Placement Success Predictor for Adolescent Mental Health Wellness

Overseen By Kimberlee J. Trudeau, Ph.D

Age: Any Age

Sex: Any

Trial Phase: Academic

Sponsor: Outcome Referrals, Inc.

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

Duration: 3 months

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial tests a new tool called the Placement Success Predictor (PSP), which uses machine learning to determine the best placement for adolescents in mental health programs. The goal is to assess whether access to PSP's predictions improves outcomes for young people after three months. Participants will have placements decided either with the help of PSP or without it. This trial suits those who have completed the TOP CS assessment and are considering different placement options for mental health support. As an unphased trial, it offers a unique opportunity to contribute to innovative mental health solutions for adolescents.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications.

What prior data suggests that the Placement Success Predictor (PSP) is safe for use in adolescent mental health wellness?

A previous study used the Placement Success Predictor (PSP) to forecast how well young people might perform in various care settings. This tool employs machine learning, a technology that enables computers to learn from data. No reports have indicated that the PSP causes physical side effects, as it is neither a drug nor a medical procedure. Instead, it assists doctors in making informed decisions about care placements. The trial's "Not Applicable" phase designation indicates minimal safety concerns due to the tool's nature. Consequently, participants do not face the typical risks associated with new medications or treatments. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about the Placement Success Predictor (PSP) because it uses advanced machine learning models to predict the success of site-specific placements for adolescents with mental health challenges. Unlike traditional methods that rely mainly on clinical judgment or historical data, PSP offers personalized predictions that can help tailor placements to each youth's unique needs. This approach has the potential to improve outcomes by ensuring that adolescents are placed in environments where they are most likely to thrive, making it a promising advancement in adolescent mental health care.

What evidence suggests that the Placement Success Predictor is effective for adolescent mental health wellness?

Research has shown that the Placement Success Predictor (PSP) uses advanced computer programs to predict positive outcomes for young people in various care settings. In this trial, some participants will access PSP site-specific placement prediction scores, offering specific predictions on each young person's likelihood of success in a particular setting. These programs have shown promise in identifying effective placements based on adjusted data about behavior and health. Early results suggest that PSP can aid in making better decisions, potentially leading to improved outcomes for adolescents in mental health care. ^{2 3 4 6 7}

Are You a Good Fit for This Trial?

This trial is for young people who are dealing with mental health and wellbeing issues. It's designed to help figure out the best care setting for each individual. To join, participants must meet certain criteria that aren't specified here.

Inclusion Criteria

Completed TOP CS assessment

Exclusion Criteria

Not applicable.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Treatment

Participants receive site-specific placement success prediction scores using the Placement Success Predictor (PSP) tool

3 months

Regular assessments using the Treatment Outcome Package (TOP)

Follow-up

Participants are monitored for well-being outcomes and healthcare costs after treatment

3 months

What Are the Treatments Tested in This Trial?

Interventions

• Placement Success Predictor (PSP)

Trial Overview The study is testing a new tool called Placement Success Predictor (PSP), which uses machine learning to predict how well a youth might do in different care settings. The clinical teams will use PSP results to make decisions, and outcomes will be compared after 3 months.

How Is the Trial Designed?

Group I: Access to PSP site-specific placement prediction scores for that youth Experimental Treatment 1 Intervention

The 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.

Group II: No PSP site-specific placement prediction scores for that youth Active Control 1 Intervention

Who Is Running the Clinical Trial?

Outcome Referrals, Inc.

Lead Sponsor

Trials

4

Recruited

1,500+

National Institute of Mental Health (NIMH)

Collaborator

Trials

3,007

Recruited

2,852,000+

State of Iowa Department of Health and Human Services

Collaborator

Trials

1

Recruited

300+

Citations

1. clinicaltrials.gov clinicaltrials.gov/study/NCT06834763

Predict the Best Level of Care Placement for Each Child's ... The purpose of this study is to test the effectiveness of a new clinical decision support tool, Placement Success Predictor (PSP), in a naturalistic setting.

2. withpower.com withpower.com/trial/placement-success-predictor-for-adolescent-mental-health-wellness-0c8f6

Placement Success Predictor for Adolescent Mental Health ... PSP will provide placement-specific predictions about the likelihood of a youth having a good outcome in each placement type using machine learning algorithms.

3. ctv.veeva.com ctv.veeva.com/study/predict-the-best-level-of-care-placement-for-each-childs-behavioral-health-needs-effectiveness-st

Predict the Best Level of Care Placement for Each Child's ... PSP will provide placement-specific predictions about the likelihood of a youth having a good outcome in each placement type at a behavioral ...

4. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC10569152/

Predicting Successful Placements for Youth in Child ... Machine learning models based on risk-adjusted behavioral health and functional data show promise in predicting positive placement outcomes.

5. mentalhealth.networkofcare.org mentalhealth.networkofcare.org/Lake/CommunityResources/ClinicalTrials/Detail/NCT06834763?keyword=%22Mental%20Health%20Wellness%22

Predict the Best Level of Care Placement for Each Child's ... This effectiveness study is to assess and improve the usage of PSP in a behavioral health setting.~Sample. Clients at Children's Hope Alliance (CHA) who ...

6. clinicaltrials.gov clinicaltrials.gov/study/NCT06815562

Predict the Best Level of Care Placement for Each Child's ... 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 ...

7. trial.medpath.com trial.medpath.com/clinical-trial/21f6266a06ffd7d9/nct06815562-machine-learning-child-behavioral-health-care

Predict the Best Level of Care Placement for Each Child's ... - MedPath The purpose of this randomized clinical trial is to test the efficacy of a new clinical decision support tool, Placement Success Predictor (PSP).