Smoking CessationLIFT-UPNCT07620301
LLM Intervention for Tobacco in Underserved Populations (LIFT-UP)
A study testing LIFT-UP Chatbot in people with Smoking Cessation, run by University of Utah at 1 site in United States.
Trial summary
This study will test a tailored, multilingual tobacco cessation chatbot called LIFT-UP (LLM Intervention for Tobacco in Underserved Populations), designed to better meet the needs of people living in persistent poverty census tracts. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Smoking Cessation
- What is being tested?
- LIFT-UP Chatbot
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 22 participants
- Where
- 1 siteUnited States
- Study dates
- 1 Nov 2026to 31 May 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 18+ years old
- Use ≥3 cigarettes/day on average
- Motivated to quit in the next 30 days
- Have a computer or tablet with internet access for 1:1 interviews
- Speak English or Spanish
- Home address is in an area characterized by persistent poverty
Who cannot join
- None
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United States1 site
Huntsman Cancer Institute/ University of Utah
Salt Lake City, Utah, 84102
Lindsey Potter, MPH, PhD, 801-213-6036, lindsey.potter@hci.utah.edu
Lindsey Potter, MPH, PhD
About this study
This study will test a tailored, multilingual tobacco cessation chatbot called LIFT-UP (LLM Intervention for Tobacco in Underserved Populations), designed to better meet the needs of people living in persistent poverty census tracts.
This study will use 1:1 semi-structured interviews to explore social drivers of health impacting TC, as well as digital access and preferences among those living in PPCTs. This qualitative approach enables guided yet flexible exploration of key domains while capturing unanticipated insights relevant to refining the chatbot.
Read the detailed description
Tobacco use is a major cause of cancer and is responsible for about half a million deaths in the United States each year. Because of this, helping people stop using tobacco is one of the most important ways to prevent cancer. Although tobacco use has decreased over time, many adults in the U.S. still use tobacco. Many people try to quit each year, but most quit attempts are not successful. One reason is that many people do not use proven, evidence-based quit support, such as counseling or quit medications.
People who live in areas with long-term poverty often face additional barriers that can make quitting harder. These areas may have fewer job and education opportunities, limited access to healthcare and community resources, and higher levels of day-to-day stress (for example, related to financial strain or lack of health insurance). People with lower income are just as likely to try to quit as those with higher income, but they are less likely to quit successfully and are less likely to use evidence-based quitting support. Many persistent poverty areas are also rural and have higher numbers of people who prefer to speak languages other than English, including Spanish, which creates an additional need for bilingual and culturally appropriate quit support.
Digital tools may help increase access to evidence-based tobacco cessation support in these communities. Mobile phone ownership is very common, including among people with lower incomes. However, some smartphone apps require reliable internet access or data plans, which can be a barrier. Text messaging is accessible on nearly all phones, does not require internet access, can be offered in multiple languages, and can be tailored to the needs of the user.
Text-based programs that use artificial intelligence (AI), such as large-language-model chatbots, may be especially useful because they can provide interactive support using natural language and can be delivered at scale. Chatbots have been used successfully in other areas of health, but many existing programs use fixed scripts and may not feel relevant or helpful for all groups. Importantly, most tobacco cessation chatbots have not been designed to address barriers faced by people living in persistent poverty areas.
- Conditions
- Smoking Cessation
- Being tested
- LIFT-UP Chatbot
- Medical subject headings
- Smoking Cessation
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
LIFT-UP ChatbotBehavioural
LIFT-UP Chatbot will be developed, evaluated, and refined using GARDE-Chat, an open-source chatbot authoring platform that has been used to support the development of chatbot-based interventions tested in large pragmatic clinical trials.
| Study group | Role | What they receive |
|---|---|---|
| Moderated Session | Experimental | Participants will attend a ~80 minute moderated "think-aloud" session via HIPAA compliant videoconferencing platform. Receives: Behavioral: LIFT-UP Chatbot |
What is being measured
The primary outcome is the main question the study is designed to answer.
System Usability Scale (SUS)
Usability will be measured using the SUS, a questionnaire assessing the perceived usability of a system, product, website, app, or digital intervention. It consists of ten 5-point Likert items ranging from "Strongly disagree" to "Strongly agree".
Scoring follows the standard SUS scoring procedure, for positively worded items, the item score is calculated as response minus 1; for negatively worded items, the item score is calculated as 5 minus the response. The 10 item scores are summed and then multiplied by 2.5 to generate the final SUS score, with higher scores indicating greater perceived usability. Score range: 0-100.
Measured: up to 1 day
Secondary outcomes (4)
Usability - Chat Bot Usability Scale (BUS-11)
Chatbot usability will be measured using the Chatbot Usability Scale (BUS-11). BUS-11 is a measured that assesses users' experiences after interacting with a chatbot or conversational agent. The BUS-11 consists of eleven 5-point Likert items ranging from "Strongly disagree" to "Strongly agree". Each item is coded from 1 to 5, and item scores are summed to create a total score. Higher scores indicate greater perceived chatbot usability. Score range: 11-55.
Measured: up to 1 day
Acceptability
Acceptability will be measured using the Acceptability of Intervention Measure (AIM). AIM is an instrument that assesses the perceived acceptability of an intervention. It consists of four 5 point Likert items ranging from "Completely "disagree" to "Strongly agree". Each item is coded from 1 to 5, and the overall score is the mean of the items score. Higher scores indicate greater perceived acceptability of the intervention. Score range: 1-5.
Measured: up to 1 day
Digital Working Alliance
Working alliance in the digital context will be measured with the Digital Working Alliance inventory (D-WAI). D-WAI is derived from the Working Alliance Inventory and measures the perceived working alliance (e.g., traditionally the collaborative bond between therapist and client) with digital interventions. It includes six 7-point Likert items ranging from "Strongly disagree" to "Strongly agree". Each item is coded from 1 to 7, and item scores are summed to create a total score. Higher scores indicate a stronger perceived digital working alliance. Score range: 7-42.
Measured: up to 1 day
Perceived cultural fit
Perceived cultural relevance will be measured using the Cultural Relevance Questionnaire (CRQ). CRQ consists of six 5-point Likert items ranging from "Strongly disagree" to "Strongly agree. Higher scores indicate greater perceived cultural appropriateness/relevance of the intervention. Score range: 5-25. An additional 5-point Likert-like question was added to reflect overall cultural fit perceived by the users.
Measured: up to 1 day
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted2 Jun 2026
- Study start1 Nov 2026 (estimated)
- Primary completion31 May 2027 (estimated)
- Study completion31 May 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Smoking CessationStudies of the same condition, open and under way.
- More trials run by University of UtahThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 22 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Utah
- Sponsor type
- University, hospital or other
- Collaborators
- National Cancer Institute (NCI), Huntsman Cancer Institute
- Responsible party
- Sponsor
- Investigators
- Chelsey Schlechter, MPH, PhD, Principal investigator, Huntsman Cancer InstituteChristian Mahony Reategui Rivera, MD, MS, Principal investigator, University of Utah
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07620301
- Sponsor's protocol ID
- 199440
- Other IDs
- U54CA280812
- Acronym
- LIFT-UP
- Status last verified
- Jun 2026
- First submitted
- 26 May 2026
- Last updated
- 1 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: De-identified data will be shared with only with investigators that have a data sharing agreement through PIVOT.
Study at a glance
From the registry record, last updated by the sponsor on 1 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- LLM Intervention for Tobacco in Underserved Populations (LIFT-UP)
- ClinicalTrials.gov ID
- NCT07620301
- Acronym / sponsor ID
- LIFT-UP / 199440
- Conditions
- Smoking Cessation
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 22 participants (estimated)
- Lead sponsor
- University of UtahUniversity, hospital or other
- Collaborators
- National Cancer Institute (NCI), Huntsman Cancer Institute
- Study start
- 1 Nov 2026 (estimated)
- Primary completion
- 31 May 2027 (estimated)
- Study completion
- 31 May 2027 (estimated)
- First posted
- 2 Jun 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study will test a tailored, multilingual tobacco cessation chatbot called LIFT-UP (LLM Intervention for Tobacco in Underserved Populations), designed to better meet the needs of people living in persistent poverty census tracts.
This study will use 1:1 semi-structured interviews to explore social drivers of health impacting TC, as well as digital access and preferences among those living in PPCTs. This qualitative approach enables guided yet flexible exploration of key domains while capturing unanticipated insights relevant to refining the chatbot.
Detailed description
Tobacco use is a major cause of cancer and is responsible for about half a million deaths in the United States each year. Because of this, helping people stop using tobacco is one of the most important ways to prevent cancer. Although tobacco use has decreased over time, many adults in the U.S. still use tobacco. Many people try to quit each year, but most quit attempts are not successful. One reason is that many people do not use proven, evidence-based quit support, such as counseling or quit medications.
People who live in areas with long-term poverty often face additional barriers that can make quitting harder. These areas may have fewer job and education opportunities, limited access to healthcare and community resources, and higher levels of day-to-day stress (for example, related to financial strain or lack of health insurance). People with lower income are just as likely to try to quit as those with higher income, but they are less likely to quit successfully and are less likely to use evidence-based quitting support. Many persistent poverty areas are also rural and have higher numbers of people who prefer to speak languages other than English, including Spanish, which creates an additional need for bilingual and culturally appropriate quit support.
Digital tools may help increase access to evidence-based tobacco cessation support in these communities. Mobile phone ownership is very common, including among people with lower incomes. However, some smartphone apps require reliable internet access or data plans, which can be a barrier. Text messaging is accessible on nearly all phones, does not require internet access, can be offered in multiple languages, and can be tailored to the needs of the user.
Text-based programs that use artificial intelligence (AI), such as large-language-model chatbots, may be especially useful because they can provide interactive support using natural language and can be delivered at scale. Chatbots have been used successfully in other areas of health, but many existing programs use fixed scripts and may not feel relevant or helpful for all groups. Importantly, most tobacco cessation chatbots have not been designed to address barriers faced by people living in persistent poverty areas.
Study design
- Primary purpose
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Moderated Session | Experimental | Behavioral: LIFT-UP ChatbotParticipants will attend a ~80 minute moderated "think-aloud" session via HIPAA compliant videoconferencing platform. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (6 listed)
- 18+ years old
- Use ≥3 cigarettes/day on average
- Motivated to quit in the next 30 days
- Have a computer or tablet with internet access for 1:1 interviews
- Speak English or Spanish
Key exclusion criteria (1 listed)
- None
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| LIFT-UP ChatbotLIFT-UP Chatbot will be developed, evaluated, and refined using GARDE-Chat, an open-source chatbot authoring platform that has been used to support the development of chatbot-based interventions tested in large pragmatic clinical trials. | Behavioural | Moderated Session |
Primary outcome
System Usability Scale (SUS)
Time frame: up to 1 day
Usability will be measured using the SUS, a questionnaire assessing the perceived usability of a system, product, website, app, or digital intervention. It consists of ten 5-point Likert items ranging from "Strongly disagree" to "Strongly agree". Scoring follows the standard SUS scoring procedure, for positively worded items, the item score is calculated as response minus 1; for negatively worded items, the item score is calculated as 5 minus the response. The 10 item scores are summed and then multiplied by 2.5 to generate the final SUS score, with higher scores indicating greater perceived usability. Score range: 0-100.
4 secondary outcomes
Usability - Chat Bot Usability Scale (BUS-11)
Time frame: up to 1 day
Acceptability
Time frame: up to 1 day
Digital Working Alliance
Time frame: up to 1 day
Perceived cultural fit
Time frame: up to 1 day
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 1 Oct 2026.
- Individual participant dataSharing planned: No. De-identified data will be shared with only with investigators that have a data sharing agreement through PIVOT.
Related trials for Smoking Cessation
Enrolling by invitationObservational study
Using Smartwatches to Monitor Smoking in Real-life Situations
Smoking
Not yet recruitingObservational study
PROMETHEE: A Shared Interregional Tele-Tobacco Cessation Platform Embedded Within the IMPULSION Lung Cancer Screening Program
Smoking Cessation, Lung Cancer Screening
Not yet recruiting
Impacto 2.0: Mobile Smoking Cessation Across Texas
Cigarette Smoking, Smoking Cessation
Not yet recruiting
Smoking Cessation Program for Lao People With HIV
Smoking Cessation, HIV
RecruitingPhase 3
Studying NMDA and Sigma-1 in Smoking Cessation Treatment (SUMMIT)
Smoking Cessation
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Chelsey Schlechter, MPH, PhD principal investigator
Huntsman Cancer Institute
Christian Mahony Reategui Rivera, MD, MS principal investigator
University of Utah
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing LIFT-UP Chatbot in people with Smoking Cessation, run by University of Utah at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 1 Oct 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Lindsey Potter, MPH, PhD (801-213-6036, Lindsey.Potter@hci.utah.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
System Usability Scale (SUS) (time frame: up to 1 day). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 1 Oct 2026.