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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 2019.  Literature review updated June 2018.
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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.
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 $659 Benefits minus costs $928
Participants $850 Benefit to cost ratio $2.18
Others $365 Chance the program will produce
Indirect ($162) benefits greater than the costs 56 %
Total benefits $1,712
Net program cost ($785)
Benefits minus cost $928
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 $7 $0 $12 $3 $22
Labor market earnings associated with major depression $288 $676 $0 $0 $964
Health care associated with externalizing behavior symptoms $116 $33 $119 $58 $326
Mortality associated with depression $0 $1 $0 $7 $8
Subtotals $411 $710 $131 $68 $1,320
From secondary participant
Crime $21 $0 $44 $10 $76
Labor market earnings associated with high school graduation $48 $113 $62 $62 $284
K-12 grade repetition $1 $0 $0 $0 $1
K-12 special education $62 $0 $0 $31 $93
Health care associated with externalizing behavior symptoms $127 $36 $131 $63 $357
Costs of higher education ($10) ($8) ($3) ($5) ($26)
Subtotals $249 $140 $234 $162 $785
Adjustment for deadweight cost of program $0 $0 $0 ($392) ($392)
Totals $659 $850 $365 ($162) $1,712
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $619 2017 Present value of net program costs (in 2018 dollars) ($785)
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.
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 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
Alcohol use^ 18 Primary 1 159 -0.030 0.165 18 n/a n/a n/a -0.084 0.596
Cannabis use^ 18 Primary 1 159 -0.078 0.174 18 n/a n/a n/a -0.217 0.206
Externalizing behavior symptoms 18 Primary 1 159 -0.072 0.112 18 -0.039 0.069 21 -0.200 0.074
Illicit drug use^ 18 Primary 1 159 -0.063 0.166 18 n/a n/a n/a -0.174 0.289
Internalizing symptoms 18 Primary 1 159 -0.068 0.111 18 -0.068 0.111 20 -0.190 0.090
Major depressive disorder 18 Primary 1 159 -0.072 0.112 18 -0.037 0.137 20 -0.200 0.074
Externalizing behavior symptoms 1 Secondary 1 156 -0.068 0.112 1 -0.038 0.069 4 -0.190 0.091
Internalizing symptoms 1 Secondary 1 156 -0.036 0.112 1 -0.036 0.112 3 -0.100 0.373

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.