Episode 307 - (LISTENER CHOICE) Tutorial: Token Economy

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. I'm a host, taken over and staying in Perry Cruz. You're a co-chief resident. I am never going to take over to assistant to the regional man in church too much responsibility. My name is Jack Jack Jackie McDonald. I kind of want if I was ever going to be a wrestler, that's how they want I'd want them to. Jack Jack Jackie. Jack Jack Jackie McDonald. I wouldn't change my last name. What would be your song as you as you walk down towards the ring? You know what I know this exactly, but I can't remember the song, but it is from the early late 80's, early 90's and it was the song that I used to sing when I would swim right before my big meat. It would be right now. Hey. It's yo tomorrow. It's been healing. It's been healing. Right now. Come on. It's everything. That would, that's what it would be still or it would be the song Beautiful Girls. Beautiful Girls all over the world. I don't know. I don't know. That's going to amp the crowd up. That would be my sexual lock-in. You got to have both. You want to hype up your crowd, like kid rock songs or something. All right, fine, but this isn't a podcast about wrestling at all. This is a podcast about behavioral analysis. I was like, is it a podcast about wrestling? No, it's a podcast about behavioral analysis and behavioral analytic research for every week. We pick a topic and discuss it at length and some relevant research articles too. And this is actually the unofficial second part of our winter listener choice. So our winter listener choice every season, we open up a poll for our patrons on patreon.com/abiainsidetrack and give them a list of article options or topic options. And one of our winners back in the winter was a how-to and it was how-to token economies and how-to procedural integrity. It's a procedural integrity. It's a wrong season. I can't remember. Material integrity. Or fidelity. And since procedural integrity/fidelity was enough to do its own episode, we said let's split this up into two. So here we are back again for our spring listener choice and do how-to token economy. And then we'll do another poll in the summer. But right now, we're going to finish up this how-to series, which we really enjoyed doing because it focuses on topics and articles that really allow you to sort of just give me the summary. So if you've used token economies before or you just want to get a little bit more information about them, this is sort of like this starting point. So you can listen to this episode, learn all you want to know, and then Diana will share at the end pairings where we've talked about token economies in more detail. This also might be a fun episode to share too. Maybe your trainees or if you have someone in your life who wants to learn about token economies, this might be a good episode to point them to. But we'll also have some articles that they could read as well. But sometimes people want to hear the audible version, you know, that's us. So we're going to be talking all about token economies, the how-to's of them. All right, Diana, what articles will we be discussing today? Sure. So we have three articles to inform our discussion today and they include practical components for getting the most from a token economy by Ackerman, Samudra, and all day. And that was published in Teaching Exceptional Children 2020. Also our meat article for today, token economies, evidence-based recommendations for practitioners by Deli Espinoza and Hackenberg. That was in, looks like behavioral interventions, yes, behavioral interventions, 2024, right before the glow up. And finally, the token economy, a decade later by Cazden, that was in Java 1982. That's old. That's old. Yeah. So someone will say a decade later, it's actually 40 years ago. (laughs) Dave. Yeah. Yes. All right, so. 40-year-old take on a 50-year-old article. There you go. So token economies, we've all used them, we all love them. But I think they are one of those systems that some folks don't know. The history of token economies, some folks think they've fallen out of fashion or they've become sort of enmeshed with very basic classroom management, definitely more B-mod than behavior analysis. However, there's still plenty of space for them to be used and a function, I think for them in a lot of settings. So hopefully, when we are done, you will have either a newfound appreciation or have rekindled your romance with token economies maybe. Just imagine the token economy book, it's got Fabio on the cover and he's a pirate. And then a token economy, sticker board with SpongeBob tokens, they're still cool, everyone loves them. And that. Fabio tokens, probably. Fabio is not going to have a romantic relationship with the token board with his own tokens on them, Diana. That's weird. I got confused in your metaphor, so. It's not a metaphor. I'll back off. It's a beautiful image. (laughs) That's what I have created. Okay. All right, let's start off talking a little bit about the cast-in, the token. Can we, can I just talk about the Ackerman one? If you would like to. First. Only because I found this one late to the game, but this is a great article that we're not going to review in depth today, but if you, like Rob said, if you're looking for stocking stuff or for that special someone that wants to know more about token economies, but maybe doesn't know much yet, this is an excellent article, an excellent place to start. So maybe if you have RBTs in your life who you want to give an introduction to token economies, perhaps you are working closely with some non-behavior analysts that you're collaborating with, like classroom teachers or special education teachers, these are both great articles that do not go into the detailed level of analysis that, like, the Delhi Espinoza article is going to in the future. So this is just a great one. It says it summarizes many of the same points that we're going to make coming up, so I'm not going to review it in that way, but go and look it up if you are looking for one that is really like a nice, consumable tutorial type article. There's got little narratives in there too. Yeah. It's got narratives, it's got diagrams, it's got checklists, it's got pictures, it's got it all. I have a couple articles that I just sort of throw into a Google Drive so that whenever I have to type token economies, I'm working with maybe a new teacher or administrator and they're talking about token economies or we're discussing it. I just type it right into Google Drive and I'm like, here's the article and I can give it to folks and I'm like, this is so readable. Yes. It is four pages long. This will explain this very, very well and then we can get into how to do it. But especially for teachers who are like, I want to try that. Just show me how. I think this is a great, great example. Yeah. All right. Okay, now you can talk about that as a background. But again, I don't think it would be something if you've used basic token economies before. It's not going to tell you anything brand new. It's just sort of a nice summary. What cast it? So why this old, old article, everyone asked me right before we started recording and I'll certainly did. And I'll tell you why, it's because I think the token economy is one of those systems or technologies that has been around for a very, very long time and many behavior analysts, especially folks who are newer to the field, don't quite have that context of how long it has been here and how many of the issues facing behavior analysts back in the 70s and the 80s are still a little bit of an issue with token economies today. So I thought let's see what people were saying those 40 years ago in terms of some challenges. And then let's look at what we know about token economies 40 years on and reflect on whether there are still areas for future endeavors related to token economy usage. So for folks who don't know, the token economy was developed by Ion and Asrin back in like the mid to late 60s. It was originally created for hospitals, for programs where there were clients who had kind of chronic psychiatric conditions going on, so this is sort of pre kind of the rise of neuroleptics to treat a lot of those conditions, a lot of the mental or a lot of the psychiatric drugs that had come out. And this was used very well in those settings that then extended into other places like schools or prison populations. But most people think token economies are for like the kid in the back of the room who doesn't want to do his spelling paper. But again, token economies originally developed in hospital settings for a variety of what we'd consider kind of mental health needs back then. In 1972, Kazden and co author Bootson looked at the state of the token economies. That was their original article sort of looking at how token economies had come so far in a short amount of time, but there were still a lot of big issues that needed to be overcome. I'm just going to kind of list off some of the big issues. Okay, I just want to say that Kazden and Bootson sounds like a great country duo. No. Really, it definitely does. Country music duo. Move over, Hollin notes. We're not only with them. Hollin notes are not a country duo. No, they're not, but it still stands. Move over. Exactly. Brooks and Dunn. Yeah, Brooks and Dunn. That's what you're thinking of, I think. Kazden and Bootson and Brooks and Dunn this summer at the token economy. The country. The western pavilion, so some of the issues brought up by that country duo were enhancing the effects that there's some percentage of participants in a lot of the research around token economies and some of the research is like. 18% just did not have a good response to token economies. What's that because token economies just inherently don't work for everybody? Was it a failure of many organizations to what we're going to talk about? Take a behavior analytic principle, including the individualization of token economies and turn it into behavior modification where the clinician in charge is like, "Everyone's getting tokens for these five things because they're all I personally care about rather than skills that were important to the individual." Could be, issues around staff training. Again, this is always fun to read old articles, and here people describe BST, but not describe it as BST because I'm not sure exactly when that term got coined. When I'm reading this article, but the idea of you can train some people, but how can you train the large number of staff that might need to run effective token economies in large scales? Resistance to the program from clients. And I think this is one that we still see a lot of of the idea of token economies being behavior modification rather than behavior analytic, meaning people don't like being told what they have to do in order to earn privileges. A lot of that time because things that used to be freely available privileges became token-only-earning privileges, which I also would not like. So again, how can we avoid getting into that situation? Are there long-term effects of token economies? Now, we know with many of the treatment plans that are put in place, we don't see generalization. That's a huge problem in our research, token economies, also being one. Once you're not in the economy, why the heck would you continue engaging in some of those same behaviors that used to have value? Because they don't when you're not in the economy anymore. So how do you ensure maintenance and generalization? And those were sort of the big issues in 1972. But in 1982, 10 years later, the article goes over a lot of improvements that went through in terms of answering some of these questions. So they talked a lot about integrity of treatment, which Daily Espinoza and Hackenberg are going to talk about as well. So the idea of making meaningful contingencies, training staff, using, modeling, and feedback, and including the interests of the clients, rather than just arbitrarily assigning tokens for non-adaptive behaviors and providing rewards that are not of any meaning to them. Administration issues sort of had become a new big issue. If leadership don't like token economies, how are you supposed to run a token economy? And this is still going to be something that we'll have to talk about because if a classroom teacher doesn't want to use a token economy, you can't tell them, well, you should for your classroom management system. Or similarly, if your organization doesn't want to use a wide spread system like a token economy for say maybe like social skill development, you're not going to use that. So how do you get people interested in that? Also, how do you find money for all the things you need in a token economy? Because you can't just have the tokens, those are a little cheaper. You need the backup reinforcers as well. There's also a question about the dissemination of token economies. Now, back in 1982, there were some questions raised about our token economy's appropriate technology. Because again, you can only use them in certain contexts. And there was a real big pushback against the idea of behavior modification. Why are we making people live in these fake bubble economies for the purposes of changing behavior that other people don't like? And that is a very, you know, accurate statement of inappropriate use of the token economy. So how do we make sure that we're disseminating that it is a meaningful behavior change procedure? But it can't just be used as a blanket procedure. So given all of those challenges, we saw some nice improvements. We understand that token economies need individualization. We understand that token economies need to be trained to be used appropriately. We understand we need to include all stakeholders in the creation of token economies. But how do we make sure we're doing all of that and hit some of those new big issues? Are we there 40 years later? Well, let's go to the future 24 and see where we're at in Delhi, Esmenosa and Hackenberg. Amazingly thorough review of the token economy. I love this article. This is a really good article. Yeah, yeah. Jackie and I are tag teaming this one because it is long. It is a long article. And it's also like so complete that I don't know what else needs to be. Publish two parts as well. Yes, it's published into two parts. And I can say that I actually learn things about token economies while reading them. I actually want to be honest here. Truth serum time. Okay. I don't like token economies. And I think I don't like them because they are always run wrong. Poorly implemented. But when I'm reading this article, I'm like, "Oh!" I could totally get on board with token economies in the way that they discuss it. Yeah, I think that they have a time and a place. And very often, we are not seeing them implemented. Tought well and implemented well. And then faded out when they can be. Or thinned. It's the correct term, thinned. So there's a lot of problematic aspects procedurally related to token economies. And that is exactly why they wrote this article. So I'm going to start us off. I'm going to review part one. And then Jackie's going to review part two. I can't even wait. I know. Just as a taster, part one is called building the economy. And then part two is called sustaining the economy. So I will talk about part one. And then just to kind of get things kicked off here. Daily Espinoza and Hackenberg said to summarize, "Token economies have been around for a really long time." As noted in Rob's 50-year-old article. And we have a lot of evidence that they can be very effective. However, it's also possible that most people don't really know how to use them correctly. It does sort of feel like token economies became the Kleenex of behavior management systems. I don't know. I'm just going to use this thing. And I'll call it token economy because that's the thing we all have heard of, right? Little stickers and little prizes. I think it's more of a put a bird on it situation, right? Or a bandaid on it. Yeah. Remember? Put a bird on it? No. Really? No. There's a twist. I don't think Jackie ever actually got that reference. She just saw a slapping. And then it's so good with her mirror neurons. That actually probably is true. Oh no, and I forgot the name of that show. What's the name of that show, Rob? Portland, yeah. Portland, yeah. I watched that. Okay. Well, way back in the day, Jackie, we would talk about DRO as a put a bird on it. Oh, I never got it. Program because in Portland, yeah, should I just explain the joke to make it less funny? Yeah, please do. You should be going. Yeah. They had a store and they had all this merchandise in this store they couldn't sell. And so they were like put a bird on it. And so they would put like a little silhouette of a bird and make it look hipster. And then they like sold out of all the materials in the store. I remember now. Okay. Yeah. So it's like, oh, you don't know what to do. Put a bird on it. So DRO, you don't know what to do. Put a DRO on it. Yeah. You don't know what to do. Put a token economy on it, right? Same ideas. Because neither of neither DRO nor token economy requires you to understand the function of behavior. You're just slapping on additional reinforcers and hoping that that produces a behavior change. Much like you might increase your sales when you slap a bird on to some product. Yeah. So that takes us all the way back to like episode two or three, I think. I do much for one now. I think I understand. I mean, it's probably been like 10 years. So it's okay. I understand. What was my point? But anyway, that's all the time we have for this episode. Rob. The token economy. You actually summarize your article briefly, doesn't mean that the rest of us don't now get to pontificate. The token economy is used in that way. We don't know what to do. We put a bird on it. Perfect. Thank you. Okay. So in this article, they're like, let's set the record straight. Let's make sure everyone actually knows what a token economy is, how it operates, and how if you want to use one, you should properly implement your token economy. So that was the idea here, and they come with receipts. This is two incredible researchers in this area, and you can totally tell that from this article. It's extremely well written. And I also learned a lot. Despite having talked about this topic, this is the third go round. In fact, that we've talked about tokens. Yeah. Like I said, it's a very good, if you already know about it, you're still going to learn something new and sort of tighten up, which you already knew. And if you don't know anything about it, great. Here's an article you can read this one. Yeah, great shape. You can wet your whistle with the acumen, and then you can like, that's like your appetizer article, and then you can really just cut into the steak that is this article right here. Okay. So what do you need to know before you get started with your token economy? There are actually three different schedules that are in play when we're talking about token economy. The first one is the token production schedule, which has to do with how and when tokens are earned, meaning what is the response required to produce the token. The second one is the exchange production schedule. This has to do with how and when the exchange periods are available. Or you could turn that as how many tokens are needed to start the exchange period. And the number three is the token exchange schedule. This has to do with how many tokens produce backup reinforcers, and also how they produce backup reinforcers, which we will get into later. So each of these three pieces, the token production, the exchange production, and the token exchange can all be manipulated independently. I wasn't thinking about that ever. - I never thought about it before that way. - Exactly. And that's why you can have so many variations on token schedules, and that's why there's so much different research to look through, and this article tries to bring it all together. But there are still times when they're like, actually, this has never really been evaluated, so we can't say with certainty what's the best way to go here. When you put these three schedules together in a series, right, this creates a complex chain schedule, and then just to quote straight for them as I don't screw it up, in which two or more schedule components are arranged successively, one after the next. Each component signaled by a distinctive stimulus and ending with reinforcement. So each of those tokens is intended to function as a conditioned reinforcer. You fill up the board. That last one is the kickoff queue, that now you can trade that in and access the backup reinforcers on whatever schedule that set up for. So that's how we have initial chain that is signaled when it ends, and when the next one becomes available, which is the trade-in component here. How do you get them, when do you use them, and what do you get? Yes. Very good summary. Okay. So part number one, as promised, is about building the token economy. So it's not sufficient, right, in most situations, to just say, hmm, let's use the token economy. Here you go. It's got five tokens in a board, and you just put them on in the trade-in. For some people, perhaps that is sufficient, but for a lot of folks who might not have the verbal rule following capabilities to follow a statement like that, you're going to end up putting something in place. It doesn't really have meaning for them. Token's don't function as reinforcers, and they're overall responding, i.e., their skill acquisition responses are going to suffer for this. So what we really should do is make sure that the way in which we're putting the token economy in place is done systematically and slowly so that the learner can understand what's happening here, and that we've put all of the requisite learning components into that big chain, so that they have an idea of what's happening, versus just more things that they're being asked to do with all of this token nonsense. Okay. So building the economy, I think, has seven different pieces that we're going to go over. I'm going to try to make them quick and tell you what the takeaway is from each of them. Okay. So number one in this list, which actually they have them lettered. So this is part A is the basic architecture, decisions have to be made first and foremost about how you're going to set up your tokens, your token board, and your backup shop. This is before any training takes place. They call the backup shop a reinforcer tray, and it's intended in their mind that you bring over the reinforcers when it's time to trade in, and so you can see all the choices. So that you can pick from them at that point in time. This could be done on like a trolley card, or it could be pictures of the reinforcers if they're big things like going out to the playground or something like that, but everything should be presented in the array at the time of choosing when the backup reinforcer is available. You also have to make decisions on the tokens. They recommend the tokens are simple and arbitrary rather than interest-based, and we will talk about that again in the future. The other decision is whether you're going to have the final token that signals the trade end period beginning look different than the others and put a pin in that because we'll come back to that as well. Okay. Part B is establishing the consumption response. So consumption response is when you are going to pick from the array, right? I love that. Yes. So the consuming actually? Yeah, exactly. So you can start here without ever introducing the tokens. You're just teaching that when that reinforcer tray comes out that something's going to be selected from it and enjoyed what would be on yours right now, if right at this exact moment. I don't know, like things that I would want to go do, maybe, is that what you mean? I have a book that I'm in the middle of, so I would kind of like to get back to that. And then I have a new crochet project that I would like to get started on, so I probably just pick between those two. What about you, Rob? Activity-based? It doesn't have to be activity-based. It's whatever you want. Kind of hunger now, so I want something a little sweet and something a little salty. Oh, no, no, no, no. It would just be Cadbury Mini Eggs, if you only need one choice in your backup tray. Right. It would be Cadbury Mini Eggs, one one, and then Cadbury Mini Eggs. So the problem with your token economy is going to be like the Mick Ribb, is it's only available when the season comes around that you purchase the eggs? Okay. The cost goes up and fall, comes down and spring. Okay. So here are the steps in the consumption response. The table is empty, we teach the learner an orientation response, so that could be looking at the instructor, something to indicate that they're like attending. It doesn't necessarily have to be eye contact, although they did review a really interesting article by, I know it's Fisk, but I want to make sure I get everybody's name, right? Silva and Fisk. Silva and Fisk. They compared orienting with eye contact versus no orientation response, and they saw really pretty big differences in skill acquisition, so just to note that it would be an interesting article I think for us to maybe circle back to at some point in the future. So some orienting response, the reinforcement trace presented, the learner looks at the tray, the teacher says take it, they pick an item, the tray is removed, they consume the item, however they are going to consume it. And then the tray comes back, the teacher says put it away, meaning like whatever the thing goes back on the tray, and then the tray is removed. So that's the consumption response, and there's no token involved, it's just learning how to select an item basically, okay? So you can start with that, just with the orientation, you can move on to adding in simple directives to that, and then vary them, and maybe move it all the way up to five, just for the consumption. Okay, part C is establishing the exchange response. So here, the exchange response is the terminal link stimulus for the chain schedule that we already discussed. They talk about how behavior is going to be strongest in the presence of those terminal links stimuli, so therefore we should work backwards from it using backward chaining. So if you want to establish this token economy by first teaching the exchange response as a discriminated operant, for this reason we want to have a, they recommend having a different last token, so in their examples in the article, it's shaped like a star instead of a circle, that signals the end of the first reinforcement schedule and the availability of the backup reinforcers. When you're training this, the board's already full, you're just teaching the handover response in order to then access the backup tray of reinforcers. So this looks like table is empty, the learner oriented to the teacher, the, sorry, what's that called token board that's full and has the final special looking star token is on it. The learner picks up the board, only once the board is picked up, the teacher opens their hand to receive the board. Oh, yeah, it's a rookie mistake otherwise. Yes. Because what should be signaling the end of the first part of the chain in the beginning of the reinforcer period is the last special star token, not the teacher opening their hand. Okay, so once they have it in their hand, then the teacher can open their hand, the learner hands the board over, and then the reinforcer selection tray becomes available. Okay, that's what part C establishing the exchange response looks like. Part D is establishing the tokens as reinforcers. So here, only once we get to part D, or even like messing around with the tokens. Well now, there was no token manipulation happening. So here we want to establish or train the tokens as condition reinforcers. So we would start this by presenting the last token with the board art, the board's full, except for the last spot, and the last token is presented as well. And we want to teach the student to put it on, which will then initiate the description stimulus for the exchange response that's already learned. With this process, the tokens can become discriminative stimuli. And then I'm going to give you guys a quote again, they say in this article, stimuli in change schedules serve dual functions, reinforcing for the response it produces them, and discriminative for responses that occur in their presence. And that is straight out of Skinner 1938. Go Skinner! The token becomes a conditioned reinforcer through its relation to a discriminative stimulus, the completed token board, the next thing in the chain that ends with the exchange period and backup reinforcers. End quote. All right? Yeah. So it's really through that establishment of the reinforcing properties of the tokens, through the discriminative training, and they're going to come to function as reinforcers through their positioning in this whole chain of events. So they really are kind of on this camp that this is how tokens come to be established as conditioned reinforcers. They talk a little bit about stimulus stimulus pairing, which is just presenting the token with the backup reinforcer together. And there's research to back both of them up and, you know, different times each of them may be at play, but they feel pretty strongly that it's occurring in this context of the chain schedule and that's really how things are kind of getting established. Okay. So to teach this, I think I reviewed it mostly. The board is present with the last spot open, the learner-oriented to the teacher and the board. The last special token is out on the table, the learner places that on the board, and you can use airless teaching to teach this if it's not learned. They pick the board up once the last token's on, then the teacher opens their hand, they pass the board over, and then the reinforcer period selection trade is presented. Okay. Part E is a slight detour. Token handling and placement. We have to decide. Handling is the learner, are you going to place the tokens on themselves, or should the teacher do it? They posit that it should enhance the discriminability of the token and have it operate more as part of the chain. If the learner manipulates it themselves, there's another article, Slime and Colleagues, that found learners prefer manipulating the tokens themselves, so that's their general recommendation. However, it is possible that the tokens could be a distraction, and that is why they recommend against those special interest tokens. We used to use those a lot. We would get a set of stickers from the hallmark store and laminate them, and then you'd have a little mini play set almost with the stickers being the different figurines and somebody's favorite TV show. They're out against this idea. It definitely could be more interesting, but for some learners, it just could be distracting, or the tokens themselves could be too fun. So, if you're seeing a lot-- We've had that before, though. Yes, and you can. But if you think that it wouldn't be an issue, you could try it, and then if it is, then don't do it. But that's the reason why it's potentially distracting, or if you end up with a lot of interfering or extra behavior about positioning the tokens or something like that, then maybe we're going to end up working against the overall learning experience for the learner, which is what this should all be about. OK, so that was a slight detour. Next up is extending the chain. This is part F. So once you have the-- putting the last token on established, now you can work on teaching the learner to fill up the token board with the other tokens. And here, they're recommending backwards chaining. So they learned to put the star token on. Now they can learn to put on token number four, and token number five, which is the star token. It makes more-- they both-- basically in the section say, it makes more sense for us to teach this backwards. You can vary the tasks, start with easier tasks, is what they recommend, but also vary it as much as you can, and sometimes still offer tokens just for the orienting response in order to keep all of this at strength, right? Can you teach you through forward chaining? They're like, yeah, I guess. But why would you want to? Right? It feels like they're perfect for what you just say about that. I'm in play. You know, they're just trying to account for all the literature that's out there. Yeah, they do that quite a bit. They're like, there's really a lot of research. But why would you do it that way? Yeah, yeah. OK. And then section G is, again, a little bit of a esoteric discussion, perhaps. But here they say, now we got to think about how the trade-in side of this is going to work. So there are two types of ways in which you could do this trade-in. It is called token-chained versus standard-chained schedules. I know. Jackie's face is like, oh, my lord. I read this part. And when I read it, when I said that, I did this. Oh, no. Yeah, right. Oh, no, they lost me. Here's where I'm falling into the hole. I'm like, pull me out. It's like a cartoon character. She's like, oh, oh, oh, oh, oh, yeah. That sound? OK. So most basic research on tokens uses a token reinforcement schedule, which is you earn three tokens. You get three things. However, most of the applied actual clinical application of token schedules doesn't really work that way. It's like, you earn three tokens, and then you get the one trade-in things, right? That's much more common. So it's kind of like there's a mismatch between what we know the most about from basic research and the way in which tokens are most often applied in the applied setting. And we kind of just don't necessarily know if that is an issue or not, because there's not a lot of research here. So in the basic research, when we see really high rates of responding, it's based on this other schedule that we hardly ever use, which is three tokens equals three things. We are more likely to increase the number of tokens and then still produce access to the one thing. And without getting into too very much detail, we don't necessarily know if that's an issue. It may be possible that when we start to see drops in responding, it could be because of the way in which we're setting the schedules up. Kind of need more research here if anybody cares to research this. Well, that's certainly going to be a key component. If there were research to support, if you're not following the token chain-- well, I can't remember which one. The token reinforcement schedule, as in the basic research, you're not going to see the same level of success. Token economies, I find it hard to believe that the way folks have done in the applied settings haven't resulted in some amount of success given that the token economy is still a going concern overall. But if it were a matter of, well, you have like 10 tokens or you're in 20 tokens, and when you pick a thing, you get 20 minutes or 20 multiples of whatever the consumable item you picked, that's going to start becoming a cost concern for a lot of places. And I think it would make the token economy less applicable. So it would be good to know that 100%. It'll never work if you do it in way X or way Y. However-- We don't know. We don't know. Yeah, yeah, yeah. But barring that research, I would say-- These are questions to think about. It's the applicable. I would use the one that's going to be more applicable, which is the way most people, I think, I've seen run token economies of your next number of tokens. And now access-- It's trade-in time. Yeah, you get access to one of the things from your track for a period of time, or until it's consumed. OK, all right, then last section here in the Building the Economy section, which is number 8, thinning the schedule. Here the question is, is it better in the mind's eye to suffer the slings and arrows of increasing the token production schedule, which requires more responses to produce a token or to increase the exchange production schedule, which is requiring more tokens to produce an exchange? I like this question. This was interesting. Yeah. So the second one, which is requiring more tokens to produce an exchange, tends to produce stronger effects than the first one, the token production schedule, requiring more responses to produce a token. All right, so in other words, increasing the number of tokens required for an exchange is thought to keep responding stronger than requiring more responses to get a particular token. It's closer to the terminal inquiry enforcer, so we see stronger effects. So their recommendation here is to keep the number of responses per token low and constant. And if you want to thin the schedule, increase the number of tokens required before the exchange. OK, love it. All right. That's easy. So easy. All right, well, thank you, Diana. So that's the first part of the article. We know how to start your token economy. But to keep it running, well, that's a question for after the break, we'll be right back. [MUSIC PLAYING] Hi. Do you want to be a BCBA? Also known as a Board Certified Behavior Analyst? Sure. We all do. Now you can come to Regis College in Western Massachusetts to get your graduate degree just minutes outside of Boston. Choose from any one of these courses. Masters of Science in Applied Behavior Analysis. Masters of Science in Special Education dual degree in Special Ed and ABA, or be eligible for your postmaster certificate. You can complete your degree and be ready to sit for the exam in two years. And our 2022 graduates had a 92% pass rate on the BACB exam. Come enjoy approved fieldwork placements, ethics, many handbooks, PhD levels, professors, small class sizes, and a service trip to Iceland, if interested. And don't forget, our program is accredited by the Association of Behavior Analysis International or ABAI as a tier one master's degree program. Don't delay. Supplies are limited. Learn more at regiscollege.edu. Again, that's www.regiscollege.edu. Regiscollege.edu. One more time, www.regiscollege.edu. See you there. Bye. (upbeat music) And we are back talking about the how-to of token economies. But before Jackie takes over and tells us how to sustain our token economies, I want to remind our listeners that ABA inside track is Ace and Quaba approved. And by listening to this episode, you can earn one learning credit, learning CE. All you need to do is finish listening to the episode, then go to our website, ABAInsideTrack.com, or click the link in the podcast player, and put in some key information, including two secret code words. I'm going to tell you the first one right now. It is Penny, P-E-N-N-Y. It is the smallest denomination of coinage here in the United States of America. And also the name of Inspector Gadget's niece. Remember, Inspector Gadget's niece-- - I love that. And Inspector Gadget's niece. - She and Brains actually solved all the crimes. dead. - Most people thought it was Inspector Gadget. He was kind of a bumbling idiot. - He had go-go gadget arms. - He did have go-go gadget arms. That's very important. All right, Jackie, let's continue. We got into open economy. We did a lot of work to make it, make it start in the first place, and now I want it to go forever and ever. What should I do? - Okay, so now I'm gonna talk about sustaining the economy. They call it practical suggestions for effective implementation. - Okay. - And I go down to F. - Okay, you got six. - Six, I was like, I can't do the numbers 'cause I'm not counted, but it goes to F. So the first thing, in mine's kind of interesting too, because I think here, when you read, they'll each section really has like one take-home message, and they like try to fill it in with the research. - So like, but really you should do it this way. - But really you should do it this way. Is this next section- - I don't mind that. - I don't mind it either. - Right, that's why we're doing a tutorial. - Right, so they asked the question first. Okay, now that it is, you have it in your repertoire to use the token economy. How can you establish and maintain it? Or how can you maintain it? And they recommend, the first question that yes, they ask is should it be variable or should it be a fixed schedule? I know. And they make the case that variable ratio schedules produce higher rates of responding, generally are more preferred in the research. So they suggest to move as quickly as possible to a varioratial schedule, changing up as many elements that you talked about before, as possible to make it hard to be predictable, right? So if you just change one, like if you just change the token, right? Then it's gonna, then kids might figure it out and that's less preferred. So you may need to change this. - Well, 'cause we want indiscriminable contingencies in order to maintain, generalize responding. - Right, yep. - And it's more preferable. People like it better. - So they do recommend that you might need to change the design of your board now because it's not gonna be static, right? It's not going to be, once you fill these five slots, then you switch the token board in and they say it. - I feel like they wanted to bold it and underline it. They're like, there will be open places on the board when the exchange occurs. This is okay. (laughs) They said it so many times. What if they're open places on the board, Jackie? - Right, it's okay, everyone. - It's okay. - So they said here, in this case, you will make the predictive token signal that exchange is possible. So just like, when Diana talked about it, the star token would signal that the exchange now is ready. - And this would not work. I can understand people being frustrated with that idea if they hadn't read the first part of the article because they'd be like, I'm just gonna be constantly sticking my hand out at random time. - No, no, no, no. - You told me don't do that too, but having that predictable token that it's, you know, stimulus control over the, giving you the token board. - Yeah, you do need to read part one. - Yes. - 'Cause I actually read part two first and then part one. - And it's a mistake. - Much easier. - You read part one first, yeah. They also remind us in this clinical applications part that you shouldn't put the predetermined amount of tokens out for the client to see, right? They said it should be in a bowl or an opaque tin so that you can't see the number of tokens that they need to answer. - I know, I love that. They're like, remember. - So you're choosing when to pull out that star or whatever the special token. - Well, you're not choosing. That's another thing that they talk about is that human beings make a lot of errors when left to their own devices. And so they said, okay, when you're gonna use a variable schedule, you need to make sure that it's predetermined, right? - Yeah. - Because everyone does it wrong. So they said the drawback to having a variable schedule is that it requires more effort in planning, right? Because you need to have a predetermined number of responses and when you're gonna do it, especially if it's a variable interval, right? Then you need the time and the response. - Oh, boy. - So you need to be thinking about that. But they-- - Here's where AI could come in handy. Say, make me a schedule that's, you know, that's gonna be around variable response six and like different numbers of trials or whatever. - Yep, and that could be like a hidden little thing for the therapist that the client can't see again, right? To make sure that we're making it unpredictable for them. But they did say, if you leave people to do it themselves, it will not be a variable schedule and it will be horrible. There'll be no schedule at all. And they give you in figure five a really nice way to see the total number of responses needed and how they got to those responses, changing each of the things. So like, for example, they had 10 blocks of trial and then they said, okay, in block number one, we're gonna have token one is gonna occur after five responses. Token two is gonna recur after one response. Token three is gonna recur after three responses, right? So it shows you how many responses you need in order to hit the variable ratio five and the variable ratio three for the exchange and for the token. And across 10, you would make 150 or 50 a hundred responses. - Oh, 50 responses with 150 exchanges. - Okay. - Yes, this definitely sounds like an AI. Make me a thousand different data sheets because people will follow that. If you're like, I need you to follow all these other cheat sheets or do the math every morning when you get it, like, no. - No one's doing it. - They'll be like, five every five, right? I'm doing every five. - But I love this. It makes a lot of sense. And then we make these types of plans for delay and denial training as well. They already have this type of like built-in variance in those, so this is just another application. A little more fluid and based on the client sort of response. You have general rules, but it's not always as, I don't think it's not quite as tightly controlled. It's tightly controlled, but not quite as tightly controlled. 'Cause I think they're recommending here for the token economy. - Okay, yeah, I agree with you, but it's cool. Now, here's where it gets really interested. - Okay. - You're like, now if you've got token economy's going, you've got performance going. Now you wanna level up. You can use second order exchange schedules. That would expand on the token economies by using two or more boards. So one token board would produce a re-informed final token, but that token would then be put on another token board to satisfy that token board requirement. - Okay. - And holy moly, this one made it confusing for me until I looked at the picture. So in the picture, I have it here, the first requirement for one token board was 10 responses. - Okay. - Right, they got a token for each response. They got the star on the 10th one. When they got the star, they put the star on the second token board, right? Then they continued, they got a token, got a token, got a star again. Now the star goes to the second token board. Then they did eight responses on the eighth response. They got another star, the star goes on the token board, and then the finally, they went four responses, got a star, and it went on the second token board, and then they could finally trade in. - Got it. - Fascinating. - Yeah, right? - You explained that well. - It was hard for me. - Yeah, it makes sense. - Yeah, so they said, think about the stars as vouchers, right, that we would use, and they said this is gonna help sustain performance over longer periods of time, and it makes it more complex so that it's actually what really happens in real life. - Mm-hmm. - Yep. And then they said, well, maybe you can't make it ratio-based, right, maybe you have to make it time-based. And this could be a adaptation if you're doing a whole classroom schedule, or if you have multiple requirements that need to be met, right? And so this could be at the end of a session. And here, they said it is advisable to use a variable interval and set up a fixed interval because what we know happens with fixed interval. - Scaloping. - Scaloping, right? - Yeah. - I wish that I could also- - I mean, they're good, but not in this context. - Not in this context, because you want- - A little brown butter. (laughing) - You want higher rates of responding, right? And we all know what the scallop pattern or the fixed interval is that a time requirement needs to be met. I'm gonna say this because many BCBAs get this wrong, and it really bugs the bejesies out of me. For a fixed interval to be met, the time requirement has to be met, and then the response following that time requirement receives the reinforcer. - Right, 'cause otherwise it's a variable- - A fixed time schedule. - When it's independent of responding. So this is one of the most common things I see people get wrong, bugs me. So I'm gonna bring it up. But what we see with the fixed interval is that there's low rates of responding following the reinforcer, and then as you get closer to the interval, you see more rates of responding. It's like me going to wait for my mail 'cause I love my mail, man. I really love him, his name's Billy. - Oh wow. - But I don't go in the mail at night. - Sure, right. - I only go, he goes to 7 a.m. - Oh wow. So I'm on there. - I haven't checked my mail in six months. - I checked my mail. - Maybe two years, Rob checks a mail. - Oh, well there you go. - So. - Hi, Billy, if you're listening. (laughing) - He's trying not listening. - I do love him now. - So yeah, they said it makes you- - It's a no-fix interval. - No. - Okay, variable interval. - Okay, got it. - And a second recommendation, a second recommendation they said is to use a token chain schedule like you talked about. This helps with sustained responding as with everything else. And the example here, you should again use the variable interval and not the variable time. - Okay. - Yeah. Then they talk about generalized reinforcement. So the next one you have to think about. So this is talked about [BLANK_AUDIO] can be exchanged for two or more backup reinforcers, right, and these tend to be more durable because they don't specify the response, right, it's less easy to be satiated on it and it doesn't have to tie to a specific motivational state. So the general recommendation here is to include a healthy array of reinforcers here. But that do they mean healthy reinforcers are just like a substantial array. Not too little, but not too many. And Goldilocks amount of reinforcers. So this is up for debate. They said that research is there is no research out there when you should ask the client what they want, if you should do it before the session, what backup reinforcement or after. But they do say that maybe you wait until the end because you might want something before and then you work so hard and now you're hungry or thirsty or you don't want it anymore because you've worked so hard and now you want to do it after, right. I was surprised that this wasn't in my section because it's a question I always have to know. Yeah. I've done it both ways and I prefer the end. I thought it's just been flexible. If someone changes their mind, I'm like, oh yeah, I don't care. That's great. You did the thing. I liked it. You're in the tokens. To contract for it initially, but then check in at the end. You could do that too. Yeah. Yeah. They didn't know. They just said, just don't be mean and if someone says, no, 30 minutes ago, you said you wanted this. I refused to let you change your mind. I like that. Maybe this is something you want. Look at all the things you have and then you can do it again. Yeah. I like that because I don't always want when I wanted 30 minutes ago. So they also reminded everyone to conduct periodic reinforcement assessments for sure what you're offering are the things that the person wants. They also suggested that it's important to encourage reinforcement sampling to make sure I love reinforcement sampling. But they're saying specifically that usually a person really wants a high preference item every single time. And it's okay to admit it sometimes. Yeah. So that they can choose other things. Yes. Yeah. All right. And then they're like, okay, let's talk about when people have differential pricing on backup reinforcers. And I love the sense where they're like, there's our research here. So we can't make up any recommendations. But another area that seems like very right for research. There would be so much research because typically, I mean, I'm in school settings, but like that's the economy I've seen. It's, you know, the one that looks like a store of the stores. Oh my gosh. There's a lot of emotional behavior classrooms. My four great teacher had one of these and things did have different prices. And I still remember fondly. Me too. It was take your tickets and go get to treatment. It's a frank folder. Right. Yeah. A lot of erasers. A lot of pencils. Yeah. A lot of folders. I have a PBIS systems have that. Right. So he tokens in every one store. Yeah. Okay. So it's like ski ball. Yeah. So here, I love that. But here is where we're all doing it wrong. They suggest not to label pricing on it. So don't tell people how much things are worth prior. Because then they're going to stop responding once they get that amount. So they said to put them in categories or bins of lower cost, medium cost and higher cost. And so then once they've met the criteria for the lower cost, they can either trade in for whatever's in the lower cost or keep working for the things that are in the higher cost. And what they recommend here is this also teaches self control. Right. Because if you really want that thing in the last, then you can save all your tokens more research. I definitely would say more research because that sounds like it would be very effective if you had like a very self-contained classroom where students were trading in pretty frequently, maybe to manage challenging behaviors, skill acquisition both. If you were using a token economy at some sort of larger scale, like a whole institution or a whole school. That would be harder. And it's like, well, it's a store day at the month. How many tokens do you have? I have a million. Okay. Well, you can only choose from the crappy shelf or you can save till next month. I'd be like, you know what? I hate this token economy. I'm just going to take what I want. Yeah. So I guess we'll see more research is there. So that was just the recommendation and they had a cute little, again, little figure where they had different color boxes. And you could exchange for that in the box or you could carry it on for the next one. I think you'd have to have a very controlled economy in terms of knowing how much could one earn so that people aren't getting there with a billion tokens and then saying, what the heck? Why can't I get the most expensive thing? Yeah, right. All right. And then the final thing they talk about is closing the economy. And they said a closed economy is one in which reinforcers are available only in the targeted context and not outside that contract. Whereas an open economy is which reinforcers are available both inside and outside those zones, right? And so they said if it's open, the demand for the reinforcers within the economy might be lower makes sense, right? Because they can get a different times. And if not available outside, the token economy will increase their value. And so they said one way to close the economy, the token economy that is is tariffs. Oh, no. One way to close the economy is to make those reinforcers only available during the token economy, right? So close it as much as possible. If you can't do that, right? Because there's like TV at school and at home, you can make it partially available with making the more reinforcing aspects only available during the token economy and the less reinforcing aspects available outside of the economy. So that's kind of neat idea. And then they made a broad suggestion that all academic learning should be within the token economy, including acquisition and maintenance and skills that are not discrete because it'll increase the value of the token economy. Yeah. And that's all. Boom. All right. Yeah. I love that. Let's move into dissemination station. Okay. Where you were saying Donna, very thorough. Very thorough. There we go. Very thorough, darling. So in terms of dissemination, I mean, I guess which of the which of the questions from 82 are still in line? I mean, I think the dissemination certainly we didn't do that between 82 to this one because so many people are doing token economies wrong, wrong without knowing so not taking advantage of some of the basic research that goes behind them. So certainly I think having an article like this to rethink of how you are running your token economies will allow you to better explain how to use them. And I think the more effective they are, the more people will want to use token economies. I think this doesn't speak to some of the other issues in terms of like leadership and administration. However, if you can demonstrate utility of token economies more so than you perhaps have in the past, they're going to get much more widespread adoption and more people will want to use them. And I think in terms of training, you know, that issue seemed a little solved in terms of, you know, we have so much research on BST, but have we been training correctly? So I think this is a great a great article to sort of come back to and review how you have used token economies, how you use token economies. Do you want to follow these recommendations? There are a couple places where there's not enough research to say you have to follow these recommendations, but there are enough that I would say you probably want to treat this as the steps you would follow through as you regain fluency with some of those missed or maybe fudged steps you've done in the past. Okay. I just love and I wish that everyone would read this article and listen to our previous episode with Jason Beret because this is not my experience with token economies. Anytime I've seen token economies will not anytime, but many times they're like, oh, they love Peppa Pig. I'm going to cut some stickers out with Peppa Pig and slap them on a board. Good five and I'll take your token board from you. I want to actually tell you that you got them and then I'll let you play with something and possibly all the child learned is I did something for a while and then I got to play or possibly learn, oh, I get to play with these Peppa Pig tokens. Yep. I don't have any, I don't know if I have anything else to add. I mean, there's like some good areas here where additional research could be done, but I think if you're going to delve into this area of research, you should read this article in detail first to make sure that you get it because it's, it seems easy on its surface, but they're actually, it seems hard. It seems easy, but hard. Well, yeah, like implementing a token economy, like you just said, you're like, I got five tokens and I'm going to give them everybody and then they trade them in. It seems easy, but then talking about like the behavioral mechanisms that are involved, it's, it is more complex, although the mechanisms themselves are not complex, but you got to know it in order to I think then like troubleshoot and figure out how to teach it the best way possible. And that is actually what they say in the summary and conclusion section is that it's actually not that hard to use token economies, but it's a lot easier to use token economies if you know all the different pieces that work and how they're intertwined together. So when it's not working or performance isn't going as you want it to, that you can then take each of these pieces and, and problem solve. Exactly. All right. All right, so read this article, listen to our episode. Well, you've listened to the episode at this point. So you now you've listened to it. I would say print out a copy of the article, get it digitally and have it as a nice reference and then you don't practice, practice doing these steps again because you might need to relearn a few of them or get them back into your repertoire. I mean, you never thought about them. Yeah, we're running a certain economy like this. Yeah. You know, I don't know that everyone gets trained in how to train a token economy, which is why we wanted to do this tutorial. Yeah, we usually think of it as the same as like you go to a store, like you do some job, you get paid and then use that money to buy things, which that could work as a token economy. I mean, how much do rules play into our use of money, but they're not always going to be effective that way. So it worked for those miners that had to pick from the catalog as a throwback to an earlier episode which brings me to Paris. Oh, thank you. I got a special sound effect this time. So, Paris is the part of the show where I tell you about past episodes that you might want to check out if you found this one interesting. I have a couple. Way, way, way back in episode two, we talked about Conditioned Reinforcers in the Social setting, which I just bring up because it talks about Conditioned Reinforcers. But more specifically, we had two episodes that we talked about token economies previously. Episode 175 is where we just introduced the idea of token economies and reviewed some research. And then we were very fortunate to have Dr. Jason Baray join us for episode 195, which is titled Under the Hood of token economies. And if you want your mind blown with everything you never knew or even knew to not know about token economies, that is the episode that you should listen to. That's the why to this episode's how? Oh, my gosh. Yes. I mean, I think that remains one of the episodes where I felt like I learned so much and clearly same had so little prior understanding to tokens than that than any topic. So please check out episode 155. And then like we said, we're, you know, trying out this tutorial series. So this is, I think only our second one in that series. And the other one is episode 301 where we did a tutorial on procedural integrity systems. And then I also like to recommend a snack that you can listen to while you, that you can eat. Oh, yeah, sorry. That you can eat while you listen to these episodes. So I got two snacks for you today. And I want you to see if you know why I'm suggesting these two snacks. Number one is the subway sandwich. And number two is the TCBY. I don't know what a TCBY is. It's a yogurt place that doesn't exist anymore. Oh, yeah. Okay. So do you know why? Oh, Diana, just tell us. I'm sure there's some really great reason that you thought of mine was banana and cell sore because that's what I was drinking and eating during this. So Rob said I wasn't making them related to the episodes enough. Oh, well, I don't know. So this is because in the past, at both of these places, they would give you a little card. And you could get a punch for every one that you got, right? So you get your order 10 sandwiches, you get 10 TCBYs, and then you would get a free one. So it operates like a little mad Martha does that ice cream place on Martha's vineyard. I've never been to Martha's video. Snobbers. Yeah, right. That sounds a little hoidy, I mean, they do. Okay. That was pairings. Please enjoy. All right. Well, thanks everybody. And that's our tutorial on token economies. We hope you enjoyed it. Thank you so much for listening to ABA Inside Track. If you like the show, please leave us a review online or wherever you get your podcasts. You can find us a lot of places online. Certainly our website, ABAInsideTrack.com, where you can find links to the articles we discussed in this episode as well as all of our previous episodes. You can find us on patreon at patreon.com/ABAInsideTrack, where you can subscribe at any level. But if you want to get access to every episode a week ahead of time and access to all of our polls, including the poll that shows this episode, you need to subscribe at the five dollar and up level. And if you say, but I like these, could they be about books and be like twice as long? Well, then you should join at the $10 and up level where you can hear our quarterly book club podcasts. And that was a great time to join because we're going to be having our what's coming out in 2026 book club choices coming out to be voted on very, very soon. In the meantime, though, you can listen to our most recent episode right now instead of waiting for it to drop a year from now in the free feed. That was on divergent mind. It was on divergent minds, which is a book we all quite enjoyed about neurodiversity, about female neurodiversity. And that is again patreon.com/ABAInsideTrack. And finally, don't forget the second secret code word, it is poker, P-O-K-E-R, another area where you probably had little chips that could be used in the token economy, right? Poker. Some final thoughts, big thanks to Dr. Jim Carr for recording our intro and outro music, Kyle Stury for interstitial music, and Dan Thabbit of the podcast doctors for his amazing editing work. We'll be back next week with another fun-filled episode. But until then, keep responding for your special token. Bye. Bye. [BLANK_AUDIO]