This clinical trial develops a chatbot smartphone application (app), QuitBot, and text messaging to help American Indians (AI) and Alaska Natives (AN) to quit smoking commercial tobacco (smoking cessation), and evaluates two remote smoking cessation programs to see how well they work for helping AI/AN people quit smoking commercial tobacco. AI/AN populations have one of the highest rates of commercial cigarette smoking of any racial and ethnic group in the United States (US). They also have a higher rate of developing smoking-related cancer but are less likely to quit smoking. The two programs are designed to provide personalized support in setting a smoking cessation goal, tasks to reach the smoking cessation goal, and motivation to remain smoke-free. This may help to keep participants engaged and support them in their quit efforts, and may improve smoking cessation among AI and AN.
Self-identifying as American Indian or Alaska Native, either alone or in combination with other races
Age 18 and older
Smoking combustible cigarettes daily in the past year
Interest in quitting smoking
The reverse of the inclusion criteria
Pregnant or breastfeeding
Use of other tobacco products (e.g., ceremonial use of tobacco, e-cigarettes) will be assessed but is not an exclusion criterion, as it would limit the study's generalizability
Parallel
QuitBot Smoking Cessation Chatbot Program
DeviceParticipate in Quitbot chatbot program
QuitBot Smoking Cessation Text Messaging Program
DeviceParticipate in Quitbot texting program
Survey Administration
Other interventionAncillary studies
Interview
Other interventionAncillary studies
Carbon Monoxide Measurement
Procedure/SurgeryAncillary studies
30-day point prevalence abstinence (PPA)
Will use a logistic regression model and standard smoking cessation trial intent-to-treat analysis, with all missing outcomes will be coded as smoking. The model will adjust for stratification factors and baseline factors that are significantly related to the outcome. Sensitivity analyses will include: (1) multiple imputation of missing outcomes, (2) complete case analysis, and (3) carbon monoxide (CO)-verified results adjusted for use of other combustible nicotine-containing tobacco products at the 12-month follow-up-in order to differentiate them from use of cigarettes at 12 months.
30-day PPA
Also 24-hour and 7-day PPA at the 3-, 6-, and 12- month follow-ups. Will use a logistic regression model and standard smoking cessation trial intent-to-treat analysis, with all missing outcomes will be coded as smoking. The model will adjust for stratification factors and baseline factors that are significantly related to the outcome. Sensitivity analyses will include: (1) multiple imputation of missing outcomes, (2) complete case analysis, and (3) CO-verified results adjusted for use of other combustible nicotine-containing tobacco products at the 12-month follow-up-in order to differentiate them from use of cigarettes at 12 months.
Measures of bond between user and conversational chatbot
Will be measured via four subscales of the 12-item Working Alliance Inventory for Tobacco (WAIT-12), with technology intervention adaptations similar to those of prior chatbot research. Will calculate the proportion of treatment effect explained by each of the mediators. Number of times participants engaged with the intervention will be adjusted in Poisson regressions that account for the number of prompts a participant received.
Agreement on goals of treatment
Will be measured via four subscales of the WAIT-12, with technology intervention adaptations similar to those of prior chatbot research. Will calculate the proportion of treatment effect explained by each of the mediators.
Agreement on tasks of treatment
Will be measured via four subscales of the WAIT-12, with technology intervention adaptations similar to those of prior chatbot research. Will calculate the proportion of treatment effect explained by each of the mediators.
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Fred Hutchinson Cancer Center
Lead sponsor
National Institute on Minority Health and Health Disparities (NIMHD)
Collaborator
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