Event Title
Objective Measurement of Functional Analysis Data
Location
CSU 253/4/5
Start Date
4-4-2011 9:00 AM
End Date
4-4-2011 10:30 AM
Student's Major
Psychology
Student's College
Social and Behavioral Sciences
Mentor's Name
Carlos Panahon
Mentor's Department
Psychology
Mentor's College
Social and Behavioral Sciences
Description
A functional analysis (FA) is a procedure used to identify the trigger of a problem behavior, and the maintaining consequence/s of that behavior. Once the reinforcing consequences are identified, an intervention can be created by targeting each of those reinforcers. Within FA data, there may be more than one identifiable maintaining function. Although, at this point there is no objective criteria for determining what those primary functions are. In this study, we proposed an objective criterion of 30 percent. This means that any consequence that is associated with 30 percent or more of the targeted behaviors shall be considered one of the maintaining functions and should also be included in the intervention. We used FA studies that were published in The Journal of Applied Behavior Analysis prior to 2011 to complete this study. For each study that included a functional analysis, we collected the frequency of the problem behavior, the identified function/s included in each intervention and also the author's statement of the interventions success or failure in meeting its particular goal. We then applied our 30 percent criterion to each article's FA to decipher which articles did identify the same function/s as our criterion and which did not. We then used a one-way ANOVA to determine any statistical differences in regards to intervention success within articles that did and did not fit our criterion. Our results provide method of FA data analysis that will help create more effective interventions leading to more positive treatment outcomes.
Objective Measurement of Functional Analysis Data
CSU 253/4/5
A functional analysis (FA) is a procedure used to identify the trigger of a problem behavior, and the maintaining consequence/s of that behavior. Once the reinforcing consequences are identified, an intervention can be created by targeting each of those reinforcers. Within FA data, there may be more than one identifiable maintaining function. Although, at this point there is no objective criteria for determining what those primary functions are. In this study, we proposed an objective criterion of 30 percent. This means that any consequence that is associated with 30 percent or more of the targeted behaviors shall be considered one of the maintaining functions and should also be included in the intervention. We used FA studies that were published in The Journal of Applied Behavior Analysis prior to 2011 to complete this study. For each study that included a functional analysis, we collected the frequency of the problem behavior, the identified function/s included in each intervention and also the author's statement of the interventions success or failure in meeting its particular goal. We then applied our 30 percent criterion to each article's FA to decipher which articles did identify the same function/s as our criterion and which did not. We then used a one-way ANOVA to determine any statistical differences in regards to intervention success within articles that did and did not fit our criterion. Our results provide method of FA data analysis that will help create more effective interventions leading to more positive treatment outcomes.
Recommended Citation
Day, Jessica A. and Brianna D. Smith. "Objective Measurement of Functional Analysis Data." Undergraduate Research Symposium, Mankato, MN, April 4, 2011.
https://cornerstone.lib.mnsu.edu/urs/2011/poster-session-A/13
