Place-based intervention matching

Five steps from spatial analysis to targeted protective factor investment

Click each step to expand details

▾ 1 Identify highest-risk areas
Juvenile referral and adult corrections geographic overlap

Using spatial analysis of juvenile court referral data and adult correctional supervision records, identify the census tracts where both systems concentrate. These are the neighborhoods where the intergenerational cycle is most active.

In Salt Lake County: The same west-side tracts (Rose Park, Glendale, west West Valley) appear in the top quintile for both juvenile referral rates and adult correctional supervision rates. The geographic overlap is not coincidental — it reflects the same underlying community conditions affecting different generations.
▾ 2 Diagnose the weakest interception window
Which care ecology domain is failing in each neighborhood?

Each high-risk tract has a different combination of infrastructure failures. The three interception windows are assessed independently to determine which is the binding constraint:

Early development

Pediatric screening
ADHD, autism, dyslexia

School environment

Counselor access
Restorative practices

Community safety net

Youth orgs, mentoring
Crisis intervention

The earliest window. 12 of 29 Utah counties have zero pediatric providers. 74% of census tracts have no local pediatrician. Children with undiagnosed ADHD are 3.1× more likely to enter the juvenile justice system. When this window is closed, conditions manifest as classroom behavioral problems and the school system responds with discipline rather than treatment.

The widest window — every child passes through school. Median student-to-counselor ratio is 442:1 (ASCA recommends 250:1). 48 Utah schools have zero counselors but law enforcement present. Schools with counselors and no LE have the lowest absenteeism. When this window is resourced, behavioral incidents become support referrals instead of justice contacts.

The last upstream window before justice contact. Every 10 additional community nonprofits per 100,000 residents reduces murder by 9% and violent crime by 6% (Sharkey et al. 2017). Care desert tracts have 40% fewer accessible youth organizations. When this window is closed, youth have fewer legitimate alternatives to street involvement.

▾ 3 Map the service gap
What specific protective factor is missing or inaccessible?

For each high-risk tract, the care ecology maps identify exactly which services are absent or out of reach:

Example: A tract may have youth organizations within reach (green on the community map) but no school counselors (red on the care-vs-control map) and no pediatrician (gray on the provider map). The binding constraint is the school environment — that is where the interception window is narrowest.
▾ 4 Match the evidence-based intervention
Proven programs matched to specific gaps

Each gap maps to an intervention with RCT or strong quasi-experimental evidence:

Key principle from Vincent et al. (2024-25): Having services nearby is not enough. Youth need risk-reduction services at sufficient dosage targeting dynamic factors. The matching step ensures the intervention addresses the specific constraint, not just the general category.
▾ 5 Deploy where the return is highest
Care deserts, not places already well-served

The marginal return on investment is highest in care deserts — neighborhoods where protective factors are most absent. Deploying a school counselor in a building that already meets the 250:1 standard has modest impact. Deploying one in a building at 650:1 in a care desert tract transforms the interception window for every student in that school.

The spatial targeting advantage: Instead of distributing resources uniformly across a district or county, the framework concentrates investment in the specific neighborhoods and schools where: (1) risk is highest, (2) protective factors are most absent, and (3) evidence-based interventions have the largest demonstrated effect sizes. This is how limited budgets produce the greatest impact.