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Multimodal therapy (MMT) for children with disruptive behavior

Children's Mental Health: Disruptive Behavior
Benefit-cost methods last updated December 2023.  Literature review updated July 2018.
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Multimodal therapy (MMT) is a specific therapeutic strategy for children with disruptive behavior disorders. MMT targets different “modalities” of a child’s personality through psychosocial interventions that may include the child, their parents, or their teachers. MMT typically takes place in more than one setting (home, school, or community). In this analysis, all studies utilize either a behavioral or cognitive-behavioral model. Interventions included in our review varied in both intensity (multiple times per day to biweekly) and duration (three months to 2.5 years). Typical dosage is weekly sessions for nine months. Programs that last longer than average were administered to children over the course of several years of elementary school and focus on providing intervention during summer breaks.
For an overview of WSIPP's Benefit-Cost Model, please see this guide. The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2022). The chance the benefits exceed the costs are derived from a Monte Carlo risk analysis. The details on this, as well as the economic discount rates and other relevant parameters are described in our Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $3,238 Benefits minus costs $11,304
Participants $6,451 Benefit to cost ratio $7.06
Others $4,148 Chance the program will produce
Indirect ($666) benefits greater than the costs 58%
Total benefits $13,170
Net program cost ($1,866)
Benefits minus cost $11,304

^WSIPP’s benefit-cost model does not monetize this outcome.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic in order to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the types of program impacts that were measured in the research literature (for example, crime or educational attainment). Treatment N represents the total number of individuals or units in the treatment group across the included studies.

An effect size (ES) is a standard metric that summarizes the degree to which a program or policy affects a measured outcome. If the effect size is positive, the outcome increases. If the effect size is negative, the outcome decreases. See Estimating Program Effects Using Effect Sizes for additional information.

Adjusted effect sizes are used to calculate the benefits from our benefit cost model. WSIPP may adjust effect sizes based on methodological characteristics of the study. For example, we may adjust effect sizes when a study has a weak research design or when the program developer is involved in the research. The magnitude of these adjustments varies depending on the topic area.

WSIPP may also adjust the second ES measurement. Research shows the magnitude of some effect sizes decrease over time. For those effect sizes, we estimate outcome-based adjustments which we apply between the first time ES is estimated and the second time ES is estimated. We also report the unadjusted effect size to show the effect sizes before any adjustments have been made. More details about these adjustments can be found in our Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured Treatment age No. of effect sizes Treatment N Adjusted effect sizes(ES) and standard errors(SE) used in the benefit - cost analysis Unadjusted effect size (random effects model)
First time ES is estimated Second time ES is estimated
ES SE Age ES SE Age ES p-value
9 2 70 0.096 0.176 10 0.063 0.194 17 0.132 0.456
9 1 40 -0.019 0.221 9 0.000 0.141 10 -0.083 0.706
9 1 40 0.031 0.221 9 0.012 0.107 10 0.135 0.647
9 1 40 0.000 0.294 9 0.000 0.310 11 0.000 1.000
9 5 195 -0.081 0.109 10 -0.045 0.068 13 -0.270 0.157
9 1 64 0.951 0.182 9 n/a n/a n/a 0.951 0.001
9 3 127 -0.222 0.182 9 -0.222 0.182 11 -0.260 0.115
1In addition to the outcomes measured in the meta-analysis table, WSIPP measures benefits and costs estimated from other outcomes associated with those reported in the evaluation literature. For example, empirical research demonstrates that high school graduation leads to reduced crime. These associated measures provide a more complete picture of the detailed costs and benefits of the program.

2“Others” includes benefits to people other than taxpayers and participants. Depending on the program, it could include reductions in crime victimization, the economic benefits from a more educated workforce, and the benefits from employer-paid health insurance.

3“Indirect benefits” includes estimates of the net changes in the value of a statistical life and net changes in the deadweight costs of taxation.
Detailed Monetary Benefit Estimates Per Participant
Affected outcome: Resulting benefits:1 Benefits accrue to:
Taxpayers Participants Others2 Indirect3 Total
Test scores Labor market earnings associated with test scores $3,062 $7,214 $3,802 $0 $14,079
Disruptive behavior disorder symptoms Criminal justice system $21 $0 $53 $11 $84
K-12 special education $224 $0 $0 $112 $336
Health care associated with disruptive behavior disorder $334 $94 $345 $167 $940
Major depressive disorder Mortality associated with depression $0 $0 $0 $0 $0
Anxiety disorder K-12 grade repetition ($2) $0 $0 ($1) ($2)
Labor market earnings associated with anxiety disorder ($358) ($844) $0 $0 ($1,202)
Health care associated with anxiety disorder ($50) ($14) ($51) ($25) ($140)
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($930) ($925)
Totals $3,238 $6,451 $4,148 ($666) $13,170
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Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $2,501 2015 Present value of net program costs (in 2022 dollars) ($1,866)
Comparison costs $868 2010 Cost range (+ or -) 50%
These interventions vary in length, with a typical length of nine months. We estimate per-participant costs based on weighted average of 57 hours of therapist time, as reported in the treatment studies. Hourly therapist cost is based on the actuarial estimates of reimbursement by modality (Mercer. (2016). Mental health and substance use disorder services data book for the state of Washington). For comparison group costs we use 2010 Washington State DSHS data to estimate the average reimbursement rate for treatment of child and adolescent disruptive behavior disorders.
The figures shown are estimates of the costs to implement programs in Washington. The comparison group costs reflect either no treatment or treatment as usual, depending on how effect sizes were calculated in the meta-analysis. The cost range reported above reflects potential variation or uncertainty in the cost estimate; more detail can be found in our Technical Documentation.
Benefits Minus Costs
Benefits by Perspective
Taxpayer Benefits by Source of Value
Benefits Minus Costs Over Time (Cumulative Discounted Dollars)
The graph above illustrates the estimated cumulative net benefits per-participant for the first fifty years beyond the initial investment in the program. We present these cash flows in discounted dollars. If the dollars are negative (bars below $0 line), the cumulative benefits do not outweigh the cost of the program up to that point in time. The program breaks even when the dollars reach $0. At this point, the total benefits to participants, taxpayers, and others, are equal to the cost of the program. If the dollars are above $0, the benefits of the program exceed the initial investment.

Citations Used in the Meta-Analysis

Barkley, R.A., Shelton, T.L., Crosswait, C., Moorehouse, M., Fletcher, K., Barrett, S., . . . Metevia, L. (2000). Multi-method psycho-educational intervention for preschool children with disruptive behavior: Preliminary results at post-treatment. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 41(3), 319-332.

Guzder, J., Paisley, V., Hickling, F.W., & Robertson-Hickling, H. (2013). Promoting resilience in high-risk children in Jamaica: A pilot study of a multimodal intervention. Journal of the Canadian Academy of Child and Adolescent Psychiatry, 22(2), 125-130.

Masi, G., Milone, A., Paciello, M., Lenzi, F., Muratori, P., Manfredi, A., . . . Muratori, F. (2014). Efficacy of a multimodal treatment for disruptive behavior disorders in children and adolescents: Focus on internalizing problems. Psychiatry Research, 219(3), 617-624.

Van de Wiel, N.M.H., Matthys, W., Cohen-Kettenis, P.T., Maassen, G.H., Lochman, J.E., & van Engeland, H. (2007). The effectiveness of an experimental treatment when compared to care as usual depends on the type of care as usual. Behavior Modification, 31(3), 298- 312.

Walker, H.M., Kavanagh, K., Stiller, B., Golly, A., Severson, H.H., & Feil, E.D. (1998). First step to success: An early intervention approach for preventing school antisocial behavior. Journal of Emotional and Behavioral Disorders, 6(2), 66-80.