课题基金 / 基金详情

Identifying Modifiable Influences on Alcohol Problems in High-Risk Neighborhoods

Identifying Modifiable Influences on Alcohol Problems in High-Risk Neighborhoods
确定对高风险社区酒精问题的可改变影响
批准号:
8841283
负责人:
Katherine J. Karriker-Jaffe
金额:
$30.8万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-05-10 至 2017-04-30

项目摘要

项目成果

Katherine J. Karriker-Jaffe的其他基金

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中文摘要
翻译
描述(由申请人提供):邻里关系可能会对酗酒结果产生负面影响,但很少有研究研究邻里关系、社会网络和个人因素之间的协同纵向相互关系如何与酗酒问题的复发和康复相关。随着时间的推移,缺乏对这些相互关系的了解,限制了我们设计全面预防和治疗以解决酒精问题的能力。为了解决现有文献中的重大差距并为服务规划提供信息,这项研究将描述抑制复发和支持康复的健康社区的特征。这项研究还将确定可以进行干预的缓冲因素,以帮助防止高危社区居民复发。我们建议开发和测试酒精问题复发和康复的社会生态学模型,以描述邻居、社会网络和个人因素如何独立和交互地预测随着时间的推移酒精问题和依赖的复发和康复。研究的目的是:(1)描述治疗设施、自助资源和酒精销售点在全县范围内相对于社区社会经济资源、稳定性和无序的分布;(2)检查这些社区特征对复发、康复、治疗利用和自助参与的纵向影响;(3)确定随着时间的推移缓冲或加剧社区影响的社会网络和个人因素;以及(4)测试问题饮酒者是否随着时间的推移而进入高危社区。这项研究使用了11年来从一个人口结构多样化的城乡县的治疗中心(N=926)和社区(N=672)招募的问题和依赖饮酒者的数据。现有的访谈数据将通过每次访谈的地理编码地址与社区指标(包括药物滥用治疗、自助资源和酒精销售点的地点和特征;社会经济资源;混乱和犯罪)联系起来。分析包括邻域映射和空间随机效应模型,以及多层次纵向分析,如潜在增长曲线建模和潜在转变分析。这项研究对预防复发、提供正式的药物滥用治疗和自助以及与饮酒渠道有关的政策有几个实际意义。这项创新的研究将通过确定在治疗期间可以解决的特定邻里触发因素来帮助预防复发。它还将确定可修改的因素,如社交网络对戒酒的支持或参与自助,以减少生活在高危社区的问题和依赖饮酒者所经历的负面后果,这可能会由治疗和预防专家来解决。还可以开发辅助项目,为财力有限的客户更换住房提供便利,帮助他们在接受治疗后离开高危社区。研究结果还将说明饮酒渠道在哪里特别有害,并强调哪里需要新的治疗计划和自助小组。
英文摘要
DESCRIPTION (provided by applicant): Neighborhood contexts can negatively impact alcohol outcomes, but few studies have examined how synergistic longitudinal interrelationships between neighborhoods, social networks and individual factors relate to relapse and recovery from alcohol problems. Lack of knowledge about these interrelationships over time limits our ability to design comprehensive prevention and treatment to address alcohol problems. To address significant gaps in the extant literature and inform service planning, this study will characterize healthy neighborhoods that inhibit relapse and support recovery. The study will also identify buffering factors amenable to intervention that can help prevent relapse by residents of high-risk neighborhoods. We propose to develop and test a socioecological model of relapse and recovery from alcohol problems to describe how neighborhood, social network and individual factors independently and interactively predict relapse and recovery from alcohol problems and dependence over time. The research aims are: (1) Describe county-wide distribution of treatment facilities, self-help resources and alcohol outlets relative to neighborhood socioeconomic resources, stability and disorder over time; (2) Examine longitudinal effects of these neighborhood characteristics on relapse, recovery, treatment utilization and self-help involvement; (3) Identify social network and individual factors that buffer or exacerbate neighborhood effects over time; and (4) Test whether there is a "downward drift" of problem drinkers into high-risk neighborhoods over time. The study uses data collected over 11 years from problem and dependent drinkers recruited from treatment centers (N=926) and the community (N=672) in a demographically diverse urban and rural county. Existing interview data will be linked with neighborhood indicators (including locations and characteristics of substance abuse treatment, self-help resources and alcohol outlets; socioeconomic resources; disorder and crime) via geocoded addresses at each interview. Analyses include neighborhood mapping and spatial random effects models, as well as multilevel longitudinal analysis, such as latent growth curve modeling and latent transition analysis. The study has several practical implications for relapse prevention, provision of formal substance abuse treatment and self-help, and policy pertaining to alcohol outlets. This innovative study will help prevent relapse by identifying specific neighborhood triggers that can be addressed during treatment. It also will identify modifiable factors, such as social network support for sobriety or participation in self-help that reduce negative consequences experienced by problem and dependent drinkers who live in high-risk neighborhoods, which could be addressed by treatment and prevention specialists. Ancillary programs also could be developed to facilitate housing changes by clients with limited financial resources to help them move from high-risk neighborhoods after treatment. Findings also will illustrate where alcohol outlets are especially detrimental and highlight where new treatment programs and self-help groups are needed.
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Supplement for Cloud Computing: Alcohol Use Disorder Treatment Simulation
  • 批准号:
    10827563
  • 项目类别:
  • 资助金额:
    $22.49万
  • 财政年份:
    2023
  • 负责人:
    Katherine J. Karriker-Jaffe
  • 依托单位:
Alcohol Use Disorder Treatment Simulation: Modeling treatment impacts on alcohol-related disparities
  • 批准号:
    10370506
  • 项目类别:
  • 资助金额:
    $76.11万
  • 财政年份:
    2022
  • 负责人:
    Katherine J. Karriker-Jaffe
  • 依托单位:
Alcohol Use Disorder Treatment Simulation: Modeling treatment impacts on alcohol-related disparities
  • 批准号:
    10602396
  • 项目类别:
  • 资助金额:
    $78.79万
  • 财政年份:
    2022
  • 负责人:
    Katherine J. Karriker-Jaffe
  • 依托单位:
Secondhand Harms from Alcohol & Drugs: Impacts on Families and Communities across the US
  • 批准号:
    10318035
  • 项目类别:
  • 资助金额:
    $62.8万
  • 财政年份:
    2021
  • 负责人:
    Katherine J. Karriker-Jaffe
  • 依托单位:
海外基金