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Mindfulness and acceptance-based interventions for obesity: Using a factorial design to identify the most effective components

Mindfulness and acceptance-based interventions for obesity: Using a factorial design to identify the most effective components
基于正念和接受的肥胖干预措施:使用因子设计来确定最有效的组成部分
批准号:
10429914
负责人:
Evan M Forman
金额:
$55.46万
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
项目状态:
已结题
起止时间:
2019-08-15 至 2024-05-31

项目摘要

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中文摘要
翻译
项目概要/摘要 行为减肥治疗(BT),教授认知和行为技能,是黄金标准, 肥胖症的一线治疗结果虽然具有临床意义,但在许多情况下被认为是次优的。 参与者未能达到和/或维持与关键健康福利相关的5%和10%基准。超过 在过去的30年里,许多试验都测试了标准BT技能的认知和行为创新,但因此, 事实上,几乎没有一种方法能显著改善体重减轻。正念和接受为基础 肥胖症的行为治疗(MABTs)是一个例外,因为严格的试验已经证明, 当直接与金标准BT相比时,这种方法的重量损失显著更大。然而, 结果各不相同,其组成也各不相同。持续改进和成功的能力 传播肥胖症的行为治疗取决于该领域对以下问题的理解: MABT组分是最有效的。与多阶段优化策略的第一阶段一致 (MOST)方法,我们回顾了MABT的理论描述,并确定了三个关键的MABT组件: (1)正念意识,(2)正念接受,(3)价值观清晰。符合第二阶段的一个 最重要的是,本研究将采用完整的2x2 x2析因设计,其中288名超重/肥胖参与者 被分配到八种行为减肥治疗之一,即,代表MABT的每个排列 治疗中包括或排除的成分。由于析因设计能够合并 条件来检验每个主效应,分析具有与双臂设计相同的功效。主要目的 本研究的目的是评估正念意识、正念接受和正念认知的独立功效。 MABT对体重减轻的清晰度分量值(治疗后以及6、12和24个月随访时) 高于标准BT。次要目的是:(1)评估正念的独立功效 意识,正念接受和价值观的明确组成部分的MABT对腰围,卡路里 摄入量、身体活动和生活质量;(2)确认每个治疗成分影响变量 它的目标;(3)为了检验治疗成分的疗效是由以下因素调节的假设: 对内部和外部食物线索的敏感性。探索性的目的是量化组件的相互作用 这些效应可以是协同的、完全加和的或部分加和的。本研究探讨了一种创新的, 特别是有前途的行为方法,并将是第一个利用肥胖的全因子设计 干预优化此外,这将是有史以来第一次进行成分分析的研究, MABT成分的独立功效,以及第一次检查行为减肥的相互作用 各组成部分之间的相互关系以及参与者的基线特征。结果将定位字段, 未来的工作,即,评价预期具有上级疗效的优化治疗, 可传播性
英文摘要
Project Summary/Abstract Behavioral weight loss treatment (BT), which teaches cognitive and behavioral skills, is the gold standard and first line of treatment for obesity. Outcomes, while clinically significant, are considered suboptimal in that many participants fail to reach and/or maintain the 5 and 10% benchmarks associated with key health benefits. Over the past 30 years, many trials have tested cognitive and behavioral innovations on standard BT skills, but thus far virtually none has produced significantly improved weight losses. Mindfulness and acceptance-based behavioral treatments (MABTs) for obesity is an exception in that rigorous trials have demonstrated considerably greater weight losses for this approach when directly compared to gold standard BT. Yet, MABTs’ outcomes have varied, as have their composition. The ability to continue improving and successfully disseminating behavioral treatments for obesity depends on the field increasing its understanding of which MABT components are most efficacious. Consistent with a Phase I of a Multiphasic Optimization Strategy (MOST) approach, we reviewed theoretical accounts of MABTs and identified three key MABT components: (1) Mindful Awareness, (2) Mindful Acceptance, and (3) Values Clarity. Consistent with the second phase of a MOST, this study will utilize a full 2x2x2 factorial design in which 288 overweight/obese participants are assigned to one of eight behavioral weight loss treatments, i.e., representing each permutation of MABT components being included or excluded from the treatment. Due to the ability of a factorial design to pool conditions to examine each main effect, analyses have the same power as a two-arm design. The primary aim of the current study is to evaluate the independent efficacy of mindful awareness, mindful acceptance and values clarity components of MABT on weight loss (at post-treatment and at 6, 12 and 24 months follow-up) over and above standard BT. Secondary aims are to: (1) To evaluate the independent efficacy of mindful awareness, mindful acceptance and values clarity components of MABT on waist circumference, calorie intake, physical activity and quality of life; (2) To confirm that each treatment component impacts the variable which it targets; (3) To test the hypotheses that the efficacy of the treatment components is moderated by susceptibility to internal and external food cues. The exploratory aim is to quantify the component interaction effects, which may be synergistic, fully additive, or partially additive. This study investigates an innovative and especially promising behavioral approach, and will be one of the first to utilize a full factorial design for obesity intervention optimization. Furthermore, it will be the first-ever study to conduct a component analysis to discern independent efficacies of MABT components, and the first to examine interactions of behavioral weight loss components with each other and with baseline characteristics of participants. Results will position the field for future work, i.e., the evaluation of an optimized treatment that can be expected to have superior efficacy and disseminability.
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Using Artificial Intelligence to Optimize Delivery of Weight Loss Treatment
  • 批准号:
    10400867
  • 项目类别:
  • 资助金额:
    $61.79万
  • 财政年份:
    2021
  • 负责人:
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  • 依托单位:
Engaging men in weight loss with a game-based mHealth and neurotraining program
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  • 项目类别:
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    2021
  • 负责人:
    Evan M Forman
  • 依托单位:
Using Artificial Intelligence to Optimize Delivery of Weight Loss Treatment
  • 批准号:
    10210830
  • 项目类别:
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    $63.42万
  • 财政年份:
    2021
  • 负责人:
    Evan M Forman
  • 依托单位:
Using Artificial Intelligence to Optimize Delivery of Weight Loss Treatment
  • 批准号:
    10627764
  • 项目类别:
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    $61.86万
  • 财政年份:
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  • 负责人:
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