Feasibility of Using a Culturally Tailored Conversational Agent for promoting smoking cessation treatment utilization in African Americans who use cigarettes

使用文化定制对话代理促进吸烟的非裔美国人戒烟治疗利用的可行性

• 批准号: 10892533
• 负责人: MICHELE L ALLEN
• 金额: $ 60.25万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-24 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10892533
• 关键词: Abstinence; African American; African American population; Artificial Intelligence; Behavior Therapy; Behavioral; Cardiovascular Diseases; Cellular Phone; Chronic; Coping Skills; Counseling; Cues; Data; Development; Disparity; Dosage Forms; Educational process of instructing; Environment; Equity; Event; Exposure to; Feasibility Studies; Focus Groups; Goals; Health Services Accessibility; Health behavior; Health behavior change; High Prevalence; Individual; Intervention; Interview; Language; Life; Location; Measures; Minnesota; Modeling; Morbidity - disease rate; Nicotine; Outcome; Participant; Persons; Pharmaceutical Preparations; Population; Prevalence; Prevention; Procedures; Race; Randomized; Reporting; Risk; Severities; Smoke; Smoking; Smoking Behavior; Smoking Cessation Intervention; Specialist; Speech; Technology; Testing; Time; Tobacco; Tobacco Use Cessation; Tobacco use; Training; Work; acceptability and feasibility; access disparities; adaptive intervention; automated speech recognition; cardiovascular disorder prevention; cardiovascular disorder risk; caucasian American; cigarette smoke; cigarette smoking; craving; evidence base; flexibility; health care availability; health disparity; high risk; improved; innovation; low health literacy; member; mortality; natural language; nicotine gum; nicotine replacement; novel; pilot test; predictive modeling; prevent; primary outcome; public health relevance; racial disparity; research study; self help; skills; smartphone application; smoking abstinence; smoking cessation; smoking cue; success; tobacco advertising; tobacco cessation intervention

PROJECT SUMMARY/ABSTRACT African Americans have higher morbidity and mortality than do White Americans. One contributing factor to this health disparity is tobacco use and access to and utilization of smoking cessation treatment. Just in time adaptive interventions use predictive models to identify high risk situations for smoking and alert the user to use coping skills such as medication or behavioral strategies. They are typically delivered via smartphone technology. Recent advances in artificial intelligence technology using large language models (e.g., ChatGPT) provide an opportunity to create lifelike and flexible conversational agents to support health behavior change in those with low healthcare access. However, there are racial disparities in automated speech recognition that could limit utility among African Americans. The overarching goal of this proposed new project for the Center for Cardiovascular Disease Reduction and Equity Promotion Across Minnesota is to develop a Just In Time Adaptive Intervention for trigger management for African Americans who smoke. In support of this goal, we have two specific Aims. (A1) Develop a novel and racially unbiased Personal Assistant for Smoking Cessation with Artificial Intelligence and Large Language Models (PASCAL) for managing smoking triggers. (A2) Pilot test PASCAL to determine its feasibility and acceptability; and collect preliminary efficacy data. In support of these aims we will conduct 3 studies. First, we will conduct focus groups (N=20-24) to determine the acceptability of a conversational agent for smoking cessation among African Americans who smoke cigarettes. Next, we will conduct a Wizard of Oz study where the smoking cessation app will be trained using conversations between African American people who smoke (N=20) and a tobacco treatment specialist impersonating a conversational agent. Following the development of the Just In Time Adaptive Intervention app, we will conduct a third study to pilot test the App among African Americans who smoke (N=100). All participants will be given a two-week supply of nicotine lozenges and self-help cessation materials. Participants will track their smoking for 1 week pre-quit to identify smoking triggers. At the end of the week, participants will be randomly assigned to quit smoking with the support of PASCAL or to quit on their own. Participants will be followed for 8 weeks post quit. The co-primary outcomes are feasibility of study procedures and acceptability of PASCAL. We will also collect data on lozenge use, behavioral skills use, and CO-verified point prevalence abstinence at 2 and 8 weeks post quit. This proposal is significant as it is one of the first to test the use of large language models to generate content for conversational agents for health behavior change. In addition, it centers African Americans, a priority population for cardiovascular disease prevention in the development of a new health behavior change intervention.

项目概要/摘要 非裔美国人的发病率和死亡率高于美国白人。造成这一现象的一个因素是 健康差距在于烟草使用以及戒烟治疗的获得和利用。恰逢其时 适应性干预措施使用预测模型来识别吸烟的高风险情况并提醒用户 使用药物或行为策略等应对技巧。它们通常通过智能手机交付 技术。使用大型语言模型（例如 ChatGPT）的人工智能技术的最新进展 提供创建逼真且灵活的对话代理的机会，以支持健康行为的改变 那些医疗保健机会较低的人。然而，自动语音识别存在种族差异， 可能会限制非裔美国人的效用。该中心拟议新项目的总体目标 明尼苏达州减少心血管疾病和促进公平的目标是制定一个及时 针对吸烟的非裔美国人的触发管理的适应性干预。为了支持这一目标，我们 有两个具体目标。 (A1) 开发新颖且不带种族偏见的戒烟个人助理 使用人工智能和大型语言模型 (PASCAL) 来管理吸烟诱因。 (A2) 中试 PASCAL确定其可行性和可接受性；并收集初步疗效数据。为了支持这些 我们将进行 3 项研究。首先，我们将进行焦点小组（N=20-24）以确定 为吸烟的非裔美国人提供戒烟对话代理。接下来，我们将 进行绿野仙踪研究，其中戒烟应用程序将通过对话进行训练 吸烟的非裔美国人 (N=20) 和冒充烟草治疗专家的人 会话代理。随着及时适应性干预应用程序的开发，我们将进行 第三项研究是在吸烟的非裔美国人 (N=100) 中对该应用程序进行试点测试。所有参与者都将获得 供应两周的尼古丁含片和自助戒烟材料。参与者将追踪他们的吸烟情况 戒烟前 1 周确定吸烟诱因。在本周结束时，参与者将被随机分配到 在 PASCAL 的支持下戒烟或自行戒烟。参与者将被跟踪 8 周 辞职。共同主要结果是研究程序的可行性和 PASCAL 的可接受性。我们还将 收集有关含片使用、行为技能使用以及 2 点和 8 点经共同验证的点禁欲率的数据 戒烟后几周。该提案意义重大，因为它是第一个测试大型语言模型的使用的提案之一 为对话代理生成内容以改变健康行为。此外，它以非洲为中心 美国人是新健康发展中心血管病预防的重点人群 行为改变干预。

项目成果

Negative Mood is Associated with Sociobehavioral Factors Contributing to Cardiovascular Risk in an Immigrant Population.

消极情绪与导致移民人群心血管风险的社会行为因素有关。

• 发表时间: 2024-03-12
• 作者: Tranby, Brianna N;Sia, Irene G;Clark, Matthew M;Novotny, Paul J;Lohr, Abby M;Pardo, Laura Suarez;Patten, Christi A;Iteghete, Sheila O;Zeratsky, Katherine A;Rieck, Thomas M;Molina, Luz;Capetillo, Graciela Porraz;Ahmed, Yahye;Drie, Hana;Wielan
• 通讯作者: Wielan

Healthy immigrant community study protocol: A randomized controlled trial of a social network intervention for cardiovascular risk reduction among Hispanic and Somali adults.

健康移民社区研究方案：一项针对西班牙裔和索马里成年人降低心血管风险的社交网络干预的随机对照试验。

• 发表时间: 2024-03
• 影响因子: 2.2
• 作者: Wieland, Mark L;Molina, Luz;Goodson, Miriam;Capetillo, Graciela Porraz;Osman, Ahmed;Ahmed, Yahye;Elmi, Hindi;Nur, Omar;Iteghete, Sheila O;Torres;Dirie, Hana;Clark, Matthew M;Lohr, Abby M;Smith, Kaiti;Zeratsky, Katherine;Riec
• 通讯作者: Riec

Using Community-Based Participatory Research Methods to Inform the Development of Medically Tailored Food Kits for Hispanic/Latine Adults with Hypertension: A Qualitative Study.

使用基于社区的参与性研究方法为西班牙裔/拉丁裔高血压成人开发医学定制食品包提供信息：一项定性研究。

• 发表时间: 2023-08-17
• 影响因子: 5.9
• 作者: Crusan, Ambria;Roozen, Kerrie;Godoy;Zamarripa, Kathy;Remache, Anayeli
• 通讯作者: Remache, Anayeli

Efficacy and Adherence Rates of a Novel Community-Informed Virtual World-Based Cardiac Rehabilitation Program: Protocol for the Destination Cardiac Rehab Randomized Controlled Trial.

新型社区知情虚拟世界心脏康复计划的功效和依从率：目的地心脏康复随机对照试验方案。

• 发表时间: 2023-12-05
• 影响因子: 5.4
• 作者: Brewer, LaPrincess C;Abraham, Helayna;Clark 3rd, Donald;Echols, Melvin;Hall, Michael;Hodgman, Karen;Kaihoi, Brian;Kopecky, Stephen;Krogman, Ashton;Leth, Shawn;Malik, Shaista;Marsteller, Jill;Mathews, Lena;Scales, Robert;Schulte, Phillip;Shu
• 通讯作者: Shu