Personalized Smoking Relapse Prevention Delivered in Real-Time via Just-in-time Adaptive Interventions

NIH RePORTER · NIH · K23 · $189,006 · view on reporter.nih.gov ↗

Abstract

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 algorithm...

Key facts

NIH application ID
10319774
Project number
7K23DA041616-05
Recipient
MEHARRY MEDICAL COLLEGE
Principal Investigator
Bryan Wayne Heckman
Activity code
K23
Funding institute
NIH
Fiscal year
2021
Award amount
$189,006
Award type
7
Project period
2021-02-01 → 2023-01-31