Collin Flake and Dr. Renata Forste, Sociology
After several discussions with my faculty mentor and a thorough review of the existing research, I set out to examine the effectiveness of after school programs in Utah, specifically the Boys and Girls Clubs of the Greater Salt Lake area. The purpose of my research is twofold. The first is to identify the complex behavioral, academic, and mental and physical health issues that challenge youth from disadvantaged backgrounds. The second is to evaluate the effectiveness of current community programs in addressing these issues.
I began my project by reviewing the literature relating to my research questions. Most of the members of after school programs like the Boys and Girls Clubs come from disadvantaged homes. Youth from these backgrounds face a significant number of risk factors including poverty, community violence, and family distress (Gabarino et. al., 1992). These at-risk young people are more likely to be delinquent, are less likely to succeed academically, and are in danger of having low self-esteem and poor health (Carlson, 2006; Daniels, 2006). It is particularly worrisome when youth are confronted with these obstacles because life course trajectories are often established during adolescence.
I found that researchers debate whether government or private after-school programs succeed in helping children overcome their challenges. Findings from one study suggest that attending these programs is associated with negative academic, emotional, and social outcomes in comparison to mother care and self care (Vandell & Corasaniti, 1988). By contrast, Anderson-Butcher et. al. (2003) found that disadvantaged youth who actively participated in Boys and Girls Clubs had better academic outcomes than those who did not (Anderson-Butcher et. al., 2003).
To answer my research questions, I revised the existing national Boys and Girls Clubs survey and administered it to club members in Tooele, Lied, Park City, Sugar House, and Capitol West. I then constructed a dataset and entered the data (N=547) in SPSS. The key independent variables are membership length (years) and club attendance (days per week). Dependent variables include academic, behavioral, and health measures. After running descriptive statistics and performing factor analyses, I applied linear regression to four models. My analysis establishes the probability that membership length and club attendance are associated with attitudinal and behavioral outcome scales.
Tables 1 and 2 present the findings of my analysis. Table 1 provides descriptive statistics of member characteristics, as well as various outcome measures created through factor analyses. Average membership length is 2.2 years and average club attendance is 2-3 days per week. Latinos make up the highest proportion of club members at 34%, followed by whites at 33.8% and blacks at 11.8%. Based on body mass index, 18.8% of club members are overweight and 15.4% are obese.
Linear regression analysis revealed that as club attendance increases, deviance (self-reported) decreases. Both academic and self-concept measures also decrease with each year a member gets older. Interestingly, self-concept measures slightly decrease as club attendance increases. Not surprisingly, being overweight or obese is associated with poorer physical health. The regression analysis suggests that less deviant behavior and success in academics is associated with frequency of attendance rather than length of membership.
My survey research found that participation in club activities is associated with a number of positive outcomes. Members who regularly attended have high opinions of club staff, higher racial tolerance, increased inter-personal problem solving and leadership skills, decreased self-perception of failing in school, and decreased delinquent behavior. Clearly, the club is having a positive impact on the youth it serves.
I created an in-depth summary of my findings for presentation to administrators of the Boys and Girls Clubs. In this report, regression models (OLS) are used to predict the relationship between club attendance and various outcome measures. Scale values (0, 1, 2) are entered into the predicted models to determine predicted outcomes for each level of club attendance. Statistically significant (p<.05) relationships are presented in a bar graphs, and the relationship between length of club membership and outcomes is presented in order from strongest to weakest. After I analyzed the data, I have focused my efforts on writing up the summary report, which will be presented to club officials when I administer the third wave of surveys in January of 2010. To further develop the writing and data analysis areas of my research, I will use the data I have collected for projects in my graduate research methods courses next semester. In order to display my research publicly, I am constructing a poster that will be presented at the 2010 Mary Lou Fulton Mentored Research Conference at Brigham Young University.