NAME______________________________________________SCORE_________/20 CASE STUDY: Ways to improve an angry mood: A look at gender and sports participation Research conducted by: Emily Zitek and Mindy Ater, Rice University Case study prepared by: Emily Zitek 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 nonathletes. 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. Descriptions of Variables Variable Sports Gender Anger-Out (AO) Anger-In (AI) Control-Out (CO) Description 1 = athletes, 2 = non-athletes 1 = males, 2 = females high scores demonstrate that people deal with anger by expressing it in a verbally or physically aggressive fashion high scores demonstrate that people experience anger but do not express it (suppress their anger) high scores demonstrate that people control the outward expression of angry feelings high scores demonstrate that people control angry feelings by calming down Control-In (CI) or cooling off Expression index of general anger expression: (AE) (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. Use the data that was provided earlier, and answer the following two questions. To get a full credit you need to provide the following 1. The best point estimate for each group. 2. Find the margin of error by hand, show all your calculations. 3. Construct a confidence interval 4. You must upload your work to Canvas, I will create an assignment tab under modules to submit your work. 5. No need to upload the whole case study, the question's sheet will be enough. 1. Compute a 95% confidence interval for the mean Control-Out scores of the athletes AND a 95% confidence interval for the mean Control-Out scores for non-athletes. Show the intervals on the same number line. What can you conclude about the mean Control-Out scores for athletes and non-athletes? In addition to showing your CIs, write a statement using the definition of Control-out. Control-out: high scores demonstrate that people control the outward expression of angry feelings 2. Calculate a 95% confidence interval for the mean Anger-In score for the males and a 95% confidence interval for the mean Anger-In for females. Show the intervals on the same number line .What can you conclude about the mean Anger-In scores for males and females? In addition to showing your CIs, write a statement using the definition of Anger-in. Anger-In: high scores demonstrate that people experience anger but do not express it (suppress their anger) Gender 2 2 2 2 1 1 1 2 2 2 1 1 1 1 2 1 2 2 2 2 1 1 2 2 2 2 1 1 2 2 2 2 2 2 1 1 2 1 2 2 1 1 1 2 2 1 2 2 2 1 Sports 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 AngerOut 18 14 13 17 16 16 12 13 16 12 12 17 18 27 18 9 13 20 16 23 12 15 26 17 20 9 24 12 23 14 23 13 18 11 15 20 11 16 11 15 17 18 16 14 18 11 12 18 21 22 AngerIn 13 17 14 24 17 22 12 16 16 16 13 23 19 10 14 20 25 21 24 16 21 29 21 30 19 24 20 21 14 12 26 11 19 22 27 22 26 15 19 31 22 17 21 18 13 22 13 14 22 20 Control Out 23 25 28 23 26 25 31 22 22 29 24 24 29 23 17 28 27 15 26 15 29 29 14 16 17 21 18 26 17 22 28 27 21 25 21 16 24 30 22 21 22 27 30 20 27 32 24 19 25 17 ControlIn 20 24 28 23 28 23 27 31 24 29 25 22 30 27 11 24 24 18 26 14 15 23 13 18 14 21 13 24 14 22 23 21 19 24 16 18 25 26 16 22 19 24 30 17 20 22 22 19 19 18 2 1 1 2 2 2 2 2 2 2 1 2 1 1 2 2 1 2 1 1 1 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 22 26 11 17 16 9 11 17 13 18 19 15 15 18 12 15 14 14 15 21 18 17 24 14 10 11 15 15 17 24 15 18 18 14 23 11 22 19 15 21 22 18 16 18 14 22 15 19 19 10 19 11 18 14 17 17 22 15 29 28 24 32 24 21 21 27 19 25 25 20 31 30 27 30 27 21 24 18 18 18 30 29 20 24 23 16 19 20 22 32 16 24 21 22 19 26 24 19 32 29 23 29 27 17 23 17 23 15 32 24 18 26 Gender 2 2 2 2 1 1 1 2 2 2 1 1 1 1 2 1 2 2 2 2 1 1 2 2 2 2 1 1 2 2 2 2 2 2 1 1 2 1 2 2 1 1 1 2 2 1 2 2 2 1 Sports 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 AngerOut 18 14 13 17 16 16 12 13 16 12 12 17 18 27 18 9 13 20 16 23 12 15 26 17 20 9 24 12 23 14 23 13 18 11 15 20 11 16 11 15 17 18 16 14 18 11 12 18 21 22 AngerIn 13 17 14 24 17 22 12 16 16 16 13 23 19 10 14 20 25 21 24 16 21 29 21 30 19 24 20 21 14 12 26 11 19 22 27 22 26 15 19 31 22 17 21 18 13 22 13 14 22 20 Control Out 23 25 28 23 26 25 31 22 22 29 24 24 29 23 17 28 27 15 26 15 29 29 14 16 17 21 18 26 17 22 28 27 21 25 21 16 24 30 22 21 22 27 30 20 27 32 24 19 25 17 ControlIn 20 24 28 23 28 23 27 31 24 29 25 22 30 27 11 24 24 18 26 14 15 23 13 18 14 21 13 24 14 22 23 21 19 24 16 18 25 26 16 22 19 24 30 17 20 22 22 19 19 18 2 1 1 2 2 2 2 2 2 2 1 2 1 1 2 2 1 2 1 1 1 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 22 26 11 17 16 9 11 17 13 18 19 15 15 18 12 15 14 14 15 21 18 17 24 14 10 11 15 15 17 24 15 18 18 14 23 11 22 19 15 21 22 18 16 18 14 22 15 19 19 10 19 11 18 14 17 17 22 15 29 28 24 32 24 21 21 27 19 25 25 20 31 30 27 30 27 21 24 18 18 18 30 29 20 24 23 16 19 20 22 32 16 24 21 22 19 26 24 19 32 29 23 29 27 17 23 17 23 15 32 24 18 26