Join the Library

Weekly Episode List

Nov 28, 2021

Hey there behaviorists!

Welcome to another week of the Behaviorist Book Club Podcast! This week, we will be covering the Journal of Applied Behavior Analysisissue 54, number 4, pages 1514 to 1552.

A relatively short three articles, these papers focus on a diverse and fun group of topics! In a somewhat random manor, we cover hospital rounding practices, trial based functional analysis visual inspection methods, and final machine learning!


This article is written by Dr. Nicole Gravina and colleagues, and is focused on physician and nursing rounding procedures in a hospital setting. As someone who has recently been in the hospital with a pregnant wife, there is nothing more frustrating than waiting hours and hours for rounds that will never come, only to have your concerns brushed aside by doctors who are too busy to worry about the little things. At first glance, this article may not seem applicable to the everyday clinician, but at its core, these authors discuss changing adult behavior using feedback, checklists, and progress graphing. All of these components can be identified by the performance diagnostic checklist and should be applied in the typical clinical setting. 

Citation + DOI:

Gravina, N., Sleiman, A., Southwick, F. S., Matey, N., Harlan, E., Lukose, K., Hack, G., & Radhakrishnan, N. S. (2021). Increasing adherence to a standardized rounding procedure in two hospital in-patient units. Journal of Applied Behavior Analysis, 54(4), 1514-1525.


This next article is over another fun and novel concept. The application of a standard visual analysis criteria for the trial based functional analysis. Quickly becoming my favorite clinically practical assessment, the trial based functional analysis excels in practicality, except for one aspect. The standard research suggests a fixed number of trials, and then examining the data in a summary format rather than continued visual analysis. This article attempts to solve that problem by promote a form of ongoing visual analysis and structured set of rules for identifying behavioral functions. 

Citation + DOI:

Standish, C. M., Bailey, K. M., Lambert, J. M., Copeland, B. A., Banerjee, I., & Lamers, M. E. (2021). Formative applications of ongoing visual inspection for trial-based functional analysis: A proof of concept. Journal of Applied Behavior Analysis, 54(4) 1526-1540.


To end out the week, we have something truly out of left field. The application of machine learning to behavior analytic single case design graphs. These authors focus on the teeter totter between type 1 and type 2 errors. The less type 1 errors, the higher the probability that rater is susceptible to type 2 errors. This presents a particularly interesting challenge for our field, as we stray away from type 1 errors and accept more type 2 errors. This error bias is inherent in our visual analysis methods and our expectation of clear and strong demonstrations of effect size. Due to conflicting research related to the reliability of visual analysis, these authors attempt to demonstrate a potential solution.

Citation + DOI

Lanovaz, M. J., & Hranchuk, K. (2021). Machine learning to analyze single-case graphs: A comparison to visual inspection. Journal of Applied Behavior Analysis, 54(4), 1541-1552.

Sign up below to get instant access to Clarifying Trauma Informed Care!

This 5 hour, 3 CEU course is all about helping you understand the complexities of trauma informed care so you can implement evidenced based ABA through a compassionate lense.

Signing up will also subscribe you to the email list. Unsubscribe at anytime! We will never sell your information, for any reason.