Three-term contingency of the day: Laundry keeps spinning

  • Antecedent: Clothes are drying in the dryer (that happens to have a window front load); each article is being tossed around in circles not quite in sync with the others.
  • Behaviour: I stand there and watch the clothes.
  • Consequence: Visual effect that is pleasing to the senses (automatic positive reinforcement).
  • Sometimes we do things because it produces a consequence that pleases us sensorially. We have many behaviours - from the subtle to most outwardly - that fit into this category. We do them repeatedly over and over again because of the pleasure it has provided us before. And we often do these without thought or analysis.


Data, data, data, data, data, data, data, data, data, data, data, data,



Four-term contingency of the day: Wasabi burn

  • Motivating operation: Just finished half a container of wasabi peas and tongue feels like it is burning
  • Discriminative stimulus: Milk carton
  • Behaviour: Pour a glass of milk and chug it
  • Consequence: Milk taste (positive reinforcement) and removal of the wasabi burn (negative reinforcement)
  • This is why I keep milk in the fridge. I should probably put the container away as that seems to signal I can eat more.

"I suppose I could use some brevity in my writing but therein lies a problem. Everyone wants and accepts the TL;DR version allowing pseudoscience to just slip right in there. Pseudoscience relies on people not taking the time to read further. Unfortunately, there can be no such thing as TL;DR when reviewing the research."

— My reply to a comment, “TL;DR” left on my post about science and scientific literacy.

Four-term contingency of the day

  • Motivating operation: A student in my class was eating a giant chocolate chip cookie and it looked really good.
  • Discriminative stimulus: cafeteria display with the same chocolate chip cookie
  • Behaviour: Pick up the cookie and pay for it
  • Consequence: Cookie tastes good!
  • When I'm back on campus and in the cafeteria I am likely to get myself another cookie because it tastes so good!

This is About Science

So now that people have settled from the brouhaha that was the #JennyAsks response on Twitter (myself included), I feel it is only fair to come out and say that my snark directed at Jenny McCarthy had nothing to do with being pro-vaccine (or the opposite).  This was about being pro-science and against alarmist pseudoscience by respecting the different levels of scientific inquiry.  

I respect that parents will do their research on vaccines and make decisions for themselves and their child.  I also respect that some parents will describe their children has having changed post-MMR vaccine.   Description of events or behaviours and its dimensions is one level of science.  

In Applied Behaviour Analysis (ABA) description is achieved by gathering background information, taking observation notes and measuring behaviours. That information tells a story but it does not lead to any conclusions beyond what was seen or heard.  In other words, someone else’s experience is not suggestive or predictive of your or others’ experiences.  What it can do is lead to a good research question and more information gathering.

The next level of science is prediction.  Over repeated observations and note taking we may start to see a pattern or relationship forming between two events. We can take a lot of the raw information we gathered and start to make comparisons. This is where correlations are made.  I don’t doubt that many parents of children with autism who also meet other parents of children with autism will begin to compare notes. Now there is a shared experiences of autism-like behaviours occurring shortly after the scheduled MMR vaccine. This certainly raises the question - does one cause the other leading to a possible experiment. However, this correlation does not answer it. We must not jump to all-or-nothing conclusions based on correlation, and if we act on this information, we must always hold a certain amount of skepticism that our hypotheses could be wrong.

In ABA we also look for patterns in behaviour and environmental variables. We analyze the timing of events and try to predict when a behaviour is likely to occur through the process of a functional behaviour assessment. We make data-informed decision to change one of these variables then see if the pattern changes. This process however is not error-proof as cause and effect cannot be determined at this level. This is why on-going data collection is insisted upon by behaviour analysts because we need a mechanism to monitor whether or not our hypotheses were correct. If they were incorrect, we stop the intervention, re-assess and try something else.  

Finally, we aim for greater scientific understanding through the process of experimental control.  This means that a functional relationship i.e., “cause and effect” has repeatedly been demonstrated in experiments where one event was purposely added or removed to monitor its effect on another event. This level of control is achieved through randomized control groups (in the case of group design) or single-subject research design involving reversals, alternating treatments and/or multiple baselines. To date, I have yet to find a sound research study that controlled for the MMR vaccine and results showed a higher incidence of autism because of it*.       

In ABA, we almost exclusively use single-subject research design (e.g., reversal, multielement, multiple baseline) to act as the controlling mechanism demonstrating that the introduction of a behaviour analytic variable reliably and repeatedly resulted in behaviour change. That behaviour change must be demonstrated in multiple studies across different people, settings and behaviour-types. We use a multielement design to conduct functional analyses and determine the likely function of a behaviour. If we have a case whose personal and behavioural components match those in the research then we can implement a similar intervention with confidence. This is routinely referred to as using evidenced-based practice.  

My practice of ABA relies heavily on all three levels of science.  I am a scientist-practitioner which means I consume, participate in and disseminate science. When I see false unsubstantiated claims, poor research design, personal anecdotes as evidence and people jumping on fad therapies because it has been packaged and marketed as a soda:

I will raise questions.  

I will call out for more evidence.

I will show people what evidence is out there. 

I will advise people to proceed with caution.

And I just might suggest that someone develop their scientific literacy skills.


Cooper, J.O., Heron, T.E., & Heward, W.L.  (2007).  Applied Behavior Analysis (2nd ed.).  Upper Saddle River, NJ: Pearson Education Inc.  

Hayes, S.C., Barlow, D.H. & Nelson-Gray, R.O.  (1999).  The scientist-practitioner: Research and accountability in the age of managed care (2nd ed.).  Needham Heights, MA: Allyn & Bacon

Normand, M.P. (2008).  Science, skepticism, and applied behavior analysis.  Behavior Analysis in Practice, 1(2), 42-49.

Smith, T. (2013).  What is evidence-based behavior analysis?  The Behavior Analyst, 36(1), 7-33.

* but you are welcome to share with me or steer me in the direction of any controlled research designs that show a MMR-autism link. 

Source:  Anna Lissa Bantigue
Happy birthday to one of the most radical dudes in science and behaviour analysis

Source:  Anna Lissa Bantigue

Happy birthday to one of the most radical dudes in science and behaviour analysis