Increasing Treatment Efficacy Using SMART Methods for Personalizing Care
Phase: NA
Conditions: Anxiety Disorders, Post Traumatic Stress Disorder, Obsessive-Compulsive Disorder
Sponsor: Shannon E. Sauer-Zavala

Document Coversheet
Study Title: Increasing Treatment Efficacy Using SMART Methods for Personalizing Care
Institution/Site: 
University of Kentucky 
Document (Approval/Update) Date:
1/10/2025 
NCT Number:
NCT04642898
IRB Number
59307
Coversheet created:
5/8/2025

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IRB Approval
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IRB # 59307
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Statistical Design and Power
Statistical Design 
Study Feasibility. Clinician and patient enrollment, a measure of feasibility of a large RCT, will be 
assessed by reporting percentages for the 6 clinician and 5 patient enrollment variables. Rates of treatment and 
assessment completion will also be reported. Clinician adherence will be evaluated by coding 20% of treatment 
sessions according to a UP adherence checklist and reporting adherence rates within each condition. 
Study and Treatment Acceptability. Quantitative measures of study and treatment acceptability (e.g., 
the AFQ, Clinician and Patient Versions) will be assessed through the use of descriptive statistics. Qualitative 
analyses of clinician and patient perceptions of study and treatment protocols will be analyzed in conjunction 
with quantitative results (e.g., QUAL + QUAN121, 122). Qualitative analysts will review interview recordings and 
transcriptions, identifying and coding the primary issues raised by respondents using a grounded theory123, 
embedded in Willms, et al.’s124 guidelines for coding: reaching consensus on coding assignment, identifying 
concordance among codes, and using the process of constant comparisons to generate a taxonomy of themes 
and identify their relationships to one another. This will have analysts: 1) review all transcripts to develop a broad 
understanding of the content and document initial impressions of topics and themes, defining the boundaries of 
specific codes125, 2) independently code empirical material to condense data into analyzable units and form a 
codebook, 3) discuss disagreements in code assignment/description (each test will be reviewed by at least two 
analysts), 4) compare reliability of assigning the same codes to identical text segments126, and 5) use the 
computer program NVivo to examine the association between different a priori and emergent categories. 
Pilot Test of Personalization Aims (ordering and discontinuation). In addition to our primary aim of 
establishing the feasibility/acceptability of our personalization strategies and study design, we seek to determine 
whether a preliminary signal exists to support the notion that personalized sequencing and target-informed 
discontinuation can enhance treatment efficiency. First, to explore whether personalized sequencing leads to 
more efficient improvements in the core process addressed by the UP, we will use hierarchical linear mixed 
modeling (HLMM) to compare the average rate of change in clinical outcomes among the three UP sequencing 
conditions (UPS, UPP-CA, and UPP-CO). The primary outcome measure for aim is the distress aversion 
subscale from the MEAQ (MEAQ-DA), which has previously been used to demonstrate target engagement with 
the UP (see Preliminary Studies). Additionally, to examine whether core process engagement can serve as an 
early indicator of treatment response, prompting discontinuation, we will assess variability in MEAQ-DA levels at 
the second stage randomization (S5 assessment), along with the degree to which any patients randomized to 
discontinue demonstrate additional symptom improvement (using HAM-A ratings) in the absence of treatment 
such that they are responders by the W20 assessment. We will also explore whether patterns exist between S5 
MEAQ-DA scores and responder status for those that discontinued after session 6. 
Power Analyses. 
This proposal is designed as a pilot trial to, as noted in the RFA, collect relevant data to inform the design 
(and increase the likelihood of obtaining meaningful results) in a subsequent well-powered trial. To do this, we 
are measuring potential mechanisms of change and exploring preliminary effect sizes and the variability of 
treatment effects. This will allow us (and future reviewers) to determine whether further testing is warranted. 

IRB Approval
4/9/2021
IRB # 59307
NMED

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