In addition, those adolescents who are poorly prepared for social-emotional encounters are less likely to engage in safe sexual practices. Thus, adolescents who are still developing their social-emotional cognitive abilities are more likely to engage in situations that may put them at risk for pregnancy and sexually transmitted diseases (STDs). Furthermore, adolescents who have children are less likely to graduate and are more likely to require welfare assistance (Kotchick et al., 2006).
Youth who abstain from sexual activity are significantly more likely to graduate from both high school and college. High-risk females—those more likely to engage in RSBs—have significantly lower grade point averages (GPAs) in high school (Luster & Small, 1994). Those youth who maintain high levels of religiosity are more likely to avoid risky behavior (Rostosky, Wilcox, Wright, & Randall, 2004).
One study found that youth who are more susceptible to peer pressure are 2.2 times more likely to be sexually active (Allen, Porter, & McFarland, 2006). Therefore, children who were predisposed to engage in risky situations were more likely to be influenced by peers to engage in RSBs. More specifically, Maxwell found that a teenager is 1.9 times more likely to engage in risky behavior if their friend had it.
Teens who engage in positively perceived sexual exploration are more likely to engage in those encounters in the future.
Method
This study examined the relationship between social-emotional intelligence (SEI) and risky sexual behaviors (RSBs) during adolescence. Risk behaviors among individuals aged 13 to 19 include earlier age of first intercourse (especially before age 13), limited to no use of contraception, multiple sexual partners, and frequent intercourse (Bryan & Stallings, 2002; Harden, et al., 2008) ; Houlihan et al., 2008; Sienbruner et al., 2007). Most of the questions for measuring these variables were taken from questions used in previous research.
One Likert scale item was slightly modified to indicate use 11 or more times, rather than 15 or more times as reported in previous research. The BarOn EQ-i:YV (BarOn & Parker, 2000) is a self-report measure of social-emotional intelligence. This scale and its predecessors were developed based on BarOn's model of emotional intelligence.
The measure was selected for this research because it is the most widely used instrument for SEI and provides validated data on emotional dimensions related to adolescence (Killgore & Yurgullen-Todd, 2007). The development of the youth version of the scale is based entirely on BarOn's model of social-emotional intelligence and has been normed on 9,172 children aged seven to 18 years (BarOn & Parker, 2000). While producing a total emotional intelligence (EQ) score, the BarOn EQ-i:YV includes four domains of emotional competencies including Intrapersonal, Interpersonal, Stress Management, and Adaptability (see Appendix C) as determined by confirmatory factor analysis.
This is a self-report Likert scale test with separate norms for gender (male and female) and age (grouped into seven to nine years, ten to 12 years, 13 to 15 years, and 16 to 18 years). This was designed to identify children who “faked” the test, thereby improving validity (BarOn, 2007; BarOn & Parker, 2000). This task was reported to take only ten minutes to complete, compared to the expected 30 minutes for the long form.
Like the long form, the short form has demonstrated moderate to high reliability and validity (see tables in Appendices D and E). Studies using BarOn for predictors of performance have shown that this scale and its components are better predictors of such traits than other scales based on ability models (BarOn, 2006). Thus, it is a robust, reliable, valid, and highly researched tool suitable for the parameters of the current investigation.
Results
The regression analyzes sought to determine whether social-emotional intelligence could explain some of the variance in RSBs not otherwise explained by variables already described in previous research. This leptokurtic distribution indicated that most students responded similarly and that their scores clustered around the sample mean. Regarding the control variables, risky sexual behavior was not related to academic achievement, parental education, or participation in sex education.
Interpersonal EQ and Delinquency were the most strongly correlated with risky sexual behavior (r = .46 and -.36, respectively). However, analysis of the beta weights showed that Interpersonal EQ on the EQ scale was the only significant predictor of RSBs (β = −.30, p = .04). The regression analyzes for Total EQ (see Table 5), Intrapersonal EQ (see Table 6), Stress Management EQ (Table 7) and Adaptability EQ (Table 8) did not have significant correlations between the BarOn scales and variables with risk for sexual behavior.
In contrast, the Interpersonal EQ scale (Table 9) had a significant relationship with risky sexual behavior. Standardized coefficients from regression analysis predicting total emotional intelligence from risky sexual behavior and control variables. Standardized coefficients from regression analysis predicting intrapersonal emotional intelligence from risky sexual behavior and control variables.
Standardized coefficients of regression analysis Predicting stress management Emotional intelligence from risky sexual behavior and control variables. Standardized Coefficients of Regression Analysis Predicting Adaptability Emotional Intelligence from Risky Sexual Behavior and Control Variables. Standardized coefficients of regression analysis Predicting interpersonal emotional intelligence from risky sexual behavior and control variables.
Although statistical significance was found in some regression relationships, failure to achieve a priori sample size, post-hoc power, and effect size were analyzed in the Interpersonal EQ regression model (see Table 10). Power and effect sizes for variables in the regression model measuring interpersonal EQ, control variables, and risky sexual behavior. There is no further support that there are problems with multicollinearity, as the power of the variance inflation factors is quite low (ranging from 1.092 to 2.136).
Discussion
Onttrek van http://www.apa.org/pubs/journals/dev/index.aspx Brackett, M.A., Mayer, J.D., & Warner, R.M. Onttrek van http://www.highbeam.com/Jounral+of+Humanist ic+Counseling%2c+Education+and+Development/publications.aspx.
