Item Response Theory for Sequential Data in Drug Therapy

药物治疗中顺序数据的项目反应理论

• 批准号: 7500673
• 负责人: TIMOTHY J OZECHOWSKI
• 金额: $ 6.66万
• 依托单位: OREGON RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-28 至 2010-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7500673
• 关键词: Adolescent; Alcohol abuse; Behavior; Behavioral Research; Cereals; Characteristics; Clinical Services; Code; Communication; Computer software; Data; Data Analyses; Development; Drug Formulations; Drug abuse; Family; Family Process; Family Research; Link; Measures; Methods; Modeling; Numbers; Patient Self-Report; Pattern; Personal Satisfaction; Pharmacotherapy; Population; Process; Psychometrics; Range; Research; Research Personnel; Statistical Models; Substance abuse problem; Testing; Time; Variant; adolescent drug abuse; adolescent substance abuse; base; cohesion; interest; novel; psychologic; response; theories; therapy development; trait

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.

描述（由申请人提供）：研究阐明与青少年滥用药物滥用有关的家庭过程类型对于该人群的持续理论和干预发展至关重要。关于与青少年药物滥用有关的家庭过程的大多数知识是基于家庭评估的自我报告方法。然而，最近，家庭研究的观察方法的兴趣和进步已经大大飙升。家庭研究人员越来越多地利用观察性评估策略来捕获基于自我报告方法的微妙而动态的基于理论的家庭交流过程。不幸的是，观察编码数据的普遍分析方法的直接模型基于理论的过程的能力有限。因此，很少提供直接信息来为理论和干预发展提供信息。为了认识到对家庭互动的观察数据进行数据分析策略的进步的需求，该项目旨在开发项目响应理论（IRT）的新颖应用，可以将其应用于观察性家庭评估中的微编码数据。 IRT非常适合提供有关表征潜在的潜在特征或过程的特定行为模式的细粒度信息。与当前的顺序数据分析方法相比，所有这些方法都基于经典的测试理论，IRT分析方法可以更充分地利用观察数据的丰富性，用于对观察到的沟通序列进行基础的过程进行理论驱动的研究。尽管历史上一直将IRT用于对传统测试项目的心理测量分析，但IRT软件的新发展大大扩展了其在心理和行为研究中的潜在应用范围。当前的研究将开发出在非常灵活的广义线性混合建模（GLMM）框架内实施的IRT的应用。 GLMM公式使IRT的适应能够符合观察数据的独特意外情况，包括随机变化的家族之间观察到的通信序列的数量和类型。 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) u​​se the基于观察到的沟通模式，与青少年滥用水平相关的沟通模式发展了“家庭凝聚力”的概况。