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Reinforcement Theory

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Do you remember back in elementary school, when you received stickers and smiley faces on your worksheets? Or maybe you were occasionally chosen for class monitor. It always made you feel a warm glow, like you were doing something right. On the other hand, the feeling of receiving a timeout or missing recess was dreadful.

These various rewards and punishments are all examples of reinforcement theory at work. Though we can remember examples all the way back from elementary school, reinforcement theory still influences our lives every day.

Put simply, reinforcement theory suggests that a behavior can be strengthened when good events follow it, and reduced when undesirable events follow it. It relies on the idea that behavior is influenced by its consequences. For instance, when action A results in a desirable outcome, one is more likely to do action A; when action B results in an unpleasant outcome, one is less likely to do action B. You’re more likely to study for your spelling test after getting your teacher’s praise; you’re less likely to pull your friend’s hair after getting a stern lecture.

Reinforcement theory is a framework, also known as operant conditioning, detailed in the chart below:

Reinforcement aims to encourage a behavior, whereas punishment aims to reduce a behavior. Both reinforcement and punishment can be positive or negative. A positive stimulus entails adding desirable effects, while negative entails removing undesirable effects of a behavior.

I think, as much as people moan at things like award ceremonies, it gives people role models. It provides real positive reinforcement that you can be who you are and still massively achieve. – Jack Monroe

Behaviorism : The systematic study of external behavior

Operant: Behavior performed by an individual as a response

Reinforcement: Encouragement of a behavior

Punishment: Discouragement of a behavior

Negative: Removing a behavior’s consequences

Positive: Adding consequences to a behavior

Earlier developments in the field of conditioning focused on simply the association between stimuli and the influence it has on involuntary responses. You likely know Pavlov’s dogs, who started to salivate when they heard the sound of his assistant’s footsteps, long before the food was in front of them. This became known as classical conditioning: a stimulus A and a resulting response, such as food and salivation, becomes associated with a different, neutral stimulus, such as the sound of the assistant approach. B becomes associated with A over time, and as a result, prompts the same response as A. Eventually, the dogs learn that approaching footsteps means food, and salivate over the footsteps.

Classical conditioning was developed during a period of psychology that was primarily concerned about an individual’s internal needs and motivations. Maslow and Herzberg completed related work during this period.

For behaviorists, the psychoanalytical approach was dissatisfying because there were no external, observable phenomena that allowed its techniques to be verified and tested. In the early 1900s, Edward Thorndike concretized the Law of Effect, suggesting that individuals are more likely to perform actions that have satisfying rewards. This marked a significant outward shift in behaviorism; subsequent research began examining the external effects of an action and how they influence choices, as opposed to theorizing how internal responses were influenced by past events. More specifically, Thorndike proposed that if the link between an action and the satisfying effect is strengthened, the action will become more likely in the future.

F. Skinner further differentiated between the means in which stimulus and action affect behavior, deviating even more from the early studies in classical conditioning. As per Skinner’s framework, Pavlov’s work studied stimuli. In the above example, stimulus B (footsteps) becomes a conditioned stimulus that generates the same involuntary action (salivating). Skinner studied how the action itself is conditioned through its own effects rather than other stimuli. He termed this action “operant” instead of “response” to highlight that the action was not just a response to a stimulus, but a voluntary action that is tangibly linked to its effects. 1 This led to his monumental framework: operant conditioning. Skinner, as well as the behaviorist paradigm, would come to define a key evolutionary step in psychology, as reinforcement theory began to move psychology away from it’s psychoanalytic roots and closer towards the empirical, scientific paradigm that it is today.

The story of reinforcement is the result of trying to understand the interplay between an action and its consequences, specifically how the probabilistic strengthening of this link operates.

Ivan Pavlov

A Russian physiologist known for his early research on classical conditioning. Pavlov did significant research in behaviorism – the systematic study of behaviors – and conditioning. Classical conditioning is notably different from operant conditioning: classical conditioning deals with involuntary behavior, whereas operant conditioning involves modifying voluntary behavior. Nevertheless, Pavlov was a major influence to all behaviorists, including practitioners of operant conditioning, like Skinner.

Edward Thorndike

An American psychologist and pioneer in the field of behaviorism. Thorndike developed a more empirically driven approach in assessing behavior. He formulated the Law of Effect, which stated that an action followed by a desirable effect strengthens the link between that action and the following effect, thereby making the action more likely to recur. While this may seem obvious to us now, Thorndike’s law of effect set the stage for empirical testing of reinforcement to occur.

Burrhus Frederick Skinner

An American psychologist best known for his seminal work on behavior, B.F. Skinner is known as the father of operant conditioning. He believed that people’s behavior is a result of how they have been conditioned by the consequences of their past behavior.

Consequences

Reinforcement theory can be a powerful way to promote positive behavior and is thus important to any team or organization. It is often used to achieve a team’s objectives, such as enhancing productivity or improving communication. Another way to visualize reinforcement theory is as a two-dimensional table, as shown below with examples in each quadrant:

Reinforcement can also act as an enhancer for other behavioral techniques. For example, antecedents, such as warnings or providing information in an attempt to encourage certain behavior, are insubstantial on their own. However, when used in conjunction with reinforcing consequences, they are significantly more effective. 2 Thus when addressing workforce problems, modifying the consequences of actions can serve to enhance verbal suggestions.

Schedules of conditioning:

When building his theory of operant conditioning, Skinner found that his conditioning’s effectiveness was significantly altered by the schedule it was employed in. This led Skinner to develop a key concept in behaviorism, which is now known as schedules of reinforcement. The theory boils down to a simple, practical conclusion: to assure behavioral change, some reinforcement schedules may be better suited than others for a particular problem.

A reinforcement schedule can be continuous, meaning reinforcement will occur every time the target behavior happens. Another option is having reinforcement occur in fixed intervals, which are typically based on a certain period of time elapsing or after the behavior has been performed a certain number of times. Finally, a reinforcement schedule can reinforce behavior at variable intervals. In this case, the time or occurrences of the behavior are not fixed. In essence, an individual is rewarded on a random basis, regardless of behavior.

Controversies

Skinner was averse to examinations of the mind, discussions of goals, and internal motivations. 3 This perspective itself is a major point of disagreement in the psychology community, since it eliminates a whole angle of looking at behavior.

Some academics and studies have taken issue with the perceived efficacy of reinforcement theory. As early as 1994, it has been argued that behavioral therapists are increasingly adopting procedures supported by reinforcement theory that lack tangible empirical evidence of working in a clinical setting. 4 They point out that there have even been instances in which such procedures have had a counterproductive effect, suggesting that these techniques “may actually reduce positive behaviors and increase resistance to change.”

For example, Dan Pink suggests that having incentive-driven policies is effective when the task at hand is clear cut with straightforward rules, but otherwise it “ dulls thinking and blocks creativity.” In contrast, intrinsic motivation, feeling purposeful, and having autonomy may be better factors in increasing desirable behaviors. Strategies to encourage these behaviors could thus be more effective for complex tasks. 5

Finally, reinforcement theory can inadvertently influence our judgment, such as when we make decisions based on past experiences and discard new or contradicting information in doing so.

Case Studies

Seat belt reminders in cars.

While seat belts in cars have been mandatory since 1960, it was initially difficult to ensure that the mandate was being followed. 6 After years of figuring out the best way to enforce the rule, the seat belt reminder sound found its way into most cars. When the driver and passengers have not buckled up and the car starts moving, the car beeps loudly and relentlessly, until the seat belts are finally clicked. This annoying beeper is a classic example of negative reinforcement: after the target action is performed, the negative stimuli is removed. To avoid this annoyance in the future,we’re encouraged to put on the seat belt as early as possible next time we get in the car.

Examining the effect of positive reinforcement and punishment on cigarette use

When it comes to smoking, our experience with our first cigarette often dictates if we develop a dependence later on. In a 2018 study, researchers surveyed respondents on their feelings, reactions, and symptoms during the first few times they smoked. It was found that if our first cigarette was a positive experience, we tended to get hooked later on. This finding strongly suggests that reinforcement could be a key driver of habitual smoking, as we have come to associate it with positive feelings. On the other hand, they found that an unpleasant first experience, which acts as a positive punishment, did not significantly decrease the smoking frequency later in life. Accordingly, positive initiation experiences could predict cigarette use with some accuracy, whereas negative experiences could not. 7

About the Authors

Dan is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. Dan has a background in organizational decision making, with a BComm in Decision & Information Systems from McGill University. He has worked on enterprise-level behavioral architecture at TD Securities and BMO Capital Markets, where he advised management on the implementation of systems processing billions of dollars per week. Driven by an appetite for the latest in technology, Dan created a course on business intelligence and lectured at McGill University, and has applied behavioral science to topics such as augmented and virtual reality.

Dr. Sekoul Krastev

Sekoul is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. A decision scientist with a PhD in Decision Neuroscience from McGill University, Sekoul's work has been featured in peer-reviewed journals and has been presented at conferences around the world. Sekoul previously advised management on innovation and engagement strategy at The Boston Consulting Group as well as on online media strategy at Google. He has a deep interest in the applications of behavioral science to new technology and has published on these topics in places such as the Huffington Post and Strategy & Business.

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Skinner’s Box Experiment (Behaviorism Study)

We receive rewards and punishments for many behaviors. More importantly, once we experience that reward or punishment, we are likely to perform (or not perform) that behavior again in anticipation of the result.

Psychologists in the late 1800s and early 1900s believed that rewards and punishments were crucial to shaping and encouraging voluntary behavior. But they needed a way to test it. And they needed a name for how rewards and punishments shaped voluntary behaviors. Along came Burrhus Frederic Skinner , the creator of Skinner's Box, and the rest is history.

What Is Skinner's Box?

The "Skinner box" is a setup used in animal experiments. An animal is isolated in a box equipped with levers or other devices in this environment. The animal learns that pressing a lever or displaying specific behaviors can lead to rewards or punishments.

This setup was crucial for behavioral psychologist B.F. Skinner developed his theories on operant conditioning. It also aided in understanding the concept of reinforcement schedules.

Here, "schedules" refer to the timing and frequency of rewards or punishments, which play a key role in shaping behavior. Skinner's research showed how different schedules impact how animals learn and respond to stimuli.

Who is B.F. Skinner?

Burrhus Frederic Skinner, also known as B.F. Skinner is considered the “father of Operant Conditioning.” His experiments, conducted in what is known as “Skinner’s box,” are some of the most well-known experiments in psychology. They helped shape the ideas of operant conditioning in behaviorism.

Law of Effect (Thorndike vs. Skinner)

At the time, classical conditioning was the top theory in behaviorism. However, Skinner knew that research showed that voluntary behaviors could be part of the conditioning process. In the late 1800s, a psychologist named Edward Thorndike wrote about “The Law of Effect.” He said, “Responses that produce a satisfying effect in a particular situation become more likely to occur again in that situation, and responses that produce a discomforting effect become less likely to occur again in that situation.”

Thorndike tested out The Law of Effect with a box of his own. The box contained a maze and a lever. He placed a cat inside the box and a fish outside the box. He then recorded how the cats got out of the box and ate the fish.

Thorndike noticed that the cats would explore the maze and eventually found the lever. The level would let them out of the box, leading them to the fish faster. Once discovering this, the cats were more likely to use the lever when they wanted to get fish.

Skinner took this idea and ran with it. We call the box where animal experiments are performed "Skinner's box."

Why Do We Call This Box the "Skinner Box?"

Edward Thorndike used a box to train animals to perform behaviors for rewards. Later, psychologists like Martin Seligman used this apparatus to observe "learned helplessness." So why is this setup called a "Skinner Box?" Skinner not only used Skinner box experiments to show the existence of operant conditioning, but he also showed schedules in which operant conditioning was more or less effective, depending on your goals. And that is why he is called The Father of Operant Conditioning.

How Skinner's Box Worked

Inspired by Thorndike, Skinner created a box to test his theory of Operant Conditioning. (This box is also known as an “operant conditioning chamber.”)

The box was typically very simple. Skinner would place the rats in a Skinner box with neutral stimulants (that produced neither reinforcement nor punishment) and a lever that would dispense food. As the rats started to explore the box, they would stumble upon the level, activate it, and get food. Skinner observed that they were likely to engage in this behavior again, anticipating food. In some boxes, punishments would also be administered. Martin Seligman's learned helplessness experiments are a great example of using punishments to observe or shape an animal's behavior. Skinner usually worked with animals like rats or pigeons. And he took his research beyond what Thorndike did. He looked at how reinforcements and schedules of reinforcement would influence behavior.

About Reinforcements

Reinforcements are the rewards that satisfy your needs. The fish that cats received outside of Thorndike’s box was positive reinforcement. In Skinner box experiments, pigeons or rats also received food. But positive reinforcements can be anything added after a behavior is performed: money, praise, candy, you name it. Operant conditioning certainly becomes more complicated when it comes to human reinforcements.

Positive vs. Negative Reinforcements

Skinner also looked at negative reinforcements. Whereas positive reinforcements are given to subjects, negative reinforcements are rewards in the form of things taken away from subjects. In some experiments in the Skinner box, he would send an electric current through the box that would shock the rats. If the rats pushed the lever, the shocks would stop. The removal of that terrible pain was a negative reinforcement. The rats still sought the reinforcement but were not gaining anything when the shocks ended. Skinner saw that the rats quickly learned to turn off the shocks by pushing the lever.

About Punishments

Skinner's Box also experimented with positive or negative punishments, in which harmful or unsatisfying things were taken away or given due to "bad behavior." For now, let's focus on the schedules of reinforcement.

Schedules of Reinforcement

We know that not every behavior has the same reinforcement every single time. Think about tipping as a rideshare driver or a barista at a coffee shop. You may have a string of customers who tip you generously after conversing with them. At this point, you’re likely to converse with your next customer. But what happens if they don’t tip you after you have a conversation with them? What happens if you stay silent for one ride and get a big tip?

Psychologists like Skinner wanted to know how quickly someone makes a behavior a habit after receiving reinforcement. Aka, how many trips will it take for you to converse with passengers every time? They also wanted to know how fast a subject would stop conversing with passengers if you stopped getting tips. If the rat pulls the lever and doesn't get food, will they stop pulling the lever altogether?

Skinner attempted to answer these questions by looking at different schedules of reinforcement. He would offer positive reinforcements on different schedules, like offering it every time the behavior was performed (continuous reinforcement) or at random (variable ratio reinforcement.) Based on his experiments, he would measure the following:

Response rate (how quickly the behavior was performed)
Extinction rate (how quickly the behavior would stop)

He found that there are multiple schedules of reinforcement, and they all yield different results. These schedules explain why your dog may not be responding to the treats you sometimes give him or why gambling can be so addictive. Not all of these schedules are possible, and that's okay, too.

Continuous Reinforcement

If you reinforce a behavior repeatedly, the response rate is medium, and the extinction rate is fast. The behavior will be performed only when reinforcement is needed. As soon as you stop reinforcing a behavior on this schedule, the behavior will not be performed.

Fixed-Ratio Reinforcement

Let’s say you reinforce the behavior every fourth or fifth time. The response rate is fast, and the extinction rate is medium. The behavior will be performed quickly to reach the reinforcement.

Fixed-Interval Reinforcement

In the above cases, the reinforcement was given immediately after the behavior was performed. But what if the reinforcement was given at a fixed interval, provided that the behavior was performed at some point? Skinner found that the response rate is medium, and the extinction rate is medium.

Variable-Ratio Reinforcement

Here's how gambling becomes so unpredictable and addictive. In gambling, you experience occasional wins, but you often face losses. This uncertainty keeps you hooked, not knowing when the next big win, or dopamine hit, will come. The behavior gets reinforced randomly. When gambling, your response is quick, but it takes a long time to stop wanting to gamble. This randomness is a key reason why gambling is highly addictive.

Variable-Interval Reinforcement

Last, the reinforcement is given out at random intervals, provided that the behavior is performed. Health inspectors or secret shoppers are commonly used examples of variable-interval reinforcement. The reinforcement could be administered five minutes after the behavior is performed or seven hours after the behavior is performed. Skinner found that the response rate for this schedule is fast, and the extinction rate is slow.

Skinner's Box and Pigeon Pilots in World War II

Yes, you read that right. Skinner's work with pigeons and other animals in Skinner's box had real-life effects. After some time training pigeons in his boxes, B.F. Skinner got an idea. Pigeons were easy to train. They can see very well as they fly through the sky. They're also quite calm creatures and don't panic in intense situations. Their skills could be applied to the war that was raging on around him.

B.F. Skinner decided to create a missile that pigeons would operate. That's right. The U.S. military was having trouble accurately targeting missiles, and B.F. Skinner believed pigeons could help. He believed he could train the pigeons to recognize a target and peck when they saw it. As the pigeons pecked, Skinner's specially designed cockpit would navigate appropriately. Pigeons could be pilots in World War II missions, fighting Nazi Germany.

When Skinner proposed this idea to the military, he was met with skepticism. Yet, he received $25,000 to start his work on "Project Pigeon." The device worked! Operant conditioning trained pigeons to navigate missiles appropriately and hit their targets. Unfortunately, there was one problem. The mission killed the pigeons once the missiles were dropped. It would require a lot of pigeons! The military eventually passed on the project, but cockpit prototypes are on display at the American History Museum. Pretty cool, huh?

Examples of Operant Conditioning in Everyday Life

Not every example of operant conditioning has to end in dropping missiles. Nor does it have to happen in a box in a laboratory! You might find that you have used operant conditioning on yourself, a pet, or a child whose behavior changes with rewards and punishments. These operant conditioning examples will look into what this process can do for behavior and personality.

Hot Stove: If you put your hand on a hot stove, you will get burned. More importantly, you are very unlikely to put your hand on that hot stove again. Even though no one has made that stove hot as a punishment, the process still works.

Tips: If you converse with a passenger while driving for Uber, you might get an extra tip at the end of your ride. That's certainly a great reward! You will likely keep conversing with passengers as you drive for Uber. The same type of behavior applies to any service worker who gets tips!

Training a Dog: If your dog sits when you say “sit,” you might treat him. More importantly, they are likely to sit when you say, “sit.” (This is a form of variable-ratio reinforcement. Likely, you only treat your dog 50-90% of the time they sit. If you gave a dog a treat every time they sat, they probably wouldn't have room for breakfast or dinner!)

Operant Conditioning Is Everywhere!

We see operant conditioning training us everywhere, intentionally or unintentionally! Game makers and app developers design their products based on the "rewards" our brains feel when seeing notifications or checking into the app. Schoolteachers use rewards to control their unruly classes. Dog training doesn't always look different from training your child to do chores. We know why this happens, thanks to experiments like the ones performed in Skinner's box.

Operant Conditioning (Examples + Research)
Edward Thorndike (Psychologist Biography)
Schedules of Reinforcement (Examples)
B.F. Skinner (Psychologist Biography)
Fixed Ratio Reinforcement Schedule (Examples)

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Operant Conditioning: What It Is, How It Works, and Examples

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

Operant conditioning, or instrumental conditioning, is a theory of learning where behavior is influenced by its consequences. Behavior that is reinforced (rewarded) will likely be repeated, and behavior that is punished will occur less frequently.

By the 1920s, John B. Watson had left academic psychology, and other behaviorists were becoming influential, proposing new forms of learning other than classical conditioning . Perhaps the most important of these was Burrhus Frederic Skinner. Although, for obvious reasons, he is more commonly known as B.F. Skinner.

Skinner’s views were slightly less extreme than Watson’s (1913). Skinner believed that we do have such a thing as a mind, but that it is simply more productive to study observable behavior rather than internal mental events.

The work of Skinner was rooted in the view that classical conditioning was far too simplistic to be a complete explanation of complex human behavior. He believed that the best way to understand behavior is to look at the causes of an action and its consequences. He called this approach operant conditioning.

How It Works

Skinner is regarded as the father of Operant Conditioning, but his work was based on Thorndike’s (1898) Law of Effect . According to this principle, behavior that is followed by pleasant consequences is likely to be repeated, and behavior followed by unpleasant consequences is less likely to be repeated.

Skinner introduced a new term into the Law of Effect – Reinforcement. Behavior that is reinforced tends to be repeated (i.e., strengthened); behavior that is not reinforced tends to die out or be extinguished (i.e., weakened).

Skinner (1948) studied operant conditioning by conducting experiments using animals which he placed in a “ Skinner Box ” which was similar to Thorndike’s puzzle box.

Skinner box or operant conditioning chamber experiment outline diagram. Labeled educational laboratory apparatus structure for mouse or rat experiment to understand animal behavior vector illustration

A Skinner box, also known as an operant conditioning chamber, is a device used to objectively record an animal’s behavior in a compressed time frame. An animal can be rewarded or punished for engaging in certain behaviors, such as lever pressing (for rats) or key pecking (for pigeons).

Skinner identified three types of responses, or operant, that can follow behavior.

Neutral operants : responses from the environment that neither increase nor decrease the probability of a behavior being repeated.
Reinforcers : Responses from the environment that increase the probability of a behavior being repeated. Reinforcers can be either positive or negative.
Punishers : Responses from the environment that decrease the likelihood of a behavior being repeated. Punishment weakens behavior.

We can all think of examples of how our own behavior has been affected by reinforcers and punishers. As a child, you probably tried out a number of behaviors and learned from their consequences.

For example, when you were younger, if you tried smoking at school, and the chief consequence was that you got in with the crowd you always wanted to hang out with, you would have been positively reinforced (i.e., rewarded) and would be likely to repeat the behavior.

If, however, the main consequence was that you were caught, caned, suspended from school, and your parents became involved, you would most certainly have been punished, and you would consequently be much less likely to smoke now.

Positive Reinforcement

Positive reinforcement is a term described by B. F. Skinner in his theory of operant conditioning. In positive reinforcement, a response or behavior is strengthened by rewards, leading to the repetition of desired behavior. The reward is a reinforcing stimulus.

Primary reinforcers are stimuli that are naturally reinforcing because they are not learned and directly satisfy a need, such as food or water.

Secondary reinforcers are stimuli that are reinforced through their association with a primary reinforcer, such as money, school grades. They do not directly satisfy an innate need but may be the means. So a secondary reinforcer can be just as powerful a motivator as a primary reinforcer.

Skinner showed how positive reinforcement worked by placing a hungry rat in his Skinner box. The box contained a lever on the side, and as the rat moved about the box, it would accidentally knock the lever. Immediately it did so that a food pellet would drop into a container next to the lever.

The rats quickly learned to go straight to the lever after being put in the box a few times. The consequence of receiving food, if they pressed the lever, ensured that they would repeat the action again and again.

Positive reinforcement strengthens a behavior by providing a consequence an individual finds rewarding. For example, if your teacher gives you £5 each time you complete your homework (i.e., a reward), you will be more likely to repeat this behavior in the future, thus strengthening the behavior of completing your homework.

The Premack principle is a form of positive reinforcement in operant conditioning. It suggests using a preferred activity (high-probability behavior) as a reward for completing a less preferred one (low-probability behavior).

This method incentivizes the less desirable behavior by associating it with a desirable outcome, thus strengthening the less favored behavior.

Negative Reinforcement

Negative reinforcement is the termination of an unpleasant state following a response.

This is known as negative reinforcement because it is the removal of an adverse stimulus which is ‘rewarding’ to the animal or person. Negative reinforcement strengthens behavior because it stops or removes an unpleasant experience.

For example, if you do not complete your homework, you give your teacher £5. You will complete your homework to avoid paying £5, thus strengthening the behavior of completing your homework.

Skinner showed how negative reinforcement worked by placing a rat in his Skinner box and then subjecting it to an unpleasant electric current which caused it some discomfort. As the rat moved about the box it would accidentally knock the lever.

Immediately, it did so the electric current would be switched off. The rats quickly learned to go straight to the lever after a few times of being put in the box. The consequence of escaping the electric current ensured that they would repeat the action again and again.

In fact, Skinner even taught the rats to avoid the electric current by turning on a light just before the electric current came on. The rats soon learned to press the lever when the light came on because they knew that this would stop the electric current from being switched on.

These two learned responses are known as Escape Learning and Avoidance Learning .

Punishment is the opposite of reinforcement since it is designed to weaken or eliminate a response rather than increase it. It is an aversive event that decreases the behavior that it follows.

Like reinforcement, punishment can work either by directly applying an unpleasant stimulus like a shock after a response or by removing a potentially rewarding stimulus, for instance, deducting someone’s pocket money to punish undesirable behavior.

Note : It is not always easy to distinguish between punishment and negative reinforcement.

They are two distinct methods of punishment used to decrease the likelihood of a specific behavior occurring again, but they involve different types of consequences:

Positive Punishment :

Positive punishment involves adding an aversive stimulus or something unpleasant immediately following a behavior to decrease the likelihood of that behavior happening in the future.
It aims to weaken the target behavior by associating it with an undesirable consequence.
Example : A child receives a scolding (an aversive stimulus) from their parent immediately after hitting their sibling. This is intended to decrease the likelihood of the child hitting their sibling again.

Negative Punishment :

Negative punishment involves removing a desirable stimulus or something rewarding immediately following a behavior to decrease the likelihood of that behavior happening in the future.
It aims to weaken the target behavior by taking away something the individual values or enjoys.
Example : A teenager loses their video game privileges (a desirable stimulus) for not completing their chores. This is intended to decrease the likelihood of the teenager neglecting their chores in the future.

There are many problems with using punishment, such as:

Punished behavior is not forgotten, it’s suppressed – behavior returns when punishment is no longer present.
Causes increased aggression – shows that aggression is a way to cope with problems.
Creates fear that can generalize to undesirable behaviors, e.g., fear of school.
Does not necessarily guide you toward desired behavior – reinforcement tells you what to do, and punishment only tells you what not to do.

Examples of Operant Conditioning

Positive Reinforcement : Suppose you are a coach and want your team to improve their passing accuracy in soccer. When the players execute accurate passes during training, you praise their technique. This positive feedback encourages them to repeat the correct passing behavior.

Negative Reinforcement : If you notice your team working together effectively and exhibiting excellent team spirit during a tough training session, you might end the training session earlier than planned, which the team perceives as a relief. They understand that teamwork leads to positive outcomes, reinforcing team behavior.

Negative Punishment : If an office worker continually arrives late, their manager might revoke the privilege of flexible working hours. This removal of a positive stimulus encourages the employee to be punctual.

Positive Reinforcement : Training a cat to use a litter box can be achieved by giving it a treat each time it uses it correctly. The cat will associate the behavior with the reward and will likely repeat it.

Negative Punishment : If teenagers stay out past their curfew, their parents might take away their gaming console for a week. This makes the teenager more likely to respect their curfew in the future to avoid losing something they value.

Ineffective Punishment : Your child refuses to finish their vegetables at dinner. You punish them by not allowing dessert, but the child still refuses to eat vegetables next time. The punishment seems ineffective.

Premack Principle Application : You could motivate your child to eat vegetables by offering an activity they love after they finish their meal. For instance, for every vegetable eaten, they get an extra five minutes of video game time. They value video game time, which might encourage them to eat vegetables.

Other Premack Principle Examples :

A student who dislikes history but loves art might earn extra time in the art studio for each history chapter reviewed.
For every 10 minutes a person spends on household chores, they can spend 5 minutes on a favorite hobby.
For each successful day of healthy eating, an individual allows themselves a small piece of dark chocolate at the end of the day.
A child can choose between taking out the trash or washing the dishes. Giving them the choice makes them more likely to complete the chore willingly.

Skinner’s Pigeon Experiment

B.F. Skinner conducted several experiments with pigeons to demonstrate the principles of operant conditioning.

One of the most famous of these experiments is often colloquially referred to as “ Superstition in the Pigeon .”

This experiment was conducted to explore the effects of non-contingent reinforcement on pigeons, leading to some fascinating observations that can be likened to human superstitions.

Non-contingent reinforcement (NCR) refers to a method in which rewards (or reinforcements) are delivered independently of the individual’s behavior. In other words, the reinforcement is given at set times or intervals, regardless of what the individual is doing.

The Experiment:

Pigeons were brought to a state of hunger, reduced to 75% of their well-fed weight.
They were placed in a cage with a food hopper that could be presented for five seconds at a time.
Instead of the food being given as a result of any specific action by the pigeon, it was presented at regular intervals, regardless of the pigeon’s behavior.

Observation:

Over time, Skinner observed that the pigeons began to associate whatever random action they were doing when food was delivered with the delivery of the food itself.
This led the pigeons to repeat these actions, believing (in anthropomorphic terms) that their behavior was causing the food to appear.
In most cases, pigeons developed different “superstitious” behaviors or rituals. For instance, one pigeon would turn counter-clockwise between food presentations, while another would thrust its head into a cage corner.
These behaviors did not appear until the food hopper was introduced and presented periodically.
These behaviors were not initially related to the food delivery but became linked in the pigeon’s mind due to the coincidental timing of the food dispensing.
The behaviors seemed to be associated with the environment, suggesting the pigeons were responding to certain aspects of their surroundings.
The rate of reinforcement (how often the food was presented) played a significant role. Shorter intervals between food presentations led to more rapid and defined conditioning.
Once a behavior was established, the interval between reinforcements could be increased without diminishing the behavior.

Superstitious Behavior:

The pigeons began to act as if their behaviors had a direct effect on the presentation of food, even though there was no such connection. This is likened to human superstitions, where rituals are believed to change outcomes, even if they have no real effect.

For example, a card player might have rituals to change their luck, or a bowler might make gestures believing they can influence a ball already in motion.

Conclusion:

This experiment demonstrates that behaviors can be conditioned even without a direct cause-and-effect relationship. Just like humans, pigeons can develop “superstitious” behaviors based on coincidental occurrences.

This study not only sheds light on the intricacies of operant conditioning but also draws parallels between animal and human behaviors in the face of random reinforcements.

Schedules of Reinforcement

Imagine a rat in a “Skinner box.” In operant conditioning, if no food pellet is delivered immediately after the lever is pressed then after several attempts the rat stops pressing the lever (how long would someone continue to go to work if their employer stopped paying them?). The behavior has been extinguished.

Behaviorists discovered that different patterns (or schedules) of reinforcement had different effects on the speed of learning and extinction. Ferster and Skinner (1957) devised different ways of delivering reinforcement and found that this had effects on

1. The Response Rate – The rate at which the rat pressed the lever (i.e., how hard the rat worked).

2. The Extinction Rate – The rate at which lever pressing dies out (i.e., how soon the rat gave up).

Skinner found that the type of reinforcement which produces the slowest rate of extinction (i.e., people will go on repeating the behavior for the longest time without reinforcement) is variable-ratio reinforcement. The type of reinforcement which has the quickest rate of extinction is continuous reinforcement.

(A) Continuous Reinforcement

An animal/human is positively reinforced every time a specific behavior occurs, e.g., every time a lever is pressed a pellet is delivered, and then food delivery is shut off.

Response rate is SLOW
Extinction rate is FAST

(B) Fixed Ratio Reinforcement

Behavior is reinforced only after the behavior occurs a specified number of times. e.g., one reinforcement is given after every so many correct responses, e.g., after every 5th response. For example, a child receives a star for every five words spelled correctly.

Response rate is FAST
Extinction rate is MEDIUM

(C) Fixed Interval Reinforcement

One reinforcement is given after a fixed time interval providing at least one correct response has been made. An example is being paid by the hour. Another example would be every 15 minutes (half hour, hour, etc.) a pellet is delivered (providing at least one lever press has been made) then food delivery is shut off.

Response rate is MEDIUM

(D) Variable Ratio Reinforcement

behavior is reinforced after an unpredictable number of times. For examples gambling or fishing.

Extinction rate is SLOW (very hard to extinguish because of unpredictability)

(E) Variable Interval Reinforcement

Providing one correct response has been made, reinforcement is given after an unpredictable amount of time has passed, e.g., on average every 5 minutes. An example is a self-employed person being paid at unpredictable times.

Extinction rate is SLOW

Applications In Psychology

1. behavior modification therapy.

Behavior modification is a set of therapeutic techniques based on operant conditioning (Skinner, 1938, 1953). The main principle comprises changing environmental events that are related to a person’s behavior. For example, the reinforcement of desired behaviors and ignoring or punishing undesired ones.

This is not as simple as it sounds — always reinforcing desired behavior, for example, is basically bribery.

There are different types of positive reinforcements. Primary reinforcement is when a reward strengths a behavior by itself. Secondary reinforcement is when something strengthens a behavior because it leads to a primary reinforcer.

Examples of behavior modification therapy include token economy and behavior shaping.

Token Economy

Token economy is a system in which targeted behaviors are reinforced with tokens (secondary reinforcers) and later exchanged for rewards (primary reinforcers).

Tokens can be in the form of fake money, buttons, poker chips, stickers, etc. While the rewards can range anywhere from snacks to privileges or activities. For example, teachers use token economy at primary school by giving young children stickers to reward good behavior.

Token economy has been found to be very effective in managing psychiatric patients . However, the patients can become over-reliant on the tokens, making it difficult for them to adjust to society once they leave prison, hospital, etc.

Staff implementing a token economy program have a lot of power. It is important that staff do not favor or ignore certain individuals if the program is to work. Therefore, staff need to be trained to give tokens fairly and consistently even when there are shift changes such as in prisons or in a psychiatric hospital.

Behavior Shaping

A further important contribution made by Skinner (1951) is the notion of behavior shaping through successive approximation.

Skinner argues that the principles of operant conditioning can be used to produce extremely complex behavior if rewards and punishments are delivered in such a way as to encourage move an organism closer and closer to the desired behavior each time.

In shaping, the form of an existing response is gradually changed across successive trials towards a desired target behavior by rewarding exact segments of behavior.

To do this, the conditions (or contingencies) required to receive the reward should shift each time the organism moves a step closer to the desired behavior.

According to Skinner, most animal and human behavior (including language) can be explained as a product of this type of successive approximation.

2. Educational Applications

In the conventional learning situation, operant conditioning applies largely to issues of class and student management, rather than to learning content. It is very relevant to shaping skill performance.

A simple way to shape behavior is to provide feedback on learner performance, e.g., compliments, approval, encouragement, and affirmation.

A variable-ratio produces the highest response rate for students learning a new task, whereby initial reinforcement (e.g., praise) occurs at frequent intervals, and as the performance improves reinforcement occurs less frequently, until eventually only exceptional outcomes are reinforced.

For example, if a teacher wanted to encourage students to answer questions in class they should praise them for every attempt (regardless of whether their answer is correct). Gradually the teacher will only praise the students when their answer is correct, and over time only exceptional answers will be praised.

Unwanted behaviors, such as tardiness and dominating class discussion can be extinguished through being ignored by the teacher (rather than being reinforced by having attention drawn to them). This is not an easy task, as the teacher may appear insincere if he/she thinks too much about the way to behave.

Knowledge of success is also important as it motivates future learning. However, it is important to vary the type of reinforcement given so that the behavior is maintained.

This is not an easy task, as the teacher may appear insincere if he/she thinks too much about the way to behave.

Operant Conditioning vs. Classical Conditioning

Learning type.

While both types of conditioning involve learning, classical conditioning is passive (automatic response to stimuli), while operant conditioning is active (behavior is influenced by consequences).

Classical conditioning links an involuntary response with a stimulus. It happens passively on the part of the learner, without rewards or punishments. An example is a dog salivating at the sound of a bell associated with food.
Operant conditioning connects voluntary behavior with a consequence. Operant conditioning requires the learner to actively participate and perform some type of action to be rewarded or punished. It’s active, with the learner’s behavior influenced by rewards or punishments. An example is a dog sitting on command to get a treat.

Learning Process

Classical conditioning involves learning through associating stimuli resulting in involuntary responses, while operant conditioning focuses on learning through consequences, shaping voluntary behaviors.

Over time, the person responds to the neutral stimulus as if it were the unconditioned stimulus, even when presented alone. The response is involuntary and automatic.

An example is a dog salivating (response) at the sound of a bell (neutral stimulus) after it has been repeatedly paired with food (unconditioned stimulus).

Behavior followed by pleasant consequences (rewards) is more likely to be repeated, while behavior followed by unpleasant consequences (punishments) is less likely to be repeated.

For instance, if a child gets praised (pleasant consequence) for cleaning their room (behavior), they’re more likely to clean their room in the future.

Conversely, if they get scolded (unpleasant consequence) for not doing their homework, they’re more likely to complete it next time to avoid the scolding.

Timing of Stimulus & Response

The timing of the response relative to the stimulus differs between classical and operant conditioning:

Classical Conditioning (response after the stimulus) : In this form of conditioning, the response occurs after the stimulus. The behavior (response) is determined by what precedes it (stimulus).

For example, in Pavlov’s classic experiment, the dogs started to salivate (response) after they heard the bell (stimulus) because they associated it with food.

The anticipated consequence influences the behavior or what follows it. It is a more active form of learning, where behaviors are reinforced or punished, thus influencing their likelihood of repetition.

For example, a child might behave well (behavior) in anticipation of a reward (consequence), or avoid a certain behavior to prevent a potential punishment.

Looking at Skinner’s classic studies on pigeons’ / rat’s behavior we can identify some of the major assumptions of the behaviorist approach .

• Psychology should be seen as a science , to be studied in a scientific manner. Skinner’s study of behavior in rats was conducted under carefully controlled laboratory conditions . • Behaviorism is primarily concerned with observable behavior, as opposed to internal events like thinking and emotion. Note that Skinner did not say that the rats learned to press a lever because they wanted food. He instead concentrated on describing the easily observed behavior that the rats acquired. • The major influence on human behavior is learning from our environment. In the Skinner study, because food followed a particular behavior the rats learned to repeat that behavior, e.g., operant conditioning. • There is little difference between the learning that takes place in humans and that in other animals. Therefore research (e.g., operant conditioning) can be carried out on animals (Rats / Pigeons) as well as on humans. Skinner proposed that the way humans learn behavior is much the same as the way the rats learned to press a lever.

So, if your layperson’s idea of psychology has always been of people in laboratories wearing white coats and watching hapless rats try to negotiate mazes in order to get to their dinner, then you are probably thinking of behavioral psychology.

Behaviorism and its offshoots tend to be among the most scientific of the psychological perspectives . The emphasis of behavioral psychology is on how we learn to behave in certain ways.

We are all constantly learning new behaviors and how to modify our existing behavior. behavioral psychology is the psychological approach that focuses on how this learning takes place.

Critical Evaluation

Operant conditioning can be used to explain a wide variety of behaviors, from the process of learning, to addiction and language acquisition . It also has practical applications (such as token economy) which can be applied in classrooms, prisons and psychiatric hospitals.

Researchers have found innovative ways to apply operant conditioning principles to promote health and habit change in humans.

In a recent study, operant conditioning using virtual reality (VR) helped stroke patients use their weakened limb more often during rehabilitation. Patients shifted their weight in VR games by maneuvering a virtual object. When they increased weight on their weakened side, they received rewards like stars. This positive reinforcement conditioned greater paretic limb use (Kumar et al., 2019).

Another study utilized operant conditioning to assist smoking cessation. Participants earned vouchers exchangeable for goods and services for reducing smoking. This reward system reinforced decreasing cigarette use. Many participants achieved long-term abstinence (Dallery et al., 2017).

Through repeated reinforcement, operant conditioning can facilitate forming exercise and eating habits. A person trying to exercise more might earn TV time for every 10 minutes spent working out. An individual aiming to eat healthier may allow themselves a daily dark chocolate square for sticking to nutritious meals. Providing consistent rewards for desired actions can instill new habits (Michie et al., 2009).

Apps like Habitica apply operant conditioning by gamifying habit tracking. Users earn points and collect rewards in a fantasy game for completing real-life habits. This virtual reinforcement helps ingrain positive behaviors (Eckerstorfer et al., 2019).

Operant conditioning also shows promise for managing ADHD and OCD. Rewarding concentration and focus in ADHD children, for example, can strengthen their attention skills (Rosén et al., 2018). Similarly, reinforcing OCD patients for resisting compulsions may diminish obsessive behaviors (Twohig et al., 2018).

However, operant conditioning fails to take into account the role of inherited and cognitive factors in learning, and thus is an incomplete explanation of the learning process in humans and animals.

For example, Kohler (1924) found that primates often seem to solve problems in a flash of insight rather than be trial and error learning. Also, social learning theory (Bandura, 1977) suggests that humans can learn automatically through observation rather than through personal experience.

The use of animal research in operant conditioning studies also raises the issue of extrapolation. Some psychologists argue we cannot generalize from studies on animals to humans as their anatomy and physiology are different from humans, and they cannot think about their experiences and invoke reason, patience, memory or self-comfort.

Frequently Asked Questions

Who discovered operant conditioning.

Operant conditioning was discovered by B.F. Skinner, an American psychologist, in the mid-20th century. Skinner is often regarded as the father of operant conditioning, and his work extensively dealt with the mechanism of reward and punishment for behaviors, with the concept being that behaviors followed by positive outcomes are reinforced, while those followed by negative outcomes are discouraged.

How does operant conditioning differ from classical conditioning?

Operant conditioning differs from classical conditioning, focusing on how voluntary behavior is shaped and maintained by consequences, such as rewards and punishments.

In operant conditioning, a behavior is strengthened or weakened based on the consequences that follow it. In contrast, classical conditioning involves the association of a neutral stimulus with a natural response, creating a new learned response.

While both types of conditioning involve learning and behavior modification, operant conditioning emphasizes the role of reinforcement and punishment in shaping voluntary behavior.

How does operant conditioning relate to social learning theory?

Operant conditioning is a core component of social learning theory , which emphasizes the importance of observational learning and modeling in acquiring and modifying behavior.

Social learning theory suggests that individuals can learn new behaviors by observing others and the consequences of their actions, which is similar to the reinforcement and punishment processes in operant conditioning.

By observing and imitating models, individuals can acquire new skills and behaviors and modify their own behavior based on the outcomes they observe in others.

Overall, both operant conditioning and social learning theory highlight the importance of environmental factors in shaping behavior and learning.

What are the downsides of operant conditioning?

The downsides of using operant conditioning on individuals include the potential for unintended negative consequences, particularly with the use of punishment. Punishment may lead to increased aggression or avoidance behaviors.

Additionally, some behaviors may be difficult to shape or modify using operant conditioning techniques, particularly when they are highly ingrained or tied to complex internal states.

Furthermore, individuals may resist changing their behaviors to meet the expectations of others, particularly if they perceive the demands or consequences of the reinforcement or punishment to be undesirable or unjust.

What is an application of bf skinner’s operant conditioning theory?

An application of B.F. Skinner’s operant conditioning theory is seen in education and classroom management. Teachers use positive reinforcement (rewards) to encourage good behavior and academic achievement, and negative reinforcement or punishment to discourage disruptive behavior.

For example, a student may earn extra recess time (positive reinforcement) for completing homework on time, or lose the privilege to use class computers (negative punishment) for misbehavior.

To read this content please select one of the options below:

Please note you do not have access to teaching notes, reinforcement theory: a practical tool.

Leadership & Organization Development Journal

ISSN : 0143-7739

Article publication date: 1 February 1991

A “process” theory of motivation is explored, namely reinforcement theory. Reinforcement theory is defined and the four primary strategies for implementing it – positive reinforcement, negative reinforcement, punishment and extinction – are described. The advantages and disadvantages of each strategy and the ways of scheduling these are outlined, together with a discussion of current research and practical implications of the theory.

Villere, M.F. and Hartman, S.S. (1991), "Reinforcement Theory: A Practical Tool", Leadership & Organization Development Journal , Vol. 12 No. 2, pp. 27-31. https://doi.org/10.1108/01437739110138039

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What is reinforcement theory in behavioral science, what is reinforcement theory.

Reinforcement theory is a concept in behavioral psychology that suggests that behavior is driven by its consequences. Initially developed by psychologist B.F. Skinner, reinforcement theory states that rewarded behaviors are likely to be repeated, while punished behaviors are likely to cease. The theory underlines the importance of consequences as motivating factors in decision-making and action, focusing on observable behavior rather than internal mental states.

Reinforcement can be either positive or negative, and both types play a crucial role in shaping behavior. Positive reinforcement involves the addition of a rewarding stimulus to increase the likelihood of a behavior, while negative reinforcement involves the removal of an adverse stimulus to encourage behavior. On the other hand, punishment, which can also be positive (adding an adverse stimulus) or negative (removing a pleasant stimulus), aims to reduce or eliminate undesirable behavior.

Examples of Reinforcement Theory

In education, reinforcement theory is often applied to motivate learning and improve student behavior. For instance, positive reinforcement can take the form of praise, good grades, or rewards for completing homework or behaving appropriately in class. Negative reinforcement might involve removing an undesirable task when the student demonstrates good behavior.

Workplace Behavior

Reinforcement theory is frequently used in the workplace to encourage productive behavior and discourage counterproductive behavior. For instance, an employee might receive a bonus (positive reinforcement) for meeting a sales target or be allowed to leave early (negative reinforcement) after completing a challenging task. Conversely, reprimands or pay deductions can be used as punishment to discourage poor performance or unprofessional conduct.

Behavioral Therapy

In psychology, reinforcement theory is applied in behavioral therapies, such as Applied Behavior Analysis (ABA) used to treat conditions like autism. Positive behaviors might be reinforced through praise or rewards, while harmful behaviors might be discouraged through time-outs or removal of privileges.

Significance of Reinforcement Theory

Reinforcement theory is a fundamental concept in behavioral psychology, with wide-ranging applications. It offers a practical framework for understanding how behavior can be shaped and modified over time, which is particularly valuable in fields like education, therapy, and management. By focusing on the consequences of behavior, reinforcement theory provides concrete strategies for encouraging desirable behavior and discouraging undesirable behavior, influencing everything from classroom dynamics to organizational culture.

Controversies and Criticisms of Reinforcement Theory

While reinforcement theory has had a significant impact on behavioral psychology, it has faced criticism. Some critics argue that the theory oversimplifies human behavior by focusing solely on observable behaviors and ignoring internal mental processes. Others suggest that extrinsic rewards and punishments can undermine intrinsic motivation, leading to a decrease in interest or engagement once the reinforcement is removed. Additionally, critics note that the effectiveness of reinforcement can vary greatly among individuals due to factors such as personality, cultural context, and past experiences.

Related Behavioral Science Terms

Belief perseverance, crystallized intelligence, extraneous variable, representative sample, factor analysis, egocentrism, stimulus generalization, reciprocal determinism, divergent thinking, convergent thinking, social environment, decision making, related articles.

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What you’ll learn to do: explain reinforcement theory

In this section, you will learn about reinforcement theory, the counterpoint to goal-setting theory. Reinforcement theory is a behavioristic approach that says reinforcement conditions behavior.

Contributors and Attributions

Introduction to Reinforcement Theory. Authored by : David J. Thompson and Lumen Learning.. License : CC BY: Attribution

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A Review of B. F. Skinner's 'Reinforcement Theory of Motivation'

B. F. Skinner in his book Beyond Freedom and Dignity said that thinkers should make fundamental changes in human behavior, and they couldn't bring these changes only with the help of physics or biology. He believes that we only acquire the technology of behavior. Centuries ago people were seeing themselves as a person who could feel himself better any other creatures in the world. But in today " s world he is not able to understand himself. Although science have emerged vastly; but we are not able to compare anything like a science of human behavior with any other science in the world. As behaviorist B.F. Skinner brought up the Reinforcement Theory. The Reinforcement Theory is one of the oldest theories of motivation which describe behavior and how we act. This theory can called as " behaviorism " or " operant conditioning " that is taught in the today " s world of psychology. In this article we are looking at B. F. Skinner Reinforcement Theory of Motivation and we go through all details in this theory. This is a review paper based on the theorist Skinner.

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Reinforcement Theory Definition

What does reinforcement theory mean? In fact, the reinforcement theory definition is simple and intuitive.

Reinforcement theory states that an individual's behavior is shaped by the behavior's consequences.

Essentially, the relationship between a behavior and its consequences in reinforcement theory is a cause-effect one.

For example, you choose to work hard today because you know hard work can get you more money in the future. Likewise, if you can make more money, you will likely desire to work harder.

Reinforcement Theory of Motivation

In 1957, B. F. Skinner, an American psychologist at Harvard University, proposed the reinforcement theory of motivation. 1

Behavior which is reinforced tends to be repeated; behavior which is not reinforced tends to die out or be extinguished. 1

- B. F. Skinner

Further, reinforcement theory overlooks the internal conditions of individuals, such as their feelings and intrinsic motivation . Rather, reinforcement theory only focuses on the external environment and behaviors associated with individuals.

What is the core principle of the re inforcement theory of motivation?

Essentially, the re inforcement theory of motivation is based on the Law of Effect. Accordingly, individuals have several choices of behaviors for any specific situation. However, they will opt for the one that has yielded the most positive and desirable outcomes in the past.

Also, reinforcement theory involves two important psychologic concepts: operant behaviors and operant conditioning.

Operant behavior implies behavior that elicits the consequences in reinforcement theory. Operant conditioning implies a learning process that focuses on reinforcement's role in conditioning.

For example, the manager will give a sales commission when a salesperson successfully closes a deal. Closing a deal is an operant behavior while educating salespersons that they can gain a sales commission for every successful deal is operant conditioning.

Behavioral Reinforcement Theory

Reinforcement theory is an important principle in the field of organizational behavior . Accordingly, the theory provides a cohesive reinforcement theory framework, which consists of four aspects of operant conditioning: positive reinforcement, negative reinforcement, punishment, and extinction. 1

What are the roles of reinforcement and punishment?

While reinforcement increases the likelihood of the desired behavior, punishment decreases it.

Positive Reinforcement Theory

Positive reinforcement is an important o perant conditioning in reinforcement theory.

Positive reinforcement is the act of providing a desirable stimulus to reinforce positive behavior and encourage it to repeat in the future.

Positive reinforcement can adopt different stimulus types at workplaces, ranging from financial bonuses and compliments to time-off rewards and certificates.

Accordingly, the more spontaneous the stimulus is, the more likely positive reinforcement will occur. 1 For instance, if a team is expecting a pay rise and then receive the exact pay rise, it will not impact future performance as greatly as if the pay rise came out of a sudden.

What are the benefits of positive reinforcement?

Research has shown that employees who receive positive reinforcement from their seniors are more unlikely to switch jobs. Further, they are always eager to try their best at work while contributing enthusiastically to their team performance. 2

Negative Reinforcement Theory

Surprisingly, negative reinforcement does not imply negative and undesirable operant conditioning.

Negative reinforcement occurs when an unpleasant or negative thing is removed to enhance the likelihood of the desired behavior.

For example, a marketing manager requires the marketing team to deliver a daily summary report about the company's new project. However, after one month, given the project's good performance, the manager tells the team to deliver the report weekly instead. Thus, the manager has practiced negative reinforcement by removing the unnecessary daily reporting routine!

The advantages and disadvantages of negative reinforcement:

On the one hand, negative reinforcement can immediately influence the desired behavior. Additionally, it does not require constant follow-up from the management team, given the instant effectiveness of removing the adverse stimuli. 2

On the other hand, removing negative things is often self-explanatory; negative reinforcement can cause misunderstanding among team members. Also, negative reinforcement can be ineffective if it is wrongly timed. Accordingly, negative reinforcement should occur immediately after the desired behavior to maximize operant conditioning's benefits. 3

Punishment Reinforcement

Besides positive and negative reinforcement, punishment reinforcement is a stronger form of operant conditioning.

Punishment reinforcement implies imposing negative consequences to stop or reduce undesirable behaviors.

For example, an employee constantly arrives late to work. Thus, at the end of the month, the employee receives less money in the paycheck. Accordingly, the decreased paycheck is a punishment to stop the employee from arriving late.

What are the different types of punishment at work?

Managers can consider some types of punishment reinforcement at work, which range from financial penalties and probation to private feedback sessions and demotion.

Further, many people can easily mistake punishment reinforcement for negative reinforcement. However, there are certain differences between the two concepts.

Table 1 - The difference between punishment reinforcement and negative reinforcement

Is termination a type of punishment reinforcement?

A punishment reinforcement should result in a behavioral change at the end of the punishment. 1 However, regarding termination , an individual will no longer continue working at a workplace, thus being unable to change associated behaviors. Therefore, t ermination is not a type of punishment reinforcement.

Reinforcement Theory: Extinction

In reinforcement theory, extinction is a narrow and straightforward operant conditioning.

Extinction implies the act of ending any reinforcement that maintains a behavior.

For example, during the busy season, a hotel manager decided to give employees overtime pay as a positive reinforcement at work. However, after the season, the hotel manager stopped the overtime scheme as the business returned to the normal cycle. Thus, the act of stopping paying overtime is considered an extinction in reinforcement theory.

What are the risks of extinction?

Extinction must be carefully conducted. Otherwise, it can discourage individuals as they may feel unappreciated given the sudden end of positive reinforcement. Thus, inappropriately done extinction can result in decreasing morale and productivity in general.

Reinforcement Theory in the Workplace

In this section, we will have a look at factors influencing the effectiveness of reinforcement theory in workplaces. Also, we will discuss the appropriate schedule of reinforcement at work.

Influential Factors

Regardless of their choices, managers should carefully consider different factors that can influence the effectiveness of their reinforcement or punishment. Accordingly, there are three main factors influencing reinforcement theory in the workplace: employees' satisfaction, speediness, and the extent of the reinforcement or punishment. 3

Table 2 - Factors influencing reinforcement theory in the workplace

Schedule of Reinforcement

Also, the frequency of applying reinforcement theory can greatly affect its effectiveness in the workplace. Accordingly, there are two main approaches to scheduling reinforcement at work: continuous and intermittent. 1

While continuous reinforcement implies the act of reinforcing a behavior every time it is observed, intermittent reinforcement only reinforces the behavior on certain occasions.

At workplaces, intermittent reinforcement is more popular because it saves managers more time and money. Further, intermittent reinforcement can result in better long-term behavioral changes than continuous ones.

For example, managers can practice continuous reinforcement by complimenting employees each time they help their teammates. Otherwise, managers can follow intermittent reinforcement if they only compliment their employees for helping others during weekly team meetings.

Within intermittent reinforcement, managers can adopt four different ways of scheduling: 1

Fix-interval reinforcement: managers can determine when reinforcement will be conducted, such as in weekly team meetings.

Variable interval reinforcement: managers do not define set times for reinforcement. Instead, they aim to reinforce their employees as regularly as possible.

Fixed radio reinforcement: managers perform reinforcement when a fixed number of actions have been achieved. For example, a salesperson is rewarded for every ten successful weekly deals.

Variable ratio reinforcement: managers perform reinforcement when a variable number of actions have been achieved. For example, a salesperson is rewarded if all targets are met.

Reinforcement Theory Examples

Let's have a look at examples of the different types of operant conditioning.

Table 3 - Reinforcement theory example

Thus, reinforcement theory has been increasingly popular in motivating employees at work. However, a successful application of this theory requires a thorough understanding of this concept and careful consideration from managers.

The way positive reinforcement is carried out is more important than the result

Reinforcement Theory - Key takeaways

In 1957, the r einforcement theory of motivation was first proposed by B. F. Skinner, an American psychologist at Harvard University.
There are four aspects of operant conditioning: positive reinforcement, negative reinforcement, punishment, and extinction.
There are three main factors influencing reinforcement theory in the workplace: employees' satisfaction, speediness, and the extent of the reinforcement or punishment
There are two main approaches to scheduling reinforcement at work: continuous reinforcement and intermittent reinforcement.
Ferster, C. B., & Skinner, B. F. (1957). Schedules of reinforcement. New York: Appleton-Century-Crofts.
Kristie Rogers. Do Your Employees Feel Respected?. 2022. https://hbr.org/2018/07/do-your-employees-feel-respected
Mohamad Danial bin Ab. Khalil. HR Guide: Motivating Employees Using Reinforcement Theory. 2020. https://www.ajobthing.com/blog/hr-guide-motivating-employees-using-reinforcement-theory

Frequently Asked Questions about Reinforcement Theory

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Organizational Behaviour

Reinforcement Theory of Motivation

Reinforcement theory of motivation was proposed by BF Skinner and his associates. It states that individual’s behaviour is a function of its consequences. It is based on “law of effect”, i.e, individual’s behaviour with positive consequences tends to be repeated, but individual’s behaviour with negative consequences tends not to be repeated.

Reinforcement theory of motivation overlooks the internal state of individual , i.e., the inner feelings and drives of individuals are ignored by Skinner. This theory focuses totally on what happens to an individual when he takes some action.

Thus, according to Skinner, the external environment of the organization must be designed effectively and positively so as to motivate the employee.

This theory is a strong tool for analyzing controlling mechanism for individual’s behaviour. However, it does not focus on the causes of individual’s behaviour.

The managers use the following methods for controlling the behaviour of the employees:

Implications of Reinforcement Theory

Reinforcement theory explains in detail how an individual learns behaviour. Managers who are making attempt to motivate the employees must ensure that they do not reward all employees simultaneously. They must tell the employees what they are not doing correct. They must tell the employees how they can achieve positive reinforcement.

McClelland’s Theory of Needs
Goal Setting Theory
Equity Theory of Motivation
Expectancy Theory of Motivation

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Authorship/Referencing - About the Author(s)

The article is Written and Reviewed by Management Study Guide Content Team . MSG Content Team comprises experienced Faculty Member, Professionals and Subject Matter Experts. We are a ISO 2001:2015 Certified Education Provider . To Know more, click on About Us . The use of this material is free for learning and education purpose. Please reference authorship of content used, including link(s) to ManagementStudyGuide.com and the content page url.

Motivation - Introduction
Maslow’s Need Hierarchy Model
Motivation Incentives
Importance of Motivation
Motivation and Morale
Employee/Staff Motivation
Workplace Motivation
Self Motivation at Work
Team Motivation
Role of Motivation in OB
Motivational Challenges
Good Motivation System
Classical Theories of Motivation
Maslow’s Hierarchy of Needs Theory
Herzberg’s Theory of Motivation
Theory X and Theory Y
Modern Theories of Motivation
Reinforcement Theory
How the Movie Yuva Explains The Need Theory of Motivation and What Motivates Us
Why Intrinsic Motivation Matters More Now In the Times of the Great Resignation
How Motivation Can Help Millennials/Gen Zers Avoid Burnout in the Post Pandemic Age

Systematic Review of Differential Reinforcement in Skill Acquisition

Discussion and Review Paper
Published: 06 February 2024

Cite this article

Catia Cividini-Motta ORCID: orcid.org/0000-0001-5679-9294 1 ,
Cynthia Livingston ORCID: orcid.org/0000-0003-0955-4635 2 &
Hannah Efaw 1

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The purpose of this article was to review and summarize the literature investigating the impact of differential reinforcement on skill acquisition. Researchers synthesized data from 10 articles across the following categories: (1) participant characteristics; (2) setting; (3) reinforcement procedures; (4) within-subject replication; (5) results; and (6) secondary measures (e.g., social validity). Results indicated that most of the participants were male, had a diagnosis of autism, and communicated vocally. The differential reinforcement condition in which reinforcement favored independent responses (e.g., edible for independent; praise for prompted responses) was the most frequently employed differential reinforcement condition and it resulted in the acquisition of more responses or faster acquisition for most participants. In addition, when differing reinforcement procedures manipulating different parameters of reinforcements were compared, better outcomes were attained when the schedule of the reinforcer was manipulated within the differential reinforcement procedure relative to when quality or magnitude were manipulated. Limitations of the previous research, recommendations for future research, and implications for clinical practice are discussed.

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Evidence-Based Practices for Children, Youth, and Young Adults with Autism: Third Generation Review

State of the Evidence Traffic Lights 2019: Systematic Review of Interventions for Preventing and Treating Children with Cerebral Palsy

Piaget and Vygotsky’s Play Theories: The Profile of Twenty-First-Century Evidence

Data availability.

The data generated during the study are available from the first author on reasonable request.

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International Journal of Research and Innovation in Social Science (IJRISS) | Volume V, Issue VII, July 2021 | ISSN 2454–6186

A Study on Increasing Positive Behaviors Using Positive Reinforcement Techniques

Vivetha Gunaretnam (Dip. Counselling, BSW (hons), MSW (c), Sri Lanka)

National Institute of Social Development, Sri Lanka

Abstract: Positive reinforcement works by presenting a motivating/reinforcing stimulus to the person after the desired behavior is exhibited, making the behavior more likely to happen in the future. Classroom management is one of the most common problems facing by teachers because disruptive students take up valuable learning time. Students with disruptive, defiant, and disrespectful behaviors often make it difficult for teachers to teach and students to learn. The techniques based on positive reinforcement lack popular and professional acceptability because they are time-intensive, offer little compensation for educators, contradict popular views of developmental psychology, threaten special interest groups, are socially unacceptable, and demean humans. To investigate more on this area, the researcher identified positive reinforcement techniques applied by school teachers on primary students, the effectiveness of the reinforcement techniques for reward, and identified social work interventions to promote positive reinforcement. To conduct this study the researcher selected the Manmunai North zone from Batticaloa, Sri Lanka. This research study was explored through a mixed-method and sequential explanatory research design. The tools such as interview schedule and questionnaire were used to collect data. The collected data were analyzed through SPSS software and thematic analysis. The researcher was able to find the techniques under sensory, natural, material, generalized and social reinforcements. From the techniques most of the teachers agreed with positive reinforcement techniques from sensory, natural, material, generalized and social reinforcements, increase the desirable behavior high in the academic performances except two techniques from generalized reinforcement. The researcher found that the issues in promoting positive reinforcement techniques through the individual level, group level system level, and the social work interventions also found under in mentioned levels. From the overall findings, the researcher can able to induct a hybrid mixture of the explanatory model from the combination of reinforcement model and social interaction model in Social Work Practice.

Key words: Positive reinforcement, techniques, school teachers, primary students

1.INTRODUCTION

In our everyday living, it is important to realize that our behaviors play a major part in assisting us to act and behave in different settings such as at home, school, workplace, and society. Good behaviors can lead to better lives, high achievements in related fields, and good relationships with others. On the other hand, individuals that have bad behaviors might have some unfavorable outcomes in their lives. However, these inappropriate behaviors can be replaced with desirable behaviors using behavior modification techniques. Many principles can be applied in encouraging and increasing a target’s good behaviors that include reinforcements, token economy, punishment, extinction, and classical conditioning. Many kinds of research have shown that positive reinforcements are proven to be more effective in practice as compared to other principles which have some flaws when applying in certain settings. Therefore this research aims to investigate the positive reinforcement techniques applied by school teachers on school-going students in primary unit special reference from Batticaloa District. The following chart shows the conceptual framework of this study.

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Social Learning, Self-Control, and Offending Specialization and Versatility among Friends

John h. boman, iv.

1 Department of Sociology, Bowling Green State University, 240 Williams Hall, Bowling Green, OH 43403, USA

Thomas J. Mowen

George e. higgins.

2 Department of Criminal Justice, University of Louisville, Louisville, KY 40292, USA

While it is generally understood that people tend not to specialize in specific types of deviance, less is understood about offending specialization and versatility in the context of friendships. Using a large sample of persons nested within friendship pairs, this study’s goal is to explore how self-control and social learning theories contribute to an explanation for specialization and versatility in offending among friends. We estimate a series of multilevel, dyadic, mixed-effects models which regress offending versatility onto measures of perceptual peer versatility, self-reported peer versatility, attitudinal self-control, behavioral self-control, and demographic controls. Results indicate that higher amounts of perceptual peer versatility and peer self-reported versatility are both related to increases in versatility among friends. Lower levels of the target respondent’s attitudinal and behavioral self-control are also related to higher amounts of offending versatility. However, the peer’s self-control shares no relationship with offending versatility – a point which both supports and fails to support self-control theory’s expectations about how peer effects should operate. Learning and self-control perspectives both appear to explain offending versatility among friends. However, self-control theory’s propositions about how peer effects should operate are contradictory. The concept of opportunity may help remediate this inconsistency in Gottfredson and Hirschi’s theory.

Introduction

Although social learning and self-control theories both explain crime (e.g., Pratt & Cullen, 2000 ; Pratt et al., 2010 ), the theories are fundamentally at odds with each other. Underpinning both theoretical approaches is a fundamentally different understanding of deviant behavior. To the learning perspective, deviance – like all things – is learned. However, according to control theories, deviance is somewhat ingrained and must be restrained by the proper development of self-control. Despite what may be irreconcilable differences between the two theories, their strong and consistent ability to explain crime has led to a newer debate that focuses not on whether the theories explain crime, but instead on which theory explains crime the best. Considering research on this newer learning/control issue yields mixed results (cf. Pratt et al., 2010 ; Vazsonyi, Mikuška, & Kelley, 2017 ), criminologists must continue to develop innovative ways of exploring the predictive ability of the competing theories.

At the heart of the learning/control tension is a theoretical disagreement in the causal pathways that lead to specialization and versatility in offending. Gottfredson and Hirschi’s (1990) perspective suggests that individuals with low self-control should be versatile in offending, meaning that they should commit a wide range of different types of deviant behavior. That is, individuals with low self-control should not ‘specialize’ by repeatedly committing the same type of deviant behavior. Like most issues surrounding control and learning theories, however, Sutherland’s (1947) differential association theory and Burgess and Akers’ (1966 ; also Akers, 2009 ) social learning theory share a quite different prediction regarding the causes of specialization and versatility in offending. To a learning perspective, individuals who specialize in only one type of crime do so because they have learned values, skills, and definitions that promote committing that one type of crime. On the other hand, an individual who is versatile in their offending patterns should have learned definitions favorable to versatility. As such, offending specialization and versatility, like all forms of behavior in a learning context, is the result of a learned process.

Intertwined in the disagreement between learning and control theories is a very different set of assumptions made about friends and friendships. While both theories recognize that friends are of importance, self-control argues that any link between the behavior of friends generally, or versatility and specialization specifically, should be the result of similarity in the friends’ levels of self-control (e.g., Gottfredson & Hirschi, 1990 , pp. 157–159). Social learning theory, on the other hand, would argue that the offending versatility or specialization patterns of friends should directly influence an individual’s patterns of behavior (see Akers, 2009 ; Sutherland, 1947 ; Thomas, 2016 ). As such, the theories expect a much different pathway through which specialization (akin to social learning theory) and versatility (akin to either learning or self-control theory) form.

Although friendships are theoretically intertwined into the larger specialization and versatility issue, researchers have had considerable difficulty in developing a knowledge base that recognizes friendships as central to specialization and versatility. Despite this, we do know from studies on specialization and versality that most people do not specialize in their patterns of deviance (see Farrington, 2003 ; Jennings, Zgoba, Donner, Henderson, & Tewksbury, 2014 ; Mazerolle, Brame, Paternoster, Piquero, & Dean, 2000 ; Piquero, 2000 ; Piquero, Farrington, & Blumstein, 2003 ; Wright, Pratt, & DeLisi, 2008 ; also see Armstrong, 2008 ; Ha & Andresen, 2017 ; Harris, Smallbone, Dennison, & Knight, 2009 ; McGloin, Sullivan, Piquero, & Pratt, 2007 ; Sullivan, McGloin, Pratt, & Piquero, 2006 ). Although this might seem to support self-control on first glance due to the theory’s adamant stance against specialization, this relatively consistent finding could in fact support either the control or learning perspective when viewed from the perspective of friendships. Further developing a theoretical clarity and understanding of the relationship between specialization, versatility, and peer characteristics is the broad goal of this study. Using data from a large study of people nested within friendship pairs (or friendship ‘dyads’), we apply the primary tenets of self-control theory and social learning theory to versatility and specialization in offending among friends. Before discussing the specifics, however, we begin by reviewing each theory’s approach to explaining offending specialization and versatility and discussing research relevant to the competing theories’ expectations.

Self-Control, Specialization, and Versatility

As a general theory of crime, self-control theory posits that the root cause of deviance is an individual’s level of self-control. Developed in early childhood through effective parental punishment ( Gottfredson & Hirschi, 1990 ), self-control refers to the ability to restrain one’s behavior. Individuals with low self-control tend to be impulsive, insensitive, risk-taking, and tend to not consider the long-term consequences of their behavior. Gottfredson and Hirschi contend that self-control is not specific to any particular set of offending behaviors and, instead, the theory purports to explain “all crimes, at all times” (p. 117). While research on the efficacy of self-control in explaining all types of crime is mixed (e.g., LaGrange & Silverman, 1999 ; however, see DeLisi, Hochstetler, Higgins, Beaver, & Graeve, 2008 ), studies tend to support the notion that those with low self-control offend more than those with greater levels of self-control (e.g., DeLisi, 2001 ). Highlighting this stance, Pratt and Cullen’s (2000) meta-analysis on the general theory of crime concludes that “self-control [is] one of the strongest known correlates of crime” (p. 952; see also Vazsonyi et al., 2017 for a more recent meta-analysis).

Applying this argument to versatility in offending, self-control theory would posit that low self-control – as the root cause of all deviant and antisocial behaviors – should be predictive of a significant degree of variation in offending. This is due in part to the fact that most crime is highly opportunistic and requires little in the way of planning ( Pratt, Barnes, Cullen, & Turanovic, 2016 ). The result is that individuals with low self-control will engage in a variety of offending behaviors with little consistency or stability in the types of crimes they choose to commit. In this vein, Gottfredson and Hirschi (1990) hypothesize that low self-control will produce “much versatility among offenders in the criminal acts in which they engage” (p. 91). Summarizing their opinions of offending and specialization, Gottfredson and Hirschi succinctly state that “offenders do not specialize” (p. 94).

Extending this argument into the realm of friendships, Gottfredson and Hirschi (1990) are clear that people with low self-control should form friendships with one another. That is, people with low self-control tend to befriend individuals who also have low self-control, thus resulting in peer groups containing deviant members who should all have low self-control. While these friendships should be of poor quality, Gottfredson and Hirschi (p. 234) state that self-control levels should nonetheless cause deviant individuals to “flock together”. Self-control, therefore, is the basis for friendship formation and offending alike. Going one step further, self-control is also the basis for offending versatility. As such, those with low self-control should come together and coalesce into friendships which contain members who are 1) marked by low self-control, 2) are highly deviant, and 3) highly versatile in their offending patterns. Accordingly, levels of self-control among friends should be related to, and consequential for, versatility in offending among members of a friendship.

Extant research on self-control and friendship formation has, to an extent, explored Gottfredson and Hirschi’s (1990) expectations about friendships and self-control. While two studies suggest that self-control is not attributing to friendship selection preferences ( Boman, 2017 ; Young, 2011 ), other studies find that selection processes are important and may be linked to self-control ( Baron, 2003 ; Chapple, 2005 ; McGloin & Shermer, 2009 ; Simons, Wu, Conger, & Lorenz, 1994 ). However, the natural complexity of studying friendships has limited the ability of such research to examine how versatility in offending varies across friends’ levels of self-control. Despite this, research does demonstrate that individuals who choose to offend tend not to specialize (e.g., Brame, Bushway, Paternoster, & Apel, 2004 ; see also DeLisi, 2005 ). As Pratt et al. (2016) assert, “The reality is that offenders are not all that picky when it comes to their misbehavior” (p. 838). Supporting this notion, low self-control is related to numerous, versatile antisocial outcomes and offenses (e.g., see Hirtenlehner & Kunz, 2017 ). In exploring the relationship between self-control and versatility in deviance, Pratt et al. (2016) found that individuals with low self-control are likely to experience instability in employment, be held back in school, and drop out of school. They also are much more likely than those with high self-control to report experiencing problems with alcohol dependency. Other research exploring versatility and self-control has established important linkages between self-control and being involved in accidents ( Junger & Tremblay, 1999 ), academic cheating ( Bolin, 2004 ), binge eating ( Tangney, Baumeister, & Boone, 2004 ), victimization ( Schreck, 1999 ; Turanovic & Pratt, 2014 ), alcohol-induced sexual assault ( Franklin, 2011 ), and bullying ( Unnever & Cornell, 2003 ). Research has even tied low self-control to ‘drunk dialing’ and the use of profanity in public ( Reisig & Pratt, 2011 ). In short, research using self-control theory demonstrates that “offending is versatile instead of specialized” ( Farrington, 2003 , p. 223; cf. Higgins & Makin, 2004 ).

Social Learning, Specialization, and Versatility

Rooted in Sutherland’s (1947) theory of differential association, Akers’ (e.g., 2009) social learning theory posits that deviance is learned through interactions with one’s differential associates. In these interactions, people develop definitions that are either favorable or unfavorable to crime, and crime occurs when the collective weight of definitions favorable to crime exceeds the weight of definitions unfavorable to crime. Overall, research strongly supports the notion that differential association and social learning explain crime in the manner purported by Sutherland (1947) and Burgess and Akers (1966 ; see Pratt et al., 2010 ).

Applying this argument to versatility in offending, learning perspectives immediately point to a critical factor to the development of definitions – one’s differential associates. Through interactions with differential associates, people learn and model the behavior of those with whom they share meaningful relationships. In the case where a person has meaningful ties to those who are specialized on one type of deviance, one’s definitions are likely to become favorable for that one type of behavior. As such, the theory in this case would expect specialization as there is little reason to believe that this person would be versatile in their offending patterns. On the other hand, if one has meaningful ties to others who commit a wide variety of offenses, then the person will probably be versatile in their offending patterns. The implication, then, is that social learning theory’s element of differential association provides the context through which to understand how social learning theory may explain both versatility and specialization in offending.

The literature on social learning theory and specialization/versatility is surprisingly underdeveloped. Summarizing the lack of research on the topic, Thomas (2016) recently, and correctly, stated that “little is known about the role peers play in promoting offending versatility” (26). Of the research that does exist, we know that peers who are isolated tend to offend less on the whole ( Demuth, 2004 ) and in more specialized patterns ( Thomas, 2016 ), although a small portion of isolates offend extensively and in versatile patterns ( Kreager, 2004 ). For the most part, these findings play into the notion that those with friends tend to offend in versatile ways. Warr (1996 ; also 2002 , pp. 38–39) has also noted that group-level behavior tends to be more specialized than individual-level behavior. That is, offending patterns of people are diverse even though some groups only tend to engage in certain types of behaviors. This premise has received empirical support in the research. Studying egocentric networks (‘send’ networks), McGloin and Piquero (2010) found a strong positive relationship between the extent to which people are integrated into their social networks and specialization at the group, but not individual, level.

Some research also highlights that social learning approaches are consistent when people do learn specialized behaviors, such as in the case of sexual offending against adolescents ( Felson & Lane, 2009 ) and, to a lesser extent, stalking ( Fox, Nobles, & Akers, 2011 ). As such, learning theories have been found to explain both offending versatility and specialization. Since social learning is theoretically equipped to explain both behaviors, the theoretical tenets of the theory appear to be supported. Despite this, there is a need for further research on the topic in the context of friendships. This observation raises attention to the goals of the current study.

Current Study

Using a large dataset consisting of individuals nested within friendship pairs, the current study has three primary research questions. First, drawing on social learning (e.g., Akers, 2009 ) and self-control (e.g., Gottfredson & Hirschi, 1990 ) theories, is versatility in offending more related to a peer’s offending versatility or levels of self-control among members of friendships? Second, does the method of measurement of peer offending versatility change the understanding of the strength of social learning measures on versatility in offending? Specifically, we interchange an indirect, perceptual measure of peer versatility with a measure of self-reported versatility directly from the friend him/herself. Third, and in a similar mindset, does the means through which self-control is measured – through either an attitudinal or behavioral measure – change the understanding of how self-control relates to versatility in deviance? In lieu of offering hypotheses, we employ an exploratory approach to these theoretically-driven research questions and avoid making specific predictions about the relationships we seek to explore.

The data for this project come from a large sample of persons nested within self-identified friendship pairs (dyads). The data, which consists of 2154 undergraduate college students nested within half as many friendships (1077 dyads), was collected in 2009 at a large university in the southeastern United States. To collect the dyadic sample, the lead investigator contacted faculty teaching the 50 highest enrollment classes offered by the university. The instructors were asked whether they would be interested in providing extra credit to students for the completion of a survey that involved dyads. Two dozen instructors said that they would compensate their students with varying amounts of extra credit for participation in the study.

The chief investigator then prepared documentation for each course’s website and made in-class visits to notify potential participants about the opportunity. Respondents were asked to come to a university building where the study was headquartered during set operating hours. Instead of coming to the study alone, however, they were asked to attend with one of their five best friends in undergraduate studies. The procedure of asking for one of the respondent’s five best friends, which drew from precedent developed by the Add Health data (e.g., Haynie, 2002 ; Haynie & Osgood, 2005 ) and the NSCR’s (e.g., Weerman & Smeek, 2005 ) and Kandel’s (e.g., 1978 ) friendship selection procedures, was designed to attract very close friends (i.e., ‘best’ friends) as well as more ‘regular’ friends. Capturing both ‘best’ and ‘regular’ friends aligns with prior research which finds that best friends may exert a stronger behavioral influence on persons than regular friends ( Weerman & Smeek, 2005 ). Upon arrival to the study’s headquarters, dyad members provided informed consent and were then sent to different locations to complete the study.

Once separated, members of the research team provided the friends with identical paper surveys that were pre-coded with a matching dyadic identification number to link them as being members of one dyad. Each survey contained questions about the respondent, the friend, and the friendship. Research team members monitored respondents during survey administration and were instructed to eliminate any potential avenue for communication (e.g., texting) between the friends during the time the survey was being taken. Following completion of the surveys, each dyad member was individually debriefed and exited the study’s headquarters via separate exits.

Many classes in the project were very large, with several classes carrying enrollments of hundreds of students. Although the 24 classes combined to a total enrollment of 5000 persons, the sampling frame’s size cannot be calculated since it is unknown how many of each respondent’s five friends he/she would have considered bringing to the project. Due to the very large number of potential respondents, about one in five ‘friends’ also received extra credit from a selected course. No significant differences were identified between those who did and did not receive extra credit. Despite all demographic characteristics closely matching the target population, females (66% of the sample; 59% of the population) were slightly overrepresented in the sample. The sample is comprised of 1152 women nested within female-only dyads, 444 men nested within male-only dyads, and 558 people nested within split gender dyads. All dyads are independent, meaning that no person was nested within more than one friendship pair. All procedures were approved by the institution’s review board.

Dataset Structure

In the criminological context, dyadic data are unique because models can be estimated that explore how the characteristics of two individual people relate to the target respondent’s behavior. The current project uses a double-entry file (see Kenny, Kashy, & Cook, 2006 ), a type of datafile structure common in dyadic data analysis, to maximize the inferences which can be made. In the double-entry file, the units of analysis are individuals nested within dyads ( n = 2154 persons within 1077 friendships). This creates a situation where each person in the dyad has his/her own line of data and serves as the focal person of interest (called the ‘actor’) whose behavior may be dependent on characteristics of him/herself and another person (the ‘friend’). Stated differently, Person A is the actor who has Person B as a friend, and, inversely, Person B is the actor who has Person A as a friend. For more information on this file structure, see Kenny et al.’ (2006) and Campbell and Kashy’s (2002) work.

Dependent Variable

Self-reported versatility in offending.

The outcome variable in this project, which is designed to capture the extent of versatility in an acto’s offending, required several steps to construct. The data contained 20 different self-reported deviance items that asked the actor about crime over the past twelve months. Each question was worded, “In the past 12 months, how often have you item ” and was measured on the National Youth Survey’s metric of 0 (“never”) to 8 (“two to three times a day”; see Elliott, Huizinga, & Ageton, 1985 ). These 20 self-reported items load onto five distinct constructs of behavior – theft (4 items), vandalism (4 items), violence (4 items), alcohol use and related behaviors (4 items), and drug use and related behaviors (4 items). Confirmatory factor analyses (CFAs) showing evidence of very close fit (all Confirmatory Fit Indices [CFIs] ≥ .95, Tucker-Lewis Indices [TLIs] ≥ .95, and root mean square errors of approximation [RMSEAs] ≤ .06) confirmed the five-factor solution (unreported).

To construct the measure of self-reported versatility, each item was first collapsed into a binary measure where the actor either indicated that he/she engaged in the behavior or refrained from the behavior altogether (0 = did not commit; 1 = committed). Second, each binary item was then summed into a variety index for each construct of behavior, making the range of all five constructs ‘0’ to ‘4’ since each behavioral construct carries four items. Third, this project’s main goal lies in investigating the relationship between versatility in offending and theoretical predictors. This issue more closely adheres to the commission of a wide range of behaviors rather than the frequency of such behaviors. As such, each construct’s variety index was collapsed into a binary measure where a score of ‘1’ indicates the actor committed a deviant act within the purview of each behavioral construct (a score of ‘0’ means the actor did not engage in that construct of deviance whatsoever). Fourth, and finally, the binary measures of construct-specific deviance were summed into the dependent variable, self-reported offending versatility . This variety index has a range of ‘0’ – indicating that the actor’s behavior was totally non-versatile since he/she committed no deviance whatsoever – to ‘5,’ which indicates the actor’s behavior was extremely versatile since he/she engaged in all five constructs of behavior. Higher scores represent a greater offending versatility. Since the mean of this item (M = 1.834) is greater than one, the average person was at least somewhat versatile in their patterns of deviance (see Table 1 for descriptive statistics).

Summary characteristics of the dyadic sample ( N = 2154 people nested within 1077 friendships)

Descriptive characteristics for the actor and friend are identical due to the structure and nesting within the data

Independent Variables

Perceptual peer versatility in offending.

The actor’s perception of the versatility of the friend’s offending serves as the first independent variable. Created to be conceptually similar to the dependent variable, 20 questions asked the actor “In the past 12 months, how often has the friend you attended this study with item ?” The behaviors are the same as those in the dependent variable. Measured again on the NYS metric of ‘0’ (never) to ‘8’ (two to three times a day), these items also load on a 5-factor structure where each construct (theft, vandalism, violence, alcohol use and related behaviors, and drug use and related behaviors) has four items and shows evidence of close fit (unreported CFA fit statistics: all CFIs and TLIs ≥ .95, all RMSEAs ≤ .06).

To create this independent variable, the 20 base perceptual items were collapsed into binary measures indicating whether the actor thought his/her friend engaged in the behavior (scored ‘1’) or did not engage in the behavior (‘0’). These items were summed together for each construct and re-dichotomized to indicate whether the respondent thought his/her friend engaged in any deviance within the respective construct (scored ‘1’) or refrained entirely from deviance within the construct (‘0’). Finally, the binary items for each construct were summed to capture perceptual peer versatility in offending . This measure captures the number of constructs of deviance which the actor thought his/her friend had engaged in over the past year (M = 1.363, SD = 1.250, range 0–5). Higher scores represent greater versatility.

Self-Reported Peer Versatility in Offending

Due to the way the study was designed and the double-entry datafile structure, we are capable of providing an alternative measure of peer versatility that relies on reports directly from the peer him/herself. In addition to the authors of self-control theory disliking perceptual measures of offending (e.g., Gottfredson & Hirschi, 1990 ), research demonstrates that measures of perceptual peer offending (termed ‘indirect’ peer deviance) operate differently in multivariate models than measures of self-reported offending gathered directly from peers themselves (called ‘direct’ peer deviance; see Meldrum, Young, & Weerman, 2009 ).

Accordingly, we include a measure of direct peer deviance that captures self-reported peer versatility in offending . Although the measure captures the versatility of the friend’s offending, it is constructed in an identical manner to the dependent variable. Due to the double-entry data structure, this measure has the same descriptive statistics as the outcome measure (see Kenny et al., 2006 ), although its nesting in the dataset makes it a unique variable (also see Campbell & Kashy, 2002 ).

Attitudinal Self-Control

Two measures of self-control are used in this project. The first, attitudinal self-control , is captured through the frequently-used scale developed by Grasmick, Tittle, Bursik, and Arneklev (1993) . This measure, which contains 24 items, captures the six subdimensions of self-control–impulsivity, a preference for simple tasks, a preference for physical activities, risk-seeking, self-centeredness, and temper – which were defined by Gottfredson and Hirschi (1990) . This average-item-score scale, which fits the data consistently (Cronbach’s α =.84), is coded so that higher scores measure higher self-control levels (M = 2.878, SD = 0.350, range 1–4). The actor’s and the friend’s attitudinal self-control levels are both utilized as independent variables in the forthcoming analysis.

Behavioral Self-Control

Behavioral measures of self-control are preferred by self-control theory’s original authors (see Hirschi & Gottfredson, 1993 ). To capture behavioral self-control , we use the reduced version of the Retrospective Behavioral Self-Control Scale (the ‘RBS’; see Marcus, 2003 ). The original RBS contained 67 items which inquired about behaviors relevant to self-control during the age ranges of 8–13, 14–18, and 19–25 years of age. The items are measured on a scale of 1, indicating the respondent ‘never’ behaved in that manner, to ‘7,’ indicating that he/she ‘always’ behaved that way.

Despite having the advantage that the scale asks about behaviors rather than attitudes, many of the original items on the RBS were tautological because they directly asked about crime. Using item-response modeling in conjunction with face validity tests, Ward, Gibson, Boman, and Leite (2010) reduced the 67 item RBS to 18 items that showed both face and internal validity. Ward and colleagues’ items were used to construct an average-item-response scale – the RBS reduced version (RBS-r) – in this study. The RBS-r is coded so that higher scores capture higher self-control (M = 5.596, SD = 0.687, range 0–7). The items scale consistently ( α = .82), and actor and friend measures of the RBS-r are used as independent variables in forthcoming analyses. The wording of the items can be seen in Appendix Table 4 .

Models are estimated with demographic controls of the actor and the friend. First, we control for the sex (1 = male [33.6% of the sample]; 0 = female) of the actor and the friend. Second, we control for the race of the actor and friend, which is defined as a dichotomy that compares those who are non-white (coded ‘1’; 36.9% non-white) to those who are white (coded ‘0’). Third, we include a standalone measure of whether the respondent identified as being of Hispanic ethnicity (1 = Hispanic [18.6% of the sample]; 0 = non-Hispanic). Fourth, and finally, we include a measure of the age of the actor and the friend, measured as a count (M = 19.339, SD = 1.433).

Analytical Strategy

With naturally nested data, a multilevel analysis is necessary. Accordingly, this study employs the use of two-level, mixed-effects hierarchical linear models. These models fall under the classification of actor-partner interdependence models, a type of analysis specifically designed for dyadic data (see Kenny et al., 2006 ). In this case, a mixed model is necessary because there is variation both within dyads (friends are different from each other) and between dyads (friendships are different from each other). The level 1 equation will include characteristics of the actor and the partner and is the focal level of interest in this study. Level 2 in the forthcoming models is called a ‘grouping’ level, as it simply groups the level 1 equation around the dyadic friendship identification variable.

Very minor amounts of missing data (less than 1% missing on all variables) were imputed using a Markov-chain Monte Carlo imputation technique (20 draws from 200 burn-in iterations). Models using listwise deletion (not reported) showed similar results. All models were estimated with Stata version 14.2.

Primary Findings: Social Learning, Self-Control, and Versatility

Results relevant to the first research question are presented in a series of mixed models in Table 2 . Model 1 regresses the actor’s versatility in offending onto actor measures of perceptual peer versatility, attitudinal self-control ( Grasmick et al., 1993 ), and controls. The actor’s perception of the peer’s versatility is positive and highly significant (b = .511, SE = .021, p ≤ .001), indicating that actors who perceive their peers are more diverse in offending are more diverse themselves. Additionally, the actor’s attitudinal self-control is negative and also significant (b = −.043, SE = .003, p ≤ .001), suggesting that those who have lower levels of attitudinal self-control tend to have a higher versatility in offending. Although most controls do not approach levels of statistical significance, males (b = .337, SE = .054, p ≤ .001) report significantly more offending versatility than women.

Mixed models regressing the actor’s offending versatility onto characteristics of the actor and the friend (attitudinal self-control results; N = 2154)

Model 2 of Table 2 adds friend measures to the level 1 equation. However, no friend measures reach statistical significance, and the overall patterns of significance in the actor effects from Model 1 remain unchanged. However, results do change in Model 3 of Table 2 , which removes the peer effects but adds a measure of self-reported peer versatility captured directly from the peer’s self-reports. This measure reaches high levels of statistical significance (b = .192, SE = .020, p ≤ .001), and the direction indicates that those who have friends who self-report high levels of versatility in their offending are versatile themselves. However, the coefficient strength of the perceptual measure in Model 2 (b = .514) is much stronger than the coefficient in Model 3 (b = .192) with approximately the same standard error, suggesting that the perceptual measure of peer versatility is more impactful than the peer’s self-report. Finally, white (b = −.206, SE = .059, p ≤ .001) male (b = .425, SE = .060, p ≤ .001) actors report significantly higher versatility in offending than non-whites and females, respectively.

The final model in Table 2 , Model 4, once again adds in the friend effects to examine their relationship on the direct measure of versatility in peer offending. Namely, while attitudinal actor self-control is still significant (b = −.056, SE = .004, p ≤ .001), the peer’s level of self-control is unrelated to the actor’s versatility in offending. Besides the peer’s self-reported offending versatility (b = .186, SE = .022, p ≤ .001), no other peer measures reach significance and the actor effects are similar to those in Model 3.

Table 3 presents a similar set of mixed models as reported in Table 2 , but instead removes the attitudinal measure of actor and friend self-control and replaces it with the behavioral measure (the RBS-r). InModel1 of Table 3 , the actor’s perception of the peer’s versatility is significant and positively related to the actor’s offending versatility (b = .519, SE = .021, p ≤ .001). The actor’s behavioral level of self-control is negative and highly significant (b = −.456, SE = .043, p ≤ .001), suggesting that actors with lower behavioral self-control are much more likely to be versatile in their offending. Additionally, males (b = .398, SE = .054, p ≤ .001) and those of Hispanic descent (b = .133, SE = .065, p ≤ .05) are more likely to be versatile. Non-whites (b = −.121, SE = .053, p ≤ .05) and younger (b = −.049, SE = .018, p ≤ .01) actors are less likely to demonstrate versatility.

Mixed models regressing the actor’s offending versatility onto characteristics of the actor and the friend (behavioral self-control results; N = 2154)

Peer measures are added into Model 2 of Table 3 . No peer measures are significantly related to the actor’s versatility in offending, including the peer’s behavioral self-control. However, the inclusion of these measures does reduce the actor’s race and ethnicity to levels of non-significance, although the actor’s perception of the peer’s versatility (b = .518, SE = .022, p ≤ .001) and behavioral self-control levels (b = −.457, SE = .043, p ≤ .001) remain significant at nearly identical levels as in Model 1.

When the actor’s perception of the peer’s versatility is removed and replaced by the peer’s self-reported offending versatility ( Table 3 ‘s third model), the direct measure reaches high levels of statistical significance (b = .200, SE = .020, p ≤ .001) in a positive direction with the actor’s self-reported versatility. The actor’s behavioral self-control coefficient (b = −.623) also increases substantially in magnitude over the prior model (b = −.457). Finally, when peer covariates are added back into the model (Model 4, Table 3 ), the coefficient of direct peer versatility (b = .184) decreases slightly, but maintains high levels of statistical significance. Additionally, lower levels of the actor’s behavioral self-control (b = −.626, SE = .047, p ≤ .001) remain strongly related to versatility in offending. Male (b = .487, SE = .066) and Hispanic actors (b = .161, SE = .07, p ≤ .05) are more likely to offend in a versatile manner, whereas non-white (b = −.179, SE = .068, p ≤ .01) actors and those with non-white friends (b = −.168, SE = .067, p ≤ .05) are less likely to offend in a versatile manner.

Discussion and Conclusions

Drawing from social learning and self-control theories and using data from a large sample of people nested within friendship pairs, this study explored the relationships between specialization and versatility in offending among friendships. Results from a series of multilevel models demonstrated that versatility in offending is related to the actor’s self-control as well as the actor’s perception of his/her friend’s versatility. When friend effects were entered into the equations, the peer’s self-reported versatility also positively related to the actor’s versatility, although the peer’s self-control did not. This same basic pattern of significant findings was observed when the commonly used attitudinal measure of self-control developed by Grasmick et al. (1993) was interchanged with a behavioral measure of self-control developed by Marcus (2003) and refined by Ward et al. (2010) . Despite the similarities in the significance patterns, the actor’s attitudinal self-control had a substantially weaker relationship with offending versatility than the actor’s behavioral self-control. In this section, we discuss the implications of our findings for social learning, self-control, and the broader context of offending specialization and versatility in the context of friendships.

Results from this study carry important implications for self-control theory. While findings demonstrated that the actor’s self-control related to offending versatility as self-control theory would clearly expect ( Gottfredson & Hirschi, 1990 ), the friend’s level of self-control was not significantly associated with the actor’s versatility in offending. There are two ways this can be interpreted. First, the lack of a significant peer effect supports self-control theory because self-control is an intra-individual trait that should seemingly be uninfluenced by external forces. Accordingly, any peer effect should be either inconsequential, spurious, or an artifact of measurement error. As a consequence, the peer’s self-control should not have an effect on actor’s behavior – a theoretical tenet which our results strongly support.

A second interpretation of these results is also possible. The lack of a significant peer self-control effect on the actor’s offending versatility is, in a way, paradoxical. Gottfredson and Hirschi (1990) clearly outline that individuals with low self-control will form friendships with others who also have low self-control. Due to self-control causing a dual process of both friendship formation and offending versatility, the friend’s self-control should be related to characteristics of the actor’s offending because of a strong correlation that should exist between the friends’ levels of self-control. From this point of view, it is theoretically counterintuitive to expect that peer self-control – which should be virtually identical to the actor’s self-control – to be unrelated to offending. Accordingly, the results regarding peer self-control from the first perspective support self-control theory. However, from the second perspective, support is not provided to the theory. It appears that self-control theory’s hypotheses regarding peer effects compete with one another. Stated differently, the theory appears to contradict itself in regard to the meaning of peer influence.

Interestingly, Gottfredson and Hirschi do offer a potential explanation for the peer effect that is based in the concept of opportunity. According to Gottfredson and Hirschi (1990 , p. 92), any specialized offending that occurs among individuals with low-self-control is “determined by convenience and opportunity.” It could be the case that individuals within friendships do have similar levels of self-control but experience varying levels of opportunity to commit crime and/or specialize in it. Indeed, the variation in opportunity among friends (see Osgood & Anderson, 2004 ) could very well explain the lack of a relationship between friend self-control and the actor’s level of offending versatility – a point which future research should explore. The opportunity construct will be imperative to resolving the contradictory expectations from Gottfredson and Hirschi’s (1990) theory regarding how the peer’s self-control should relate to an actor’s behavior.

Following prior literature (e.g., Boman, 2017 ; Evans, Cullen, Burton, Dunaway, & Benson, 1997 ), we included a measure of attitudinal self-control derived from Grasmick et al.’ (1993) work as well as a behavioral measure (from Marcus, 2003 and Ward et al., 2010 ; see Appendix Table 4 for more information). Despite similarity in the overall (in)significance patterns of the peer self-control effect for both the attitudinal and behavioral measures, there were differences for the actor’s self-control that were measurement dependent. While both the attitudinal and behavioral measures were significant, the coefficients of the actor’s behavioral self-control were much stronger than the coefficients of attitudinal self-control. As such, our findings demonstrate empirical support to Hirschi and Gottfredson’s (1993) preference for behavioral measures of self-control while also highlighting the utility of different operationalizations of the general theory’s primary construct.

In addition to carrying new and unique findings for how self-control relates to versatility in deviance, our results also carry implications for Burgess and Akers’ (1966 ; also Akers, 2009 ) theory of social learning. Results across all models clearly demonstrated that the construct of differential association is of importance in relation to offending versatility. Specifically, models using a perceptual measure of the versatility of the peer’s offending demonstrated that the differential association-informed construct was positive in direction and highly statistically significant. As such, the models suggest that actors tend to offend in more versatile ways when they think their peers are also versatile and, inversely, that actors tend to be more specialized when they believe their friends to be highly specialized. When the measure of differential association was changed from a perception of the peer’s deviance to the peer’s self-reported deviance, the results were largely the same: The measure was significantly related to offending versatility and positive in direction. Regardless of how the versatility construct is operationalized, differential association and social learning theories are supported (see, generally, Boman, Stogner, Miller, Griffin, & Krohn, 2012 ; Meldrum & Boman, 2013 ; Young, Rebellon, Barnes, & Weerman, 2014 ).

Overall, findings from the perceptual peer and peer’s self-reported versatility measures demonstrate a considerable amount of support for social learning and differential association theories. Despite the measurement technique, the measure of differential association related strongly to the actor’s offending versatility. While social learning theory ( Akers, 2009 ) would expect the perceptual measure of peer versatility to be the most meaningful on the outcome, the theory would also hypothesize that the peer’s self-reported versatility would be influential as well ( Akers, 2009 , pp. 117–120). Differences in the coefficient sizes between the two measurement methods could easily be interpreted as being supportive of this very specific hypothesis from Akers. As such, social learning theory has received strong support as differential association relates to offending versatility regardless of how the construct is measured.

As research on social learning and specialization and versatility moves into the future, an important avenue of inquiry may lie in recognizing that some behaviors are more ‘groupy’ than others. That is, some behaviors are more likely to be committed in groups than other types of behavior. The term ‘groupy’ was developed by Warr (2002) and has become used in conjunction with the related term of ‘non-groupy’ (see Boman & Gibson, 2016 ) that completes Warr’s taxonomy. Examples of groupy behavior include vandalism, substance use, and status crimes. On the other hand, examples of non-groupy behavior include theft, certain types of serious assault, and sexual battery (see Warr, 2002 ). Research on the groupy and non-groupy issue has proven to be imperative in other contexts in criminology (e.g., Boman & Gibson, 2016 ; Boman & Mowen, 2018 ; also see Beaver et al., 2011 for a related study), and there is ample reason to believe that the same issue may also be of importance in the specialization and versatility context. The groupy/non-groupy taxonomy may also help research segue into the notion of friendship-level specialization, an important theoretical and policy-based issue that – unfortunately – has remained largely unexplored by criminologists to date (for the exceptions, see McGloin & Piquero, 2010 ; Thomas, 2016 ; Warr, 1996 ). There are also measurement issues surrounding perceptual peer specialization and versatility that are immediately relevant to the difference in the coefficient magnitude between the perceptual and direct peer specialization measures. Similar in concept to issues surrounding peer deviance, there has been no literature to date investigating how peer specialization could be or should be measured. This literature would be very useful, and it could incorporate Warr’s groupy and non-groupy taxonomy to determine how the nature of specialization impacts our understanding of specialization and versatility in general and in a friendship context specifically.

Despite some valuable findings and necessary future directions regarding how social learning and self-control relate to specialization and versatility in offending among friends, the current study has some notable limitations. First and foremost, the current data come from a cross-section of students attending only one American university. Not only does this limit our ability to determine causal order between our key variables of interest, our findings are likely to be of limited generalizability to those in other populations. An overrepresentation of females may also have limited the variance in our dependent variables. Second, while a strength of the current study is the dyadic design, dyads are an inherently limited unit of analysis. People typically have several friends, meaning they are nested within multiple dyads. Unfortunately, our data contain only one of a person’s potentially many dyadic friendships. A similar analysis using social network data would be valuable as it would build upon recent work by Thomas (2016) and McGloin and Piquero (2010) . Such a study should seek to explore other methods of capturing specialization, including the methods developed by Osgood and Schreck (2007) as well as the method by DeLisi et al. (2011) . Third, our outcome and key predictor measures are constructed from only twenty items spanning five types of offending. We highlight that there are different types of control ( DeLisi & Vaughn, 2014 ) and many more types of offenses, meaning the variability in these measures is limited. Although our study has some limitations, the findings nonetheless further develop the state of knowledge as to how offending versatility relates to constructs derived from two of our field’s most prominent theories.

Findings from this study offer strong support to both self-control ( Gottfredson & Hirschi, 1990 ) and social learning ( Akers, 2009 ) perspectives’ expectations on offending specialization and versatility. However, what is most apparent is the many future directions of necessary exploration to which findings from this study raise attention. Future research should seek to explore how self-control and opportunity ( Osgood & Anderson, 2004 ) interact for versatility in the friendship context. Future research on this topic also has the ability to remediate a notable inconsistency regarding how peer effects should operate within the context of self-control theory. This study highlights that the lack of a peer effect supports the theory. But, at the same time, low self-control theoretically causes friendships to form while also causing both offending and versatility in offending, forming a strange paradox in how Gottfredson and Hirschi view friends and friendships. Additionally, certain behaviors are more (or less) likely to be committed in groups than others ( Warr, 2002 ), and the notion of friendship-level specialization is emphasized (see McGloin & Piquero, 2010 ; Warr, 1996 ; 2002 ). Perhaps people engage in specialized behaviors when around only certain friends – that is, a person may only consume alcohol with one friend, and may only use opioids with another friend (see Warr, 2002 , p. 38). If this were the case, then offending may appear versatile overall (e.g., Farrington, 2003 ) even though friendship-level contexts may carry overlooked, but nonetheless important, patterns of specialization. If this were true, the current understanding that people ‘do not specialize’ in offending may be incorrect at worst or misleading at best. Either way, the notion of friendship-level specialization must take precedence in the research on specialization and versatility due to the established importance of peers and the applicability of friendship-level events to many different types of theory.

Acknowledgements

This research was supported in part by the Center for Family and Demographic Research, Bowling Green State University, which has core funding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (P2CHD050959).

John Boman is an Assistant Professor at Bowling Green State University in the Department of Sociology. His research focuses on the roles of interpersonal influences, and particularly peers and friends, on crime, deviance, and substance use over the life-course. His recent work appears in Criminology , the Journal of Criminal Justice , and the Journal of Youth and Adolescence.

Thomas J. Mowen is an Assistant Professor in the Department of Sociology at Bowling Green State University. His research broadly examines the consequences of school security and punishment as well as the process of prison reentry. His recent research has appeared in Criminology, Justice Quarterly, Journal of Quantitative Criminology, and Journal of Research in Crime and Delinquency.

George E. Higgins is Professor in the Department of Criminal Justice at the University of Louisville. He received his Ph.D. in Criminology from Indiana University of Pennsylvania in 2001. His most recent publications appear or are forthcoming in Journal of Criminal Justice, Criminal Justice and Behavior, Justice Quarterly, Deviant Behavior, and Youth and Society.

Wording of items in the behavioral self-control RBS-r scale

All items measured on a scale of 1–7 (1 = never; 2 = once; 3 = two or three times; 4 = fairly many times; 5 = often; 6 = very often; 7 = always) . For more information, see Marcus (2003) and Ward et al. (2010)

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