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（由申请人提供）：拟议的研究测试了基于动态系统的理论，该理论解释了康复之家居民与康复相关的态度、行为和社会关系如何共同演变，以及这些新兴的个人特征和房屋层面的社会关系如何共同演变该理论采用了群体和社交网络动态的概念，将其置于更广泛的社区心理健康框架内，通过衡量信任、友谊和建议/指导的动态多重关系来进行操作和测试。社交网络（Snijders 等人，2012）——每个房子内存在多种、同时相互依赖的关系——这些关系被认为随着时间的推移而共同演变，影响着与康复相关的态度和行为，以及房子外的个人网络。通过汇集房屋之间的动态关系，我们将应用面向参与者的随机建模框架（Snijders 等，2010）来估计一组随机、连续时间差分方程。 然后对模型进行理论分析，旨在提出改善该人群的结果（例如维持居住）的可能策略。我们提出的研究将确定社会环境影响健康结果的机制，从而通过改善来减少不必要的医疗保健成本。美国住宅康复之家系统的有效性以及重组和改善其他基于社区的康复环境可以带来更好的客户护理和治疗结果，我们提出的研究将为内部结构的改进和动态提供重要的见解。作为个人保持积极康复可能性的预测指标轨迹；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、动态）和内部社交网络的相互作用的信息，并且它可能会识别个人的“失败”点。此外，这项工作应该为康复之家的网络动态研究提供一个初步框架，这将有助于更广泛的康复之家领域的理论发展和实证研究。