This is the third of the three-part introduction to thisseason of the Behavioral Data Science Podcast. During this season, Jake and I discuss the intersection of behavior science and data science as they relate to client outcomes in Applied Behavior Analysis service delivery.

In this episode, we discuss the importance and challenges of contextualizing outcome measures based on the unique clinical presentation of each client.

This is the second of the three-part introduction to this season of the Behavioral Data Science Podcast. During this season, Jake and I discuss the intersection of behavior science and data science as they relate to client outcomes in Applied Behavior Analysis service delivery.

In this episode, we discuss the history of outcome measurement in Applied Behavior Analysis, broadly, and the role the data science can play moving forward.

This is the first of the three-part introduction to this season of the Behavioral Data Science Podcast. During this season, Jake and I discuss the intersection of behavior science and data science as they relate to client outcomes in Applied Behavior Analysis service delivery.

In this episode, we discuss the history of quality measurement in healthcare, broadly.

In this episode, Jake and David discuss articles from the ⁠recent issue of the Journal of Applied Behavior Analysis. They also discuss how the underlying technologies and concepts might be extended via data science techniques.

In this episode, Jake and David discuss articles from the recent issue of Artificial Intelligence in Medicine. They also discuss how the underlying technologies and concepts might be translated to behavioral health services.

OpenAI and Anthropic have recently released products where users can connect health-related data and receive healthcare advice and guidance.

Jake and David discuss these products, the potential benefits to ease of access to personalized healthcare-related information, and the potential harms from inaccurate (or dangerous) recommendations and data privacy concerns.

At the end of the episode, they each answer the question we all have to ask ourselves: "Will you be hooking your data up to these systems?"

Realistically, you can't build any model of behavior-environment relations if you can't (a) find the data you need and (b) integrate those data into a usable database.

In this episode of The Behavioral Data Science Podcast, we discuss the many considerations and decisions one needs to make. And, we do so by discussing a seven-year-long project Jake has been working on to build a usable database of all open-source articles published within five behavior-analytic journals.

Crucial to any behavioral data science project is identifying either (a) what behavior you want to analyze and how you'll get the data; or (b) what data you can get and what behaviors those data allow you to analyze well.

In this episode, we chat about these decisions in the context of the literally wild behavior of birds at backyard feeders.

For the interested, here's a link to the backyard ecology dashboard referenced during the episode: https://david-j-cox.github.io/backyard-ecology/