SMART Weight Loss Management
SMART Weight Loss Management
批准号:
9547033
负责人:
Inbal Billie Nahum-Shani
金额:
$9.42万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-03-01 至 2021-02-28
关键词:
AddressAdultBehaviorBehavior TherapyBody Weight decreasedCar PhoneCaringCellular PhoneClinicalConsumptionCounselingDependencyEarly treatmentEquilibriumEvidence based treatmentFailureGuidelinesHealthHeterogeneityHigh PrevalenceIndividualInternetKnowledgeMaintenanceMediatingMonitorMotivationObesityOutcomeOverweightParticipantPathway interactionsPatientsPoliciesPopulationPublic HealthRandomizedRegulationResearchResourcesRiskSelf EfficacyTechnologyTestingTextTimeTreatment FailureWeightcostcost effectivenessfollow-upmHealthmobile applicationnovelobesity managementobesity treatmentpopulation healthpredictive modelingprimary outcomeprogramspublic health relevancerandomized trialresponsesoundstandard of caretooltrial designuptakeweight loss intervention
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): Obesity's high prevalence and costs make it a public health crisis, but current standard of care treatment impedes uptake and depletes resources by taking a one-size-fits-all approach. Guidelines recommend provision of expensive, burdensome treatment components (e.g., counseling, meal replacement) continuously to all consumers regardless of weight loss response. Stepped care that tries less costly evidence-based treatments first, reserving more resource-intensive treatments for suboptimal responders is a logical, equitable population health management strategy. However, stepped care approaches to obesity treatment have not yet incorporated inexpensive, widely available mHealth tools. It is unclear whether conjoint clinical and cost outcomes are better optimized by providing a low cost, low intensity, autonomously controlled mHealth treatment as the initial treatment with risk of nonresponse, or by providing a more costly, traditional obesity treatment with the potential to create a dependency that undermines autonomous motivation. The potential pitfall of beginning with mHealth treatment is that long-term outcome may be poor if nonresponse to initially insufficient treatment allows demoralization to set in. To reduce that risk, we will identify nonresponders earlier than previously has been possible by applying a predictive model derived from our prior mHealth obesity research and will quickly reallocate nonresponders to augmented treatment. We propose to use a novel experimental approach, the SMART (Sequential Multiple Assignment Randomized Trial), to randomize 400 overweight/obese adults to one of two first line treatments, either (1) an app alone (APP), or (2) the app plus coaching (APP +C). Those who do not respond to the first line treatment (i.e., evidenced by failure to lose weight) will be e-randomized to one of two subsequent augmentation tactics, either: (1) Modestly Step-Up: add another mHealth component (e.g., text messages), or (2) Vigorously Step-Up: add both a mHealth component (e.g., texts) and a more traditional component (e.g., coaching, meal replacement). Responders will continue with the same first line treatment for 12 weeks. Assessments will occur at 3, 6, and 12 months to determine (1) whether mHealth or traditional obesity treatment (coaching) is the optimal first line treatment for overweight/obese adults; and (2) whether the optimal response to weight loss failure is to modestly or vigorously augment the first line treatment. As the first stepped care trial to integrate mHealth tools and implement our predictive model of weight loss failure, SMART will be the most temporally and resource efficient strategy evaluated to date.
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会议论文
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资助金额:$44.42万
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Novel use of mHealth data to identify states of vulnerability and receptivity to JITAIs
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批准号:10090968
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资助金额:$21.41万
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财政年份:2018
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负责人:Inbal Billie Nahum-Shani
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依托单位:
SMART Weight Loss Management
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项目类别:
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资助金额:$67.88万
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财政年份:2016
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负责人:Inbal Billie Nahum-Shani
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依托单位:
海外基金