Top

Administration and Policy in Mental Health and Mental Health Services Research

Published in:

01-07-2017 | Original Article

Using Complier Average Causal Effect Estimation to Determine the Impacts of the Good Behavior Game Preventive Intervention on Teacher Implementers

Authors: Juliette K. Berg, Catherine P. Bradshaw, Booil Jo, Nicholas S. Ialongo

Published in: Administration and Policy in Mental Health and Mental Health Services Research | Issue 4/2017

Abstract

Complier average causal effect (CACE) analysis is a causal inference approach that accounts for levels of teacher implementation compliance. In the current study, CACE was used to examine one-year impacts of PAX good behavior game (PAX GBG) and promoting alternative thinking strategies (PATHS) on teacher efficacy and burnout. Teachers in 27 elementary schools were randomized to PAX GBG, an integration of PAX GBG and PATHS, or a control condition. There were positive overall effects on teachers’ efficacy beliefs, but high implementing teachers also reported increases in burnout across the school year. The CACE approach may offer new information not captured using a traditional intent-to-treat approach.

Abenavoli, R. M., Jennings, P. A., Greenberg, M. T., Harris, A. R., & Katz, D. A. (2013). The protective effects of mindfulness against burnout among educators. The Psychology of Education Review, 37, 57–69.

Angrist, J. D., Imbens, G. W., & Rubin, D. B. (1996). Identification of causal effects using instrumental variables. Journal of the American Statistical Association, 91, 444–455.CrossRef

Barnard, J., Frangakis, C. E., Hill, J. L., & Rubin, D. (2003). Principal stratification approach to broken randomized experiments. Journal of American Statistical Association, 98, 299–323. doi:10.1198/016214503000071.CrossRef

Botvin, G. J., Baker, E., Dusenbury, L., Botvin, E. M., & Diaz, T. (1995). Long-term follow-up results of a randomized drug abuse prevention trial in a white middle-class population. JAMA, 273, 1106–1112.CrossRefPubMed

Bradshaw, C. P., Koth, C. W., Bevans, K. B., Ialongo, N., & Leaf, P. J. (2008). The impact of school-wide Positive Behavioral Interventions and Supports (PBIS) on the organizational health of elementary schools. School Psychology Quarterly, 23, 462–473. doi:10.1037/a0012883.CrossRef

Bradshaw, C. P., Koth, C. W., Thornton, L. A., & Leaf, P. J. (2009a). Altering school climate through school-wide Positive Behavioral Interventions and Supports: Findings from a group-randomized effectiveness trial. Prevention Science, 10(2), 100–115. doi:10.1007/s11121-008-0114-9.CrossRefPubMed

Bradshaw, C. P., Zmuda, J. H., Kellam, S. G., & Ialongo, N. S. (2009b). Longitudinal impact of two universal preventive interventions in first grade on educational outcomes in high school. Journal of Educational Psychology, 101(4), 926–937. doi:10.1037/a0016586.CrossRefPubMedPubMedCentral

Bryk, A. S., & Schnieder, B. (2002). Trust in schools: a core resource for improvement. New York: Russell Sage.

Chen, H. T. (1998). Theory-driven evaluations. Advances in Educational. Productivity, 7, 15–34.

Conduct Problems Prevention Research Group. (1999). Initial impact of the fast track prevention trial for conduct problems: II. Classroom effects. Journal of Consulting and Clinical Psychology, 67, 648–657.CrossRefPubMedCentral

Connell, A. M., Dishion, M. Y., & Kavanagh, K. (2007). An adaptive approach to family intervention: Linking engagement in family-centered intervention to reductions in adolescent behavior. Journal of Consulting and Clinical Psychology, 75, 568–579. doi:10.1037/0022-006X.75.4.568.CrossRefPubMed

Cowen, J. M. (2008). School choice as a latent variable: Estimating the “complier average causal effect” of vouchers in Charlotte. The Policy Studies Journal, 36, 301–315.CrossRef

Derzon, J. H., Sale, E., Springer, J. F., & Brounstein, P. (2005). Estimating intervention effectiveness: Synthetic projection of field evaluation results. Journal of Primary Prevention, 26, 321–343.CrossRefPubMed

Domitrovich, C. E., Bradshaw, C. P., Berg, J., Pas, E. T., Becker, K., Musci, R, Ialongo, N. (2016). How do school-based prevention programs impact teachers? Findings from a randomized trial of combined classroom management and social-emotional programs. Journal of Prevention Science, 1–13.

Domitrovich, C., Bradshaw, C., Greenberg, M., Embry, D., Poduska, J., & Ialongo, N. (2010). Integrated models of school-based prevention: Logic and theory. Psychology in the Schools, 47, 71–88.PubMedPubMedCentral

Domitrovich, C. E., Bradshaw, C. P., Poduska, J. M., Hoagwood, K. E., Buckley, J. A., Olin, S., & Ialongo, N. S. (2008). Maximizing the implementation quality of evidence-based preventive interventions in schools: A conceptual framework. Advances in School Mental Health Promotion, 1, 6–28.CrossRefPubMedPubMedCentral

Domitrovich, C. E., Gest, S. D., Gill, S., Jones, D. J., & DeRouise, R. S. (2009). Teacher factors related to the professional development process of the Head Start REDI intervention. Early Education and Development, 20, 402–430.CrossRef

Domitrovich, C., Pas, E., Bradshaw, C. P., Becker, K., Keperling, J. P., Embry, D., & Ialongo, N. (2015). Individual and school organizational factors that influence implementation of the Pax Good Behavior Game intervention. Prevention Science, 6(8), 1064–1074.CrossRef

Domitrovich, C. & Poduska, J. (2008). The social-emotional learning efficacy scale. Unpublished technical report.

Durlak, J. A., & DuPre, E. P. (2008). Implementation matters: A review of research on the influence of implementation on program outcomes and the factors affecting implementation. American Journal of Community Psychology, 41, 327–350.CrossRefPubMed

Durlak, J. A., Weissberg, R. P., Dymnicki, A. B., Taylor, R. D., & Schellinger, K. B. (2011). The impact of enhancing students’ social and emotional learning: A meta-analysis of school-based universal interventions. Child Development, 82, 405–432.CrossRefPubMed

Embry, D., Staatemeier, G., Richardson, C., Lauger, K., & Mitich, J. (2003). The PAX Good Behavior Game (1st ed.). Center City : Hazelden.

Fixsen, D., Naoom, S., Blasé, K., Friedman, R., & Wallace, F. (2005). Implementation research: A synthesis of the literature. Tampa: University of South Florida, Louis de la Parte Florida Mental Health Institute. The National Implementation Research Network (FMHI Publication #231).

Frangakis, C. E., & Rubin, D. B. (2002). Principal stratification in causal inference. Biometrics, 58, 21–29.CrossRefPubMedPubMedCentral

Frank, J. L., Jennings, P. A., & Greenberg, M. T. (2016). Validation of the mindfulness in teaching scale. Mindfulness, 1, 155–163.CrossRef

Greenberg, M., & Kusché, C. (2006). Building social and emotional competence: The PATHS Curriculum. In S. R. Jimerson & M. J. Furlong (Eds.), Handbook of school violence and school safety: From research to practice (pp. 395–412). Mahwah: Erlbaum.

Greenberg, M. T., Kusché, C. A., & Conduct Problems Prevention Research Group. (2011). Grade level PATHS (Grades 3-5). South Deerfield: Channing-Bete Co.

Greenberg, M., Kusché, C., Cook, E., & Quamma, J. (1995). Promoting emotional competence in school-aged children: The effects of the PATHS curriculum. Development and Psychopathology, 7, 117–136.CrossRef

Han, S., & Weiss, B. (2005). Sustainability of teacher implementation of school-based mental health programs. Journal of Abnormal Child Psychology, 33, 665–679.CrossRefPubMed

Holland, P. W. (1986). Statistics and causal inference. Journal of the American Statistical Association, 81, 945–970.CrossRef

Hulleman, C. S., & Cordray, D. S. (2009). Moving from the lab to the field: The role of fidelity and achieved relative intervention strength. Journal of Research on Educational Effectiveness, 2, 88–110.CrossRef

Ialongo, N., Poduska, J., Werthamer, L., & Kellam, S. (2001). The distal impact of two first-grade preventive interventions on conduct problems and disorder in early adolescence. Journal of Emotional and Behavioral Disorders, 9, 146–160.CrossRef

Ialongo, N., Wethamer, L., Kellam, S., Brown, C., Wang, S., & Lin, Y. (1999). Proximal impact of two first-grade preventive interventions on the early risk behaviors for later substance abuse, depression, and anti-social behavior. American Journal of Community Psychology, 27, 599–641.CrossRefPubMed

Jo, B. (2002). Estimation of intervention effects with noncompliance: Alternative model specifications. Journal of Educational and Behavioral Statistics, 27, 385–409.CrossRef

Jo, B., Asparouhov, T., Muthén, B. O., Ialongo, N. S., & Brown, C. H. (2008). Cluster randomized trials with treatment noncompliance. Psychological Methods, 13, 1–18.CrossRefPubMedPubMedCentral

Jo, B., & Muthén, B. (2003). Longitudinal studies with intervention and noncompliance: Estimation of causal effects in growth mixture modeling. In N. Duan & S. Reise (Eds.), Multilevel modeling: Methodological advances, issues, and applications (pp. 112–139). Mahwah: Lawrence Erlbaum Associates.

Jo, B., Wang, C. P., & Ialongo, N. S. (2009). Using latent outcome trajectory classes in causal inference. Statistics Interface, 2, 403–412.CrossRef

Kellam, S., Brown, C. H., Poduska, J., Ialongo, N., Wang, W., Toyinbo, P., & Wilcox, H. (2008). Effects of a universal classroom behavior management program in first and second grades on young adult behavioral, psychiatric, and social outcomes. Drug and Alcohol Dependence, 95S, S5–S28.CrossRef

Kusché, C. A., Greenberg, M. T., &, & Conduct Problems Prevention Research Group. (2011). Grade level PATHS (Grades 1-2). South Deerfield: Channing-Bete Co.

Little, R. J. A., & Rubin, D. B. (2002). Statistical analysis with missing data. Hoboken: Wiley.CrossRef

Little, R. J. A., & Yau, L. H. Y. (1998). Statistical techniques for analyzing data from prevention trials: Treatment of no-shows using Rubin’s causal model. Psychological Methods, 3, 147–159.CrossRef

Main, S., & Hammond, L. (2008). Best practice or most practiced? Pre-service teachers’ beliefs about effective behavior management strategies and reported self-efficacy. Australian Journal of Teacher Education, 33, 28–39.CrossRef

Maslach, C., Jackson, S. E., & Leiter, M. P. (1997). Maslach burnout inventory. In R. J. Wood (Ed.), Evaluating stress: A book of resources (3rd ed., pp. 191–218). Lanham: Scarecrow Education.

O’Donnell, C. L. (2008). Defining, conceptualizing, and measuring fidelity of implementation and its relationship to outcomes in K-12 curriculum intervention research. Review of Educational Research, 78, 33–84.CrossRef

Pas, E., & Bradshaw, C. P. (2014). What affects teacher ratings of student behaviors? The potential influence of teachers’ perceptions of the school environment and experiences. Prevention Science, 15, 940–950. doi:10.1007/s11121-013-0432-4.CrossRefPubMed

Payne, A. A., & Eckert, R. (2010). The relative importance of provider, program, school, and community predictors of the implementation quality of school-based prevention programs. Prevention Science, 11(2), 126–141.CrossRefPubMed

Ringeisen, H., Henderson, K., & Hoagwood, K. (2003). Context matters: Schools and the “research to practice gap” in children’s mental health. School Psychology Review, 32(2), 153–169.

Rohrbach, L. A., Graham, J. W., & Hansen, W. B. (1993). Diffusion of a school-based substance abuse prevention program: Predictors of program implementation. Preventive Medicine, 22, 237–260.CrossRefPubMed

Schochet, P. Z., Puma, M., & Deke, J. (2014). Understanding variation in treatment effects in education impact evaluations: An overview of quantitative methods (NCEE 2014-4017). Washington, DC: U.S. Department of Education, Institute of Education Sciences, national Center for Education Evaluation and Regional Assistance, Analytic Technical Assistance and Development. Retrieved from http://ies.ed.gov/ncee/edlabs.

Sobel, M. E. (2006). What do randomized studies of housing mobility demonstrate: Causal inference in the face of interference. Journal of the American Statistical Association, 101, 1398–1407.CrossRef

Stanger, C., Ryan, S. R., Fu, H., & Budney, A. J. (2011). Parent training plus contingency management for substance abuse families: A Complier Average Causal Effects (CACE) analysis. Drug and Alcohol Dependence, 118, 119–126. doi:10.1016/j.drugalcdep.2011.03.007.CrossRefPubMedPubMedCentral

Stuart, E. A., Perry, D. F., Le, H., & Ialongo, N. S. (2008). Estimating intervention effects of prevention programs: Accounting for noncompliance. Prevention Science, 9, 288–298. doi:10.1007/s11121-008-0104-y.CrossRefPubMedPubMedCentral

Weiss, M. J., Bloom, H. S., & Brock, T. (2013). A conceptual framework for studying the sources of variation in program effects. MDRC. New York: MDRC.

Title: Using Complier Average Causal Effect Estimation to Determine the Impacts of the Good Behavior Game Preventive Intervention on Teacher Implementers
Authors: Juliette K. Berg
Catherine P. Bradshaw
Booil Jo
Nicholas S. Ialongo
Publication date: 01-07-2017
Publisher: Springer US
Published in: Administration and Policy in Mental Health and Mental Health Services Research / Issue 4/2017
Print ISSN: 0894-587X
Electronic ISSN: 1573-3289
DOI: https://doi.org/10.1007/s10488-016-0738-1

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Using Complier Average Causal Effect Estimation to Determine the Impacts of the Good Behavior Game Preventive Intervention on Teacher Implementers

Abstract

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Please log in to get access to this content

Other articles of this Issue 4/2017

Homeless Caseload is Associated with Behavioral Health and Case Management Staffing in Health Centers

Integrating the Electronic Health Record into Behavioral Health Encounters: Strategies, Barriers, and Implications for Practice

Factors Associated with Clinician Participation in TF-CBT Post-workshop Training Components

Discrepancies in Leader and Follower Ratings of Transformational Leadership: Relationship with Organizational Culture in Mental Health

Juvenile Probation Officer Self-Assessed Mental Health Competency as a Predictor of Case Management Practices

Encounter Preparedness, Satisfaction, and Performance Effects of Influence in Assertive Community Treatment (ACT) Teams