2008
DOI: 10.1353/mpq.2008.0019
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Predicting Youth Out-of-School Time Participation: Multiple Risks and Developmental Differences

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Cited by 22 publications
(13 citation statements)
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“…The most heavily researched family predictor of participation is SES. As expected, research suggests that children from high-SES families are more likely to participate in after-school activities than are children from low-SES families (e.g., Dearing et al, 2009;Marsh & Kleitman, 2002;Wimer et al, 2008). Having a limited income can create barriers, as poor communities have fewer activities available (Furstenberg, Cook, Eccles, Elder, & Sameroff, 1999;Quiroz, 2000;Shann, 2001) and low-SES families have less money to spend on activities (Halpern, Barker, & Mollard, 2000;Shann, 2001).…”
Section: How To Design Programs To Successfully Recruit and Retain Youthmentioning
confidence: 59%
“…The most heavily researched family predictor of participation is SES. As expected, research suggests that children from high-SES families are more likely to participate in after-school activities than are children from low-SES families (e.g., Dearing et al, 2009;Marsh & Kleitman, 2002;Wimer et al, 2008). Having a limited income can create barriers, as poor communities have fewer activities available (Furstenberg, Cook, Eccles, Elder, & Sameroff, 1999;Quiroz, 2000;Shann, 2001) and low-SES families have less money to spend on activities (Halpern, Barker, & Mollard, 2000;Shann, 2001).…”
Section: How To Design Programs To Successfully Recruit and Retain Youthmentioning
confidence: 59%
“…Findings indicate that adolescents with greater academic and social problems (child-level risks) and those from less supportive, involved, and engaged families (family-level risks) were less likely to participate in organized activities. The findings for school and neighborhood risks were less straightforward; they varied by age and activity type (Wimer et al, 2008). …”
Section: Programs As a Context Of Developmentmentioning
confidence: 99%
“…More randomized experiments are needed to reach casual conclusions and in particular to rule out selection bias. Youth elect to join ASPs and comparing those who volunteer with controls who have not fails to address the variety of known individual and contextual factors that are linked to why some youth are interested in ASPs while others are not (e.g., Bouffard et al 2006;Mahoney et al 2009b;Wimer et al 2008). It is also important to not only collect baseline data on participants including information on their prior school performance and behavioral adjustment, but also, in control group designs, to test for pre-treatment equivalence and control for any initial differences that are present in subsequent statistical analyses.…”
Section: General Recommendations For Future Program Evaluationsmentioning
confidence: 99%