# Increasing Treatment Efficiency Using SMART Methods for Personalize Care

> **NIH NIH R34** · UNIVERSITY OF KENTUCKY · 2021 · $135,798

## Abstract

Project Summary/Abstract
Anxiety and depressive disorders are highly prevalent, costly, and debilitating, representing a serious public
health concern. Although time-limited, efficacious interventions have been developed for these common
conditions, these treatment protocols often require more sessions than patients in community practice typically
attend. Thus, it is critical to increase the efficiency of our interventions such that the skills that drive therapeutic
change are presented as early as possible. Transdiagnostic interventions designed to directly target core
processes implicated in the development of a range of conditions may increase treatment efficiency by
simultaneously leading to improvements across comorbid conditions. However, transdiagnostic treatments
contain multiple treatment elements (modules) and it is possible that some skills may be better suited for target
engagement based on each patient’s clinical presentation; prioritization of those modules may lead to earlier and
more robust symptom improvements. Unfortunately, we lack empirical evidence to guide treatment planning so
that care is personalized to the patient’s unique strengths and weaknesses. Additionally, evidence-based
decision rules regarding when to terminate treatment based on promising early markers of improvement, rather
than complete symptom remission, may also improve treatment efficiency, making care available to a greater
number of individuals. It is also possible that engagement of core processes may serve as an early indication
that a sufficient dose of treatment has been received, aiding decisions about when to discontinue care. The
proposed study will determine the feasibility, tolerability, and acceptability of a study that tests: 1) personalized
treatment delivery (i.e., module sequencing and treatment discontinuation timing) aimed at increasing the
efficiency of care, and 2) the research protocol designed to evaluate the effects of this personalized care. A
sample of 60 participants with heterogeneous anxiety disorders (and comorbid conditions, including depression)
will be enrolled in a pilot sequential multiple assignment randomized trial (SMART). Patients will be randomly
assigned to one of three sequencing conditions: transdiagnostic treatment administered in its standard module
order, module sequences that prioritize capitalizing on relative strengths, and module sequences that prioritize
compensating for relative weaknesses. Next, after 6 sessions, participants will be randomly assigned to either
continue or discontinue treatment to evaluate post-treatment change at varying levels of target engagement.
This proposal will enable us to 1) test the feasibility, acceptability, and tolerability of the research protocol,
treatment sequencing conditions, and early treatment discontinuation, 2) determine whether a preliminary signal
that capitalization or compensation module sequencing improves treatment efficiency exists, and 3) explore
preliminary...

## Key facts

- **NIH application ID:** 10369846
- **Project number:** 3R34MH123601-01S1
- **Recipient organization:** UNIVERSITY OF KENTUCKY
- **Principal Investigator:** DAVID A LANGER
- **Activity code:** R34 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $135,798
- **Award type:** 3
- **Project period:** 2020-07-20 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10369846

## Citation

> US National Institutes of Health, RePORTER application 10369846, Increasing Treatment Efficiency Using SMART Methods for Personalize Care (3R34MH123601-01S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10369846. Licensed CC0.

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