Measurement Timing in Growth Mixture Modeling of Alcohol Trajectories

酒精轨迹生长混合物模型中的测量时序

• 批准号: 8060825
• 负责人: Anne Marie Fairlie
• 金额: $ 3.32万
• 依托单位: UNIVERSITY OF RHODE ISLAND
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-01-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8060825
• 关键词: Adolescence; Adolescent; Advisory Committees; Affect; Alcohol abuse; Alcohol consumption; Alcoholism; Alcohols; Area; Biological; Cereals; Data; Decision Making; Development; Distal; Exhibits; Future; Growth; Individual; Intercept; Intervention Studies; Knowledge; Longitudinal Studies; Longitudinal Surveys; Measurement; Measures; Modeling; National Institute on Alcohol Abuse and Alcoholism; Outcome; Pattern; Positioning Attribute; Prevalence; Prevention; Preventive Intervention; Public Health; Reporting; Research; Research Design; Research Personnel; Shapes; Societies; Study models; Subgroup; Surgeon; Techniques; Time; United States Dept. of Health and Human Services; Variant; Youth; abstracting; alcohol behavior; base; design; drinking; drinking behavior; improved; interest; intervention program; longitudinal design; public health relevance; simulation; social; trend; underage drinking; young adult

DESCRIPTION (provided by applicant): Abstract: Alcohol use during adolescence and young adulthood remains a critical area for research, which is well-recognized by the National Institute on Alcohol Abuse and Alcoholism's (NIAAA) Underage Drinking Research Initiative and the report from the Task Force of the National Advisory Council on Alcohol Abuse and Alcoholism (2002). Alcohol use and its negative consequences are a significant public health concern given the biological, social, and environmental effects they exert on individuals and society. It is important to better understand the variable patterns of alcohol use that individuals exhibit over time (e.g., consistently low alcohol use, rapidly increasing alcohol use) during this key developmental period. Growth mixture modeling (GMM) is a statistical technique that is used to identify latent subgroups of individuals who exhibit distinct patterns of alcohol use over time. Despite the widespread use of GMM, a limited number of studies have examined how study design factors may affect alcohol use trajectories used to identify latent subgroups in GMM. The proposed research focuses specifically on the effect of measurement timing (i.e., number and spacing of assessments) in longitudinal studies. Decision-making about how to space assessments is particularly challenging in the context of GMM, because the hypothesized latent subgroups may exhibit different trends in alcohol use over time based on design features rather than actual changes. This project proposes to investigate how measurement timing affects the shape of individuals' alcohol use trajectories in the context of GMM. The specific aims are to: (1) conduct a Monte Carlo simulation study that evaluates how the number and spacing of assessments affects the alcohol use trajectories used to identify latent alcohol use subgroups in GMM; (2) provide an application of GMM using alcohol data from the National Longitudinal Survey of Youth 1997 that demonstrates the extent to which the number and spacing of assessments affects the alcohol use trajectories used to identify the latent subgroups; and (3) communicate the findings to both quantitative and applied researchers and suggest specific considerations for designing longitudinal GMM studies. The main implication of the proposed research is to aid applied researchers in designing GMM studies that adequately measure the patterns of alcohol use that individuals exhibit over time. Researchers may then conduct more fine-grained examinations of etiological predictors of and distal outcomes associated with the latent class trajectories. These and subsequent findings may also facilitate identification of individuals for prevention or intervention programs based on information about the predictors of particular alcohol use trajectories. PUBLIC HEALTH RELEVANCE: Project Narrative: The proposed research seeks to enhance our knowledge of how to best measure individuals' patterns of alcohol use during adolescence and young adulthood, which is a key period for the development of alcohol- related behaviors. As indicated in the Surgeon General's report (U.S. Department of Health and Human Services, 2007), it is important to understand individuals' patterns of alcohol use over time given the implications such understanding has for tailoring prevention and intervention programs to individuals who exhibit particular patterns of alcohol use.

描述（由申请人提供）： 摘要：青春期和青年期的饮酒仍然是一个重要的研究领域，这一点得到了国家酒精滥用和酒精中毒研究所 (NIAAA) 未成年人饮酒研究计划以及国家酒精滥用和酒精中毒问题咨询委员会工作组的报告 (2002) 的充分认可。鉴于饮酒对个人和社会产生的生物、社会和环境影响，饮酒及其负面后果是一个重大的公共卫生问题。更好地了解个人在这个关键发育时期随时间表现出的不同饮酒模式（例如，持续低饮酒量、快速增加饮酒量）非常重要。增长混合模型 (GMM) 是一种统计技术，用于识别随着时间的推移表现出不同饮酒模式的潜在个体亚组。尽管 GMM 得到广泛使用，但仍有少数研究探讨了研究设计因素如何影响用于识别 GMM 中潜在亚组的饮酒轨迹。拟议的研究特别关注纵向研究中测量时间（即评估的数量和间隔）的影响。在 GMM 背景下，关于如何分配评估空间的决策尤其具有挑战性，因为根据设计特征而不是实际变化，假设的潜在亚组可能会随着时间的推移表现出不同的饮酒趋势。 该项目旨在研究测量时间如何影响 GMM 背景下个人饮酒轨迹的形状。具体目标是：（1）进行蒙特卡罗模拟研究，评估评估的数量和间隔如何影响酒精使用轨迹，用于识别 GMM 中的潜在酒精使用亚组； (2) 使用 1997 年全国青年纵向调查的酒精数据提供 GMM 的应用，表明评估的数量和间隔在多大程度上影响用于识别潜在亚组的酒精使用轨迹； (3) 将研究结果传达给定量研究人员和应用研究人员，并提出设计纵向 GMM 研究的具体考虑因素。拟议研究的主要意义是帮助应用研究人员设计 GMM 研究，以充分测量个人随时间推移表现出的饮酒模式。然后，研究人员可以对与潜在类别轨迹相关的病因预测因子和远端结果进行更细粒度的检查。这些和随后的发现也可能有助于根据有关特定酒精使用轨迹的预测因素的信息识别个人以进行预防或干预计划。 公共卫生相关性： 项目叙述：拟议的研究旨在增强我们对如何最好地衡量个人在青春期和成年早期的饮酒模式的了解，这是酒精相关行为发展的关键时期。正如卫生局局长的报告（美国卫生与公众服务部，2007 年）所指出的，了解个人随时间的饮酒模式非常重要，因为这种了解对于针对表现出特定饮酒模式的个人制定预防和干预计划具有重要意义。