Impact of Social Network Structure on Stroke Recovery
社交网络结构对中风康复的影响
基本信息
- 批准号:9899275
- 负责人:
- 金额:$ 15.67万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-12-01 至 2020-12-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAdultAgeAreaAutomobile DrivingBehaviorBehavior TherapyBiometryCaregiver BurdenCaregiversClinical InvestigatorClinical ResearchCommunitiesDataDevelopmentDiseaseEducational CurriculumElementsEmotionalFailureFamilyFriendshipsFutureGoalsHome environmentHumanHypertensionImpairmentIndividualInfluentialsInstitutionInterventionIntervention StudiesInterviewIschemic StrokeKnowledgeLeadMapsMeasuresMediatingMediationMediator of activation proteinMental DepressionMentored Patient-Oriented Research Career Development AwardMentorsMethodological StudiesMethodologyMethodsModelingMorbidity - disease rateNatural HistoryNatureNetwork-basedNeurologicNeurologistOutcomeOutcomes ResearchPathway AnalysisPatientsPersonsPhysical FunctionPlayPredictive ValueProspective cohort studyPublic HealthRecoveryRegression AnalysisRehabilitation therapyResearchResearch PersonnelScienceScientistSeveritiesSocial EnvironmentSocial NetworkSocial isolationSocial supportStatistical Data InterpretationStrokeStructureSurveysTestingTimeTrainingUnited States National Institutes of HealthUniversitiesWashingtonWorkaddictionbasecareercohortdensitydesignexecutive functionfunctional outcomeshealth care service utilizationimprovedinnovationmembermultidisciplinarynovelpatient orientedpost strokeprimary outcomeprofessorprogramspublic health relevancerecruitsecondary outcomesocialsocial factorssocial structurestroke outcomestroke recoverystroke survivortheories
项目摘要
DESCRIPTION (provided by applicant): Dr. Amar Dhand is a neurologist and young investigator who pursues patient-oriented clinical research on social networks structure and ischemic stroke recovery. A K23 award will allow Dr. Dhand to fulfill his long-term career goal of becoming an independent clinical investigator through training in three areas: advanced social network analysis, biostatistics, and intervention research. Dr. Dhand has recruited a multidisciplinary team of mentors and designed a detailed curriculum to accomplish this goal. This training will take place at Washington University in St. Louis, an institution with a long trak record of training clinician scientists. His mentors include Dr. Jin-Moo Lee, his primary advisor, who is a neurologist with expertise in translational stroke research, Dr. Doug Luke, a public health professor with expertise in social network analysis, and Dr. Catherine Lang, a rehabilitation investigator with expertise in longitudinal stroke outcomes research. His project begins with the understanding that social mechanisms in stroke recovery are influential and understudied. Social isolation is associated with poor recovery, while increased social support and community engagement is associated with improved recovery. Despite this knowledge, the mechanisms by which social factors influence recovery is unknown, and this has led to multiple social support interventions that have failed to improve stroke recovery or reduce caregiver burden. It is unknown whether this failure is due to an inappropriate social unit target (e.g., caregiver versus family versus friendship group), timing of intervention (e.g., immediately after stroke or delayed), or duration and potency of the program. To address this gap, he proposes a prospective cohort study of 200 stroke survivors using a novel methodology-social network analysis-to quantitatively map the social structure around a patient and its predictive value on recovery. Social network analysis is based on the theory that human behavior is most fully understood by analysis of the structure of social relations around an individual. These data may, subsequently, inform network interventions that have been efficacious in other diseases, such as addiction disorders and hypertension. We hypothesize that stroke survivors' personal social networks will become smaller and denser especially in those with more severe strokes, and certain network variables at stroke onset will independently predict functional outcomes through specific mediators. This hypothesis will be tested by the following specific aims: Aim 1 will determine changes in social network structure after stroke of varying severity; Aim 2 will assess the predictive value of social network variables at stroke onset on stroke outcomes; Aim 3 will determine the factors that mediate the relationship between social networks and stroke outcomes. This study is significant because it will show the natural history of network structures in stroke recovery, their relation to stroke outcomes, and the mediators between networks and recovery. This project is innovative because it introduces a novel analytical framework that challenges current social support models and improves the theoretical underpinnings of social support interventions.
项目成果
期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Social network structure and composition in former NFL football players.
- DOI:10.1038/s41598-020-80091-w
- 发表时间:2021-02-01
- 期刊:
- 影响因子:4.6
- 作者:Dhand A;McCafferty L;Grashow R;Corbin IM;Cohan S;Whittington AJ;Connor A;Baggish A;Weisskopf M;Zafonte R;Pascual-Leone A;Barabási AL
- 通讯作者:Barabási AL
Caregivers and Families of Critically Ill Patients.
危重病人的护理人员和家属。
- DOI:10.1056/nejmc1608225
- 发表时间:2016
- 期刊:
- 影响因子:0
- 作者:Dhand,Amar;Feske,StevenK
- 通讯作者:Feske,StevenK
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Amar Dhand其他文献
Amar Dhand的其他文献
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{{ truncateString('Amar Dhand', 18)}}的其他基金
Social networks and risk of delayed arrival to the hospital during stroke
社交网络和中风期间延迟到达医院的风险
- 批准号:
10611852 - 财政年份:2022
- 资助金额:
$ 15.67万 - 项目类别:
Social networks and risk of delayed arrival to the hospital during stroke
社交网络和中风期间延迟到达医院的风险
- 批准号:
10374360 - 财政年份:2022
- 资助金额:
$ 15.67万 - 项目类别:
SocialBit: Establishing the accuracy of a wearable sensor to detect social interactions after stroke
SocialBit:建立可穿戴传感器的准确性以检测中风后的社交互动
- 批准号:
10396124 - 财政年份:2020
- 资助金额:
$ 15.67万 - 项目类别:
SocialBit: Establishing the accuracy of a wearable sensor to detect social interactions after stroke
SocialBit:建立可穿戴传感器的准确性以检测中风后的社交互动
- 批准号:
9973762 - 财政年份:2020
- 资助金额:
$ 15.67万 - 项目类别:
SocialBit: Establishing the accuracy of a wearable sensor to detect social interactions after stroke
SocialBit:建立可穿戴传感器的准确性以检测中风后的社交互动
- 批准号:
10250357 - 财政年份:2020
- 资助金额:
$ 15.67万 - 项目类别:
Impact of Social Network Structure on Stroke Recovery
社交网络结构对中风康复的影响
- 批准号:
9150302 - 财政年份:2015
- 资助金额:
$ 15.67万 - 项目类别:
Impact of Social Network Structure on Stroke Recovery
社交网络结构对中风康复的影响
- 批准号:
9319474 - 财政年份:2015
- 资助金额:
$ 15.67万 - 项目类别:
Impact of Social Network Structure on Stroke Recovery
社交网络结构对中风康复的影响
- 批准号:
9033380 - 财政年份:2015
- 资助金额:
$ 15.67万 - 项目类别:
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