The Effects of Physical Exercise on Stereotypic Behaviors in Autism: Small-n Meta-Analyses

2019 ◽  
Vol 35 (1) ◽  
pp. 26-35 ◽  
Author(s):  
Christopher W. Tarr ◽  
Ashlea Rineer-Hershey ◽  
Karen Larwin
Keyword(s):  
Physical Exercise ◽  
Effect Size ◽  
Effect Sizes ◽  
Single Subject ◽  
Single Subject Design ◽  
Current Investigation ◽  
Design Studies ◽  
Aggregate Score ◽  
Subject Design ◽  
Meta Analyses

Physical exercise has shown the potential to reduce stereotypic behaviors. The current investigation conducted three meta-analyses on the effects of physical exercise on stereotypic behaviors in individuals with autism. Study 1 produced four aggregate score studies ( n = 54) that included nine effect sizes ranging from d = –.85 to .31. Study 1 yielded an overall effect size of d = –.463. Study 2 produced six single subject design studies ( n = 13) that included 48 effect sizes ranging from d = −1 to .5156. Study 2 yielded an overall effect size of d = –.456. Study 3 combined all 10 studies ( n = 67) that included effect sizes ranging from d = −1 to .5156. The n = 10 articles combined produced an overall effect size of d = –.456. The effect sizes demonstrate that physical exercise does have the potential to decrease stereotypic behaviors in individuals with autism.

Investigation of Regression-Based Effect Size Methods Developed in Single-Subject Studies

2021 ◽  
pp. 014544552110540
Author(s):  
Nihal Sen
Keyword(s):  
Effect Size ◽  
Experimental Studies ◽  
Single Subject ◽  
Single Subject Design ◽  
Data Set ◽  
Design Studies ◽  
Sample Data ◽  
The Difference ◽  
D Values ◽  
Effect Size Calculation

The purpose of this study is to provide a brief introduction to effect size calculation in single-subject design studies, including a description of nonparametric and regression-based effect sizes. We then focus the rest of the tutorial on common regression-based methods used to calculate effect size in single-subject experimental studies. We start by first describing the difference between five regression-based methods (Gorsuch, White et al., Center et al., Allison and Gorman, Huitema and McKean). This is followed by an example using the five regression-based effect size methods and a demonstration how these methods can be applied using a sample data set. In this way, the question of how the values obtained from different effect size methods differ was answered. The specific regression models used in these five regression-based methods and how these models can be obtained from the SPSS program were shown. R2 values obtained from these five methods were converted to Cohen’s d value and compared in this study. The d values obtained from the same data set were estimated as 0.003, 0.357, 2.180, 3.470, and 2.108 for the Allison and Gorman, Gorsuch, White et al., Center et al., as well as for Huitema and McKean methods, respectively. A brief description of selected statistical programs available to conduct regression-based methods was given.

SSDOnt: An Ontology for Representing Single-Subject Design Studies

2018 ◽  
Vol 57 (01/02) ◽  
pp. 55-61
Author(s):  
Jesus Bermúdez ◽  
Arantza Illarramendi ◽  
Idoia Berges
Keyword(s):  
Description Logic ◽  
Formal Model ◽  
Reference Model ◽  
Single Subject ◽  
Single Subject Design ◽  
Design Studies ◽  
Single Subject Research ◽  
Ontology Language ◽  
Subject Design ◽  
Research Studies

Summary Background: Single-Subject Design is used in several areas such as education and biomedicine. However, no suited formal vocabulary exists for annotating the detailed configuration and the results of this type of research studies with the appropriate granularity for looking for information about them. Therefore, the search for those study designs relies heavily on a syntactical search on the abstract, keywords or full text of the publications about the study, which entails some limitations. Objective: To present SSDOnt, a specific purpose ontology for describing and annotating single-subject design studies, so that complex questions can be asked about them afterwards. Methods: The ontology was developed following the NeOn methodology. Once the requirements of the ontology were defined, a formal model was described in a Description Logic and later implemented in the ontology language OWL 2 DL. Results: We show how the ontology provides a reference model with a suitable terminology for the annotation and searching of single-subject design studies and their main components, such as the phases, the intervention types, the outcomes and the results. Some mappings with terms of related ontologies have been established. We show as proof-of-concept that classes in the ontology can be easily extended to annotate more precise information about specific interventions and outcomes such as those related to autism. Moreover, we provide examples of some types of queries that can be posed to the ontology. Conclusions: SSDOnt has achieved the purpose of covering the descriptions of the domain of single-subject research studies.

Improving Treatment Plan Implementation in Schools: A Meta-analysis of Single Subject Design Studies

2013 ◽  
Vol 23 (1) ◽  
pp. 168-191 ◽  
Author(s):  
George H. Noell ◽  
Kristin A. Gansle ◽  
Joanna Lomas Mevers ◽  
R. Maria Knox ◽  
Joslyn Cynkus Mintz ◽  
...  
Keyword(s):  
Treatment Plan ◽  
Meta Analysis ◽  
Single Subject ◽  
Single Subject Design ◽  
Design Studies ◽  
Plan Implementation ◽  
Subject Design
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