# Research Project 1: Navigation and Artificial Intelligence Technology for Indigenous Virtual Education on smoking cessation (NAITIVE)

> **NIH NIH U19** · FRED HUTCHINSON CANCER CENTER · 2024 · $567,642

## Abstract

PROJECT SUMMARY/ABSTRACT
American Indian/Alaska Native (AIAN) people have the highest rates of commercial cigarette smoking of any
racial/ethnic group in the US. Compared to other racial/ethnic groups, they have 6 times higher rates of
developing smoking-related cancers and are only half as likely to quit smoking. The result is that commercial
cigarette smoking now accounts for half of all deaths among AIAN communities nationwide. These dramatic
inequities are mainly due to two causes: (1) AIAN peoples’ lack of access to smoking cessation interventions,
and (2) the lack of efficacious smoking cessation interventions for AIAN populations. Addressing the dual
challenges of access and efficacy requires high-impact population-level interventions for smoking cessation.
Recent advances in large language model (LLM)-based smartphone app-delivered conversational chatbots offer
a promising solution, leveraging machine learning and natural language processing to emotionally engage users
and to provide personalized support and skills training. Chatbots can deliver supportive, empathic, and
personalized responses. To date, nothing is known about the efficacy and underlying mechanisms of chatbots
for helping AIAN people quit cigarette smoking. Regarding accessibility, chatbots require no in-person delivery
and no provider training, do not require integration into complex medical systems, can be freely accessed through
an app store, and are available at any time and any place. These smartphone-delivered chatbot apps have
potentially high population-level reach given that 68-78% of AIAN people own smartphones. We developed
“QuitBot” using an agile, user-centered design framework. QuitBot, the first-known chatbot with LLM-supported
conversation features, offers a comprehensive 42-day smoking cessation program. We initially assessed QuitBot
through a diary study, followed by a pilot RCT (N = 404), comparing it with the National Cancer Institute (NCI)’s
SmokefreeTXT program. The pilot RCT proved highly feasible with a 96% retention rate. QuitBot participants
interacted more frequently with their intervention and used it longer than SmokefreeTXT. Building on our
preliminary data, we propose to conduct a fully powered two-arm RCT comparing QuitBot (n = 386) to
SmokefreeTXT (n = 386) among nationally recruited AIAN participants in order to determine: (1) the efficacy of
QuitBot relative to SmokefreeTXT for biochemically verified 30-day point prevalence commercial cigarette
abstinence at 12 months post-randomization; (2) if QuitBot’s effect on 12-month smoking cessation is mediated
by therapeutic alliance and engagement. We will also (1) explore if key baseline factors moderate the primary
cessation outcome and (2) conduct qualitative interviews with QuitBot participants and Tribal partners, Tribal
organizations, urban Indian partner organizations, and other relevant organizations and policymakers in tobacco
control to identify barriers and facilitators to disseminati...

## Key facts

- **NIH application ID:** 11160297
- **Project number:** 1U19MD020533-01
- **Recipient organization:** FRED HUTCHINSON CANCER CENTER
- **Principal Investigator:** Jonathan B Bricker
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $567,642
- **Award type:** 1
- **Project period:** 2024-09-21 → 2029-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11160297

## Citation

> US National Institutes of Health, RePORTER application 11160297, Research Project 1: Navigation and Artificial Intelligence Technology for Indigenous Virtual Education on smoking cessation (NAITIVE) (1U19MD020533-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/11160297. Licensed CC0.

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