Empirical studies show low perceived risk is correlated with unsafe sexual behavior, increased rates of STDs and HIV, tobacco use, and multi-substance misuse [ 29 — 31 ]. The internal consistency for this study was 0. Athletes must contend with both academic and athletic demands, thus separating athletes from their non-athlete peers [ 15 , 16 ]. Furthermore, the collective nature of athletic teams could have a normative effect on perceptions and behaviors. Through a mediational model, it is hypothesized that athletes have a lower perceived risk of harm than non-athletes. This special treatment may lead athletes to believe they can engage in various behaviors without negative consequences. Goals and Analyses The primary goals of this study were to:
The purpose of this study was to assess whether athletes begin to engage in more alcohol use and sexual activity before college, and if low perceived risk plays a role in this process. The dual role as athlete and student may create an environment that increases the likelihood of athletes engaging in behavioral risks, including sexual activity and alcohol use [ 15 ]. As such, there seems to be a shift at some point where athletes become at-risk for substance use and sexual activity. Results Relative to non-athletes, athletes reported greater alcohol use, more sexual partners, and lower perceived risk. For example, one well-known university has enforced a tutoring policy whereby athletes receive different tutoring i. The internal consistency for this study was 0. Perceived risk partially mediated the association between sports participation and episodes of unsafe sexual activity in both men and women. For example, student athletes consume significantly more drinks per week and drink more frequently than non-athletes [ 8 , 9 ]. Athletics, Perceived Risk, Alcohol Drinking, Sexual Activity Studies among younger athletes indicate that sports participation may serve as a protective factor against behavioral risk, such as alcohol use and risky sexual activity [ 1 — 4 ]. Furthermore, the collective nature of athletic teams could have a normative effect on perceptions and behaviors. Exponentiated betas were also included to provide incidence rate ratios IRR as estimates of effect size such that a rate ratio of 1. Because distributions indicated extreme non-normality, generalized linear modeling GLM was used to assess the associations among sports participation, perceived risk, alcohol use, and sexual activity. As adolescents age and athletic roles become more competitive and prominent, there seems to be a shift in sexual activity between athletes and non-athletes. First, there must be a significant association between the predictor sports participation and outcome alcohol use, number of sexual partners, or unsafe sex , as well as the predictor and the mediator perceived risk. A negative binomial distribution and log link was selected when the outcome variable was number of sexual partners and instances of unsafe sex in the past three months because the variables were count variables with integer values and heteroskedasticity, and the distribution had a high number of zero-values. Moreover, highly active high school athletes are more likely to binge drink, use tobacco, and use multiple drugs i. Although a gamma distribution is not a perfect fit to the data because zero is undefined by the gamma distribution, the gamma distribution fits the current data better than a Gaussian distribution. Conclusions These findings suggest a potential cognitive mechanism which may account for differences in alcohol use and sexual activity between athletes and non-athletes during late adolescence. Sexual activity Number of sexual partners i. Goals and Analyses The primary goals of this study were to: GLM results are interpreted similarly to ordinary least squares regression; however, the use of z and chi-square tests are used instead of the corresponding t and f-tests, and a measure of association i. Research on sexual activity among athletes and non-athletes has yielded mixed findings. If college athletes drink more often and in greater quantities and engage in sexual activity more often than non-athletes, but younger athletes do not, this shift in behavior may occur in high school, just before the spotlight of collegiate athletics. Athlete status As part of a larger measure of how they spend their time, participants were asked to indicate the number of hours spent in competitive athletes. At the time of high school data collection, the mean age of the participants was
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