Improving Weight Loss in Early Non-responders to Behavioral Treatment

改善早期行为治疗无反应者的减肥效果

基本信息

  • 批准号:
    10063868
  • 负责人:
  • 金额:
    $ 18.35万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-01-10 至 2023-11-30
  • 项目状态:
    已结题

项目摘要

PROJECT SUMMARY/ABSTRACT My long-term career goal is to be an independent investigator who develops effective obesity treatments and matches these treatments to patients' characteristics. Through my training in clinical psychology, I gained skills in the development and delivery of behavioral treatments (BTs) for obesity and in conducting randomized controlled trials (RCTs) to test their efficacy. As a postdoctoral fellow, I was then introduced to obesity pharmacotherapy, but still have limited experience in this area. In order to successfully develop a career in precision medicine for obesity, I will need additional training in behavioral, biological, and pharmacological influences on body weight. The proposed K23 award will allow me to devote 95% effort to filling critical gaps in my training and to conducting research that will prepare me to be an independent investigator in obesity treatment. My training plan will prepare me for an independent research career by increasing my knowledge in three key areas: 1) behavioral phenotypes associated with obesity and methods for their objective measurement; 2) neuroendocrine mechanisms of energy balance regulation that may impact weight loss; and 3) the use of pharmacologic agents to improve weight loss. I will accomplish these objectives by receiving guidance from mentors, engaging in hands-on research training, and completing relevant coursework and seminars. My research project will complement these training goals by examining behavioral phenotypes and neuroendocrine biomarkers as predictors of early weight loss and by testing whether medication enhances weight loss in patients with a suboptimal early response to BT alone. Participants will complete an initial assessment of behavioral and biological characteristics, followed by 4 weeks of BT. Those who lose < 2.0% of initial weight during the run-in will then be randomly assigned to an additional 24 weeks of: 1) BT plus placebo; or 2) BT plus medication (liraglutide 3.0 mg). I believe that low satiety will predict poor early weight loss with BT and that pharmacotherapy will enhance 24-week weight loss for patients with suboptimal response to BT. This project could shape best practice recommendations for obesity treatment and ultimately result in algorithms for matching treatments to patient characteristics. The environment at the Center for Weight and Eating Disorders at the University of Pennsylvania is well-equipped with staff, resources, and infrastructure to support the proposed project. I will also access state-of-the-art facilities, coursework, and seminars at Penn to complete my research and training goals. My mentorship team will be led by Dr. Thomas Wadden (Professor of Psychology) and includes training from Dr. Tanja Kral (Associate Professor of Nursing) in behavioral phenotypes of obesity and Dr. Matthew Hayes (Associate Professor of Nutritional Neuroscience) in mechanisms of energy balance. This comprehensive, interdisciplinary mentored approach will allow me to acquire knowledge in areas essential to my career goals, implement the proposed research plan, and develop a successful R01 application prior to the end of the K23 award.
项目总结/文摘

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Jennifer Shaw Tronieri其他文献

Jennifer Shaw Tronieri的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Jennifer Shaw Tronieri', 18)}}的其他基金

Improving Weight Loss in Early Non-responders to Behavioral Treatment
改善早期行为治疗无反应者的减肥效果
  • 批准号:
    10304857
  • 财政年份:
    2019
  • 资助金额:
    $ 18.35万
  • 项目类别:
Improving Weight Loss in Early Non-responders to Behavioral Treatment
改善早期行为治疗无反应者的减肥效果
  • 批准号:
    10528433
  • 财政年份:
    2019
  • 资助金额:
    $ 18.35万
  • 项目类别:

相似海外基金

Approximate algorithms and architectures for area efficient system design
区域高效系统设计的近似算法和架构
  • 批准号:
    LP170100311
  • 财政年份:
    2018
  • 资助金额:
    $ 18.35万
  • 项目类别:
    Linkage Projects
AMPS: Rank Minimization Algorithms for Wide-Area Phasor Measurement Data Processing
AMPS:用于广域相量测量数据处理的秩最小化算法
  • 批准号:
    1736326
  • 财政年份:
    2017
  • 资助金额:
    $ 18.35万
  • 项目类别:
    Standard Grant
Low Power, Area Efficient, High Speed Algorithms and Architectures for Computer Arithmetic, Pattern Recognition and Cryptosystems
用于计算机算术、模式识别和密码系统的低功耗、面积高效、高速算法和架构
  • 批准号:
    1686-2013
  • 财政年份:
    2017
  • 资助金额:
    $ 18.35万
  • 项目类别:
    Discovery Grants Program - Individual
Rigorous simulation of speckle fields caused by large area rough surfaces using fast algorithms based on higher order boundary element methods
使用基于高阶边界元方法的快速算法对大面积粗糙表面引起的散斑场进行严格模拟
  • 批准号:
    375876714
  • 财政年份:
    2017
  • 资助金额:
    $ 18.35万
  • 项目类别:
    Research Grants
Low Power, Area Efficient, High Speed Algorithms and Architectures for Computer Arithmetic, Pattern Recognition and Cryptosystems
用于计算机算术、模式识别和密码系统的低功耗、面积高效、高速算法和架构
  • 批准号:
    1686-2013
  • 财政年份:
    2016
  • 资助金额:
    $ 18.35万
  • 项目类别:
    Discovery Grants Program - Individual
Low Power, Area Efficient, High Speed Algorithms and Architectures for Computer Arithmetic, Pattern Recognition and Cryptosystems
用于计算机算术、模式识别和密码系统的低功耗、面积高效、高速算法和架构
  • 批准号:
    1686-2013
  • 财政年份:
    2015
  • 资助金额:
    $ 18.35万
  • 项目类别:
    Discovery Grants Program - Individual
Low Power, Area Efficient, High Speed Algorithms and Architectures for Computer Arithmetic, Pattern Recognition and Cryptosystems
用于计算机算术、模式识别和密码系统的低功耗、面积高效、高速算法和架构
  • 批准号:
    1686-2013
  • 财政年份:
    2014
  • 资助金额:
    $ 18.35万
  • 项目类别:
    Discovery Grants Program - Individual
AREA: Optimizing gene expression with mRNA free energy modeling and algorithms
区域:利用 mRNA 自由能建模和算法优化基因表达
  • 批准号:
    8689532
  • 财政年份:
    2014
  • 资助金额:
    $ 18.35万
  • 项目类别:
CPS: Synergy: Collaborative Research: Distributed Asynchronous Algorithms and Software Systems for Wide-Area Monitoring of Power Systems
CPS:协同:协作研究:用于电力系统广域监控的分布式异步算法和软件系统
  • 批准号:
    1329780
  • 财政年份:
    2013
  • 资助金额:
    $ 18.35万
  • 项目类别:
    Standard Grant
CPS: Synergy: Collaborative Research: Distributed Asynchronous Algorithms and Software Systems for Wide-Area Mentoring of Power Systems
CPS:协同:协作研究:用于电力系统广域指导的分布式异步算法和软件系统
  • 批准号:
    1329745
  • 财政年份:
    2013
  • 资助金额:
    $ 18.35万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了