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
基本信息
- 批准号:9762330
- 负责人:
- 金额:$ 65.3万
- 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:2019-08-15 至 2024-05-31
- 项目状态:已结题
- 来源:
- 关键词:AftercareAttentionAwarenessBehavior TherapyBehavioralBenchmarkingBody Weight decreasedCaloriesCause of DeathCharacteristicsCognitiveCuesDataEffectivenessElementsEvaluationFoodFutureGoalsGoldHealth BenefitHealth PrioritiesIndividualIntakeInterventionKnowledgeObesityOutcomeOverweightParticipantPhasePhysical activityPositioning AttributePredispositionQuality of lifeScienceSeriesTestingTrainingTreatment EfficacyTreatment outcomeUncertaintyWeight maintenance regimenWorkarmbaseclinically significantcognitive testingcostdesignfollow up assessmentfollow-upimprovedinnovationmindfulnessobesity treatmentpsychologicrandomized trialskillstherapy designtreatment optimizationvirtualwaist circumference
项目摘要
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.
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)
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Evan M Forman其他文献
Evan M Forman的其他文献
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{{ truncateString('Evan M Forman', 18)}}的其他基金
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10400867 - 财政年份:2021
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Using Artificial Intelligence to Optimize Delivery of Weight Loss Treatment
使用人工智能优化减肥治疗的实施
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10210830 - 财政年份:2021
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- 资助金额:
$ 65.3万 - 项目类别:
Engaging men in weight loss with a game-based mHealth and neurotraining program
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- 资助金额:
$ 65.3万 - 项目类别:
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
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- 资助金额:
$ 65.3万 - 项目类别:
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
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