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Technical, Relational, & Conditional Process Models of MI Efficacy: Meta-Analysis

技术性、关系性、

基本信息

批准号：
9020920
负责人：
Molly Magill
金额：
$ 19.15万
依托单位：
BROWN UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-03-01 至 2018-02-28
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9020920
关键词：
Accounting Address Affect Alcohol consumption Area Behavior Behavior Therapy Behavioral Client Clinical Code Data Data Correlations Data Set Databases Effectiveness Empathy Evidence based intervention Future Guidelines Health Individual Intervention Knowledge Lead Measurement Measures Mediation Meta-Analysis Methods Modeling Motivation National Institute on Alcohol Abuse and Alcoholism Outcome Outcome Study Outcomes Research Pathway interactions Process Psychometrics Public Health Publishing Readiness Research Resistance Review Literature Rosa Sampling Sampling Studies Sea Series Testing Theoretical model Therapeutic Time Treatment Efficacy Work addiction alcohol abuse therapy alcohol use disorder base behavior change evidence base follow-up interest motivational enhancement therapy motivational processes skills theories treatment responders

项目摘要

DESCRIPTION (provided by applicant): This R21 application responds to PAR-14-053. Research examining the theoretical models proposed by treatment developers is a valuable approach to enhancing the impact of existing evidence-based behavioral addictions treatments (Magill & Longabuagh, 2013). The intent is to empirically-derive the causal processes that are responsible for treatment benefit, and the result is identification of: 1) key therapeutic behavior, 2) skill proficiency thresholds, 3) key proximal client outcomes, and 4) the conditions under which these principles are most operative (i.e., conditional process models). Motivational interviewing (MI) is arguably the most important behavioral treatment upon which to conduct this kind of research. Recently, Magill and colleagues (Magill et al., 2013; MS under revise/resubmission) conducted a meta-analysis of studies testing specific pathways of the Technical Model of MI Efficacy as proposed by Miller and Rose (2009). While this research contributes to an emerging picture of how MI affects behavior change, an additional, more comprehensive meta-analytic study is needed to test the full theoretical framework, to identify conclusively which causal pathways have support, under what conditions, and which, if any, require major theoretical revision. The proposed project will address this aim not only with a larger sample of primary studies, but also with a database comprised of raw, rather than published and available, data. The Project will first compile a comprehensive dataset of bivariate correlations for fulfillment of all scientific aims. Next, it will test the Technical, Relational, nd a series of conditional process models (e.g., by client and treatment implementation factors) of MI efficacy at an aggregate, meta-analytic level. Finally, this large-scale, primary study dataset wil enable an exploratory, psychometric assessment of observationally-rated, within-session summary scores as well as individual therapist and client behavior codes. The breadth of findings from this study will inform the following three key areas of the MI evidence base: a) clinical guidelines for MI implementation, b) knowledge on MI causal theory, and c) empirically-derived measurement guidelines for future MI process research.

描述（由申请人提供）：本R21申请响应PAR-14-053。对治疗开发者提出的理论模型进行研究是一种有价值的方法，可以增强现有循证行为成瘾治疗的影响（马吉尔& Longabuagh，2013）。其目的是间接推导出导致治疗获益的因果过程，结果是识别：1）关键治疗行为，2）技能熟练度阈值，3）关键近端客户结局，以及4）这些原则最有效的条件（即，条件过程模型）。动机访谈（MI）可以说是进行这类研究的最重要的行为治疗。最近，马吉尔及其同事（马吉尔等人，二〇一三年; MS（修订/重新提交）对米勒和Rose（2009）提出的MI疗效技术模型的特定途径进行了荟萃分析。虽然这项研究有助于MI如何影响行为改变的新图景，但还需要一项额外的、更全面的元分析研究来测试完整的理论框架，以最终确定哪些因果途径有支持，在什么条件下，以及哪些（如果有的话）需要重大的理论修正。拟议的项目将不仅通过更大的初步研究样本，而且通过由原始数据而不是已公布和可获得的数据组成的数据库来实现这一目标。该项目将首先编制一个全面的双变量相关性数据集，以实现所有科学目标。接下来，它将测试技术、关系和一系列条件流程模型（例如，由客户和治疗实施因素）的MI疗效的汇总，荟萃分析水平。最后，这个大规模的主要研究数据集将能够对观察评级的会话内汇总评分以及个体治疗师和客户行为代码进行探索性的心理测量评估。本研究结果的广度将为MI证据库的以下三个关键领域提供信息：a）MI实施的临床指南，B）MI因果理论知识，以及c）未来MI过程研究的经验性测量指南。