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Washington State Institute for Public Policy
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Family Check-Up (also known as Positive Family Support)

Public Health & Prevention: Home- or Family-based
Benefit-cost methods last updated December 2018.  Literature review updated June 2014.
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Positive Family Support/Family Check-Up (formerly Adolescent Transitions Program) is a three-tiered intervention implemented in middle schools. The first level is a universal component that involves the establishment of a family resource center and a six-week prevention curriculum. The second tier is Family Check-Up, an assessment and brief motivational interview component for students identified as at-risk. The third tier is the Family Intervention Menu, which directs parents of substance-using adolescents to treatment options, parenting groups, and family therapy sessions. Our review is of the entire Positive Family Support model and not solely the second tier Family Check-Up component.
The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2017). 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 $99 Benefits minus costs ($127)
Participants $4 Benefit to cost ratio $0.62
Others $224 Chance the program will produce
Indirect ($116) benefits greater than the costs 49 %
Total benefits $211
Net program cost ($339)
Benefits minus cost ($127)
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 $88 $0 $213 $47 $348
K-12 grade repetition $0 $0 $0 $0 $0
K-12 special education $3 $0 $0 $2 $5
Property loss associated with alcohol abuse or dependence $0 $1 $3 $0 $4
Labor market earnings associated with major depression $0 $0 $0 $0 $0
Health care associated with externalizing behavior symptoms $8 $2 $9 $5 $24
Mortality associated with depression $0 $0 $0 $0 $0
Adjustment for deadweight cost of program $0 $0 $0 ($170) ($170)
Totals $99 $4 $224 ($116) $211
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $164 2013 Present value of net program costs (in 2017 dollars) ($339)
Comparison costs $0 2013 Cost range (+ or -) 10 %
This program is typically delivered over a two-year period. The cost estimate includes training, materials, and setup costs obtained from Blueprints for Healthy Youth Development ( The estimate also includes compensation costs for a half-time (0.5 FTE) intervention/family resource staff member. To calculate a per-student annual cost, we divide the implementation and staff costs by the number of students in a middle school in Washington’s Prototypical School model.
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.

^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.

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
Alcohol use in high school 12 1 500 -0.017 0.152 18 -0.017 0.152 18 -0.050 0.741
Alcohol use before end of middle school 12 1 386 -0.116 0.208 13 -0.116 0.208 14 -0.350 0.092
Cannabis use in high school 12 1 500 -0.041 0.152 18 -0.041 0.152 18 -0.126 0.410
Cannabis use before end of middle school 12 1 386 -0.101 0.208 13 -0.101 0.208 14 -0.305 0.142
Crime 12 1 500 -0.013 0.152 18 -0.013 0.152 28 -0.039 0.797
Externalizing behavior symptoms 12 1 500 -0.004 0.152 17 -0.002 0.091 20 -0.012 0.939
Grade point average^ 12 1 500 -0.020 0.152 18 n/a n/a n/a -0.062 0.685
Major depressive disorder 12 1 52 -0.098 0.468 15 0.000 0.039 16 -0.296 0.527
Smoking in high school 12 1 500 -0.048 0.152 14 -0.048 0.152 18 -0.145 0.342
Smoking before end of middle school 12 1 386 -0.240 0.208 13 -0.240 0.208 14 -0.727 0.001

Citations Used in the Meta-Analysis

Connell, A.M., & Dishion, T.J. (2008). Reducing depression among at-risk early adolescents: three-year effects of a family-centered intervention embedded within schools. Journal of Family Psychology (division 43), 22(4), 574-85.

Connell, A.M., Dishion, T.J., Yasui, M., & Kavanagh, K. (2007). An adaptive approach to family intervention: linking engagement in family-centered intervention to reductions in adolescent problem behavior. Journal of Consulting Clinical Psychology, 75, 568-579.

Stormshak, E.A., Connell, A., & Dishion, T.J. (2009). An adaptive approach to family-centered intervention in schools: Linking intervention engagement to academic outcomes in middle and high school. Prevention Science, 10(3), 221-235.

Stormshak, E.A., Connell, A.M., Veronneau, M.H., Myers, M.W., Dishion, T.J., Kavanagh, K., & Caruthers, A.S. (2011). An ecological approach to promoting early adolescent mental health and social adaptation: Family-centered intervention in public middle schools. Child Development, 82(1), 209-225.

Van, R.M.J., & Dishion, T.J. (2012). The impact of a family-centered intervention on the ecology of adolescent antisocial behavior: modeling developmental sequelae and trajectories during adolescence. Development and Psychopathology, 24(3), 1139-55.