Optimizing a Paraprofessional, Family Partner Navigation Model for Children
优化儿童辅助专业人员、家庭合作伙伴导航模型
基本信息
- 批准号:10210234
- 负责人:
- 金额:$ 82.44万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2018
- 资助国家:美国
- 起止时间:2018-08-01 至 2023-05-31
- 项目状态:已结题
- 来源:
- 关键词:AdoptedAgeAttention deficit hyperactivity disorderAttitudeCaringChildChildhoodClinicCollaborationsCommunitiesCommunity HealthComplexComputerized Medical RecordConsumptionDataDiseaseEffectivenessEnhancement TechnologyEthnic OriginExperimental DesignsFaceFamilyFederally Qualified Health CenterFutureHIVHealth ServicesHealth Services AccessibilityHomeHome visitationImprove AccessIndividualInformation NetworksInsuranceInterventionLanguageLow incomeMalignant NeoplasmsMeasuresMediator of activation proteinMental HealthMental Health ServicesMental disordersMethodsModelingMonitorMotivationOnline SystemsOregonOutcomeOutcome StudyPatient EducationPersonsPopulationPrimary Health CareProblem SolvingProtocols documentationRaceRandomizedResearchResourcesSchoolsSeveritiesStructureSymptomsSystemTechnologyTestingTimeTransportationautism spectrum disorderbasebehavioral healthcare coordinationcare deliverycare systemschronic care modelcostcost effectivedesigndisparity reductioneffectiveness evaluationeffectiveness testingevidence basefamily supporthealth knowledgeimplementation strategyinnovationinstrumentmeetingsmotivational enhancement therapymulti-component interventionmultiphase optimization strategynovel strategiespatient portalprimary outcomepublic health interventionresponsescreeningsocial stigmasuccesstelehealththeories
项目摘要
PROJECT SUMMARY
Two decades of evidence support the effectiveness of family navigation (FN) as a care-management approach
to reducing disparities in access to health services for disorders; despite substantial promise, widespread
dissemination of FN still faces significant challenges. FN is a complex, multi-component intervention that
generally incorporates motivational interviewing, problem-solving strategies, patient education, and care
coordination. Each of these components can be delivered through a range of strategies including in-person
meetings, telehealth, home visits, and/or web-based technologies. Our team’s research strongly supports FN’s
effectiveness as a whole; however, three questions remain: 1) what are the most effective delivery strategies
for FN; 2) which FN components are the “active ingredients;” and 3) how can FN be disseminated to a broad
population. In the current proposal, FN will be will be delivered by a Family Partner and deployed to improve
access to behavioral health services among children ages 3-12 years. Our study will be carried out at a large
federally qualified health center within a newly formed Accountable Care Organization. For this project, we
propose to optimize FN for dissemination at scale. First, using the Multiphase Optimization Strategy
(MOST), which relies on a randomized, multi-factorial design, we will simultaneously test the effectiveness of
three novel strategies for delivering FN components: (A) technology-assisted delivery of care coordination
using an innovative, web-based platform; (B) community-based; and (C) enhanced symptom tracking using
evidence-based screening instruments (compared to standard pediatric surveillance). Second, using path
analysis, we will test mediators and moderators of FN outcomes. Third, using a mixed-methods approach, we
will study factors that influence implementation. Integration of our three aims will yield a FN model that is
optimized for efficiency, effectiveness, and wider implementation. Our specific aims are: (1) To evaluate the
effectiveness of three strategies to deliver FN components. We will use a 2 x 2 x 2 factorial experimental
design to test three strategies to deliver FN components. Families (n=304) will be randomized to one of eight
conditions. We will estimate main effects of the three experimental factors and the additive effects of
combinations of factors on the study’s primary outcome – engagement in appropriate mental health services. (2)
To evaluate mechanisms of FN effectiveness and for whom it is most effective. (3) To Optimize FN for
dissemination and evaluate implementation strategies. Following Aarons’ scaling-out framework, we will
use mixed methods to explore barriers and facilitators to implementation by evaluating fidelity (to intervention
and implementation), reach, and cost. Then, working with our team of stakeholders, we will integrate these
findings with data from Aim 1 and 2 to optimize FN based on effectiveness, identified mediators and
moderators, and implementation success.
项目摘要
二十年的证据支持家庭导航(FN)作为护理管理方法的有效性
减少在获得疾病保健服务方面的差距;尽管有很大的希望,
新生力量的传播仍然面临重大挑战。FN是一种复杂的多成分干预措施,
一般包括动机访谈、解决问题的策略、病人教育和护理
协同每个组成部分都可以通过一系列战略来提供,包括亲自
会议、远程保健、家访和/或基于网络的技术。我们团队的研究强烈支持FN
然而,仍然存在三个问题:1)最有效的交付战略是什么?
2)FN的哪些成分是“活性成分”; 3)FN如何传播到广泛的
人口在当前的提案中,FN将由家庭合作伙伴交付并部署以改进
3-12岁儿童获得行为健康服务。我们的研究将在一个广泛的
在新成立的责任医疗组织内的联邦合格的健康中心。对于这个项目,我们
建议优化FN,以便大规模传播。首先,使用多阶段优化策略
(MOST),它依赖于一个随机,多因素设计,我们将同时测试的有效性,
提供FN组件的三种新策略:(A)技术辅助提供护理协调
使用创新的基于网络的平台;(B)基于社区;(C)使用
循证筛查工具(与标准儿科监测相比)。第二,使用路径
分析,我们将测试FN结果的调解人和主持人。第三,使用混合方法,我们
将研究影响实施的因素。我们三个目标的整合将产生一个FN模型,
优化了效率、效果和更广泛的实施。我们的具体目标是:(1)评估
这三项战略的有效性。我们将使用一个2x2 x2阶乘实验
设计测试三种战略,以提供FN组件。家庭(n=304)将被随机分配至8个
条件我们将估计三个实验因素的主效应和
研究的主要结果-参与适当的心理健康服务的因素组合。(二)
评价新军的有效机制,并对谁最有效。(3)要优化FN,
传播和评价执行战略。根据Aarons的横向扩展框架,我们将
使用混合方法,通过评估(对干预的)忠诚度,探索实施的障碍和促进因素
和实施)、覆盖范围和成本。然后,与我们的利益相关者团队合作,我们将整合这些
目标1和目标2的数据发现,以根据有效性、确定的介质和
主持人和实施成功。
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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EMILY FEINBERG其他文献
EMILY FEINBERG的其他文献
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{{ truncateString('EMILY FEINBERG', 18)}}的其他基金
Collaborative Care Model for Perinatal Depression Support Services -- Population-Level Equity-Centered Systems Change (COMPASS-PLUS): A Hybrid Type 2 Cluster Randomized Trial
围产期抑郁症支持服务协作护理模式——以人口水平公平为中心的系统变革 (COMPASS-PLUS):混合 2 型集群随机试验
- 批准号:
10835287 - 财政年份:2023
- 资助金额:
$ 82.44万 - 项目类别:
Improving Preschool Outcomes by Addressing Maternal Depression in Head Start
通过提前解决母亲抑郁症问题来改善学前教育成果
- 批准号:
10543380 - 财政年份:2022
- 资助金额:
$ 82.44万 - 项目类别:
Improving Preschool Outcomes by Addressing Maternal Depression in Head Start
通过提前解决母亲抑郁症问题来改善学前教育成果
- 批准号:
10083218 - 财政年份:2020
- 资助金额:
$ 82.44万 - 项目类别:
Improving Preschool Outcomes by Addressing Maternal Depression in Head Start
通过提前解决母亲抑郁症问题来改善学前教育成果
- 批准号:
9884948 - 财政年份:2020
- 资助金额:
$ 82.44万 - 项目类别:
Optimizing a Paraprofessional, Family Partner Navigation Model for Children
优化儿童辅助专业人员、家庭合作伙伴导航模型
- 批准号:
10409572 - 财政年份:2018
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Early identification and service linkage for urban children with autism
城市自闭症儿童早期识别与服务联动
- 批准号:
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- 资助金额:
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城市自闭症儿童早期识别与服务联动
- 批准号:
9305159 - 财政年份:2014
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