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).
Tobacco smoking is the leading cause of preventable death worldwide, and the need for new and improved treatment approaches is further highlighted by the fact that only 5% of smokers who make a quit attempt can maintain abstinence for at least one year. In an effort to reduce relapse risk the proposed studies will evaluate a personalized intervention that will deliver evidence-based treatment in real-time through mobile phones to meet the dynamic needs of patients engaged in a quit attempt. Given the high rates of mobile phone ownership, this intervention has great promise for increasing access to smoking cessation/relapse prevention services, thereby benefiting public health.
|Heckman, Bryan W; Dahne, Jennifer; Germeroth, Lisa J et al. (2018) Does cessation fatigue predict smoking-cessation milestones? A longitudinal study of current and former smokers. J Consult Clin Psychol 86:903-914|
|Stein, Jeffrey S; Heckman, Bryan W; Pope, Derek A et al. (2018) Delay discounting and e-cigarette use: An investigation in current, former, and never cigarette smokers. Drug Alcohol Depend 191:165-173|
|Heckman, Bryan W; Cummings, K Michael; Stoltman, Jonathan J K et al. (2018) Longer duration of smoking abstinence is associated with waning cessation fatigue. Behav Res Ther :|
|Dahne, Jennifer; Wahlquist, Amy E; Garrett-Mayer, Elizabeth et al. (2018) State Tobacco Policies as Predictors of Evidence-Based Cessation Method Usage: Results From a Large, Nationally Representative Dataset. Nicotine Tob Res 20:1336-1343|
|Fix, Brian V; O'Connor, Richard J; Benowitz, Neal et al. (2017) Nicotine Metabolite Ratio (NMR) Prospectively Predicts Smoking Relapse: Longitudinal Findings From ITC Surveys in Five Countries. Nicotine Tob Res 19:1040-1047|
|Dahne, Jennifer; Wahlquist, Amy E; Garrett-Mayer, Elizabeth et al. (2017) The differential impact of state tobacco control policies on cessation treatment utilization across established tobacco disparities groups. Prev Med 105:319-325|
|Carpenter, Matthew J; Heckman, Bryan W; Wahlquist, Amy E et al. (2017) A Naturalistic, Randomized Pilot Trial of E-Cigarettes: Uptake, Exposure, and Behavioral Effects. Cancer Epidemiol Biomarkers Prev 26:1795-1803|
|Heckman, Bryan W; MacQueen, David A; Marquinez, Nicole S et al. (2017) Self-control depletion and nicotine deprivation as precipitants of smoking cessation failure: A human laboratory model. J Consult Clin Psychol 85:381-396|
|Heckman, Bryan W; Cummings, K Michael; Kasza, Karin A et al. (2017) Effectiveness of Switching Smoking-Cessation Medications Following Relapse. Am J Prev Med 53:e63-e70|
|Ditre, Joseph W; Zale, Emily L; Heckman, Bryan W et al. (2017) A measure of perceived pain and tobacco smoking interrelations: pilot validation of the pain and smoking inventory. Cogn Behav Ther 46:339-351|