Finn, PhD                                                                                                   Kathy Flannery

Paul Finn, PhD                                                                                                   Kathy Flannery, PhD
Department of Psychology                                                                                  Department of Psychology
Saint Anselm College                                                                                          Saint Anselm College
(603) 641-7131                                                                                                 (603) 641-7254
Paulfinn@anselm.edu                                                                                          Kflanner@anselm.edu
 
 

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