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Multiple Regression Results

APPLYING A YOUTH ENGAGEMENT FRAMEWORK TO PREDICTING COMMUNITY INVOLVEMENT Michael A. Busseri, Linda Rose-Krasnor, Kelly Campbell, and Holly Stack Brock University (Canada) and the Centre of Excellence for Youth Engagement (Health Canada).

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Multiple Regression Results

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  1. APPLYING A YOUTH ENGAGEMENT FRAMEWORK TO PREDICTING COMMUNITY INVOLVEMENT Michael A. Busseri, Linda Rose-Krasnor, Kelly Campbell, and Holly Stack Brock University (Canada) and the Centre of Excellence for Youth Engagement (Health Canada) The Centres of Excellence are a Health Canada-funded program. The opinions expressed in this poster do not necessarily reflect those of Health Canada. • Introduction • Previous studies have linked youth activity involvement with positive developmental outcomes, including reduced risk behaviors, higher academic success, better psychological functioning, and stronger interpersonal bonds. • Comparatively fewer studies, however, have systematically examined predictors of youth involvement. • We have proposed a process-oriented framework for youth “engagement”, which we define as sustained, meaningful activity involvement. • As shown in the figure below, our Youth Engagement Framework comprises four primary components: initiating factors expected to promote youth engagement; sustaining factors expected to support and maintain engagement; youth engagement itself; and outcomes. • The present study focuses on relationships between initiating and sustaining factors and youth engagement, evaluated at three hypothesized levels of influence: personal beliefs, attitudes, and predispositions (self-level); interpersonal relations (social-level); and society and institutions (systems-level). Results Summary of Study Measures and Correlations with Youth Involvement As shown in the table below,with few exceptions, initiating and sustaining factor indicators showed positive bivariate associations with both current community involvement (CI) and next year intentions (NYI). Note. N = 190. * Efficacy composite combines scores from two systems-level factors (self-level ‘perceived efficacy’, and systems-level ‘openness to change’). Underlined values indicate ps < .05 Multiple Regression Results Standardized beta weights are shown in the prediction of community involvement (CI) and next year intentions (NYI) – controlling for current involvement. Note. Underlined values indicate ps < .05. Youth Engagement Framework Note. The ‘layers’ surrounding initiating and sustaining factors represent self, social, and systems-level influences. Dashed box indicates components assessed in the current study. Initiating factors Youth engagement Outcomes Sustaining factors Predicting Next Year Intentions The hierarchical regression model explained 50% of the variance in next year intentions (NYI); R = .71, p < .001. In step 1, current involvement explained 37% of the variance (p < .001). In step 2, the initiating and sustaining factor indicators explained an additional 13% of the variance (p = .002). As shown in the table above, in the final regression model five predictors made significant, unique contributions to the prediction of stronger intentions for next year involvement: more frequent current involvement, less valuing of ambition, greater openness to new experiences, stronger social support, and greater perseverance. • Participants and Procedures • Results were based on survey responses from 190 youth: female undergraduates ranging in age from 17 to 19 years old (M = 18.48 years, SD = 0.53). • The study survey was completed at the participant’s convenience and encompassed questions related to each of the primary components of our Youth Engagement Framework. • Measures • Ten initiating factor indicators and eight sustaining factor indicators were derived from previous studies, as well as our conceptual work. Indicators were based on multi-item measures (see table in next column). • Community involvement was assessed by mean frequency of current involvement in five activities in the past year (volunteering/community service, political action, school clubs, community youth groups, conferences/workshops), as was a composite measure of involvement intentions for the coming year. • Analysis • Pairwise correlations: initiating and sustaining factor indictors with youth involvement (current community involvement, next year intentions). • Multiple regression of current involvement on initiating and sustaining factor indicators. • Hierarchical multiple regression of next year intentions on current involvement (step 1) and initiating and sustaining factors (step 2). • Discussion • Initiating and sustaining factors both were associated with current community involvement and future intended involvement in bivariate and multivariate analyses. • Regression results support the unique role of two of three hypothesized levels of influence: self-level and social-level variables. • No inferences can be made about causal influence including how relations among framework components unfold over time. Results may vary depending on the type of involvement examined and the specific initiating and sustaining factor indicators. • Conclusion • Our Youth Engagement Framework - comprising multiple types and levels of influence - holds promise for the study of youth engagement. Predicting Community Involvement Together the initiating and sustaining factors indicators explained a total of 41% of the variance in current community involvement (CI) was explained (R = .64, p < .001). As shown in the table at the top of the next column, several indicators made significant and unique contributions to the prediction of community involvement including: greater interest in getting involved, greater social encouragement, higher perceived efficacy, and more positive engagement attitudes.

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