Gender differences in problem drinking trajectories

描述（由申请人提供）：此酒精服务二次分析应用程序在一项独特的纵向研究中研究了672名未经治疗的依赖者和问题饮酒者的概率样本中的性别差异，以及926名进入酒精治疗的个人。最初的研究在1995-96年以及1年、3年、5年和7年后采访了受访者。我们的主要目的是更好地了解问题和依赖性饮酒者在人口统计学特征和问题严重程度（“个人特征”），酒精治疗和其他健康和人类服务机构（“正式服务”）的接触和干预以及社交网络和12步参与（“非正式影响”）在7年内改善饮酒轨迹中的作用方面的性别差异。我们建立在文献和我们的研究到目前为止。以前，我们研究性别作为一个重要的控制变量。我们的研究结果表明，在解决医疗，精神病，刑事司法和福利服务，以及工作场所，12步参与和社交网络对酒精消费的影响问题时，需要更多地关注性别差异。我们的方法借鉴了纵向数据分析的现代方法，以及我们处理这些和类似数据的经验。我们将使用增长曲线分析（GCA）和潜在类增长模型（LCGM）。我们建议解决仔细假设分析的性别差异的基础上的文献，以及我们的实证工作的样本，使用层次模型来评估性别差异，酒精治疗和社区机构的利用，并在AA使用，在7年。我们研究如何个人特征，非正式的影响和正式的服务影响个人饮酒轨迹的妇女和男子。我们还研究了潜在的类的基础上的酒精消费量和饮酒模式，以及他们对酒精相关的问题，男性和女性在7年的影响。我们的研究结果对社交网络、社区机构和酒精治疗机构的干预措施有影响，并将有助于我们理解性别差异对饮酒的影响，因为随着时间的推移，这些影响得到了证明。

DESCRIPTION (provided by applicant): This alcohol services secondary analysis application studies gender differences in a unique , longitudinal study of a probability sample of 672 untreated dependent and problem drinkers, and 926 individuals entering alcohol treatment. The original study interviewed respondents in 1995-96, and 1, 3, 5, and 7 years later. Our primary aim is to better understand gender differences among problem and dependent drinkers in the roles of demographic characteristics and problem severity ("individual characteristics"), contacts and interventions from alcohol treatment and other health and human service agencies ("formal services"), and from social networks and 12-step involvement ("informal influences") in improving drinking trajectories over a 7 year period. We build on the literature and our study to date. Previously we examined gender as an important control variable. Our findings suggest the need for greater attention to gender differences in addressing questions about the influences of medical, psychiatric, criminal justice, and welfare services, as well as the workplace, 12-step participation, and social networks on alcohol consumption over time. Our approach draws upon modern methods for longitudinal data analysis, and from our experience working with these and similar data. We will use both Growth Curve Analysis (GCA) and Latent Class Growth Modeling (LCGM). We propose to address carefully hypothesized analyses of gender differences based on the literature, as well as our empirical work on the sample, using hierarchical modeling to assess gender differences in alcohol treatment and community agency utilization, and in AA use, over the 7 years. We examine how individual characteristics, informal influences and formal services affect individual drinking trajectories for women and men. We also examine underlying latent classes based on volume of alcohol consumed and on drinking patterns, and their effects on alcohol-related problems for men and women over the 7 years. Our findings have implications for interventions by social networks, by community agencies, and by alcohol treatment agencies, and will contribute to our understanding of the impact of gender differences in drinking as they are evidenced over time.