Abstract
Mentoring programs are a popular approach to preventing problem behavior and promoting positive youth development. However, mentoring relationships that end prematurely may have negative consequences for youth. Previous research has investigated match-level indicators of premature match closure, highlighting possible individual mentor- or mentee-level characteristics that might influence the match staying together. However, less work has investigated the importance of program-level variables in match retention. Mentor training and support may be one key modifiable program-level feature that could curtail the risk of premature match closure. In this study, we used data from a national survey of youth mentoring programs (N = 1451) to examine training and other potential predictors of premature match closures (Garringer et al. 2017). We used a Bayesian Additive Regression Trees (BART) model to predict program-reported premature match closure rates from a set of four training-related variables and 26 other covariates (e.g., program size, budget, demographic composition). Findings indicate that the set of predictors explained about one-fifth of the variation in reported rate of premature match closure (cumulative pseudo R2 = .21), and the strongest, and only statistically significant, predictor of premature match closure was the frequency of ongoing training and support contacts per month. Overall, findings indicate that there is substantial noise in predicting program-reported premature match closure, but program-reported provision of ongoing training and support seems to emerge as a relatively stable signal in the noise.
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References
Chipman, H. A., George, E. I., & McCulloch, R. E. (2010). BART: Bayesian additive regression trees. The Annals of Applied Statistics, 4, 266–298. https://doi.org/10.1214/09-AOAS285.
DuBois, D. L., Holloway, B. E., Valentine, J. C., & Cooper, H. (2002). Effectiveness of mentoring programs for youth: a meta-analytic review. American Journal of Community Psychology, 30, 157–197. https://doi.org/10.1023/A:1014628810714
DuBois, D. L., Portillo, N., Rhodes, J. E., Silverthorn, N., & Valentine, J. C. (2011). How Effective Are Mentoring Programs for Youth? A Systematic Assessment of the Evidence. Psychological Science in the Public Interest, 12, 57–91. https://doi.org/10.1177/1529100611414806.
Eby, L. T., Allen, T. D., Evans, S. C., Ng, T., & Dubois, D. (2008). Does mentoring matter? A multidisciplinary meta-analysis comparing mentored and non-mentored individuals. Journal of vocational behavior, 72, 254–267. https://doi.org/10.1016/j.jvb.2007.04.005.
Garringer, M., McQuillin, S., & McDaniel, H. (2017). Examining youth mentoring services across America: Findings from the 2016 National Mentoring Program Survey. The National Mentoring Partnership: Technical Report Produced by MENTOR http://www.mentoring.org/program-resources/mentor-resources-and-publications/national-survey/. Accessed 12 Dec 2019.
Grossman, J. B., Chan, C. S., Schwartz, S. E. O., & Rhodes, J. E. (2012). The test of time in school-based mentoring: The role of relationship duration and re-matching on academic outcomes. American Journal of Community Psychology, 49, 43–54. https://doi.org/10.1007/s10464-011-9435-0.
Grossman, J. B., & Rhodes, J. E. (2002). The test of time: Predictors and effects of duration in youth mentoring relationships. American Journal of Community Psychology, 30(2), 199–219. https://doi.org/10.1023/A:1014680827552.
Herrera, C., Grossman, J. B., Kauh, T. J., Feldman, A. F., McMaken, J., & Jucovy, L. Z. (2007). Making a difference in schools: The Big Brothers Big Sisters School-Based Mentoring impact study. Philadelphia: Public/Private Ventures.
Hill, J. L. (2011). Bayesian nonparametric modeling for causal inference. Journal of Computational and Graphical Statistics, 20(1), 217–240.
Kapelner, A., & Bleich, J. (2013). bartMachine: Machine learning with Bayesian additive regression trees. ArXiv:1312.2171 [Cs, Stat]. Retrieved from http://arxiv.org/abs/1312.2171. Accessed 12 Dec 2019.
Kupersmidt, J., Stump, K., Stelter, R., & Rhodes, J. (2017). Predictors of premature match closure in youth mentoring relationships. American Journal of Community Psychology, 59(1). https://doi.org/10.1002/ajcp.12124.
Loh, W.-Y. (2011). Classification and regression trees. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 1, 14–23. https://doi.org/10.1002/widm.8.
McQuillin, S., & Lyons, M. (2016). Brief instrumental school-based mentoring for middle school students: theory and impact. Advances in School Mental Health Promotion, 9, 73–89. https://doi.org/10.1080/1754730X.2016.1148620.
McQuillin, S., Lyons, M., Becker, K., Hart, M., & Cohen, K. (2019). Strengthening and expanding child services in low resource communities: The role of task-shifting and just-in-time training. American Journal of Community Psychology. https://doi.org/10.1002/ajcp.12314.
McQuillin, S., Strait, G., & Saeki, E. (2015). Program support and value of training in mentors’ satisfaction and anticipated continuation of school-based mentoring relationships. Mentoring and Tutoring: Partnership in Learning, 23, 133–148. https://doi.org/10.1080/13611267.2015.1047630.
MENTOR. (2015) Elements of effective practice for mentoring (4th ed). Author: Boston. https://www.mentoring.org/new-site/wp-content/uploads/2015/09/FAQ_Elements_February2015.pdf. Accessed 12 Dec 2019.
National Mentoring Resource Center (2019) Training evidence: Summary narrative. Training evidence synthesis. Retrieved from https://nationalmentoringresourcecenter.org/images/PDF/Training_Evidence_Synthesis.pdf. Accessed 12 Dec 2019.
Raposa, E. B., Rhodes, J., Stams, G., Card, N., Burton, S., Schwartz, S., et al. (2019). The Effects of Youth Mentoring Programs: A Meta-analysis of Outcome Studies. Journal of youth and adolescence, 48, 423–443. https://doi.org/10.1007/s10964-019-00982-8.
Rhodes, J. E. (2015). The many invisible forces: Why mentoring “best” practices are sometimes not enough. The chronicle of evidence-based mentoring. Retrieved from http://chronicle.umbmentoring.org/the-many-invisible-forces-why-mentoring-best-practices-are-sometimes-not-enough. Accessed 12 Dec 2019.
Spencer, R., Basualdo-Delmonico, A., Walsh, J., & Drew, A. L. (2017). Breaking up is hard to do: A qualitative interview study of how and why youth mentoring relationships end. Youth & Society, 49(4), 438–460. https://doi.org/10.1177/0044118X14535416.
Acknowledgments
The authors would like to thank Dr. David DuBois and Dr. Jean Rhodes for their help in selecting covariates for the final model. The authors would like to acknowledge the substantial contributions of four blind reviewers who helped improve the manuscript.
Funding
The NMRC is funded by the Office of Juvenile Justice and Delinquency Prevention (OJJDP) through a cooperative agreement with MENTOR: The National Mentoring Partnership (2016-MU-MU-K001).
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This research was conducted on de-identified extant program-level data. No human subject data are included in this study. All procedures performed in this study were in accordance with the ethical standards of the American Psychological Association and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The original research included informed consent for programs to report program-level data. This study represents a secondary data analysis and was solicited by the National Mentoring Resource Center. The viewpoints and conclusions represented in this manuscript do not necessarily represent those of either OJJDP or MENTOR.
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The authors declare that they have no conflicts of interest.
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This manuscript is based on a technical report written by the first author for the National Mentoring Resource Center (NMRC). The purpose of original technical report was to test the hypothesis that training influences premature match closure, controlling for other influences.
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McQuillin, S.D., Lyons, M.D. A National Study of Mentoring Program Characteristics and Premature Match Closure: the Role of Program Training and Ongoing Support. Prev Sci 22, 334–344 (2021). https://doi.org/10.1007/s11121-020-01200-9
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DOI: https://doi.org/10.1007/s11121-020-01200-9