Investigating strategies to increase general education teachers' adherence to evidence-based social-emotional behavior practices: A meta-analysis of the single-case literature

Abstract

Educational researchers have produced a variety of evidence-based practices (EBP) to address social, emotional, and behavioral (SEB) needs among students. Yet, these practices are often insufficiently adopted and implemented with fidelity by teachers to produce the beneficial outcomes associated with the EBP, leaving students at risk for developing SEB problems. If ignored, SEB problems can lead to other negative outcomes, such as academic failure. Therefore, implementation strategies (i.e., methods and procedures designed to promote implementation outcomes) are needed to improve teachers' uptake and delivery of EBPs with fidelity. This meta-analysis sought to examine the types and magnitude of effect of implementation strategies that have been designed and tested to improve teacher adherence to SEB EBPs. Included studies (a) used single case experimental designs, (b) employed at least one implementation strategy, (c) targeted general education teachers, and (d) evaluated adherence as a core dimension of fidelity related to the delivery of EBPs. In total, this study included 28 articles and evaluated 122 effect sizes. A total of 15 unique implementation strategies were categorized. Results indicated that, on average, implementation strategies were associated with increases in teacher adherence to EBPs above baseline and group-based pre-implementation trainings alone (g = 2.32, tau = 0.77). Moderator analysis also indicated that larger effects were associated with implementation strategies that used a greater number of unique behavior change techniques (p < .001). Implications and future directions for research and practice regarding use of implementation strategies for general education teachers are discussed.

Keywords: Behavior change; Implementation strategies; Mechanism; School-based; Single case; meta-analysis.

Figure 1

PRISMA Flow Chart Note. This diagram depicts the flow of information through the different phases of the systematic review. It maps out the number and source of records identified, included and excluded, and the reasons for exclusions.

Figure 2

Funnel Plots Note. These funnel plots represent the distribution of effect sizes without the trim-and-fill method (left), and a funnel plot including the trim-and-fill method (right). Black dots represent observed datapoints, while white dots represent studies that should be present if publication bias was not observed in the dataset.

Figure 3

Forest Plot of Hedge’s g Effect Sizes for Each Study Note. Larger dots represent a greater precision (i.e. lower variance among participants within the study). Horizontal bands indicate the standard error of each study estimate. These effect sizes represent unweighted averages obtained to make the plot more readable. The diamond shape at the bottom represents the average effect size across studies.

Figure 4

Forest Plot of Tau Effect Sizes for Each Study Note. Effect size limited to 1, which is the upper limit of Tau. Larger dots represent a greater precision (i.e. lower variance among participants within the study). Horizontal bands indicate the standard error of each study estimate. These effect sizes represent unweighted averages obtained to make the plot more readable. The diamond shape at the bottom represents the average effect size across studies.

Figure 5

Relationship of BCTs to Effect Size (Hedge’s g) Note. This plot depicts the total number of BCTs utilized for each participant by their effect size. The loess smoother indicates a nonlinear relationship between effect size and the total number of BCTs used, with a diminishing trend.