Alcohol Use: Nonlinearities in Intraindividual Variables

饮酒：个体内变量的非线性

• 批准号: 6835341
• 负责人: ARCHANA JAJODIA
• 金额: $ 3.38万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-08-16 至 2006-08-15
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6835341
• 关键词: adult human (21+); alcoholic beverage consumption; alcoholism /alcohol abuse; artificial intelligence; behavior prediction; behavioral /social science research tag; case history; clinical research; computer human interaction; expectancy; experience; human subject; interview; longitudinal human study; mathematical model; model design /development; personality; predoctoral investigator; questionnaires; reflex

DESCRIPTION (provided by applicant): Alcohol use is a complex and dynamic phenomenon, determined by a multiplicity of factors that possibly interact in a nonlinear manner. There has been very limited research so far exploring the nonlinearities in the etiology of alcohol use. The purpose of the proposed study is to design a nonlinear predictive model of alcohol use and abuse in the general population with the help of implicit and explicit alcohol expectancy measures, as well as self-reports of family history and personality style. The complex and changing relationship of negative expectancies and alcohol use will also be examined with respect to participants' drinking histories and positive alcohol expectancies. The role of implicit expectancies in predicting drinking behavior, over and above explicit questionnaires, in a large (N = 400) community population will also be studied. Participants will complete a reaction time measure of their memory associations to alcohol, as well as other self-report measures of drinking, alcohol expectancies, personality, family history, etc., and a drinking history interview. Long-term data on drinking (3-month follow up) will also be collected. Data analysis will include artificial neural network modeling and multiple regression analyses.

描述（由申请人提供）：酒精使用是一种复杂且动态的现象，由可能以非线性方式相互作用的多种因素决定。迄今为止，探索酒精使用病因学非线性的研究非常有限。本研究的目的是借助隐性和显性的酒精预期测量以及家族史和人格风格的自我报告，设计一般人群中酒精使用和滥用的非线性预测模型。消极预期和饮酒之间复杂且不断变化的关系也将根据参与者的饮酒史和积极的饮酒预期进行检查。还将研究在大量（N = 400）社区人口中，除了显性问卷之外，隐性预期在预测饮酒行为中的作用。参与者将完成对酒精记忆关联的反应时间测量，以及饮酒、酒精预期、性格、家族史等的其他自我报告测量，以及饮酒史访谈。还将收集长期饮酒数据（3 个月随访）。数据分析将包括人工神经网络建模和多元回归分析。