이 페이지는 자동 번역되었으며 번역의 정확성을 보장하지 않습니다. 참조하십시오 영문판 원본 텍스트의 경우.

LLM Intervention for Tobacco in Underserved Populations (LIFT-UP) (LIFT-UP)

2026년 6월 1일 업데이트: University of Utah

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.

연구 개요

상태

아직 모집하지 않음

정황

상세 설명

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.

연구 유형

중재적

등록 (추정된)

22

단계

  • 해당 없음

연락처 및 위치

이 섹션에서는 연구를 수행하는 사람들의 연락처 정보와 이 연구가 수행되는 장소에 대한 정보를 제공합니다.

연구 연락처

연구 장소

    • Utah
      • Salt Lake City, Utah, 미국, 84102
        • Huntsman Cancer Institute/ University of Utah
        • 연락하다:
        • 수석 연구원:
          • Lindsey Potter, MPH, PhD
        • 수석 연구원:
          • Christian Mahony Reategui Rivera, MD, MS

참여기준

연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.

자격 기준

공부할 수 있는 나이

  • 성인
  • 고령자

건강한 자원 봉사자를 받아들입니다

아니

설명

Inclusion Criteria:

  • 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

Exclusion Criteria:

  • None

공부 계획

이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.

연구는 어떻게 설계됩니까?

디자인 세부사항

  • 주 목적: 다른
  • 할당: 해당 없음
  • 중재 모델: 단일 그룹 할당
  • 마스킹: 없음(오픈 라벨)

무기와 개입

참가자 그룹 / 팔
개입 / 치료
실험적: Moderated Session
Participants will attend a ~80 minute moderated "think-aloud" session via HIPAA compliant videoconferencing platform.
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.

연구는 무엇을 측정합니까?

주요 결과 측정

결과 측정
측정값 설명
기간
System Usability Scale (SUS)
기간: 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.

up to 1 day

2차 결과 측정

결과 측정
측정값 설명
기간
Usability - Chat Bot Usability Scale (BUS-11)
기간: up to 1 day
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.
up to 1 day
Acceptability
기간: up to 1 day
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.
up to 1 day
Digital Working Alliance
기간: up to 1 day
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.
up to 1 day
Perceived cultural fit
기간: up to 1 day
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.
up to 1 day

공동 작업자 및 조사자

여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.

스폰서

수사관

  • 수석 연구원: Chelsey Schlechter, MPH, PhD, Huntsman Cancer Institute/ University of Utah
  • 수석 연구원: Christian Mahony Reategui Rivera, MD, MS, University of Utah

연구 기록 날짜

이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.

연구 주요 날짜

연구 시작 (추정된)

2026년 6월 1일

기본 완료 (추정된)

2027년 5월 31일

연구 완료 (추정된)

2027년 5월 31일

연구 등록 날짜

최초 제출

2026년 5월 26일

QC 기준을 충족하는 최초 제출

2026년 5월 26일

처음 게시됨 (실제)

2026년 6월 2일

연구 기록 업데이트

마지막 업데이트 게시됨 (실제)

2026년 6월 3일

QC 기준을 충족하는 마지막 업데이트 제출

2026년 6월 1일

마지막으로 확인됨

2026년 6월 1일

추가 정보

이 연구와 관련된 용어

추가 관련 MeSH 약관

기타 연구 ID 번호

  • HCI199440
  • U54CA280812 (미국 NIH 보조금/계약)

개별 참가자 데이터(IPD) 계획

개별 참가자 데이터(IPD)를 공유할 계획입니까?

아니요

IPD 계획 설명

De-identified data will be shared with only with investigators that have a data sharing agreement through PIVOT.

약물 및 장치 정보, 연구 문서

미국 FDA 규제 의약품 연구

아니

미국 FDA 규제 기기 제품 연구

아니

이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .

LIFT-UP Chatbot에 대한 임상 시험

구독하다