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Washington State Institute for Public Policy
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Family Spirit

Public Health & Prevention: Home- or Family-based
Benefit-cost methods last updated December 2024.  Literature review updated June 2018.
Family Spirit is a home visiting programs for pregnant adolescent American Indian women. Family Spirit aims to improve parenting skills, prevent maternal drug abuse, and promote maternal life skill and positive psychosocial development. The intervention is delivered through home visits by trained American Indian paraprofessionals. The intervention includes 43 scheduled lessons delivered from the prenatal period (<32 weeks gestation) until 36 months after birth. In the single study included in this analysis, participants received home visits until 12 months after the birth of their child.
 
ALL
BENEFIT-COST
META-ANALYSIS
CITATIONS
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 (2023).  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 $859 Benefits minus costs $1,254
Participants $1,159 Benefit to cost ratio $2.36
Others $418 Chance the program will produce
Indirect ($257) benefits greater than the costs 57%
Total benefits $2,179
Net program cost ($925)
Benefits minus cost $1,254

^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 to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the program impacts measured in the research literature (for example, impacts on 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 on how we estimate effect sizes.

The effect size may be adjusted from the unadjusted effect size estimated in the meta-analysis. Historically, WSIPP adjusted effect sizes to some programs based on the methodological characteristics of the study. For programs reviewed in 2024 or later, we do not make additional adjustments, and we use the unadjusted effect size whenever we run a benefit-cost analysis.

Research shows the magnitude of effects may change 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. More details about these adjustments can be found in our Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured Treatment age Primary or secondary participant No. of effect sizes Treatment N 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
18 Primary 1 159 -0.030 0.165 18 n/a n/a n/a -0.084 0.596
18 Primary 1 159 -0.063 0.166 18 n/a n/a n/a -0.174 0.289
18 Primary 1 159 -0.078 0.174 18 n/a n/a n/a -0.217 0.206
18 Primary 1 159 -0.072 0.112 18 -0.037 0.137 20 -0.200 0.074
18 Primary 1 159 -0.072 0.112 18 -0.039 0.069 21 -0.200 0.074
18 Primary 1 159 -0.068 0.111 18 -0.068 0.111 20 -0.190 0.090
1 Secondary 1 156 -0.068 0.112 1 -0.038 0.069 4 -0.190 0.091
1 Secondary 1 156 -0.036 0.112 1 -0.036 0.112 3 -0.100 0.373
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
Major depressive disorder Labor market earnings associated with major depression $406 $956 $0 $0 $1,361
Mortality associated with depression $0 $1 $0 $8 $10
Externalizing behavior symptoms Criminal justice system $8 $0 $14 $4 $25
Health care associated with externalizing behavior symptoms $130 $37 $134 $65 $367
Subtotals $544 $994 $148 $77 $1,763
From secondary participant
Externalizing behavior symptoms Criminal justice system $25 $0 $52 $12 $89
Labor market earnings associated with high school graduation $57 $135 $73 $0 $265
K-12 special education $100 $0 $0 $50 $150
Health care associated with externalizing behavior symptoms $143 $40 $147 $71 $402
Costs of higher education ($11) ($9) ($3) ($5) ($29)
Internalizing symptoms K-12 grade repetition $1 $0 $0 $0 $1
Subtotals $315 $166 $270 $129 $879
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($463) ($463)
Totals $859 $1,159 $418 ($257) $2,179
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Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $619 2017 Present value of net program costs (in 2023 dollars) ($925)
Comparison costs $0 2017 Cost range (+ or -) 20%
We estimate provider hours including service provision hours, training hours, and supervisory hours; apply the 2017 mean hourly wage estimate for Washington State reported by the Bureau of Labor Statistics (retrieved June 2018) for the appropriate provider; and increase wages by a factor of 1.441 to account for the cost of employee benefits. The included study averaged 18 home visiting hours, 5 training hours, and 2 supervisory hours per participant. We assume that supervisors are social workers. We used estimates of hours of training and service provision based on Barlow et al., 2013.
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

Barlow, A., Mullany, B., Neault, N., Compton, S., Carter, A., Hastings, R., . . . Walkup, J.T. (2013). Effect of a paraprofessional home-visiting intervention on American Indian teen mothers’ and infants’ behavioral risks: a randomized controlled trial. The American Journal of Psychiatry, 170(1), 83-93.