# Neuroimaging approaches to improve prediction of smoking initiation and nicotine use escalation among young adult electronic nicotine delivery systems users

> **NIH NIH K01** · UNIVERSITY OF CALIFORNIA SANTA BARBARA · 2024 · $158,137

## Abstract

PROJECT SUMMARY/ABSTRACT
The proposed career development application provides research training for Dr. Jiaying Liu to facilitate her
transition to independence. The goal of the proposed research is to identify neurobehavioral makers of nicotine
use escalation and cigarette smoking initiation among young adult (YA) users of electronic nicotine delivery
systems (ENDS). Findings are expected to inform regulatory policy and improve YA responsiveness to public
health campaign communications. Given the accumulating evidence that ENDS use conveys 5-fold additional
risk for smoking initiation and other tobacco use escalation, recent YA increases in use are alarming,
threatening a resurgence of dependence that may reverse decades of tobacco control success. Therefore, it is
crucial to identify predictive markers of smoking initiation and tobacco use escalation in this vulnerable
population, and to provide actionable evidence that informs regulatory and prevention efforts. Functional
magnetic resonance imaging (fMRI) generates information complementary to traditional behavioral risk
assessments, with direct observations of the neural substrates that underlie the subjective states known to
perpetuate addiction, in order to yield objective and putatively more predictive measures. Assessment of
behavioral and brain markers associated with smoking onset and tobacco use escalation is proposed. The goal
is to determine whether baseline neurobehavioral markers will predict smoking transition and tobacco use
escalation beyond traditional makers at 3, 6, 9 and 12 months. A one-year public service announcement (PSA)
intervention with a cross-over design will also be conducted, in which two message exposure orders and one
control condition allow testing whether novel anti-ENDS PSAs addressing harms associated with ENDS flavors
will more effectively prevent tobacco use escalation compared to the existing regular PSAs. The proposed
research is among the first that aims to inform regulation of flavored ENDS marketing, and to provide
recommendations for developing effective PSAs for prevention campaigns. These aims directly address
multiple priorities of FDA Center for Tobacco Products (Marketing Influences, Communications, Behavior and
Addiction), and they are expected to pinpoint effective regulatory gates to address the current ENDS epidemic.
Dr. Liu’s long-term goal is to become an independent researcher translating communication neuroscience
research to regulatory actions for improvements in health campaigns and interventions utilizing persuasive
anti-tobacco messaging. Her near-term goal is to prepare a competitive R01 application to implement
randomized controlled trials of PSAs to maximize impact on deterrence of smoking and substance use
transition among ENDS users. The proposed training experience is designed to develop competencies in (a)
neuroscience, (b) functional neuroimaging, (c) tobacco regulatory science, and (d) grant writing. The proposed
research st...

## Key facts

- **NIH application ID:** 10916568
- **Project number:** 5K01DA049292-05
- **Recipient organization:** UNIVERSITY OF CALIFORNIA SANTA BARBARA
- **Principal Investigator:** Jiaying Liu
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $158,137
- **Award type:** 5
- **Project period:** 2023-09-01 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10916568

## Citation

> US National Institutes of Health, RePORTER application 10916568, Neuroimaging approaches to improve prediction of smoking initiation and nicotine use escalation among young adult electronic nicotine delivery systems users (5K01DA049292-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10916568. Licensed CC0.

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