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Positive Family Support/Family Check-Up

Public Health & Prevention: Home- or Family-based
Benefit-cost methods last updated December 2019.  Literature review updated February 2019.
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Positive Family Support/Family Check-Up (formerly Adolescent Transitions Program) is a three-tiered general prevention program implemented in middle schools. The first level is a universal school component that establishes a family resource center available to students and families. A six-week prevention curriculum delivered to students introduces them to this resource. The second and third tiers provide more intensive services targeted to students with behavioral or emotional problems. The central component of these targeted services is the Family Check-Up, which includes a family assessment and motivational interviewing. Parents may also receive referrals to community services.

Because the intervention is tailored to the needs and risks of participants, participating families may receive varying amounts of services. On average, families receiving the Family Check-Up received between 6 and 12 hours of intervention services. This analysis includes evaluations of the entire three-tier Positive Family Support model and not solely the Family Check-Up component. The program can be delivered by a variety of school staff, including school counselors, school psychologists, school social workers, administrators, teachers, etc.
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 (2018). 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 $2,798 Benefits minus costs $8,886
Participants $5,209 Benefit to cost ratio $197.50
Others $424 Chance the program will produce
Indirect $500 benefits greater than the costs 70 %
Total benefits $8,931
Net program cost ($45)
Benefits minus cost $8,886
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 $36 $0 $89 $18 $144
Labor market earnings associated with test scores ($255) ($599) ($316) $0 ($1,170)
K-12 grade repetition $0 $0 $0 $0 $0
K-12 special education $5 $0 $0 $3 $8
Health care associated with smoking $616 $174 $636 $308 $1,734
Labor market earnings associated with alcohol abuse or dependence $2,391 $5,616 $0 $0 $8,006
Property loss associated with alcohol abuse or dependence $0 $8 $15 $0 $22
Mortality associated with smoking $5 $11 $0 $194 $209
Adjustment for deadweight cost of program $0 $0 $0 ($23) ($23)
Totals $2,798 $5,209 $424 $500 $8,931
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $23 2018 Present value of net program costs (in 2018 dollars) ($45)
Comparison costs $0 2018 Cost range (+ or -) 30 %
The average per-family cost includes the cost of providing training and materials to teachers, and the cost of program-related teacher and staff time that occurs outside of regular school hours. We estimate the average total hours of services provided to each family who received Family Check-Up, as reported in the included studies. We assume that one eighth of the total hours per family were provided outside of the normal school day. We apply the mean hourly wage for relevant providers to this portion of the total. The provider wage is an average of several types of school staff personnel (including administrators, teachers, counselors, social workers, psychologists, and aides) expected to deliver the intervention, weighted by their average FTE in Washington State. Their wages were calculated from Washington State compensation costs (including benefits) for the 2017-18 school year as reported by the Office of the Superintendent of Public Instruction (https://www.k12.wa.us/sites/default/files/public/safs/pub/per/1718/all.pdf). We also include the cost of training, materials, and setup (including a family resource center). We assume the program is delivered over a two-year period. We divide the total cost by the total number of participants served by Positive Family Support. Information on training, materials, setup costs, and providers was obtained from Blueprints for Healthy Youth Development (https://www.blueprintsprograms.org/program-costs/positive-family-support) and from communication with Marianne Fillhouer of Positive Family Support on April 25, 2019.
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
Grade point average^ 12 1 500 -0.023 0.152 16 n/a n/a n/a -0.062 0.685
School attendance^ 12 2 6957 0.001 0.017 13 n/a n/a n/a 0.001 0.949
Alcohol use^ 12 1 488 -0.075 0.154 21 n/a n/a n/a -0.197 0.201
Cannabis use^ 12 1 488 -0.047 0.154 21 n/a n/a n/a -0.125 0.418
Substance use^ 12 1 6457 0.005 0.018 13 n/a n/a n/a 0.005 0.789
Alcohol use before end of high school 12 1 500 -0.019 0.152 16 -0.019 0.152 18 -0.050 0.743
Alcohol use before end of middle school 12 1 386 -0.129 0.208 13 -0.129 0.208 13 -0.341 0.101
Alcohol use disorder 12 1 488 -0.187 0.154 22 -0.187 0.154 32 -0.491 0.002
Cannabis use before end of high school 12 1 500 -0.046 0.152 16 -0.046 0.152 18 -0.120 0.431
Cannabis use before end of middle school 12 1 386 -0.112 0.208 13 -0.112 0.208 13 -0.294 0.157
Cannabis use disorder 12 1 488 -0.091 0.154 22 -0.091 0.154 32 -0.238 0.123
Crime 12 3 362 -0.005 0.166 16 -0.005 0.166 26 -0.013 0.936
Externalizing behavior symptoms 12 2 6957 -0.009 0.017 13 -0.005 0.011 16 -0.010 0.584
Major depressive disorder 12 2 438 -0.081 0.190 14 0.000 0.310 16 -0.111 0.558
Regular smoking 12 1 488 -0.168 0.154 21 -0.168 0.154 31 -0.442 0.004
Smoking before end of high school 12 1 500 -0.052 0.152 16 -0.052 0.152 18 -0.138 0.367
Smoking before end of middle school 12 1 386 -0.193 0.208 13 -0.193 0.208 13 -0.507 0.015
Test scores 12 1 6457 -0.008 0.018 13 -0.006 0.019 17 -0.008 0.668

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.

Connell, A.M., Klostermann, S., & Dishion, T.J. (2012). Family Check up effects on adolescent arrest trajectories: Variation by developmental subtype. Journal of Research on Adolescence, 22(2), 367-380.

Fosco, G.M., Van Ryzin, M.J., Connell, A.M., & Stormshak, E.A. (2016). Preventing adolescent depression with the family check-up: Examining family conflict as a mechanism of change. Journal of Family Psychology, (30)1, 82-92.

Smolkowski, K., Seeley, J.R., Gau, J.M., Dishion, T.J., Stormshak, E.A., Moore, K.J., . . . Garbacz, S.A. (2017). Effectiveness evaluation of the Positive Family Support intervention: A three-tiered public health delivery model for middle schools. Journal of School Psychology, 62, 103-125.

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 Ryzin, 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.

Véronneau, M.H., Dishion, T.J., Connell, A.M., & Kavanagh, K. (2016). A randomized, controlled trial of the family check-up model in public secondary schools: Examining links between parent engagement and substance use progressions from early adolescence to adulthood. Journal of Consulting and Clinical Psychology, 84(6), 526-543.