Grant Details
Grant Number: |
5R01CA247156-05 Interpret this number |
Primary Investigator: |
Bricker, Jonathan |
Organization: |
Fred Hutchinson Cancer Center |
Project Title: |
Full Scale Randomized Trial of an Innovative Conversational Agent for Smoking Cessation |
Fiscal Year: |
2024 |
Abstract
PROJECT SUMMARY/ABSTRACT (DESCRIPTION)
Cigarette smoking accounts for 480,000 premature deaths and one third of all cancer deaths annually in the
US. There is enormous need for high-impact, cost-effective population-level interventions for smoking
cessation. For the past 15 years, mobile phone-delivered text messaging interventions such as the NCI’s
SmokefreeTXT have been a prominent technology addressing this need. However, very much like all widely
available technologies for smoking cessation (e.g., websites), text messaging interventions have modest quit
rates, driven largely by low engagement. Fortunately, a new technology provides a therapeutic conversation to
address the problem of engagement that impacts text messaging and other current digital technologies for
smoking cessation. Advances in machine learning, natural language processing, and cloud computing are now
making it possible to create and widely disseminate conversational agents (CAs), which are computer-powered
digital coaches designed to form long-term social-emotional connections with users through conversations.
CAs are supportive, empathic, reflectively listen, provide personalized responses, and offer goal setting and
advice appropriately timed to the needs of the user. Regarding CAs for smoking cessation, the major
knowledge gaps are: (1) their efficacy, (2) theoretical mechanisms, and (3) the cost-effectiveness. Also
unexplored are the potential baseline moderators of CAs for smoking cessation. We recently developed a CA
for smoking cessation, called “QuitBot,” evaluated it in a diary study, and then tested it in a pilot randomized
controlled trial (N = 306), comparing it with the NCI’s SmokefreeTXT. The pilot RCT design was very feasible
with 93% three-month follow-up. QuitBot had: (a) high participant engagement and (b) high quit rates at the
three-month follow-up—very promising in comparison with SmokefreeTXT. Addressing these knowledge gaps
and building on the promising results of our QuitBot research, the project will conduct a randomized controlled
trial of QuitBot (n = 760) versus SmokefreeTXT (n = 760) with 12-month follow-up in order to determine
whether QuitBot: (1) provides higher quit rates than SmokefreeTXT, (2) has smoking cessation outcomes
significantly mediated by therapeutic alliance processes and engagement, and (3) is cost-effective vs.
SmokefreeTXT. In addition, this study will explore whether these baseline factors moderate the effectiveness
of QuitBot: trust, social support, and demographics (e.g., sex). This innovative project will advance the fields of
research on CAs both for smoking cessation in particular and for health behavior change in general—
regardless of whether the results are positive or null. Positive results could have high population-level impact
and stimulate new lines of research into CA dissemination and implementation, and the adaptation of CAs for
multiple subpopulations of smokers, languages, and community and medical settings.
Publications
Do medications increase the efficacy of digital interventions for smoking cessation? Secondary results from the iCanQuit randomized trial.
Authors: Bricker J.B.
, Santiago-Torres M.
, Mull K.E.
, Sullivan B.M.
, David S.P.
, Schmitz J.
, Stotts A.
, Rigotti N.A.
.
Source: Addiction (abingdon, England), 2023-11-27 00:00:00.0; , .
EPub date: 2023-11-27 00:00:00.0.
PMID: 38009551
Related Citations
Can a Single Variable Predict Early Dropout From Digital Health Interventions? Comparison of Predictive Models From Two Large Randomized Trials.
Authors: Bricker J.
, Miao Z.
, Mull K.
, Santiago-Torres M.
, Vock D.M.
.
Source: Journal Of Medical Internet Research, 2023-01-20 00:00:00.0; 25, p. e43629.
EPub date: 2023-01-20 00:00:00.0.
PMID: 36662550
Related Citations