Systems Approach to Modeling of Drug Use Recovery
药物使用回收建模的系统方法
基本信息
- 批准号:8416409
- 负责人:
- 金额:$ 24.13万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2012
- 资助国家:美国
- 起止时间:2012-02-15 至 2015-03-31
- 项目状态:已结题
- 来源:
- 关键词:AccountingAddressAffectAlcoholsAttentionBiological ModelsCase ManagementCharacteristicsChronicChronic DiseaseCollaborationsCommunicable DiseasesCommunitiesComplexContinuity of Patient CareCrack CocaineData SetDatabasesDevelopmentDiseaseDrug usageEnvironmentEnvironmental PolicyGoalsHealth systemHeroinHeroin DependenceIllicit DrugsImprisonmentIndividualInfluentialsInpatientsInterventionKnowledgeLaw EnforcementLeadLinkLiteratureMaintenance TherapyMarketingMethadoneMethamphetamineModalityModelingMonitorOutcomeOutpatientsPatientsPatternPeer ReviewPharmaceutical PreparationsPilot ProjectsPoliciesPreventionProcessPublicationsRecoveryRelapseResearchResearch PersonnelResistanceServicesSimulateSocial NetworkStagingStructureSystemTestingTreatment EffectivenessTypologyWorkaddictionbasecontextual factorsdrug marketexperiencemethadone maintenancepreventresearch studysuccesstreatment strategy
项目摘要
DESCRIPTION (provided by applicant): This pilot study will build an agent-based model that will describe heroin use and recovery trajectories in the context of complex interconnections with current treatment practices, recovery-oriented services, and the illicit drug market. Treatment of heroin addiction is associated with a chronic cycle of relapse, treatment reentry, and recovery, often lasting for decades. The most commonly used treatment for heroin addiction is methadone therapy, which is pharmacologically efficient, but due to a complex interaction of organizational, community, and policy factors that affect relapse to heroin use, it is not always optimally effective and is thus unable to prevent relapse in many addicts. To date, a number of studies have collected information about heroin addiction recovery trajectories; however no model has yet been developed to integrate influential factors into one model, considering them as part of a system. The proposed effort represents the first systems modeling approach to address the topic of heroin recovery, including influences from contextual factors. Accordingly, the development of the proposed model simultaneously takes into account characteristics of heroin addiction treatment strategies (e.g., residential vs. outpatient modality) and the user's contextual environment (e.g., social networks, illicit drug markets) to more aptly assess the processes that promote or, conversely, interfere with recovery. Model parameters will be obtained from well studied datasets on heroin use trajectories identified by leading experts from UCLA and Chestnut Health Systems, as well as from other relevant studies. The resulting model will be used to address questions about the optimal combination and staging of treatment approaches and to explore whether some combinations could lead to qualitative (e.g., cessation) rather than simply quantitative (e.g., delayed relapse) changes in recovery cycle. Specifically, we aim to (1) Develop an agent-based model of heroin use and recovery process that would describe the main systems components influencing the success of recovery, (2) Through simulated experiments, evaluate the success of specific complex strategies aimed to increase treatment effectiveness, and (3) Evaluate the feasibility of approaches that show the most promise, address potential resistance to policy strategies, and evaluate generalizability of the model in regard to other drug treatments.
描述(由申请人提供):这项试点研究将建立一个基于主体的模型,该模型将在与当前治疗实践、以康复为导向的服务和非法毒品市场的复杂相互联系的背景下描述海洛因使用和康复轨迹。海洛因成瘾的治疗与复发、再入治疗和恢复的慢性循环有关,通常持续数十年。海洛因成瘾最常用的治疗方法是美沙酮疗法,它在药理学上是有效的,但由于影响海洛因使用复发的组织、社区和政策因素的复杂相互作用,它并不总是最有效的,因此无法防止许多成瘾者复发。迄今为止,许多研究收集了有关海洛因成瘾恢复轨迹的信息;然而,目前还没有一个模型能够将影响因素整合到一个模型中,将它们视为系统的一部分。提出的努力代表了第一个系统建模方法来解决海洛因恢复的主题,包括来自背景因素的影响。因此,拟议模型的发展同时考虑了海洛因成瘾治疗策略的特征(例如,住院与门诊模式)和使用者的背景环境(例如,社交网络,非法药物市场),以更恰当地评估促进或相反地干扰康复的过程。模型参数将从加州大学洛杉矶分校和栗子卫生系统的主要专家确定的海洛因使用轨迹的经过充分研究的数据集以及其他相关研究中获得。由此产生的模型将用于解决有关治疗方法的最佳组合和分期的问题,并探索某些组合是否会导致恢复周期中的定性(例如,停止)而不是简单的定量(例如,延迟复发)变化。具体来说,我们的目标是(1)开发一个基于主体的海洛因使用和恢复过程模型,该模型将描述影响恢复成功的主要系统组件;(2)通过模拟实验,评估旨在提高治疗效果的特定复杂策略的成功;(3)评估最有希望的方法的可行性,解决政策策略的潜在阻力。并评估该模型在其他药物治疗方面的通用性。
项目成果
期刊论文数量(0)
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GEORGIY BOBASHEV其他文献
GEORGIY BOBASHEV的其他文献
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{{ truncateString('GEORGIY BOBASHEV', 18)}}的其他基金
Supplement for Cloud Computing: Opioid Policy Models
云计算的补充:阿片类药物政策模型
- 批准号:
10826888 - 财政年份:2020
- 资助金额:
$ 24.13万 - 项目类别:
Systems Approach to Modeling of Drug Use Recovery
药物使用回收建模的系统方法
- 批准号:
8224973 - 财政年份:2012
- 资助金额:
$ 24.13万 - 项目类别:
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