Keywords

Description and Diagnosis

The prevalence and debilitation of depression makes it one of the most significant mental health concerns and most impairing psychiatric disorders for individuals, their family members, and society as a whole. Lifetime prevalence of depression is estimated to be 10–15%, with a 12-month prevalence of 9% in the United States (Lépine & Briley, 2011). Men and women with depression are respectively 20.9 and 27 times more likely to die by suicide than the general population (Ösby et al., 2001). When investigating all causes of death, individuals with depression are twice as likely to die prematurely in comparison to those without a diagnosis of depression (Ösby et al., 2001). In a 40-year longitudinal study, children or adults with depression worked 7 fewer weeks per year, had a 20% decrease in potential income, and contributed to a lifetime loss of $300,000 for each family (Smith & Smith, 2010).

Age of onset is typically between mid-adolescence and mid-40s, with the median age of the first episode of major depression occurring before 20 years of age (Nihalani et al., 2009; Moffitt et al., 2010). The debilitating effects of depression are further intensified by relapse and recurrence, with 50–85% of individuals with depression experiencing multiple episodes of depression in their lifetimes (Coyne et al., 1999). Women are twice as likely to receive a diagnosis of depression in comparison to men and this gender gap is thought to be related to biological (e.g., hormonal changes during puberty) and environmental factors (e.g., women’s greater hours of housework, tendency to care for more stressful/demanding situations at home, exposure to sexual abuse, use of ruminative coping, body image concerns, increased chances of widowhood/bereavement and lower pay compared to men) (Hyde et al., 2008; Mirowsky, 1996).

Depression can be defined by a number of symptoms that cause functional impairment for an individual and form a syndrome (Malhi & Mann, 2018). Symptoms of depression include depressed mood, anhedonia (i.e., a decreased inability to feel pleasure), neurovegetative symptoms (e.g., loss of appetite or weight, fatigue, insomnia), suicidal ideation, and difficulty with concentration. A diagnosis of depression for an individual is warranted after experiencing five of nine depressive symptoms nearly every day for a two-week period, as dictated by the Diagnostic and Statistical Manual for Mental Disorders (DSM-5) (American Psychiatric Association, 2013).

Behavioral Model of Depression

Operant Conditioning

Before one can fully understand the theory behind the behavioral model of depression, it may be helpful to provide a brief description of the principles of operant conditioning and its implications on the frequency of behavior. Skinner (1957) proposed that behaviors that operate on the environment lead to consequences that in turn affect the frequency of the occurrence of the functional class of behaviors in the future (hence the name operant). Therefore, the frequency of a behavior is controlled by its consequences. Specifically, positive reinforcement (i.e., the addition of a stimulus to the environment that leads to an increase in future frequency of behavior), negative reinforcement (i.e., the withdrawal of a stimulus from the environment that leads to an increase in future frequency of behavior), positive punishment (i.e., the addition of a stimulus to the environment that leads to a decrease in future frequency of behavior) and negative punishment (i.e., the removal of a stimulus from the environment that leads to a decrease in future frequency of behavior) affect the rate at which an organism responds (Skinner, 1957). Following these principles, extinction occurs when emitting a behavior no longer leads to reinforcement, so the frequency of the behavior decreases over time (Fantino & Stolarz-Fantino, 2012).

In addition, Skinner (1958) wrote that the organism often has emotional reactions to these operations, typically a more positive reaction to reinforcement than to punishment. Similarly, a behavior can be more likely to occur if it is followed by the removal of an aversive stimulus in the environment. An individual can either avoid contacting the aversive stimulus or escape it once it has been contacted (Fantino & Stolarz-Fantino, 2012). With this knowledge, a clinician can begin to understand which variables in their client’s environment may be maintaining their depressive symptoms by completing a functional analysis or a descriptive functional assessment of the depressive behavior (Murphy & Lupfer, 2014). A functional analysis or assessment identifies the idiographic antecedents and consequences that are causal and controllable in terms of their effects on the target behavior (Haynes & O’Brien, 1990).

With a better understanding of operant conditioning and the application of functional analyses for clients with depression, the knowledgeable clinician may begin to realize that there are two critical aspects of their client to be aware of. First, clients appear to be experiencing an emotional reaction to positive/negative reinforcement/punishment. Second, there is a certain amount of positive reinforcement in one’s life that feels good and must be achieved in order to continue to feel good. Therefore, it stands to reason that increasing positive reinforcement in one’s life is likely to reduce their depressive symptoms.

History of Development

Skinner (1965) was the first to offer a functional description of depression. In Science and Human Behavior, Skinner (1965) conceptualized depression as an extinction phenomenon in which behaviors that were formerly socially positively reinforced are later interrupted. This interruption in an established sequence of behavior was hypothesized to lead to feelings of loneliness (Skinner, 1965). Skinner’s (1965) functional analysis of depression served as the foundation upon which the first-wave treatment for depression (i.e., behavioral activation) was developed. Although some have argued against the conceptualization of behavioral activation as a first-wave behavioral treatment, it is considered to be a part of the first generation of behavior therapy because it directly applies operant conditioning to change overt behavior (Hayes & Hofmann, 2017). By contrast, the second wave focused on both behavior and cognitions, whilst the third and final wave of behavioral therapies included the addition of mindfulness techniques to change behavior (Hayes & Hofmann, 2017).

Ferster (1965, 1966) further behaviorally characterized the defining characteristic of depression as the reduced frequency of a positively reinforced behavior. He viewed most behaviors of a person with depression as passive and reactive, rather than active and freely emitted (Ferster, 1973). Ferster (1973) also identified escape and avoidance from aversive social consequences as potential antecedents for depression.

Similarly, Lazarus (1968) viewed depression as a lack of adequate or sufficient reinforcers in one’s environment. He proposed that an individual with depression is on an extinction schedule which results in a weakened repertoire. Initially, a significant reinforcer in one’s environment is withdrawn. The individual then either grieves the loss of the significant reinforcer or utilizes other reinforcers in their environment (Lazarus, 1968). If an individual lacks the capacity or opportunity to utilize other reinforcers at their disposal, then a chronic condition arises in which the individual is unaffected by most stimuli in their environment and then enters a depressive state (Lazarus, 1968).

Following the aforementioned behavioral views of depression, Lewinsohn and Atwood (1969) hypothesized that the depressive syndrome could be explained by a low rate of response-contingent positive reinforcement, which acts as an unconditioned stimulus for dysphoria, fatigue and some somatic symptoms. The social environment also maintains depressive symptoms by providing sympathy for depressive verbal behaviors (e.g., expressions of pessimism, fatigue, self-blame, and low self-esteem). The social environment can lead to a further decrease in positive reinforcement in one’s environment because an individual’s social supports may begin to avoid the aversive depressive verbal behaviors of the individual, further exacerbating their depressive symptoms.

Lewinsohn (1975) postulated that three variables affect response-contingent positive reinforcement that an individual can experience: (a) the number of activities that may be reinforcing for an individual, which is determined by one’s personal characteristics and experiences, (b) the availability of potentially reinforcing events in one’s environment, and (c) the extent to which the individual emits behaviors that increase the likelihood of contact with potentially reinforcing events in one’s environment. With these three tenets of Lewinsohn’s (1975) behavioral model established, clinicians can begin to identify how their clients with depression enter a depressive downward cycle in which they begin to engage in less activity, which leads to a decrease in positive reinforcement from their environment, and then become progressively more passive and depressed over time as the cycle continues (Kaiser et al., 2016).

To better understand our clients’ downward spiral of depression, it is helpful to acknowledge that there are many examples of reinforcing and punishing relations that affect mood. For example, putting on a coat when it is cold is negatively reinforcing and feels good because it removes the aversive chill. Going on vacation with friends in Hawaii is positively reinforcing and feels amazing because it adds enjoyable activities in one’s life. Eating gross food is a form of positive punishment and leads to a foul mood because it adds a horrible taste in our mouth. Finally, a friend canceling dinner plans is negatively punishing and leads to upset feelings because it removes the opportunity to have an enjoyable evening. With this context, it is easy to understand why people with depressive symptoms report engaging in fewer pleasant and more unpleasant events compared to those without depressive symptoms (Lewinsohn & Amenson, 1978).

Empirical Evidence in Support

Although no studies were able to clearly accept or reject the claims of the behavioral model of depression at its conception, there were a number of studies that were consistent with the model. First, given that people with depression emit fewer behaviors than those without depression (due to lower levels of behavior emission in general) (Libet & Lewinsohn, 1973; Libet et al., 1973), and that it is presumably reinforcing to be attended to, we can postulate that people with depression receive less social reinforcement from their environment than those without depression. Second, the number of pleasant activities that an individual engages in is significantly associated with their mood (Lewinsohn & Graf, 1973; Lewinsohn & Libet, 1972). In this way, engagement in pleasant activities acts as a reinforcer such that the probability of future engagement in pleasant activities increases. Third, individuals with depression obtain less positive reinforcement in their lives than nondepressed psychiatric and normal control groups and the subjective enjoyability of engaging in pleasant events for individuals with depression is rated lower (MacPhillamy & Lewinsohn, 1973). Fourth, individuals with depression appear to be more sensitive to social and painful aversive stimuli than nondepressed subjects and rate unpleasant events (i.e., punishers) as significantly more unpleasant (Lewinsohn et al., 1973; Libet et al., 1973; Schless et al., 1974). Therefore, we can expect that individuals with depression are more likely to avoid or escape unpleasant situations to provide short-term relief from the heightened aversiveness of unpleasant events, which leads to isolation and further exacerbation of depressive symptoms in the long-term, creating a positive feedback loop. Fifth, the incidence of aversive life events (e.g., marital conflict, work changes, death, and illness) in the 6 months prior to a depressive episode was shown to be three times higher than in a nondepressed group during the same period of time (Paykel et al., 1969). Therefore, we can deduce that a dramatic decrease in pleasant events (i.e., positive reinforcement) in one’s environment may be a critical antecedent for developing depression.

Since its conception in the 1970s, a number of studies concerning the behavioral model of depression continue to provide support for the model. Hopko and Mullane (2008) demonstrated that students with depression engage in fewer social, physical, and academic activities than nondepressed students. In addition, participants with depression exhibited higher negative affect, lower activity level, and a significant relationship between each activity and its corresponding reward value when behavior and mood were tracked every 2 h (Hopko et al., 2003a). These findings provide further support for the notion that changes in reinforcement correspond highly with mood in the moment and across time. Furthermore, individuals with depression experience less pleasure from engaging in daily activities and also expect future behaviors to be less rewarding (Hopko et al., 2003a, b; Hopko & Mullane, 2008). This pessimistic view follows Lewinsohn’s (1975) assumption that individuals with depression are essentially on an extinction schedule in which behaviors that are no longer rewarding are removed from their repertoire with time due to a weaker association between behavior and reinforcement. Furthermore, those with depressive symptoms experience more unpleasant events (i.e., punishers) in their lives and perceive them to be more aversive than those without depressive symptoms (Lewinsohn & Amenson, 1978).

Empirical Evidence Against

Although a number of studies provided support for the behavioral model of depression, some research conducted during its inception demonstrated inconsistent results. Contrary to the researcher’s predictions, individuals with depression appeared to encounter unpleasant events during a 30-day period with the same frequency as those who did not have depression, which does not align with the model’s assumptions concerning the low rate of positive reinforcement for those with depressive symptoms (Lewinsohn & Talkington, 1979). The same study found that those with depression only rated some, but not all, unpleasant events as more aversive than the control group, which directly conflicts with the behavioral model of depression and the findings of Schless et al. (1974). Costello (1972) also questioned if the behavioral model of depression can be simplified by hypothesizing that it is the loss of a reinforcer’s effectiveness (via biochemical or neurological changes or the disruption of a chain of behavior), rather than the loss of overall reinforcement, that accounts for the development of depressive symptoms. His support for this argument, however, is more anecdotal in nature and related to the depressive symptoms that follow death, rather than chronic symptoms of depression. He goes on to acknowledge that “there is no experimental evidence to support or embarrass this” (Costello, 1972, p. 597).

More recent research has also questioned the behavioral model of depression for a number of reasons. Theoretically, it does not account for depression onset without an apparent environmental cause and the strictly behavioral view does not consider the impact of cognition, relaxation, and values-consistent or inconsistent behaviors, which was viewed as a significant limitation in comparison to the second and third wave behavioral theories by some, but not all, behaviorists (Hayes, 2004). Additionally, the model neglects to acknowledge aversive control (i.e., negatively reinforcing and punishing contingencies) as a possible factor in impacting the onset and maintenance of depression (Kanter et al., 2008). For example, choosing to not attend a yoga class may help one avoid the possibility of humiliation, but it may also prevent positive social engagement opportunities as well. Studies indicate that depression is more typically characterized by the accrual of multiple chronic mild aversive situations (e.g., financial trouble, work-related stress, and homemaking demands) than by a decrease in positive reinforcement (e.g., job loss, divorce; Kanter et al., 2008). Although, it is important to recognize that the avoidance and escape of aversive stimuli can often lead to a decrease in positive reinforcement opportunities (e.g., calling in sick to work can be a form of avoidance that disallows one to contact possible reinforcers at work or on the way to and from work), so these two concepts are intricately related (Kanter et al., 2008).

Behavioral Activation

Description

As the evidence base for the behavioral theory of depression grew, so did interest in applying the model to treating depression. Based on the propositions of the behavioral model, the main objective of the behavioral treatment of depression is to achieve a satisfactory level of positive reinforcement in the lives of clients with depression by impacting the level, quality, and range of activities that one engages in (Lewinsohn, 1975). The singularly behavioral component of this type of therapy came to be known as behavioral activation. Unlike the psychodynamic treatments that were popular during its establishment, behavioral activation is derived from empirical research and applies a pragmatic approach. Prior to implementing behavioral activation treatment, however, it is essential to first complete a functional assessment in order to achieve five critical components: (1) evaluate the severity of the depressive symptoms, including suicide riski (2) identify any and all relevant behavioral deficits and excesses as these are thought to interfere with gaining reinforcers, (3) understand the variables that maintain the depressive symptoms such as partners reinforcing lower response rates, (4) develop a treatment plan by applying specific behavioral goals, and (5) enhance the client’s buy-in to treatment (Lewinsohn, 1975). Because clients are asked to commit fairly extensive work outside of session in behavioral activation treatment, it is crucial that buy-in to treatment is maximized while presenting the treatment rationale and developing treatment goals with clients in order to enhance motivation and treatment adherence. In practice, typical strategies to increase buy-in with clients include providing psychoeducation (e.g., stating that “behavioral activation is an evidence-based treatment known to improve the wellbeing of people with similar concerns to yours”), building rapport and enhancing the therapeutic alliance, and applying motivational interviewing techniques (e.g., utilizing decisional balances and increasing change talk).

Engaging in activity can be incredibly arduous for clients with depression, so the application of basic clinical skills is essential when implementing behavioral activation with clients (Martell, 2018). One manner in which to enhance collaboration and treatment adherence with clients is to deliberately put yourself in their shoes and clearly demonstrate an empathic and genuine concern for their unique situation. Therapists might also enhance clients’ treatment outcomes by actively attending to the present moment with clients so that examples of improvements in behavior offered by the client can be emphasized. Validating a client’s experience is a third clinical skill that can help clients engage in activities in a new way by demonstrating that the therapist truly understands that even basic activity engagement can feel insurmountable when living a life that feels absent of pleasurable experiences (Martell, 2018). Validating a client’s struggle can also be advantageous in strengthening the therapeutic alliance because an overly positive “cheerleading” therapist can lead some clients with depression to believe that the therapist is far too different from them to be of any value (Dozois & Bieling, 2010).

After completing a functional analysis with a client and whilst implementing clinical skills, a clinician is prepared to implement behavioral activation treatment with their client. Although researchers and clinicians have implemented behavioral activation in a multitude of forms across the past several decades, research indicates that it is effective when implemented as a structured and brief format or in a less formal manner, when a clear behavioral formulation has been achieved (Martell, 2018). Despite the proposal of many behavioral therapies for depression, the behavioral activation approach outlined by Lewinsohn et al. (1980) was the most influential during the first wave therapy movement and will therefore be discussed in the most detail (Kaiser et al., 2016).

Use of the Pleasant Events Schedule (PES; MacPhillamy & Lewinsohn, 1975) and the Unpleasant Events Schedule (UES; Lewinsohn et al., 1985) is helpful at the start of treatment to identify specific events in a client’s life that may be affecting their depressive symptoms (Lewinsohn et al., 1980). Each list consists of 320 items that one may find pleasant or unpleasant. The client’s ratings of the frequency of pleasant and unpleasant activities across the past month is thought to reflect the rate of positive reinforcement and aversiveness experienced by the client. The 80 most frequent pleasant and unpleasant items are then combined to form an individualized Activity Schedule, which clients use to track their daily activity engagement and mood throughout treatment. The main objective of tracking mood and activity is to demonstrate the covariation between these two variables for the client, which can be easily demonstrated via a visual graph depiction. The daily and continuous feedback during treatment allows the therapist and client to make adjustments as necessary to treatment procedures and goals (Lewinsohn et al., 1980).

Empirical Evidence in Support

Since its development in the 1970s and 1980s, a wealth of empirical support has demonstrated that behavioral activation is a promising treatment intervention for depression. Early research on treatment effectiveness primarily consisted of case studies which indicated that behavioral activation can be effective in treating depression, but more rigorous research was later completed (Lewinsohn, 1975). In a meta-analysis of 16 studies consisting of 780 subjects on behavioral activation, a difference between behavioral activation and control conditions revealed a pooled effect size of 0.87 at posttest (Cuijpers et al., 2007). A larger meta-analysis of 34 studies consisting of 2055 participants also demonstrated a difference between behavioral activation and control conditions at posttest with a large pooled effect size of 0.78 (Mazzucchelli et al., 2009). The authors of both meta-analyses did not find a significant difference between behavioral activation and cognitive therapies at posttest or follow-up. Taken together, these results indicate that behavioral activation is a parsimonious and effective treatment intervention for adults with depression.

The transition into the second wave of behavioral therapies led to the integration of behavioral activation with cognitive therapies, but it became apparent that a component analysis of cognitive behavioral therapies for depression was necessary to delineate the active components of the increasingly more complex interventions. Jacobson et al. (1996) compared the following three groups: behavioral activation alone, behavioral activation and automatic thought modification, and full cognitive therapy treatment. Behavioral activation alone was found to be equal in efficacy in comparison to the other two groups and demonstrated similar relapse rates at a two-year follow-up (Gortner et al., 1998). Given that behavioral activation is a more parsimonious intervention technique, it may be more accessible to less experienced clinicians or paraprofessionals, and therefore better able to benefit more clients (Jacobson et al., 1996).

In addition, behavioral activation may be more effective than cognitive behavioral therapies because clients have a lower attrition rate in behavioral activation treatment and it is known to be useful for clients that do not respond to cognitive therapies (e.g., individuals with severe depression, substance use, and dementia; Sturmey, 2009). Compared to medication, behavioral activation is also a cheaper option that results in lower relapse rates and fewer side effects (Sturmey, 2009). Given what we now know about behavioral activation, there is adequate evidence to conclude that it is an evidence-based therapy for depression (Sturmey, 2009). Furthermore, the first wave of behavior therapy for depression (i.e., behavioral activation) appears to be as effective as the second wave (i.e., cognitive therapies) in treating depressive symptoms and is a more parsimonious treatment intervention.

Empirical Evidence Against

Although behavioral activation is supported by evidence in numerous studies, some studies do not shed as favorable of a light upon behavioral activation as an effective treatment for depression. For example, Martell et al. (2004) proposed that it seems unlikely that arbitrary behavioral prescriptions (e.g., riding a bike for a certain amount of time) will alleviate the symptoms of depression, which is supported by the fact that busy people can experience severe symptoms of depression. They additionally recognize the following criticisms: (a) support for behavioral activation treatment does not equate support for the behavioral theory of depression, (b) the practical and parsimonious dissemination of treatment has yet to be determined, (c) we do not know the mechanisms of change in behavioral activation, and (d) it is unclear if behavioral activation can be dismantled further.

Less specific criticisms include a common argument in treatment outcome research that participants in controlled trials tend to be less severe and are not affected by comorbid conditions, which does not accurately reflect clients in real-world settings (Dozois & Bieling, 2010). There is also a desperate need for research on treatment outcomes for racial/ethnic minorities as this is a neglected area in research on treatments for depression (Hu et al., 2020).

Use with Different Clients

Because behavioral activation is contextualistic (i.e., idiographic) in nature, its application may be well suited for treating depression in culturally diverse populations. Behavioral activation treatment manual adaptations have been formed for Latinos (BA-L; Kanter et al., 2014), Muslims (BA-M; Mir et al., 2016) and African Americans (Bowe, 2013). To date, 17 studies have culturally adapted behavioral activation to fit culturally diverse populations and ethnic minorities, with the following target populations: seven for Latin Americans, four for African Americans, one for Muslim patients in the United Kingdom, two for adults in Indian primary health centers, one for victims of systematic violence in Iraq, one for locals in Iran, and one for older adults living alone in China (Lehmann & Bördlein, 2020). Access to services was amplified by providing treatment via phone or in clients’ homes, by providing treatment in clients’ native language, and by treatment being delivered effectively by less experienced practitioners. A systematic review of the 17 studies claimed that behavioral activation is an “effective, cost-efficient, and well-fitting treatment for depression in these target groups” because it allows clients and practitioners to consider cultural, social, environmental, and psychological factors that may be impacting the maintenance of depression and the course of treatment (Lehmann & Bördlein, 2020, p. 700). As advocated by Hu et al. (2020), there is a clear need for continued research on treatments for depression in culturally diverse populations and ethnic minorities, with a specific focus on evaluating the components of culturally adapted treatment interventions that impact outcomes being particularly important (Lehmann & Bördlein, 2020).

The majority of the research on behavioral activation investigates individual therapy formats, despite groups having greater therapeutic efficiency with a greater capacity to benefit more clients (Porter et al., 2004; Raines et al., 2020). Porter et al. (2004) addressed this by developing the Behavioral Activation Group Therapy (BAGT) manual which led to significant decreases in depressive symptoms at posttest and three-month follow-up after only 10 weeks of group therapy. Similarly, Chu et al. (2009) developed a transdiagnostic Group Behavioral Activation Therapy (GBAT) for youth in a school setting which evidenced superior posttreatment and four-month follow-up outcomes for adolescents in comparison to a waitlist control (Chu et al., 2016). It is important to continue to consider the implementation of group therapy formats because providing effective treatment to more clients in a shorter amount of time is cost-effective for clinicians and their clients and allows services to be delivered to a greater number of clients, which is particularly essential in regions where access to healthcare is limited (Porter et al., 2004).

A key issue to consider is how much one needs to increase reinforcers, which is largely unknown at a group (i.e., nomothetic) level. For this reason, the individual (i.e., idiographic) nature of behavioral activation is an immense strength that the astute clinician would be wise to utilize effectively. For example, it may be important to consider if your client finds social reinforcers (e.g., being complimented) to be more impactful than solitary reinforcers (e.g., putting on make-up) so that the stronger reinforcer can be emphasized in the treatment process.

Clinical Case Example

Description

Behavioral activation is appropriate for clients with the following characteristics: (a) experience depressive symptoms, (b) believe that changing behavior can impact mood, (c) willingness to work towards changing behavior, and (d) concerned about the side effects and cost of medications (Lejuez et al., 2001). Behavioral activation can also be customized for individuals with a diagnosis of depression and a comorbid mental health and/or physical health disorder (Cannity & Hopko, 2017). Therefore, it seems that anyone with depressive symptoms will likely benefit from the implementation of behavioral activation treatment. The following fictional clinical case description matches these qualities and will serve as a representative client for behavioral activation treatment.

Jane Doe is a 33-year-old Caucasian cisgender woman who meets criteria for major depressive disorder, recurrent, moderate. Jane is married, has a 2-year-old daughter, and teaches third grade at her local public school. She experienced two prior depressive episodes which persisted for approximately 12 months at ages 19 and 27. Her current depressive episode began shortly after she returned to teaching for the fall semester, approximately 2 months ago. She is not currently taking any medications and does not match criteria for any other mental health diagnoses, though she does express feeling anxious about work and home duties at times. Jane’s primary complaints include general anhedonia, frequent bouts of crying, depressed mood, hypersomnia, and lethargy. Jane reports that spending time with her daughter and husband is incredibly rewarding, but that she is so tired after work that she does not have the energy to spend time with them. She also expresses that she is too tired to keep up with household tasks (e.g., cooking, cleaning dishes, and laundry), so her husband completes all domestic duties in the home. Jane sleeps approximately 10–12 h per day, which further limits the time that she can spend engaging in rewarding activities (e.g., socializing with friends and family, exercising, and engaging in preferred hobbies). Jane reports that she used to enjoy reading, hiking, and walking her dog, but that these activities no longer bring her a sense of enjoyment, so she no longer participates in these behaviors.

Jane’s weekly activity log shows that she wakes up at 6:30 am, works 8 am–6 pm, and then sleeps 7:30 pm–6:30 am Monday through Friday. On the weekends, she tends to wake up at 9 am and lies in bed watching TV until noon, grades papers until 5 pm, goes back to bed at 5:30 pm and watches TV in bed until she falls asleep around 9 pm. Her husband brings her breakfast, lunch and dinner in bed because she reports that she is too tired from the week to cook or leave her bed to eat. Jane reports that working is important to her, but that she does not have energy left to engage in other activities that are meaningful.

Application

Because it can be quite challenging for a client with depression to increase their activity levels, providing a reasonable treatment rationale is a critical first step in behavioral activation treatment. Jane’s clinician might provide the following treatment rationale (adapted from Lejuez et al., 2001), which implements idiographic characteristics specific to Jane’s case and promotes collaboration with Jane:

Jane, it seems that you may be waiting to feel better before engaging in some of your more enjoyable activities, such as spending time with your family, reading, hiking, and walking your dog. As you are aware, it can be hard to wait to feel better, so I am proposing we try a different method together. Based on an abundance of prior research, which I am happy to share with you if you would like, we believe that the first step to feeling better is engaging in more positive situations in your life. We theorize that if you are engaging in activities that bring you a sense of joy and accomplishment, then it is challenging to feel depressed. It can be difficult to start, but it tends to get easier with the more positive experiences you encounter. The treatment can be hard at times, but I am here to help you through this process, and we will work together at a pace that feels best for you.

With Jane’s buy-in and active collaboration, her clinician can next create a functional analysis in order to identify the controllable variables in her environment that are maintaining her depressive behaviors. For example, we can theorize that Jane’s husband may be negatively reinforcing her depressive symptoms by completing all the required domestic duties.

Following Lewinsohn et al.’s (1980) treatment protocol, the next step for Jane’s treatment involves completing a Pleasant and Unpleasant Events Schedule to identify the 80 most pleasant and unpleasant items to place on Jane’s activity log. Jane’s top ten most pleasant and unpleasant items are displayed in Table 1. Upon careful review, Jane’s clinician can understand that the majority of her pleasant and unpleasant activities are related to time spent with her husband and daughter, so emphasizing engagement in pleasant activities with her family will be Jane’s primary treatment focus with her clinician. Jane and her clinician can collaboratively identify enjoyable family-focused activities and begin to schedule these during the times that are most reasonable for Jane.

Table 1 Jane’s top ten pleasant and unpleasant events most highly correlated with mood
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Jane’s therapist can ask her to track her daily mood on a scale from 1–10 (1 = poor, 10 = very good) and to track the number of pleasant and unpleasant events that Jane engages in each day, based on her top 10 pleasant and unpleasant activities. With this valuable information, her clinician can create a graph to depict changes in her mood and activity engagement over time (see Fig. 1). The visual depiction allows Jane and her clinician to easily observe how engaging in less unpleasant events and more pleasant events correlates with an increase in mood for Jane over time.

Fig. 1
A line graph of events and mood from 0 to 10 versus days from 1 to 46 plots the curves for unpleasant, pleasant, and mood events. All lines exhibit peaks and troughs in an increasing trend except the unpleasant line which is decreasing.

Case presentation: daily monitoring of unpleasant and pleasant events with mood

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Depressive symptoms have a high propensity for relapse, so it is essential to form a relapse prevention plan with Jane prior to treatment termination. Helping Jane to understand how her behaviors affect her mood, with significant help from the graph depicted in Fig. 1, is a critical component of Jane’s therapeutic process and will significantly decrease the chance of relapse. At this stage, it is also helpful for Jane’s clinician to review the purpose of a functional analysis and clarify how Jane may understand the influence of the environment on her mood in order to manipulate the relevant controlling variables in the future. For example, Jane’s clinician may query Jane on how excessive sleeping negatively reinforced her depressive symptoms. By collaboratively creating a functional analysis of her own behavior with her clinician, Jane will be more effective at manipulating the controlling variables in her environment in the future and preventing the onset of an additional depressive episode. Additionally, Jane’s clinician can review normal fluctuations in mood with Jane so as to not pathologize increases or decreases in Jane’s future disposition.

Potential Difficulties

Ambivalence

Fewer than 20% of individuals who seek treatment are prepared to take action to change their mental health problem, so clinicians must be prepared to address ambivalence with their clients (Prochaska, 2000). For individuals with depressive symptoms, it can be particularly challenging to enhance motivation for change because avoidance is a common behavioral response to their depressive mood (Dozois & Bieling, 2010). In these instances, motivational interviewing can be particularly helpful for clinicians to meet clients where they are by simply validating, exploring, and genuinely understanding a client’s perspective regarding their ambivalence to change (Hettema et al., 2005). In so doing, a client may begin to engage in change talk (i.e., statements related to a client’s desire, need, and ability to change), which can be selectively reflected back by their clinician. With this back-and-forth process, clients can hear their own motivations for change which can enhance client’s commitment to change. In fact, the commitment strength of change talk stated during the final moments of a session by clients are the strongest predictor for future behavior change (Amrhein et al., 2003).

Homework Compliance

Although homework completion is known to enhance therapy outcomes (Kazantzis et al., 2010), clinicians report issues with homework compliance and out-of-session tasks with 50% of their cases (Helbig & Fehm, 2004). Because homework completion is a vital part of behavioral activation treatment, it is important for clinicians to be prepared to address issues with homework completion when implementing behavioral activation treatment. Clinicians can revisit the treatment rationale, provide additional psychoeducation, break tasks into simpler and more manageable steps, and reinforce the importance of homework with clients in order to enhance homework completion with their clients (Dozois & Bieling, 2010).

Arguably one of the most effective ways to address homework noncompliance in behavioral activation treatment is by completing a functional assessment with a client. With careful consideration of the client’s antecedent-behavior-consequence (ABC) sequence, clinicians can identify potential barriers to activation and/or homework completion for clients (Martell, 2018). Given that the purpose of a functional analysis or descriptive functional assessment is to understand the variables that increase/decrease the frequency of a behavior over time, clinicians can work with their client to identify and manipulate the relevant variables that may contribute to increasing homework completion. For example, in our clinical case example, Jane struggled to spend time with her family because she was tired at the end of her workday. In this example, we can conceptualize lethargy as the antecedent, isolation as the behavior, and the lack of increase in mood or time spent with her family as the consequence. Via an exploratory discussion with Jane, a number of potential ideas could be proposed that directly affect the ABC sequence such as spending time with her family before work, working fewer hours during the day, drinking coffee when she got home, or planning activities with her family after work that she could not cancel. Based on Jane’s preferences, she can select the preferred activity, which is likely to increase Jane’s chances of completing the activity. Asking Jane to formally commit to engaging in her preferred activity at the end of session is an additional strategy to increase the chances that she will complete it (Amrhein et al., 2003). By completing this process collaboratively and openly with Jane, she is additionally more likely to be able to complete her own functional analyses in the future, which will assist with relapse prevention post-treatment termination.

Resistance

Some clients may also resist scheduling activities with their clinician. If the resistance appears to stem from ambivalence about change, similar tactics (e.g., revisiting treatment rationale, providing additional psychoeducation, breaking tasks into smaller steps, and utilizing motivational interviewing techniques) may be applied that were discussed above. A functional analysis may also be helpful to identify the variables that may be contributing to the resistance. If the resistance stems from a client’s desire to be spontaneous and unconstrained, however, it may be beneficial to ask clients how this technique has been working for them so far (Leahy et al., 2011). Clients that are resisting activity scheduling may also benefit from hearing their clinician describe activity scheduling as an exercise analogy (Leahy et al., 2011). For example, Jane’s therapist might ask questions such as “If you want to get in shape, would you only exercise when you feel like it,” “What might be the outcomes of approaching fitness in this way,” or “Have you ever exercised even though you didn’t feel like it?”. These types of questions might help Jane and similar clients think about how activity scheduling can be a vital aspect of enhancing their mental health and hence increase treatment adherence and outcomes.

Summary

Depressive symptoms have a debilitating impact on self, family and society. Lewinsohn’s (1975) behavioral model of depression proposes that depressive symptoms are maintained by a low rate of response-contingent positive reinforcement in which individuals with depression engage in less activity which diminishes their contact with positive reinforcement and further decreases their overall activity engagement and mood. From the behavioral theory emerged the first wave behavioral treatment for depression (i.e., behavioral activation) designed to achieve satisfactory levels of positive reinforcement in one’s life by affecting the quality, level, and range of positive reinforcement that individuals contact in their environment (Lewinsohn, 1975).

Functional assessment that identifies the antecedent-behavior-consequence (ABC) sequence of behaviors are an essential first step to treatment and basic clinical skills are beneficial for clinicians to apply throughout treatment. Lewinsohn et al.’s (1980) treatment approach advocates for the application of the Pleasant and Unpleasant Event Schedules to form clients’ Activity Logs and encourages daily activity and mood monitoring for clinicians to graph and share with their clients.

Behavioral activation has demonstrated impressive clinical utility with ethnic minorities and in group format and continues to gain empirical support. When faced with challenges in treatment, clinicians will benefit from revisiting the treatment rationale and utilizing functional analyses to address and resolve barriers. Future research should work to identify the mechanisms of change in behavioral activation, with a particular focus on the aspects of culturally adapted treatment interventions that impact outcomes for culturally diverse populations and ethnic minorities.