PROJECT SUMMARY/ABSTRACT
Candidate:
My research has been funded by the National Institute of Drug Abuse (NIDA) since 2012, first
through a F31 to support my dissertation work that identified novel precipitants of smoking relapse, and then
through a T32 [and K12] at the Medical University of South Carolina (MUSC) to support my work examining
novel relapse prevention approaches. My research has been recognized through awards (locally and nationally)
and publications in high-impact journals. I am excited to take the next step in my career development, and with
K23 support I will be able to engage in the research and training experiences I need to become an expert in the
emerging area of just-in-time-adaptive interventions (JITAIs) and pioneer their use in the addiction field.
Career Development Plan: Career development activities build upon my clinical psychology training and twelve
years of addiction-focused clinical research experience. K23 training objectives are to develop the knowledge,
skills, and collaborations necessary to become a leader in the field of relapse prevention, with a focus on JITAIs.
Training will be obtained through participation in scientific conferences, methods workshops, coursework, and
[structured mentorship from Drs. Matthew Carpenter, Michael Cummings, David Gustafson, Andrew Lawson,
Michael Saladin, and Thomas Kirchner, all of which will contribute towards the development of my expertise in]:
1) tobacco control, 2) precision medicine via mHealth technologies, 3) ecological momentary assessment (EMA),
4) geospatial statistics, 5) predictive analytics relevant to JITAIs and relapse, and 6) grant writing. These
experiences will ensure research aims are met, and I will be prepared to transition to research independence.
[Research Plan: We will beta test, refine (Aim 1), and pilot test (Aim 2) a personalized JITAI designed to guide
delivery of fast acting nicotine replacement therapy (NRT; lozenge) in real-time, to prevent smoking relapse.
Feedback from three rounds of beta testing (10 participants per round) will guide intervention refinement before
it is tested in a small-scale randomized controlled trial (RCT), thereby ensuring usability, functionality,
acceptability, and technical feasibility]. Specifically, a smartphone application (app), will integrate pre-quit
smoking data with objective location data captured via global positioning system (GPS) to establish relapse risk
(hotspot) algorithms. During a quit attempt, the GPS-enabled app (MyQuit) will detect proximity to hotspots and
deliver NRT prompts, all of which will occur automatically and prior to exposure. Thus, MyQuit will optimize NRT
use to prevent cue-provoked cravings known to undermine sustained abstinence, thereby repurposing this
evidence-based cessation medication to promote relapse prevention. MyQuit will be tested against standard
care (NRT with brief instructions). Two versions of MyQuit will be tested, which will differ only in how hotspot
algorithms are derived: retrospectively from locations recalled at the onset of a quit attempt (MyQuit-Recall) or
based on real-time EMA completed pre-quit (MyQuit+). We are not powered to examine clinical efficacy [(N=75)],
but results will provide preliminary data to estimate effect sizes, and support a R01 submission, for a fully
powered Stage II efficacy trial of these innovative approaches. We hypothesize effect sizes will suggest better
outcomes (1 week, 1 month, 3 month abstinence) in both MyQuit conditions relative to standard care. We also
expect MyQuit+ will outperform MyQuit-Recall, but test both because they each offer unique reach potential.
MyQuit-Recall will advance the limited evidence-base for relapse prevention tools available to former smokers.
Mentorship Team: All 5 mentors have external funding (3 with center grants), and collectively have over 900
publications and mentored 3 K awardees. Collaborations will result in 3-4 peer-reviewed publications per year.
Environment and Institutional Commitment: The research environment, facilities, and resources at the MUSC
are ideally suited for mentored career development in addiction research. An abundance of training activities are
available across campus (workshops/seminars), and over 30 faculty are involved with addiction research
training. I will carry out K23 activities as an Assistant Professor in the Addiction Sciences Division, within the
Department of Psychiatry and Behavioral Sciences. Many of the nation's preeminent addiction researchers are
members of the department, including NIH's highest funded psychiatric researcher. In FY2014 the department
was ranked 8th in NIH research funding among domestic psychiatry departments.
Conclusions: The need to accelerate advances in relapse prevention through technology is paramount.
Smoking remains the leading cause of preventable death worldwide, and 95% of cessation attempts fail. High
relapse rates are, in part, due to environmental triggers and improper NRT use. MyQuit minimizes both by guiding
NRT use in anticipation of triggers. Compared to traditional interventions, tailored (idiographic) and dynamic (in-
the-moment) interventions may improve effectiveness. Personalized JITAIs offer great promise for benefiting
public health, and could be adopted to treat a wide range of addictive problems. The use of mHealth technology
to provide idiographic and real-time treatment is consistent with NIDA's Strategic Plan and the NIH-supported
Precision Medicine Initiative. K23 mentored career development will support my transition to independence, and
position me to become an expert in emerging and novel approaches to addiction treatment (i.e., JITAIs).