Allison B. Dymnicki

The impact of enhancing students' social and emotional learning: a meta-analysis of school-based universal interventions

This article presents findings from a meta-analysis of 213 school-based, universal social and emotional learning (SEL) programs involving 270,034 kindergarten through high school students. Compared to controls, SEL participants demonstrated significantly improved social and emotional skills, attitudes, behavior, and academic performance that reflected an 11-percentile-point gain in achievement. School teaching staff successfully conducted SEL programs. The use of 4 recommended practices for developing skills and the presence of implementation problems moderated program outcomes. The findings add to the growing empirical evidence regarding the positive impact of SEL programs. Policy makers, educators, and the public can contribute to healthy development of children by supporting the incorporation of evidence-based SEL programming into standard educational practice.

A Meta-analysis of the Impact of Service-Learning on Students

Service-learning (SL) has become a popular teaching method everywhere from elementary schools to colleges. Despite the increased presence of SL in the education world, it is still unclear what student outcomes are associated with SL programs and what factors are related to more effective programs. A meta-analysis of 62 studies involving 11,837 students indicated that, compared to controls, students participating in SL programs demonstrated significant gains in five outcome areas: attitudes toward self, attitudes toward school and learning, civic engagement, social skills, and academic performance. Mean effects ranged from 0.27 to 0.43. Furthermore, as predicted, there was empirical support for the position that following certain recommended practices—such as linking to curriculum, voice, community involvement, and reflection—was associated with better outcomes. Current data should be gratifying for educators who incorporate SL into their courses, and should encourage more SL research to understand how students benefit and what conditions foster their growth and development.

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

This study sought to understand school-level influences on aggressive behavior and related social cognitive variables. Participants were 5106 middle school students participating in a violence prevention project. Predictors were school-level norms opposing aggression and favoring nonviolence, interpersonal climate (positive student-teacher relationships and positive student-student relationships), and school responsiveness to violence (awareness and reporting of violence and school safety problems). Outcomes were individual-level physical aggression, beliefs supporting aggression, and self-efficacy for nonviolent responses. School norms and both interpersonal climate variables had effects on all three outcomes in theorized directions. Only one of the responsiveness measures, awareness and reporting of violence, had theoretically consistent effects on all outcomes. The other, school safety problems, affected self-efficacy later in middle school. Evidence of gender moderation was generally consistent with greater influence of school-level factors on female adolescents. Discussion focuses on implications in light of previous research and intervention possibilities.

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

Several recent meta-analyses of universal school-based violence prevention studies indicate the overall positive impacts of these approaches on aggression. These studies, however, assess impacts on broadly defined measures of aggression. Furthermore, little research has analyzed the mechanisms through which these programs attempt to reduce overt aggressive behavior. The current study analyzed overall impacts on a more narrowly defined outcome—overt aggressive behavior—and identified associated mediators in 36 universal prevention studies conducted with kindergarten through fifth-grade students. Programs were associated with a significant, although small, reduction in overt aggression behavior. Three types of mediators were identified: measures of skill acquisition, social-cognitive processes, and classroom characteristics. Using MacKinnons joint significance test to test for mediation, four measures of skill acquisition, two measures of social cognitive, and one measure of classroom characteristics were identified as significant mediating variables. Implications for the design of effective violence prevention programs and mediators to assess in future research are discussed.

Trajectories of multiple adolescent health risk behaviors in a low-income African American population.

This study examined interdependent trajectories of sexual risk, substance use, and conduct problems among 12- to 18-year-old African American youths who were followed annually as part of the Mobile Youth Study. We used growth mixture modeling to model the development of these three outcomes in the 1,406 participants who met the inclusion criteria. Results indicate that there were four distinct classes: normative, low risk (74.3% of sample); increasing high-risk takers (11.9%); adolescent-limited conduct problems and drug risk with high risky sex (8.0%); and early experimenters (5.8%) The higher risk classes had higher rates of pregnancy and sexually transmitted infections diagnoses than the normative sample at each of the ages we examined. Differing somewhat from our hypothesis, all of the nonnormative classes exhibited high sexual risk behavior. Although prevention efforts should be focused on addressing all three risk behaviors, the high rate of risky sexual behavior in the 25% of the sample that fall into the three nonnormative classes underscores an urgent need for improved sex education, including teen pregnancy and HIV/sexually transmitted infections prevention, in this community.

Use of Clustering Methods to Understand More about the Case

During the past seventy years, the field of cluster analysis has emerged, accompanied by a plethora of methods, algorithms, concepts, and terminology that are used in cluster-related research. We refer to cluster analysis (CA) as a general approach composed of several multivariate methods for delineating natural groups or clusters in data sets. In this paper, we describe the ability of CA to provide rich information about the individual case and highlight potential underlying social processes. First, we discuss the theory behind CA as well as differentiate between more and less familiar clustering approaches. Second, we illustrate the value of less familiar clustering techniques by comparing the results of a four wave growth mixture model of family variables versus clustering the same data with a more familiar two-step approach. The growth mixture modelling approach suggested a one-class cluster solution where all families shared similar growth trajectories in parenting practices and family relationship characteristics. However the two-step clustering approach suggested a four-class solution. Finally, we describe ways that CA allows researchers to model processes whose outcomes are the results of a combination of multiple factors and additional benefits of less familiar clustering methods.

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

Qualitative methods potentially add depth to prevention research but can produce large amounts of complex data even with small samples. Studies conducted with culturally distinct samples often produce voluminous qualitative data but may lack sufficient sample sizes for sophisticated quantitative analysis. Currently lacking in mixed-methods research are methods allowing for more fully integrating qualitative and quantitative analysis techniques. Cluster analysis can be applied to coded qualitative data to clarify the findings of prevention studies by aiding efforts to reveal such things as the motives of participants for their actions and the reasons behind counterintuitive findings. By clustering groups of participants with similar profiles of codes in a quantitative analysis, cluster analysis can serve as a key component in mixed-methods research. This article reports two studies. In the first study, we conduct simulations to test the accuracy of cluster assignment using three different clustering methods with binary data as produced when coding qualitative interviews. Results indicated that hierarchical clustering, K-means clustering, and latent class analysis produced similar levels of accuracy with binary data and that the accuracy of these methods did not decrease with samples as small as 50. Whereas the first study explores the feasibility of using common clustering methods with binary data, the second study provides a “real-world” example using data from a qualitative study of community leadership connected with a drug abuse prevention project. We discuss the implications of this approach for conducting prevention research, especially with small samples and culturally distinct communities.

Community monitoring for youth violence surveillance: testing a prediction model.

Predictive epidemiology is an embryonic field that involves developing informative signatures for disorder and tracking them using surveillance methods. Through such efforts assistance can be provided to the planning and implementation of preventive interventions. Believing that certain minor crimes indicative of gang activity are informative signatures for the emergence of serious youth violence in communities, in this study we aim to predict outbreaks of violence in neighborhoods from pre-existing levels and changes in reports of minor offenses. We develop a prediction equation that uses publicly available neighborhood-level data on disorderly conduct, vandalism, and weapons violations to predict neighborhoods likely to have increases in serious violent crime. Data for this study were taken from the Chicago Police Department ClearMap reporting system, which provided data on index and non-index crimes for each of the 844 Chicago census tracts. Data were available in three month segments for a single year (fall 2009, winter, spring, and summer 2010). Predicted change in aggravated battery and overall violent crime correlated significantly with actual change. The model was evaluated by comparing alternative models using randomly selected training and test samples, producing favorable results with reference to overfitting, seasonal variation, and spatial autocorrelation. A prediction equation based on winter and spring levels of the predictors had area under the curve ranging from .65 to .71 for aggravated battery, and .58 to .69 for overall violent crime. We discuss future development of such a model and its potential usefulness in violence prevention and community policing.

Adolescent Development for Students with Learning Disabilities and Behavioral Disorders: The Promise of Social Emotional Learning

Although a large body of research has focused on young children with learning disabilities (LD) and behavioral disorders (BD) in preschool and elementary school settings, there is considerably less information about this population during adolescence. Recent work suggests that youth with these disabilities experience challenges in areas such as social skills, increased depressive symptoms, and involvement in the juvenile justice system. In addition, for a small percentage of the population, negative outcomes experienced during early childhood appear to persist in adolescence and early adulthood suggesting the need for additional interventions. Two primary aims guide the current chapter. First, we review key domains of adolescent development (social, emotional, and behavioral) and highlight ways in which development differs for students with LD and BD. Second, we introduce the field of social and emotional learning (SEL) and the accumulating body of research that suggests that this approach could have numerous benefits for this population. We describe the results of recent meta-analytic reviews of SEL programs to indicate the current state of the field, highlight a few evidence-based universal and indicated SEL programs for secondary school settings, and describe important areas for future research.

Building Schools’ Readiness to Implement a Comprehensive Approach to School Safety

Research consistently finds that a comprehensive approach to school safety, which integrates the best scientific evidence and solid implementation strategies, offers the greatest potential for preventing youth violence and promoting mental and behavioral health. However, schools and communities encounter enormous challenges in articulating, synthesizing, and implementing all the complex aspects of a comprehensive approach to school safety. This paper aims to bridge the gap between scientific evidence and the application of that evidence in schools and communities by defining the key components of a comprehensive approach to school safety and describing how schools can assess their readiness to implement a comprehensive approach. We use readiness and implementation data from the Safe Communities Safe Schools project to illustrate these challenges and solutions. Our findings suggest that (1) readiness assessment can be combined with feasibility meetings to inform school selection for implementation of a comprehensive approach to school safety and (2) intentionally addressing readiness barriers as part of a comprehensive approach may lead to improvements in readiness (motivation and capacity) to effectively implement a comprehensive approach to school safety.