Emergent Social Environments As Predictors of Recovery Resident Outcomes

新兴社会环境作为居民康复结果的预测因素

• 批准号: 8814340
• 负责人: Leonard A Jason
• 金额: $ 63.23万
• 依托单位: DE PAUL UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-06-01 至 2020-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8814340
• 关键词: Abstinence; Acute; Address; Affect; Aftercare; Age; Age Factors; Alcoholics Anonymous; Attitude; Beer; Behavior; Behavioral; Beryllium; Caring; Characteristics; Cities; Client; Communities; Complex; Country; Crime; Data; Development; Drug Formulations; Drug Metabolic Detoxication; Effectiveness; Ego; Elements; Ensure; Environment; Environmental Risk Factor; Equation; Etiology; Evolution; Face; Failure; Friends; Friendships; Gender; Health; Health Care Costs; Home environment; Housing; Individual; Investigation; Lead; Length; Life; Life Style; Light; Link; Literature; Measures; Mental Health; Mentors; Modeling; Neighborhoods; Network-based; Outcome; Patients; Personal Behavior; Personality; Persons; Pharmaceutical Preparations; Population; Process; Prognostic Marker; Recovery; Relapse; Relative (related person); Research; Role; Social Behavior; Social Environment; Social Network; Social support; Structure; Substance Use Disorder; Support Groups; System; Systems Analysis; Testing; Therapeutic; Time; Treatment outcome; Trust; Walkers; Work; Writing; addiction; alcohol availability; base; behavior change; design; improved; insight; network models; programs; public health relevance; residence; response; simulation; sobriety; social; social cognitive theory; social integration; success; theories; treatment program

 DESCRIPTION (provided by applicant): The proposed research tests a dynamic systems-based theory, which explains how recovery house residents' recovery-related attitudes, behaviors, and social relationships co-evolve, and how these emergent individual characteristics and house-level social structures subsequently link to individuals' recovery endpoints. The theory adapts concepts from group and social network dynamics, placing them within a broader community mental health framework. It is operationalized and tested by measuring relationships of trust, friendship, and advice/mentoring as dynamic multiplex social networks (Snijders et al., 2012)-multiple, simultaneous interdependent relationships--that exist within each house. These relationships are assumed to co-evolve over time, affecting and affected by recovery-related attitudes and behaviors, and personal networks outside the house. By pooling dynamic relationships across houses, we will apply the Stochastic Actor-Oriented Modeling framework (Snijders et al., 2010) to estimate a set of stochastic, continuous-time difference equations. This model will then be subjected to theoretical analyses designed to suggest possible strategies for improving outcomes (e.g. maintaining residence) for this population. Our proposed study will identify mechanisms through which social environments affect health outcomes, and thereby contribute to reducing unnecessary health care costs by improving the effectiveness of the residential recovery home system in the US and also restructuring and improving other community-based recovery settings. These types of improvements could lead to better client care and treatment outcomes. Our proposed research would provide significant insight on within house structure and dynamics as predictors of an individual's likelihood of maintaining a positive recovery trajectory; it would provide information on the interactions of external recovery behaviors (e.g. AA), external ego-centered networks (scope, composition, dynamics), and within-setting social networks, and it might identify points of "failure" where the individual reaches a significant likelihood of relapse. In addition, this work should result in an initial framework for the study of network dynamics in recovery homes which should facilitate both the theoretical development and empirical investigation of the broader domain of recovery homes.

 描述（由适用提供）：拟议的研究测试基于动态的基于系统的理论，该理论解释了康复居民与恢复相关的参与者，行为和社会关系如何共同发展，以及这些新兴的个人特征和房屋级别的社会结构随后如何与个人的恢复端口联系起来。该理论适应了群体和社交网络动态的概念，将它们置于更广泛的社区心理健康框架之内。它是通过衡量动态多个社交网络的信任，友谊和指导/指导的关系来实现和测试的（Snijders等，2012） - 多个，简单的相互依存关系 - 在每个房屋中都存在。假定这些关系会随着时间的流逝而共同发展，从而影响并受到与恢复相关的参与者和行为以及众议院外的个人网络的影响。通过汇总整个房屋的动态关系，我们将应用随机参与者的建模框架（Snijders等，2010）来估计一组随机的，连续的时间差方程。这 然后，模型将经过理论分析，旨在提出改善该人群结果的可能策略（例如维持居住）。我们拟议的研究将确定社会环境影响健康结果的机制，从而通过提高美国住宅恢复家庭系统的有效性以及恢复和改善其他基于社区的恢复环境，从而有助于降低不必要的医疗保健成本。这些类型的改进可能会带来更好的客户护理和治疗结果。我们提出的研究将对房屋结构和动态内部的重要见解，作为个人维持积极恢复轨迹的可能性的预测指标。它将提供有关外部恢复行为（例如AA），外部以自我为中心的网络（范围，组成，动力学）和设定的社交网络的相互作用的信息，并且它可能会识别“失败”个人具有很大的退休金可能性。此外，这项工作应该为研究恢复家庭中的网络动态研究带来一个初步框架，这应该促进恢复房屋更广泛领域的理论发展和经验投资。