Washington State Institute for Public Policy
Cognitive Behavioral Therapy (CBT) for depressed adolescents
Children's Mental Health: Depression
Benefit-cost estimates updated December 2016.  Literature review updated April 2012.
Treatments include various components, such as cognitive restructuring, scheduling pleasant experiences, emotion regulation, communication skills, and problem-solving. Most commonly, studies offering this treatment provided 10-20 therapeutic hours per client in individual or group modality. One well-known example is the Adolescent Coping With Depression (CWD-A) program.
BENEFIT-COST
META-ANALYSIS
CITATIONS
The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2015). 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 $71 Benefits minus costs ($429)
Participants $46 Benefit to cost ratio $0.16
Others $69 Chance the program will produce
Indirect ($105) benefits greater than the costs 38 %
Total benefits $81
Net program cost ($511)
Benefits minus cost ($429)
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
Benefits from changes to:1 Benefits to:
Taxpayers Participants Others2 Indirect3 Total
Crime $0 $0 $1 $0 $1
K-12 grade repetition $0 $0 $0 $0 $0
K-12 special education $3 $0 $0 $2 $5
Labor market earnings associated with major depression $13 $28 $0 $121 $161
Health care associated with major depression $55 $18 $69 $29 $171
Costs of higher education $0 $0 $0 $0 $0
Adjustment for deadweight cost of program $0 $0 $0 ($256) ($256)
Totals $71 $46 $69 ($105) $81
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $1,207 2010 Present value of net program costs (in 2015 dollars) ($511)
Comparison costs $733 2010 Cost range (+ or -) 10 %
We estimated per-participant cost by computing the weighted average treatment hours for this sample of studies (average hours of group and individual therapy reported in the studies), multiplied by the actuarial estimates of reimbursement by modality reported in Mercer. (2013). Behavioral Health Data Book for the State of Washington for Rates Effective January 1, 2014.
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.
Estimated Cumulative Net Benefits Over Time (Non-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 non-discounted dollars to simplify the “break-even” point from a budgeting perspective. 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.

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.

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 Primary or secondary participant 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
Major depressive disorder 11 426 -0.278 0.088 16 0.000 0.024 17 -0.595 0.001
Externalizing behavior symptoms 5 293 -0.015 0.093 17 0.000 0.008 18 -0.039 0.698
Suicide attempts 1 41 0.000 0.215 16 0.000 0.017 17 0.000 1.000
Hospitalization (psychiatric) 1 41 -0.091 0.214 16 0.000 0.019 17 -0.153 0.504
Primary care visits 1 41 -0.086 0.214 16 0.000 0.019 17 -0.135 0.529
Suicidal ideation 2 146 -0.329 0.130 16 0.000 0.029 17 -0.329 0.011
Global functioning 6 390 0.178 0.097 16 0.000 0.016 19 0.230 0.040
Citations Used in the Meta-Analysis

Brent, D.A., Holder, D., Kolko, D., Birmaher, B., Baugher, M., Roth, C., . . . Johnson, B.A. (1997). A clinical psychotherapy trial for adolescent depression comparing cognitive, family, and supportive therapy. Archives of General Psychiatry, 54(9), 877-885.

Clarke, G.N., Rohde, P., Lewinsohn, P.M., Hops, H., & Seeley, J.R. (1999). Cognitive-behavioral treatment of adolescent depression: Efficacy of acute group treatment and booster sessions. Journal of the American Academy of Child & Adolescent Psychiatry, 38(3), 272-279.

Clarke, G.N., Hornbrook, M., Lynch, F., Polen, M., Gale, J., O'Connor, E., . . . Debar, L. (2002). Group cognitive-behavioral treatment for depressed adolescent offspring of depressed parents in a health maintenance organization. Journal of the American Academy of Child & Adolescent Psychiatry, 41(3), 305-313.

Kahn, J.S., Kehle, T.J., Jenson, W.R., & Clark, E. (1990). Comparison of cognitive-behavioral, relaxation, and self-modeling interventions for depression among middle-school students. School Psychology Review, 19(2), 196-211.

Kennard, B., Silva, S., Vitiello, B., Curry, J., Kratochvil, C., Simons, A., et al. (2006). Remission and residual symptoms after short-term treatment in the Treatment of Adolescents with Depression Study (TADS). Journal of the American Academy of Child & Adolescent Psychiatry, 45(12), 1404-1411.

Lewinsohn, P.M., Clarke, G.N., Hops, H. & Andrews, J. (1990). Cognitive-behavioral treatment for depressed adolescents. Behavior Therapy, 21(4), 385-401.

March, J., Silva, S., Petrycki, S., Curry, J., Wells, K., Fairbank, J., et al. (2004). Fluoxetine, cognitive-behavioral therapy, and their combination for adolescents with depression: Treatment for Adolescents With Depression Study (TADS) randomized controlled trial. JAMA, 292(7), 807-820.

Reynolds, W.M., & Coats, K.I. (1986). A comparison of cognitive-behavioral therapy and relaxation training for the treatment of depression in adolescents. Journal of Consulting and Clinical Psychology, 54(5), 653-660.

Rohde, P., Clarke, G.N., Mace, D.E., Jorgensen, J.S., & Seeley, J.R. (2004). An efficacy/effectiveness study of cognitive-behavioral treatment for adolescents with comorbid major depression and conduct disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 43(6), 660-668.

Rossello, J., Bernal, G. (1999). The efficacy of cognitive-behavioral and interpersonal treatments for depression in Puerto Rican adolescents. Journal of Consulting and Clinical Psychology, 67(5), 734-745.

Vitiello, B., Rohde, P., Silva, S., Wells, K., Casat, C., Waslick, B., et al. (2006). Functioning and quality of life in the Treatment for Adolescents with Depression Study (TADS). Journal of the American Academy of Child & Adolescent Psychiatry, 45(12), 1419-1426.

Vostanis, P., Feehan, C., Grattan, E., & Bickerton, W.L. (1996). Treatment for children and adolescents with depression: Lessons from a controlled trial. Clinical Child Psychology and Psychiatry, 1(2), 199-212.

Vostanis, P., Feehan, C., & Grattan, E. (1998). Two-year outcome of children treated for depression. European Child & Adolescent Psychiatry, 7(1), 12-8.

Wood, A., Harrington, R., & Moore, A. (1996). Controlled trial of a brief cognitive-behavioural intervention in adolescent patients with depressive disorders. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 37(6), 737-746.

For more information on the methods
used please see our Technical Documentation.
360.664.9800
institute@wsipp.wa.gov