case study of behavioral theory

4 Fascinating Classical Conditioning & Behaviorism Studies

Did you experience a rumble in your stomach, even before you entered the dining hall and saw any food?

If so, your unconscious behavior was actually a real-life example of classical conditioning.

This article provides historical background and theory into classical conditioning and behaviorism. You will also learn how these theories are applied in today’s society and still hold considerable importance when learning about human behavior.

Before you continue, we thought you might like to download our three Positive Psychology Exercises for free . These science-based exercises will explore fundamental aspects of positive psychology including strengths, values, and self-compassion, and will give you the tools to enhance the wellbeing of your clients, students, or employees.

This Article Contains:

Classical conditioning in psychology history, pavlov’s dog experiment explained, a look at the birth of behaviorism, watson’s little albert research, skinner’s conditioning studies, 4 contemporary findings and case studies, resources from positivepsychology.com, a take-home message.

To understand classical conditioning theory , you first need to understand learning. Learning is the process by which new knowledge, ideas, behaviors, and attitudes are acquired (Rehman, Mahabadi, Sanvictores, & Rehman, 2020). Learning can occur consciously or unconsciously (Rehman et al., 2020).

Classical conditioning is the process by which an automatic, conditioned response and stimuli are paired (McSweeney & Murphy, 2014). There are references in the classical conditioning literature to this being stimulus and response behavior (McSweeney & Murphy, 2014).

A famous work on classical conditioning is that by Russian physiologist Ivan Pavlov, born in 1849. His influence on the study of classical conditioning has been tremendous. He won the Nobel Prize in Physiology or Medicine for this piece of research (The Nobel Prize, n.d.). Classical conditioning was discovered accidentally and was referred to as ‘Pavlovian conditioning’ (Pavlov, 1927).

In this related article you will find practical classroom examples of Classical Conditioning .

Technical terms

Pavlov (1927) developed the following technical terms to explain the process of classical conditioning and how it works.

• The  unconditioned stimulus (UCS) occurs naturally and automatically, and unconditionally triggers a response.
• The unconditioned response (UCR) is the unlearned response. It occurs naturally as a response to the UCS.
• The conditioned stimulus (CS) is a previously neutral stimulus that after being associated with the UCS, results in the triggering of a conditioned response.
• The conditioned response (CR) is a response to the CS being associated with the UCS. The CR is a response that is made to the CS alone and without the UCS being required.

One interesting observation Pavlov made was that just before being given food, the dogs began to salivate. Sometimes this was just from the sight of the lab coats of the technicians feeding them. This made Pavlov wonder why the dogs salivated when there was no food in sight.

Pavlov decided to undertake a series of experiments with the dogs to investigate these observations. Pavlov rang a bell each time, just before feeding the dogs. At first there was no response. Then when the food came out, the dogs realized the sound of the bell meant food, and they salivated. After that, the sound of the bell on its own caused the dogs to salivate. They associated the bell with the arrival of food.

The following diagram (Figure 1) shows the different stages in the classical conditioning process in Pavlov’s (1897) dog experiments.

Classical conditioning has its roots in behaviorism. Behaviorism measures observable behaviors and events (Watson, 1913; Watson 1924).

John B. Watson, like Pavlov, investigated conditioned neutral stimuli eliciting reflexes in respondent conditioning (Watson & Rayner, 1920). Behaviorism views the environment as the primary influence upon human behavior, not genetic factors (Thorndike, 1905).

Behaviorism derived from the earlier research of Edward Thorndike (1905) and the Law of Effect in the later 19th century. This looked at consequences that strengthen and weaken behavior.

It attempted to replace depth psychology (Vladislav & Didier, 2018), considered having roots in the theories of Sigmund Freud, Carl Gustav, and Alfred Adler (Lewis, 1958). Depth psychology had difficulty testing predictions experimentally (Vladislav & Didier, 2018).

B. F. Skinner, an American psychologist, developed his own stance on the behaviorist approach, known as radical behaviorism (Schneider & Edward, 1987). He suggested that cognitions and emotions have the same variables of control as observed behavior (Mecca, 1974).

His technique was known as operant conditioning . This deals with reinforcement and punishment to increase or decrease the performance of behavior (Skinner, 1953).

Watson showed that humans can also be conditioned similarly to animals (Beck, Levinson, & Irons, 2009).

Watson used a small infant in his experiments referred to as Little Albert (Watson & Rayner, 1920). The child was exposed to different stimuli, including a rabbit, dog, wool, mask, monkey, and burning newspapers to see his reactions.

Little Albert showed no fear of the objects. It was not until the objects were paired with a loud noise (banging a metal bar with a hammer) that he began to cry after being shown a white rat. The child then expected to hear a frightening noise when he saw the white rat (neutral stimulus) on its own.

The white rat became the conditioned stimulus, and the emotional response of crying became the conditioned response. This is similar to the distress (unconditioned response) he initially displayed to the noise. Further studies showed Little Albert becoming distressed with furry objects and even a Santa Claus mask (Watson & Rayner, 1920).

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B. F. Skinner (1948) conducted various experiments on rats in a box known as the ‘Skinner Box.’ At first, he put a hungry rat in the box that wandered around and discovered a lever. The rat eventually realized that after it pressed the lever, food was released into the box.

The rat then pressed the lever again each time it was hungry. It then pressed the lever immediately each time it was placed in the box, which showed that it was conditioned. Pressing the lever is the operant response, and the food is the reward (Skinner, 1948).

This type of experiment is also known as instrumental conditioning learning (Ainslie, 1992). The response is instrumental in receiving food. This experiment highlighted positive reinforcement (Skinner, 1948).

Skinner then undertook another experiment with rats. He put the rat in a similar box, and this time an electric current was used. As the rat became distressed and ran around the box, it accidentally knocked the lever. This automatically stopped the electric current.

The rat then learned to head first to the lever to prevent the discomfort of the electric current. Pressing the lever is the operant response, and stopping the electric current is its reward. This experiment highlighted negative reinforcement (Skinner, 1951).

Let’s take a look.

1. Classical conditioning and phobias

The classical and operant conditioning models developed by Pavlov, Watson, and Skinner are very relevant in contemporary society today. They can help explain the etiology and treatment of phobias in humans (Davey, 1992).

A phobia is a persistent and irrational fear to a specific situation, object, or activity (American Psychological Association, n.d.).

As an example, consider aerophobia, which is the fear of flying. People who have this phobia have an intense fear and anxiety around flying, sometimes at the mere thought of an airplane.

People with this phobia may avoid flying as much as possible to limit their distress. A closer look at the reason why people develop a fear of flying shows that a bad experience of taking off, terrible weather when flying, or turbulence may have been a crucial factor in the past (Clark & Rock, 2016).

We can think back to Pavlov’s dog experiments to understand more. It seems that the sight or thought of a plane has become the conditioned stimulus, and the fear of flying is the conditioned response.

Effective treatments for a phobia of flying often use the same principles of classical conditioning and learning (Rothbaum, Hodges, Lee, & Price, 2000). Therapists might activate the fear structure by exposing the person to the feared stimuli. This will elicit a fearful response (Rothbaum et al., 2000).

Once the exposure has been undertaken several times, in a process known as habituation (Bouton, 2007), the phobia is no longer reinforced (known as extinction) and eventually disappears (Miltenberger, 2012). In this way, a phobia can be reversed with the same principles of classical conditioning.

2. Classical conditioning and social anxiety

Social anxiety disorder is an anxiety disorder that has characteristics of extreme and persistent social anxiety that causes distress and prevents someone from participating in social activities (American Psychological Association, n.d.).

Social anxiety disorder may be triggered by some kind of stressful event early in a child’s life, such as being bullied, family abuse, or some type of public embarrassment (Erwin, Heimberg, Marx, & Franklin, 2006).

The dominant psychological treatment for anxiety disorders also involves repeated exposure, similar to the treatment of phobias described above.

Systematic desensitization is a gradual exposure to the phobic stimulus, perhaps including a gradual exposure to social situations.

Flooding is an alternative approach and not gradual. It is an immediate exposure to the most frightening aspect of the situation (American Psychological Association, n.d.), such as attending a large gathering.

Systematic desensitization and flooding can be undertaken in vitro (imagining exposure to the phobic stimulus) or in vivo (actually exposure to the phobic stimulus). Menzies and Clarke (1993) found that in vivo techniques are much more successful. In vitro can be used if it is more practical.

This is yet another example of how acquired fears can be removed by the principles of classical conditioning.

3. Operant conditioning and gambling

Gambling works based on operant conditioning, as gambling behavior is reinforced, increasing the likelihood that the behavior will be repeated. Gambling can become an addiction and is defined as such in the Diagnostic and Statistical Manual of Mental Disorders (American Psychological Association, n.d.).

Griffiths (2009) suggests that some types of gambling, such as slot machines, are addictive because financial rewards can be gained from pulling the lever. He also describes many other rewards, such as physiological rewards (adrenaline rush of winning), psychological rewards (excitement), and social rewards (praise from peers).

Aasved (2003) found that gamblers continued to gamble and repeat these experiences. Gambling is not prone to extinction, as it is reinforced partially (not every time), which makes the gambler repeat the behavior.

Gambling involves only partial reinforcement, as only a portion of responses are reinforced. The lack of predictability keeps people gambling. Does this remind you of Skinner’s study with rats and the rewards of food they gained from pressing the lever?

There are many treatments for gambling addiction. Treatment that combines the principles of Cognitive-Behavioral Therapy and in vivo strategies of imagining the consequences of gambling behaviors can be effective for problem gamblers (Bowden-George & Jones, 2015).

4. Operant conditioning and substance misuse

Some individuals use alcohol and drugs because of the pleasant positive feelings they gain from the experience. If they compulsively repeat the experience over time to achieve the same rewarding stimuli, the adverse consequence can be addiction (Angres & Bettinardi-Angres, 2008).

Aversion therapy (American Psychological Association, n.d.) is one way of eliminating addictions, through association with noxious and unpleasant experiences (Brewer, Streel, & Skinner, 2017; Platt, 2000). It is based on operant conditioning principles.

Aversion therapy involves pairing the unwanted and addictive behavior with an unpleasant experience. As an example, someone could be administered a medication that causes them to feel nauseous and vomit if they consume alcohol.

After aversion therapy, alcohol may be associated with the feeling of nausea, and so the person does not want to repeat this behavior (Brewer, Meyers, & Johnson, 2000).

Once again, this resembles the technique used by Skinner, when the rats were exposed to an electric shock and learned to press a level to avoid the experience.

What every person can learn from dog training – Noa Szefler

Throughout our blog, you’ll find many resources to help your clients address negative habits unconsciously acquired through repeated conditioning.

The tools below can help your clients become more aware of these habits and behaviors and help them gain control over their lives.

• Graded Exposure Worksheet This worksheet invites clients to rank their phobias from least to most feared as a first step toward conducting an exposure intervention.
• Building New Habits This worksheet succinctly explains how habits are formed and includes a space for clients to craft a plan to develop a new positive habit.
• Action Brainstorming This exercise helps clients identify, evaluate, and then break or change habits that may be getting in the way of making desired changes or moving closer to goals.
• Changing Physical Habits This worksheet helps clients reflect on their vulnerabilities and habits surrounding aspects of their physical health and consider steps to develop healthier habits.
• Reward Replacement Worksheet This worksheet helps clients identify the negative consequences of behaviors they use to reward themselves and select different reward behaviors with positive consequences to replace them.

If you’re looking for more science-based ways to help others enhance their wellbeing, this signature collection contains 17 validated positive psychology tools for practitioners. Use them to help others flourish and thrive.

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Classical and operant conditioning had great significance on the birth of behaviorism.

Classical conditioning has proven to be most valuable in understanding the acquisition of negative and unwanted behaviors such as phobias, anxiety, and addictions.

It is also valuable in providing people with treatment, as the same principles are used to undo inadvertently developed behaviors. These new treatments include exposure therapy, aversion therapy, systematic desensitization, and flooding.

We hope you enjoyed reading this article and will be able to help your own clients make the changes they need with the recommended resources.

We hope you enjoyed reading this article. Don’t forget to download our three Positive Psychology Exercises for free .

• Ainslie, G. (1992). Picoeconomics: The strategic interaction of successive motivational states within the person . Harvard University Press.
• American Psychological Association. (2021). Dictionary of psychology. 
• Angres, D. H., & Bettinardi-Angres, K. (2008). The disease of addiction: Origins, treatment, and recovery. Disease-A-Month , 54 (10), 696–721.
• Aasved, M. (2003). The sociology of gambling (vol. 2). Charles C Thomas.
• Beck, H. P., Levinson, S., & Irons, G. (2009). Finding Little Albert. American Psychologist , 64 , 605–614.
• Bouton, M. E. (2007). Learning and behavior: A contemporary synthesis . MA Sinauer.
• Bowden-George, H., & Jones, S. (2015). A clinician’s guide to working with problem gamblers . Routledge.
• Brewer, C., Meyers, R., & Johnson, J. (2000). Does disulfiram help to prevent relapse in alcohol abuse? CNS Drugs , 14 , 329–341.
• Brewer, C., Streel, E., & Skinner, M. (2017). Supervised disulfiram’s superior effectiveness in alcoholism treatment: Ethical, methodological, and psychological aspects. Alcohol and Alcoholism , 52 (2), 213–219.
• Clark, G. I., & Rock, A. J. (2016). Processes contributing to the maintenance of flying phobia: A narrative review. Frontiers in Psychology , 7 , 754.
• Davey, G. C. (1992). Classical conditioning and the acquisition of human fears and phobias: A review and synthesis of the literature. Advances in Behaviour Research and Therapy , 14 (1), 29–66.
• Erwin, B. A., Heimberg, R. G., Marx, B. P., & Franklin, M. E. (2006). Traumatic and socially stressful life events among persons with social anxiety disorder. Journal of Anxiety Disorders , 20 , 896–914.
• Griffiths, M. D. (2009). The psychology of gambling: A personal overview. Psychology Review , 16 (1), 25–27.
• Lewis, J. W. (1958). A survey of Adler’s writing. New Scientist , 4 (83), 224–225.
• McSweeney, F. K., & Murphy, E. S. (2014). The Wiley Blackwell handbook of operant and classical conditioning . Malden.
• Mecca, C. (1974). Radical behaviorism: The philosophy and the science . Authors Co-operative.
• Menzies, R. G., & Clarke, J. C. (1993). A comparison of in vivo and vicarious exposure in the treatment of childhood water phobia. Behavior Research and Therapy , 31 (1), 9–15.
• Miltenberger, R. (2012). Behavior modification, principles and procedures (5th ed.). Wadsworth.
• The Nobel Prize. (n.d.). Retrieved on June 11, 2021, from https://www.nobelprize.org/prizes/medicine/1904/pavlov/facts/
• Pavlov, I. P. (1897). The work of the digestive glands . Griffin.
• Pavlov, I. P. (1927). Conditioned reflexes: An investigation of the physiological activity of the cerebral cortex . Oxford University Press.
• Rehman, I., Mahabadi, N., Sanvictores, T., & Rehman, C. (2020). Classical conditioning . StatPearls. Retrieved June 2, 2021, from https://www.ncbi.nlm.nih.gov/books/NBK470326/
• Rothbaum, B. O., Hodges, L. S., Lee, J. H., & Price, L. (2000). A controlled study of virtual reality exposure therapy for the fear of flying. Journal of Consulting and Clinical Psychology , 68 (6), 1020–1026.
• Skinner, B. F. (1948). ‘Superstition’ in the pigeon. Journal of Experimental Psychology , 38 , 168–172.
• Skinner, B. F. (1951). How to teach animals . Freeman.
• Skinner, B. F. (1953). Science and human behavior . MacMillan
• Thorndike, E. L. (1905). The elements of psychology . A. G. Seiler.
• Watson, J. B. (1913). Psychology as the behaviorist views it. Psychological Review , 20 , 158–177.
• Watson, J. B. (1924). Behaviorism . People’s Institute.
• Watson, J. B., & Rayner, R. (1920). Conditioned emotional reactions. Journal of Experimental Psychology , 3 (1), 1–14.
• Vladislav, S., & Didier, G.J. (2018). Dark religion: Fundamentalism from the perspective of Jungian psychology . Chiron.

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Behaviourism

How would you solve these behaviour issues without using behaviourist techniques?      

Room Profile

Non-traditional classroom with no desks and a high-risk environment with very expensive equipment and supplies.

Class Profile

• Class of 30 grade 9 students consisting of 6 girls and 24 boys.
• Because it’s a pandemic year, students don’t get their choice of electives so only 3 students actually chose this class as their elective
• 16 designations total
• 6 IEPs - ranging from needing written instructions to having to keep them at your side and a close eye on them for the safety of the student and those in the classroom
• No EA or student aide help
• 2.5 hour class every day for 10 weeks

Description of Behaviours

Every other word uttered by students is a swear and they are incredibly disrespectful toward themselves, each other, the teacher, and the physical environment. One student is so keen on being in the room that they won’t let the teacher talk without interrupting with questions. Three other students keep talking to their neighbours and distracting them regardless of how many times the teacher waits for silence (which ends up about 25 minutes the first time on the first day). Two students refuse to put their phones away claiming they can be on them because of their IEPs; however, they cannot. One student won’t sit down and is physically throwing things around the classroom. This student’s IEP specifies that the teacher has to make sure they are seated very close to them and not to let the student “get away” with anything.

The teacher works on respectful language and discusses code switching, specifically how the classroom has different norms and behavioural expectations than outside of school and students must “switch” to adhere to these expectations when in the classroom. Emails are sent home about language use. The teacher also sits the class down for a minimum of 30 minutes each day to discuss appropriate behaviour and language in class (this continues for the first three weeks of the quarter as behaviour does not change enough to do any curriculum work). The teacher has the class come up with the following list of disciplinary measures increasing in severity:

• 1st offense: Verbal warning
• 2nd offense: Verbal warning and student moved from current location
• 3rd offense: Student sent outside of classroom
• 4th offense: Student sent outside and email home
• 5th offense: Student sent to office and email home
• 6th offense: Student removed from class      

The space is split into two parts, the classroom area and performance area. Students are not to use the performance area due to the pandemic and cleaning load of the janitors. The teacher puts tape lines on the carpet to distinguish the classroom space, but these are ignored. Emails are sent home detailing necessary classroom boundaries for the health and safety of students in the space. Chairs are put up above the lines with signs on them noting the boundaries, but these are also ignored. Emails are again sent home and administration is notified. Despite all these efforts, the behaviour persists.          .

Second week

The principal comes in to talk to the class. The behaviour continues, but the teacher notes that the use of language has gotten better.

The teacher pulls five senior students out of their classes for one day and divides the class into separate, carefully curated, groups. The teacher also arranges for a peer-tutor to come work with one student, and another is sent to the support room. Two other students are sent to the construction shop to work with the shop teacher. Everyone is successful for one hour. However, the behaviour continues when everyone is back in the classroom together. The teacher removes the students from the classroom and goes into library space with the librarian and vice principal present.

Fourth week

The Library is booked this week so the class is moved primarily outside, as it is safer to be outside during the pandemic anyway. Little to no actual classwork has happened so far.

Traditional classroom with table groups, reading area, teacher desk, and three computer stations

• Class of 30 grade 6 students consisting of 10 girls and 20 boys
• 10 designations total
• 6 IEPs - ranging from needing written instructions to having to keep them at your side and a close eye on them for the safety of the student and others in the classroom

Students exhibit a wide array of disruptive behaviours. The majority of the class is running around, yelling at each other, using disrespectful language or derogatory terms to address one another, and throwing papers and materials across the room. When the teacher tries to address the students, only a handful pay attention and listen for instructions. When the teacher asks for silence, some of the students keep talking to each other, while others keep interrupting the teacher and moving around the classroom. One student with a designation refuses to stop playing games on his phone, claiming he can use it because of his IEP accommodations; however, this student’s IEP specifies that the student should be seated very close to the teacher and to not let him “get away with anything.” Despite the teacher’s efforts, the majority of students won't remain silent or still, mocking the teacher whenever they speak. It takes the teacher 25 minutes to get the students' attention and for them to be relatively quiet. The lesson is not effective since most students tend to be distracted and off-task.

The teacher works on respectful language and discusses code switching, specifically how the classroom has different norms and behavioural expectations than outside of school and students must “switch” to adhere to these expectations when in the classroom. Emails are sent home about language use and respectful behaviour. The teacher also sits the class down for a minimum of 20 minutes each day to discuss appropriate behaviour and language in class (this continues for the first three weeks of the quarter as behaviour does not change enough to do any curriculum work). The teacher has the class come up with the following list of disciplinary measures increasing in severity:

Students are not to use the computers due to the pandemic and cleaning load of the janitors. The teacher puts tape lines on the carpet to distinguish the classroom space, but these are ignored. Emails are sent home detailing necessary classroom boundaries for the health and safety of students in the space. Chairs are put up above the lines with signs on them noting the boundaries, but these are also ignored. Emails are again sent home and administration is notified. Despite all these efforts, the behaviour persists.

The teacher pulls five students out of their classes for one day and divides the class into separate, carefully curated, groups. The teacher also arranges for a peer-tutor to come work with one student, and another is sent to the support room. Two other students are sent to the library to work with the librarian. Everyone is successful for one hour. However, the behaviour continues when everyone is back in the classroom together.

The teacher decides to move the class outside as it is safer to be outside during the pandemic anyway. Little to no actual classwork has happened so far.

Behaviourism on Station 12?

Congratulations Earthling!

As one of Earth’s top teacher candidates, you have been selected to take a tour of Station 12, one of the most advanced elementary schools on Mars! As your friendly Martian tour guide, I’ll be showing you how our education system has advanced to be one of the best in the galaxy! In honesty, our progress is all thanks to you, and your fellow Earth-dwellers. You see, about 50 years ago, we received a time capsule from Earth containing tons of interesting information, sounds, and images! In addition to learning about Justin Bieber, apparently one of Earth’s greatest poets, we learned all about Behaviorism and the perils of dehumanizing our young learners through rewards and punishments. Anyways, that’s enough jibber-jabber, where are my Martian-manners! Let’s go check out Station 12 and you can see for yourself!

As you enter Station 12, you immediately notice the absence of any shiny trophy cases that commonly adorn the lobbies of schools on Earth. You think to yourself: “I guess Martians truly don’t offer rewards for certain behaviours, at least in terms of athletics.” Noticing your curiosity, your friendly Martian turns to you and says, “We don’t use any objective forms of rewards or punishments in our classrooms! We understand that if a student receives a reward or punishment for their behaviour, they may not develop intrinsic motivation for learning.”

As you continue to walk through the hallways of Station 12, you get glimpses of different classroom environments and teaching practices. Interestingly, you don’t notice any signs of grades, stars, or points systems being used in the classrooms. On the surface, the students also seem to be completely engaged and intrinsically motivated.

As you round the next corner, your tour guide invites you into a classroom where students are just about to return from recess and continue working on their independent research projects. As the students enter the classroom on time, the teacher is giving them a big, gleaming smile. After the students are settled, you begin walking around the classroom and learning about their projects. You discover that one student is learning about Earth and another about the gravity on the Moon. The students are at different stages of their projects and some are still deciding on their topics. You overhear one student inform the teacher that they have decided to study the constellations closest to Mars. As an avid astronomer, the teacher excitedly says, “I think that is a wonderful choice!” Just then, a student enters the classroom 10 minutes late from recess. The teacher lets out a quick “hmm” and shows the slightest suggestion of a frown. Your Martian tour guide turns to you and says, “Did you see that!? No detention for arriving late to the classroom!” Before you can respond, you notice another student beginning to get distracted from their work. You watch as the teacher walks over to a student sitting beside them and, with a warm smile, says, “Great job! I’m so happy you are working hard today and staying focused. I am so proud!” Interestingly, you notice the distracted student begin working again. Another student approaches the teacher and says, “I’ve decided to change my topic to the gravitational pull of the Moon!” Hearing this, the teacher says, “That's a clever idea!” and offers them a quick wink and a warm smile as the student bounces away, seemingly happy with the interaction. Just as you’re about to leave the classroom, you watch as another student explains to the teacher that they have decided to research Emily Carr and the emotions her paintings surface in both humans and Martians. Just as you exit the classroom, you watch the teacher scrunch their noise ever so slightly and say, “Oh. Okay. That’s a good choice,” before immediately moving their attention to another student.

As you leave the school, your Martian tour guide turns to you and says, “So!? What do you think? Pretty impressive, eh? We learned from the time capsule and don’t use any forms of rewards or punishments!” Before you can respond, you are awoken by one of your friends. You’re in EPSE 308 and it’s your turn to discuss your perspectives on Behaviourism. Good luck, Earth-dweller!

Possible Discussion Questions

• In the classrooms on Station 12, you were informed that there were no objective forms of rewards or punishments for students' behaviour. Did you notice any subtle (maybe even unconscious) forms of behaviourism?
• As a teacher candidate, you may be motivated to cultivate a classroom environment that fits your needs and values as a teacher. In this case study, the teacher did this by encouraging students to attend class on time, stay engaged in their work, and pick topics that they themselves deemed worthy. Are these subtle forms of behaviourism more or less harmful, compared to more tangible and objective rewards and punishments? Explain your reasoning.
• As a future teacher, how might you become more aware of your subconscious values and goals for your classroom? How will you manage them in your classroom?
• What do you see as the pros and cons of behaviourism?

Dear Colleague

I can’t imagine you have an answer to this question, but you seem to have been thinking a lot about how to motivate your students and when it comes to this, I’m at a total loss! I thought I had it all figured out, but no – my plan to motivate my students has totally backfired. Help!

I’m teaching seventh grade language arts for the first time this year, and one goal of mine going into this term was to encourage my students to become independent readers. Well, lucky for me, the school librarian, Ms. Daniels, had a program set up this year to do just that! You see, there’s a new book coming out at the end of the year – it’s the latest in a series of young adult novels that’s all the rage right now. Vampires, wizards, a dystopian world – this series has got it all. Anyway, the school librarian KNOWS that this book will be a hot commodity the moment it’s released. When the last in the series came out, she had about fifty holds on it the second she entered it into the library catalogue!

Ms. Daniels devised a system to encourage independent reading. It’s simple: each time a student reads a book from the library – any book – they fill out a worksheet to reflect on it and show they’ve read it. It's just a few questions, asking for a brief plot summary, something they liked about the book, something it made them think about – things like that. Anyway, each time a student hands in a worksheet on a book they’ve read, they get a point, or points, depending on the length of the book. You get one point if you read a book that’s at least 100 pages, two if you read a book that’s at least 200 pages, three if it’s more than 300 pages – you get the idea. The student in the school who has the most points at the end of the year wins a copy of that new young adult novel that everyone wants. It’s bound to fly off the shelves and be sold out for weeks, so they’ll be one of the first to get it!

Well, since I’m teaching language arts this year, I thought I’d supplement Ms. Daniels' competition with some extra motivation – to really get my students wanting to read. After all, not every student in my class is a fan of this series. So, I told my class that for every reading worksheet they hand in to the librarian, they'll also get a bonus mark they can add to their final assignment for the year. It would never change their grade significantly, but hopefully just enough to get them reading. Simple, right?

It all seemed to be going smoothly at first. In the beginning, Bilal was the student who was gaining the most points. He's a high achiever and has always been an avid reader, so that wasn't surprising. But then I had some unexpected runner-ups. A few students who were otherwise struggling in my class, Andy and Sobiga, started gaining more points, and fast! They were giving Bilal a run for his money.

At first, I was thrilled! But that all changed on Friday afternoon. Bilal and Andy had been close friends all term, but on Friday during class, they seemed to have a falling out. Then Bilal lingered after the bell to talk to me. Bilal declared: "Andy is cheating!" When I asked him what he meant, he explained: "He doesn't actually READ any books! He just looks at summaries online to fill out those worksheets!"

To add to my stress, I heard the next day that students in the neighbouring seventh grade class, taught by Mr. Chu, were complaining that my students had an unfair advantage over them because of the bonus marks I had promised. Mr. Chu has even gotten several calls from parents who felt that my students have an advantage over theirs.

As you can see, my plan to encourage reading has gone totally awry! What should I do now? And, most importantly, how can I motivate my students to read?

Ms. Mahmoud

Potential Reflection Questions

1. Identify and provide examples of the types of behaviourism used in the case study (positive reinforcement, negative reinforcement, positive punishment, negative punishment).

2. Going beyond the events described in this scenario, what are possible pros and cons of this teacher’s choice to establish a reward system to encourage reading?

3. What suggestions would have for this teacher and the librarian to encourage reading without relying on behaviourist strategies?

4. Assuming Bilal's allegations about Andy are true, how might you deal with this situation? What might be contributing to Andy's behaviour? How could this issue have been prevented?

Additional resources

• https://www.alfiekohn.org/article/reading-incentives/
• https://www.thisamericanlife.org/713/made-to-be-broken/act-two-11

When re-using this resource, please attribute as follows:

This UBC EPSE 308 Behaviourism Open Case Study was developed by Benjamin Dantzer, Lee Iskander, and Sharmilla Miller and it is licensed under a under a Creative Commons Attribution 4.0 International License

Post Image: Educators .co.uk, CC BY 2.0 via Wikimedia Commons

Behaviorism In Psychology

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.

Learn about our Editorial Process

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:

Behaviorism, also known as behavioral learning theory, is a theoretical perspective in psychology that emphasizes the role of learning and observable behaviors in understanding human and animal actions. Behaviorism is a theory of learning that states all behaviors are learned through conditioned interaction with the environment. Thus, behavior is simply a response to environmental stimuli. The behaviorist theory is only concerned with observable stimulus-response behaviors, as they can be studied in a systematic and observable manner. Some of the key figures of the behaviorist approach include B.F. Skinner, known for his work on operant conditioning, and John B. Watson, who established the psychological school of behaviorism.

Principles of Behaviorism

The behaviorist movement began in 1913 when John B. Watson wrote an article entitled Psychology as the behaviorist views it , which set out several underlying assumptions regarding methodology and behavioral analysis:

All behavior is learned from the environment:

One assumption of the learning approach is that all behaviors are learned from the environment. They can be learned through classical conditioning, learning by association, or through operant conditioning, learning by consequences.

Behaviorism emphasizes the role of environmental factors in influencing behavior to the near exclusion of innate or inherited factors. This amounts essentially to a focus on learning. Therefore, when born, our mind is “tabula rasa” (a blank slate).

Classical conditioning refers to learning by association, and involves the conditioning of innate bodily reflexes with new stimuli.

Pavlov’s Experiment

Ivan Pavlov showed that dogs could be classically conditioned to salivate at the sound of a bell if that sound was repeatedly presented while they were given food.

He first presented the dogs with the sound of a bell; they did not salivate so this was a neutral stimulus. Then he presented them with food, they salivated.

The food was an unconditioned stimulus and salivation was an unconditioned (innate) response.

Pavlov then repeatedly presented the dogs with the sound of the bell first and then the food (pairing) after a few repetitions, the dogs salivated when they heard the sound of the bell.

The bell had become the conditioned stimulus and salivation had become the conditioned response.

Examples of classical conditioning applied to real life include:

• taste aversion – using derivations of classical conditioning, it is possible to explain how people develop aversions to particular foods
• learned emotions – such as love for parents, were explained as paired associations with the stimulation they provide
• advertising – we readily associate attractive images with the products they are selling
• phobias – classical conditioning is seen as the mechanism by which – we acquire many of these irrational fears.

Skinner argued that learning is an active process and occurs through operant conditioning . When humans and animals act on and in their environmental consequences, follow these behaviors. 

If the consequences are pleasant, they repeat the behavior, but if the consequences are unpleasant, they do not.

Behavior is the result of stimulus-response:

Reductionism is the belief that human behavior can be explained by breaking it down into smaller component parts.

Reductionists say that the best way to understand why we behave as we do is to look closely at the very simplest parts that make up our systems, and use the simplest explanations to understand how they work.

Psychology should be seen as a science:

Theories need to be supported by empirical data obtained through careful and controlled observation and measurement of behavior. Watson (1913) stated:

“Psychology as a behaviorist views it is a purely objective experimental branch of natural science. Its theoretical goal is … prediction and control.” (p. 158).

The components of a theory should be as simple as possible. Behaviorists propose using operational definitions (defining variables in terms of observable, measurable events).

Behaviorism introduced scientific methods to psychology. Laboratory experiments were used with high control of extraneous variables.

These experiments were replicable, and the data obtained was objective (not influenced by an individual’s judgment or opinion) and measurable. This gave psychology more credibility.

Behaviorism is primarily concerned with observable behavior, as opposed to internal events like thinking and emotion:

The starting point for many behaviorists is a rejection of the introspection (the attempts to “get inside people’s heads”) of the majority of mainstream psychology.

While modern behaviorists often accept the existence of cognitions and emotions, they prefer not to study them as only observable (i.e., external) behavior can be objectively and scientifically measured.

Although theorists of this perspective accept that people have “minds”, they argue that it is never possible to objectively observe people’s thoughts, motives, and meanings – let alone their unconscious yearnings and desires.

Therefore, internal events, such as thinking, should be explained through behavioral terms (or eliminated altogether).

There is little difference between the learning that takes place in humans and that in other animals:

There’s no fundamental (qualitative) distinction between human and animal behavior. Therefore, research can be carried out on animals and humans.

The underlying assumption is that to some degree the laws of behavior are the same for all species and that therefore knowledge gained by studying rats, dogs, cats and other animals can be generalized to humans.

Consequently, rats and pigeons became the primary data source for behaviorists, as their environments could be easily controlled.

Types of Behaviorist Theory

Historically, the most significant distinction between versions of behaviorism is that between Watson’s original methodological behaviorism, and forms of behaviorism later inspired by his work, known collectively as neobehaviorism (e.g., radical behaviorism).

John B Watson: Methodological Behaviorism

As proposed by John B. Watson, methodological behaviorism is a school of thought in psychology that maintains that psychologists should study only observable, measurable behaviors and not internal mental processes.

According to Watson, since thoughts, feelings, and desires can’t be observed directly, they should not be part of psychological study.

Watson proposed that behaviors can be studied in a systematic and observable manner with no consideration of internal mental states.

He argued that all behaviors in animals or humans are learned, and the environment shapes behavior.

Watson’s article “Psychology as the behaviorist views it” is often referred to as the “behaviorist manifesto,” in which Watson (1913, p. 158) outlines the principles of all behaviorists:

“Psychology as the behaviorist views it is a purely objective experimental branch of natural science. Its theoretical goal is the prediction and control of behavior. Introspection forms no essential part of its methods, nor is the scientific value of its data dependent upon the readiness with which they lend themselves to interpretation in terms of consciousness.”

In his efforts to get a unitary scheme of animal response, the behaviorist recognizes no dividing line between man and brute.

Man’s behavior, with all of its refinement and complexity, forms only a part of the behaviorist’s total scheme of investigation.

This behavioral perspective laid the groundwork for further behavioral studies like B.F’s. Skinner who introduced the concept of operant conditioning.

Radical Behaviorism

Radical behaviorism was founded by B.F Skinner , who agreed with the assumption of methodological behaviorism that the goal of psychology should be to predict and control behavior.

Radical Behaviorism expands upon earlier forms of behaviorism by incorporating internal events such as thoughts, emotions, and feelings as part of the behavioral process.

Unlike methodological behaviorism, which asserts that only observable behaviors should be studied, radical behaviorism accepts that these internal events occur and influence behavior.

However, it maintains that they should be considered part of the environmental context and are subject to the same laws of learning and adaptation as overt behaviors.

Another important distinction between methodological and radical behaviorism concerns the extent to which environmental factors influence behavior. Watson’s (1913) methodological behaviorism asserts the mind is a tabula rasa (a blank slate) at birth.

In contrast, radical behaviorism accepts the view that organisms are born with innate behaviors and thus recognizes the role of genes and biological components in behavior.

Social Learning

Behaviorism has undergone many transformations since John Watson developed it in the early part of the twentieth century.

One more recent extension of this approach has been the development of social learning theory, which emphasizes the role of plans and expectations in people’s behavior.

Under social learning theory , people were no longer seen as passive victims of the environment, but rather they were seen as self-reflecting and thoughtful.

The theory is often called a bridge between behaviorist and cognitive learning theories because it encompasses attention, memory, and motivation.

Historical Timeline

• Pavlov (1897) published the results of an experiment on conditioning after originally studying digestion in dogs.
• Watson (1913) launches the behavioral school of psychology, publishing an article, Psychology as the behaviorist views it .
• Watson and Rayner (1920) conditioned an orphan called Albert B (aka Little Albert) to fear a white rat.
• Thorndike (1905) formalized the Law of Effect .
• Skinner (1938) wrote The Behavior of Organisms and introduced the concepts of operant conditioning and shaping.
• Clark Hull’s (1943) Principles of Behavior was published.
• B.F. Skinner (1948) published Walden Two , describing a utopian society founded upon behaviorist principles.
• Journal of the Experimental Analysis of Behavior began in 1958.
• Chomsky (1959) published his criticism of Skinner’s behaviorism, “ Review of Verbal Behavior .”
• Bandura (1963) published a book called the Social Leaning Theory and Personality development which combines both cognitive and behavioral frameworks.
• B.F. Skinner (1971) published his book, Beyond Freedom and Dignity , where he argues that free will is an illusion.

Applications

Mental health.

Behaviorism theorized that abnormal behavior and mental illness stem from faulty learning processes rather than internal conflicts or unconscious forces, as psychoanalysis claimed.

Based on behaviorism, behavior therapy aims to replace maladaptive behaviors with more constructive ones through techniques like systematic desensitization, aversion therapy, and token economies. Systematic desensitization helps phobia patients gradually confront feared objects.

The behaviorist approach has been used in treating phobias. The individual with the phobia is taught relaxation techniques and then makes a hierarchy of fear from the least frightening to the most frightening features of the phobic object.

He then is presented with the stimuli in that order and learns to associate (classical conditioning) the stimuli with a relaxation response. This is counter-conditioning.

Aversion therapy associates unpleasant stimuli with unwanted habits to discourage them. Token economies reinforce desired actions by providing tokens redeemable for rewards.

The implications of classical conditioning in the classroom are less important than those of  operant conditioning , but there is still a need for teachers to try to make sure that students associate positive emotional experiences with learning.

If a student associates negative emotional experiences with school, then this can obviously have bad results, such as creating a school phobia.

For example, if a student is bullied at school, they may learn to associate the school with fear. It could also explain why some students show a particular dislike of certain subjects that continue throughout their academic career. This could happen if a teacher humiliates or punishes a student in class.

Cue reactivity is the theory that people associate situations (e.g., meeting with friends)/ places (e.g., pub) with the rewarding effects of nicotine, and these cues can trigger a feeling of craving (Carter & Tiffany, 1999).

These factors become smoking-related cues. Prolonged use of nicotine creates an association between these factors and smoking based on classical conditioning.

Nicotine is the unconditioned stimulus (UCS), and the pleasure caused by the sudden increase in dopamine levels is the unconditioned response (UCR). Following this increase, the brain tries to lower the dopamine back to a normal level.

The stimuli that have become associated with nicotine were neutral stimuli (NS) before “learning” took place but they became conditioned stimuli (CS), with repeated pairings. They can produce the conditioned response (CR).

However, if the brain has not received nicotine, the levels of dopamine drop and the individual experiences withdrawal symptoms, therefore, is more likely to feel the need to smoke in the presence of the cues that have become associated with the use of nicotine.

Issues & Debates

Free will vs. determinism.

Strong determinism of the behavioral approach as all behavior is learned from our environment through classical and operant conditioning. We are the total sum of our previous conditioning.

Softer determinism of the social learning approach theory recognizes an element of choice as to whether we imitate a behavior or not.

Nature vs. Nurture

Behaviorism is very much on the nurture side of the debate as it argues that our behavior is learned from the environment.

The social learning theory is also on the nurture side because it argues that we learn behavior from role models in our environment.

The behaviorist approach proposes that apart from a few innate reflexes and the capacity for learning, all complex behavior is learned from the environment.

Holism vs. Reductionism

The behaviorist approach and social learning are reductionist ; they isolate parts of complex behaviors to study.

Behaviorists believe that all behavior, no matter how complex, can be broken down into the fundamental processes of conditioning.

Idiographic vs. Nomothetic

It is a nomothetic approach as it views all behavior governed by the same laws of conditioning.

However, it does account for individual differences and explains them in terms of differences in the history of conditioning.

Critical Evaluation

Behaviorism has experimental support: Pavlov showed that classical conditioning leads to learning by association. Watson and Rayner showed that phobias could be learned through classical conditioning in the “Little Albert” experiment.

An obvious advantage of behaviorism is its ability to define behavior clearly and measure behavior changes. According to the law of parsimony, the fewer assumptions a theory makes, the better and the more credible it is. Therefore, behaviorism looks for simple explanations of human behavior from a scientific standpoint.

Many of the experiments carried out were done on animals; we are different cognitively and physiologically. Humans have different social norms and moral values that mediate the effects of the environment.

Therefore people might behave differently from animals, so the laws and principles derived from these experiments, might apply more to animals than to humans.

Humanism rejects the nomothetic approach of behaviorism as they view humans as being unique and believe humans cannot be compared with animals (who aren’t susceptible to demand characteristics). This is known as an idiographic approach.

In addition, humanism (e.g., Carl Rogers) rejects the scientific method of using experiments to measure and control variables because it creates an artificial environment and has low ecological validity.

Humanistic psychology also assumes that humans have free will (personal agency) to make their own decisions in life and do not follow the deterministic laws of science . 

The behaviorist approach emphasis on single influences on behavior is a simplification of circumstances where behavior is influenced by many factors. When this is acknowledged, it becomes almost impossible to judge the action of any single one.

This over-simplified view of the world has led to the development of ‘pop behaviorism, the view that rewards and punishments can change almost anything. 

Therefore, behaviorism only provides a partial account of human behavior, that which can be objectively viewed. Essential factors like emotions, expectations, and higher-level motivation are not considered or explained. Accepting a behaviorist explanation could prevent further research from other perspectives that could uncover important factors.

For example, the psychodynamic approach (Freud) criticizes behaviorism as it does not consider the unconscious mind’s influence on behavior and instead focuses on externally observable behavior. Freud also rejects the idea that people are born a blank slate (tabula rasa) and states that people are born with instincts (e.g., eros and Thanatos).

Biological psychology states that all behavior has a physical/organic cause. They emphasize the role of nature over nurture. For example, chromosomes and hormones (testosterone) influence our behavior, too, in addition to the environment.

Behaviorism might be seen as underestimating the importance of inborn tendencies. It is clear from research on biological preparedness that the ease with which something is learned is partly due to its links with an organism’s potential survival.

Cognitive psychology states that mediational processes occur between stimulus and response, such as memory , thinking, problem-solving, etc.

Despite these criticisms, behaviorism has made significant contributions to psychology. These include insights into learning, language development, and moral and gender development, which have all been explained in terms of conditioning.

The contribution of behaviorism can be seen in some of its practical applications. Behavior therapy and behavior modification represent one of the major approaches to the treatment of abnormal behavior and are readily used in clinical psychology.

The behaviorist approach has been used in the treatment of phobias, and systematic desensitization .

Many textbooks depict behaviorism as dominating and defining psychology in the mid-20th century, before declining from the late 1950s with the “cognitive revolution.”

However, the empirical basis for claims about behaviorism’s prominence and decline has been limited. Wide-scope claims about behaviorism are often based on small, unrepresentative samples of historical data. This raises the question – to what extent was behaviorism actually dominant in American psychology?

To address this question, Braat et al. (2020) conducted a quantitative bibliometric analysis of 119,278 articles published in American psychology journals from 1920-1970.

They generated cocitation networks, mapping similarities between frequently cited authors, and co-occurrence networks of frequently used title terms, for each decade. This allowed them to examine the structure and development of psychology fields without relying on predefined behavioral/non-behavioral categories.

Key findings:

• In no decade did behaviorist authors belong to the most prominent citation clusters. Even a combined “behaviorist” cluster accounted for max. 28% of highly cited authors.
• The main focus was measuring personality/mental abilities – those clusters were consistently larger than behaviorist ones.
• Between 1920 and 1930, Watson was a prominent author, but behaviorism was a small (19%) slice of psychology. Larger clusters were mental testing and Gestalt psychology.
• From the 1930s, behaviorism split into two clusters, possibly reflecting “classical” vs. “neobehaviorist” approaches. However, the combined behaviorist cluster was still smaller than mental testing and Gestalt clusters.
• The influence of behaviorism did not dramatically decline after 1950. The behaviorist cluster was stable at 28% during the 1940s-60s, and its citation count quadrupled.
• Contrary to narratives, Skinner was not highly cited in the 1950s-60s – he did not dominate behaviorism after WWII.
• Analyses challenge assumptions that behaviorism was the single dominant force in mid-20th-century psychology. The story was more diverse.

However, behaviorist vocabulary became more prominent over time in title term analyses. This suggests behaviorists were influential in shaping psychological research agendas, if not fully dominating the field.

Overall, quantitative analyses provide a richer perspective on the development of behaviorism and 20th-century psychology. Claims that behaviorism “rose and fell” as psychology’s single dominant school appear too simplistic.

Psychology was more multifaceted, with behaviorism as one of several influential but not controlling approaches. The narrative requires reappraisal.

Bandura, A., & Walters, R. H. (1963). Social learning and personality development . New York: Holt, Rinehart, & Winston.

Braat, M., Engelen, J., van Gemert, T., & Verhaegh, S. (2020). The rise and fall of behaviorism: The narrative and the numbers. History of Psychology, 23 (3), 252-280.

Carter, B. L., & Tiffany, S. T. (1999). Meta‐analysis of cue‐reactivity in addiction research.  Addiction ,  94 (3), 327-340.

Chomsky, N. (1959). A review of BF Skinner’s Verbal Behavior . Language, 35(1) , 26-58.

Holland, J. G. (1978). BEHAVIORISM: PART OF THE PROBLEM OR PART OF THE SOLUTION?  Journal of Applied Behavior Analysis ,  11 (1), 163-174.

Hull, C. L. (1943). Principles of behavior: An introduction to behavior theory . New York: Appleton-Century-Crofts.

Pavlov, I. P. (1897). The work of the digestive glands . London: Griffin.

Skinner, B. F. (1938). The behavior of organisms: An experimental analysis . New York: Appleton-Century.

Skinner, B. F. (1948). Walden two. New York: Macmillan.

Skinner, B. F. (1971). Beyond freedom and dignity . New York: Knopf.

Thorndike, E. L. (1905). The elements of psychology . New York: A. G. Seiler.

Watson, J. B. (1913). Psychology as the behaviorist views it . Psychological Review, 20 , 158-178.

Watson, J. B. (1930). Behaviorism (revised edition). University of Chicago Press.

Watson, J. B., & Rayner, R. (1920). Conditioned emotional reactions . Journal of Experimental Psychology, 3 , 1, pp. 1–14.

What is the theory of behaviorism?

What is behaviorism with an example.

An example of behaviorism is using systematic desensitization in the treatment of phobias. The individual with the phobia is taught relaxation techniques and then makes a hierarchy of fear from the least frightening to the most frightening features of the phobic object.

How behaviorism is used in the classroom?

In the conventional learning situation, behaviorist pedagogy applies largely to issues of class and student management, rather than to learning content.

It is very relevant to shaping skill performance. For example, unwanted behaviors, such as tardiness and dominating class discussions, can be extinguished by being ignored by the teacher (rather than being reinforced by having attention drawn to them).

Who founded behaviorism?

John B. Watson founded behaviorism. Watson proposed that psychology should abandon its focus on mental processes, which he believed were impossible to observe and measure objectively, and focus solely on observable behaviors.

His ideas, published in a famous article “ Psychology as the Behaviorist Views It ” in 1913, marked the formal start of behaviorism as a major school of psychological thought.

Is behavior analysis the same as behaviorism?

No, behavior analysis and behaviorism are not the same. Behaviorism is a broader philosophical approach to psychology emphasizing observable behaviors over internal events like thoughts and emotions.

Behavior analysis , specifically applied behavior analysis (ABA), is a scientific discipline and set of methods derived from behaviorist principles, used to understand and change specific behaviors, often employed in therapeutic contexts, such as with autism treatment.

CONCEPTUAL ANALYSIS article

A process-based approach to cognitive behavioral therapy: a theory-based case illustration.

• 1 Department of Psychology, University of Toledo, Toledo, OH, United States
• 2 Department of Psychological and Brain Sciences, Boston University, Boston, MA, United States
• 3 Department of Psychology, University of Nevada, Reno, Reno, NV, United States
• 4 Department of Psychology, Philipps-Universität Marburg, Marburg, Germany

Despite the significant contribution of cognitive-behavioral therapy to effective treatment options for specific syndromes, treatment progress has been stagnating, with response rates plateauing over the past several years. This stagnation has led clinical researchers to call for an approach that instead focuses on processes of change and the individual in their particular context. Process-based therapy (PBT) is a general approach representing a model of models, grounded in evolution science, with an emphasis on idiographic methods, network models of case conceptualization, and enhancing wellbeing. In this paper, we describe the theory underlying PBT and present a case study for how to apply PBT tools and principles to deliver process-informed and person-centered evidence-based treatment. In addition, we discuss lessons learned from our case and provide suggestions for future considerations when implementing PBT in clinical settings.

Introduction

Historical dominance of cognitive-behavioral therapy.

For decades, cognitive-behavioral therapy (CBT) has been the gold standard of evidence-based care for many mental illnesses as defined by the Diagnostic and Statistical Manual of Mental Disorders (DSM), ranging from generalized anxiety disorder to eating disorders ( Covin et al., 2008 ; Linardon et al., 2017 ). CBT, in turn, has built its credibility on copious data accrued from the gold standard of clinical experimental design: randomized controlled trials. The most basic design of a randomized controlled trial entails comparing the means of two groups of randomly assigned people after one group receives the active intervention and the second does not. If the treatment group mean is found to be “significantly” better than that of the control group, statistically speaking, the treatment is deemed efficacious.

Data from hundreds of randomized controlled trials have shown that protocol-based CBT leads to more symptom improvement on average compared to other interventions (e.g., Butler et al., 2006 ; Hofmann et al., 2012 ). In addition, adjunctive treatment components are constantly tested to facilitate incremental gains from CBT, such as adding motivational interviewing ( Marker and Norton, 2018 ) or contingency management ( Worden et al., 2017 ). Prevailing wisdom over the past few decades declared that CBT tailored to specific disorders and randomized controlled trials are the solution to mental health struggles, and most clinical research and funding accordingly have operated on this assumption ( Chambless and Hollon, 1998 ; Tolin, 2020 ).

At the same time, treatment progress has been stagnating. CBT response rates have hovered around 50% for anxiety disorders for years ( Loerinc et al., 2015 ; Springer et al., 2018 ), suggesting that the gold standard is not getting better, despites decades and millions of dollars of research. Furthermore, relevance of the nomothetic principles underlying randomized controlled trials to individual wellbeing is tenuous, calling into question the utility of randomized controlled trials as a means of evaluating treatment efficacy and the generalizability of study findings to individual clients ( Molenaar, 2004 ). If the solution is not CBT protocols for disorders and randomized controlled trials, then we need to look elsewhere to ensure that clinical psychological science can adequately meet the needs of those who are suffering.

Move toward personalized care

Over the past few decades, there has been a growing movement toward using idiographic methods (or methods that focus in the individual and their functioning rather than groups and averages) in clinical psychology research, with the ultimate objective of personalizing psychotherapy for every client ( Rubel et al., 2018 ; Fisher et al., 2019 ; Levinson et al., 2021 ). Broadly speaking, idiographic treatment research strives to answer Paul’s famous question, “What treatment, by whom, is most effective for this individual with that specific problem, and under which set of circumstances?” (p. 111, Paul, 1967 ). For example, Levinson et al. (2021) identified central symptoms in individual-level networks among participants with eating disorders, then developed treatment plans by selecting corresponding modules from evidence-based treatments (e.g., emotion regulation module from dialectical behavior therapy [DBT] for feelings of shame and guilt).

Closely related to idiographic methods is a network approach to understanding psychopathology, which posits that symptoms have causal interrelationships with each other rather than are caused by a latent disease as assumed by the biomedical model ( Bringmann et al., 2022 ). Together, these ideas reflect a conceptualization of psychopathology as networks of interrelated biopsychosocial processes and problems that form a causal and dynamic network in ways unique to each person. Thus, even if two people present to therapy with a similar complaint, their prescribed treatments may vary depending on the person’s individual network of ways of addressing problems this is causing or maintaining this complaint ( Levinson et al., 2021 ).

Development of process-based therapy

Against the backdrop of burgeoning interest in idiographic and network-based clinical research ( Piccirillo et al., 2019 ), a new model of personalized evidence-based psychological treatment has emerged: process-based therapy (PBT; Hofmann and Hayes, 2019 ; Hayes et al., 2020a ). PBT is a general approach to clinical assessment, conceptualization, and treatment, representing a model of models . PBT is not a new therapy. Rather, it is a new framework to organize evidence-based therapeutic techniques—already known to psychologists—along basic psychological dimensions relevant to human adaptation to a given context, including cognition, attention, affect, behavior, self, and motivation, as well as biophysiological and sociocultural levels ( Hayes et al., 2022 ).

The dimensional model undergirding PBT is called the extended evolutionary meta-model or EEMM (rhymes with “dream;” Hayes et al., 2020b ). Its job is to clarify the inter-relatedness among processes with respect to EEMM dimensions and levels and to facilitate finding optimal therapeutic strategies to target the most relevant processes. Analogous to a closet, the EEMM provides space to consider different aspects of one’s psychological repertoire. In much the same way that a closet is rendered useful by the clothing it contains, the utility of the EEMM ultimately depends on the existence of meaningful content but it can be considered independently of content.

Along with the EEMM, PBT provides tools for idiographic assessment to guide treatment planning for the individual-in-context. These tools begin with a network approach wherein clinicians identify key variables relevant to the client’s presenting problem and hypothesize about how these variables relate to one another. Using PBT graphic conventions ( Hofmann et al., 2021 ), the direction and strength of the relationships are represented by opacity and size of arrowheads, respectively. For example, in Figure 1 , the network shows that the core belief, “I am a bad person” is hypothesized to lead the client to experience feelings of worthless and guilt, low mood, and low motivation to engage in hobbies (excitatory effect depicted with opaque arrowhead), with a stronger hypothesized effect on feelings of worthless and guilt. In contrast, modifying core beliefs is thought to have an inhibitory effect on the original core belief, as illustrated with a blank arrowhead, meaning that modifying core beliefs weakens the influence of the thought, “I am a bad person,” along with corresponding downstream effects.

Figure 1. Example of network model for a specific client. Extended evolutionary meta-model (EEMM) dimensions represented by each node are bolded. Size of the arrowheads indicates hypothesized strength of the relationship (bigger arrowheads = stronger correlation), and opacity reflects direction of the relationship (opaque = positive/excitatory, transparent = negative/inhibitory).

The intended function of PBT is to provide a theoretically coherent framework broad enough to encompass the gamut of psychotherapy orientations and furnish a lingua franca with which psychologists can use to communicate seemingly disparate ideas. Accordingly, PBT is grounded in evolution science, precisely because evolutionary principles have been postulated as a unifying theoretical framework across virtually all life science disciplines, including psychology ( Mesoudi et al., 2006 ; Hayes and Sanford, 2015 ). PBT views psychopathology as maladaptation to a given context due to problems in variation, selection, and retention of biopsychosocial processes in multiple dimensions and levels ( Hayes et al., 2020b ). While considering the complexity and interconnectedness of problems, clinicians strive to perturbate the client’s maladaptive network of such processes while building an adaptive, self-sustaining alternative network. This is done by applying specific treatment kernels that introduce new responding (variation), identify which strategies are most adaptive for a client given their goals (selection), help clients persist in useful responding (retention), across various psychological facets (dimensions), on intrapersonal and interpersonal scales (levels), in ways that are sensitive to history, situational demands and personally relevant aspirations (context).

Although PBT emphasizes idiographic methods and network models of case conceptualization, similar to other approaches observed in clinical psychology ( Fisher et al., 2019 ; Levinson et al., 2021 ), it goes beyond methodology. It also takes an explicit philosophical stance against diagnostic and symptom-driven models, instead directing efforts toward understanding clinically relevant processes and enhancing wellbeing , embodying a clear departure from randomized controlled trials and the symptom-focused tradition of clinical psychology. In other words, idiographic research focused on symptoms alone is still inadequate from a PBT perspective.

Rather, PBT entails attention to processes of change unique to the individual in their context over symptoms enumerated in a diagnostic manual (e.g., in the context of social anxiety and fear of negative judgment about physical appearance due to childhood bullying and emphasis on physical appearance in family of origin vs. fear of negative evaluation). Extending Paul’s classic question with a demand for precision, PBT instead asks, “What core biopsychosocial processes should be targeted with this client given this goal in this situation, and how can they most efficiently and effectively be changed?” (p. 2, Hayes et al., 2020a ). In a way, for PBT, personalizing treatment is not an end in itself, but a means to the end of developing more effective and efficient treatments for all individuals given limited available resources.

Given its explicit philosophical and methodological stance, PBT has the potential to undermine the barriers presently facing treatment development in two ways: ( Covin et al., 2008 ) it targets processes of change, not symptoms, and ( Linardon et al., 2017 ) it is evaluated on the level of the individual not only the group. That is, PBT is not diagnosis-specific and hence flexible enough to be used with presentations poorly captured by DSM diagnoses (e.g., multiple co-occurring diagnoses). PBT also considers individual differences and prioritizes what works for a person in their unique context, rather than an illusory average. Moreover, the goal of PBT is to improve wellbeing not symptom reduction, the default metric against which most evidence-based psychotherapies to date have been evaluated ( Linardon et al., 2017 ; Springer et al., 2018 ).

The difference between a diagnosis-based and process-based approach may be illustrated by an example. The network in Figure 1 represents a client who plausibly fits the diagnostic profile of major depressive disorder according to the DSM or ICD, given that they report such depressive symptoms as low mood, low motivation to engage in hobbies, and feelings of worthlessness and guilt. Nonetheless, assignment of a diagnosis would require a standard diagnostic interview and cannot be made based on the elements of Figure 1 alone. If, however, this client was given a diagnosis of “major depressive disorder” based on a formal assessment, choices for evidence-based treatment would include behavioral activation, cognitive behavioral therapy, and interpersonal therapy ( Gloaguen et al., 1998 ; Cuijpers et al., 2007 , 2011 ), and clinicians could choose among these options. However, as depicted in Figure 1 , the core belief that “I am a bad person” appears to be a primary driver of the other aspects of the client’s presentation. Thus, a clinician might decide to focus on cognitive intervention strategies as a first step, predicting that it would result in downstream effects of improving other problems.

Application of process-based therapy and current case illustration

In PBT, the treatment goal is to move clients toward adaptive growth relying on variation, selection, and retention along the EEMM dimensions and levels in a given context. In the closet analogy, this is equivalent to having the client try on different items of clothing ( variation ), identify which work for which occasions ( selection in context ; e.g., flip-flops for the beach and coat for winter hiking), and keep wearing appropriate clothing in specific contexts ( retention in context ). For the client in Figure 1 , this may mean trying different cognitive strategies (e.g., restructuring from cognitive therapy, defusion from acceptance, and commitment therapy [ACT]) in different contexts (e.g., when feeling sad vs. feeling neutral) to cope with the core belief, and to be able to deploy those strategies matched to context the next time the core belief shows up.

If PBT becomes the vehicle for evidence-based intervention to shift from a focus on protocols for disorders to a focus on the personalized needs of particular people, networks mapping clinically relevant processes for each person (see Figure 2 for an example) will become commonplace as a way of organizing the idiographic deployment of evidence-based treatment components or kernels (e.g., interpersonal effectiveness skills from DBT and interoceptive exposure from CBT). This is not an entirely new vision since it echoes the focus on functional analysis in the early days of behavior therapy, wherein general principles were applied to individual presentations, such that even if reinforcement was targeted, the form it took could be vastly different (e.g., attention vs. candy vs. money; Barlow and Hersen, 1973 ; Kanfer and Grimm, 1977 ).

Figure 2. Preliminary case conceptualization for Amy. EEMM dimensions represented by each node are bolded. Size of the arrowheads indicates hypothesized strength of the relationship (bigger arrowheads = stronger correlation), and opacity reflects direction of the relationship (opaque = positive/excitatory, transparent = negative/inhibitory). Right-angled rectangles reflect manipulable variables and rounded rectangles indicate immutable moderators (e.g., historical events).

There are major differences, however. The set of replicated nomothetic processes of change is now vastly larger than the behavioral learning principles (e.g., positive reinforcement in operant conditioning) that were then emphasized, which means there are many more tools and processes from which clinicians can choose on aggregate ( Hayes et al., 2022 ). However, an idiographic lens entails precision in how processes are targeted, with the understanding that not every process is relevant to every client. For instance, distress tolerance might be important for someone with high emotional reactivity and sensitivity, whereas social skills training may be more important for someone who lacks interpersonal skills. Furthermore, unlike direct nonverbal contingencies alone, contemporary biopsychosocial processes of change are understood to be dynamic and progressive, and thus to require such analytic tools as dynamical systems analysis—wherein the state of a datapoint is assumed to be time-varying but predictable based on certain inputs (e.g., past behavior predicting future behavior)—to construct adequate functional analyses ( Curtiss et al., 2021 ; Hofmann et al., 2021 ; Roefs et al., 2022 ), not merely classical single case designs ( Hayes et al., 1999 ).

While the possible number of relevant processes of change is very large, evolutionary science has emerged as a parsimonious framework within which to help organize comprehensive analyses of client needs and goals across relevant dimensions and levels of biopsychosocial processes ( Hayes et al., 2020a , b ). Importantly, measurement tools and statistical methods are now available to help gradually turn this new approach to functional analysis into a largely empirical rather than a largely conceptual tool (e.g., Group Iterative Multiple Model Estimation [GIMME], Process-Based Assessment Tool [PBAT]; Gates and Molenaar, 2012 ; Ciarrochi et al., 2022 ; Sanford et al., 2022 ).

Clearly, from our vantage point, the potential of PBT is vast. We anticipate that PBT can fundamentally alter how we conceptualize mental wellbeing and design psychological treatments, leading to the development of interventions that can more effectively and efficiently meet the needs entailed in infinite human complexity. Yet, more research and clinical testing are needed to clarify and refine its application across a range of contexts. The present case illustration represents an initial step toward this effort of explicating the application of PBT principles, to provide a clinical face to the core theoretical features of the PBT research program.

Case illustration

Client description.

To illustrate how PBT may be applied with a real-life example, we describe the course of treatment for an actual recent client, Amy, who was treated using a PBT approach to CBT. Some content details have been changed to anonymize Amy, but concepts remain functionally similar. Amy (she/her) was a cisgender White woman in her late 30 s working full-time at a university administrative job while managing a consultation business part-time at the point of study enrollment.

Based on results from the Mini International Neuropsychiatric Interview 7.0 ( Sheehan et al., 1998 ), a semi-structured clinical interview for DSM-5 diagnoses, Amy was assigned a primary diagnosis of generalized anxiety disorder. The specific problems Amy reported were “incessant checking” of financial and email accounts, avoidance of going outside due to compulsion to report public hazards to local authorities, indecision around her own career path, and rigid adherence to standards around being “responsible.” Amy’s initial treatment goals were to clarify her values, increase physical activity, develop a plan for leaving her full-time job to focus on her consulting business, be more present in interpersonal interactions, and maintain healthy interpersonal boundaries with loved ones.

Case conceptualization via network modeling

In the first two sessions of treatment, the therapist and Amy developed a preliminary network model based on her self-reported problems via clinical interview and discussion (see Figure 2 ). Each node (events represented in rectangles) or edge (relationships represented by arrows) were agreed to by Amy before being added to the network. Right-angled rectangles reflect manipulable variables and rounded rectangles indicate immutable moderators (e.g., historical events). Changeable nodes (rectangles) were defined functionally rather than topographically. For example, “proactively solving problems” covered Amy’s reporting of public hazards to authorities as well as other forms of excessive problem solving, such as making contingency plans for anticipated negative outcomes.

The selection of which nodes and edges were emphasized and retained were determined by functional analyses rooted in Amy’s primary presenting concerns: excessive checking and constant pressure to act responsibly or thoughtfully. For example, starting with excessive checking (identified behavior), the therapist and Amy explored potential antecedents and consequences contributing to or maintaining the unhelpful behavior. Together, they clarified that the pressure to act responsibly directly contributed to Amy’s excessive checking and that checking was reinforced by a sense of peace and reductions in worry about being seen as irresponsible and pressure to be responsible in the short term. Similarly, Amy hypothesized that the constant pressure she experienced to be responsible might be linked to a core belief that she needs to prove her worth and worries about being seen by others as irresponsible.

Further functional analyses were used to clarify how newly identified nodes were linked to the existing network or branched off to new areas. For instance, the self-label of “selfish” was absent at the inception of the network; it was only added after several functional analytic explorations and Socratic questioning wherein Amy realized that she had been carrying the self-label of “selfish” and the label was, in turn, driving other nodes like worry about external judgment and the core belief of needing to prove her worthiness. Typically, in the first few follow-up functional analyses, we would find that newly identified nodes linked back to existing ones. As shown in Figure 2 , for example, the “selfish” self-label was hypothesized to be associated with five other nodes.

As expected, however, the further out we went from the core problem, the fewer the number of edges connected back to the network. Thus, in terms of deciding how much to expand the network, we used the recommendation outlined in the PBT guide, Learning PBT : “as complex as necessary and as simple as possible” (p. 20, Rubel et al., 2018 ). In other words, we considered relevance to the network and presenting concern to give us a sufficiently complex understanding of Amy’s struggles to inform treatment planning, while letting go of other variables that may have been related to Amy’s struggles but did not incrementally contribute to treatment planning.

As an example, an early iteration of Amy’s network included a history of learning difficulties that she believed contributed to her attentional bias toward things going wrong, but through discussion, it seemed that the more pertinent contributor was her upbringing in a volatile household. Moreover, learning difficulties did not directly relate to other parts of her network or shape treatment planning beyond that explained by existing nodes (e.g., critical parents), thus, it was excluded from the first draft of Amy’s network.

Once the network was completed, self-amplifying subnetworks were identified to clarify potential treatment targets. As can be seen in Figure 2 , Amy’s preliminary network contains several self-amplifying loops or subnetworks that are self-maintained, one of which is illustrated in Figure 3 . In this self-amplifying loop, occurrence of the self-concept of “selfish” leads Amy to worry that others will perceive her as irresponsible or selfish, which then leads her to focus on problems in the physical or social environment in a hyper-vigilant way. This attentional bias, in turn, leads her to be more likely to view herself as “selfish” and to worry even more about external judgment. Because this part of the network is self-amplifying, no external input is needed to maintain the self-criticism, worry, and attentional bias cycle, making it especially critical to disrupt it during intervention.

Figure 3. Self-amplifying loop from Amy’s broader case conceptualization. EEMM dimensions represented by each node are bolded. Size of the arrowheads indicates hypothesized strength of the relationship (bigger arrowheads = stronger correlation).

A different example of a subnetwork is shown in Figure 4 . In this case, inhibitory arrows contribute to the self-perpetuating pattern. A moderator from Amy’s past (“parents were critical”) continues to drive the worry of being viewed as selfish and the core belief that she needs to prove herself worthy, despite the inhibitory influence of checking behavior. For instance, worry that others will see her as selfish brings up fear of making an “irresponsible” decision, which leads Amy to repeatedly check online accounts and to research decisions. These compulsive behaviors are negatively reinforced in the short term because they decrease her worry of being viewed as selfish and fear of making a poor decision. Without the sociocultural moderator of critical family members, this should dampen the self-perpetuating cycle, but Amy’s history keeps her worry and core belief active (note the relatively bigger arrowheads reflecting stronger hypothesized influence), such that the loop persists despite short-term reduction in worry and fear. Furthermore, the subnetwork functions on a short timescale (daily), such that a similar subnetwork with a monthly timescale may actually show that checking increases worry.

Figure 4. Subnetwork with inhibitory effects. EEMM dimensions represented by each node are bolded. Size of the arrowheads indicates hypothesized strength of the relationship (bigger arrowheads = stronger correlation), and opacity reflects direction of the relationship (opaque = positive/excitatory, transparent = negative/inhibitory). Right-angled rectangles reflect manipulable variables and rounded rectangles indicate immutable moderators (e.g., historical events).

Of note, a key node in Amy’s network is worry about being perceived as irresponsible or selfish, which coheres with the primary assigned diagnosis of GAD, potentially raising questions about the incremental utility of a network case conceptualization. Although a PBT approach may ultimately identify the same broad treatment target as a DSM diagnosis, which is “worry” in this case, the distinct feature of PBT is that it also identifies the downstream and upstream variables tied to worry (e.g., attentional bias for things going wrong, “selfish” label, pressure to be responsible, excessive checking, problem solving; see Figure 2 ) that may elude a GAD diagnosis alone. The practical implication of this is that the PBT approach would provide more personalized treatment targets for Amy (e.g., acceptance of perceived pressure to be responsible and mindfulness training to increase attentional flexibility) rather than recommend general evidence-based approaches for worry like worry time or cognitive restructuring.

Assessment of treatment progress

The network is a dynamic, transitory system to guide case conceptualization and treatment progress ( Fried et al., 2017 ; Curtiss et al., 2021 ; Roefs et al., 2022 ). Its purpose is to capture the complexity of the client’s problems and to serve as a way to identify causal influences, identify treatment targets, and monitor treatment progress. In a PBT approach, the network is viewed as constantly changing and thus needs to be re-examined on a regular basis, especially during therapy.

In order to characterize the network of processes of change empirically, over the course of treatment, Amy completed personalized ecological momentary assessment (EMA) items four times a day based on her case conceptualization (see Table 1 ). EMA items were rated using a visual analog scale from 1 to 100. The wording and frequency of items are presented in Table 1 .

Table 1. Personalized ecological momentary assessment items over the course of treatment.

Daily self-report items

Assessment initially included behavioral goals (duration) and key nodes in Amy’s network determined in the first two sessions of treatment. As Amy began to practice new skills and add adaptive nodes to her existing network, we replaced the original prompts with items describing her new adaptive network and assessing progress vis-à-vis her goals. All items were personalized to Amy’s presentation and developed collaboratively with her input. That is, items were only added to the daily assessment if Amy agreed that they would be relevant to her wellbeing. Table 1 lists these daily self-report items from baseline to the end of treatment.

Network analysis

Amy’s network data were analyzed using the Group Iterative Multiple Model Estimation (GIMME; Gates and Molenaar, 2012 ) package in R version 4.2.0 ( R Core Team, 2022 ). GIMME is an idiographic algorithm applied in a structural equation modeling (SEM) and Vector Autoregressive (VAR) framework that identifies how variables of interest relate to each other and evaluates the strength of the relationship among variables. GIMME accounts for longitudinal data and corresponding autoregressive effects by estimating the unified SEM ( Lane et al., 2021 ), which permits evaluation of contemporaneous and temporally lagged relations among variables of interest simultaneously. In addition, contemporaneous directionality is indicated when X at time t explains more variance in Y at time t than Y at time t does in X at time t , after addressing other variables in the model, including autoregressive effects. Contemporaneous directionality is not equivalent to causality given lack of experimental control, but it can be generally predictive of temporal relationships in smaller temporal windows than those used to collect the EMA data.

In GIMME, individual-level models are first estimated independent of any group-level data, and group-level (and, if relevant, subgroup level) models are subsequently generated based on individual-level models, retaining edges only if they apply to the majority of individuals in the sample. In the present case, because there was only one participant, only an individual-level model was generated, and the group-level step produced the exact same results as the individual-level model given an N of 1. The subsequent model fitting for the individual-level model is resolved when there is an excellent model fit based on two of four model fit indices: root mean square error of approximation (RMSEA) < 0.05, standardized root mean square residual (SRMR) < 0.05, non-normed fit index (NNFI) > 0.96, and comparative fit index (CFI) > 0.95 ( Bentler and Bonett, 1980 ; Bentler, 1990 ; Steiger, 1990 ; Hu and Bentler, 1999 ; Brown, 2015 ). Model estimation and missing data were handled using full information maximum likelihood. More details on GIMME procedures can be found in Gates and Molenaar (2012) .

Treatment plan

In the third session, the therapist reviewed the conceptual network model with Amy ( Figure 2 ), confirming with her that the model was accurate to her experience. In the third session, the therapist reviewed the conceptual network model with Amy ( Figure 2 ), confirming with her that the model fit with her experience and with her own conceptualization of her struggles. This is in the spirit of the idiographic PBT approach to assessment as opposed to a top-down “expert clinician” approach. Based on this understanding of Amy’s struggles, the therapist and Amy collaboratively developed a treatment plan. Based on Amy’s goals and network, they agreed that treatment would start with targeting inflexibility around personal standards (e.g., needing to be responsible or worthy) and attentional control (e.g., being more present).

Amy’s rigidity around personal expectations manifested in significant time spent on problem solving, checking online accounts, and researching prior to decision making in response to worry and her core belief. For example, her need to be responsible or perceived as responsible led to her spending hours comparing household products before purchasing one. Thus, we hypothesized that if Amy was able to hold personal standards more lightly, she would respond to them in more values-consistent and wellness-enhancing ways.

Amy also had difficulty regulating her attention, primarily focusing on negative aspects of situations and people—partly due to her chaotic childhood in which this hypervigilance was adaptive. As an adult, however, the hypervigilance reinforced the self-concept that she was “selfish,” led to worry about negative evaluation, and motivated excessive preemptive problem solving. We hypothesized that if Amy learned to shift attention intentionally, she would still retain the ability to be vigilant, when necessary, but also be present and open to other sources of data about herself and those around her (e.g., she is kind, others find her charming) when not exclusively attuned to negative concepts.

Treatment description

At the end of the first three sessions of collaborative case conceptualization and treatment planning, the therapist provided psychoeducation on how standards govern behavior when they are held rigidly and asked Amy to think of examples where standards may be driving her behavior (functional analysis from CBT; e.g., Barlow et al., 2017 ). Amy noted that the expectation that she “needs to respond to people as quickly as possible” was a motivator of her incessant checking behavior. The therapist then assigned homework to Amy to identify 5-10 standards she follows and ways in which those standards influence her behaviors to increase self-awareness through self-monitoring.

In session 4, Amy reported that she had discovered many standards that were influencing her behavior and, with this awareness, was able to respond to them more flexibly using cognitive defusion from ACT. For instance, Amy had gone on a vacation in between sessions and noticed the standard, “I need to make the most of my vacation,” which would have typically led her to pack her schedule with back-to-back activities. Instead, once she noticed this standard, she intentionally chose to enjoy a slow breakfast in the morning and only started exploring the city in the late morning, demonstrating healthy variation in responding (i.e., potentially useful responses outside her existing repertoire).

To facilitate selection of adaptive responding, the therapist asked Amy to track the consequences of this new behavior. For instance, Amy noted that she enjoyed her day more and relaxing her standards even gave her the opportunity to try out unplanned activities, which satisfied her desire for adventure. Directing Amy’s attention to these outcomes was important for helping Amy determine if her new responses were adaptive (and thus should be selected for retention in her repertoire) or maladaptive (and thus continued variation was needed). In other words, variation alone is inadequate. Amy also needed to evaluate the utility of any new responding to eventually shape a more salubrious set of responses.

In addition, Amy said that tracking her behaviors had been helpful for supporting desired behavior change. To capitalize on momentum toward positive behavior change and to reinforce flexible responding, the therapist asked Amy to practice doing behaviors that served her wellbeing for homework. Note that by defining the behavioral task functionally (i.e., “serve wellbeing”), the therapist was giving Amy room to continue varying forms of enhancing wellbeing (e.g., waking up late, going to the gym, and connecting with old friends) and to ultimately select those that were most effective in meeting her needs.

In the next three sessions ( Worden et al., 2017 ; Marker and Norton, 2018 ; Tolin, 2020 ), Amy reported that identifying and responding flexibly to standards had been “empowering” for her. She provided examples of explicitly communicating her needs, asking for help from others, driving instead of walking when it was cold, saying no to burdensome requests, and delaying responding to emails. Amy noted that these behaviors were consistent with her values (she had previously done values clarification work through a leadership training) and was able to generalize flexible responding to rules to various life domains. Moreover, Amy observed that the feeling of empowerment she derived from flexible responding was “self-reinforcing.” The reinforcing function of the feeling of empowerment, along with other new behaviors, was added to Amy’s network conceptualization (see Figure 5 ). The eventual objective was to transition from Amy’s stable maladaptive network to a sustainable adaptive network.

Figure 5. Subnetwork with adaptive nodes added after start of treatment. EEMM dimensions represented by each node are bolded. Size of the arrowheads indicates hypothesized strength of the relationship (bigger arrowheads = stronger correlation), and opacity reflects direction of the relationship (opaque = positive/excitatory, transparent = negative/inhibitory). Right-angled rectangles reflect manipulable variables and rounded rectangles indicate immutable moderators (e.g., historical events). Reinforcing valence of “feeling empowered” is indicated by double-headed excitatory arrows with “responding flexibly to standards and expectations,” “setting and adhering to interpersonal boundaries,” “building connection with others,” and “engaging in self-care activities.”

During this time, Amy made two significant life decisions. The first was to resign from her full-time administrative job to focus on her consulting business and the second was to undergo an elective surgery to improve her physical health, which generated anticipatory excitement and indecisiveness, eliciting the familiar pressure to act responsibly or thoughtfully. These decisions resulted in re-activation of her original network (e.g., increasing worry that others will judge her decisions negatively), though Amy clarified that the decisions was consistent with her values and could conceptualize them as forms of self-care, engaging with her newer “adaptive” subnetwork (see Figure 5 ).

At the end of session 7, the therapist and Amy reviewed personalized items to track via EMA, which led to a revision of the EMA survey (see Table 1 ). The revisions clarified Amy’s current treatment goals and added progress items to monitor progress toward her updated goals. The reason for the EMA review was that Amy had already achieved her early treatment goals of clarifying her values, increasing physical activity, leaving her full-time job, being more present in interpersonal interactions, and maintaining healthy interpersonal boundaries with loved ones.

Starting in session 8, treatment became more focused on retaining newly selected behaviors and further enhancing wellbeing, after Amy indicated that she would like to continue treatment to work on practicing healthy detachment from thoughts and feelings, structuring her life in a more balanced way (e.g., having hobbies outside of work), and being more intentional with her actions. At this time, Amy reported continued reduction in problematic behavior (e.g., reporting public hazards once a week vs. multiple times a week) and an increase in helpful behaviors, such as building interpersonal connections, being more present, and practicing detachment from her expectations and emotions—which, in turn, facilitated valued action.

At the same time, Amy experienced novel stressors related to her significant decisions: managing a business on which she was now primarily financially dependent and decreased access to values-based activities (e.g., socializing with friends, attending public events, and exercise) due to recovery from surgery. For example, she worried about finding health insurance, filing taxes as a business owner, and maintaining financial stability. Thus, although Amy had retained selected skills, her context shifted, providing a useful test for the resilience of Amy’s adaptive network in Figure 5 : would she revert to maladaptive responses (e.g., compulsive checking) or be able to engage in new strategies she had been practicing?

Amy reported improved ability to handle some of these new stressors due to increased “trust in [herself]” to make healthy decisions and evaluating the effectiveness of those decisions with respect to her values. However, she also observed that, in other instances, she was “still trying to prove herself by overcommitting,” which was related to her core belief that she needed to prove her self-worth to others. Treatment was thus spent on reinforcing referencing values rather than standards when making choices in the presence of distress and reflecting on how well she was able to accomplish this since the last session.

In session 12, Amy brought up the issue of struggling to keep up with her values, and it became apparent that Amy had been trying to maximize her values to the extent that doing so felt overwhelming. In addition, she was so concerned with planning her “best life” that she was having difficulty being present when engaging in valued activities. These problems, while different in form, were functionally similar to Amy’s original struggles of attentional rigidity and compulsive problem solving, indicating that Amy had indeed reverted back to parts of her old network. While Amy reported that she was able to respond flexibly to standards and preset boundaries, she found attentional flexibility more challenging. Accordingly, the therapist and Amy reviewed attentional control and mindfulness skills and being discerning about which values to enact.

The final three sessions 16–18 consisted of reflecting on helpful strategies, the contexts in which they worked, ways to generalize and evaluate effectiveness of strategies, progress made, and areas to continue to strengthen. In particular, the sessions focused on the sustainability of changes she was implementing.

Treatment outcomes

Ecological momentary assessment items included Amy’s initial behavioral goals of decreasing use of the email app on her phone and increasing physical activities and, in the latter part of treatment, progress toward new goals. Figure 6 shows changes over time in Amy’s initial behavioral goals, which appears to show greater variability in physical activity over time (with less activity in March due to recovery from surgery) and a steady increase in use of her email app. These behavioral outcomes along would suggest little response to treatment, though it is possible their function changed over time given Amy’s significant contextual shift (e.g., resigning from job to run coaching business full-time). For instance, Amy reported that checking emails became more about managing the transition from part-time to full-time consulting rather than to alleviate worry.

Figure 6. Minutes spent using mail app and engaging in physical activity over the course of treatment. The dashed vertical line indicates the start of treatment. Shaded area shows 95% confidence intervals for best-fitting lines.

We also tracked Amy’s degree of progress toward goals and trust in herself (e.g., to make healthy decisions and engage in valued action) daily (see Figure 7 ). Even though Amy rated herself highly on progress toward goals and trust in self (scores were around 90 out of 100) at the beginning of assessment, there was more fluctuation in the first 2 months (February to April) relative to the latter 2 months of tracking (May to July), suggesting that these indices of progress became more consistent over time.

Figure 7. Amy’s scores for self-rated progress toward goals and degree of trust in herself from mid- to posttreatment.

Group iterative multiple model estimation networks

We used the GIMME algorithm to empirically map parts of Amy’s network during the start and end of treatment (97 observations over 36 days and 233 observations over 169 days, respectively; note that data were collapsed over weeks and do not represent any specific timepoint). Due to participant burden of responding to multiple items multiple times a day, we modeled approximately five nodes of the network for each period. To evaluate consistency between our hypothesized network and the data-driven network, we inspected presence, direction, and strength of the relationships between nodes, noting any significant discrepancies (e.g., direction of arrow was opposite to prediction). The plan was to clarify these discrepancies with the client and adjust the treatment plan accordingly, before continuing empirical testing to see if our revised hypotheses led to more adaptive responding.

The network on the left of Figure 8 shows that, at the start of treatment, Amy’s hyper-vigilance for things going wrong was associated with feeling less peaceful and more attentional bias at the next measurement occasion. In turn, feeling at peace was related to less perceived pressure to act responsibly or thoughtfully. In other words, the hyper-vigilance had a suppressive influence on what could have been a buffer for feeling pressure to be responsible, which was itself linked to more problem solving. Problem solving was associated with greater attentional bias toward problems in her environment, completing a cyclical pattern of looking out for problems and feeling an obligation to immediately resolve them.

Figure 8. Group Iterative Multiple Model Estimation (GIMME)-derived network showing contemporaneous and lagged relationships among EMA items completed by Amy in the first month of treatment on the left, compared to our hypothesized network on the right. Solid lines, contemporaneous; dashed lines, lagged; solid arrowhead, excitatory or positive relationship; blank arrowhead, inhibitory or negative relationship. Size of arrowheads corresponds to strength of relationship estimated by GIMME analyses. Beta estimates are presented in Supplementary Table S1 in Supplementary material .

Our hypothesized network on the right of Figure 8 indicates several discrepancies compared to the empirically formulated network. For example, we had missed the suppressive influence of feeling at peace on the pressure to be responsible and misidentified the direction of the relationship between hypervigilance and problem solving. In terms of treatment planning, this means that we could have done more to practice strategies to bolster Amy’s feelings of peacefulness or to address the pressure to be responsible. In this specific instance, the intervention plan of focusing on attentional regulation and flexibility with respect to standards ended up targeting overlapping pathways (e.g., attentional regulation may have helped Amy to feel more at peace, which led to less problem solving through less pressure to be responsible), which may explain why treatment was still effective. However, our hypothesized processes of change were inaccurate and understanding how change actually occurred has implications for which strategies would be most helpful for targeting potential resurgence of maladaptive behaviors in the future.

As the original nodes became less relevant to Amy’s treatment given that she was building new skills, we began tracking new processes in the latter part of treatment to assess whether Amy was able to maintain a new adaptive network in the presence of stressors. Using GIMME, we found that responding flexibly to standards and expectations was associated with more awareness of current feelings, self-care, and connection building, demonstrating validity that cognitive flexibility was an important skill for Amy (see Figure 9 ). Furthermore, it resulted in more flexible responding at the next measurement occasion, suggested it was self-sustaining, similar to awareness of feelings. The lagged self-recursive relations suggest that the more Amy practiced these skills, the more she was able to access them at subsequent occasions.

Figure 9. Group Iterative Multiple Model Estimation-derived network showing contemporaneous and lagged relationships among EMA items completed by Amy in the final few weeks of treatment on the left, compared to our hypothesized network on the right. Solid lines, contemporaneous; dashed lines, lagged; solid arrowhead, excitatory or positive relationship. Size of arrowheads corresponds to strength of relationship estimated by GIMME analyses. Beta estimates are presented in Supplementary Table S2 in Supplementary material .

Building connection and being present with others not only led to more connection building at the next timepoint but also was associated with an increase in feeling empowered. Feeling empowered also resulted in more of the same at the next assessment, corroborating Amy’s self-report that empowerment was self-reinforcing. Feeling empowered was itself linked to more cognitive flexibility and self-care. By looping back to cognitive flexibility, a three-node self-amplifying subnetwork resulted (cognitive flexibility → building connection → empowerment).

A second self-amplifying networks was identified empirically by GIMME through the feeling of empowerment node because self-care was related to more awareness of current feelings and, at the next timepoint, building connection with others and then back to empowerment.

All the relationships in these networks were excitatory and every node was endogenous (had an arrow feeding into it). Taken as a whole, the entire network and these two self-amplifying subnetworks in particular, seem likely to be stable and self-perpetuating. Clinically, we observed that Amy continued to access skills of cognitive defusion and building connection in the presence of significant stressors, which supports that possibility.

In comparison to the empirical network, the hypothesized network missed that cognitive flexibility and self-care might be positively linked to building connection with others and that self-care was more likely to drive awareness of current feelings that the other way around (see Figure 9 ). While this discrepancy would not significantly change our treatment plan, we might place less emphasis on practicing mindfulness of feelings as its own end if Amy did not find this to be a helpful skill. In this case, Amy reported that it was helpful in itself, even though it did not influence other nodes as we had hypothesized.

Lessons learned

Burden of repeated tracking on client.

Although Amy was initially compliant with completing EMA surveys four times daily, she reported that she found it stressful and difficult to keep up with the surveys on several occasions, resulting in more missing observations toward the end of treatment. This was the primary reason we chose to minimize the number of items administered in each survey. Ideally, we would track every node in Amy’s networks, but this was not pragmatically feasible.

The potential burden of tracking for some clients warrants judicious planning, to the extent possible when working with complex dynamic systems, of variables that can be consistently assessed over the course of treatment. This set of variables should include problematic and desired behaviors and progress toward established treatment goals to capture a comprehensive picture of client functioning and wellbeing. Furthermore, clinicians should generally strive eliminate redundancy and select maximally orthogonal items to explain as much variance with as few items as possible. This may require some form of pilot testing in the first couple weeks of treatment to empirically determine which items to retain.

However, as a caveat, by definition, a dynamic system changes over time, and our preliminary best guesses are necessarily based on a snapshot of the client at intake. Thus, even with careful planning, clinicians may still need to adjust assessment based on client’s evolving needs and goals to meet the constant objective of improving their wellbeing and reducing suffering. Furthermore, given empirical considerations, clinicians also need to be aware of the potential ramifications of administering fewer items, especially if classical psychometric theory is a primary guide. Psychometric validity may be compromised when as few as one item is used to capture a multifaceted psychological construct, increasing measurement error as traditionally viewed within psychometrics ( Piccirillo et al., 2019 ; Bringmann et al., 2022 ). Possible ways to circumvent these issues include incorporating passively collected data (e.g., from wearables and smartphones), reducing number of assessment timepoints, and using planned missing data designs and imputation methods for multivariate time series data ( Piccirillo et al., 2019 ; Bringmann et al., 2022 )—though implementation of these strategies must be theoretically and methodologically defensible, especially since the idiographic basis of PBT challenges features of traditional psychometrics ( Ciarrochi et al., 2022 ).

Duration of assessment

Group Iterative Multiple Model Estimation requires a minimum of 60 datapoints (ideally 100) to reliably estimate a network for a given individual ( Lane et al., 2019 ). Considering our previous point about participant burden, one might recognize a tension between getting data quickly to empirically verify hypotheses as soon as possible and minimizing the number of times a client has to complete a daily EMA survey. For instance, we could collect the necessary data for GIMME analyses in approximately 2 weeks with four daily assessments or take a month with two daily assessments. In addition, aside from addressing pragmatic concerns, using varying timescales impacts the construct validity of variables being measured as viewed in a psychometric context ( Bringmann et al., 2022 ). For example, assessing rapidly shifting constructs less frequently (or vice versa) increases measurement error as traditionally conceived. Thus, clinicians must bear in mind the hypothesized rate of change of variables of interest when determining the delivery schedule of EMA items. While Bayesian methods may eventually permit fewer observations for analysis due to initial consideration of clinically driven starting estimates (as opposed to starting from zero information; Burger et al., 2021 ), most currently available statistical methods still require significant client input via intensive longitudinal assessment.

Changing relevance and function of personalized items

Amy was very involved in the case conceptualization and assessment process, providing input into which items she hypothesized would be helpful to track and were most relevant to her goals. As Amy expanded her network over the course of treatment—adding adaptive nodes and decreasing engagement in maladaptive nodes—the most relevant items changed accordingly. For example, Amy initially tracked how much she felt pressure to be responsible or thoughtful, which contributed to compulsive problem solving and checking, but later was more interested in tracking the extent to which she acted in ways that served her wellbeing as her compulsive behaviors decreased over time and self-care activities gradually increased.

The decision to drop items with low frequency was clinical and pragmatic. First, the therapist and Amy decided that it would be more helpful to focus on behaviors that Amy wanted to retain over time from a strengths-based perspective. Second, Amy found completing surveys four times daily for more than five to eight items burdensome, so we needed to distill the EMA items down to the most relevant and essential variables. However, the change in variables measured presented a research problem: how do we measure progress using different metrics at pre- and posttreatment? Our solution to this quandary was to introduce progress items (see bottom row of Table 1 ) that were designed to capture overall progress with respect to Amy’s overarching treatment goals. These goals were important in that the closer Amy was to accomplishing these goals, the more she was satisfied with the direction of her life.

Failure of topographical behavioral variables to capture adaptive change

Amy initially presented as extremely high-functioning and had already been reporting high frequency of desired behavior (i.e., exercise), which made seeing a further increase in physical activity improbable. In addition, the function of her use of the email app on her smartphone changed over the course of treatment, such that its consistent frequency did not reflect a constant state. Specifically, Amy quit her full-time job during treatment and dedicated more time to building her consulting business. Thus, the initial function of checking emails to reduce anxiety about being perceived as irresponsible or selfish shifted to approaching her value of being financially stable and growing her business. These interpretations are supported by Amy’s self-report that she was no longer immediately responding to emails and more willing to wait until it was a convenient time to do so. In this case, even though the variable remained the same, its meaning and relevance to Amy’s wellbeing had changed. Said in another way, this case revealed once again that topographically defined behavioral goals are not necessarily the same as functionally defined outcomes. The topography-function discrepancy in assessment is one reason to focus on processes of change. In this case the therapist and Amy also introduced variables that were a shorthand for positive change Amy had made in treatment.

The importance of empirical case networks

Knowing that treatment works is not the same as knowing how treatment works. It would have been reasonable to assume because our clients improved in expected ways, that our treatment plan accurately represented core struggles and processes of change. GIMME, used as an empirical case conceptualization tool, showed otherwise. In the present case, this discrepancy turned out to be largely inconsequential—given that our treatment plan targeted pathways that overlapped with those indicated by the empirically derived network—but that should not be assumed. Understanding how treatment works for specific individuals is important once a process-focus is adopted and, thus, the larger lesson of the present case is that conceptual network analysis should not be relied on as the sole evidence of how processes of change apply to a case. Empirical methods need to be developed and used in conjunction with clinical judgment ( Burger et al., 2021 ).

With GIMME, we were able to clarify the processes of change involved in Amy’s response to treatment by checking parts of our hypothesized networks against empirically derived ones. Generally, while we found that had accurately hypothesized certain relationships, we sometimes overlooked relations or misidentified their directionality. The oversight, in Amy’s case, did not warrant an overhaul of our treatment plan, but it is entirely plausible that it could have. For example, if flexible responding to standards exerted no influence on any other node, then we would have needed to examine if Amy was properly practicing flexible responding to standards or if another cognitive strategy would have been more effective. At the same time, most analysts currently will hold empirically derived networks accountable to such traditional psychometric issues as measurement error, so clinicians will need to optimize their data collection setup for hypothesis testing beforehand. Moreover, once analyses have been completed, clinicians should verify empirical findings against clinical observations and client self-report to ensure they maintain a balanced and useful case conceptualization.

The inconsistency between conceptual and empirical networks points to a long-standing weakness of functional analysis, underscoring the need to take into account multiple sources of information ( Steiger, 1990 ). Functional analysis is still advocated in clinical psychology ( Haynes et al., 2011 ), but it is not commonplace because it has remained more of an art than a science. In applied behavior analysis, functional analysis grew substantially when it integrated empirical methods by using an alternating treatment design ( Barlow and Hayes, 1979 ) to identify idiosyncratic reinforcers for undesirable behavior ( Iwata et al., 1982 ). Unfortunately, if clients are even minimally verbal, that direct contingency approach plumets in its ability to reliably identify the functions of actions ( Belisle et al., 2017 ). Another functional analytic approach needs to be found that can accommodate the degree to which verbal/cognitive processes operate on and alter other processes. The present study suggests that the use of EMA data on processes of change analyzed empirically as an idiographic complex network may be that pathway forward. If broadly used, such an approach might provide data person by person on the use of precise clinical interventions linked to processes of change; in effect, building a constellation of cases that can help to inform future case conceptualization.

There will be multiple problems to overcome before that future is fully available, however. For example, when developing and interpreting client networks, clinicians need to clarify the timescale of the relationships among nodes. Hypothesized networks can readily specify variable temporal lags (e.g., healthy eating — > feeling energetic could take a week, whereas feeling energetic — > engaging in hobbies may occur over minutes) but existing network tools such as GIMME often assume that data are measured at equal intervals. Self-report items are difficult to assess on a granular level, but physiological data from wearables (e.g., heartrate variability) may be measured many times each second. In the present case, the empirically derived GIMME networks appeared to be less sensitive to temporally proximal relationships, such as the possible negative reinforcement of compulsive checking through reduction of anxiety. Thus, the generation of adequate idiographic biopsychosocial complex networks are far from turnkey at the present time.

Summary and recommendations

In this report, we provided a case illustration for using a process-based approach to case conceptualization, treatment planning, and treatment delivery to a client, Amy, in an outpatient setting. Generally, results from assessment data indicated that, despite initial high levels of functioning, Amy accumulated new skills targeting key nodes in her initial network that appeared to be resilient against external stressors and further improved her functioning. The specific steps of this case included:

(a) using a network comprised of interrelated variables rather than diagnostic labels and topographical symptoms to describe our client’s presenting problem;

(b) collaborating with the client on her case conceptualization, using her wording and input as much as possible;

(c) administering EMA items on a daily basis to collect intensive longitudinal data to evaluate treatment progress;

(d) designing treatment plan to target nodes that appeared to be contributing to other struggles;

(e) using idiographic statistical analysis to verify hypothesized networks;

(f) adjusting the treatment plan in response to empirical data and contextual shifts (should also be done in response to lack of progress, which did not occur in this case); and

(g) aiming to establish adaptive network and assessing sustainability and resilience of new network.

In some ways, because of the rigor, consideration, and expertise that went into our application of PBT, this case illustration may be considered a current “best-effort” example of how to implement PBT. We recognize that many clinicians may not have the time or bandwidth to monitor daily EMA data from clients, learn advanced statistical techniques, and generate multiple networks for each of the many clients on their caseload. Furthermore, we ourselves observed several aspects that we would do differently in the future, as noted in the Lessons Learned section above. Yet, our objective in providing this case illustration along with the lessons learned along the way was precisely to show that delivering PBT is an iterative process; no clinician will ever consistently deliver PBT “perfectly” given the complexity of our clients and fallibility of human clinicians.

Nonetheless, we believe that implementing principles and core pieces of a process-based approach is feasible. First, clinicians can create networks with their clients to better understand how their problems relate to and drive each other. This could supplement or replace the standard intake interview that most clinicians already do. Second, clinicians can design treatment plans based on the network, selecting among techniques they already have in their therapeutic arsenal. The difference is that the application of these techniques would be process-based, individually tailored, and hypothesis-driven—thereby more precise—rather than diagnosis-focused, similar to making a specific recommendation to eat more leafy greens over asking someone to eat more fruits and vegetables. Thirdly, clinicians who use routine outcome monitoring can use those existing items to test their hypotheses to the extent that the items are relevant and modify their approach accordingly. These changes would not require immense commitments and bring clinicians closer to a process-based approach. Finally, there is no reason that EMA and statistical tools cannot be automated in the form of apps, software, and clinical tools, making the applied task far easier.

Ultimately, through iterative learning, curiosity, cumulative skill acquisition, and the development of technical supports, clinicians will become better able to implement process-based principles with facility and build on existing methods to improve their delivery of idiographic, empirically grounded, and process-based care. It will gradually become easier to engage in intensive longitudinal data collection by automating passive collection of data, administration of self-report items, and complex analysis of these data as the field moves more in a PBT direction.

While PBT has the potential to reform the foundations of clinical practice, it is important to treat its value as a hypothesis that is as yet unproven. The change in direction it suggests is profound. Methods that have adopted a process-focused development strategy have been successful ( Hayes et al., 2022 ), and some supportive early randomized trials of PBT methods have appeared ( Ong et al., 2022 ), but that does not mean that adopting a PBT approach will necessarily lead to greater efficacy in psychological intervention writ large. Many case examples, clinical trials, and laboratory experiments with diverse populations will be needed to put empirical muscle on PBT’s theoretical skeleton. Thus, we offer the present case as a useful beginning example. We hope this paper will be the first of many to evaluate the efficacy and feasibility of a process-based approach. That is the only way to determine whether PBT can live up to its field-changing potential.

Ethics statement

The studies involving human participants were reviewed and approved by the Boston University Charles River Campus Institutional Review Board. The patients/participants provided their written informed consent to participate in this study.

Author contributions

CO analyzed the data. SCH and SGH provided clinical supervision. All authors contributed to case conceptualization and manuscript write-up.

This study was funded in part by the Alexander von Humboldt Foundation.

Acknowledgments

We would like to thank Lisa Smith for providing additional supervision on this case.

Conflict of interest

SGH receives financial support from the Alexander von Humboldt Foundation and the James S. McDonnell Foundation 21st Century Science Initiative in Understanding Human Cognition – Special Initiative. He receives compensation for his work as editor from Springer Nature. He also receives royalties from various publishers.

The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2022.1002849/full#supplementary-material

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Keywords : process-based therapy, case study, processes of change, network analysis, process-based approach

Citation: Ong CW, Hayes SC and Hofmann SG (2022) A process-based approach to cognitive behavioral therapy: A theory-based case illustration. Front. Psychol. 13:1002849. doi: 10.3389/fpsyg.2022.1002849

Received: 25 July 2022; Accepted: 10 October 2022; Published: 25 October 2022.

Reviewed by:

Copyright © 2022 Ong, Hayes and Hofmann. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Clarissa W. Ong, [email protected] ; Steven C. Hayes, [email protected] ; Stefan G. Hofmann, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Behavioral Perspective

The basic idea, theory, meet practice.

TDL is an applied research consultancy. In our work, we leverage the insights of diverse fields—from psychology and economics to machine learning and behavioral data science—to sculpt targeted solutions to nuanced problems.

Many philosophers, scientists and biologists have long sought to answer a simple question: What motivates human beings? What can explain our decisions, actions and behavior? According to the behavioral perspective, the way we behave and learn can be explained through our interactions with the environment. Our actions are always responses to stimuli, which either occur naturally or because of a learned response. 1

The behavioral perspective belongs to a school of thought known as behaviorism or behavioral theory. Behavioral theory is the overarching analysis of human behavior focused on examining a person’s environment and learned associations. Behaviorism suggests that all behavior is acquired through conditioning and can therefore be observed without consideration of thoughts or feelings. Since all behavior is but a response, behaviorism also suggests that anyone can learn to perform any action with the right conditioning. Instead of attributing talents, skills, or behaviors to genetics, personality, or cognition, behaviorists believe them to be simply a product of conditioning. 2

Give me a dozen healthy infants, well-formed, and my own specified world to bring them up and I’ll guarantee to take any one at random and train him to become any type of specialist I might select – doctor, lawyer, merchant-chief, and yes, even beggar man and thief – regardless of his talents, penchants, tendencies, abilities, vocations, and race of his ancestors. – John B. Watson in his paper  “Psychologists as the Behaviorists View It” 2

Stimulus:  Anything that occurs in the environment which makes an individual react to it.

Response:  While we typically think of a response as a physical action, responses can also be verbal or written. As long as the behavior/action is observable and is a reaction to a stimulus, it is known as a response.

Unlearned drive:  A natural human tendency toward food, drink, sleep, or sex that influences decisions and behavior.

Learned drive:  A particular behavior that an individual is taught to exhibit.

Classical Conditioning:  A learning technique that pairs a naturally-occurring stimulus with a chosen stimulus in order to teach an individual to react the same way to the chosen stimulus as they do to the naturally occurring stimulus. 2

Operant Conditioning:  A learning technique that uses positive and negative reinforcements (rewards or punishments) to teach an individual to either continue or cease particular behaviors.

Incentivization :  Trying to coax someone into doing something, or making it more appealing, by promise of reward afterwards.

Behavioral theory was established when behavioral psychologist John B. Watson published his paper “Psychology as the Behaviorists View It” in 1913. 2   In this paper, Watson suggested that people begin life as blank slates and can be conditioned or taught into behaving in any way.

While Watson is often referred to as the father of the behavioral perspective, Ivan Pavlov is the founder of classical conditioning.  Pavlov’s famous experiment is colloquially known as “Pavlov’s Dogs” and was accidentally discovered in 1897 while trying to measure how much saliva dogs produced. Pavlov’s lab assistant would give the dogs a bowl of food, which causes them to salivate. He found that after a while, the dogs would salivate when they would see the lab assistant, regardless of whether he was bringing them food. The naturally-occurring response of salivating when food was presented became associated with a different stimulus, the lab assistant. This study, which demonstrated classical conditioning, helped create a foundation for the behavioral perspective, because it showed that behavior can be trained. 4

Seven years after publishing his paper, Watson also conducted the infamous Little Albert Experiment. Today, this experiment would be deemed unethical, but there were fewer policies and guidelines for psychological experiments in the 1920s. In the Little Albert Experiment, Watson and his graduate student Rosalie Rayner wanted to see if classical conditioning also worked for humans, since Pavlov had shown that it did for dogs. They tested the theory on a baby, Albert. Watson and Rayner showed Little Albert neutral stimuli, including a white rat, a rabbit, and a monkey. Initially, Albert did not respond to any stimulus in a way that indicated fear. However, Albert would burst into tears if a hammer was struck against a steel bar behind his head. Watson and Rayner decided to strike the steel bar when Albert was being shown the white rat. This was repeated a number of times, over two sessions a week apart. At that point, Albert learned to cry when presented with the white rat because he had learned the fear response by associating the rat with a loud noise. 5

Following Watson’s footsteps, from around 1920 to the mid 1950s, the behavioral perspective continued to grow until it became the dominant theory of motivation.This was in part due to the fact that psychology was trying to establish itself as an objective and measurable science. Since the behavioral perspective suggested that internal characteristics have no influence on actions or emotions, it provided the opportunity for objectivity and measurement of external stimuli. 2

Edward Thorndike

Thorndike is best known for his work on learning theory, which B.F. Skinner drew on to theorize operant conditioning in humans. Thorndike developed the ‘law of effect’ which states that satisfying responses in one particular  situation become more likely to occur again in the same situation. Thorndike studied learning theory with cats who attempted to get out of a box using different methods. He found that those who noticed  a lever which would enable them to get out of the box would push the lever again when put back in the box. This experiment became a basis for operant conditioning. 6

Burrhus Frederic (B.F.) Skinner

Skinner was a foundational figure for the behavioral perspective. Skinner thought that classical conditioning was too simplistic as an explanation for all of human behavior and was interested in not only the cause of an action, but also the consequences. He found that behavior that is reinforced through rewards tends to be repeated, whereas behavior which is not reinforced or that which leads to punishment tends to die out. He called this kind of conditioning operant conditioning. 7

Hull believed that human behavior could be explained by conditioning and reinforcement. His theory rested on the concept of homeostasis: he suggested that human motivation arises as a result of biological need. When thirsty, hungry, or tired, Hull claimed that people feel a ‘drive’, defined as tension or arousal, which causes them to behave in ways that will reduce their drive. 8  Hull published these theories in  Principles of Behavior  in 1943.

Kenneth Spence

Spence was Hull’s student and helped him develop his ideas on learning and drive. He took ideas about operant conditioning a step further by suggesting that a response is in fact influenced by the size or value of a reward. For example, if money is being used as an incentive, the amount of money will impact the likelihood of a person exhibiting the desired response. Spence thus suggested that performance depends on reinforcement, as well as motivational incentives. 3

Consequences

With the rise in popularity of the behavioral perspective came a new understanding of psychology. If behavior could be observed and measured, psychology was more similar to science than had previously been understood. Watson wrote in his paper that “ psychology as a behaviorist views it [is] a purely objective experimental branch of natural science. ” 9  

As the behavioral perspective was being adopted throughout the early 20th century, it changed not only how behavior was explained, but what kind of behavior was studied. Only what was observable was deemed important by the behaviorism school of thought, which meant that emotions, cognitive biases, or other internal events were ignored.

The fact that the behavioral perspective studies objective, measurable actions means that it is able to formulate clear predictions about behavior. A vast number of studies support the perspective because it is easy to replicate the stimulus-response environment in a lab. Its findings can also have positive implications in a number of fields. For example, in the field of education, understanding operant conditioning and positive reinforcement can help engage students in the material and motivate them to work hard. In the field of psychotherapy, classical conditioning can be used to help phobic clients rid themselves of fear by associating their feared objects with more neutral or positive stimuli. Behaviorism also provides insights into habit formation and suggests that bad habits can be broken and that good habits can be developed since all behavior is learned. The behavioral perspective lends support to the nurture side of the ‘nature versus nurture’ debate as it attributes all complex behavior to our responses to the environment.

Controversies

Since the behavioral perspective suggests that our behavior (and thus who we are) is all dependent on learning and conditioning, critics argue that the perspective negates free will. Instead of being active agents in our decision-making processes, behaviorists argue that we simply respond to stimuli. This view seems to reduce complex human beings to machinic entities. For this reason, the psychodynamic approach, which Sigmund Freud developed, criticizes the behavioral perspective for not taking into account unconscious influences. Moreover, Freud criticized the behavioral perspective because it views newborns as blank slates who can be conditioned to behave in any way. 9

Moreover, one of the biggest criticisms of the behavioral perspective is that it is reductionist. It suggests  everything  can be explained through the stimulus-response relationship and ignores what cannot be observed, like emotions, internal thoughts, or cognitive biases. To suggest that all behavior can easily be traced back to a response from our environment is to ignore many  facets of our humanity. Individual differences are explained as mere differences in conditioning instead of results of different personalities. 9

Belief in the behavioral perspective has also led to some unethical applications. Cognitive behavioral therapy, the branch of psychotherapy associated with behaviorism, tries to change thinking patterns. While it can be useful to help people deal with anxiety, depression, or maladaptive or intrusive thoughts, it is also historically drawn on in conversion therapy, which tries to convert people’s sexuality from gay to straight.

A number of other perspectives contradict the behavioral perspective, namely:

• The biological perspective, which has gained traction with  scientific advancements, has  allowed us to ‘see’ what happens on the inside. The biological perspective states that all behavior has a physical or organic cause. While our biology can be shaped by the environment, the biological perspective believes that our actions can be explained largely by what happens inside our bodies. 9
• The cognitive perspective rejects the biological perspective because it believes the biological perspective reduces humans to their biological instincts. The cognitive perspective instead suggests that humans are information processors: when we are exposed to stimuli, we access the information that we’ve stored in our minds to form an appropriate response. While the cognitive perspective shares some similarities to the behavioral perspective, it is more concerned with non-observable things like  memory and decision-making. 1
• The cross-cultural perspective, which is relatively new, suggests that behavior is guided by cultural influences. It is often used to describe behavior that seems odd to some people but that is actually a product of norms and customs of a different culture. 1

Since there are so many perspectives, it is difficult to suggest that all behavior can be explained by learning and conditioning alone. While some actions are certainly reinforced or diminished  through conditioning, other factors like genetics, cultures, thoughts, feelings, and environments certainly play into human behavior.

Case Studies

The behavioral perspective and autism.

The behavioral perspective has helped shape therapy and treatment techniques such as  applied behavioral analysis (ABA). ABA helps children learn new behaviors or reduce problematic behaviors and can be especially useful when applied to children who are autistic or who have developmental delays. 10

Children with autism have a range of diverse needs; a common one is help with social skills. They find it difficult to develop stimulus control, so they can benefit from conditioning to learn appropriate responses to stimuli. Through a technique called “discrete child training,” which breaks down tasks into individual components, ABA therapists may provoke a desired behavior, such as asking a polite question, and then reinforce it by use of reward. In this way, ABA therapists condition their clients into behaving in socially acceptable ways. While ABA has been around for a while, it has received extreme criticism from the autistic community, who often call its methods harsh and reductive. Read more  here .

Attachment Styles and Relationships

You might have heard of the four child attachment styles: secure, avoidant, anxious and disorganized. 13  According to the behavioral perspective, experiences during our childhood inform our attachment styles, which influence how we seek out and manage relationships in our adulthood.

When a child develops  a secure attachment style as a kid, she is more likely to grow into an  autonomous adult. Children who exhibit avoidant attachment styles are likely to be dismissive with emotions and expectations from a partner. Those who demonstrate an anxious attachment style as a child are likely to be needy and insecure in adult romantic relationships. Lastly, those with disorganized attachment styles  might find it difficult to tolerate emotional closeness and intimacy with a partner as adults. 13

The belief that there is a chronic pattern of relational behaviors that result from childhood experiences of attachment owes itself to the behavioral perspective. because it suggests that prior experiences condition people to respond to others in particular ways. 14

Related TDL Content

Phantom Cellphone Buzzes: A Behavioral Perspective

Since cellphones are part of the modern day social fabric, this article explores whether excessive use of technology can be considered an addiction. Addictions cause people to become hypersensitive to cues related to rewards they crave. This article provides a behavioral perspective which might help explain why we think our phone has buzzed or pinged even when it hasn’t.

The Science of Reward

Reinforcement learning is one of the biggest takeaways from the behavioral perspective. In this article, we take a deep dive into understanding what kind of incentives motivate behavior and why. In particular, we answer the question: is money an effective incentive for employees?

• Finkelstein, M. (2019, July 1).  What is the behavioral perspective? Understanding the relationship between stimulus, response, and behavior . BetterHelp.  https://www.betterhelp.com/advice/behavior/what-is-the-behavioral-perspective-understanding-the-relationship-between-stimulus-response-and-behavior/
• Cherry, K. (2019, September 24).  History and Key Concepts of Behavioral Psychology . Verywell Mind.  https://www.verywellmind.com/behavioral-psychology-4157183#
• Behavioral Perspective: AP® Psychology Crash Course . (2020, July 23). Albert Resources.  https://www.albert.io/blog/behavioral-perspective-ap-psychology-crash-course
• Husson University. (2018, June 1).  Consumer behavior theories: Pavlovian theory .  https://online.husson.edu/consumer-behavior-pavlovian-theory/
• McLeod, S. (2020).  The Little Albert Experiment . Simply Psychology.  https://www.simplypsychology.org/little-albert.html
• McLeod, S. (2018).  Edward Thorndike: The Law of Effect . Simply Psychology.  https://www.simplypsychology.org/edward-thorndike.html
• McLeod, S. (2007, February 5).  B.F. Skinner – Operant Conditioning . Simply Psychology.  https://www.simplypsychology.org/operant-conditioning.html
• Cherry, K. (2020, September 17).  Drive-Reduction Theory and Human Behavior . Verywell Mind.  https://www.verywellmind.com/drive-reduction-theory-2795381
• McLeod, S. (2007, February 5).  Behaviorist Approach . Simply Psychology.  https://www.simplypsychology.org/behaviorism.html
• Cherry, K. (2020, February 3).  Behavior Analysis in Psychology . Verywell Mind.  https://www.verywellmind.com/what-is-behavior-analysis-2794865
• Hixson, M. D., Wilson, J. L., Doty, S. J., & Vladescu, J. C. (2008). A review of the behavioral theories of autism and evidence for an environmental etiology.  The Journal of Speech and Language Pathology – Applied Behavior Analysis ,  3 (1), 46-59.  https://doi.org/10.1037/h0100232
• Welch, C. D., & Polatajko, H. J. (2016). Applied behavior analysis, autism, and occupational therapy: A search for understanding.  American Journal of Occupational Therapy ,  70 (4), 7004360020p1.  https://doi.org/10.5014/ajot.2016.018689
• Levy, T. (2017, May 25).  Four styles of adult attachment . Evergreen Psychotherapy Center.  https://www.evergreenpsychotherapycenter.com/styles-adult-attachment/
• Mikulincer, M., & Shaver, P. R. (2006). A Behavioral Systems Approach to Romantic Love Relationships: Attachment, Caregiving, and Sex. In R. J. Sternberg & K. Weis (Eds.),  The New Psychology of Love  (pp. 259-279). Yale University Press.

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What Is a Case Study?

Weighing the pros and cons of this method of research

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Cara Lustik is a fact-checker and copywriter.

Verywell / Colleen Tighe

• Pros and Cons

What Types of Case Studies Are Out There?

Where do you find data for a case study, how do i write a psychology case study.

A case study is an in-depth study of one person, group, or event. In a case study, nearly every aspect of the subject's life and history is analyzed to seek patterns and causes of behavior. Case studies can be used in many different fields, including psychology, medicine, education, anthropology, political science, and social work.

The point of a case study is to learn as much as possible about an individual or group so that the information can be generalized to many others. Unfortunately, case studies tend to be highly subjective, and it is sometimes difficult to generalize results to a larger population.

While case studies focus on a single individual or group, they follow a format similar to other types of psychology writing. If you are writing a case study, we got you—here are some rules of APA format to reference.  

At a Glance

A case study, or an in-depth study of a person, group, or event, can be a useful research tool when used wisely. In many cases, case studies are best used in situations where it would be difficult or impossible for you to conduct an experiment. They are helpful for looking at unique situations and allow researchers to gather a lot of˜ information about a specific individual or group of people. However, it's important to be cautious of any bias we draw from them as they are highly subjective.

What Are the Benefits and Limitations of Case Studies?

A case study can have its strengths and weaknesses. Researchers must consider these pros and cons before deciding if this type of study is appropriate for their needs.

One of the greatest advantages of a case study is that it allows researchers to investigate things that are often difficult or impossible to replicate in a lab. Some other benefits of a case study:

• Allows researchers to capture information on the 'how,' 'what,' and 'why,' of something that's implemented
• Gives researchers the chance to collect information on why one strategy might be chosen over another
• Permits researchers to develop hypotheses that can be explored in experimental research

On the other hand, a case study can have some drawbacks:

• It cannot necessarily be generalized to the larger population
• Cannot demonstrate cause and effect
• It may not be scientifically rigorous
• It can lead to bias

Researchers may choose to perform a case study if they want to explore a unique or recently discovered phenomenon. Through their insights, researchers develop additional ideas and study questions that might be explored in future studies.

It's important to remember that the insights from case studies cannot be used to determine cause-and-effect relationships between variables. However, case studies may be used to develop hypotheses that can then be addressed in experimental research.

Case Study Examples

There have been a number of notable case studies in the history of psychology. Much of  Freud's work and theories were developed through individual case studies. Some great examples of case studies in psychology include:

• Anna O : Anna O. was a pseudonym of a woman named Bertha Pappenheim, a patient of a physician named Josef Breuer. While she was never a patient of Freud's, Freud and Breuer discussed her case extensively. The woman was experiencing symptoms of a condition that was then known as hysteria and found that talking about her problems helped relieve her symptoms. Her case played an important part in the development of talk therapy as an approach to mental health treatment.
• Phineas Gage : Phineas Gage was a railroad employee who experienced a terrible accident in which an explosion sent a metal rod through his skull, damaging important portions of his brain. Gage recovered from his accident but was left with serious changes in both personality and behavior.
• Genie : Genie was a young girl subjected to horrific abuse and isolation. The case study of Genie allowed researchers to study whether language learning was possible, even after missing critical periods for language development. Her case also served as an example of how scientific research may interfere with treatment and lead to further abuse of vulnerable individuals.

Such cases demonstrate how case research can be used to study things that researchers could not replicate in experimental settings. In Genie's case, her horrific abuse denied her the opportunity to learn a language at critical points in her development.

This is clearly not something researchers could ethically replicate, but conducting a case study on Genie allowed researchers to study phenomena that are otherwise impossible to reproduce.

There are a few different types of case studies that psychologists and other researchers might use:

• Collective case studies : These involve studying a group of individuals. Researchers might study a group of people in a certain setting or look at an entire community. For example, psychologists might explore how access to resources in a community has affected the collective mental well-being of those who live there.
• Descriptive case studies : These involve starting with a descriptive theory. The subjects are then observed, and the information gathered is compared to the pre-existing theory.
• Explanatory case studies : These   are often used to do causal investigations. In other words, researchers are interested in looking at factors that may have caused certain things to occur.
• Exploratory case studies : These are sometimes used as a prelude to further, more in-depth research. This allows researchers to gather more information before developing their research questions and hypotheses .
• Instrumental case studies : These occur when the individual or group allows researchers to understand more than what is initially obvious to observers.
• Intrinsic case studies : This type of case study is when the researcher has a personal interest in the case. Jean Piaget's observations of his own children are good examples of how an intrinsic case study can contribute to the development of a psychological theory.

The three main case study types often used are intrinsic, instrumental, and collective. Intrinsic case studies are useful for learning about unique cases. Instrumental case studies help look at an individual to learn more about a broader issue. A collective case study can be useful for looking at several cases simultaneously.

The type of case study that psychology researchers use depends on the unique characteristics of the situation and the case itself.

There are a number of different sources and methods that researchers can use to gather information about an individual or group. Six major sources that have been identified by researchers are:

• Archival records : Census records, survey records, and name lists are examples of archival records.
• Direct observation : This strategy involves observing the subject, often in a natural setting . While an individual observer is sometimes used, it is more common to utilize a group of observers.
• Documents : Letters, newspaper articles, administrative records, etc., are the types of documents often used as sources.
• Interviews : Interviews are one of the most important methods for gathering information in case studies. An interview can involve structured survey questions or more open-ended questions.
• Participant observation : When the researcher serves as a participant in events and observes the actions and outcomes, it is called participant observation.
• Physical artifacts : Tools, objects, instruments, and other artifacts are often observed during a direct observation of the subject.

If you have been directed to write a case study for a psychology course, be sure to check with your instructor for any specific guidelines you need to follow. If you are writing your case study for a professional publication, check with the publisher for their specific guidelines for submitting a case study.

Here is a general outline of what should be included in a case study.

Section 1: A Case History

This section will have the following structure and content:

Background information : The first section of your paper will present your client's background. Include factors such as age, gender, work, health status, family mental health history, family and social relationships, drug and alcohol history, life difficulties, goals, and coping skills and weaknesses.

Description of the presenting problem : In the next section of your case study, you will describe the problem or symptoms that the client presented with.

Describe any physical, emotional, or sensory symptoms reported by the client. Thoughts, feelings, and perceptions related to the symptoms should also be noted. Any screening or diagnostic assessments that are used should also be described in detail and all scores reported.

Your diagnosis : Provide your diagnosis and give the appropriate Diagnostic and Statistical Manual code. Explain how you reached your diagnosis, how the client's symptoms fit the diagnostic criteria for the disorder(s), or any possible difficulties in reaching a diagnosis.

Section 2: Treatment Plan

This portion of the paper will address the chosen treatment for the condition. This might also include the theoretical basis for the chosen treatment or any other evidence that might exist to support why this approach was chosen.

• Cognitive behavioral approach : Explain how a cognitive behavioral therapist would approach treatment. Offer background information on cognitive behavioral therapy and describe the treatment sessions, client response, and outcome of this type of treatment. Make note of any difficulties or successes encountered by your client during treatment.
• Humanistic approach : Describe a humanistic approach that could be used to treat your client, such as client-centered therapy . Provide information on the type of treatment you chose, the client's reaction to the treatment, and the end result of this approach. Explain why the treatment was successful or unsuccessful.
• Psychoanalytic approach : Describe how a psychoanalytic therapist would view the client's problem. Provide some background on the psychoanalytic approach and cite relevant references. Explain how psychoanalytic therapy would be used to treat the client, how the client would respond to therapy, and the effectiveness of this treatment approach.
• Pharmacological approach : If treatment primarily involves the use of medications, explain which medications were used and why. Provide background on the effectiveness of these medications and how monotherapy may compare with an approach that combines medications with therapy or other treatments.

This section of a case study should also include information about the treatment goals, process, and outcomes.

When you are writing a case study, you should also include a section where you discuss the case study itself, including the strengths and limitiations of the study. You should note how the findings of your case study might support previous research. 

In your discussion section, you should also describe some of the implications of your case study. What ideas or findings might require further exploration? How might researchers go about exploring some of these questions in additional studies?

Need More Tips?

Here are a few additional pointers to keep in mind when formatting your case study:

• Never refer to the subject of your case study as "the client." Instead, use their name or a pseudonym.
• Read examples of case studies to gain an idea about the style and format.
• Remember to use APA format when citing references .

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach .  BMC Med Res Methodol . 2011;11:100.

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach . BMC Med Res Methodol . 2011 Jun 27;11:100. doi:10.1186/1471-2288-11-100

Gagnon, Yves-Chantal.  The Case Study as Research Method: A Practical Handbook . Canada, Chicago Review Press Incorporated DBA Independent Pub Group, 2010.

Yin, Robert K. Case Study Research and Applications: Design and Methods . United States, SAGE Publications, 2017.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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Behavioral Management for Children and Adolescents: Assessing the Evidence

• Melissa H. Johnson , M.A., M.P.H. ,
• Preethy George , Ph.D. ,
• Mary I. Armstrong , Ph.D. ,
• D. Russell Lyman , Ph.D. ,
• Richard H. Dougherty , Ph.D. ,
• Allen S. Daniels , Ed.D. ,
• Sushmita Shoma Ghose , Ph.D. , and
• Miriam E. Delphin-Rittmon , Ph.D.

Search for more papers by this author

Behavioral management services for children and adolescents are important components of the mental health service system. Behavioral management is a direct service designed to help develop or maintain prosocial behaviors in the home, school, or community. This review examined evidence for the effectiveness of family-centered, school-based, and integrated interventions.

Literature reviews and individual studies published from 1995 through 2012 were identified by searching PubMed, PsycINFO, Applied Social Sciences Index and Abstracts, Sociological Abstracts, Social Services Abstracts, Published International Literature on Traumatic Stress, the Educational Resources Information Center, and the Cumulative Index to Nursing and Allied Health Literature. Authors chose from three levels of evidence (high, moderate, and low) based on benchmarks for the number of studies and quality of their methodology. They also described the evidence of service effectiveness.

The level of evidence for behavioral management was rated as high because of the number of well-designed randomized controlled trials across settings, particularly for family-centered and integrated family- and school-based interventions. Results for the effectiveness of behavioral management interventions were strong, depending on the type of intervention and mode of implementation. Evidence for school-based interventions as an isolated service was mixed, partly because complexities of evaluating group interventions in schools resulted in somewhat less rigor.

Conclusions

Behavioral management services should be considered for inclusion in covered plans. Further research addressing the mechanisms of effect and specific populations, particularly at the school level, will assist in bolstering the evidence base for this important category of clinical intervention.

Problem behavior early in life can be related to later development of negative outcomes, such as school dropout, academic problems, violence, delinquency, and substance use; in addition, early childhood delinquent behavior may predict criminal activity in adulthood ( 1 – 7 ). Therefore, interventions designed to address problem behavior and increase prosocial behavior are important for children and adolescents and for families, teachers, school officials, community members, and policy makers. This article provides an assessment of behavioral management interventions for children and adolescents who have behavior problems.

This article reports the results of a literature review that was undertaken as part of the Assessing the Evidence Base Series (see box on next page). For purposes of this series, the Substance Abuse and Mental Health Services Administration (SAMHSA) has described behavioral management as a direct service that is designed to help a child or adolescent develop or maintain prosocial behaviors in the home, school, or community. Examples of these behaviors include demonstrating positive, nonaggressive relationships with parents, teachers, and peers; showing empathy and concern for others; and complying with rules and authority figures. Table 1 presents a description of the service and its components. Behavioral management interventions are individualized to the person’s needs.

About the AEB Series

The Assessing the Evidence Base (AEB) Series presents literature reviews for 13 commonly used, recovery-focused mental health and substance use services. Authors evaluated research articles and reviews specific to each service that were published from 1995 through 2012 or 2013. Each AEB Series article presents ratings of the strength of the evidence for the service, descriptions of service effectiveness, and recommendations for future implementation and research. The target audience includes state mental health and substance use program directors and their senior staff, Medicaid staff, other purchasers of health care services (for example, managed care organizations and commercial insurance), leaders in community health organizations, providers, consumers and family members, and others interested in the empirical evidence base for these services. The research was sponsored by the Substance Abuse and Mental Health Services Administration to help inform decisions about which services should be covered in public and commercially funded plans. Details about the research methodology and bases for the conclusions are included in the introduction to the AEB Series ( 26 ).

The treatment literature includes a variety of behavioral management interventions that are designed to address problem behaviors (for example, externalizing or acting-out behaviors) of children and adolescents when implemented in various settings. Given the breadth and variations of these interventions, behavioral health policy makers, providers, and family members may benefit from a brief review of specific behavioral management interventions and their value as covered services in a benefit package.

The purposes of this article are to describe behavioral management services and highlight specific behavioral management interventions that are implemented in community settings, rate the level of evidence (methodological quality) of existing studies, and describe the effectiveness of these services on the basis of the research. We identify three models of behavioral management interventions that can be implemented, depending on the intervention setting and the needs of children or groups of children and their families. To facilitate use by a broad audience of mental health services personnel and policy makers, we provide an overall assessment of research quality and briefly highlight key findings. The results will provide state mental health directors and staff, policy officials, purchasers of health services, and community health care administrators with a simple summary of the evidence for a range of behavioral management services and implications for research and practice.

Description of behavioral management

Behavioral management for children and adolescents is a general category of intervention that is often incorporated as part of a variety of clinical practices that differ by setting and populations of focus. These interventions share common goals, which are listed in Table 1 . Behavioral management interventions for children and adolescents included in this review address various problem behaviors, including noncompliance at home or at school, disruptive behavior, aggressive behavior, rule breaking, and delinquent behaviors. For purposes of this article, clinical components of behavioral management interventions for children were compiled from various practice-relevant sources ( 8 – 11 ).

Behavioral management is grounded in social learning theory and applied behavior analysis. Social learning theory asserts that people learn within a social context, primarily by observing and imitating the actions of others, and that learning is also influenced by being rewarded or punished for particular behaviors ( 12 ). Based on the principles of social learning theory, applied behavior analysis uses general learning principles, direct observation, objective measurement, and analytic assessment to shape behavior and solve problems that are clinically significant for an individual or family ( 11 ). The approach often is used for children with autism spectrum disorders; however, applied behavior analysis principles and techniques can be used more generally with behavioral management interventions for various child behavior problems.

Examples of specific behavioral management treatment activities include observing and documenting child behaviors, identifying antecedents of behaviors, utilizing motivating factors in reinforcement strategies, developing behavioral plans to address identified problem behaviors, coordinating interventions across different settings in which children function, and training other individuals in a child’s life to address specific behavioral objectives or goals. Behavioral management services typically are delivered through an individualized plan that is based on a clinical assessment. An assessment identifies the needs of the child or adolescent and the family and establishes goals, intervention plans, discharge criteria, and a discharge plan. Behavioral management plans are implemented through teaching, training, and coaching activities that are designed to help individuals establish and maintain developmentally appropriate social and behavioral competencies. Services may involve coordination of other care or referral to complementary services.

Behavioral management interventions may be delivered by family members, teachers, professional therapists, or a team of individuals working in concert to address the needs of a child or adolescent. A behavioral management therapist collaborates with the child or adolescent and the family to develop specific, mutually agreed-upon behavioral objectives and interventions to alter or improve specific behaviors. The resulting behavioral management treatment plan may also include a risk management or safety plan to identify risks that are specific to the individual. In some cases, a contingency plan is developed to address specific risks should they arise. Behavioral management professionals work in partnership with family members or teachers to implement a behavioral plan and monitor the child’s behavior and progress.

Three basic models of behavioral management interventions in the research literature are family-centered behavioral interventions, school-based behavioral interventions that can include services implemented across grades or classrooms or as individually targeted services, and integrated home-school programs. We focus on behavioral management interventions for children who are evidencing problem behavior and on interventions that include families and have some level of personalization that addresses the child’s needs.

Family-centered behavioral interventions

Family-centered interventions emphasize the role of parents or other caregivers in helping to manage problem behaviors of children, and they frequently focus on parenting practices. The interventions can be clinic based or offered in community settings or in the home. Behavioral parent training interventions are among the more commonly used family-centered behavioral management models. These interventions specifically target individual children with identified behavior problems and their families and generally teach parents to increase positive interactions with children and reduce harsh and inconsistent discipline practices. Behavioral parent training programs are delivered in a variety of formats. For example, some behavioral parenting interventions may involve parents, children, or teachers, and some may be delivered only to parents. Behavioral parent training interventions also vary in the extent to which they are customized to specific needs of the child. For purposes of this article, we focus on behavioral parent training interventions that involve planning for specific behavior problems that are expressed by a child and working with the parent and child, rather than group-based parent training programs that do not involve the child or are not customized based on specific behavioral needs.

Two family-centered behavioral interventions that meet the criteria for this review are Parent-Child Interaction Therapy (PCIT) and the Incredible Years programs. PCIT uses live coaching of parents during parent-child interactions to help parents establish nurturing relationships with their children, clear parent-child communication and limit setting, and consistent contingencies for child behavior ( 13 , 14 ). The Incredible Years parent training and child training programs involve addressing problem behavior of children aged two to ten years who have a diagnosis of a disruptive behavior disorder or are exhibiting subclinical levels of problem behavior ( 15 , 16 ). During treatment, a therapist works with parents and children in group settings and uses vignettes, focused discussions, role plays, and problem-solving approaches to illustrate and discuss specific behavioral management techniques. Both of these interventions incorporate behavioral management strategies of rewarding prosocial behavior, limiting reinforcement of inappropriate behavior, and delivering appropriate consequences for misbehavior.

School-based behavioral interventions

School-based behavioral interventions specifically target problem behaviors that occur in the school setting, and they use teachers and school staff as interveners in the management of student behaviors. One model that is commonly used in school settings is Positive Behavior Support (PBS). This model describes strategies that are implemented with the whole school to improve behavior and school climate and to prevent or change patterns of problem behavior ( 17 ). Based on applied behavior analysis, person-centered planning (an approach designed to assist the individual in planning his or her life and supports, often to increase self-determination and independence), and inclusion principles, PBS aims to support behavioral success by implementing nonpunitive behavioral management techniques in a systematic and consistent manner ( 18 , 19 ). PBS models of intervention seek to prevent problem behavior by altering conflict-inducing situations before problems escalate while concurrently teaching appropriate alternative behaviors ( 8 ).

Specific school-based interventions developed based on the PBS model include Positive Behavioral Interventions and Supports ( 20 ) and Safe & Civil Schools ( 21 ). These school-based interventions implement behavioral management strategies and tailor the level of intervention for the unique needs of a child or adolescent. PBS interventions utilize three levels of treatment: a primary tier, applied to the entire school setting to prevent challenging behaviors; a secondary tier, targeting individuals who display emerging or moderate behavior problems; and a tertiary tier for students who evidence more significant behavior problems and require complex and individualized team-based support beyond what is delivered at the primary and secondary levels ( 10 ). Interventions at the tertiary level involve tailored behavioral management strategies outlined in a behavioral management plan ( 22 ). To direct this review to treatment approaches for children with identified behavior problems, we focused on school-based behavioral management interventions that fall within the tertiary tier of intensity.

Integrated behavioral interventions

Integrated interventions combine school- and family-centered treatment components to create cohesive programs that address child behaviors in school and home settings. Three integrated programs are assessed in this review: Fast Track, Child Life and Attention Skills (CLAS), and the Adolescent Transitions Program (ATP). The Fast Track program is a long-term intervention that is designed to prevent antisocial behavior and psychiatric disorders among children identified as demonstrating disruptive behavior by parents and teachers. It uses a combination of parent behavioral management training, child social cognitive skills training, tutoring or mentoring, individualized home visits, and a classroom curriculum ( 23 ). The CLAS program is designed to reduce inattention symptoms and improve organizational and social skills among children with attention-deficit hyperactivity disorder (ADHD), inattentive type, through a combination of teacher consultation, parent training, and child skills training ( 24 ). ATP is a communitywide, family-centered intervention delivered through schools that takes a multilevel approach to addressing adolescent behavior problems ( 25 ). Similar to the three-tiered system of intervention described with school-based PBS, ATP uses tiered universal, selected, and indicated interventions to address different groups of children and families, depending on the child’s level of symptom expression. That is, universal interventions are designed for all parents and children in a school setting, selected interventions are for families and children at elevated risk, and indicated interventions are for families of children with early signs of problem behavior that do not yet meet clinically diagnosable levels of a mental disorder. The indicated level of intervention entails a variety of family treatment services, including brief family intervention, a school monitoring system, parent groups, behavioral family therapy, and case management services. These components vary depending on the individual needs of the child and family.

Search strategy

To provide a summary of the evidence and effectiveness for behavioral management, we conducted a survey of major databases: PubMed (U.S. National Library of Medicine and National Institutes of Health), PsycINFO (American Psychological Association), Applied Social Sciences Index and Abstracts, Sociological Abstracts, Social Services Abstracts, Published International Literature on Traumatic Stress, the Educational Resources Information Center, and the Cumulative Index to Nursing and Allied Health Literature.

We reviewed meta-analyses, research reviews, and individual studies from 1995 through 2012. We also examined bibliographies of major reviews and meta-analyses. We used combinations of the following search terms: behavioral management, behavior management, behavioral management therapy, behavior specialist, mental health, substance abuse, children, and adolescents. Additional citations were gathered from reference sections of articles. We used an independent consensus process when reviewing abstracts found through the literature search to determine whether a study used a behavioral management approach, on the basis of the conceptual definition of behavioral management provided above.

Inclusion and exclusion criteria

This review included U.S. and international studies in English of the following types: randomized controlled trials (RCTs), quasi-experimental studies, and review articles, such as meta-analyses and systematic reviews. The focus of this review was on clinical intervention approaches for children or adolescents who presented with problem behaviors or elevated risk at the beginning of the intervention. Included in the search were studies of family-focused parent training interventions that involved individualization based on the needs of the child and that involved the child and family members. Also included were studies of interventions in which the child or adolescent was selected for inclusion on the basis of the presence of problem behaviors that were targeted for change during the active treatment period.

Some populations and intervention programs were excluded to ensure basic similarities of the participants, interventions, and outcome measures and to be able to draw conclusions about whether the behavioral management intervention itself (as opposed to other intervention components) was associated with the outcomes. Studies that focused on children with autism spectrum disorders or other pervasive developmental disorders, intellectual disabilities, or fetal alcohol spectrum disorder were excluded. There is a large body of literature on behavioral management interventions for children with autism spectrum disorders and developmental disabilities, which we believe would be more appropriately reviewed in a separate article. Also excluded were universal preventive interventions that are not part of a multitiered program, because of our focus on individualized clinical intervention approaches. Universal preventive interventions address all individuals in a population, regardless of symptom severity or level of risk; as a result, the strategies and approaches used are distinct from those of more targeted interventions and more appropriately reviewed in a separate article. Finally, we excluded intervention models that may incorporate behavioral management components but are not exclusively behavioral management interventions or do not explicitly focus on child and adolescent behavior problems, such as Homebuilders, Multisystemic Therapy, Functional Family Therapy, individual cognitive-behavioral therapy, and behavioral management interventions in residential treatment centers and psychiatric hospitals.

Strength of the evidence

The methodology used to rate the strength of the evidence is described in detail in the introduction to this series ( 26 ). The research designs of the studies identified by the literature search were examined. Three levels of evidence (high, moderate, and low) were used to indicate the overall research quality of the collection of studies. Ratings were based on predefined benchmarks that considered the number and quality of the studies. If ratings were dissimilar, a consensus opinion was reached.

In general, high ratings indicate confidence in the reported outcomes and are based on three or more RCTs with adequate designs or two RCTs plus two quasi-experimental studies with adequate designs. Moderate ratings indicate that there is some adequate research to judge the service, although it is possible that future research could influence initial conclusions. Moderate ratings are based on the following three options: two or more quasi-experimental studies with adequate design; one quasi-experimental study plus one RCT with adequate design; or at least two RCTs with some methodological weaknesses or at least three quasi-experimental studies with some methodological weaknesses. Low ratings indicate that research for this service is not adequate to draw evidence-based conclusions. Low ratings indicate that studies have nonexperimental designs, there are no RCTs, or there is no more than one adequately designed quasi-experimental study.

We accounted for other design factors that could increase or decrease the evidence rating, such as how the service, populations, and interventions were defined; use of statistical methods to account for baseline differences between experimental and comparison groups; identification of moderating or confounding variables with appropriate statistical controls; examination of attrition and follow-up; use of psychometrically sound measures; and indications of potential research bias.

Effectiveness of the service

We described the effectiveness of the service—that is, how well the outcomes of the studies met the service goals. We compiled the findings for separate outcome measures and study populations, summarized the results, and noted differences across investigations. We considered the quality of the research design in our conclusions about the strength of the evidence and the effectiveness of the service.

Results and discussion

Level of evidence.

Five reviews of family-centered behavioral interventions ( 16 , 27 – 30 ), two reviews of school-based behavioral interventions ( 9 , 19 ), and one review of integrated behavioral interventions ( 25 ) were identified. Twelve RCTs that had been published after the previous reviews had been conducted were also identified. Their topics were family-centered behavioral interventions ( 31 – 34 ), school-based behavioral interventions ( 35 – 37 ), and integrated behavioral interventions ( 23 , 24 , 38 – 40 ). Tables 2 and 3 summarize the reviews and the RCTs, respectively.

a Articles are in chronological order by intervention type. Review articles sometimes included citations for interventions not described in this article. Only studies of interventions included in this article are described in the table. Abbreviations: ADHD, attention-deficit hyperactivity disorder; CD, conduct disorder; ODD, oppositional defiant disorder; PCIT, Parent-Child Interaction Therapy; RCT, randomized controlled trial

a Articles are in chronological order by intervention type. Abbreviations: ADHD, attention-deficit hyperactivity disorder; CD, conduct disorder; CLAS, Child Life and Attention Skills; ODD, oppositional defiant disorder; PCIT, Parent-Child Interaction Therapy;

b Multiple publications based on the same randomized controlled trial

Participants who received behavioral management interventions included children in preschool, elementary, middle, and high school grades. Studies included a range of racial-ethnic groups and rural and urban populations. Across studies, children who received behavioral management interventions typically were described as exhibiting problem behaviors or externalizing behaviors.

Overall, given the strength of the research designs in more than three RCTs, the level of evidence for the various types of behavioral management interventions was rated as high. However, the complexities of evaluating school-based interventions have resulted in somewhat less rigor in that area of behavioral management research. Reviews and individual studies of family-based and integrated family- and school-based behavioral management interventions included in this review used strong RCT designs, and several included intent-to-treat analyses.

RCTs of family-centered behavioral interventions (as defined for this article) have been examined in multiple review articles ( 27 – 30 ) and individual studies. Across both types of publications, the evaluations examining the effects of PCIT and Incredible Years behavioral parenting programs had adequate statistical power to detect treatment effects, used well-designed RCTs, utilized interventions with treatment manuals and fidelity data, and measured clinical outcomes with reliable and valid assessment instruments. Findings for both programs have also been replicated in multiple RCTs conducted by independent investigators.

Researchers have noted that most studies evaluating the effectiveness of tertiary-level school-based interventions have included students with significant disabilities in self-contained classrooms, which limits the generalizability of the evidence to general education students in typical classroom settings ( 37 , 41 ). Researchers also noted that studies in this body of literature generally have small samples, lack RCTs, use single-subject or within-group research designs, do not always use standardized behavioral management protocols, and are limited in their ability to report whether school personnel were implementing the interventions with fidelity ( 37 , 41 – 43 ). However, in this review we included three studies of tertiary-level school-based interventions using RCTs ( 35 – 37 ). Researchers indicated various limitations of the design (which varied across studies), including the lack of fidelity measures of team implementation of the intervention, attrition over time, limited measurement of interrater reliability of observational data, lack of validated assessment measurement, and lack of statistical analyses to account for school-level differences.

Integrated behavioral management intervention studies included in this review used strong RCT designs, had adequate statistical power to detect treatment effects, and used intent-to-treat analyses ( 23 – 25 ). One limitation is that these integrated behavioral management interventions have been studied primarily by program developers. The literature would be strengthened if these RCTs were replicated by independent researchers and demonstrated similar results.

Family-centered behavioral interventions.

Family-centered parent training interventions have been reviewed extensively and have demonstrated strong effects in reducing and preventing problem behaviors across a range of ages and populations when compared with wait-list control groups ( 16 , 28 – 30 ). Reviews found PCIT to be effective in reducing disruptive behavior of young children. Eyberg and colleagues ( 16 ) reviewed two well-designed RCTs with wait-list control groups and indicated that PCIT was superior in reducing disruptive behavior of children aged three to six years. The comparison groups in the two studies were not active controls or placebo treatment conditions, which resulted in a “probably efficacious” rating for PCIT ( 16 ). A meta-analysis of PCIT included 13 studies from eight cohorts and three research groups ( 28 ). The researchers compared children who received PCIT with children in nonclinical comparison groups and concluded that mothers of children who received PCIT reported greater declines in problem behaviors. There were large effects for positive behaviors observed in the classroom.

Adaptations and abbreviated versions of PCIT and the Incredible Years program showed preliminary positive effects in various populations, including Mexican-American families ( 44 ), Chinese families ( 33 , 45 ), African-American families ( 46 ), children in Head Start ( 47 , 48 ), and children identified in pediatric medical settings ( 31 , 32 , 49 ). Various forms of the Incredible Years program implemented for children with significant needs reduced problem behaviors among children with a diagnosis of ADHD ( 34 ) and oppositional defiant disorder ( 50 ) six months after the intervention. Overall, compared with control groups, these family-centered parent training programs had strong effects in reducing externalizing behaviors (immediately after the intervention and at follow-up) among children across a range of ages.

School-based interventions.

Research findings were mixed on the effectiveness of tertiary-level school-based interventions. Two meta-analyses of tertiary-level interventions that used functional behavioral assessments found that these interventions were effective in reducing problem behavior across a range of disabilities and grades ( 9 , 19 ). However, these results should be interpreted with caution, because the studies evaluated in these reviews had methodological limitations (for example, single-participant research designs and small samples). Two RCTs with elementary school students found effects in reducing externalizing behavior, compared with control groups, at the end of the intervention ( 36 ) and at the follow-up 14 months after the pretest ( 37 ), as indicated by self-reported scores on standardized instruments and observer ratings of student behavior. Compared with students in control groups, students in the intervention group also evidenced higher ratings of self-reported social skills; improvements were also seen in time engaged in academic activities, as measured by independent observational assessment ( 36 ). These positive effects were not replicated in a rigorous RCT that examined the effects of a three-tiered, schoolwide aggression intervention in early- and late-grade elementary schools in an inner city and in an urban poor community ( 35 ). Researchers found that compared with the control condition, the tertiary-level intervention had significant effects on aggressive behavior when it was delivered to children during the early school years in the urban poor community. Aggressive behavior was measured through a composite of standardized assessment instruments. However, none of the interventions were effective in preventing aggression among older elementary school children.

Integrated behavioral management interventions.

Integrated interventions demonstrated promising findings in preventing and reducing problem behaviors among diagnosed and at-risk children. The Fast Track program had a significant impact on lowering the likelihood of diagnosis of conduct disorder and externalizing behavior among children identified as being at the highest risk of antisocial behavior; however, the intervention did not have an impact on the resulting diagnoses of children who had moderate baseline risk levels ( 23 ). In a recent article that assessed the impact on the onset of various disorders of random assignment to the Fast Track intervention, researchers found that the intervention implemented over a ten-year period prevented externalizing psychiatric disorders among the highest risk group, including during the two years after the intervention ended ( 40 ). In another study, youths who had participated in the Fast Track program had reduced use of professional general medical, pediatric, and emergency department services for health-related problems, compared with youths in a control group, ten years after the first year of the intervention ( 39 ). These findings indicate that this program could be very beneficial and cost-effective if targeted to high-risk children.

The CLAS program also demonstrated significant positive results; children receiving this intervention showed decreased inattention symptoms and increased social and organizational skills compared with peers who were assigned randomly to a control group ( 24 ). For families randomly assigned to ATP, adolescents had lower rates of antisocial behavior and substance use, and families reported stronger parent-child interactions and parenting practices, compared with those in control conditions ( 25 , 38 ). Overall, the effectiveness of integrated behavioral management interventions can be characterized as relatively strong.

Evidence is promising regarding the effectiveness of specific behavioral management interventions. Although these effects vary depending on setting and intervention type and some studies had methodological limitations, a number of reviews and subsequent studies have reported positive results of these interventions for improving child behavior in multiple settings. The level of evidence is in the high range, particularly among family-centered and integrated family-school program models (see box on this page). The benefits of integrated family-school models include service access for families. If implemented early, such interventions may assist in early detection and treatment of problem behaviors before they become more severe. Children and adolescents have been shown to benefit from these interventions, and given the importance of early intervention to reduce the potentially negative consequences of disruptive behavior later in life, these findings are encouraging. In addition, integrated family-school approaches appear to allow strategies that are implemented in the home to be reinforced in school settings, thus providing an additional level of collaboration and support between the school and family.

Evidence for the effectiveness of behavioral management for children and adolescents: high

Overall, positive outcomes found in the literature:

For policy makers and payers (for example, state mental health and substance use directors, managed care companies, and county behavioral health administrators), the findings of this review suggest a number of benefits to the implementation of behavioral management interventions. Detection and intervention at early stages of problem behavior generally are less costly than intensive services for severe problem behavior. Implementation of effective treatment when children exhibit early signs of problem behavior may prevent future engagement in criminal activity, substance use, and juvenile justice system involvement. It may also reduce the need for costly emergency services or residential treatment. There has been limited research examining the long-term outcomes of behavioral management interventions; however, some studies—such as those investigating Fast Track ( 39 , 40 )—have shown positive long-term results into young adulthood. There could be considerable cost savings if these interventions demonstrate long-lasting impacts; thus, future research should continue to examine the long-term outcomes of these types of behavioral management programs.

Studies need to be replicated by independent investigators in ethnically and racially diverse populations to confirm the strength of the evidence base and generalizability of the results. The level of evidence is somewhat dependent on the implementation setting assessed, and research findings are mixed on the effectiveness of school-based interventions that are not integrated with family interventions. There is a need for further research to examine for whom and under what conditions tertiary school-based interventions are effective, and research suggests that starting early in development may be a particularly effective approach.

For decision makers, research has established the value of behavioral management approaches to address problem behavior, and we recommend that behavioral management be considered as part of covered services. However, additional research is needed to examine the effects of behavioral management interventions implemented in school settings, given various methodological limitations in the literature. Current limitations of research conducted in this area are related to generalizability, measurement, study design, and long-term outcomes. Also, as researchers have highlighted, interventions that are designed to address the behavioral needs of children in school settings should examine not only the treatment effects but also the conditions under which an intervention in a school setting is most effective ( 35 ). Factors such as symptom severity, school characteristics, and the child’s race, ethnicity, language (including language fluency of the parents), and sex are important moderating variables to examine when determining the effects of a school-based intervention. In addition, future research on behavioral management interventions should specifically examine the various treatment components included in the intervention to determine whether there are “key ingredients” associated with particular outcomes that are effective without commercial packaging or whether the specific combinations of practices contained in these intervention packages are required to produce the reported results.

Acknowledgments and disclosures

Development of the Assessing the Evidence Base Series was supported by contracts HHSS283200700029I/HHSS28342002T, HHSS283200700006I/HHSS28342003T, and HHSS2832007000171/HHSS28300001T from 2010 through 2013 from the Substance Abuse and Mental Health Services Administration (SAMHSA). The authors acknowledge the contributions of Paolo del Vecchio, M.S.W., Kevin Malone, B.A., and Suzanne Fields, M.S.W., from SAMHSA; John O’Brien, M.A., from the Centers for Medicare & Medicaid Services; Garrett Moran, Ph.D., from Westat; and John Easterday, Ph.D., Linda Lee, Ph.D., Rosanna Coffey, Ph.D., and Tami Mark, Ph.D., from Truven Health Analytics. The views expressed in this article are those of the authors and do not necessarily represent the views of SAMHSA.

The authors report no competing interests.

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• Review Article
• Published: 10 May 2022

Understanding and shaping the future of work with self-determination theory

• Marylène Gagné   ORCID: orcid.org/0000-0003-3248-8947 1 ,
• Sharon K. Parker   ORCID: orcid.org/0000-0002-0978-1873 1 ,
• Mark A. Griffin   ORCID: orcid.org/0000-0003-4326-7752 1 ,
• Patrick D. Dunlop   ORCID: orcid.org/0000-0002-5225-6409 1 ,
• Caroline Knight   ORCID: orcid.org/0000-0001-9894-7750 1 ,
• Florian E. Klonek   ORCID: orcid.org/0000-0002-4466-0890 1 &
• Xavier Parent-Rocheleau   ORCID: orcid.org/0000-0001-5015-3214 2  

Nature Reviews Psychology volume  1 ,  pages 378–392 ( 2022 ) Cite this article

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Self-determination theory has shaped our understanding of what optimizes worker motivation by providing insights into how work context influences basic psychological needs for competence, autonomy and relatedness. As technological innovations change the nature of work, self-determination theory can provide insight into how the resulting uncertainty and interdependence might influence worker motivation, performance and well-being. In this Review, we summarize what self-determination theory has brought to the domain of work and how it is helping researchers and practitioners to shape the future of work. We consider how the experiences of job candidates are influenced by the new technologies used to assess and select them, and how self-determination theory can help to improve candidate attitudes and performance during selection assessments. We also discuss how technology transforms the design of work and its impact on worker motivation. We then describe three cases where technology is affecting work design and examine how this might influence needs satisfaction and motivation: remote work, virtual teamwork and algorithmic management. An understanding of how future work is likely to influence the satisfaction of the psychological needs of workers and how future work can be designed to satisfy such needs is of the utmost importance to worker performance and well-being.

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Introduction

The nature of work is changing as technology enables new forms of automation and communication across many industries. Although the image of human-like robots replacing human jobs is vivid, it does not reflect the typical ways people will engage with automation and how technology will change job requirements in the future. A more relevant picture is one in which people interact over dispersed networks using continuously improving communication platforms mediated by artificial intelligence (AI). Examples include the acceleration of remote working arrangements caused by the COVID-19 pandemic and the increased use of remote control operations across many industries including mining, manufacturing, transport, education and health.

Historically, automation has replaced more routine physically demanding, dangerous or repetitive work in industries such as manufacturing, with little impact on professional and managerial occupations 1 . However, since the mid-2010s, automation has replaced many repetitive error-prone administrative tasks such as processing legal documents, directing service queries and employee selection screening 2 , 3 . Thus, work requirements for employees are increasingly encompassing tasks that cannot be readily automated, such as interpersonal negotiations and service innovations 4 : in other words, work that cannot be easily achieved through algorithms.

The role of motivation is often overlooked when designing and implementing technology in the workplace, even though technological changes can have a major impact on people’s motivation. Self-determination theory offers a useful multidimensional conceptualization of motivation that can help predict these impacts. According to self-determination theory 5 , 6 , three psychological needs must be fulfilled to adequately motivate workers and ensure that they perform optimally and experience well-being. Specifically, people need to feel that they are effective and masters of their environment (need for competence), that they are agents of their own behaviour as opposed to a ‘pawn’ of external pressures (need for autonomy), and that they experience meaningful connections with other people (need for relatedness) 5 , 7 . Meta-analytic evidence shows that satisfying these three needs is associated with better performance, reduced burnout, more organizational commitment and reduced turnover intentions 8 .

Self-determination theory also distinguishes between different types of motivation that workers might experience: intrinsic motivation (doing something for its own sake, out of interest and enjoyment), extrinsic motivation (doing something for an instrumental reason) and amotivation (lacking any reason to engage in an activity). Extrinsic motivation is subdivided according to the degree to which external influences are internalized (absorbed and transformed into internal tools to regulate activity engagement) 5 , 9 . According to meta-analytic evidence, more self-determined (that is, intrinsic or more internalized) motivation is more positively associated with key attitudinal and performance outcomes, such as job satisfaction, organizational commitment, job performance and proactivity than more controlled motivation (that is, extrinsic or less internalized) 10 . Consequently, researchers advocate the development and promotion of self-determined motivation across various life domains, including work 11 . Satisfaction of the three psychological needs described above is significantly related to more self-determined motivation 8 .

Given the impact of the needs proposed in self-determination theory on work motivation and consequently work outcomes (Fig.  1 ), it is important to find ways to satisfy these needs and avoid undermining them in the workplace. Organizational research has consequently focused on managerial and leadership behaviours that support or thwart these needs and promote different types of work motivation 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 (Fig.  2 ). There is also substantial research on the effects of work design (the nature and organization of people’s work tasks within a job or role, such as who makes what decisions, the extent to which people’s tasks are varied, or whether people work alone or in a team structure) and compensation systems on need satisfaction and work motivation 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , and how individuals can seek to meet their needs and enhance their motivation through proactive efforts to craft their jobs 38 , 39 , 40 .

According to self-determination theory, satisfaction of three psychological needs (competence, autonomy and relatedness) influences work motivation, which influences outcomes. More intrinsic and internalized motivations are associated with more positive outcomes than extrinsic and less internalized motivations. These needs and motivations might be influenced by the increased uncertainty and interdependence that characterize the future of work.

Summary of research findings 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 and available meta-analyses 8 , 10 . In cases where the evidence is mixed, a negative sign indicates a negative correlation, a positive sign indicates a positive correlation, and a zero indicates no statistically significant correlation.

Importantly, the work tasks that people are more likely to do in future work will require high-level cognitive and emotional skills that are more likely to be developed, used, and sustained when underpinned by self-determined motivation 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 . Therefore, if individuals are to be effective in future work, it is important to understand how future work might meet — or fail to meet — the psychological needs proposed by self-determination theory.

In this Review, we outline how work is changing and explain the consequences of these changes for satisfying workers’ psychological needs. We then focus on two areas where technology is already changing the worker experience: when workers apply for jobs and go through selection processes; and when the design of their work — what work they do, as well as how, when and where they do it — is transformed by technology. In particular, we focus on three domains where technology is already changing work design: remote work, virtual teams and algorithmic management. We conclude by discussing the importance of satisfying the psychological needs of workers when designing and implementing technologies in the workplace.

Future work requirements

The future workplace might evolve into one where psychological needs are better fulfilled, or one where they are neglected. In addition, there is growing concern that future work will meet the needs of people with adequate access to technology and the skills to use it, but will further diminish fulfillment for neglected and disadvantaged groups 51 (Box  1 ). To understand how future work might align with human needs, it is necessary to map key work features to core constructs of self-determination theory. Future work might be characterized by environmental uncertainty interdependence, complexity, volatility and ambiguity 52 . Here we focus on uncertainty and interdependence because these features capture core concerns about the future and its implication for connections among people in the changing context of work 53 . Higher levels of uncertainty require more adaptive behaviours, whereas higher levels of interdependence require more social, team-oriented and network-oriented behaviours 54 .

We first consider the increasing role of uncertainty in the workplace. Rapid changes in technology and global supply chains mean that the environment is more unpredictable and that there is increasing uncertainty about what activities are needed to be successful. Reducing uncertainty is central to most theories of human adaptation 55 and is a strong motivational basis for goals and behaviour 56 . If uncertainty becomes a defining and pervasive feature of organizational life, organizational leaders should think beyond reducing uncertainty and instead leverage and even create it 55 . In other words, in a highly dynamic context, it might be more functional and adaptive for employees and organizational leaders to consider more explorative approaches to coping with uncertainty, such as experimentation and improvization. All of these considerations imply that future effective work will require adaptive behaviours such as modifying the way work is done, and proactive behaviours such as innovating and creating new ways of working 54 .

Under higher levels of uncertainty, specific actions are difficult to define in advance. In contrast to action sequences that can be codified (for example, with algorithms) and repeated in predictable environments, the best action sequence is likely to involve flexibility and experimentation when the workplace is more uncertain. In this context, individuals must be motivated to explore new ideas, adjust their behaviour and engage with ongoing change. In stable and predictable environments, less self-determined forms of motivation might be sufficient to maintain the enactment of repetitive tasks and automation is more feasible as a replacement or support. However, under conditions of uncertainty, individuals will benefit from showing cognitive flexibility, creativity and proactivity, all behaviours that are more likely to emerge when people have self-determined motivation 40 , 41 , 44 , 46 , 47 , 48 , 49 , 57 .

Adaptive (coping with and responding to change) and proactive (initiating change) performance can be promoted by satisfying the needs for competence, autonomy and relatedness, and self-determined motivation 4 , 58 . For example, when individuals experience internalized motivation, they have a ‘reason to’ engage in the sometimes psychologically risky behaviour of proactivity 40 . Both adaptivity and proactivity depend on individuals having sufficient autonomy to work differently, try new ideas and negotiate multiple pathways to success. Hence, successful organizational functioning depends on people who can act autonomously to regulate their behaviour in response to a more unpredictable and changing environment 31 , 54 , 59 .

The second feature of the evolving workplace is an increasing level of interdependence among people, systems and technology. People will connect with each other in more numerous and complex ways as communication technologies become more reliable, deeply networked and faster. For example, medical teams from disparate locations might collaborate more easily in real time to support remote surgical procedures. They will also connect with automated entities such as cobots (robots that interact with humans) and decision-making aids supported by constantly updating algorithms. For example, algorithms might provide medical teams with predictive information about patient progress based on streaming data such as heart rate. As algorithms evolve in complexity and predictive accuracy, they will modify the work context and humans will need to adapt to work with the new information created 60 .

This interconnected and evolving future workplace requires individuals who can interact effectively across complex networks. The nature of different communication technologies can both increase and decrease feelings of relatedness depending on the extent to which they promote meaningful interactions. Typically, work technologies are developed to facilitate productivity and efficiency. However, given that human performance is also influenced by feelings of relatedness 8 , it is important to ensure that communication technologies and the way networks of people are managed by these technologies can fulfill this need.

The rapid growth of networks enabled by communication technologies (for example, Microsoft Teams, Slack and Webex) has produced positive and negative effects on performance and well-being. For example, these technologies can be a buffer against loneliness for remote workers or homeworkers 61 and enable stronger connections among distributed workers 62 . However, networking platforms lead some individuals to experience more isolation rather than more connectedness 63 . Workplace networks might also engender these contrasting effects by, for example, building a stronger understanding between individuals in a work group who do not usually get to interact or by limiting contact to more superficial communication that prevents individuals from building stronger relationships.

Both uncertainty and interdependence will challenge people’s feelings of competence. Uncertainty can lead to reduced access to predictable resources and less certainty about the success of work effort; the proliferation of networks and media can lead to feeling overwhelmed and to difficulties in managing communication and relationships. Moreover, technologies and automation can lead to the loss of human competencies as people stop using these skills 64 , 65 , 66 , 67 . For example, automating tasks that require humans to have basic financial skills diminishes opportunities for humans to develop expertise in financial skills.

Uncertainty and interdependence are likely to persist and increase in the future. This has implications for whether and how psychological needs will be satisfied or frustrated. In addition, because uncertainty and interdependence require people to behave in more adaptive and proactive ways, it is important to create future work that satisfies psychological needs.

Box 1 Inequalities caused by future work

Future work is likely to exacerbate inequalities. First, the digital divide (unequal access to, and ability to use, information communication technologies) 51 is likely to be exacerbated by technological advances that might become more costly and require more specialized skills. Moreover, the COVID-19 pandemic exacerbated work inequalities by providing better opportunities to those with digital access and skills 210 , 211 . The digital divide now also includes ‘algorithm awareness’ (knowing what algorithms do) which influences whether and how people are influenced by technology. Indeed, the degree to which algorithms influence attitudes and behaviours is negatively associated with the degree to which people are aware of algorithms and understand how they work 212 .

Second, future work is likely to require new technical and communication skills, as well as adaptive and proactive skills. Thus, people with such skills are more likely to find work than those who do not or who have fewer opportunities (for example, education access) to develop them. Even gig work requires that workers have access to relevant platforms and adequate skills for using them. These future work issues are therefore likely to increase gaps between skilled and non-skilled segments of the population, and consequently to increase societal pay disparities and poverty.

For example, workforce inequalities between mature and younger workers are likely to increase owing to real or perceived differences in technology-related skills, with increased disparities in the type of jobs these workers engage in 210 , 213 . Older workers might miss out on opportunities to upskill or might choose to leave the workforce early rather than face reskilling. This could decrease workforce diversity and strengthen negative stereotypes about mature workers (such as that they are not flexible, adaptable or motivated to keep up with changing times) 214 . Furthermore, inequalities in terms of pay have already been observed between men and women 215 . Increased robotization increases the gender pay gap 216 , and this gap is likely to be exacerbated as remote working becomes more common (as was shown during the pandemic) 217 . For example, one study found that salaries did not increase as much for women working flexibly compared to men 218 ; another study found that home workers tended to be employees with young children and these workers were 50% less likely to be promoted than those based in the office 140 .

To promote equality in future work and ensure that psychological needs are met, managers will need to adopt ‘meta-strategies’ to promote inclusivity (ensuring that all employees feel included in the workplace and are treated fairly, regardless of whether they are working remotely or not), individualization of work (ensuring that work is tailored to individual needs and desires) and employee integration (promoting interaction between employees of all ages, nationalities and backgrounds) 213 .

The future of employee selection

Changing economies are increasing demand for highly skilled labour, meaning that employers are forced to compete heavily for talent 68 . Meanwhile, technological developments, largely delivered online, have radically increased the reach, scalability and variety of selection methods available to employers 69 . Technology-based assessments also afford candidates the autonomy to interact with prospective employers at times and locations of their choosing 70 , 71 . Furthermore, video-based, virtual, gamified and AI-based assessment technologies 3 , 72 , 73 , 74 have improved the fidelity and immersion of the selection process. The fidelity of a selection assessment represents the extent to which it can reproduce the physical and psychological aspects of the work situation that the assessment is intended to simulate 75 . Virtual environments and video-based assessments can better reproduce working environments than traditional ‘paper and pencil’ assessments, and AI is being used to simulate social interactions in work or similar contexts 74 . Immersion represents how engrossing or absorbing an assessment experience is. Immersion is enhanced by richer media and gamified assessment elements 75 , 76 . These benefits have driven the widespread adoption of technology in recruitment practices 77 , but they have also attracted criticism. For example, the use of AI to analyse candidate data (such as CVs, social media profiles, text-based responses to interview questions, and videos) 78 raises concerns about the relevance of data being collected for selecting employees, transparency in how the data are used, and biases in selection based on these data 79 .

Candidates with a poor understanding of what data are being collected and how they are being used might experience a technology-based selection process as autonomy-thwarting. For example, the perceived job-relatedness of an assessment is associated with whether or not candidates view the assessment positively 69 , 80 . However, with today’s technology, assessments that appear typical or basic (such as a test or short recorded interview response) might also involve the collection of additional ‘trace’ data such as mouse movements and clicks (in the case of tests), or ancillary information such as ‘micro-expressions’ or candidates’ video backdrops 81 . We expect that it would be difficult for candidates to evaluate the job-relatedness of this information, unless provided with a rationale. Candidates may also feel increasing pressure to submit to employers’ requests to share personal information, such as social media profiles, which may further frustrate autonomy to the extent that candidates are reluctant to share this information 82 .

Furthermore, if candidates do not understand how technology-driven assessments work and are not able to receive feedback from assessment systems, their need for competence may be thwarted 83 . For example, initial research shows that people perceive fewer opportunities to demonstrate their strengths and capabilities in interviews they know will be evaluated by AI, compared to those evaluated by humans 83 .

Finally, because candidates are increasingly interacting with systems, rather than people, their opportunities to build relatedness with employers might be stifled. A notable exemplar is the use of asynchronous video interviews 70 , 71 , a type of video-based assessment where candidates log into an online system, are presented with a series of questions, and are asked to video-record their responses. Unlike a traditional or videoconference interview, candidates completing an asynchronous video interview do not interact directly with anyone from the employer organization, and they consequently often describe the experience as impersonal 84 . Absent any interventions, the use of asynchronous video interviews removes the opportunity for candidates to meet the employer and get a feel for what it might be like to work for the employer, or to ask questions of their own 84 .

Because technologies have changed rapidly, research on candidates’ reactions to these new selection methods has not kept up 69 . Nonetheless, to the extent that test-related and technology-related anxiety influences motivation and performance when completing an online assessment or a video interview, the performance of applicants might be adversely affected 85 . Furthermore, candidate experience can influence decisions to accept a job offer and how positively the candidate will talk about the organization to other potential candidates and even clients, thereby influencing brand reputation 86 . Thus, technology developments offer clear opportunities to improve the satisfaction of candidates’ needs and to assess them in richer environments that more closely resemble work settings. However, there are risks that technology that is needs-thwarting or is implemented in a needs-thwarting manner, will add to the uncertainty already inherent in competitive job applications. In the context of a globally competitive skills market, employers risk losing high-quality candidates.

The future of work design

Discussion in the popular press about the impact of AI and other forms of digitalization focuses on eradicating large numbers of jobs and mass unemployment. However, the reality is that tasks within jobs are being influenced by digitalization rather than whole jobs being replaced 87 . Most occupations in most industries have at least some tasks that could be replaced by AI, yet currently there is no occupation in which all tasks could be replaced 88 . The consequence of this observation is that people will need to increasingly interact with machines as part of their jobs. This raises work design questions, such as how people and machines should share tasks, and the consequences of different choices in this respect.

Work design theory is intimately connected to self-determination theory, with early scholars arguing that work arrangements should create jobs in which employees can satisfy their core psychological needs 89 . Core aspects of work design, including decision-making power, the opportunity to use skills and do a variety of tasks, the ability to ascertain the impact of one’s work, performance feedback 90 , social contact, time pressure, emotional demands and role conflict 91 are important predictors of job satisfaction, job performance 92 and work motivation 93 . Some evidence suggests that these motivating characteristics (considered ‘job resources’ according to the jobs demands–resources model) 94 are especially important for fostering motivation or reducing strain when job demands (aspects of a job that require sustained physical, emotional or mental effort) are high 93 , 95 . For example, autonomy and social support can reduce the effect of workload on negative outcomes such as exhaustion 96 .

Technology can potentially influence work design and therefore employee motivation in positive ways 1 . Increasing workers’ task variety and opportunities for more complex problem-solving should occur whenever technology takes over tasks (such as assembly line or mining work). Leaving the less routine and more interesting tasks for people to do 97 increases the opportunity for workers to fulfill their need for competence. For example, within manufacturing, complex production systems in which cyber-machines are connected in a factory-wide information network require strategic human decision-makers operating in complex, varied and high-level autonomy jobs 98 . Technology (such as social media) can also enhance social contact and support in some jobs and under some circumstances 86 , 87 (but see ref. 63 ), increasing opportunities for meeting relatedness needs.

However, new technologies can also undermine the design of motivating work, and thus reduce workers’ need satisfaction 1 . For example, in the aviation industry, manual flying skills can become degraded due to a lack of opportunity to practice when aircraft are highly automated 99 , decreasing the opportunity for pilots to meet their need for competence. As another example, technology has enabled the introduction of ‘microwork’ in which jobs are broken down into small tasks that are then carried out via information communication technologies 100 . Such jobs often lack variety, skill use and meaning 101 , again reducing the opportunity for the work to meet competence needs. In an analysis of robots in surgery, technology designed purely for ‘efficiency’ reduced the opportunities for trainee surgeons to engage in challenging tasks and resulted in impaired skill development 102 , and therefore probably reduced competence need satisfaction. Thus, poor work design might negatively influence work motivation through poor need satisfaction, especially the need for competence, owing to the lack of opportunity to maintain one’s skills or gain new ones 2 .

As the above examples show, the impact of new technologies on work design, and hence on need satisfaction, is powerful — but also mixed. That is, digital technologies can increase or decrease motivational work characteristics and can thereby influence need satisfaction (Fig.  3 ). The research shows that there is no deterministic relationship between technology and work design; instead, the effect of new technology on work design, and hence on motivation, depends on various moderating factors 1 . These moderating factors include individual aspects, such as the level of skill an individual has or the individual’s personality. Highly skilled individuals or those with proactive personalities might actively shape the technology and/or craft their work design to better meet their needs and increase their motivation 1 . For example, tech-savvy Uber drivers subject to algorithmic management sometimes resist or game the system, such as by cancelling rides to avoid negative ratings from passengers 103 .

The causal relationships among the possible (but not exhaustive) variables implicated in the influence of technology on work design and work motivation discussed in this Review.

More generally, individuals proactively seek a better fit with their job through behaviours such as idiosyncratic deals (non-standard work arrangements negotiated between an employee and an employer) and job crafting (changing one’s work design to align one’s job with personal needs, goals and skills) 39 , 40 (Box  2 ). Consequently, although there is relatively little research on proactivity in work redesign through technology, it is important to recognize that individuals will not necessarily be passive in the face of negative technologies. Just as time pressure can stimulate proactivity 104 , we should expect that technology that creates poor work design will motivate job crafting and other proactive behaviours from workers seeking to meet their psychological needs better 105 . This perspective fits with a broader approach to technology that emphasizes human agency 106 .

Importantly, mitigating and managing the impact of technology on work is not the sole responsibility of individuals. Organizational implementation factors (for example, whether technology is selected, designed and implemented in a participatory way or how much training is given to support the introduction of technology) and technological design factors (for example, how much worker control is built into automated systems) are also fundamental in shaping the effect of technology on work design. Understanding these moderating factors is important because they provide potential ‘levers’ for creating more motivating work while still capitalizing on the advantages of technologies. For example, in one case study 107 , several new digital technologies such as cobots and digital paper flow (systems that integrate and automate different organizational functions, such as sales and purchasing with accounting, inventory control and dispatch) were implemented following a strong technocentric approach (that is, highly focused on engineering solutions) with little worker participation, and with limited attention to creating motivating work design. A more human-centred approach could have prevented the considerable negative outcomes that followed (including friction, reduced morale, loss of motivation, errors and impaired performance) 107 . Ultimately, how technology is designed and implemented should be proactively adapted to better meet human competencies, needs and values.

Box 2 The future of careers

Employment stability started to decline during the 1980s with the rise of public ownership and international trade, the increased use of performance-based incentives and contracts, and the introduction of new technologies. Employment stability is expected to continue to decline with the growth of gig work and continued technological developments 219 , 220 . Indeed, people will more frequently be asked to change career paths as work is transformed by technology, to use and ‘sell’ their transferrable skills in creative ways, and to reskill. The rise of more precarious work and new employment relationships (for example, in gig work) adds to these career challenges 221 . The current generation of workers is likely to experience career shocks (disruptive events that trigger a sensemaking process regarding one’s career) caused by rapid technological changes, and indeed many workers have already experienced career shocks from the pandemic 222 . Moreover, rapid technological change and increasing uncertainty pushes organizations to hire for skill sets rather than fitting people into set jobs, requiring people to be aware of their skills and to know how to market them.

In short, the careers of the current and future workforce will be non-linear and will require people to be more adaptive and proactive in crafting their career. For this reason, the concept of a protean career, whereby people have an adaptive and self-directed career, is likely to be increasingly important 223 . A protean career is a career that is guided by a search for self-fulfillment and is characterized by frequent learning cycles that push an individual into constant transformation; a successful protean career therefore requires a combination of adaptivity skills and identity awareness 224 , 225 . Adaptivity allows people to forge their career by using, or even creating, emerging opportunities. Having a solid sense of self helps individuals to make choices according to personal strengths and values. However, a protean career orientation might fit only a small segment of the labour market. Change-averse individuals might regard protean careers as career-destructive and the identity changes associated with a protean career might be regarded as stressful. In addition, overly frequent transitions might limit deep learning opportunities and achievements, and disrupt important support networks 221 .

Nonetheless, career-related adaptive and proactive behaviours can be encouraged by satisfying psychological needs. In fact, protean careers tend to flourish in environments that provide autonomy and allow for proactivity, with support for competence and learning 223 , 226 . Moreover, people have greater self-awareness when they feel autonomous. Indeed, self-awareness is a component of authenticity and mindfulness, both of which are linked to the satisfaction of the need for autonomy 227 , 228 . Thus, supporting psychological needs during training, development and career transitions is likely to assist people in crafting successful careers.

Applications

In what follows, we describe three specific cases where technology is already influencing work design (virtual and remote work, virtual teamwork, and algorithmic management), and consider the potential consequences for worker need satisfaction and motivation.

Virtual and remote work

Technologies have significantly altered when and where people can work, with the Covid-19 pandemic vastly accelerating the extent of working from home (Box  3 ). Remote work has persisted beyond the early stages of the Covid-19 pandemic with hybrid working — where people work from home some days a week and at the workplace on other days — becoming commonplace 108 . The development of information communication technologies (such as Microsoft Teams) has enabled workers to easily connect with colleagues, clients and patients remotely 105 , for example, via online patient ‘telehealth’ consultations, webinars and discussion forums. Technology has even enabled the remote control of other technologies, such as manufacturing machinery, vehicles and remote systems that monitor hospital ward patient vital signs through AI 1 . However, even when people are working on work premises (that is, not working remotely), an increasing amount of work in many jobs is done virtually (for example, online training or communicating with a colleague next door via email).

Working virtually is inherently tied to changes in uncertainty and interdependence. Virtual work engenders uncertainty because workplace and interpersonal cues are less available or reliable in providing virtual employees with role clarity and ensuring smooth interactions. Indeed, ‘screen’ interactions are more stressful and effortful than face-to-face interactions. It is more difficult to decipher and synchronize non-verbal behaviour on a screen than face-to-face, particularly given the lack of body language cues due to camera frame limitations, increasing the cognitive load for meeting attendees 109 , 110 , 111 , 112 . Non-verbal synchrony can be affected by the video streaming speed, which also increases cognitive load 109 , 110 , 111 , 112 . Virtual interactions involve ‘hyper gaze’ from seeing grids of staring faces, which the brain interprets as a threat 109 , 110 , 111 , 112 . Seeing oneself on screen increases self-consciousness during social interactions, which can cause anxiety, especially in women and those from minoritized groups 109 , 110 , 111 , 112 . Finally, reduced mobility from having to stay in the camera frame has been shown to reduce individual performance relative to face-to-face meetings 109 , 110 , 111 , 112 . Research on virtual interactions is still in its infancy. In one study, workers were randomly assigned to have their camera either on or off during their daily virtual meetings for a week. Those with the camera on during meetings experienced more daily fatigue and less daily work engagement than those with the camera off 113 .

Lower-quality virtual communication between managers and colleagues can leave individuals unclear about their goals and priorities, and how they should achieve them 114 . This calls for more self-regulation 115 because employees must structure their daily work activities and remind themselves of their work priorities and goals, without relying on the physical presence of colleagues or managers. If virtual workers must coordinate some of their work tasks with colleagues, it can be difficult to synchronize and coordinate actions, working schedules and breaks, motivate each other, and assist each other with timely information exchange 115 . This can make it harder for employees to acquire and share information 53 .

Virtual work also affects work design and changes how psychological needs can be satisfied and frustrated (Table  1 ), which has implications for both managers and employees. Physical workplace cues that usually guide work behaviours and routines in the office do not exist in virtual work, consequently demanding more autonomous regulation of work behaviours 116 , 117 . Some remote workers experience an increased sense of control and autonomy over their work environment 118 , 119 , 120 under these circumstances, resulting in lower family–work conflict, depression and turnover 121 , 122 . However, managers and organizations might rob workers of this autonomy by closely monitoring them, for example by checking their computer or phone usage 123 . This type of close monitoring reflects a lack of manager trust in individuals’ abilities or intentions to work effectively remotely. This lack of trust leads to decreased feelings of autonomy 124 , increased employee home–work conflict 105 and distress 125 , 126 . Surveillance has been shown to decrease self-determined motivation 127 . It is therefore important to train managers in managing remote workers in an autonomy-supportive way to avoid these negative consequences 128 . The negative effects of monitoring can also be reduced if monitoring is used constructively to help employees develop through feedback 129 , 130 , 131 , 132 , 133 , and when employees participate in the design and control of the monitoring systems 134 , 135 .

Information communication technology might satisfy competence needs by increasing access to global information and communication and the ability to analyse data 136 . For example, online courses, training and webinars can improve workers’ knowledge, skills and abilities, and can therefore help workers to carry out their work tasks more proficiently, which increases self-efficacy and a sense of competence. Furthermore, the internet allows people to connect rapidly and asynchronously with experts around the world, who may be able to provide information needed to solve a work problem that local colleagues cannot help with 136 . This type of remote work is increasingly occurring whether or not individuals themselves are based remotely, and can potentially enhance performance.

At the same time, technology might thwart competence needs, and increase fatigue and stress. For example, constant electronic messages (such as email or keeping track of online messaging platforms such as Slack or Microsoft Teams) are likely to increase in volume when working remotely, but can be distracting and prevent individuals from completing core tasks while they respond to incoming messages 136 . The frustration of the need for competence can increase if individuals are constantly switching tasks to deal with overwhelming correspondence and failing to finish tasks in a timely manner. In addition, information communication technology enables access to what some individuals might perceive as an overwhelming amount of information (for example, through the internet, email and messages) which can lead to a lot of time spent sifting and processing information. This can be interpreted as a job demand that might make individuals feel incompetent if it is not clear what information is most important. Individuals might also require training in the use of information communication technology, and even then, technology can malfunction, preventing workers from completing tasks, and causing frustration and distress 136 , 137 .

Finally, remote workers can suffer from professional isolation because there are fewer opportunities to meet or be introduced to connections that enable career development and progression 138 , which could influence their feelings of competence in the long run. Although some research suggests that those who work flexibly are viewed as less committed to their career 139 and might be overlooked for career progression 140 , other research has found no relationship between remote working and career prospects 119 .

Virtual work can also present challenges for meeting workers’ need for relatedness 141 . Remote workers can feel isolated from, and excluded by, colleagues and fail to gain the social support they might receive if co-located 142 , 143 , weakening their sense of belonging to a team or organization 144 and their job performance 145 . This effect will probably be accentuated in the future: if the current trend for working from home continues, more people will be dissociated from office social environments more often and indefinitely. Office social environments could be degraded permanently if fewer people frequent the office on a daily basis, such that workers may not be in the office at the same time as collaborators, and there might be fewer people to ask for help or talk with informally. We do not yet know the long-term implications of a degraded social environment, but some suggest that extended virtual working could create a society where people have poor communication skills and in which social isolation and anxiety are exacerbated 146 . Self-determination theory suggests that it will be critical to actively design hybrid and remote work that meets relatedness needs to prevent these long-term issues. When working remotely, simple actions could be effective, such as actively providing opportunities for connecting with others, for example, through ‘virtual coffee breaks’ 147 . Individuals could also be ‘buddied’ up into pairs who regularly check in with each other via virtual platforms.

Hybrid work seems to offer the best of both worlds, providing opportunities for connection and collaboration while in the workplace, and affording autonomy in terms of flexible working. Some research suggests that two remote workdays a week provides the optimum balance 148 . However, it is likely that this balance will be affected by individual characteristics and desires, as well as by differences in work roles and goals. For example, Israeli employees with autism who had to work from home during the COVID-19 pandemic experienced significantly lower competence and autonomy satisfaction than before the pandemic 149 . Yet remote workers high in emotional stability and job autonomy reported higher autonomy and relatedness satisfaction compared to those with low emotional stability 120 . These findings suggest that managers and individuals should consider the interplay between individual characteristics, work design and psychological need satisfaction when considering virtual and remote work.

Box 3 The ‘great resignation’

‘The great resignation’ refers to the massive wave of employee departures during the COVID-19 pandemic in several parts of the world, including North America, Europe and China 229 , 230 , that can be attributed in part to career shocks caused by the pandemic 222 . In the healthcare profession, the shock consisted of an exponential increase in workload and the resulting exhaustion, coupled with the disorganization caused by lack of resources and compounded by health fears 231 . In other industries, the pandemic caused work disruptions by forcing or allowing people to work from home, furloughing employees for varying periods of time, or lay-offs caused by an abrupt loss of business (such as in the tourism and hospitality industries).

Scholars have speculated that these shocks have resulted in a staggering number of people not wanting to go back to work or quitting their current jobs 232 . For example, the hospitality and tourism industries failed to attract employees back following lay-offs 233 . Career shocks can trigger a sensemaking process that can lead one to question how time is spent at work and the benefits one draws from it. For example, the transition to working from home made employees question how and why they work 234 . Frequent health and financial concerns, juggling school closures and complications in caring for dependents have compounded exhaustion and disorganization issues. Some have even renamed ‘the great resignation’ as ‘the great discontent’ to highlight that many people reported wanting to quit because of dissatisfaction with their work conditions 235 .

It might be helpful to understand ‘the great resignation’ through the lens of basic psychological need satisfaction. Being stretched to the limit might influence the need for competence and relatedness when workers feel they have suboptimal ways to connect with colleagues and insufficient time to balance work with other life activities that connect them to family and friends 128 , 236 . The sensemaking process that accompanies career shocks might highlight a lack of meaningful work that decreases the satisfaction of the need for autonomy. This lack of need satisfaction might lead people to take advantage of the disruption to ‘cut their losses’ by reorienting their life priorities and career goals, leading to resignation from their current jobs 237 , 238 .

Alternatively, the experiences gained from working differently during the COVID-19 pandemic might have made many workers aware of how work could be (for example, one does not have to commute), emboldening them to demand better work design and work conditions for themselves. Not surprisingly, barely a year after ‘the great resignation’ many are now talking about ‘the great reshuffle’, suggesting that many people who quit their jobs used this time to rethink their careers and find more satisfying work 239 . Generally, this has meant getting better pay and seeking work that aligns better with individual values and that provides a better work–life balance: in other words, work that better meets psychological needs for competence, autonomy and relatedness.

Virtual teamwork

Uncertainty and interconnectedness make work more complex, increasing the need for teamwork across many industries 150 . Work teams are groups of individuals that must both collaborate and work interdependently to achieve shared objectives 151 . Technology has created opportunities to develop work teams that operate virtually. Virtual teams are individuals working interdependently towards a common goal but who are geographically dispersed and who rely on electronic technologies to perform their work 152 , 153 . Thus, virtual teamwork is a special category of virtual work that also involves collective psychological experiences (that are shaped by and interact with virtual work) 154 . This adds another layer of complexity and therefore requires a separate discussion.

Most research conceptualizes team virtuality as a construct with two dimensions: geographical dispersion and reliance on technology 153 , 155 . Notably, these dimensions are not completely independent because team members require technology to communicate and coordinate tasks when working in different locations 156 , 157 . Virtuality differs between and within teams. Team members might be in different locations on some days and the same location on other days, which changes the level of team virtuality over time. Thus, teams are not strictly virtual or non-virtual. Team virtuality influences how team members coordinate tasks and share information 130 , which is critical for team effectiveness (usually assessed by a team’s tangible outputs, such as their productivity, and team member reactions, such as satisfaction with, or commitment to, the team) 158 .

Although individual team members might react differently to working in a virtual team, multi-level theory suggests that team members collectively develop shared experiences, called team emergent states 159 , 160 . Team emergent states include team cohesion (the bond among group members) 161 , team trust 162 , and team motivation and engagement 159 , 163 . These emergent states arise out of individual psychological behaviours and states 164 and are influenced by factors that are internal (for example, interactions between team members) and external (for example, organizational team rewards, organizational leadership and project deadlines) to the team, as well as team structure (for example, team size and composition). Team emergent states, particularly team trust, are critical for virtual team effectiveness because reliance on technology often brings uncertainties and fewer opportunities for social control 165 .

Team virtuality is likely to affect team functioning via its impact on psychological need satisfaction, in a fashion similar to remote work. However, the need for coordination and information sharing to achieve team goals is likely to be enhanced by how team members support and satisfy each other’s psychological needs 166 , which might be more difficult under virtual work conditions. In addition to affecting individual performance, need satisfaction within virtual teams can also influence collective-level team processes, such as coordination and trust, which ultimately affect team performance. For example, working in a virtual team might make it more difficult to feel meaningful connections because team members in different locations often have less contact than co-located team members. Virtual team members predominantly interact via technology, which — as described in the previous section — might influence the quality of relationships they can develop with their team members 141 , 167 , 168 and consequently the satisfaction of relatedness needs 169 .

Furthermore, virtual team members must master electronic communication technology (including virtual meeting and breakout rooms, internet connectivity issues, meeting across different time zones, and email overload), which can lead to frustrations and ‘technostress’ 170 . Frustrations with electronic communication might diminish the psychological need for competence because team members might feel ineffective in mastering their environment.

In sum, virtual team members might experience lower relatedness and competence need satisfaction. However, these needs are critical determinants of work motivation. Furthermore, virtual team members can also develop shared collective experiences around their need satisfaction. Thus, self-determination theory offers explanatory mechanisms (that is, team members’ need satisfaction, which influences work motivation) that are at play in virtual teams and that organizations should consider when implementing virtual teams.

Algorithmic management

Algorithmic management refers to the use of software algorithms to partially or completely execute workforce management functions (for example, hiring and firing, coordinating work, and monitoring performance) 2 , 123 , 171 , 172 . This phenomenon first appeared on gig economy platforms such as Uber, Instacart and Upwork, where all management is automated 173 . However, it is rapidly spreading to traditional work settings. Examples include monitoring the productivity, activity and emotions of remote workers 174 , the algorithmic determination of truck drivers’ routes and time targets 175 , and automated schedule creation in retail settings 176 . The constant updating of the algorithms as more data is collected and the opacity of this process makes algorithmic management unpredictable, which produces more uncertainty for workers 177 .

Algorithmic management has repercussions for work design. Specifically, whether algorithmic management systems consider human motivational factors in their design influences whether workers are given enough autonomy, skills usage, task variety, social contact, role clarity (including knowing the impact of one’s work) and a manageable workload 123 . So far, empirical evidence show that algorithmic management features predominantly reduce employees’ basic needs for autonomy, competence and relatedness because of how they influence work design (Fig.  4 ).

Summary of the features and consequences of algorithmic management on autonomy needs, relatedness needs and competence needs.

Algorithmic management tends to foster the ‘working-for-data’ phenomenon (or datafication of work) 172 , 178 , 179 , leading workers to focus their efforts on aspects of work that are being monitored and quantified at the expense of other tasks that might be more personally valued or meaningful. This tendency is reinforced by the fact that algorithms are updated with new incoming data, increasing the need for workers to pay close attention to what ‘pays off’ at any given moment. Monitoring and quantifying worker behaviours might reduce autonomy because it is experienced as controlling and narrows goal focus to only quantifiable results 127 , 180 ; there is some evidence that this is the case when algorithmic management systems are used to this end 172 , 178 , 181 . Rigid rules about how to carry out work often determine performance ratings (for example, imposing a route to deliver goods or prescribing how equipment and materials must be used) and even future task assignments and firing decisions, with little to no opportunity for employee input 182 , 183 , 184 . Thus, the combination of telling workers what to do to reach performance targets and how to get it done significantly limits their autonomy to make decisions based on their knowledge and skills.

Some algorithmic management platforms do not reveal all aspects of a given task (for example, not revealing the client destination before work is accepted) or penalize workers who decline jobs 185 , thereby severely restricting their choices. This encourages workers to either overwork to the point of exhaustion, find ways to game the system 184 , or misbehave 186 . Moreover, the technical complexity and opacity of algorithmic systems 187 , 188 , 189 deprives workers of the ability to understand and master the system that governs their work, which limits their voice and enpowerment 172 , 185 , 190 . Workers’ typical response to the lack of transparency is to organize themselves on social media to share any insights they have on what the algorithm ‘wants’ as a way to gain back some control over their work 183 , 191 .

Finally, algorithmic management usually provides comparative feedback (comparing one’s results to other workers’) and is linked to incentive pay structures, both of which reduce self-determined motivation as they are experienced as more controlling 26 , 192 . For instance, after algorithms estimated normal time standards for each ‘act’, algorithmic tracking and case allocation systems forced homecare nurses to reduce the ‘social’ time spent with patients because they were assigned more patients per day, thereby limiting nurses’ autonomy to decide how to perform their work 181 . Because these types of quantified metric are often directly linked to performance scores, pay incentives and future allocation of tasks or schedules (that is, getting future work), algorithmic management reduces workers’ freedom in decision-making related to their work, which can significantly reduce their self-determined motivation 123 .

Algorithmic management also tends to individualize work, which affects the need for relatedness. For example, algorithmic management inevitably transforms or reduces (sometimes even eliminates) contact with a supervisor 2 , 182 , 193 , leading to the feeling that the organization does not care about the worker and provides little social support 194 , 195 . ‘App-workers’, who obtain work through gig-work platforms such as Uber, reportedly crave more social interactions and networking opportunities 179 , 185 , 194 and often attempt to compensate for a lack of relatedness by creating support groups that connect virtually and physically 183 , 191 , 195 . Increased competitive climates due to comparative feedback or displaying team members’ individual rankings 175 , 196 can also hamper relatedness. Indeed, when workers have to compete against each other to rank highly (which influences their chances of getting future work and the financial incentives they receive), they are less likely to develop trusting and supportive relationships.

Researchers have formulated contradictory predictions about the potential implications of algorithmic management on competence satisfaction. On the one hand, using quantified metrics, algorithmic management systems can provide more frequent, unambiguous and performance-related feedback, often in the form of ratings and rankings 177 , and simultaneously link this feedback to financial rewards. Informational feedback can enhance intrinsic motivation because it provides information about one’s competence. At the same time, linking rewards to this feedback could decrease intrinsic motivation, because the contingency between work behaviour and pay limits worker discretion and therefore reduces their autonomy 26 . The evidence so far suggests that the mostly comparative feedback provided by algorithmic management is insufficiently informative because the value of the feedback is short-lived — continuously updating algorithms change what is required to perform well 177 , 183 , 185 . This short-lived feedback can undermine feelings of mastery or competence. In addition, algorithmic management is often associated with simplified tasks, and with lower problem-solving opportunities and job variety 123 . However, gamification features on some platforms might increase intrinsic motivation 179 , 183 .

The nascent research on the effects of algorithmic management on workers’ motivation indicates mostly negative effects on self-determined forms of motivation, because the way it is designed decreases the satisfaction of competence, autonomy and relatedness needs. Algorithmic management is being rapidly adopted across an increasing number of industries. Thus, technology developers and those who implement the technology in organizations will need to pay closer attention to how it changes work design to avoid negative effects on work motivation.

Summary and future directions

Self-determination theory can help predict the motivational consequences of future work and these motivational considerations should be taken into account when designing and implementing technology. More self-determined motivation will be needed to deal with the uncertainty and interdependence that will characterize future work. Thus, research examining how need satisfaction and work motivation influence people’s ability to adapt to uncertainty, or even leverage it, is needed. For example, future research could examine how different managerial styles influence adaptivity and proactivity in highly uncertain work environments 197 . Need-satisfying leadership, such as transformational leadership (charismatic or inspirational) 15 , can encourage job crafting and other proactive work behaviours 198 , 199 . Transactional leadership (focused on monitoring, rewarding and sanctioning) might promote self-determined motivation during organizational crises 23 . In addition, research on the quality of interconnectedness (the breadth and depth of interactions and networks) could provide insight on how to manage the increased interconnectedness workers are experiencing.

Technology can greatly assist in recruiting and selecting workers; self-determination theory can inform guidelines on how to design and use such technologies. It is important that the technology is easy to use and perceived as useful to the candidates for best representing themselves 200 , 201 . This can be done by ensuring that candidates have complete instructions before an assessment starts, even possibly getting a ‘practice run’, to improve their feelings of competence. It is also important for candidates to feel some amount of control and less pressure associated with online asynchronous assessments. Giving candidates some choice over testing platforms and the order of questions or settings, explaining how the results will be used, or allowing candidates to ask questions, could improve feelings of autonomy 70 . Finally, it is crucial to enhance perceptions that the organization cares about getting to know candidates and forging connections with them despite using these tools. For example, enhancing these tools with personalized videos of organizational members and providing candidates with feedback following selection decisions might increase feelings of relatedness. These suggestions need to be empirically tested 202 .

More research is also needed on how technology is transforming work design, and consequently influencing worker need satisfaction and motivation. Research in behavioural health has examined how digital applications that encourage healthy behaviours can be designed to fulfill the needs for competence, autonomy and relatedness 203 . Whether and how technology designed for other purposes (such as industrial robots, information communication technology, or automated decision-making systems) can be deliberately designed to meet these core human needs remains an open question. To date, little research has examined how work technologies are created, and what can be done to influence the process to create more human-centred designs. Collaborative research across social science and technical disciplines (such as engineering and computing) is needed.

In terms of implementation, although there is a long history of studies investigating the impact of technology on work design, current digital technologies are increasingly autonomous. This situation presents new challenges: a human-centred approach to automation in which the worker has transparent influence over the technical system has frequently been recommended as the optimal way to achieve high performance and to avoid automation failures 1 , 204 . But it is not clear that this work design strategy will be equally effective in terms of safety, productivity and meeting human needs when workers can no longer understand or control highly autonomous technology.

Given the likely persistence of virtual and remote work into the future, there is a critical need to understand how psychological needs can be satisfied when working remotely. Multi-wave studies that explore the boundary conditions of need satisfaction would advance knowledge around who is most likely to experience need satisfaction, when and why. Such knowledge can be leveraged to inform the design of interventions, such as supervisor training, to improve well-being and performance outcomes for virtual and remote workers. Similarly, no research to date has used self-determination theory to better understand how team virtuality affects how well team members support each other’s psychological needs. Within non-virtual teams, need satisfaction is influenced by the extent to which team members exhibit need-supportive behaviours towards each other 205 . For example, giving autonomy and empowering virtual teams is crucial for good team performance 206 . Studies that track team activities and interaction patterns, including virtual communication records, over time could be used to examine the effects of need support and thwarting between virtual team members 207 , 208 .

Finally, although most studies have shown negative effects of algorithmic management on workers’ motivation and work design characteristics, researchers should not view the effects of algorithmic management as predetermined and unchangeable. Sociotechnical aspects of the system 2 , 209 (such as transparency, privacy, accuracy, invasiveness and human control) and organizational policies surrounding their use could mitigate the motivational effects of algorithmic management. In sum, it is not algorithms that shape workers’ motivation, but how organizations design and use them 3 . Given that applications that use algorithmic management are developed mostly by computer and data scientists, sometimes with input from marketing specialists 185 , organizations would benefit from employing psychologists and human resources specialists to enhance the motivational potential of these applications.

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Replacement Behavior: Definition and 10 Examples

A replacement behavior is a term often used in applied behavior analysis that refers to socially acceptable behavior that can replace an unwanted problem behavior (known as the target behavior).

The unwanted behavior is usually disruptive to home life or classroom instruction , or possibly harmful to the student or child.

The replacement behavior serves as a constructive substitute that will be a prosocial behavior that supports both the individual student and their family and peers.

Replacement Behavior Definition and Overview

In applied behavior analysis, practitioners focus on two behaviors:

• The Target Behavior : This is the behavior that we want to phase out throughout the ABA intervention.
• The Replacement Behavior: This is the behavior we want to phase in as a replacement for the target behavior.

Replacement behavior is sometimes referred to as functionally equivalent behavior , defined as:

“desirable/acceptable behaviors that achieve the same outcome as a less desirable problem behavior” (D’Eramo, 2013, p. 1379).

The crucial element of the replacement behavior is that it serves the same function as the problem behavior, but is more socially acceptable.

Replacement Behavior Examples

The theory: replacing disruptive behavior.

In order for the replacement behavior to be effective, it must serve the same function as the disruptive behavior.

So, if the child is answering questions out of turn because they want the teacher to recognize that they studied, then the replacement behavior must allow the student to satisfy that need as well.

There are four main functions of a student’s disruptive behavior.

• Attention Seeking: The child is being disruptive to gain the attention of an adult or other children. Behaviors may include making silly noises, crying/whining, or calling out answers. Even though the adult may show displeasure with these actions, negative attention is still attention.
• Escape: This can be escape from a task or situation. The goal is to get away and avoid doing an assignment or participating in an activity.  Behaviors can include crying, throwing a temper tantrum, or simply running away.
• Access to Tangibles: The child is trying to obtain a toy or participate in an activity. Because they have not learned constructive ways to gain access, they may show anger, cry/whine, or engage in physical aggression such as pushing another child out of the way.
• Sensory: Some children need extra sensory stimulation, while others feel overwhelmed by even slight stimulation. Therefore, the child engages in disruptive behavior to stimulate their senses, such as excessively bouncing in their chair or kicking their feet. 

In other cases, the child may scream or run away to block external stimulation.

How To Assess the Function of a Disruptive Behavior

To determine the function of a behavior, either the teacher by themselves or a team of professionals (teachers, school counselor, psychologist) will conduct a functional behavioral analysis (FBA).

“a collection of methods for gathering information about antecedents, behaviors, and consequences in order to determine the reason (function) of behavior” (Gresham et al., 2001, p. 158).

The chart below identifies different ways to perform an FBA.

Indirect methods include examining school records or conducting interviews with teachers and parents. This will provide a wealth of information about the child’s typical behavioral patterns.

Teachers and parents can often provide valuable insight into what is driving the child’s actions.

Direct methods include observing the child in a naturalistic setting such as the classroom or playground.

An ABC recording form stands for antecedents, behaviors, and consequences.

Detailed instructions for how to use the chart can be found here , with a free downloadable template found here .

This video demonstrates how a recording sheet is used in an actual classroom.

Experimental analysis involves the teacher testing different triggers and antecedents to determine if they evoke the disruptive behavior. It is a form of hypothesis testing with an individual student.

Case Studies of Replacement Behavior     

1. replacement behaviors for escape-motivated behaviors.

Dwyer et al. (2012) examined the effectiveness of four replacement behaviors (teacher help, break, choice between help or break, or none) for three young male students (ages 7 and 8) with emotional disturbance (ED).

The researchers began by gathering data.

“An FBA was conducted for each participant. Specifically, the first two authors reviewed each student’s file, interviewed each student’s teacher, interviewed each student, and performed systematic direct observations to document the levels of problem behaviors and identify antecedents and consequences of students’ problem behaviors” (p. 117).

This analysis revealed that all three students’ off-task disruptive behavior was maintained by a desire to escape instruction.

The students received training (two 15-minute sessions) on replacement behaviors such as using a help card, break card, with guided practice, modeling, and role playing.

The students’ on-task and off-task behaviors were observed during a baseline phase and during application of the treatment conditions in which the students were instructed to use one of the four replacement behaviors.

The results revealed that “All students displayed the lowest levels of off-task behavior, on average, during the choice (help and break) condition” (p. 122).

2. Aggression and Replacement Behaviors

Bailey et al. (2202) received a referral for a group-home resident named Jack, a 24-year-old man with profound mental retardation and aggressive behavior.  

Jack’s aggression “was nearly always directed at staff and had caused injuries ranging from bruising to bleeding…Jack was at-risk for losing his placement in the group home, being medicated to reduce his aggression, or both” (p. 356).

An antecedent analysis indicated that aggression was least likely when Jack received social attention in the form of physical contact and conversation with the staff.

The staff were trained on how to implement two versions of replacement behavior for Jack: Point and Spell.

The Point behavior involved Jack pointing to a picture of two people talking to each other. The Spell behavior involved Jack spelling the word “talk” on his laminated keyboard.

Notable results (p. 366) were as follows:

• For the 4 months prior to the study, “aggression occurred on average of 21.2 times per month.”
• During the 4 months immediately following the study, “aggression occurred a mean of 1.4 times per month.”
• Two years after the study, Jack formed sentences by pointing to pictures, “starting with the phrase, ‘I want’ and concluding with: talk, help, peanut butter and jelly, crackers, pizza, hamburger, Dad.”

3. Replacing Fidgeting Behavior with Fidgeting Behavior

Not all replacement behaviors involve substituting severe disruptive behavior such as aggression. Lots of young students can be disruptive because they are so busy fidgeting, making unnecessary noises and creating distractions. They just need to find a more constructive way to expel energy. For this, we use a strategy called noncontingent reinforcement (as opposed to a reinforcement contingent upon a behavior ).

Enter the wide array of resources to address fidgeting. Fidget toys are popular for hand manipulation or sensory stimulation.

There are also several items for large motor fidgeting, such as the Wiggle Seat, Bouncy Ball Chair, and the Fidget Band. These items are sometimes referred to as kinesthetic equipment.

But, does this equipment allow the child to engage in a constructive replacement behavior instead of being disruptive due to excessive movement? That is the question.

Flippin et al. (2021) provided several elementary classrooms with five types of kinesthetic equipment (i.e., exercise balls, standing desks, kneel-and-spin desks, under desk pedals, and bouncy bands).

The results showed that:

“Use of kinesthetic equipment was associated with significant increases in the proportion of students’ time on-task during equipment weeks compared with baseline and withdrawal weeks” (p. 11).

Replacement behavior refers to teaching a child to rely on a constructive means of obtaining something they want instead of being disruptive.

In order for a replacement behavior to be adopted by the student however, it must serve the same purpose (i.e., function) as the disruptive behavior.

To determine the function of the disruptive behavior, the teacher or a team of professionals conduct a functional behavioral analysis (FBA).

The FBA is conducted by examining existing records, interviewing individuals that interact with the student, and observing the child in their natural surroundings to identify triggers and consequences of their actions.

That analysis then informs the action plan that is then implemented with the individual.

Although replacement behaviors are usually discussed in the context of severe behavioral issues, they can also be useful in other populations.

Bailey, J., McComas, J. J., Benavides, C., & Lovascz, C. (2002). Functional assessment in a residential setting: Identifying an effective communicative replacement response for aggressive behavior. Journal of Developmental and Physical Disabilities , 14 , 353-369.

D’Eramo, K. (2013). Functionally equivalent alternative behavior. In: Volkmar, F.R. (Eds.) Encyclopedia of Autism Spectrum Disorders , 1379–1380. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-1698-3_1038

Dwyer, K., Rozewski, D., & Simonsen, B. (2012). A comparison of function-based replacement behaviors for escape-motivated students. Journal of Emotional and Behavioral Disorders , 20 (2), 115-125.

Flippin, M., Clapham, E. D., & Tutwiler, M. S. (2021). Effects of using a variety of kinesthetic classroom equipment on elementary students’ on-task behaviour: A pilot study. Learning Environments Research , 24 , 137-151.

Seifert, A. M., & Metz, A. E. (2017). The effects of inflated seating cushions on engagement in preschool circle time. Early Childhood Education Journal , 45 , 411-418.

Appendix: Graph Reproduced as Text

Functional Behavioral Assessment Methods:

1. Indirect methods 1.1 Behavioral checklists and school records 1.2 Interviews and surveys oft eachers and parents

2. Direct Methods 2.1 Descriptive naturalistic observation 2.2 ABC recording form

3. Experimental functional analysis 3.1 Identify and maipulate antecedent triggers 3.2 Identify and manipulate maintaining consequences

Dave Cornell (PhD)

Dr. Cornell has worked in education for more than 20 years. His work has involved designing teacher certification for Trinity College in London and in-service training for state governments in the United States. He has trained kindergarten teachers in 8 countries and helped businessmen and women open baby centers and kindergartens in 3 countries.

• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 25 Positive Punishment Examples
• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 25 Dissociation Examples (Psychology)
• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 15 Zone of Proximal Development Examples
• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ Perception Checking: 15 Examples and Definition

Chris Drew (PhD)

This article was peer-reviewed and edited by Chris Drew (PhD). The review process on Helpful Professor involves having a PhD level expert fact check, edit, and contribute to articles. Reviewers ensure all content reflects expert academic consensus and is backed up with reference to academic studies. Dr. Drew has published over 20 academic articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education and holds a PhD in Education from ACU.

• Chris Drew (PhD) #molongui-disabled-link 25 Positive Punishment Examples
• Chris Drew (PhD) #molongui-disabled-link 25 Dissociation Examples (Psychology)
• Chris Drew (PhD) #molongui-disabled-link 15 Zone of Proximal Development Examples
• Chris Drew (PhD) #molongui-disabled-link Perception Checking: 15 Examples and Definition

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Behavioral Theories in Leadership

• 1.0.2 Styles of Leadership in Behavioral Theories
• 1.0.3 The Ohio State Studies – Two Factor Concept
• 1.0.4 The Michigan Leadership Studies
• 1.0.5 The Blake and Mouton Managerial Grid
• 2.0.1 Hersey-Blanchard Situational Leadership Vis-a-vis Behavioral Theories
• 2.0.2 Transactional Leadership – An offshoot of the Ohio State Studies
• 2.0.3 Transformational Leadership – Linkage with the Michigan Leadership Studies
• 2.0.4 Charismatic Leadership Vis-a-vis the Blake and Mouton Managerial Grid
• 2.0.5 Contingency Theories – Consideration and Initiating Structure in Context
• 2.0.6 Practical Examples in the Corporate World
• 4.0.1 Path-goal theory of Leadership
• 4.0.2 Leader-Member Exchange Theory (LMX)
• 4.0.3 Authentic Leadership
• 4.0.4 Servant Leadership

Understanding Behavioral Theories in Leadership

In this article, we will review Behavioral Theories in Leadership .

Let’s start by understanding these two words individually:

• Behavioral : This focuses on actions. How someone reacts in certain situations.
• Theory : An idea or set of ideas intended to explain something.

Let’s merge these terms and understand the phrase, ‘Behavioral Theories of Leadership’. Essentially, these dictate that great leaders are made, not born. These theories try to explain how leaders can be made in an organizational environment.

Styles of Leadership in Behavioral Theories

• Autocratic leadership : Here’s a style akin to a classroom with a stern teacher. This leader makes all decisions, unilaterally. The leader does not consult team members or consider their needs and opinions.
• Democratic leadership : Picture a teacher who loves group work, where everyone gets a say. Here, the leader involves employees in decision-making processes, encourages teamwork, and fosters creativity and initiative.
• Laissez-Faire leadership : Think of a substitute teacher who lets the class do what they want, and only steps in when required. This leader allows members to make decisions while retaining ultimate responsibility.

The Ohio State Studies – Two Factor Concept

The Ohio State University carried out extensive research on behavioral theories and came up with a two-factor concept:

• Leaders who exhibit consideration , that is, friendliness, respect, and nurturing relationships.
• Leaders who showcase initiating structure : this means clarifying roles , scheduling work, and giving directions.

The Michigan Leadership Studies

The University of Michigan conducted their studies, focusing on two types of leadership:

• Employee orientation : Here, leaders take an interest in their followers as individuals.
• Production orientation : Here, leaders emphasize technical aspects of the job.

The Blake and Mouton Managerial Grid

The theory suggests five potential leadership styles, based on concern for people and concern for production.

• Impoverished Management : Low concern for both people and production.
• Country Club Management : High concern for people, low concern for production.
• Authority-obedience : Low concern for people, high concern for production.
• Middle-road Management : Median concern for both parameters.
• Team Management : High concern for both people and production.

Understanding these key sections and theories will give you a comprehensive knowledge of the behavioral theories of leadership.

Keep in mind, each leadership style has its own merit, and the best leaders are often able to adapt and switch styles, based on the situation at hand.

Examining Case Studies Application of Behavioral Theories

Hersey-blanchard situational leadership vis-a-vis behavioral theories.

The Hersey-Blanchard Situational Leadership theory is a concrete example of the practical application of behavioral theories.

In this approach, leaders adjust their style depending on the maturity and capability level of their team. Essentially, the theory posits that there’s no one-size-fits-all leadership style – it changes based on the situation.

This bears a striking resemblance to the various leadership styles highlighted in our discussion about styles of leadership in behavioral theories such as Democratic, Autocratic, and Laissez-Faire leadership.

Transactional Leadership – An offshoot of the Ohio State Studies

Transactional leadership is another notable example. This approach relies heavily on the concept of “initiating structure” identified in the Ohio State Studies.

Leaders set clear tasks and rewards or punishments for their completion or non-completion, respectively. It’s like a business transaction, so you can see the connection to our earlier discussions, can’t you?

Transformational Leadership – Linkage with the Michigan Leadership Studies

In transformational leadership , leaders motivate their teams by setting high expectations and inspiring them to meet these goals.

The leaders, in turn, highly regard their team members’ abilities. This relationship-oriented leadership style relates to the “employee-oriented” type identified in the Michigan Leadership Studies.

Charismatic Leadership Vis-a-vis the Blake and Mouton Managerial Grid

Charismatic leadership, where leaders inspire enthusiastic support and acceptance through charisma, is a practical application of the “high concern for people” identified in the Blake and Mouton Managerial Grid. The leader’s appeal lies in their character and how they use it to influence their team.

Contingency Theories – Consideration and Initiating Structure in Context

In Contingency theories, the leader’s effectiveness is contingent or dependent on how their leadership style fits the context.

The leader uses a mix of initiating structure and consideration factors, thereby aligning with the behavioral theories from the Ohio State Studies.

Practical Examples in the Corporate World

To illustrate, take Apple, Inc. After Steve Jobs returned to Apple in 1997, he exhibited transformational leadership, inspiring a corporate turnaround which pushed Apple to the forefront of innovative technology. Jobs set high expectations, focused on building a good workplace culture, and motivated his team to produce groundbreaking devices. That sounds a lot like the employee orientation discussed in the Michigan Leadership studies, doesn’t it?

In contrast, Amazon’s Jeff Bezos is reputedly a transactional leader. His demanding and exacting standards, coupled with a structured work environment, mirrors the production orientation and initiating structure from the Ohio State Studies.

Why not take a moment to consider some leaders you know or have read about, and see if you can identify examples of these leadership styles? You’ll be surprised at how these behavioral theories come to life in the real-world scenarios.

Limitations of Behavioral Theories in Leadership

One of the main limitations of behavioral theories is that they largely overlook individual differences. These theories often propose a “one-size-fits-all” approach to leadership, suggesting that certain behaviors will be effective regardless of the characteristics of the team members or the context. However, in reality, people have diverse perspectives, abilities, and motivations that could impact how they react to different leadership styles.

Here is an example: A democratic leadership style involves team members in decision making, which can foster a sense of belonging and commitment. However, if team members are more introverted or lack experience, they might prefer autocratic leadership, where decisions are made by the leader alone.

Lack of Versatility:

The behavioral theories of leadership do not account for the need for versatility in leadership styles. The idea of employing just one style across all situations seems rather unrealistic.

Real-life example: Steve Jobs was known for his autocratic leadership style in the early years of Apple, a style that might not have worked at all in a startup where collective consensus is often essential.

Time and Context are Ignored:

Behavioral theories tend to ignore the dimension of time and context. The world is not static and neither should leadership styles. It means that what worked in the 1980s might not work as well in the 2020s due to changes in technology, societal norms, and our understanding of human psychology.

Take Amazon as a case study:

The company’s leadership principles, formulated by Jeff Bezos, have been essential to its success. However, they have also been critiqued due to the high-pressure environment they can foster, hinting at the need for transformational leadership that meshes well with the pace of technological evolution.

Overemphasis on Observable Behaviors:

Behavioral theories tend to focus too much on observable behaviors, ignoring mental processes and inherent traits that could affect a leader’s effectiveness. This lack of focus on internal dynamics fails to account for the impact of a leader’s perception, personality , and motivations.

Limited Use for Training:

In terms of practicality, these theories are limited. Behavioral theories provide a broad understanding of leadership but fail to offer clear guidance for developing effective leaders. So while they help you identify what behaviors are associated with effective leadership, they don’t exactly lay out a roadmap for how to develop them.

While the behavioral theories offer valuable insights on the roles leadership styles play, their limitations mean they should not be treated as the definitive guide to effective leadership.

Instead, incorporating a variety of frameworks, including flexibility in leadership styles and specific situational analysis, is essential in understanding and applying leadership effectively.

Photo by benofthenorth on Unsplash

Alternative Leadership Theories

Path-goal theory of leadership.

One significant alternative theory to the behavioral leadership approach is the path-goal theory . Developed by Robert House, this theory takes the perspective that a leader’s job is to assist their followers in attaining their goals and to provide the necessary direction and support to ensure that their goals are compatible with the overarching objectives of the group or organization.

It maintains that the leader’s style can be flexible and adjusted to fit the employee’s needs and the working environment.

Now, let’s break down an example of this in practice. Imagine a coach for a youth basketball team. If a player is struggling with their shooting, the coach can adjust their style to be more explanatory and hands-on to help the player, providing more direct assistance.

This type of adjustment and flexibility is one key aspect of the path-goal theory – it stresses upon the importance of leaders being adaptable to meet team members’ needs.

Leader-Member Exchange Theory (LMX)

Another alternative theory is the Leader-Member Exchange Theory (LMX). This theory emphasizes the two-way relationship between supervisors and subordinates.

A high-quality relationship between a leader and a subordinate is characterized by mutual trust, respect, and obligation. High-quality exchanges will result in deeper connection, and consequently, more positive organizational outcomes.

Take UPS, for instance. The logistics company is known for its unique culture of promoting from within and listening to employees at all levels. This method creates a sense of mutual respect between the leaders and the employees, something that is crucial in the LMX theory.

Authentic Leadership

Authentic Leadership , another non-behavioral theory, is all about leaders who are deeply aware of how they think and behave, and are perceived by others as being aware of their own and others’ values/moral perspectives, knowledge, and strengths.

Authentic leaders are seen as people who promote openness. They are often characterized by a transparent approach towards their followers.

An example here is Howard Schultz, the former CEO of Starbucks. Schultz is known for building trust with employees by being transparent about company policies and future goals. By increasing transparency, he was able to promote a sense of authenticity and trust, hallmarks of authentic leadership.

Servant Leadership

Finally, Servant Leadership is a leadership theory that emphasizes the leader’s role as a steward of the resources provided by the organization. It encourages leaders to serve others while still achieving organizational goals. They put their team’s needs before their own, thereby improving the overall performance and morale.

A good example of this kind of leader is Mahatma Gandhi. He exerted influence not by asserting authority, but by dedicated service to his followers and unwavering commitment to his principles.

Each of these theories offers a different perspective on leadership, countering the behavioral approach. They emphasize adaptability , two-way relationships, authenticity, and serving others as alternative styles of effective leadership.

It’s important to remember, however, that no one approach is necessarily “the best”. It’s the unique combination of approaches, tailored to individual teams and scenarios, which makes a truly effective leader.

About The Author

Geoff Fripp

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Putting Theory Into Practice: A Case Study of Diabetes-Related Behavioral Change Interventions on Chicago's South Side

Monica e. peek.

1 University of Chicago, Chicago, IL, USA

Molly J. Ferguson

Tonya p. roberson, marshall h. chin.

Diabetes self-management is central to diabetes care overall, and much of self-management entails individual behavior change, particularly around dietary patterns and physical activity. Yet individual-level behavior change remains a challenge for many persons with diabetes, particularly for racial/ethnic minorities who disproportionately face barriers to diabetes-related behavioral changes. Through the South Side Diabetes Project, officially known as “Improving Diabetes Care and Outcomes on the South Side of Chicago,” our team sought to improve health outcomes and reduce disparities among residents in the largely working-class African American communities that comprise Chicago's South Side. In this article, we describe several aspects of the South Side Diabetes Project that are directly linked to patient behavioral change, and discuss the theoretical frameworks we used to design and implement our programs. We also briefly discuss more downstream program elements (e.g., health systems change) that provide additional support for patient-level behavioral change.

Introduction

Diabetes self-management is central to diabetes care overall, and much of self-management entails individual behavior change, particularly around dietary patterns and physical activity. In a recent review of behavior change, Fisher et al. (2011) found that behavior changes are associated with multiple aspects of diabetes, including the onset of disease and disease prevention (e.g., dietary intake and obesity are risk factors for the development of diabetes; lifestyle changes can prevent diabetes in high-risk individuals; Diabetes Prevention Research Group, 2002 ; Eyre, Kahn, & Robertson, 2004 ; Tuomilehto et al., 2001 ), disease management (e.g., diabetes self-management programs can improve disease management, improve metabolic control, and prevent complications; The Diabetes Control and Complications Trial Research Group, 1993 ; Norris, Engelgau, & Narayan, 2001 ; Norris, Lau, Smith, Schmid, & Engelgau, 2002 ), and quality of life (e.g., behavior changes can reduce distress and depressive symptoms, increase emotional and social function, reduce anxiety, and improve general quality of life among persons with diabetes; Blumenthal et al., 2005 ; Cochran & Conn, 2008 ; Vale et al., 2003 ).

Despite the strong evidence base and the growing public health need for implementation, individual-level behavior change remains a challenge for many persons with diabetes. Racial/ethnic minorities disproportionately face barriers to diabetes-related changes, including access to healthy food, safe places for physical activity, diabetes education, and other self-management resources. Through the South Side Diabetes Project, officially known as “Improving Diabetes Care and Outcomes on the South Side of Chicago,” our team sought to improve health outcomes and reduce disparities among residents in the largely working-class African American communities that comprise Chicago's South Side ( Chin, Ferguson, Goddu, Maltby, & Peek, in press ; ( Peek, Wilkes, et al., 2012 ). A key part of this strategy involves the promotion of individual behavior change among persons with diabetes—changes in healthy behaviors (e.g., nutrition, physical activity), treatment adherence (e.g., medication adherence), self-care activities (e.g., self–foot examinations), and active involvement in treatment decisions with their health care providers (i.e., shared decision making [SDM]).

In this article, we describe several aspects of the South Side Diabetes Project that are directly linked to patient behavioral change, and discuss the theoretical frameworks we used to design and implement our programs. We also briefly discuss more macro-level program elements (e.g., health systems change) that provide additional support for patient-level behavioral change.

Program Components that Support Diabetes-Related Behavior Change

Patient education classes.

We have developed a patient empowerment curriculum that provides culturally tailored, evidence-based diabetes education with skills training in patient–provider communication and SDM. This educational program has been described in detail elsewhere ( Peek, Harmon, et al., 2012 ), but it has been summarized here. The classes met once weekly for 2 to 3 hours for 10 consecutive weeks. The first 6 weeks consisted of culturally tailored diabetes education, which modified the evidence-based BASICS curriculum developed by the International Diabetes Center and covered basic diabetes knowledge and management skills ( Peek, Harmon, et al., 2012 ). The curriculum was adapted to meet the literacy, adult-learning, and cultural needs of the population. The following 3 weeks addressed patient–provider communication and SDM; patients were taught skills and strategies to become more actively involved in discussions and decisions about their diabetes treatment plans ( Peek, Harmon, et al., 2012 ). The SDM curriculum addressed identified barriers, cultural norms, and beliefs among low-income African Americans with diabetes that we had previously identified about SDM ( Peek et al., 2008 ; Peek et al., 2009 ; Peek et al., 2010 ). The classes were interactive and used role-play, testimonials, games, film, and hands-on skills training to help teach key educational components and support behavior change skills. Each cohort was led by a multidisciplinary team of certified diabetes educators, nurses, dietitians, and physicians. Family and friends were invited to the classes to help support patients in developing and sustaining diabetes-related behavioral changes. Statistically significant improvements were seen in diabetes self-care behaviors, including following a “healthful eating plan,” self-glucose monitoring, exercise, and self–foot care, as well as glucose control (i.e., HbA1c [glycated haemoglobin] values; ( Peek, Harmon, et al., 2012 ).

“Prescriptions” for Food and Exercise

Our team has worked collaboratively with Walgreens and the 61st Street Farmer's Market to provide “Food Rx” for fresh fruits and vegetables. Our Food Rx program has been described in detail elsewhere ( Goddu, Roberson, Raffel, Chin, & Peek, in press ), but it is briefly summarized here. Nine Walgreens stores were selected based on their “food desert” designation (i.e., are located within a food desert and provide expanded healthy food options) and location within the catchment area of one of our six participating health centers. The Farmer's Market was selected based on its proximity to the University of Chicago and its commitment to providing skills-based education (e.g., cooking demonstrations) and serving low-income communities. For example, this Farmer's Market is the first and largest market participant in Illinois' food stamp (LINK) program, where the value of the LINK card purchase is doubled by the Farmer's Market ( Experimental Station, 2009 ). Physicians and mid-level providers (i.e., physician assistants and nurse practitioners) sign the Food Rx, which are distributed in the clinic to interested patients. The Food Rx combine the power of physician recommendations regarding lifestyle changes with patient educational information (the Food Rx are attached to a one-page low-literacy nutritional sheet that highlights examples of food recommendations), financial incentives (on the back of the Food Rx is a $5 coupon for Walgreens or a $9 voucher for the Farmer's Market), and information about local community resources.

Similar to the Food Rx, we have promoted an Exercise Rx where high-risk obese patients (i.e., those with diabetes, hypertension, cardiovascular disease, and/or asthma) can receive prescriptions redeemable for 6 months of free services at any of the 64 Chicago Park District locations, which offer a variety of fitness classes and services.

Food Shopping Tours

Each month at the Save-A-Lot (SAL) grocery, a low-cost grocery chain prevalent on Chicago's South Side, we conduct a grocery store tour called “Shop Smart, Save a Lot, and Be Healthy.” The tours are conducted three Saturdays a month at three different store locations on Chicago's South Side. Participants are taken around the perimeters of the store (where fresh/frozen items are showcased) and taught how to read food labels, shop healthy on a budget, and make healthy food choices. At the end of the tour, participants receive a $25 gift card, donated by SAL, to purchase healthy food items. Initially led by a registered dietician/certified diabetes educator, our team has trained over 30 community members (e.g., fitness instructors, diabetes patients, nutritionists, public health students), who also lead the tours. Since January 2012, over 500 people have participated in the SAL tours, some of whom were referred from one of our participating health centers and 15 of whom had participated in our patient education classes.

We have adapted the food shopping script for the 61st Street Farmer's Market and Walgreens partner stores. Community members are currently doing educational tours of the Farmer's Market, where patients and community residents learn to identify and use the wide variety of produce at the market (that may have been previously unfamiliar), meet the farmers, and receive “special invitations” for the cooking demonstrations. In the first 4 months of the program, nearly 150 people have participated in the Farmer's Market tours. At Walgreens, pharmacists (also trained in diabetes education) are due to begin conducting tours of the healthy food sections in the stores in the fall of 2013 at participating stores.

Community Food Pantries

We have partnered with a local community center to enhance the access of our patients to free healthy food. The K.L.E.O. Community Family Life Center distributes several tons of fresh produce and other healthy food items, provided by the Greater Chicago Food Depository, to South Side community members every month. We have reorganized the food pantry to become a more comprehensive community health event by incorporating health education, fitness and cooking demonstrations, free health screenings, and referrals for regular medical care. Our team is currently working with several faith-based organizations and churches with food pantries to implement a similar model elsewhere on Chicago's South Side. From April 2012 to September 2013, we have had 1,459 touch points with 1,122 unique persons, 77 of whom were referred from one of our six health centers. An estimated 200 persons have been screened for diabetes and hypertension, and 85 persons without a regular physician were referred to a medical home.

Skills Training in Healthy Food Preparation/Cooking

Our team has worked closely with local chefs and culinary experts to provide skills training in healthy food preparation throughout the South Side, including our regular community events (e.g., Farmer's Market, K.L.E.O. Food Pantry) as well as other health events (e.g., health fairs). We have launched an Annual Diabetes Cook-Off, whose purpose is to showcase community-created diabetes-friendly dishes that are flavorful and can be enjoyed by everyone (i.e., also persons without diabetes). The Cook-Off is held in conjunction with a local community college's culinary arts program; instructors and students at the college support the Cook-Off semifinalists with the “professional presentation” of their food dishes to a panel of judges, which include celebrity chefs, nutritionists, persons with diabetes, and community leaders. The Diabetes Cook-Off is aired on a local cable television station and hosted by a local media personality. In the first year of the Cook-Off (2012), we had over 75 recipe submissions from patients and community members. Two of the semifinalists had completed our diabetes education classes.

Physical Activity Classes

Despite the widespread availability of parks within Chicago, many residents on the South Side do not have access to safe places for physical activity because of crime and other challenges within the local built environment. The Community Fitness Program is held at the Museum of Science and Industry and was designed by the University of Chicago Medical Center to encourage healthy fitness habits and to provide a safe place to exercise and help alleviate some of the most common barriers to exercise. The program offers a safe, warm place to walk for 90 minutes or participate in a free fitness class. We help promote this program within the patient education classes, clinics, and community venues.

In 2013, our team launched the Community Fitness Passport Program (CFPP), designed to expose South Side residents to a variety of fitness program (e.g., yoga, zumba, weight training) as well as a variety of local resources for physical activity (e.g., Park District centers, local churches with open fitness facilities, YMCA locations). The first CFPP class enrolled 25 participants, 19 of whom had completed the diabetes education classes. Because several of the “stops” along the Passport “journey” were at Chicago Park District centers, participants were exposed to existing facilities, programs, and resources that they could continue using through the Exercise Rx, which provide 6 months of free access to a local Park District center. The Passport program was designed to help community residents identify physical activity behaviors and facilities that they enjoyed and in which they would continue engaging after the CFPP ended.

Provider Workshops

We have conducted a workshop series among health care providers (i.e., physicians, nurse practitioners, physician assistants) and staff designed to increase knowledge and skills in motivational interviewing, patient–provider communication (with a focus on SDM), and culturally competent care. The goal of these interactive workshops is to equip health care teams to better activate diabetes patients from racial/ethnic minority communities and support such patients in making lifestyle changes to improve their health. To date, 100 providers and staff have been trained at the six participating health centers. In pre– posttest surveys using Likert-type response options, statistically significant improvements were noted in participants' self-rated ability to assess patients' readiness and motivation to change behavior, help patients initiate and maintain behavior change, understand potential barriers to engaging patients as active partners in care, and support patients' active participation in care ( p < .001 for all).

Mobile Technology Program

We developed a theory-driven interactive mobile technology program to support diabetes patients. The program components are described in detail elsewhere ( Dick et al., 2011 ; Nundy et al., 2012 ) but are summarized briefly here. Patients received interactive text messages to support them with diabetes self-management. Text messages were categorized into four content domains: education, medication reminders, glucose-monitoring reminders, and foot care reminders. Each domain was comprised of 2-week modules, which vary by topic and frequency of messages. The education domain covered diabetes self-management (e.g., purpose of medication and glucose monitoring, nutrition, foot care, and exercise) as well as living with a chronic illness (e.g., navigating the health care system, coping with stress). The other three domains supported behavior change with reminders (“Time to take your diabetes medication”), tips (“Think of your plate as a meal plan. Half your plate should be vegetables, a quarter meat or other proteins, and a quarter starches”), assessments (“On how many of the past 7 days did you take all of your diabetes medications?”), and feedback (“Great job!”). In addition, nurse-administrators used the automated text messaging to provide personalized self-management support for diabetes patients and facilitated care coordination with the primary care team.

Behavior Change Theoretical Frameworks

Several behavior change theoretical frameworks have informed the design and implementation of components of the South Side Diabetes Project. In this section, we describe the relevant theoretical constructs and discuss how we have directly applied them to our work. We use the following levels of the ecological model ( Fisher et al., 2002 ; Sallis, Owen, & Fisher, 2008 ) to organize the discussion: Patients; Family, Friends and Small Groups; Organizations, Communities, and Culture; and Government, Policies, and Large Systems. Within each of these levels, we describe behavioral theories that have direct relevance to our intervention and our target population. Some theories (e.g., health belief model) are more salient to behavior initiation (an important goal of the intervention), whereas other theories (e.g., self-efficacy) are more salient to the maintenance of behavior change.

At the individual patient level, we used several behavioral theories, which have some content overlap, to inform our program.

Health Belief Model

The health belief model theorizes that health behaviors are influenced by perceptions of the threat, severity of illness, and its consequences; perceived barriers to behavior change; and beliefs about the benefits of behavior change ( Janz & Becker, 1984 ). Thus, patients must first believe that they are at risk for the disease and/or its complications before behavior change can occur to reduce these risks. Risk perception has been shown to play an important role in developing healthy behaviors, such as dietary changes ( Janz & Becker, 1984 ). However, because the prevalence, morbidity, and mortality related to diabetes are disproportionately high among African Americans ( Chow, Foster, Gonzalez, & McIver, 2012 ), particularly within South Side communities, many of the persons with diabetes in our project believed that their risk for diabetes-related complications was significantly greater than it actually was. That is, they believed that personal complications from diabetes (e.g., renal failure, lower extremity amputation) were inevitable because of the experiences of friends and family members with the disease. Ironically, because of these fatalistic beliefs, many patients admitted to using “denial” as a coping strategy for dealing with diabetes ( Peek et al., 2009 ). Consequently, although our diabetes education classes included important information about diabetes complications, the curriculum focused more on risk factor reduction and the benefits of behavior change. One of the key messages of the classes has been “You can have diabetes, but diabetes doesn't have to have you.” That is, diabetes is a chronic disease that can be controlled, and the risks of complications are significantly reduced by patients' decisions and behaviors. We encouraged the sharing of success stories among diabetes patients within the class to help promote the idea, through personal testimonials, that diabetes is a condition over which patients can have control. In our interactive mobile texting program, we specifically included text messages designed to influence health beliefs; program participants had statistically significant changes in their health beliefs (e.g., perceived risk of long-term complications) at program completion ( Nundy, Mishra, et al., 2014 ).

Our program has addressed perceived barriers to behavior change, a key aspect of the health belief model. We have used multiple strategies, including active problem-solving and skills-building exercises within the patient classes (e.g., hands-on instructions about self-glucose testing, role-playing with teachers about SDM), identifying and promoting community resources for lifestyle changes (e.g., “prescriptions” for healthy food and exercise), providing social support, and sending regular text message reminders about diabetes self-care activities.

Self-Efficacy

Self-efficacy, or the sense of confidence in one's ability to perform an activity, is an important precursor to behavioral change ( Bandura, 1997 ). In Bandura's model, self-efficacy is built through mastery experience, social persuasions, physiological factors, and social modeling ( Skaff, Mullan, Fisher, & Chesla, 2003 ; Walker, Mertz, Kalten, & Flynn, 2003 ). In mastery experience , small successes raise self-efficacy. That is, individuals are more likely to believe they can do something continually if they have seen for themselves that they can do it at least once. A major goal of our overall project is to provide opportunities for small success in diabetes self-care and management through experiential learning. For example, in our diabetes classes, participants practice reading food labels, role-play ordering food from local restaurant menus, participate in chair-based exercises to jazz music, and role-play asking their physicians questions about recommended medications. We provide real-world opportunities for mastery experience through our guided shopping tours (where people practice reading food labels and shopping for healthy food options on budget), cooking demonstrations and community cook-off events, and “Ask the Doctor” opportunities at community venues, where community residents can engage physicians on our team and ask general questions about health/health care.

Social persuasions are defined as the encouragements or discouragements that affect an individual's self-efficacy. In the diabetes classes, we created an environment in which participants' behavior changes (e.g., beginning a physical activity regimen, discussing concerns about medication side effects with physicians at a prior clinic visit) and health outcomes (e.g., reduced HbA1c values, weight loss) were celebrated by the entire group. Class participants wanted to “make their teammates proud” of them and looked forward to sharing small victories during the class. Participants in the mobile texting program described the desire to “not let down” the text manager in aspects of their diabetes self-care and appreciated receiving positive feedback texts (e.g., “Great job!”) when they reported medication adherence.

Because hyperglycemia and hypoglycemia frequently cause physical symptoms, physiological factors played an important role in building self-efficacy. As patients in the classes reported fewer symptoms (e.g., fatigue, polyuria, blurry vision, palpitations, diaphoresis) related to unregulated glucose, it reinforced the positive behavioral changes they were making regarding their diet, physical activity, and treatment adherence. The relationship between symptoms and diabetes control was underscored for patients during the weekly reviews of blood glucose logbooks and discussions of diabetes-related symptoms and behavior modifications.

Social modeling has been a key strategy used by our team to influence the behavior of persons with diabetes. We have provided multiple opportunities for people to meet and learn from others who were living healthy lives because of the personal decisions and behaviors they made about their diabetes management. We celebrate graduates from our diabetes classes who have seen improvements in their diabetes, blood pressure, lipids, and/or weight. Some former class participants have served as peer mentors for patients struggling with their diabetes management, have been tour guides at the Farmer's Market and SAL, and work with our team at community outreach events (e.g., health fairs). We have worked closely with celebrity chefs, several of whom have diabetes or family members with the disease, who bring personal testimony to the real possibility of controlling diabetes with lifestyle changes. Thus, our team has sought to enhance the self-efficacy of our participants in performing diabetes-related health behaviors. In both the patient classes and the mobile texting program, statistically significant improvements in diabetes self-efficacy were noted among participants.

Theory of Planned Behavior

According to the theory of planned behavior (TPB), individual behavior is determined by a person's intention to perform it and by perceived control (self-efficacy) over performing the behavior ( Ajzen, 1991 ). A person's intention is determined by the weighted relative importance of the behavioral attitudes (positive or negative feelings about performing a behavior that reflect the summation of behavioral beliefs ) and the subjective norms (perceived social pressure to perform a behavior that reflects a summation of the normative beliefs ; Ajzen, 1991 ). That is, the TPB posits that behavior change is influenced by an individual's attitudes, perceived social norms, intention to perform the behavior, and perceived control over the process to change the behavior. We sought to influence each of the elements in the TPB model to promote behavior change among our patients with diabetes, many of which conceptually overlap with the health belief model and Bandura's (1997) self-efficacy model. As described earlier, our team has sought to modify beliefs and attitudes about diabetes-related health behaviors and increase patients' self-efficacy at successfully implementing behavioral changes.

In addition, we have tried to modify participants' subjective norms and normative beliefs about diabetes self-care: that is, what people believe is “normal behavior” for persons with diabetes and what they feel under social pressure to do regarding their diabetes care. We have largely accomplished this goal through the “social modeling” described above, but we have also used large media campaigns, involving television (e.g., annual 13-week series on the cable access network that takes live call-ins, interviews with local news stations), radio (e.g., regular interviews with several key African American radio stations), print media (e.g., community newspapers, major city newspapers), and social media, to influence subjective norms within the community.

Family, Friends, Small Groups

Support from friends, family members, and peers can help patients with diabetes modify their behaviors and achieve better health outcomes ( Peek, Harmon, et al., 2012 ); Samuel-Hodge et al., 2000 ; Trento et al., 2001 ). We purposely encouraged class participants to bring family members and/or friends (“whoever helps you manage your diabetes”) to the classes and facilitated the development of a family-like atmosphere within the classes themselves. Participants reported that the strong social bonds formed with their classmates, as well as the teachers, were a motivator for class retention and a facilitator of behavior change ( Goddu, Raffel, & Peek, 2012 ; Raffel, Goddu, & Peek, 2012 ).

Social Support

Social support has also been shown to have positive associations with diabetes behaviors and outcomes (Peek, Harmon, et al., 2012b; Samuel-Hodge et al., 2000 ; Trento et al., 2001 ). In Barrera's model, there are three types of social support: perceived support, enacted support, and social integration ( Cohen, Shmukler, Ullman, Rivera, & Walker, 2010 ). Perceived support is a person's subjective judgment that others will offer or have offered help. Enacted support includes specific supportive actions offered by others during times of need. Social integration is the extent to which a recipient is connected within a social network. We designed the diabetes education classes with the goal of implementing all three of these aspects of social support. We wanted participants to feel supported, both interpersonally and in tangible ways, throughout the class. We introduced the class as a “second family” and established a cultural expectation of emotional support throughout each session. Teachers were available before and after classes to provide individual assistance (e.g., rereviewing educational concepts), and participants used that time to provide social support to each other as well. During the classes, participants received glucometers and other tools to assist with diabetes self-care (e.g., measuring cups, pedometers, diabetes socks), real-time assistance and referrals to address pressing health issues (e.g., mental health counselors, urgent care visits), and other tangible means of support. Participants in the class were also socially integrated with each other; they would communicate outside of class, referred to each other as “teammates” and “family,” and relied on one another during class sessions.

We were able to leverage this social integration to facilitate behavioral change, particularly in the utilization of community-based resources that our research team collaboratively developed. Class participants reported being more comfortable using a new resource for the first time with the “warm hand-off” provided by trusted peers, class teachers, and other members of the intervention team (e.g., clinic staff, project managers). Class participants have participated in the K.L.E.O. Food Pantry, Diabetes Cook-Off, Museum of Science and Industry walking program, and the CFPP; they have used Food Rx at both the 61st Street Farmer's Market and at Walgreens locations and have joined local fitness facilities together using the Chicago Park District Exercise Rx distributed by our health care providers; and class graduates have led tours of the Farmer's Market and SAL grocery store and helped our team staff at health fairs and other community events (see Figure 1 ).

NOTE: Clockwise from upper right: K.L.E.O. Food Pantry participant; community leaders of Farmer's Market tours (including a patient class graduate), along with project staffer and state congressman; patient class graduate as a semifinalist in the 2012 Diabetes Cook-Off; Save-A-Lot grocery store tour being led by a dietician/certified diabetes educator; patient class graduate at the Farmer's Market.

Interestingly, participants in the mobile texting program reported statistically significant improvements in daily social support for diabetes self-care and qualitatively described feeling supported by the program. ( Nundy, Mishra, et al., 2014 ). Some participants in the texting program said they benefited from the feeling that “someone” was monitoring them and that help was available if needed. Some participants described the text messaging program as a “friend” or “support group,” and many valued the daily interaction the system provided.

Organizations, Communities, Culture

Ecological model.

This model expands behavior change influences from beyond the individual and their immediate social units (e.g., peers, family) to include environmental factors such as organizations, communities, and culture ( Fisher et al., 2002 ; Sallis et al., 2008 ). Health care organizations , and the providers within these organizations, can provide the infrastructure to not only improve patient care but also support patients in making behavior changes. For example, nurse care managers have been shown to enhance social support, increase medication adherence, and facilitate the adoption of lifestyle behaviors regarding diet and physical activity ( Sherbourne, Hays, Ordway, DiMatteo, & Kravitz, 1992 ). At one of our clinic sites, a nurse practitioner serves as a care manager for high-risk diabetes patients. She also coteaches in the diabetes education classes and, as such, is able to provide a seamless transition between intensive education, behavioral modification support, and care delivery. Increasingly, health systems are using team-based care and care coordination strategies for the management of chronic diseases such as diabetes, and a central component has been patient education and support of behavior change ( Peek, Ferguson, Bergeron, Maltby, & Chin, 2014 ). Within our project, we set out to provide additional tools and skills for providers and staff in motivational interviewing, engaging patients in SDM, and providing culturally competent care. Participants in our 4-hour workshop reported increased confidence in their ability to engage patients in their care and guide them along the “stages of change” in behavioral modifications. Our project also includes a quality improvement collaborative, composed of the quality improvement teams of the six participating health centers, which is currently working to incorporate diabetes care coordinators. One of roles of the care coordinators will be to provide personalized “coaching” for behavior change and lifestyle modification. As part of our mobile texting program, we piloted the use of a patient-generated health data tool, which summarized data from patients' texts into a one-page document, among primary care physicians and endocrinologists at one of our participating clinics. Providers found it to be a helpful tool for focusing their clinic visits on specific barriers to diabetes self-care, including behavior change ( Nundy, Lu, Hogan, Mishra, & Peek, 2014 ).

The importance of the local community , and its built environment, cannot be underestimated when assessing the feasibility of patients making recommended lifestyle changes to improve their health. Numerous studies have linked food deserts, the disproportionate presence of fast food venues (vs. grocery stores), and physical activity barriers (e.g., limited availability of parks and sidewalks, high traffic areas, crime/violence) to poor dietary patterns, sedentary lifestyles, obesity, and diabetes ( Dutton, Johnson, Whitehead, Bodenlos, & Brantley, 2005 ; Krishnan, Cozier, Rosenberg, & Palmer, 2009; Mari Gallagher Research and Consulting Group, 2006 ; Seligman & Schillinger, 2010 ). Thus, identifying and leveraging community resources to facilitate the adoption of healthy lifestyles are critical to any program seeking to change health behaviors among persons with diabetes. In our program, we specifically set out to identify and collaborate with local community resources that would help our activated patients sustain the behaviors they were eager to adopt. We did so in ways that addressed some of the financial constraints to the early adoption of behaviors, when patient ambivalence may allow financial constraints to outweigh the perceived benefits. Our Food Rx came with coupons or vouchers that allowed patients to obtain free, healthy food at locations close to their home. The Exercise Rx waived the fees for 6 months associated with the use of fitness facilities within the Chicago Park District, many of which are located within Chicago's South Side. The CFPP sought to expose participants to fitness resources on the South Side, at no cost, that they may not been aware of (e.g., local churches with designated space for weight training and exercise classes, University of Chicago recreational space that is open to the community) or may not have previously visited (e.g., local YMCA). The CFPP also sought to expose people to a range of physical activity types (e.g., weight training, yoga, running, line dancing) in order to help individuals “find their passion” about a specific physical activity that they would be willing to engage in long term. People are more likely to sustain behaviors that they enjoy (vs. cognitively recognize will improve their health), and so helping diabetes patients explore physical activity options, with the support of peers and members of our intervention team, may be an important way to bridge patients to community resources and sustain behavior change.

Patients living on the South Side of Chicago are largely working-class African Americans that were part of the Great Migration (or descendants of it) from the Southern United States ( Tolnay, 2003 ) As such, we have culturally tailored much of our program to fit the needs of this population. Our patient empowerment classes were designed based on qualitative research among African American diabetes patients on the South Side of Chicago ( Peek et al., 2008 ; Peek et al., 2009 ; Peek et al., 2010 ), and in consultation with a panel of experts that included community members with diabetes. We tailored the educational content, SDM training, to a teaching style (e.g., use of narrative, or storytelling) to fit the needs of the population ( Goddu et al., 2012 ; Peek, Harman, et al., 2012 ; Raffel et al., 2012 ). Similarly, we developed a bank of over 800 text messages for our mobile technology program with the help of a certified diabetes educator, who had worked on Chicago's South Side for decades, and several African American diabetes patients ( Dick et al., 2011 ; Nundy et al., 2012 ). Our CFPP incorporates components that culturally resonate with African Americans (e.g., incorporation of line dancing and zumba classes, the use of local African American fitness celebrities, the use of a “passport” whose design includes images of African Americans engaging in physical activity). Our community cooking demonstrations use African American chefs who are able to showcase traditional African American foods prepared in healthy, diabetes-friendly ways.

Government, Policies, Large Systems

The ecological model also recognizes that macro-level factors, such as governmental agencies, policies, and large systems, can significantly affect individual behavior change ( Fisher et al., 2002 ; Sallis et al., 2008 ). For example, diabetes education has long been a key recommendation of the American Diabetes Association (2012) in their annual treatment guidelines, but it remains significantly underfunded by health insurers ( U.S. Department of Health and Human Services, 2011 ). Moreover, a recent review of insurance plans (private and federal) found that coverage of support for diabetes self-management in general was minimal, with the exception of services such as nurse phone lines for patient calls ( Carpenter, Fisher, & Greene, 2012 ). However, the health policy landscape is changing in ways that will facilitate support of diabetes care. For example, in January 2014, the Centers for Medicare and Medicaid Services will provide Medicaid reimbursement for preventive health services by nontraditional health providers (e.g., community health workers), provided that the services have been recommended by a physician or other licensed health professional ( Centers for Medicare and Medicaid Services, 2013 ). Other reimbursement changes (e.g., global payment systems, accountable care organizations) with the implementation of the Accountable Care Act will support a greater emphasize on prevention among persons with diabetes, including behavioral changes that enhance disease control and reduce complications. Our team has been part of the Alliance to Reduce Disparities in Diabetes and, through this Alliance, has helped share and promote lessons learned with state and federal health policy makers. We have participated in webinars, conferences, and individual meetings to talk about the importance of health policy changes to support behavioral changes and diabetes self-management. In 2012, the Alliance to Reduce Disparities in Diabetes hosted a Diabetes Summit in Washington, D.C., cosponsored by the Office of Minority Health and the Division of Diabetes Translation of the Centers for Disease Control and Prevention, with the goal of having a national conversation with multiple stakeholders about critical health policy changes needed to improve the health and reduce disparities among vulnerable populations with diabetes (e.g., racial/ethnic minorities). One of the key messages at the Summit was the importance of insurance reimbursement for community health educators.

Summary and Conclusions

In a 2013 Consensus Report, Marrero et al. described a “21st-century” approach to behavioral medicine that acknowledges the complexities of behavior change and highlights the importance of using a multitude of strategies and systems to support behavior change among persons with diabetes. Patients, rightly so, are usually the core focus of behavioral interventions, and we need to spend significant time identifying ways to modify health beliefs, enhance self-efficacy, and change cultural norms regarding behavioral change. Yet patients live in social communities of families, friends, and peers, whose support can prove invaluable to patients initiating or sustaining behavioral changes. Health systems and larger policy changes are now on the cutting edge for influencing individual-level behavior changes. In the South Side Diabetes Project, we have taken a comprehensive “21st-century” approach to supporting behavior change among persons with diabetes, and have evidence that such a strategy is improving the health behaviors and health outcomes of participants.

Acknowledgments

Supported by the Merck Foundation, NIDDK R18 DK083946, and Chicago Center for Diabetes Translation Research (P30 DK092949). Dr. Chin was also supported by a National Institute of Diabetes and Digestive and Kidney Diseases Midcareer Investigator Award in Patient-Oriented Research (K24 DK071933).

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