Harmonizing Multiple Data Sources And Psychological Autopsy To Characterize Suicides Among Opioid-Related Deaths
Harmonizing Multiple Data Sources And Psychological Autopsy To Characterize Suicides Among Opioid-Related Deaths
批准号:
10426651
负责人:
Paul Sasha Nestadt
金额:
$19.87万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-06-01 至 2027-05-31
关键词:
AccidentsAutopsyCause of DeathCessation of lifeCharacteristicsClassificationClinicalClinical DataCollaborationsCoronerCountryDataData CollectionData LinkagesData SetDetectionDetermination of DeathDevelopmentDrug usageElectronic Health RecordEpidemiologistEpidemiologyFaceFamilyFellowshipFundingFutureGenerationsGeographyGoalsGrantIndividualInterventionInterviewInvestigationLinkLogistic RegressionsManuscriptsMarylandMeasuresMedical ExaminersMentored Patient-Oriented Research Career Development AwardMentorsMentorshipMethodsModelingNational Institute of Drug AbuseOpioidOverdosePathway interactionsPhysiciansPoliciesPositioning AttributePrecipitating FactorsPredisposing FactorPreventionProbabilityProtocols documentationPsychiatric DiagnosisPsychiatric epidemiologyPsychiatristPsychological InterviewPublic HealthPublicationsRecording of previous eventsResearchResearch MethodologyResearch PersonnelResearch TrainingResourcesRiskRisk FactorsSamplingSelf-Injurious BehaviorSocietiesStrategic PlanningSubgroupSuicideSuicide preventionSystemTimeToxicologyTrainingTraining ProgramsTranslatingValidationWorkWritingaddictioncareercase-baseddata warehousedemographicsdesigndiverse dataendophenotypeepidemiologic dataepidemiology studyexperienceimprovedinformantinnovationlarge datasetsmental statemortalitymultiple data sourcesnovelopioid epidemicopioid mortalityopioid overdoseopioid useopioid useroverdose deathoverdose riskpeerpredictive testpreventive interventionprogramspsychologicscaffoldskill acquisitionskillssocialstatisticssuicidalsuicidal morbiditysuicide ratetheoriestherapy development
中文摘要
项目摘要/摘要
这个以患者为导向的导师研究职业发展奖旨在为申请者提供
有必要的高级培训,以建立一个独立的流行病学研究方案
服药过量死亡和自杀。提出了一个全面的培训计划,结合正规课程,
指导和实践培训经验,旨在发展数据联系/协调方面的专门知识,
潜伏班模型(LCA)、定性心理尸检(PA)和混合方法研究。
随着过量死亡人数的增加,他们继续被视为阿片类药物使用变化造成的事故。
然而,流行病学研究表明,这些死亡中的许多人很可能是自杀,这一点很重要
适当针对干预措施的影响。我们将衡量这种错误分类的严重程度
死亡方式(MOD;意向性),并确定可能引导法医进行更多
对自杀死者进行准确分类。我们假设大约三分之一与阿片类药物有关的死亡
不确定的方式是真正的自杀,LCA可以区分出死者的亚群具有更大的
有自杀意图的可能性。我们将在之前未确定的意图遗赠者的子集中使用PA进行测试
经验派生类的预测能力,并表征过量用药的不同途径。
我们建议使用人口统计学方法分析2006-2019年马里兰州所有阿片类药物过量死亡(n=13,861)。
社会和临床数据,我们将从马里兰自杀数据仓库链接到其中的死亡数据
首席验尸官办公室(OCME)。首先,取这个样本的三分之一,我们将比较案例
从意外(n=756)和未确定的意图(n=3,748)三方面分类为自杀(n=115)
多项Logistic回归。接下来,被发现是最显著的比较器的变量将被用于
其余病例为OCME MOD分类不可知(n=9286)。将经验派生的类与
在指定OCME时,我们将评估每一类指定自杀和事故的比例。最后,
从每个潜在类别中,我们将选出40名被OCME指定为“待定方式”的遗属
将由多个附属面谈PA进一步检查,以证实这些潜在的类别。通过泛化
根据LCA和PA的研究结果,可以做出更准确的自杀率估计。调查结果将影响未来
国防部的指定以及潜在的预防干预措施如何针对意外过量和自杀。
培训和指导计划将使候选人处于有利地位,成为一名独立的医生-
流行病学家,能够利用定性和定量方法对大型关联数据进行验证
描述相互关联的自杀和吸毒过量危机的集合。他的长期职业目标包括阐明
自伤死亡的机制,使用混合方法产生和研究新的
关于自杀途径的假设,以及将这些发现转化为自杀预防的能力。
英文摘要
Project Summary/ Abstract
This Mentored Patient-Oriented Research Career Development Award is designed to provide the applicant
with the advanced training necessary to establish an independent program of research in the epidemiology of
overdose mortality and suicide. A comprehensive training program is proposed, combining formal coursework,
mentoring, and hands-on training experiences designed to develop expertise in data linkage/ harmonization,
latent class modeling (LCA), qualitative psychological autopsy (PA) and mixed methods research.
As overdose deaths increase, they continue to be treated as accidents resulting from changes in opioid use.
However, epidemiologic research suggests that many of these deaths are likely suicides, This has important
implications for appropriately targeting interventions. We will measure the magnitude of this misclassification of
manner of death (MOD; intentionality) and identify factors that may guide medical examiners to more
accurately classify suicide decedents. We hypothesize that approximately one third of opioid related deaths of
undetermined manner are truly suicides, and that LCA can distinguish subgroups of decedents with greater
likelihood of suicidal intent. We will use PA in a subset of previously undetermined intent decedents to test
predictive ability of empirically-derived classes and characterize the diverse paths to overdose.
We propose to analyze all opioid overdose deaths in Maryland from 2006-2019 (n=13,861) using demographic,
social, and clinical data which we will link from the Maryland Suicide Data Warehouse to mortality data from
the Office of the Chief Medical Examiner (OCME). First, taking one third of this sample, we will compare cases
classified as suicidal (n=115) from accidental (n=756) and undetermined intent (n=3,748) using a three-way
multinomial logistic regression. Next, variables found to be most salient comparators will be used in LCA of the
remaining cases, agnostic of OCME MOD class (n=9,286). Comparing the empirically derived classes with the
OCME designations, we will assess the proportion of designated suicides and accidents in each class. Finally,
from each of these latent classes, we will select 40 decedents designated by OCME as ‘undetermined manner’
to be further examined by multiple collateral interview PA, to corroborate these latent classes. By generalizing
findings from LCA and PA, more accurate suicide rate estimates can be made. Findings would impact future
MOD designation and potentially, how prevention interventions target accidental overdoses and suicides.
Training and mentorship plans will leave the candidate well positioned to become an independent physician-
epidemiologist, able to utilize both qualitative and quantitative methods for the validation of large linked data
sets describing the interrelated suicide and overdose crises. His long term career goals include the elucidation
of mechanisms of self injury mortality, the use of mixed methods for the generation and investigation of novel
hypotheses regarding pathways to suicide, and the ability to translate these findings into suicide prevention.
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Harmonizing Multiple Data Sources And Psychological Autopsy To Characterize Suicides Among Opioid-Related Deaths
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批准号:10623253
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项目类别:
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资助金额:$19.74万
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财政年份:2022
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负责人:Paul Sasha Nestadt
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依托单位:
海外基金