Operant Contingencies in Everyday Persistence

The Core Unit of Operant Analysis

An antecedent sets the occasion for a response. The response produces a consequence. This sequence forms the three-term contingency. Operant behavior emerges from such relations. Reinforcement increases the future probability of the response. Punishment decreases it. Skinner identified this unit because it captures environmental interactions without invoking internal states. Consequences shape behavior directly. Antecedents signal when responses pay off. Thus, the contingency explains learning through selection by consequences.

Reinforcement contingencies strengthen responses. Positive reinforcement adds a stimulus after the response. Negative reinforcement removes a stimulus. Both raise response rates. Punishment contingencies weaken responses. Positive punishment adds an aversive stimulus. Negative punishment removes a appetitive stimulus. Effects depend on individual history. A stimulus reinforcing for one person punishes another. Contingencies operate continuously in daily life.

Reinforcement in Action: Coffee Ritual

Morning alarm rings. I drag myself to the kitchen. Brew coffee. Aroma fills the room. First sip delivers warmth and alertness. Behavior of preparing coffee increases. This exemplifies positive reinforcement. The antecedent is the alarm and groggy state. The response is grinding beans, boiling water, pouring. The consequence is the pleasurable taste and caffeine effect. Contingency: alarm (discriminative stimulus) – preparation – coffee consumption. Rate of early rising ties to this outcome. Without coffee, mornings drag.

Negative reinforcement appears in deadline avoidance. Email notification pings about a report due. I open the laptop immediately. Complete the task. Notification stops. Anxiety drops. Behavior of prompt starting persists. Antecedent: the ping and looming deadline. Response: typing and submitting. Consequence: removal of the alert and worry. Thus, escape maintains the habit. Delays would escalate pressure.

Punishment Encounter: Speeding Ticket

Highway stretches empty. Foot presses accelerator. Speedometer climbs past limit. Sirens wail behind. Officer issues ticket. Fine deducts from wallet. Behavior of speeding decreases. This is positive punishment. Antecedent: open road and urge to arrive faster. Response: exceeding 80 mph. Consequence: added fine and lecture. Contingency locks in caution. Future drives stay under limit near that stretch.

Negative punishment hit during college. Borrowed friend’s notes. Forgot to return before exam. Friend withholds future loans. Access to materials vanishes. Behavior of careless borrowing stops. Antecedent: rushed schedule. Response: keeping notes overnight. Consequence: removal of borrowing privilege. Thus, prompt returns become routine.

Schedules and Matching in Maintenance

Coffee preparation follows a fixed-interval schedule in some ways. Weekday mornings demand it at 6 AM. Reward arrives predictably after waking. Scalloped pattern emerges: slow start, rush near time. Weekends shift to variable-ratio. Brew only when craving hits unpredictably. Persistence holds despite delays. Matching law applies across beverages. Time allocated to coffee versus tea matches reinforcement obtained. Stronger brew pulls more effort. Weaker tea gets ignored.

Speeding avoidance ties to variable-ratio punishment. Tickets occur unpredictably. One infraction deters for months. Matching emerges in route choice. Highways with rare patrols receive more speed. Patrolled streets get compliance. Relative punishment rates dictate allocation. Thus, behavior distributes proportionally.

Interplay and Persistence

Reinforcement builds habits. Punishment suppresses alternatives. Coffee ritual endures because positive consequences outweigh occasional burns. Ticket memory fades until another open road tempts. Schedules stretch resistance to extinction. Variable reinforcement proves toughest to break. Matching predicts shifts when options change. New cafe offers better brew. Allocation tilts. Old machine gathers dust.

Negative reinforcement in work avoidance compounds. Deadlines cluster. Prompt responses escape piling aversives. Ratio strain hits during overload. Breaks increase. Punishment from missed promotions reins it back. Contingencies overlap daily. Analysis reveals why habits stick despite intent to change.

Broader Implications from Contingencies

Three-term units scale to complex repertoires. Social interactions follow similar patterns. Smile prompts conversation. Laughter reinforces sharing. Scorn punishes oversharing. Schedules govern relationships. Intermittent praise maintains effort. Constant criticism extinguishes. Matching allocates time across friends based on payoff. Understanding contingencies aids self-modification. Alter antecedents or consequences deliberately. Behavior follows suit.

Cooper, J., Heron, T., & Heward, W. (2020). Applied behavior analysis (3rd ed.). Pearson.

Fisher, W., Piazza, C. & Roane, H. (2021). Handbook of applied behavior analysis. Guilford Press.

Normand, M. P., Dallery, J., & Slanzi, C. M. (2021). Leveraging applied behavior analysis research and practice in the service of public health. Journal of Applied Behavior Analysis, 54(2), 457–483.

Bouton, M. E., & Balleine, B. W. (2019). Prediction and control of operant behavior: What you see is not all there is. Behavior Analysis: Research and Practice, 19(2), 202–212.

Campanaro, A. M., Vladescu, J. C., Kodak, T., DeBar, R. M., & Nippes, K. C. (2020). Comparing skill acquisition under varying onsets of differential reinforcement: A preliminary analysis. Journal of Applied Behavior Analysis, 53(2), 690–706.

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PS560

Begin by describing the three-term contingency, and explain why it is described as the basic unit of analysis for operant behavior. In reviewing the contingencies of reinforcement and punishment, discuss how each set of contingencies has an effect on an individual’s behavior.

Choose a behavior from your own experience that has been reinforced, and identify whether that behavior was positively or negatively reinforced, outlining the specific three term contingency of that operant behavior. Next, choose a behavior from your own experience that has been punished and identify whether that behavior was positively or negatively punished; outline the specific three term contingency of that operant behavior. Finally, in either of those behaviors, discuss how matching law or schedules of reinforcement may contribute to the maintenance of the behavior under certain circumstances.

PS560 APA References

PS560 Course Textbooks

Cooper, J., Heron, T., & Heward, W. (2020). Applied behavior analysis (3rd ed.). Pearson.

Fisher, W., Piazza, C. & Roane, H. (2021). Handbook of applied behavior analysis. The

Guilford Press.

PS560 Readings

Unit 1

Allyon, T., & Michael, J. (1959). The psychiatric nurse as a behavioral engineer. Journal of

The Experimental Analysis of Behavior 2, 323–334.

Bailey, J. S. (2000). A futurist perspective for applied behavior analysis. In J. Austin & J. E. Carr (Eds.), Handbook of applied behavior analysis. Context Press.

Furman, T. M. & Lepper, T. L. (2018). Applied behavior analysis: Definitional

difficulties. Psychological Record, 68(1), 103–105.

Normand, M. P., Dallery, J., & Slanzi, C. M. (2021). Leveraging applied behavior analysis

research and practice in the service of public health. Journal of Applied Behavior Analysis, 54(2), 457–483.

Schwartz, I. S., & Kelly, E. M. (2021). Quality of life for people with disabilities: Why applied behavior analysts should consider this a primary dependent variable. Research & Practice for Persons with Severe Disabilities, 46(3), 159–172.

Storey, K., & Haymes, L. (2017). Case studies in applied behavior analysis for students and adults with disabilities. Charles C Thomas.

Watson, J. B. (1913). Psychology as the behaviorist views it. Psychological Review 20(2),

158–177.

Unit 2

Collins, B. C., Lo, Y., Park, G., & Haughney, K. (2018). Response prompting as an ABA-based

instructional approach for teaching students with disabilities. Teaching Exceptional Children, 50(6), 343–355.

Cowie, S., Gomes-Ng, S., Hopkinson, B., Bai, J. Y. H., & Landon, J. (2020). Stimulus control

depends on the subjective value of the outcome. Journal of the Experimental Analysis of Behavior, 114(2), 216–232.

Hendrickson, J. M., Gable, R. A., & Shores, R. E. (2010). The ecological perspective:

Setting events and behavior. The Pointer, 31(3), 40–44.

Unit 3

Keller, F. S., & Schoenfeld, W. N. (1950). Psychology and the reflex. In Principles of

psychology: A systematic text in the science of behavior (pp. 15–35). Appleton-Century-Crofts.

Keller, F. S., & Schoenfeld, W. N. (1950). Respondent conditioning. In Principles of psychology:

A systematic text in the science of behavior (pp. 15–35). Appleton-Century-Crofts.

Stussi, Y., Ferrero, A., Pourtois, G., & Sander, D. (2019). Achievement motivation modulates

Pavlovian aversive conditioning to goal-relevant stimuli. NPJ Science of Learning, 4, 4.

Unit 4

Baron, A. & Galizio, M. (2005). Positive and negative reinforcement: Should the distinction

be preserved? The Behavior Analyst, 28, 85–98.

Bouton, M. E., & Balleine, B. W. (2019). Prediction and control of operant behavior: What

you see is not all there is. Behavior Analysis: Research and Practice, 19(2), 202–212.

Brewer, A., Li, A., Leon, Y., Pritchard, J., Turner, L., & Richman, D. (2018). Toward a better

basic understanding of operant-respondent interactions: Translational research on phobias. Behavior Analysis: Research and Practice, 18(4), 328–332.

Senuik, H. A., Williams, L. W., Reed, D. D., & Wright, J. W. (2015). An examination of

matching with multiple response alternatives in professional hockey. Behavior Analysis: Research and Practice, 15(3–4), 152–160.

Unit 5

Campanaro, A. M., Vladescu, J. C., Kodak, T., DeBar, R. M., & Nippes, K. C. (2020).

Comparing skill acquisition under varying onsets of differential reinforcement: A preliminary analysis. Journal of Applied Behavior Analysis, 53(2), 690–706.

Johnson, K. A., Vladescu, J. C., Kodak, T., & Sidener, T. M. (2017). An assessment of

differential reinforcement procedures for learners with autism spectrum disorder. Journal of Applied Behavior Analysis, 50(2), 290–303.

May, B. K., & Catrone, R. (2021). Reducing rapid eating in adults with down syndrome: Using

token reinforcement to increase interresponse time between bites. Behavior Analysis: Research and Practice, 21(3), 273–281.

Unit 6

Carbone, V. J. (2019). The motivational and discriminative functions of motivating operations.

Journal of the Experimental Analysis of Behavior, 112(1), 10–14.

Edwards, T. L., Lotfizadeh, A. D., & Poling, A. (2019). Motivating operations and stimulus

control. Journal of the Experimental Analysis of Behavior, 112(1), 1–9.

Michael, J. (1993). Establishing operations. The Behavior Analyst, 16, 191–206.

van Haaren, F. (2020). Extinction revisited: Implications for application. Behavior Analysis:

Research and Practice, 20(1), 36–42.

Wulfert, E. (2013). Rule-governed behavior. Salem Press Encyclopedia of Health.

Unit 7

Lattal, K. A. (2013). The five pillars of the experimental analysis of behavior. In Madden, G.,

Dube, W. V., Hackenberg, T. D., Hanley, G. P., & Lattal, K. A. (Eds.). APA handbook of behavior analysis, Volume 1: Methods and principles (pp. 33–63). American Psychological Association.

Unit 8

Fryling, M. (2017). The functional independence of Skinner’s verbal operants: Conceptual

and applied implications. Behavioral Interventions 32, 70–78.

LaFrance, D. L., & Tarbox, J. (2020). The importance of multiple exemplar instruction in the

establishment of novel verbal behavior. Journal of Applied Behavior Analysis, 53(1), 10–24.

Miguel, C. F. (2018). Problem-solving, bidirectional naming, and the development of verbal

repertoires. Behavior Analysis: Research and Practice, 18(4), 340–353.

Unit 9

Barens-Holmes, D., Finn, M., McEnteggart, C., & Barnes-Holmes, Y. (2018). Derived stimulus relations and their role in a behavior-analytic account of human language and cognition. Perspectives on Behavior Science, 41(1), 155–173.

Belisle, J., Paliliunas, D., Lauer, T., Giamanco, A., Lee, B., & Sickman, E. (2020). Derived

relational responding and transformations of function in children: A review of applied behavior-analytic journals. Analysis of Verbal Behavior, 36(1), 115–145.

Ming, S., Moran, L., & Stewart, I. (2014). Derived relational responding: Applications and future directions for teaching individuals with autism spectrum disorders. European Journal of Behavior Analysis.

Perez, W. F., de Azevedo, S. P., Gomes, C. T., & Vichi, C. (2021). Equivalence relations and

the contextual control of multiple derived stimulus functions. Journal of the Experimental Analysis of Behavior, 115(1), 405–420.

Törneke, N. (2010). Derived relational responding as the fundamental element in human

language. In Learning RFT: An introduction to relational frame theory and its clinical application (pp. 59–89). Context Press.

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The Three-Term Contingency and the Dynamics of Operant Behavior

Understanding the Three-Term Contingency as a Behavioral Unit

Operant behavior rests on a simple yet powerful framework: the three-term contingency. It is written as Antecedent–Behavior–Consequence (A–B–C). Each term captures a conditional relationship that explains why a behavior occurs and how it changes. The antecedent sets the stage, the behavior represents the measurable action, and the consequence determines whether that behavior will appear again. Skinner’s experimental work made this sequence the cornerstone of behavioral analysis, offering a concrete unit of study rather than abstract inference (Cooper, Heron, and Heward, 2020). The importance of the contingency lies in its precision: it defines behavior as a function of its environment, not as a projection of inner states. When the relationship among the three elements becomes predictable, behavior becomes lawful and modifiable. This unit remains essential because it allows both experimental and applied behavior analysts to identify what triggers and maintains actions across settings, populations, and reinforcement systems.

Applied work has confirmed that this tripartite relation is not static. It adjusts dynamically as environmental contingencies shift. For instance, Cowie et al. (2020) observed that stimulus control depends on how individuals value outcomes rather than on mere sensory features. Consequently, the contingency model evolves as motivational and contextual variables shape the predictive value of the antecedent and consequence. To study operant behavior without the three-term contingency would be to overlook the functional interplay that sustains human and animal learning.

Reinforcement and Punishment as Behavioral Modifiers

Reinforcement and punishment define how consequences affect future actions. Reinforcement increases the likelihood of a behavior, while punishment decreases it. Each may occur in positive or negative forms, depending on whether something is added or removed. Reinforcement is not a moral term; it describes a statistical outcome: if behavior strengthens, reinforcement occurred. Baron and Galizio (2005) argued that the distinction between positive and negative reinforcement is sometimes overstated, yet it remains analytically useful for isolating environmental influences. Positive reinforcement, such as praise after effort, adds a desirable event; negative reinforcement, such as relief from noise after closing a window, removes an aversive condition. Both change future behavior through contingency regularity.

Punishment operates similarly but in the opposite direction. Positive punishment introduces an aversive stimulus following an action, while negative punishment removes a valued one. The distinction is not trivial, because their effects on behavior differ in stability and side effects. Bouton and Balleine (2019) emphasized that punishment rarely eliminates a behavior entirely; it suppresses it while reinforcement histories remain intact beneath the surface. The persistence of extinguished behavior after punishment reveals that control is often partial and context-dependent. Consequently, understanding the three-term contingency allows analysts to predict when reinforcement or punishment will have enduring effects.

Behavior Reinforced Through Positive Contingency

During graduate study, maintaining consistent early-morning writing was initially difficult. Over time, the behavior stabilized through positive reinforcement. The antecedent was the quiet environment before others were awake. The behavior was sitting to write at a desk each morning. The consequence was the satisfaction of measurable progress and the self-administered reward of breakfast only after completing a section. The reinforcement was positive because a preferred outcome—the meal and the sense of achievement—was added following the behavior. The three-term contingency was: quiet morning (antecedent) → writing (behavior) → breakfast and progress satisfaction (consequence). As the contingency repeated, writing behavior became more automatic and required less internal prompting.

Research supports how consistent positive reinforcement strengthens complex, sustained behaviors. Campanaro et al. (2020) demonstrated that differential reinforcement procedures accelerate skill acquisition even under varying onset times of reinforcement. Reinforcement schedules that provide consistent, immediate rewards for desirable responses generate durable habits. The writing example mirrors this principle: short-term reinforcement consolidated long-term self-regulation. When reinforcement was delayed or removed, productivity decreased, suggesting the direct influence of consequence timing within the three-term model.

Behavior Suppressed Through Negative Punishment

A contrasting case involved excessive use of social media during working hours. The antecedent was a low-effort moment during study. The behavior was checking a phone. The consequence, imposed deliberately, was self-restriction: losing access to streaming media for the evening if social apps were used during scheduled work. This formed a negative punishment contingency because something desirable—relaxation time—was removed after the target behavior. The sequence was: study time (antecedent) → phone checking (behavior) → loss of evening leisure (consequence). Over several weeks, phone use during work declined sharply.

Empirical studies show that negative punishment can be effective when implemented with consistency and immediate feedback. Johnson et al. (2017) noted that differential reinforcement and token loss procedures in learners with autism functioned as mild negative punishment systems that reduced unwanted responses without harmful emotional fallout. The crucial condition is predictability. If the consequence is applied irregularly, suppression weakens. In my own case, lapses in enforcing the restriction reintroduced the behavior, aligning with the contingency’s predictive nature. The analysis suggests that punishment contingencies shape not only reduction of behavior but also the formation of avoidance patterns.

The Role of Matching Law and Reinforcement Schedules

Behavioral persistence under reinforcement depends not only on single contingencies but also on the distribution of rewards across alternatives. Matching law explains that organisms allocate behavior proportionally to the rate of reinforcement available for each option. Senuik et al. (2015) observed that professional athletes distributed effort among alternatives according to reinforcement density, supporting the generality of this law beyond laboratory conditions. Applying this to daily writing, competing behaviors—checking messages, making coffee, browsing articles—each carried distinct reinforcement frequencies. The steady output of reinforcement from morning writing outweighed other activities only when feedback was immediate and consistent. As reinforcement ratios shifted, so did the distribution of attention.

Schedules of reinforcement also determine response maintenance. Variable ratio schedules, where reinforcement occurs unpredictably, often produce high and stable response rates. In contrast, fixed interval schedules lead to pauses followed by rapid responding near reinforcement delivery. May and Catrone (2021) found that token systems employing variable intervals sustained engagement better than fixed ones among adults with developmental disabilities. My writing routine reflected a fixed ratio: reinforcement occurred after each completed section. Predictably, effort slowed when deadlines felt distant. Adjusting reinforcement to intermittent acknowledgment—reading feedback or sharing drafts—maintained motivation, illustrating how schedule design shapes response consistency.

Integrating Contingencies with Motivation and Context

No behavior occurs in isolation from motivation. Establishing operations alter the reinforcing value of consequences. Michael (1993) introduced this concept to explain why identical contingencies yield different outcomes depending on context. Hunger increases food’s reinforcing value; satiation diminishes it. In the earlier writing example, motivation varied with academic pressure, sleep quality, or external deadlines. When intrinsic motivation aligned with reinforcement conditions, behavior strength rose. Carbone (2019) extended this by distinguishing the motivational and discriminative functions of environmental events: one determines the likelihood of response, the other signals when reinforcement is available. Together, these shape moment-to-moment variations in operant strength.

The effectiveness of punishment also fluctuates with motivational conditions. A person under stress may engage in punished behaviors if alternative reinforcement sources are lacking. Bouton and Balleine (2019) argued that environmental predictability moderates punishment outcomes because behavior is sensitive to both the availability and reliability of consequences. Therefore, analysts who modify behavior without addressing motivational context risk temporary change rather than lasting adaptation.

Implications for Behavioral Analysis and Intervention

Recognizing the three-term contingency as the fundamental analytical unit provides a structured path for intervention. Behavioral engineering, as Ayllon and Michael (1959) described, involves designing environments where desired contingencies dominate. Every classroom management plan, therapy session, or workplace incentive system rests on the same logic. Reinforcement builds skill repertoires; punishment suppresses interference. Yet the subtleties of timing, magnitude, and contextual fit determine outcomes. Fryling (2017) highlighted that even verbal behavior—complex linguistic acts—follows operant contingencies, reaffirming the model’s explanatory breadth.

The matching law’s contribution lies in its ecological realism. Behavior distributes across options that compete for reinforcement. Analysts and practitioners benefit from acknowledging this proportionality instead of assuming single-contingency dominance. Whether addressing academic habits or maladaptive patterns, one must examine the balance of reinforcement rates among available choices. In everyday practice, this means altering not just consequences for one behavior but the entire network of concurrent contingencies that surround it.

Conclusion

The three-term contingency remains the central analytical unit of operant behavior because it captures the functional relation between environment and action. Reinforcement and punishment, as distinct but complementary processes, reveal how behavior changes through experience. Personal examples of reinforced writing and punished distraction illustrate that these processes are not abstractions; they structure daily learning. Matching law and reinforcement schedules explain why some behaviors persist despite competing alternatives, grounding motivation in quantifiable contingencies rather than willpower. Contemporary research continues to refine these ideas, linking them to neurobehavioral evidence and applied outcomes. Behavior analysis thrives not through theoretical expansion but through empirical clarity: every measurable change has an environmental condition that explains it.

References

Baron, A., & Galizio, M. (2005). Positive and negative reinforcement: Should the distinction be preserved? The Behavior Analyst, 28(1), 85–98.
Bouton, M. E., & Balleine, B. W. (2019). Prediction and control of operant behavior: What you see is not all there is. Behavior Analysis: Research and Practice, 19(2), 202–212.
Campanaro, A. M., Vladescu, J. C., Kodak, T., DeBar, R. M., & Nippes, K. C. (2020). Comparing skill acquisition under varying onsets of differential reinforcement. Journal of Applied Behavior Analysis, 53(2), 690–706.
Carbone, V. J. (2019). The motivational and discriminative functions of motivating operations. Journal of the Experimental Analysis of Behavior, 112(1), 10–14.
Senuik, H. A., Williams, L. W., Reed, D. D., & Wright, J. W. (2015). An examination of matching with multiple response alternatives in professional hockey. Behavior Analysis: Research and Practice, 15(3–4), 152–160.

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