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Adolescent Well-BeingNCT06815562

Predict the Best Level of Care Placement for Each Child's Behavioral Health Needs - Efficacy Study

A study testing Clinical team access to Placement Success Predictor (PSP) results in people with Adolescent Well-Being and Mental Health Wellness, run by Outcome Referrals, Inc. at 1 site in United States.

Completed

Finished. The study has ended and is not enrolling. Results may be posted on the official record.

Official record

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Trial summary

The purpose of this randomized clinical trial is to test the efficacy of a new clinical decision support tool, Placement Success Predictor (PSP). PSP will provide placement-specific predictions about the likelihood of a youth having a good outcome in each placement type using machine learning algorithms. Read more about this study

Who is it for?
Any age
Conditions the study is for
Adolescent Well-Being, Mental Health Wellness
What is being tested?
Clinical team access to Placement Success Predictor (PSP) results
Could I receive a placebo?
No, everyone receives an active treatment
How many people
213 participants
Where
1 siteUnited States
Study dates
3 Feb 2025to 26 Jan 2026
Phase
Interventional

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages Any age
  • All sexes
  • No healthy volunteers
  • Child, Adult, Older adult

Who may be able to join

  • Completed TOP CS assessment

Who cannot join

  • None

Trial locations and contacts

1 site in 1 country.

United States1 site
  • Outcome Referrals, Inc.

    Framingham, Massachusetts, 01701

Other trials in United States

About this study

Official title: Placement Success Predictor: Using Site-Customized Machine Learning Models to Predict the Best Level of Care Placement for Each Child's Behavioral Health Needs

The purpose of this randomized clinical trial is to test the efficacy of a new clinical decision support tool, Placement Success Predictor (PSP). PSP will provide placement-specific predictions about the likelihood of a youth having a good outcome in each placement type using machine learning algorithms.

The primary hypothesis is that if clinical team members have access to PSP results for youth in the experimental group, these youth will have better outcomes at the 3-month follow-up compared to youth in the control group.

Read the detailed description

In 2017, a total of 669,799 children were confirmed victims of maltreatment in the United States; of the 442,733 children in foster care, 34% have been in more than one placement and 11% are in a group home or institution. Stakes are extremely high for making the best out-of-home placement choice per child because some placement types and multiple placements are associated with poor outcomes. In the past few years, legislation has been created to guide placement decisions for children. Federal law 42 U.S. Code 675 requires that children in the care of the state are placed "in a safe setting that is the least restrictive (most family like)." In addition, the Family First Prevention Services Act signed into law by the U.S. Congress in 2018 includes measures to reduce the number of children in long-term residential settings. This study is an effort to develop and test a science-based clinical decision support tool using behavioral health data collected through standard clinical practice.

A randomized controlled trial (RCT) design will be used to assess efficacy of clinical team access to Placement Success Predictor (PSP) on child welfare clients' well-being outcomes and healthcare costs.

Sample. Clients at the State of Iowa Department of Health and Human Services (Iowa HHS) are the sample for this efficacy study.

Randomization. The outcome of a single coin toss was applied to an undisclosed algorithm for the client's record number to determine who gets assigned to the experimental group (i.e., client has PSP results).

Methods. The Treatment Outcome Package (TOP), a behavioral health assessment, is a standard part of care delivered in Iowa and its completion is required by the state. Iowa HHS clinical teams were provided PSP results for clients in the experimental condition. A request for a waiver of consent for this study was approved by the WCG IRB.

Being tested
Clinical team access to Placement Success Predictor (PSP) results

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

  • Clinical team access to Placement Success Predictor (PSP) resultsOther

    PSP is a machine-learning based clinical decision support tool that is designed to assist clinical team members in making placement decisions for youth.

Study groups in NCT06815562
Study groupRoleWhat they receive
Access to PSP site-specific placement prediction scores for that youthExperimentalThe PSP system will provide site-specific placement success prediction scores [i.e., client's likelihood of success per placement based on machine learning models] for each youth randomized to this condition in the efficacy study.
Receives: Other: Clinical team access to Placement Success Predictor (PSP) results
No PSP site-specific placement prediction scores for that youthNo interventionNot described

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Mean Difference in Average Domain Z-scores Across Raters Within Two Weeks on the Clinical Scale of the Treatment Outcome Package (TOP-CS) Between a) Baseline and b) Follow-up.

    The Child Treatment Outcome Package (TOP-CS) is a 48-item scale for children (ages 3 - 18) that assesses 13 domains. The Adolescent TOP-CS is a 58-item scale for adolescents (ages 11 - 21) that assesses 12 domains. TOP-CS assesses the client's past 2-week experience on domains including Depression, Violence, and Suicidality (scores are risk-adjusted for case mix variables assessed via 37 items on the companion TOP-Case Mix form regarding stressful life events, comorbidity). Participants answer "All" to "None of the Time" for each item on a 6-point Likert scale.

    A domain z-score of 0 represents the general population mean. Domain z-scores are averaged into a summary score per participant. Higher (more positive) average z-scores indicate greater symptom severity and lower behavioral well-being (a worse outcome). The value reported is the mean difference in this average z-score between baseline and follow-up; a negative mean difference indicates improvement (reduced severity).

    Measured: At baseline (within 2 weeks of study start) and approximately 60-120 days later

Secondary outcomes (1)
  1. Mean Difference Between the Average Risk-adjusted Predicted TOP-CS Total Score Across Raters at Study Baseline and the Actual Average TOP-CS Total Score Across Raters at Follow-up

    The Child Treatment Outcome Package (TOP-CS) is a 48-item scale for children (ages 3 - 18) that assesses 13 domains. The Adolescent TOP-CS is a 58-item scale for adolescents (ages 11 - 21) that assesses 12 behavioral health domains. Participants answer "All" to "None of the Time" for each item on a 6-point Likert scale.

    The TOP-CS Total Score is computed by averaging item responses. The range is 48 to 288 for the Child TOP-CS and 56 to 336 for the Adolescent TOP-CS. Higher Total Scores represent better behavioral well-being (a better outcome). Total Scores are averaged across raters per participant. The value reported is the mean difference between each participant's model-predicted, risk-adjusted Total Score (the outcome expected given their baseline profile) and their actual observed Total Score at follow-up. A positive mean difference indicates that the actual follow-up outcome exceeded the model-predicted outcome (i.e., the participant did better than predicted).

    Measured: At baseline (within 2 weeks of study start) and approximately 60-120 days later

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted7 Feb 2025
  2. Study start3 Feb 2025
  3. Primary completion26 Jan 2026
  4. Study completion26 Jan 2026

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Interventional
Phase
Phase N/A
Primary purpose
Health services research
Allocation
Randomised
Intervention model
Parallel groups
Model description
Efficacy (randomized clinical trial) study
Masking
None (open label)
Enrolment
213 participants (actual)
IDs, dates and publications
ClinicalTrials.gov ID
NCT06815562
Sponsor's protocol ID
2R44MH125486-02A1-Aim 2A
Other IDs
2R44MH125486-02A1
Status last verified
Jun 2026
First submitted
28 Jan 2025
Last updated
8 Jul 2026
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
No

Publications

  • Baxter, E. E., Alexander, P. C., Kraus, D. R., Bentley, J. H., Boswell, J. F., & Castonguay, L. G. (2016). Concurrent validation of the Treatment Outcome Package (TOP) for children and adolescents. Journal of Child and Family Studies, 25, 2415-2422.

  • Trudeau KJ, Yang J, Di J, Lu Y, Kraus DR. Predicting Successful Placements for Youth in Child Welfare with Machine Learning. Child Youth Serv Rev. 2023 Oct;153:107117. doi: 10.1016/j.childyouth.2023.107117. Epub 2023 Aug 4.

    PubMed 37841819
  • Kraus DR, Seligman DA, Jordan JR. Validation of a behavioral health treatment outcome and assessment tool designed for naturalistic settings: The Treatment Outcome Package. J Clin Psychol. 2005 Mar;61(3):285-314. doi: 10.1002/jclp.20084.

    PubMed 15546147

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