TY - JOUR
T1 - Functional analysis patterns of automatic reinforcement
T2 - A review and component analysis of treatment effects
AU - Virues-Ortega, Javier
AU - Clayton, Kylee
AU - Pérez-Bustamante, Agustín
AU - Gaerlan, Belinda Faye S.
AU - Fahmie, Tara A.
N1 - Funding Information:
Part of the data reported in Study 2 was obtained during the thesis research of Ms. Belinda F. S. Gaerlan conducted in partial fulfillment of the requirements of the degree of Master's in Science at The University of Auckland (New Zealand). ABA España, an affiliated chapter of the Association for Behavior Analysis International, supported this study through a research contract with The University of Auckland (project no. CON02739). Support was also obtained from a Canadian Institutes of Health Research Synthesis Grant (KRS‐132038) awarded to the first author.
Publisher Copyright:
© 2022 The Authors. Journal of Applied Behavior Analysis published by Wiley Periodicals LLC on behalf of Society for the Experimental Analysis of Behavior (SEAB).
PY - 2022/3/1
Y1 - 2022/3/1
N2 - Functional analysis (FA) conditions include different antecedent or consequent events that may disrupt responding. Thus, varying patterns of FA differentiation may predict treatment outcomes of problem behavior maintained by automatic reinforcement. These patterns could be used to inform the development of individualized interventions. An approach to classifying these patterns is to categorize FA outcomes as attention condition lowest, demand condition lowest, and play condition lowest, according to the condition in which problem behavior is most disrupted. In Study 1, we applied this criterion to 120 datasets finding that 60% could be classified using this method, whereas 89% of datasets showed a disruption of 50% or higher. In Study 2, we conducted a treatment component analyses for 3 individuals whose FAs each exhibited one of the 3 distinct patterns. The results indicated that specific elements of the FA conditions could reduce problem behavior. The predictive utility of these disruption patterns is discussed.
AB - Functional analysis (FA) conditions include different antecedent or consequent events that may disrupt responding. Thus, varying patterns of FA differentiation may predict treatment outcomes of problem behavior maintained by automatic reinforcement. These patterns could be used to inform the development of individualized interventions. An approach to classifying these patterns is to categorize FA outcomes as attention condition lowest, demand condition lowest, and play condition lowest, according to the condition in which problem behavior is most disrupted. In Study 1, we applied this criterion to 120 datasets finding that 60% could be classified using this method, whereas 89% of datasets showed a disruption of 50% or higher. In Study 2, we conducted a treatment component analyses for 3 individuals whose FAs each exhibited one of the 3 distinct patterns. The results indicated that specific elements of the FA conditions could reduce problem behavior. The predictive utility of these disruption patterns is discussed.
KW - automatic reinforcement
KW - component analyses
KW - functional analysis
KW - systematic review
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U2 - 10.1002/jaba.900
DO - 10.1002/jaba.900
M3 - Article
C2 - 35067932
AN - SCOPUS:85123467131
SN - 0021-8855
VL - 55
SP - 481
EP - 512
JO - Journal of Applied Behavior Analysis
JF - Journal of Applied Behavior Analysis
IS - 2
ER -