Longitudinal Dyadic Analysis of HIV-positive Substance Users with Trauma History

有创伤史的艾滋病毒阳性物质使用者的纵向二元分析

基本信息

批准号：
8033452
负责人：
Deborah Lynne Jones
金额：
$ 8.05万
依托单位：
UNIVERSITY OF MIAMI SCHOOL OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-09-30 至 2011-09-29
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8033452
关键词：
AIDS prevention AIDS/HIV problem Address Adult Age Alcohol or Other Drugs use Autoimmune Diseases Award Behavior Belief Brain Cardiovascular Diseases Childhood Cognitive Collaborations Competence Complex Couples Data Data Set Development Diabetes Mellitus Equation Ethnic Origin Female Frequencies Gender Goals HIV HIV Seropositivity Health Health behavior Individual Intervention K-18 conjugate K-Series Research Career Programs Learning Life Linear Models Malignant Neoplasms Mediating Mediator of activation protein Mental Health Mental disorders Mentors Meta-Analysis Methods Modeling Neurosecretory Systems Outcome Outcome Study Participant Population Post-Traumatic Stress Disorders Pregnancy Process Public Health Randomized Recording of previous events Relative (related person)Research Research Personnel Research Project Grants Risk Risk Behaviors Risk Reduction Role Severities Sex Orientation Sexual Partners Sexually Transmitted Diseases Socioeconomic Status Statistical Methods Stress Survivors Symptoms Techniques Theoretical model Time Translational Research Translations Trauma Victimization Woman behavioral/social science career experience group intervention immune function member men pediatric trauma post intervention response sex risk sexual trauma skills standard of care stressor translational study

项目摘要

DESCRIPTION (provided by applicant): As a mid-career investigator in applied behavioral and social sciences related to HIV/AIDS, my goal in applying for a Short-term Mentored Career Development Award (K-18) is to learn to employ hierarchical linear modeling/structural equation modeling analytic strategies to more comprehensively address the complexity of the dyadic data sets generated by my collaborative research on HIV prevention with couples. These analytic skills would then enable me to assess the interactive effects of trauma, substance use, sexual partners and HIV on health behavior and health outcomes and apply those results at the individual, couple and population level. To meaningfully apply these data at the population level also require the ability to utilize and collaboratively develop statistical methods for translational studies and public health models. The research project, "Longitudinal Dyadic Analysis of HIV-positive Substance Users with a Trauma History" addresses the role of a potential third variable (substance use and sexual partners) on risk behavior outcomes in response to interventions among men and women as couples in which one member or both may be substance users and have a history of sexual trauma. This project seeks to clarify the relationship between the influence of sexual partners, substance use and sexual trauma on risk behaviors utilizing longitudinal dyadic analysis within the Actor Partner Interdependence Model framework (APIM). Specifically, I propose the following educational and research goals to: 1. Learn how to apply the APIM (theoretical model) for interpreting couples behavior and their response to interventions using the associated longitudinal dyadic statistical techniques (analytic component) to analyze existing data sets. Additionally, I propose to conduct analyses on a research project to using an existing R01: 2. Address the interactive effects of trauma, substance use, sexual partners and HIV on health behavior and health outcomes at the individual, couple and population level, utilizing longitudinal multiple groups the Actor Partner Interdependence Model framework (APIM) for indistinguishable dyads 3. Gain skills in the use and development of public health models and analytic strategies for translational studies. The APIM, which applies complex techniques of longitudinal structural equation modeling to the analysis of couple dyads in group formats, addressing the relative influences of partners and mediating factors on risk behaviors, will enable me to acquire the critical skills to interpret dyadic data and provide me with a bridge to develop dyadic translational research models and methods for couples interventions. Support through the K18 will provide protected time to gain competence in dyadic and public health statistical methods and models, while my research collaborations provide the remaining 50% time during the period of the award. PUBLIC HEALTH RELEVANCE: As a mid-career investigator in applied behavioral and social sciences related to HIV/AIDS, my goal in applying for a Short-term Mentored Career Development Award (K-18) is to learn to employ hierarchical linear modeling/structural equation modeling analytic strategies to more adequately address the complexity of the dyadic data sets generated by my research on HIV prevention with couples. These datasets address the interactive effects of trauma, substance use, sexual partners and HIV on health behavior and health outcomes at the individual, couple and population level.

描述（由申请人提供）：作为与艾滋病毒/艾滋病相关的应用行为和社会科学领域的职业中期调查员，我申请短期指导职业发展奖（K-18）的目标是学习采用分层线性建模/结构方程建模分析策略，以更全面地解决我与夫妇进行的艾滋病毒预防合作研究所生成的二元数据集的复杂性。这些分析技能将使我能够评估创伤、药物滥用、性伴侣和艾滋病毒对健康行为和健康结果的相互作用影响，并将这些结果应用于个人、夫妇和人口层面。为了在人口层面上有意义地应用这些数据，还需要能够利用和协作开发转化研究和公共卫生模型的统计方法。该研究项目“有创伤史的艾滋病毒阳性物质使用者的纵向二元分析”探讨了潜在的第三个变量（物质使用和性伴侣）对风险行为结果的作用，以应对男性和女性作为夫妇的干预措施，其中一名或两名成员可能是药物滥用者并有性创伤史。该项目旨在利用行为者伴侣相互依赖模型框架（APIM）内的纵向二元分析来阐明性伴侣、物质使用和性创伤对危险行为的影响之间的关系。具体来说，我提出以下教育和研究目标： 1. 学习如何应用 APIM（理论模型）来解释夫妻行为及其对干预措施的反应，使用相关的纵向二元统计技术（分析组件）来分析现有数据集。此外，我建议使用现有的 R01 对一个研究项目进行分析： 2. 利用纵向研究，解决创伤、药物滥用、性伴侣和艾滋病毒对个人、夫妇和人口层面的健康行为和健康结果的交互影响。将参与者合作伙伴相互依赖模型框架 (APIM) 进行多个分组，以形成无法区分的二元组 3. 获得使用和开发公共卫生模型和转化研究分析策略的技能。 APIM 将纵向结构方程建模的复杂技术应用于群体形式的情侣分析，解决合作伙伴和中介因素对风险行为的相对影响，将使我能够获得解释二元数据的关键技能，并为我提供帮助。搭建桥梁，开发夫妻干预的二元转化研究模型和方法。通过 K18 的支持将提供受保护的时间来获得二元和公共卫生统计方法和模型的能力，而我的研究合作提供了奖励期间剩余的 50% 时间。公共健康相关性：作为与艾滋病毒/艾滋病相关的应用行为和社会科学领域的职业中期调查员，我申请短期指导职业发展奖（K-18）的目标是学习采用分层线性模型/结构方程建模分析策略，以更充分地解决我在夫妻艾滋病预防研究中生成的二元数据集的复杂性。这些数据集解决了创伤、药物滥用、性伴侣和艾滋病毒对个人、夫妇和人口层面的健康行为和健康结果的交互影响。