1. The Influence of Function, Topography, and Setting on Noncontingent Reinforcement Effect Sizes for Reduction in Problem Behavior: A Meta-analysis of Single-Case Experimental Design Data
- Author
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Ritter, William A., Barnard-Brak, Lucy, Richman, David M., and Grubb, Laura M.
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Intervention (Psychology) -- Methods ,Behavior problems -- Care and treatment ,Reinforcement (Psychology) -- Health aspects ,Education - Abstract
Richman et al. (J Appl Behav Anal 48:131-152, 2015 (See CR45)) completed a meta-analytic analysis of single-case experimental design data on noncontingent reinforcement (NCR) for the treatment of problem behavior exhibited by individuals with developmental disabilities. Results showed that (1) NCR produced very large effect sizes for reduction in problem behavior, (2) NCR implemented with the functional reinforcer resulted in a slightly larger effect size compared to NCR using nonfunctional reinforcers, and (3) schedule thinning for the delivery of reinforcers typically produced temporary and modest increases in levels of problem behavior. The purpose of the current study was to conduct follow-up analyses to determine whether treatment implementation setting, topography, or the function of problem behavior influenced the treatment effect size for problem behavior exhibited by individuals with developmental disabilities. Follow-up analyses showed that NCR effect sizes were very similar across inpatient and outpatient settings and across aggression and property destruction versus self-injurious behaviors. Results showed that NCR effect size for treatment of problem behavior maintained by a form of social reinforcement was slightly greater than problem behavior maintained by automatic reinforcement. Results are discussed in terms of applying NCR in school settings as an initial treatment for problem behaviors that can interfere with academic, adaptive, and vocational skill acquisition for students with developmental disabilities., Author(s): William A. Ritter [sup.1] , Lucy Barnard-Brak [sup.1] , David M. Richman [sup.1] , Laura M. Grubb [sup.1] Author Affiliations: (Aff1) 0000 0001 2186 7496, grid.264784.b, Texas Tech University, [...]
- Published
- 2018
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