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Applying Latent Variable Modeling to Cormorbidity Treatment Research

Applying Latent Variable Modeling to Cormorbidity Treatment Research
将潜变量模型应用于疾病治疗研究
批准号:
8321080
负责人:
MATT G KUSHNER
金额:
$11.73万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-25 至 2014-08-31

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DESCRIPTION (provided by applicant): The objective of this K02 application is to allow the candidate to increase the time he has allocated to research and related career development activities from a projected annual average of between 25-45% without the K02 to between 75-80% with the K02. The application overviews the candidate's 15-year history of NI/\AA-supported alcohol research and provides a career development plan aimed at acquiring and deploying sophisticated data analytic and methodological strategies that fall under the broad heading of latent variable-structural equation modeling (LV-SEM) (e.g., factor analysis, path analysis, latent class and trait modeling, growth mixture modeling, item response theory). This would be accomplished via specific career development objectives involving: 1) interactions with mentors and collaborators (15%); 2) hypotheses testing (25%); 3) formal courses/training (25%); 4) scholarly production (25%); and, 5) teaching/ service (10%). The "parent R01" ("CBT Treatment of Anxiety Disorders in Comorbid Alcoholics" /\A0105069) targets a sample of 400 patients undergoing a standard community-based alcoholism treatment program who are also diagnosed with at least one of several common comorbid anxiety and affective ("internalizing") disorders. In addition to the alcohol treatment, patients receive one of two psychosocial treatments for internalizing disorder. LV-SEM would allow the candidate to empirically partition highly inter- correlated internalizing disorders/symptoms in the parent R01 dataset into distinct vs. common components that could then be related in causal models to the alcohol and internalizing treatment outcomes. Next, the candidate would replicate these models in community, student and psychiatric-based datasets that are either publicly available (e.g., NESARC) or available via his collaborators (e.g., Drs. Ken Sher and Carrie Randall). These efforts would provide an empirically parsimonious characterization of the internalizing problems experienced by individuals with alcohol use disorders and how these relate to alcoholism and psychiatric treatments across a number of populations and treatment modalities. The longer-term goal would be to develop more effective treatments for alcohol disorders with comorbid internalizing disorders. RELEVANCE: By further clarifying the best clinical strategies for and conceptualization of internalizing disorders occurring in alcoholism treatment patients, the proposed work will improve our ability to effectively treat alcohol dependence.
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Validating an Autonomous Interactive Internet-Based Delivery of an Empirically Supported Cognitive Behavioral Therapy for Comorbidity
  • 批准号:
    10176912
  • 项目类别:
  • 资助金额:
    $45.59万
  • 财政年份:
    2021
  • 负责人:
    MATT G KUSHNER
  • 依托单位:
Validating an Autonomous Interactive Internet-Based Delivery of an Empirically Supported Cognitive Behavioral Therapy for Comorbidity
  • 批准号:
    10597539
  • 项目类别:
  • 资助金额:
    $45.82万
  • 财政年份:
    2021
  • 负责人:
    MATT G KUSHNER
  • 依托单位:
Validating an Autonomous Interactive Internet-Based Delivery of an Empirically Supported Cognitive Behavioral Therapy for Comorbidity
  • 批准号:
    10404961
  • 项目类别:
  • 资助金额:
    $43.65万
  • 财政年份:
    2021
  • 负责人:
    MATT G KUSHNER
  • 依托单位:
Dismantling the Components and Dosing of CBT for Co-Occurring Disorders
  • 批准号:
    8716244
  • 项目类别:
  • 资助金额:
    $51.49万
  • 财政年份:
    2014
  • 负责人:
    MATT G KUSHNER
  • 依托单位:
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