Martens Brian K, Digennaro Florence D, Reed Derek D, Szczech Frances M, Rosenthal Blair D
Department of Psychology, Syracuse University, 430 Huntington Hall, Syracuse, New York 13244, USA.
J Appl Behav Anal. 2008 Spring;41(1):69-81. doi: 10.1901/jaba.2008.41-69.
Descriptive assessment methods have been used in applied settings to identify consequences for problem behavior, thereby aiding in the design of effective treatment programs. Consensus has not been reached, however, regarding the types of data or analytic strategies that are most useful for describing behavior-consequence relations. One promising approach involves the analysis of conditional probabilities from sequential recordings of behavior and events that follow its occurrence. In this paper we review several strategies for identifying contingent relations from conditional probabilities, and propose an alternative strategy known as a contingency space analysis (CSA). Step-by-step procedures for conducting and interpreting a CSA using sample data are presented, followed by discussion of the potential use of a CSA for conducting descriptive assessments, informing intervention design, and evaluating changes in reinforcement contingencies following treatment.
描述性评估方法已应用于实际场景中，以确定问题行为的后果，从而有助于设计有效的治疗方案。然而，对于描述行为-后果关系最有用的数据类型或分析策略，尚未达成共识。一种有前景的方法涉及对行为及其发生后事件的顺序记录中的条件概率进行分析。在本文中，我们回顾了几种从条件概率中识别相依关系的策略，并提出了一种称为相依空间分析（CSA）的替代策略。本文介绍了使用样本数据进行和解释CSA的分步程序，随后讨论了CSA在进行描述性评估、为干预设计提供信息以及评估治疗后强化相依关系变化方面的潜在用途。
