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IES Grant

Title: Comprehensive Meta-analysis of Malleable Factors to Support Youth with ADHD
Center: NCSER Year: 2016
Principal Investigator: Fabiano, Gregory Awardee: State University of New York (SUNY), Buffalo
Program: Social, Emotional, and Behavioral Competence      [Program Details]
Award Period: 2 years (7/1/2016-6/30/2018) Award Amount: $699,270
Type: Exploration Award Number: R324A160133
Description:

Co-Principal Investigators: William Pelham, Nicole Schatz, and Stephany Coxe (Florida International University); Ariel Aloe (University of Iowa)

Purpose: The purpose of this research is to conduct a comprehensive meta-analysis of school-based intervention treatment studies to understand which intervention practices are associated with positive outcomes for students with ADHD. Attention-deficit/hyperactivity disorder (ADHD) is a chronic disorder that results in considerable social, occupational, and academic problems for youth and their families. Unfortunately, there is considerable disagreement among professionals regarding the best interventions to recommend for students with ADHD. Professionals do not have clear guidance to help them make recommendations, as there are discrepant findings among systematic reviews and meta-analyses as well as conflicting and confusing policy documents regarding the most appropriate interventions for these students. This project aims to fill this gap by conducting a comprehensive meta-analysis of all of ADHD school-based treatment studies in the literature. In addition to examining practices associated with positive outcomes, the team will also investigate moderators of ADHD treatment effects, such as type of school-based treatment and setting where treatment takes place, and conduct analyses to best integrate research results from divergent research designs represented within the literature (i.e., between-group, crossover, and single-case designs). Ultimately this will allow practitioners to better plan and implement interventions that work for youth with ADHD in school settings.

Project Activities: From databases of published research, the research team will retrieve all of the non-pharmacological studies of ADHD treatment outcomes conducted in school settings. Studies will be coded for quality, outcomes, and presence of potential moderating factors (e.g., whether intervention included parent training). The research team will evaluate both academic and social/behavioral outcomes. To address the anticipated diversity of study designs, measures used, and malleable factors assessed within the larger literature, a variety of innovative methods will be used to best synthesize the literature and compare intervention results across research studies.

Products: The expected products from this study include results from a completed meta-analysis describing which intervention practices are associated with positive outcomes for students with ADHD, as well as publications and presentations on research findings.

Structured Abstract

Setting: This project will include studies conducted in school settings (e.g., center-based preschool or K–12 settings) from 1966 to the present.

Sample: The studies included in this meta-analysis are those that target students under 18 years of age who are diagnosed with ADHD or sufficiently well-described to suggest the characteristic behaviors of ADHD (e.g., "hyperactive," "off-task"). In studies that focus on treatment for children with externalizing behavior problems (e.g., aggressive behavior), over 50% of the participants must be diagnosed with ADHD or characterized as such. Students must have a reported IQ at or above 70 and their condition cannot be better explained by a documented organic cause (e.g., brain trauma).

Intervention: There is no specific intervention under investigation. This research will explore any type of non-pharmacological, school-based treatment that aims to improve academic and/or social outcomes for students with ADHD.

Research Design and Methods: Researchers will use meta-analysis, a method of quantitative research synthesis that uses prior study results as the unit of observation. Researchers will use the following five techniques to identify studies to include in this meta-analysis: (1) literature searches using major search engines (e.g., PsycInfo, ERIC, and Medline); (2) searches of tables of contents in journals known to publish school-based treatment studies; (3)dissertation search in the ProQuest Dissertation Database; (4) contacts with researchers known to conduct school-based treatment studies on children with ADHD; and (5) search of the online database of funded Institute of Education Sciences grants. Studies will be included if they (1) contain information that would permit the calculation of effect sizes (or researchers can contact the study's primary authors to obtain this information); (2) target a psychosocial/educational, school-based intervention or treatment, broadly defined, that aims to improve academic/social outcomes (medication-only studies will be excluded); and (3) are primarily treatment-outcome studies (laboratory investigations will be excluded).

Control Condition: Due to the nature of the research design, there is no control group.

Key Measures: The outcomes in this meta-analysis are the effect sizes for each eligible study. The type of effect size depends on the design as well as nature of the primary study dependent variable. When available, the team will estimate effect sizes from means and standard divisions. When necessary, effect sizes will be estimated from other statistics reported in primary studies as well as transformed into the d metric.

Data Analytic Strategy: Researchers will combine meta-analytic methods with hierarchical linear modeling. The team will also code each study for methods, units, treatment, observations, and settings in addition to using data needed to examine effect sizes. Data analytic strategies will include the calculation of effect size estimates from single-case design studies, the generation of effect sizes using standardized mean change, calculation of group design effect sizes, and the utilization of network analysis (an extension of meta-analysis methods that allows the direct and indirect comparison of two or more interventions).


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