Risky Decision Making by College Athletes

Decision making is a major aspect of every individual's life. The process by which each conclusion is formed varies based on the person's life experiences and personality. The level of risk of a given situation is taken into account when reaching a decision, but what makes one person take more risks than another? Previous research has examined what types of personalities, ages, and lifestyles promote more risky behavior and which promote a safer approach (Brenner & Swanik, 2007; Juliusson, Karlsson, & Gärling, 2005; Levin & Hart, 2003).

One study performed by Levin and Hart (2003) focused mainly on the effects of age on risky behavioral choices. Their subjects were mainly children, but adults were added to the second half of the study. The researchers' hypothesis stated that if children tend to make risky decisions, then those qualities would carry on into adulthood. The hypothesis also recognized that the amount of information of the outcome of the situation would have an effect on the final decision of the child (Levin & Hart, 2003).

The independent variable of Levin and Hart (2003) were boxes that contained prizes. The levels of the independent variables were the number of prizes in a specific box during the gain part of the experiment and the number of prizes taken away during the loss section. Symbols on the boxes indicated how much the child could either gain or lose. Each gain or loss ranged from one gain or loss in one line of boxes to zero or two prizes in the other. The dependent variable was the number of prizes the child was willing to risk to end up with the most prizes in the end. The children were asked to repeat the experiment and the parent accompanying the child was asked to participate as well (Levin & Hart, 2003).

During this next experiment, the researchers hypothesized that the child's risk behavior could be observed in their parental guardian. The results indicated that younger children were less risky than older children and adults and older children were more willing to take bigger risks in order to prevent loss, rather than take risks to gain. Boys were also found to take the risky option more often than girls (Levin & Hart, 2003). This study relates to our study because it suggests that the more risky an individual is during childhood, the more likely they are to make risky decisions as adults. For example, a participant that was risky as a child and played contact sports all through childhood are more likely to engage in riskier behavior today.

Another study by Juliusson, Karlsson, and Gärling (2005) researched how much risk plays a factor in making a decision. Their hypothesis states if losses occurred or potential gains could be made due to a particular course of action, then these losses and gains will affect a person's decision to continue or terminate that action. The dependent variable in this experiment were ratings given by the participants in regard to how much they favored the alternative. The independent variables are the prior investments, prior returns, current investments, and future returns (Juliusson, Karlsson, & Gärling, 2005).

The results of the experiments showed that decisions about the future are affected by the past and the future as well as gains and losses. Weights are also placed on future outcomes. This theory assumes that people will look for information that may affect the future (Juliusson, Karlsson, & Gärling, 2005). This study relates to our research because the degree of how comfortable each group was to making a risky decision was based on how the decision directly affected each person individually.

One last study by Brenner and Swanik (2007) focused on college football athletes and their risky behavior regarding alcohol. The researchers' hypothesis stated if college athletes consume more alcohol than non-athletes, then the amount of alcohol consumed by athletes is dependent on the type of sport, the season, race, and intensity of competition. The dependent variables are the amount of drinks consumed in one night and the frequency of nights when drinking. The independent variables are the sport played and participation level, race, whether the athlete is currently in the season of their particular sport, and the competition involved (Brenner & Swanik, 2007).

The results indicated the amount of alcohol consumed by athletes were higher than formerly stated findings. Brenner and Swanik suggest the high rates of alcohol consumption are due the season in which the study was performed. The experiment was done during the off-season of most sports. Overall the results showed the participation level, whether the athlete is currently active in the sport, and competition level all had an impact on alcohol consumption (Brenner & Swanik, 2007). This relates to our study because we are focusing on risky behaviors of college athletes.

Our study is interested in discovering the level of risky behavior based off the competition level of different sports. For example, does contact versus no-contact sport increase one's likelihood of participating is riskier behavior? We hypothesize that if an athlete participates in a contact sport with a high competition level, then they are more likely to participate in more risky decision making. Many studies have researched the different between athletes and non-athletes, our study takes previous findings a step further to see if the type of sport has an effect.

Methods

Participants

There were 52 male participants, all current students at Chapman University. The participants were comprised of a selection of risky sport players, non-risky sport players, and a control group that involved students who do not play in a sports team on campus. Risky sport players will be defined as those who participate in contact sports while non-risky sport players will be defined as those who participate in non-contact sports. Data was collected from the football, soccer, and tennis team. Data taken from the football and soccer team was evaluated into the "risky" sport team category while the Tennis team was categorized into the "non-risky" sport team evaluation. The risk group consisted of 20 participants, while the non-risk group consisted of 9 participants. The control group consisted of 23-male non-athletes, comprised of students from the School of Music.

Materials

A questionnaire of 23 questions was created and administered to the participants. Questions were comprised of certain situations that would require an array of different answers according to the participant's experiences. Each question surveyed the participant's decision making in the past, present, and future situation. Questions were health-related, financial-related, and some every day decision-making questions. Distracter questions were incorporated into the questionnaire in order to conceal the true purpose of the study. Results would indicate the group more likely to make risky-decisions in everyday life situations.

Three separate blanks were provided for participants to inform the experimenter of their age, academic year, and which sport they play at the very beginning of the questionnaire. The questionnaire was printed on standard white computer paper (8 ½" by 11") and the participants were asked to use a pen to answer the questions.

Research Design

The same questionnaire was administered to each participant at their practice with permission of their coach. The only independent variable was into which category each participant was placed: risky, non-risky, or control. Examples of risky behaviors in this experiment were unprotected sex, heavy drinking, drugs, and other such behaviors. The fewer amounts of times a participant engaged in the examples of risky behaviors listed, the participant would be more likely to display non-risky behavior. The purpose of our study was to determine if participating in a risky sport affects risky decision-making in real life. The dependent variable was based on the total amount of points the individual scored on the questionnaire according to the type of sport the participant played.

Procedure

In order to prevent the influence of answers on the questionnaire, participants would be informed that the purpose of the study was to investigate the effects of the partaking in team sports on basic life decisions. The control group who consisted of non-athletes would be told that the study was simply a questionnaire on everyday decision-making.

The experimenter administered the questionnaire at the beginning of practice. First, the experimenter informed the participants of the purpose of the study and stressed the confidentiality of the survey in order to receive more honest answers. The questionnaire was distributed (along with a pen) to the appointed risky, non-risky, and non-athlete participation groups. Participants were proctored by at least one experimenter in order to ensure that participants would not sway other participant's answers. Upon completion, the questionnaires were collected and participants were thanked for their partaking. A simple debriefing was given stating that different sports have different levels of decision-making (contact versus non-contact sports was left out of the debriefing as a precaution to a participant who may speak with a member of a sports team that has not completed the study).

Scoring

The questionnaires were scored according to each question's appointed value. Questions with two answer-options had a value of either 0 or 1 while questions with four answer-options ranged from a value of 0-4. Distracter questions were given no value. Participants with the highest scores would be assigned as a more risky individual than those who with lower scores. A score within the range of 0-21 would indicate an individual who takes more precaution in decision making, while a score within the range of 42-64 would indicate an extremely risky individual. Participants who scored within the rage of 21-42 would indicate moderate decision-making.

Results

We examined risky decision-making in risky and non-risky sports players by surveys. Univariate analysis of variance (ANOVA) was used to examine the data. The test of between-subject effects for the low risk group was not significant, F = .150, p > .05. This means that what sport the participants play does not affect risk-taking group. The test of between-subject effects for the moderate risk group was also not significant, F = .238, p > .05. This also supports that what sport the participants play does not affect risk group.

Discussion

Our study was interested in discovering the level of risky behavior based off the competition level of different sports. We intended to determine whether athletes involved in high-risk sports are more risky in their decision-making than athletes in low-risk sports or non-athletes. Our hypothesis was if an athlete participates in a contact sport with a high competition level, then they are more likely to participate in more risky decision-making.

Our results show that, contrary to our hypothesis, playing a contact or high-risk sport does not make a person more likely to engage in risky behavior. We also found that sophomores and seniors tend to be more risky than freshmen and juniors. We expected to find results that supported our hypothesis, and we do have reason to believe that the data is slightly inaccurate. We believe that some questions were not answered truthfully, possibly due to fear of punishment by coaches, despite the promise of anonymity. The inaccuracy of answers to the survey questions may have resulted in a different conclusion based on the data that we were given.

Previous literature shows that the more risky an individual is during childhood, the more likely they are to make risky decisions as adults (Levin & Hart, 2003). With our study surveying college students, we could hypothesize that their decisions presently could impact how risky they will be as adults. When making decisions people will look for information that may affect the future according to Juliusson, Karlsson, & Gärling (2005), however, most of the questions on our survey were about present actions and decisions. In sports the participation level, whether the athlete is currently active in the sport, and competition level all had an impact on alcohol consumption (Brenner & Swanik, 2007). Because of this study, some of the questions on our survey were about alcohol consumption. Based on this research we formed the hypothesis that if an athlete participates in a contact sport with a high competition level, then they are more likely to participate in more risky decision making. However, the results of our study did not support our hypothesis.

Much can be learned from the current study and applied in future research on college sports and risk. Having a greater participant pool would lead to more accurate and meaningful data. The participant pool in this study was less than 60, which is part of the reason that the data did not support the hypothesis. Also, the number of participants in each risk group in this study was not equal due to the time constraints and the small participant pool available at Chapman University. Equal risk groups in future research will be essential to significant data.

The environments in which the athletes took the surveys were not controlled and class year was not taken into account when analyzing the data. The researchers in this study administered the surveys at practices with coaches and teammates close by. Some of the participants did not take the surveys seriously and even read some of the questions aloud to each other. Requiring the participants to take the survey in a classroom or other controlled space would render more accurate responses. Controlling for class year and analyzing the data accordingly could also lead to some interesting results. The results from this study did show that student athletes in their freshman and junior years were less risky than those in their sophomore and senior year. Future research could possibly explain the change in risk in this study.

Another improvement that could be made to this study would be to allow the participants to rate their own level of risk prior to taking the survey, instead of the researchers placing participants into categories based on which sport they play. In this study, the total score on the survey completed by the participants determined risk. The level of risk (high, medium, or low) was then assigned to each survey by dividing the highest score possible on the survey into three tiers with the highest scores being the most risky and the lower scores being the least risky. Allowing the participants in the study to assess their own level of risk would eliminate some subjectivity and make the method of assessing risk more accurate.

References

Brenner, J., & Swanik, K. (2007). High-risk drinking characteristics in collegiate athletes.
Journal of American College Health. 56(3). Retrieved on February 13, 2008, from
ProQuest Psychology Journals.

Juliusson, E.A., Karlsson, N., & Gärling, T. (2005). Weighing the past and the future in decision

making. European Journal of Cognitive Psychology, 17(4). Retrieved February

15, 2008, from PyscARTICLES database.

Levin, I.P., & Hart, S.S. (2003). Risk preferences in young children: early evidence of
individual differences in reaction to potential gains and losses. Journal of Behavioral
Decision Making. 16(5). Retrieved February 15, 2008 from ProQuest Psychology
Journals.