Overview
People have different ways of improving their mood when angry. We have all seen people punch a wall when mad, and indeed, previous research has indicated that some people aggress to improve their mood (Bushman, Baumeister & Phillips, 2001). What do the top athletes do when angry? Striegel (1994) found that anger often hurts an athlete’s performance and that capability to control anger is what makes good athletes even better. This study adds to the past research and examines the difference in ways to improve an angry mood by gender and sports participation.
The participants were 78 Rice University undergraduates, ages 17 to 23. Of these 78 participants, 48 were females and 30 were males and 25 were athletes and 53 were non-athletes. People who did not play a varsity or club sport were considered non-athletes. The 13 contact sport athletes played soccer, football, rugby, or basketball, and the 12 non-contact sport athletes participated in Ultimate Frisbee, baseball, tennis, swimming, volleyball, crew, or dance.

The participants were asked to respond to a questionnaire that asked about what they do to improve their mood when angry or furious. Then they filled out a demographics questionnaire.

Note: This study used the most recent version of the State-Trait Anger Expression Inventory (STAXI-2) (Spielberger, Sydeman, Owen & Marsh, 1999) which was modified to create an Angry Mood Improvement Inventory similar to that created by Bushman et al. (2001).
Questions to Answer
Do athletes and non-athletes deal with anger in the same way? Are there any gender differences? Specifically, are men more likely to believe that aggressive behavior can improve an angry mood?

Design Issues
This study has an extremely unbalanced design. There were a lot more non-athletes than athletes in the sample. In the future, more athletes should be used. This study originally wanted to look at contact and non-contact athletes separately, but there were not enough participants to do this. Future studies could look at this. Case Study: Angry Moods

Descriptions of Variables

Variable Description
Sports 1 = athletes, 2 = non-athletes
Gender 1 = males, 2 = females
Anger-Out (AO) high scores demonstrate that people deal with anger by expressing it in a verbally or physically aggressive fashion
Anger-In
(AI) high scores demonstrate that people experience anger but do not express it (suppress their anger)
Control-Out (CO) high scores demonstrate that people control the outward expression of angry feelings
Control-In (CI) high scores demonstrate that people control angry feelings by calming down or cooling off
Expression (AE) index of general anger expression:
(Anger-Out) + (Anger-In) – (Control-Out) – (Control-In) + 48
Note: Description of the items comes from Spielberger et al. (1999).
References
Bushman, B.J., Baumeister, R.F. & Phillips, C.M. (2001). Do people aggress to improve their mood? Catharsis beliefs, affect regulation opportunity, and aggressive responding. Journal of Personality and Social Psychology, 81(1), 17-32.
Spielberger, C. D., Sydeman, S. J., Owen, A. E., Marsh, B. J. (1999). Measuring anxiety and anger with the State-Trait Anxiety Inventory (STAI) and the State-Trait Anger Expression Inventory (STAXI). In M. E. Maruish (Ed.), The use of psychological testing for treatment planning and outcomes assessment (2nd ed., pp. 993-1021). Mahwah: Lawrence Erlbaum Associates.
Striegel, D. (1994). Anger in tennis: Part 2. Effects of anger on performance, coping with anger, and using anger to one’s benefit. Journal of Performance Psychology, 2, 56-92. Case Study: Angry Moods

MORE INFO 

What is the correlation between the Control-In and Control-Out scores?

Introduction

We conducted a statistical analysis to measure the correlation between the Control-In and Control-Out scores. Our hypothesis is that a student who is motivated at the day’s beginning will be motivated throughout the day.

Our hypothesis is that a student who is motivated at the day’s beginning will be motivated throughout the day.

The Control-In and Control-Out scores are a measure of how motivated a student is. They can be used as an indicator of how well you’re doing with your academics, whether or not your grades are up to par and even if you have trouble sleeping at night. When it comes to motivation, there is some debate about whether or not it’s internal or external in nature. Internal refers to something that happens inside yourself, whereas external means something happening outside of yourself (such as having friends who support you). We believe that both are important when trying to understand why people behave differently during the day versus after school hours; however, we believe that our students’ responses were more likely related solely with their own internal state than anything else.

The control-in and Control-out scores are correlated (r = 0.41, p < 0.01).

You can see that there is a correlation between the Control-in and Control-out scores, which means that they are both positively correlated. We will use this information to make an inference about your ability to control behaviors.

• The coefficient of determination (r2) of 0.41 indicates that 41% of the variability in one variable can be explained by another variable. In other words, if you know how many times someone failed to follow through on a task or how many times they were late for work, then you know how much variation there is in their level of performance overall.*

The correlation between the control-in and control-out is higher when we run the analysis on students in class 3 and 4 (r = 0.71, p < 0.05) than on all 4 classes combined (r = 0.46, p < 0.01).

The correlation between the control-in and control-out scores is higher when we run the analysis on students in class 3 and 4 (r = 0.71, p < 0.05) than on all 4 classes combined (r = 0.46, p < 0.01).

The reason for this is that there are more differences between these two groups of students than there are within each group itself. In other words, it’s easier to find differences between two sets of people who were not taught by the same teacher or went through a different curriculum than it is to identify similarities within those same populations after they have been put through similar experiences together as they progress through your class materials over time

Our hypothesis was supported for some students but not for others.

You might have noticed that the correlation between the Control-In and Control-Out scores was higher for some students than others. This is not surprising, as students with lower control scores tend to be more impulsive, while those with higher control scores are often less impulsive.

However, there were also some students who did not seem to be affected by their own impulsivity. For example, one student had an average Control In score of 0.91 but still scored 0 on all four items in our test (two of which were related to his inability to control himself), whereas another student’s average Control In score was 0.82 but he scored zero on only one item!

Conclusion

We find that there is a significant correlation between the control-in and control-out scores. This suggests that a student who is motivated at the day’s beginning will be motivated throughout the day. The effect of motivation on learning can be an important consideration for teachers when planning their lessons and teaching strategies.