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IES Grant

Title: A Randomized Controlled Trial of the Combination of Two Preventive Interventions
Center: NCER Year: 2008
Principal Investigator: Ialongo, Nicholas Awardee: Johns Hopkins University
Program: Social and Behavioral Context for Academic Learning      [Program Details]
Award Period: 4 years Award Amount: $2,807,781
Goal: Efficacy and Replication Award Number: R305A080326
Description:

Purpose: The Good Behavior Game (GBG) and Promoting Alternative Thinking Strategies (PATHS) are two universal, elementary school preventive interventions that have been shown in large scale, randomized controlled trials to have an immediate and beneficial impact on aggressive/disruptive and off-task behavior. Aggressive/disruptive and off-task behaviors in elementary school are strong indicators of chronically poor academic achievement and later, more serious antisocial behavior. Nonetheless, the effects of the GBG and PATHS on early aggressive/disruptive and off-task behavior have proven modest. The purpose of this project is to examine whether combining these interventions will yield a significantly greater impact on aggressive/disruptive and off-task behavior than the GBG or PATHS alone.

Project Activities: In this project, the research team is conducting a school-based group-randomized trial to evaluate whether combining GBG and PATHS leads to a greater reduction in aggressive/disruptive behavior and time off-task in grades K to 5 than GBG alone or a standard setting (control) condition. PATHS seeks to reduce aggressive/disruptive and off-task behaviors via teacher-led instruction aimed at facilitating emotion regulation (particularly anger management), self-control, social problem-solving, and conflict resolution skills. The GBG is based on social learning principles and provides teachers with an efficient means of managing student aggressive/disruptive and off-task behavior via reinforcement of the inhibition of these behaviors within a game-like context. It is anticipated that the GBG, by increasing attention to current tasks and reducing disruptive behavior in the classroom, may facilitate the acquisition of the emotion regulation, social problem-solving, and conflict resolution skills taught in PATHS. The researchers are employing an extended nested-cohort design, which will feature three study conditions: Standard Setting (Control), versus GBG Alone, versus GBG+PATHS. Nine Maryland public elementary schools will be randomized to each condition for a total of 27 schools.

Products: Products from this project include published reports on the efficacy of combining the Good Behavior Game (GBG) and Promoting Alternative Thinking Strategies (PATHS) for reducing aggressive/disruptive behavior and time off-task among children in Grades K to 5.

Structured Abstract

Setting: The participating schools are located in Maryland.

Population: Twenty-seven Maryland public elementary schools are participating. It is estimated that the researchers will assess a total of 300-336 students per school, the majority of whom will be African-American and economically disadvantaged.

Intervention: PATHS seeks to accomplish reductions in aggressive/disruptive and off-task behaviors via teacher-led instruction aimed at facilitating emotion regulation (particularly anger management), self-control, social problem-solving, and conflict resolution skills. The GBG is based on social learning principles and provides teachers with an efficient means of managing student aggressive/disruptive and off-task behavior via reinforcing the inhibition of these behaviors within a game-like context. It is anticipated that the GBG, by increasing attention to task and reducing disruptive behavior in the classroom, may facilitate the acquisition of the emotion regulation, social problem-solving, and conflict resolution skills taught in PATHS.

Research Designs and Methods: The researchers are employing an extended nested-cohort design, which will feature three study conditions: Standard Setting (Control), versus GBG Alone versus GBG+PATHS. Nine Maryland public elementary schools will be randomly assigned to each condition for a total of 27 schools. The researchers will recruit nine schools in the first year, nine in the second year, and nine in the third year. Each set of nine will have three schools randomized to each of the three conditions. The pretest will be administered in the fall and the posttest in the spring of the year the schools are recruited; follow-up data will be collected each spring through Year 4.

Control Condition: Schools assigned to the control condition will continue business as usual.

Key Measures: Aggressive/disruptive behavior and time off task will be assessed at pretest and posttest using direct observations, peer nominations, and teacher ratings. Other outcomes will be collected annually from archival records, including standardized achievement scores, grades, number of suspensions, office referrals for disciplinary action, and referrals for and/or use of special education.

Data Analytic Strategy: A mixed-model ANCOVA will be used to compare the three conditions on aggressive/disruptive and off-task behavior as observed in the spring with regression adjustment for aggressive/disruptive and off-task behavior as observed in the fall. Condition and the fall disruptive behavior score will be included as fixed effects while school and child will be included as nested random effects.

Related IES Projects: Identifying Predictors of Program Implementation to Inform a Tailored Teacher Coaching Process (R305A130060)

Publications from this project:

Becker, K., and Domitrovich, C. (2011). Conceptualization, Integration, and Supports Of Evidence-Based Interventions In Schools. School Psychology Review, 40: 582–589.

Domitrovich, C.E., Bradshaw, C.P., Greenberg, M.T., Embry, D., Poduska, J.M., and Ialongo, N.S. (2010). Integrated Models Of School-Based Prevention: Logic and Theory. Psychology In The Schools, 47: 71–88.

Jo, B., Ginexi, E., and Ialongo, N. (2010). Handling Missing Data In Randomized Experiments With Noncompliance. Prevention Science, 11:384–396.

Jo, B., Wang, C-P., and Ialongo, N.S. (2009). Using Latent Outcome Trajectory Classes In Causal Inference. Statistics and Its Interface, 2: 403–412.

Reinke, W.M., Herman, K.C., and Ialongo, N.S. (2012). Developing and Implementing Integrated School-Based Mental Health Interventions. Advances In School Mental Health Promotion, 5: 158–160.

Reinke, W.M., Herman, K.C., Darney, D., Pitchford, J., Becker, K., Domitrovich, C., and Ialongo, N. (2012). Using The Classroom Check-Up To Support Implementation Of PATHS To PAX. Advances In School Mental Health Promotion, 5: 220–232.

Stuart, E.A. and Ialongo, N.S. (2010). Matching Methods For Selection Of Subjects For Follow-Up. Multivariate Behavioral Research, 45: 746–765.


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