Episode 234 - Idiosyncratic Functional Analyses

ABA Inside Track

Robert Parry-Cruwys

Behavioralscience, Education, Appliedbehavioranalysis, Autism, Social Sciences, Aba, Science, Specialeducation

4.6 • 623 Ratings

🗓️ 15 March 2023

⏱️ 83 minutes

🔗️ Recording | iTunes | RSS

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Summary

Did you ever have one of those weird funtional analyses? You know, the one where all the problem behavior happens in the control condition or responding remains strangely variable during the escape condition even though the client’s teacher swears he tantrums every single time she presents any work? This week we seek answers as to what to do when your FA results look like the world’s most volatile stock prices by exploring idiosyncratic variables and how to find them. Plus, could the IISCA be the most idiosyncratic FA process of all? And one of Rob’s favorite articles, discussed here becuase we didn’t know where else to put it.

This episode is available for 1.0 LEARNING CEU.

Articles discussed this episode:

Coffey, A.L., Shawler, L.A., Jessel, J., Nye, M.L., Bain, T.A., & Dorsey, M.F. (2020). Interview-informed synthesized contingency analysis (IISCA): Novel interpretations and future directions. Behavior Analysis in Practice, 13, 217-225. doi: 10.1007/s40617-019-00348-3

Querim, A.C., Iwata, B.A., Roscoe, E.M., Schlichenmeyer, K.J., Ortega, J.V., & Hurl, K.E. (2013). Functional analysis screening for problem behavior maintained by automatic reinforcement. Journal of Applied Behavior Analysis, 46, 47-60. doi: 10.1002/jaba.26

Schlichenmeyer, K.J., Roscoe, E.M., Rooker, G.W., Wheeler, E.E., & Dube, W.V. (2013). Idiosyncratic variables that affect functional analysis outcomes: A review (2001-2010). doi: 10.1002/jaba.12

Jesel, J., Hanley, G.P., & Ghaemmaghami, M. (2016). Interview-informed synthesized contingency analyses: Thirty replications and reanalysis. Journal of Applied Behavior Analysis, 49, 576-595. doi: 10.1002/jaba.316

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Transcript

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0:00.0	Hey, everybody. Welcome to ABA Inside Track the podcast that's like reading in your car, but safer. I'm your host, Robert Perry Cruz, and with me, as always, are my fabulous co-hosts.
0:23.9	Hey, Rob, it's me, Diana.
0:25.8	And it's me, fabulous third person, Jackie.
0:29.6	That's usually how we describe you, Jackie.
0:31.3	It's like, oh, here's my third person.
0:33.5	It's Jackie McDonald.
0:35.5	Well, welcome, everybody.
0:37.0	We're not going to beat around the bush because we are recording early today, because we have a million places to be.
0:42.4	That doesn't mean we're going to give this episode short shrift.
0:45.0	You know, this episode about behavior analysis and behavior analytic research in which we will discuss relevant research related to a given topic.
0:51.5	But it does mean we need to be a bit more succinct than usual,
0:55.8	which I might say is idiosyncratic to our podcast, where we like to sort of just meander
1:01.5	and see where the topics take us. How are we feeling about these topics? Today it's going to be
1:06.9	right to the point. So that's a little strange for us, which probably makes sense, because today we're going to be talking about the strangeness that can come up when you're
1:14.2	conducting a functional analysis in the form of looking for idiosyncratic variables in modifying
1:20.7	a standard functional analysis, which is, hey, that's our topic. Look at that. What a segue.
1:26.7	Who knew I could get there?
1:28.2	So we're going to be talking about research related to the idea that standard functional analysis,
1:33.4	i.e. our kind of Awada at all, 8294 analysis with our four major conditions, doesn't always result
1:40.5	in differentiation so that we're able to determine the function of a problem behavior and
1:44.9	therefore develop a function-based treatment. And sometimes you have to mess around a bit.
1:49.8	And I think this is where understanding the functions of behavior and really doing the active
	...

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