# An Adaptive Algorithm-Based Approach to Treatment for Adolescent Depression

> **NIH NIH R01** · UNIVERSITY OF MINNESOTA · 2021 · $608,315

## Abstract

PROJECT SUMMARY
Adolescent depression is a prevalent and debilitating disorder that places youth at risk for suicidality, other
psychiatric diagnoses, and functional impairment both during adolescence and into adulthood. There are a
number of effective treatments; however, 30-50% of adolescents who receive these treatments do not
respond. To improve response rates, practice parameters recommend routine systematic symptom
assessment over the course of treatment to inform decisions regarding whether to switch or augment
treatment. Research also demonstrates that regular symptom monitoring improves treatment outcomes.
Unfortunately, routine symptom assessment in usual care for adolescent depression is extremely rare. In
addition, for psychotherapy, which is the most frequent treatment for adolescent depression, there are currently
no guidelines to direct therapists regarding how to use those symptom assessments to guide subsequent
treatment decisions. Addressing this critical knowledge gap requires identifying (1) what symptoms or patient
characteristics to assess, (2) when to administer those assessments, and (3) what subsequent treatment to
provide, based on those assessments. Adaptive treatment strategies (ATSs) provide algorithms for guiding
treatment decision making. These algorithms are based on patient characteristics and outcomes collected
during the course of therapy, and they provide guidelines regarding when, how, and for whom midcourse
changes in the treatment approach should be initiated. ATSs can be developed and validated within the
context of an innovative experimental design called a sequential multiple assignment randomized trial
(SMART). In a SMART, subjects can be randomized multiple times and these randomizations occur
sequentially through time at selected critical decision points. The results of the SMART are used to define the
decision rules that make up the ATS. The purpose of the current study is to evaluate the effectiveness of two
ATSs for adolescent depression. The ATSs include delivery of an evidence-based psychotherapy for
adolescent depression (interpersonal psychotherapy, IPT-A), systematic symptom monitoring, and an
empirically-derived algorithm that specifies whether, when, and how to augment IPT-A. 200 depressed
adolescents (age 12-18) will be recruited to participate in a 16-week SMART conducted in an outpatient
community mental health clinic. The aims of this R01 are to (1) evaluate the effectiveness of the ATSs
embedded in this trial, (2) evaluate adolescents' interpersonal functioning as a treatment target of IPT-A, (3)
evaluate moderators of initial treatment and treatment augmentation strategies, and (4) conduct a process
evaluation to identify barriers and facilitators that influenced ATS implementation.

## Key facts

- **NIH application ID:** 10166940
- **Project number:** 5R01MH113748-05
- **Recipient organization:** UNIVERSITY OF MINNESOTA
- **Principal Investigator:** Meredith Lyn Gunlicks-Stoessel
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $608,315
- **Award type:** 5
- **Project period:** 2017-08-01 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10166940

## Citation

> US National Institutes of Health, RePORTER application 10166940, An Adaptive Algorithm-Based Approach to Treatment for Adolescent Depression (5R01MH113748-05). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10166940. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*