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The Impact of Enhancing Students' Social and Emotional Learning: A Meta-Analysis of School-Based Universal Interventions

Child development, 2011-01, Vol.82 (1), p.405-432

2011

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Predictors of Co-Occurring Risk Behavior Trajectories Among Economically Disadvantaged African-American Youth: Contextual and Individual Factors

Journal of adolescent health, 2014-09, Vol.55 (3), p.380-387

2014

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Clustering Methods with Qualitative Data: a Mixed-Methods Approach for Prevention Research with Small Samples

Prevention science, 2015-10, Vol.16 (7), p.1007-1016

2015

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Moderating Effects of School Climate on Outcomes for the Multisite Violence Prevention Project Universal Program

Journal of research on adolescence, 2014-06, Vol.24 (2), p.383-398

Dymnicki, Allison B.

2014

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Assessing Implementation and Effects Associated with a Comprehensive Framework Designed to Reduce School Violence: A Randomized Controlled Trial

Journal of school violence, 2021-10, Vol.20 (4), p.458-470

2021

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Supporting Local Health Departments to Lead Multisectoral Youth Violence Prevention Efforts

Health promotion practice, 2021-11, Vol.22 (6), p.863-872

2021

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Influence of school-level variables on aggression and associated attitudes of middle school students

Journal of school psychology, 2011-10, Vol.49 (5), p.481-503

2011

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Effects of positive youth development programs on school, family, and community systems

American journal of community psychology, 2007-06, Vol.39 (3-4), p.269-286

2007

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OUTREACH WORKERS' PERCEPTIONS OF POSITIVE AND NEGATIVE CRITICAL INCIDENTS: CHARACTERISTICS ASSOCIATED WITH SUCCESSFUL AND UNSUCCESSFUL VIOLENCE INTERRUPTION

Journal of community psychology, 2013-03, Vol.41 (2), p.200-217

2013

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Levels and growth of specific and general norms for nonviolence among middle school students

Journal of adolescence (London, England.), 2011-10, Vol.34 (5), p.965-976

2011

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The development of an instrument to measure school readiness for a prevention program

Learning environments research, 2015-07, Vol.18 (2), p.267-287

2015

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Middle school students overestimate normative support for aggression and underestimate normative support for nonviolent problem‐solving strategies

Journal of applied social psychology, 2013-02, Vol.43 (2), p.433-445

2013

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Developing a Federal Research Agenda for Positive Youth Development: Identifying Gaps in the Field and an Effective Consensus Building Approach

Journal of youth development (Online), 2016-12, Vol.11 (1), p.5-19

2016

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Understanding How Programs Work to Prevent Overt Aggressive Behaviors: A Meta-analysis of Mediators of Elementary School-Based Programs

Journal of school violence, 2011-10, Vol.10 (4), p.315-337

2011

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Use of Clustering Methods to Understand More about the Case

Methodological innovations online, 2011-08, Vol.6 (2), p.6-26

2011

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Empirical Evidence of Social and Emotional Learning's Influence on School Success: A Commentary on "Building Academic Success on Social and Emotional Learning: What Does the Research Say?," a book edited by Joseph E. Zins, Roger P. Weissberg, Margaret C. Wang, and Herbert J. Walberg

Journal of educational and psychological consultation, 2007-07, Vol.17 (2-3), p.225-231

2007

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Middle school students overestimate normative support for aggression and underestimate normative support for nonviolent problem-solving strategies

Journal of applied social psychology, 2013-02, Vol.43 (2), p.433-445

2013

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The Impact of Enhancing Students' Social and Emotional Learning: A Meta-Analysis of School-Based Universal Interventions: Raising Healthy Children

Child development, 2011, Vol.82 (1), p.405-432

2011

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Community Monitoring for Youth Violence Surveillance: Testing a Prediction Model

Prevention science, 2014-08, Vol.15 (4), p.437-447

2014

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The Impact of Enhancing Students' Social and Emotional Learning: A Meta-Analysis of School-Based Universal Interventions

Predictors of Co-Occurring Risk Behavior Trajectories Among Economically Disadvantaged African-American Youth: Contextual and Individual Factors

Clustering Methods with Qualitative Data: a Mixed-Methods Approach for Prevention Research with Small Samples

Moderating Effects of School Climate on Outcomes for the Multisite Violence Prevention Project Universal Program

Assessing Implementation and Effects Associated with a Comprehensive Framework Designed to Reduce School Violence: A Randomized Controlled Trial

Supporting Local Health Departments to Lead Multisectoral Youth Violence Prevention Efforts

Influence of school-level variables on aggression and associated attitudes of middle school students

Effects of positive youth development programs on school, family, and community systems

OUTREACH WORKERS' PERCEPTIONS OF POSITIVE AND NEGATIVE CRITICAL INCIDENTS: CHARACTERISTICS ASSOCIATED WITH SUCCESSFUL AND UNSUCCESSFUL VIOLENCE INTERRUPTION

Levels and growth of specific and general norms for nonviolence among middle school students

The development of an instrument to measure school readiness for a prevention program

Middle school students overestimate normative support for aggression and underestimate normative support for nonviolent problem‐solving strategies

Developing a Federal Research Agenda for Positive Youth Development: Identifying Gaps in the Field and an Effective Consensus Building Approach

Understanding How Programs Work to Prevent Overt Aggressive Behaviors: A Meta-analysis of Mediators of Elementary School-Based Programs

Use of Clustering Methods to Understand More about the Case

Empirical Evidence of Social and Emotional Learning's Influence on School Success: A Commentary on "Building Academic Success on Social and Emotional Learning: What Does the Research Say?," a book edited by Joseph E. Zins, Roger P. Weissberg, Margaret C. Wang, and Herbert J. Walberg

Middle school students overestimate normative support for aggression and underestimate normative support for nonviolent problem-solving strategies

The Impact of Enhancing Students' Social and Emotional Learning: A Meta-Analysis of School-Based Universal Interventions: Raising Healthy Children

Community Monitoring for Youth Violence Surveillance: Testing a Prediction Model

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