Common Practices used to Establish and Implement Token Economies in Clinical and Instructional Settings: A Survey of BACB Certificants.

Token economies are among the most widely used procedures in behavior analysis and research on token economies has spanned over 80 years. Several textbooks have outlined the essential components of token economies and suggested how they can be trained and implemented in practice. However, procedures evaluated in applied research can vary from how those procedures are implemented in clinical practice. It is conceivable that the way in which token economies are implemented in clinical settings does not resemble the procedures described in research and behavior analytic textbooks. We surveyed 255 board certified behavior analysts and board certified assistant behavior analysts about their commonly used practices when training and implementing token economies with individuals with autism and other neurodevelopmental disorders. Results suggest that certain aspects of token economies in practice often bear only superficial resemblance to how they are described in textbooks. Supplementary Information: The online version contains supplementary material available at 10.1007/s40617-023-00800-5.

An assessment of token value and effectiveness: A replication.

The purpose of the current study was to conduct a systematic replication of Fiske et al. (2015) to extend the behavior-analytic literature on token reinforcement. Specifically, the researchers addressed several of the limitations of Fiske et al. by including specific conditioning procedures, creating a controlled history of reinforcement with the token system, including participants with and without disabilities to extend the generality of the findings, and equating the magnitude of reinforcement across the primary and paired-token conditions. The current study evaluated the reinforcing value of tokens by using progressive-ratio schedules to compare the efficacy of primary reinforcement, paired tokens, and unpaired tokens. The results suggest that paired tokens may function as reinforcers, but they were not as consistently effective as primary reinforcers.

Reduction in X-ray Retake Rate Using the Token Economy Method.

Excessive retakes of X-ray images increase labor and material costs, as well as result in excess radiation exposure for patients and a long waiting time. In this study, we evaluated the effectiveness of the token economy method as a management method for reducing X-ray retake rate among radiology technicians. The results showed a 2.5% reduction in retake rate, indicating the effectiveness of our method. In addition, we suggest that the token-economy-based approach can be applied to other hospital management problems.

Pavlovian learning and conditioned reinforcement.

Conditioned reinforcers are widely used in applied behavior analysis. Basic research evidence reveals that Pavlovian learning plays an important role in the acquisition and efficacy of new conditioned-reinforcer functions. Thus, a better understanding of Pavlovian principles holds the promise of improving the efficacy of conditioned reinforcement in applied research and practice. This paper surveys how (and if) Pavlovian principles are presented in behavior-analytic textbooks; imprecisions and knowledge gaps within contemporary Pavlovian empirical findings are highlighted. Thereafter, six practical principles of Pavlovian conditioning are presented along with empirical support and knowledge gaps that should be filled by applied and translational behavior-analytic researchers. Innovative applications of these principles are outlined for research in language acquisition, token reinforcement, and self-control.

Using an App-Based Token Economy to Increase Engagement in Daily Living and Vocational Tasks with Adults with Developmental Disabilities.

The token economy is an evidence-based practice that improves outcomes across populations, settings, and behaviors. Nonetheless, their complex nature frequently leads to ineffective implementation. In addition, little is known about the extent to which token economies are effective for increasing engagement in adults with disabilities. Therefore, we conducted a multiple probe across participants to evaluate the effectiveness of a token economy using an app (i.e., Class Dojo) to increase engagement with daily living and vocational tasks in adults with disabilities. All participants increased their engagement with tasks following the introduction of the intervention and maintained higher than baseline levels of engagement up to 6 weeks after the intervention ended. Staff members completed an anonymous survey to indicate their perception of the feasibility and effectiveness of the intervention. Social validity results indicated that some staff members found the intervention effective, but time-consuming and challenging.

A Rapid Assessment of Sensitivity to Reward Delays and Classwide Token Economy Savings for School-Aged Children.

Delay discounting tasks measure the relation between reinforcer delay and efficacy. The present study established the association between delay discounting and classroom behavior and introduced a brief measure quantifying sensitivity to reward delays for school-aged children. Study 1 reanalyzed data collected by Reed and Martens (J Appl Behav Anal 44(1):1-18, https://doi.org/10.1901/jaba.2011.44-1, 2011) and found that 1-month delay choices predicted student classroom behavior. Study 2 examined the utility of the 1-month delay indifference point in predicting saving and spending behavior of second-grade students using token economies with two different token production schedules. Collectively, results showed (a) the 1-month delay indifference point predicted classroom behavior, (b) children who discounted less and had greater self-regulation, accrued and saved more tokens, and (c) a variable token production schedule better correlated with discounting than a fixed schedule. Implications are discussed regarding utility of a rapid discounting assessment for applied use.

Uso de la técnica de economía de fichas para incrementar conductas de tratamiento en adultos mayores con sarcopenia / Use of a token economy to increase target behaviors in older people with sarcopenia

La sarcopenia está caracterizada por la baja masa y fuerza muscular en los adultos mayores. La implementación de técnicas de modificación de la conducta como la técnica de economía de fichas (TEF) puede fungir como estrategia para mejorar la adherencia al tratamiento. El objetivo fue evaluar el efecto de la TEF sobre las conductas de tratamiento: realizar la rutina de ejercicio de resistencia, consumir el suplemento de proteína y consumir el suplemento de vitamina D. Se realizó un estudio de caso de múltiples sujetos en ocho adultos mayores con sarcopenia. El estudio estuvo conformado por tres fases: pre-intervención, intervención conductual y post-intervención conductual. Se evaluó la frecuencia de las conductas de tratamiento en las tres fases, además de los cambios en masa y fuerza muscular. El análisis de los datos se realizó por medio de estadística descriptiva. Los resultados mostraron que la frecuencia de las conductas de tratamiento aumentó en el 100% de los participantes en la etapa de intervención conductual al comparar con la fase pre-intervención, valores que no regresaron a cero en la fase post-intervención conductual. El 83.3 % de los participantes dejaron de tener el diagnóstico de sarcopenia con base en los cambios de masa y fuerza muscular.

Sarcopenia is characterized by low muscle mass and strength in older adults. It is caused by decreased physical activity and quality of dietary intake. Therefore, the implementation of behavior modification techniques such as the token economy technique can serve as a strategy to improve treatment. The aim of the current study was to evaluate the effect of the token economy technique on treatment behaviors. A multiple case studies with an ABC-type design was conducted in eight older adults with sarcopenia. The intervention consisted of modification of treatment-related behaviors; in addition, changes in muscle mass and strength were assessed. The results showed that the frequency of target behaviors increased in 100% of the participants in the intervention stage compared to baseline. The frequency of the target behaviors did not return to the obtained baseline compared to the maintenance stage. 83.3% of the participants changed their sarcopenia diagnosis.

Token Economy-Based Hospital Bed Allocation to Mitigate Information Asymmetry: Proof-of-Concept Study Through Simulation Implementation.

BACKGROUND: Hospital bed management is an important resource allocation task in hospital management, but currently, it is a challenging task. However, acquiring an optimal solution is also difficult because intraorganizational information asymmetry exists. Signaling, as defined in the fields of economics, can be used to mitigate this problem. OBJECTIVE: We aimed to develop an assignment process that is based on a token economy as signaling intermediary. METHODS: We implemented a game-like simulation, representing token economy-based bed assignments, in which 3 players act as ward managers of 3 inpatient wards (1 each). As a preliminary evaluation, we recruited 9 nurse managers to play and then participate in a survey about qualitative perceptions for current and proposed methods (7-point Likert scale). We also asked them about preferred rewards for collected tokens. In addition, we quantitatively recorded participant pricing behavior. RESULTS: Participants scored the token economy-method positively in staff satisfaction (3.89 points vs 2.67 points) and patient safety (4.38 points vs 3.50 points) compared to the current method, but they scored the proposed method negatively for managerial rivalry, staff employee development, and benefit for patients. The majority of participants (7 out of 9) listed human resources as the preferred reward for tokens. There were slight associations between workload information and pricing. CONCLUSIONS: Survey results indicate that the proposed method can improve staff satisfaction and patient safety by increasing the decision-making autonomy of staff but may also increase managerial rivalry, as expected from existing criticism for decentralized decision-making. Participant behavior indicated that token-based pricing can act as a signaling intermediary. Given responses related to rewards, a token system that is designed to incorporate human resource allocation is a promising method. Based on aforementioned discussion, we concluded that a token economy-based bed allocation system has the potential to be an optimal method by mitigating information asymmetry.

Using a Token Economy to Treat Escape-Maintained Problem Behavior Without Extinction.

The use of extinction procedures when treating escape-maintained problem behavior can be undesirable and impractical for practitioners to use. To mitigate the risks associated with escape extinction, we explored the effectiveness of a delayed reinforcement token system without the use of extinction in school and home settings to treat escape-maintained problem behavior of students with autism spectrum disorder. In lieu of escape extinction (e.g., blocking), the researchers implemented a 30 s break contingent on problem behaviors and a token (to be exchanged at the end of the session) contingent on compliance. The results of a multiple probe design indicated substantial increases in compliance and reductions in problem behavior for all four participants. These findings suggest that extinction is not necessary to eliminate escape-maintained problem behavior in children with autism.

Independent Contingency and Token Economy at Recess to Reduce Aggression.

School-wide behavior problems can vary significantly from structured to unstructured settings. Often problem behaviors can spike during unstructured times such as lunch and recess and the use of Tier 1 positive behavior interventions and supports (PBIS) can be used to reduce student behavior problems in these settings. Using a token economy as an independent group contingency, this study aimed to reduce student aggression in an elementary school during lunch/recess periods of the day. Students had the opportunity to earn school "dollars" during recess for demonstrating prosocial behaviors in which they were told could be exchanged for incentives at a student store (backup reinforcers). Across all grade levels, student levels of aggression were reduced between 50 and 100% from baseline levels in a 3-month period. However, as effect sizes indicated, only some intervention groups showed significant reduction of aggression. Despite the limitation of access to backup reinforcers, we theorized that the effectiveness of the present intervention was due to socially mediated contingencies among student group members as a result of receiving dollars.

Systematic Review and Meta-Analysis of Token Economy Practices in K-5 Educational Settings, 2000 to 2019.

Token economy systems have been widely used as an evidence-based classroom management strategy to reinforce and improve prosocial responses. While token economies have been widely applied to educational settings, there have been mixed results regarding the effectiveness depending on the classroom type. To better understand the components contributing to the effectiveness, the researchers analyzed 24 token economy studies conducted in general and special education classrooms from kindergarten to fifth grade between 2000 and 2019. Eight token economy components and effect sizes were identified for each study and compared across different classroom types. The results showed that the token economy intervention yielded large effect sizes for both general and special education classroom types. There were differences in the usage of token components including backup reinforcer types, token production rate, and exchange production rate based on classroom types. Implications for future research and practice for educators and clinicians are discussed.

Mechanism Design of Health Care Blockchain System Token Economy: Development Study Based on Simulated Real-World Scenarios.

BACKGROUND: Despite the fact that the adoption rate of electronic health records has increased dramatically among high-income nations, it is still difficult to properly disseminate personal health records. Token economy, through blockchain smart contracts, can better distribute personal health records by providing incentives to patients. However, there have been very few studies regarding the particular factors that should be considered when designing incentive mechanisms in blockchain. OBJECTIVE: The aim of this paper is to provide 2 new mathematical models of token economy in real-world scenarios on health care blockchain platforms. METHODS: First, roles were set for the health care blockchain platform and its token flow. Second, 2 scenarios were introduced: collecting life-log data for an incentive program at a life insurance company to motivate customers to exercise more and recruiting participants for clinical trials of anticancer drugs. In our 2 scenarios, we assumed that there were 3 stakeholders: participants, data recipients (companies), and data providers (health care organizations). We also assumed that the incentives are initially paid out to participants by data recipients, who are focused on minimizing economic and time costs by adapting mechanism design. This concept can be seen as a part of game theory, since the willingness-to-pay of data recipients is important in maintaining the blockchain token economy. In both scenarios, the recruiting company can change the expected recruitment time and number of participants. Suppose a company considers the recruitment time to be more important than the number of participants and rewards. In that case, the company can increase the time weight and adjust cost. When the reward parameter is fixed, the corresponding expected recruitment time can be obtained. Among the reward and time pairs, the pair that minimizes the company's cost was chosen. Finally, the optimized results were compared with the simulations and analyzed accordingly. RESULTS: To minimize the company's costs, reward-time pairs were first collected. It was observed that the expected recruitment time decreased as rewards grew, while the rewards decreased as time cost grew. Therefore, the cost was represented by a convex curve, which made it possible to obtain a minimum-an optimal point-for both scenarios. Through sensitivity analysis, we observed that, as the time weight increased, the optimized reward increased, while the optimized time decreased. Moreover, as the number of participants increased, the optimization reward and time also increased. CONCLUSIONS: In this study, we were able to model the incentive mechanism of blockchain based on a mechanism design that recruits participants through a health care blockchain platform. This study presents a basic approach to incentive modeling in personal health records, demonstrating how health care organizations and funding companies can motivate one another to join the platform.

A Model of Support for Families of Children With Autism Living in the COVID-19 Lockdown: Lessons From Italy.

Italy has been the European country most affected by the COVID-19 pandemic to date and has been in social lockdown for the longest period of time compared to other countries outside China. Almost overnight, Italian behavior analysts were faced with the challenge of setting up remotely whole-family systems aimed at maintaining adaptive skills and low levels of challenging behavior to be carried out solely by caregivers. Given these extraordinary circumstances, the protocols available from the applied behavior-analytic, parent training, and autism literature did not appear to fully meet the needs of parents having to be with their children under extreme levels of stress in a confined space with limited reinforcers for 24 hr a day, 7 days a week. To meet this unprecedented challenge, we developed a dynamic and holistic protocol that extended to the full day and that recognized the need for sustainable intervention delivered solely by parents, who were often looking after more than one child. These practices are presented in this article, together with a discussion of lessons we have learned thus far, which may be useful for behavior analysts working in other regions in which the effects of the pandemic are not yet fully realized. Although somewhat unorthodox, we include some parent comments at the end with the goal of sharing the parent perspective in real time as this pandemic unfolds across the world.

Evaluation of Manualized Instruction to Train Staff to Implement a Token Economy.

All components of behavioral skills training may not be necessary to effectively train staff to implement behavior-analytic technologies with children with disabilities. This study evaluated manualized instruction to train inexperienced staff to implement a token economy with a confederate and collect data on learner responding. A nonconcurrent multiple-baseline design across staff trainees was used to evaluate the effectiveness of manualized instruction to increase the staff trainees' accurate implementation of a token economy. Additionally, a modified general case analysis was conducted to identify potential child behaviors. Multiple-exemplar training of these behaviors was presented in random order during sessions. Following the use of the manualized instruction, staff trainees' accurate implementation of a token economy and data collection on confederate responding increased, the skills generalized from a confederate to a child with autism spectrum disorder, and the skills maintained 1 month following training.

Use of technology in facilitating remote caregiver training for token systems.

The prevalence of autism continues to rise, yet the ability to receive treatment or caregiver training through traditional in-person methods continues to be a precluding factor for many families. Studies have shown that parent training provides benefits to caregivers and children through increased success of interventions, implementation, and generalization of skills. This study evaluated the effect of using technology for remote caregiver training of a token economy for use during routine non-preferred activities. A multiple-baseline design was implemented across two participants, through three phases. Additional surveys and interviews were conducted to evaluate social validity. Results revealed that caregivers acquired necessary skills to implement the fixed interval schedule of reinforcement with token system and participants reported experiencing greater positive interactions with the children. Limitations of this study included no data were collected on the children's behavior, nor were they trained on token economy use. Extraneous variables may have affected the results, such as unplanned household events. Results suggest that remote caregiver training can increase desirable interactions between caregiver and child, improve socially significant behaviors, and extend resources not typically available to all families.

Using a guest- and confederate-delivered token economy to increase employee-guest interactions at a zoo.

The present study used a token economy to promote guest greetings by employees at a zoological facility. Guests and confederate guests delivered tokens to zoo employees for making eye contact from 10 ft (3.05 m) away and verbally greeting guests from 5 ft (1.52 m) away (called a 10-5 interaction) and the tokens were exchangeable for small prizes. An ABAB design was used to evaluate the intervention. Results showed increases of 35.3 and 45.0% in correct employee-guest interactions in each intervention phase compared to baseline, thus suggesting that a guest-delivered token economy is an effective way to improve guest greetings. Limitations of the current study and opportunities for future research are discussed.

An analysis of the value of token reinforcement using a multiple-schedule assessment.

Token systems are widely used in clinical settings, necessitating the development of methods to evaluate the reinforcing value of these systems. In the current paper, we replicated the use of a multiple-schedule reinforcer assessment (MSA; Smaby, MacDonald, Ahearn, & Dube, 2007) to evaluate the components of a token economy system for 4 learners with autism. Token systems had reinforcing value similar to primary reinforcers for 2 of the 4 learners, but resulted in lower rates of responding than primary reinforcers for the other 2 learners. Differentiated responding across learners may warrant variation in clinical recommendations on the use of tokens. The results of this study support formal assessment of token system effectiveness, and the MSA procedure provides an efficient method by which to conduct such assessments.

Does a novel teaching approach work? A Students' perspective.

BACKGROUND: There is always a call for educational reform and further research to improve educational programs. The continuous development of new educational approaches is a work in progress. Educational strategies like team-based learning, flipped classroom, and lottery-based token economy, were used to develop a novel teaching approach. AIM: This study had two major goals. The first goal was to introduce a novel teaching approach in professional healthcare academies. The second goal was to get an in-depth understanding, from the students' perspective, about the benefits and limitations of this new teaching approach. METHOD: The study was conducted using a qualitative, phenomenological research design. Third and fourth-year nursing students completed reflective journals to describe their personal experience with the new teaching approach at the end of the semester. The students' responses were analyzed and coded using Kember's four-category coding schema for reflective writing, to extract themes using thematic analysis. FINDINGS: Seventy-five students completed and returned their reflective journals. The analysis showed various challenges and facilitators/benefits of the students' experiences. The themes that emerged from the analysis were: lack of exposure vs. a sense of achievement; lack of teamwork skills vs. role fulfillment; working with new people vs. conflict resolution; variation vs. collaboration/creativity; time management vs. constructive competition; wasting resources vs. flexibility, and proactivity/active engagement. These themes summarized why the new teaching approach worked and what barriers students faced with the new assembly. CONCLUSION: Results from the current study demonstrated the great potential of the new teaching approach. Recommendations for future research were also discussed.

Token reinforcement: Translational research and application.

The present paper provides an integrative review of research on token reinforcement systems, organized in relation to basic behavioral functions and economic variables. This type of functional taxonomy provides a useful way to organize the literature, bringing order to a wide range of findings across species and settings, and revealing gaps in the research and areas especially ripe for analysis and application. Unlike standard translational research, based on a unidirectional model in which the analysis moves from laboratory to the applied realm, work in the area of token systems is best served by a bidirectional interplay between laboratory and applied research, where applied questions inspire research on basic mechanisms. When based on and contributing to an analysis, applied research on token economies can be on the leading edge of theoretical advances, helping set the scientific research agenda.

Numerical Nudging: Using an Accelerating Score to Enhance Performance.

People often encounter inherently meaningless numbers, such as scores in health apps or video games, that increase as they take actions. This research explored how the pattern of change in such numbers influences performance. We found that the key factor is acceleration-namely, whether the number increases at an increasing velocity. Six experiments in both the lab and the field showed that people performed better on an ongoing task if they were presented with a number that increased at an increasing velocity than if they were not presented with such a number or if they were presented with a number that increased at a decreasing or constant velocity. This acceleration effect occurred regardless of the absolute magnitude or the absolute velocity of the number, and even when the number was not tied to any specific rewards. This research shows the potential of numerical nudging-using inherently meaningless numbers to strategically alter behaviors-and is especially relevant in the present age of digital devices.