Token Economies in ABA Therapy

ABA Token Economy

The History of the Token Economy

Token systems date as far back as the 1800s and have been utilized as behavior-management and motivational tools in educational and rehabilitative settings (Hackenberg, 2009). Token economy systems expanded across other professional fields in the mid-1960s and quickly gained popularity as an effective intervention for treatment across diverse settings and populations (Kazdin, 1982). Hackenberg (2009) stated token economies were instrumental in the origination of Applied Behavior Analysis in the mid-1960s and are acknowledged as one of the most beneficial and effective behaviorally-based treatments in the history of psychology. 

What is a Token Economy?

A token economy is a contingency based procedure developed to aid in the reduction of maladaptive behaviors and increase desired behaviors through the deliverance of a tangible conditioned reinforcer.

 

A generalized conditioned reinforcer consists of one specific reinforcer that has been associated with at least two or more back-up reinforcers (Cooper et al., 2019). Cooper et al. (2019) defined back-up reinforcers as tangible objects (e.g., toys, candy), activities (e.g., swimming, playing at the park) or privileges (e.g., staying up later on a school night, earning extra video game time) which all function as a reinforcer for the learner and can be purchased with tokens.

 

A generalized conditioned reinforcer is not required to be a tangible item but can include more natural forms of reinforcement consistent with the context of the environment (e.g., social praise, making a friend, and other naturally occurring reinforcement). However, token economies utilize visual and tangible representation of the generalized conditioned reinforcers (Hackenberg, 2009).

 

Examples of tokens may include poker chips, marbles, stickers, color charts, pennies, popsicle sticks, Legos and so much more. Tokens can be individualized based on learner preference, the need for portability, durability, and the frequency the tokens will be delivered. 

 

The tangible conditioned reinforcer, or token, would be provided upon the occurrence of the desired target behavior/s, which would later be exchanged for predetermined back-up reinforcers (Kazdin & Bootzin, 1972). Token economies may also be paired with response cost procedures (i.e., negative punishment procedures) by incorporating the removal of tokens upon the occurrence of maladaptive behavior/s (Cooper et al., 2019). A large-scale example of a token system would be the world economy where individuals complete work (i.e., desired target behaviors) in exchange for currency (i.e., conditioned tangible reinforcer) which is used to purchase a variety of favorable items or activities such as cars, homes, electronics, etc. (i.e., back-up reinforcers). The chart below illustrates the general cycle of a token economy system.  

ABA and Toke Economoes
Figure 1. The flowchart above illustrates the basic steps encompassing the implementation of a token economy.  

Token Economy Advantages

Generalized conditioned reinforcers, as well as tangible conditioned reinforcers, have many advantages highlighted by Kazdin & Bootzin (1972) and Ayllon and Azrin (1968).  

Advantages of Generalized Conditioned Reinforcers: 

  1. Reduce the gap between the target behavior and the back-up reinforcement. 
  2. Easily allow access to reinforcement for a specific behavior at any time. 
  3. Promote maintenance of a skill over longer durations of time when the back-up reinforcement is not accessible.  
  4. Permit a sequence of behaviors to be reinforced without disruption of the task/behavior. 
  5. Assist with maintaining the value of the back-up reinforcers due states of deprivation.  
  6. Less likely to be susceptible to the effects of satiation.  
  7. The same level of reinforcement can be provided to individuals despite the differences they may have in their preference of back-up reinforcer (i.e., group contingencies). 
  8. Have the potential to become more reinforcing than a single primary reinforcer. 

Additional Advantages of Tangible Conditioned Reinforcers: 

  1. The number of tokens earned can coordinate directly with the level of reinforcement which will be provided using differential reinforcement methods. 

  2. Token can be brought with the ABA practitioner to many different places and the learner does not need to earn them all in one place. 

  3. There is no maximum number of tokens a learner can accumulate based on the program description or expectations.  

  4. Some tokens can be used in conjunction with a specific device that will automatically deliver the reinforcement (e.g., such as a candy dispenser, soda machine, etc.). 

  5. Tokens provide a visual representation of reinforcement during the time the learner is waiting for the back-up reinforcer. 

  6. Tokens can be individualized and created specifically for the particular learner.  

  7. Tokens can be created with durable material. 

  8. Tokens can be created in a manner which the learner would not be able to duplicate to ensure tokens are only provided when the learner engages in the target behavior.

Steps for Development of a Token Economy

Select Target Behaviors 

The first step toward the development of a token economy is to identify the target behaviors, both desired and reductive, which will be the focus of the intervention. Ensure the responses are defined explicitly in descriptive terms so reinforcement is provided for specific responses so there is no room for interpretation (Kazdin & Bootzin, 1972).

 

An example of a clearly defined target behavior for raising your hand could include the following: “The learner will lift one arm and hand (i.e., with an open palm) up and over their head, keeping the elbow parallel with the ear and remain in this position until called upon by an adult and in the absence of ‘calling-out’ behaviors.” A descriptive definition that encompasses both the topography (i.e., what the behavior looks like), as well as the behavior targeted for decrease (i.e., calling out) provides enough guidance to minimize the likelihood of ambiguous token delivery.  

Identify Back-up Reinforcers 

Once the target behaviors are clear, preference assessments can be used to identify the type of back-up reinforcers to offer at the exchange. Kazdin & Bootzin (1972) discussed a principle coined by Premak in 1965 which explained how higher-probability behaviors that occur frequently can be used as reinforcers for low-probability behaviors.

 

Examples of high-probability behaviors could include going on a walk, playing with the iPad, watching television, or playing with toys, and in essence, these activities can be used as the back-up reinforcement when tokens are exchanged. Another popular option is setting up a “store” where tokens can be exchanged for access to tangible items such as snacks, toys, candy, and more (Kazdin & Bootzin, 1972). 

Establish Tokens as Secondary Reinforcers 

The foundation of token conditioning will be the same concept across each intervention, but specifics of how to establish the tokens as a secondary reinforcer may vary depending on a few factors such as age, setting, and developmental or intellectual functioning level. These factors may impact communication modalities and the rate of acquisition across learners. For some learners instructions will be sufficient when paired with the rapid delivery of tokens for desired behaviors, followed by two to three opportunities to exchange within the same teaching session (Hackenberg, 2009). For others, a more systematic approach will be required. 

Token Conditioning for Early Learners 

In some cases, a more structured teaching procedure is essential, which may include contriving multiple opportunities for the learner to engage in the target behavior/s. This allows opportunities for tokens to be delivered along with other forms of conditioned reinforcement such as praise, edibles, or social games like tickles and high 5’s. By pairing the tokens with other known reinforcing activities and providing multiple opportunities to meet the contingency of exchanging tokens for back-up reinforcement, the tokens will soon become a secondary reinforcer.  

 

An example of conditioning tokens as a secondary reinforcer for an early learner or a learner with significant communication difficulties may include creating a simple token board visual, consisting of only a few tokens and paired with a simple picture trade-in menu. It may also be helpful to pre-load the token board for the first few trials and leave only one space blank. Next, opportunities would be contrived for the learner to engage in the desired response, the last token would be earned, and the reinforcer would be immediately distributed. This same procedure would be repeated a few times before moving with two empty token spaces on the board and continuing to repeat the process until there are not any tokens pre-loaded. The visuals below represent a five-token board system with a three-item trade-in menu, which also includes a simple rule board.  

ABA Token Board
Figure 2. The above illustrates a simple 5-token board system with the rules included for reference prior to, during and after tokens are earned. 
ABA Token Economy
Figure 3. The above illustrates a 3-item trade-in menu represented using pictures. 

Clearly Define the Rules 

Last, ensure the rules of the token system are well understood by the learner, despite the level of simplicity or difficulty (Kazdin & Bootzin, 1972).

 

For an early learner, the rule may be as simple as responding to a prompt will earn a token, and after 3 tokens are earned would equal an exchange for a social game like ring-around-the-rosy, rolling a ball back and forth, or a small piece of candy.  

 

For an advanced learner examples of rules may include transitioning without verbal refusal, raising their hand vs. calling out, and even responding to prompts. Tokens would be delivered upon each occurrence of the target behavior/s, resulting in the learner being provided with an option to exchange for reinforcers.

 

A trade-in menu for a more advanced learner may include options to exchange 15 tokens for a trip to the snack bar or 20 tokens for ten extra minutes of break time. Earning a large number of tokens (e.g., 50 tokens) could potentially be exchanged for a trip to the movie theater or a new video game. It is important to ensure the learner fully understands the rules, especially if a response cost procedure is incorporated, as punishment procedures may increase maladaptive behaviors for some learners and decrease the effectiveness of the token economy system. 

Final Considerations

While this article focused on the foundations of token economies, it is important to note additional considerations to investigate before implementing a token economy with a learner. Kazdin & Bootzin (1972) stated the importance of pre-planning for fading the token economy and generalization of behaviors to naturally occurring settings to ensure the maintenance of the desired behaviors are achieved after the intervention is removed.

 

These additional factors can be analyzed and incorporated by means of creating schedules of reinforcement at each phase of the token economy intervention. There are two main types of schedules of reinforcement, continuous and intermittent.

 

Continuous reinforcement schedules are associated with the acquisition of new skills, as each occurrence of the desired behavior accesses reinforcement. Whereas intermittent reinforcement schedules are variable and the desired behaviors access reinforcement on an unpredictable schedule which promotes maintenance of skills (Lattal & Neef, 1996).

 

Token economies should begin with a continuous schedule of reinforcement and systematically fade to an intermittent schedule of reinforcement, before finally fading to naturally occurring reinforcement provided by the environment.  

Conclusion

Token economies have evolved over the years into a promising treatment option across many professions and settings, especially those in the field of Applied Behavior Analysis.

 

Token economies can be advantageous for many learners and ABA practitioners alike, as they heavily focus on positive reinforcement of desired behaviors, can be individualized, support flexibility across many settings and promote clear and consistent behavioral expectations.

 

Considering the duration of time token economies have been around and the abundance of research available demonstrating their success, token economies are an incredibly valuable behavior modification procedure to consider when maladaptive behaviors are a primary focus of the behavioral treatment plan. In conclusion, behavior analysis can feel confident when making the decision to implement a token economy by acknowledging the research which illustrates many examples that have yielded positive results, while also taking advantage of the flexibility and conveniences that token economies offer.   

References

  1. Cooper, J. O., Heward, W. L., & Heron, T. E. (2019). Applied Behavior Analysis (3rd Edition ed.). Pearson Education. 
  2. DeFrancis, S. (2016, July). A Qualitative Study Analysis on How Utilizing a Token Economy Impacts Behavior and Academic Success. Brandman University: Chapman University System. Retrieved November 2020, from https://digitalcommons.brandman.edu/cgi/viewcontent.cgi?article=1031&context=edd_dissertations 
  3. Hackenberg, T. D. (2009, March). Token Reinforcement: A Review and Analysis. Journal of Experimental Analysis of Behavior91(2), 257-286. PubMed Central (PMC). 10.1901/jeab.2009.91-257. 
  4. Kazdin, A. E. (Fall 1982). The Token Economy: A Decade Later. Journal of Applied Behavior Analysis15(3), 431-445. Wiley Online Library. Retrieved November 2020, from https://onlinelibrary.wiley.com/doi/abs/10.1901/jaba.1982.15-43
  5. Kazdin, A. E., & Bootzin, R. R. (1972, Fall). The Token Economy: An Evaluative Review. Journal of Applied Behavior Analysis5(3), 343-372. PubMed Central (PMC). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1308287/pdf/jaba00041-0109.pdf 
  6. Lattal, K. A., & Neef, N. A. (1996, Summer). Recent Reinforcement Schedules Research and Applied Behavior Analysis. Journal of Applied Behavior Analysis29(2), 213-230. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1279895/pdf/jaba00002-0079.pdf 
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