Predicting Successful Mentoring Relationships using Dyadic Data from an Evaluation of Big Brothers Big Sisters School-Based Programming

• In Event: Poster Session

Abstract

As noted by positive youth development research, the presence of a close, caring relationship with a prosocial adult protects youth from engaging in risky behaviors, including truancy, violence and delinquency. School-based mentoring is growing in popularity and practice; however, best practices in this delivery mode are still being defined. This poster presents results from an evaluation of the Big Brothers Big Sisters-Greater Twin Cities school-based mentoring program being conducted in Minnesota. We collected online survey data from 304 school-based mentors (“Bigs”) at the start and end of the 2013-14 school year, in addition to mentee survey data collected by the program. Our sample of mentors is diverse with respect to age (range: 15-80), but primarily female (70%). Younger mentors, especially high school Bigs, are more diverse in terms of their race/ethnicity, while older mentors are likely to be white. The goal of this poster is to describe factors that predict higher quality mentoring relationships that lead to better outcomes for young mentees. Using Mplus, we conducted structural equation modeling of dyadic data from both mentors and mentees on the strength of their mentoring relationship, to identify individual and relationship factors that contribute to better and longer mentoring matches.

Authors

• Barbara J. McMorris, University of Minnesota

• Kara Beckman, University of Minnesota

• Shari Plowman, University of Minnesota