Item Response Theory for Sequential Data in Drug Therapy

描述(由申请人提供)：阐明与青少年药物滥用的开始、过程和停止有关的家庭过程类型的研究对于正在进行的针对这一人群的理论和干预发展至关重要。大多数已知的与青少年吸毒有关的家庭过程是基于家庭评估的自我报告方法。然而，最近，对家庭研究的观察方法的兴趣和进步有了相当大的增长。家庭研究人员越来越多地使用观察性评估策略来捕捉基于理论的微妙和动态的家庭沟通过程，而这些过程并不是用自我报告方法很好地衡量的。不幸的是，用于观测编码数据的主流分析方法在直接模拟作为观测通信序列的基础的基于理论的过程的能力方面是有限的。因此，为理论和干预发展提供的直接信息很少。鉴于需要改进家庭互动观测编码数据的数据分析策略，拟议的项目旨在开发项目反应理论(IRT)的新应用，该应用可应用于来自观察性家庭评估的微编码数据。IRT非常适合于提供关于表征潜在特征或过程的特定行为模式的细粒度信息。与目前基于经典测试理论的序列数据分析方法相比，IRT分析方法可以更充分地利用观测数据的丰富性来对观察到的交流序列背后的过程进行理论驱动的研究。虽然IRT在历史上一直被用于传统测验项目的心理测量分析，但IRT软件的新发展极大地扩展了其在心理和行为研究中的潜在应用范围。目前的研究将开发在非常灵活的广义线性混合建模(GLMM)框架内实现的IRT的应用。GLMM公式使IRT能够适应观测数据的独特偶然性，包括家庭之间观测到的通信序列的数量和类型的随机变化。拟议项目的具体目标是：(A)建立能够模拟观察到的家庭沟通序列的IRT模型；(B)使用关于治疗药物滥用的青少年家庭中的沟通模式的观察数据，在一个非线性混合建模框架内执行IRT模型；(C)使用IRT模型参数来制定描述不同程度“家庭亲密度”的观察到的沟通序列的概况；以及(D)使用IRT模型参数，根据与青少年药物滥用水平有关的观察到的沟通模式，开发“家庭凝聚力”的概况。

DESCRIPTION (provided by applicant): Research explicating the types of family processes connected to the onset, course, and cessation of drug abuse among adolescents is critical for ongoing theory and intervention development for this population. The majority of what is known regarding family processes related to adolescent drug abuse is based on self-report methods of family assessment. Recently, however, interest and advances in observational methods of family research have surged considerably. Family researchers are increasingly utilizing observational assessment strategies to capture subtle and dynamic theory-based family communication processes which are not well measured using self-report methods. Unfortunately, prevailing analytic approaches for observationally coded data are limited in the capacity to directly model theory-based processes underlying observed sequences of communication. Consequently, little direct information is provided to inform theory and intervention development. In recognition of the need for advances in data analytic strategies for observationally coded data on family interaction, the proposed project aims to develop a novel application of item response theory (IRT) which can be applied to microcoded data from observational family assessments. IRT is well suited for providing fine-grained information about specific patterns of behavior characterizing underlying latent traits or processes. Compared to current methods of sequential data analysis, all of which are grounded in classical test theory, an IRT analytic approach can more fully capitalize on the richness of observational data for conducting theory-driven research on processes underlying observed sequences of communication. Although IRT has historically been utilized for psychometric analyses of traditional test items, new developments in IRT software have greatly expanded its range of potential applications in psychological and behavioral research. The current study will develop an application of IRT implemented within the very flexible generalized linear mixed modeling (GLMM) framework. The GLMM formulation enables adaptations of IRT to fit the unique contingencies of observational data, including random variation in the number and types of observed communication sequences between families. The specific aims of the proposed project are (a) formulate an IRT model capable of modeling observed sequences of family communication, (b) execute the IRT model within a nonlinear mixed modeling framework using observational data on patterns of communication in families of adolescents in treatment for substance abuse, (c) use the IRT model parameters to develop descriptive profiles of observed sequences of communication characterizing different levels of "family cohesion", and (d) use the IRT model parameters to develop profiles of "family cohesion" based on observed patterns of communication that are associated with levels of adolescent substance abuse.