A Contextual Behavior Science Framework for Understanding How Behavioral Flexibility Relates to Anxiety

Abstract

There is a growing literature focusing on the emerging idea that behavioral flexibility, rather than particular emotion regulation strategies per se, provides greater promise in predicting and influencing anxiety-related psychopathology. Yet this line of research and theoretical analysis appear to be plagued by its own challenges. For example, middle-level constructs, such as behavioral flexibility, are difficult to define, difficult to measure, and difficult to interpret in relation to clinical interventions. A key point that some researchers have made is that previous studies examining flexible use of emotion regulation strategies (or, more broadly, coping) have failed due to a lack of focus on context. That is, examining strategies in isolation of the context in which they are used provides limited information on the suitability, rigid adherence, or effectiveness of a given strategy in that situation. Several of these researchers have proposed the development of new models to define and measure various types of behavioral flexibility. We would like to suggest that an explanation of the phenomenon already exists and that we can go back to our behavioral roots to understand this phenomenon rather than focusing on defining and capturing a new process. Indeed, thorough contextual behavioral analyses already yield a useful account of what has been observed. We will articulate a model explaining behavioral flexibility using a functional, contextual framework, with anxiety-related disorders as an example.

Keywords

contextual behavior science anxiety emotion regulation behavioral flexibility

The current commentary presents a contextual behavior science (CBS) perspective to the evolving understanding of the role of behavioral flexibility in anxiety-related disorders. While a variety of conceptualizations have emerged to describe this phenomenon (e.g., cognitive flexibility, coping flexibility, regulatory flexibility), we will use the term “behavioral flexibility” throughout this article because a CBS framework conceptualizes all of these phenomena, including cognitions (i.e., verbal behavior) as behaviors.

In recent years, a number of researchers have devoted significant effort toward developing and refining theoretical accounts of behavioral flexibility (e.g., Aldao, Sheppes, & Gross, 2015; Bonanno & Burton, 2013; Cheng, Lau, & Chan, 2014). Here, we suggest that an explanation of the phenomenon of behavioral flexibility already exists and that we can go back to our behavioral roots to understand this phenomenon rather than invoking one or more new processes. In doing so, we provide an account that suggests that behavioral flexibility is an outcome, rather than a mechanism, that can be influenced by well-recognized behavioral processes. We first provide a brief background on the development of behavioral flexibility models and the challenges related to this work. We then provide a CBS account of behavioral flexibility using anxiety-related disorders as an example. Finally, we argue that this CBS account may be a useful conceptualization of behavioral flexibility that identifies clear and targetable change mechanisms.

Emergence of Behavioral Flexibility

While a full history of the research on flexible responding to aversive environmental or internal stimuli are beyond the scope of the current article (though see Aldao et al., 2015, for an excellent discussion of this history), a recent, more focused attempt to characterize and evaluate flexibility processes can be traced in large part to the popular work in emotion regulation strategy selection (e.g., Aldao et al., 2015; Gross, 1998; Gross & John, 2003). Over the past several decades, researchers have focused on identifying emotion regulation strategies associated with resilience or psychopathology. Gross’ model, which identified various stages in the emotion generative process at which one could respond, with earlier responses thought to be more adaptive for effectively downregulating emotions, led to an explosion of promising research (Gross, 1998; Gross & John, 2003). “Adaptive” strategies, such as problem solving, reappraisal, and acceptance have been associated with increased psychological well-being, while relative deficits in their use (frequency or ability) were shown to be associated with lower overall well-being (e.g., Gross & John, 2003; Salters-Pedneault, Roemer, Tull, Rucker, & Mennin, 2006; Tull, Barrett, McMillan, & Roemer, 2007; Tull & Roemer, 2007). Conversely, “maladaptive” strategies (e.g., suppression, experiential avoidance, and rumination) were clearly associated with increased risk for psychopathology (e.g., Campbell-Sills, Barlow, Brown, & Hofmann, 2006; Kashdan, Morina, & Priebe, 2009; Nolen-Hoeksema & Morrow, 1993). The promise of this work lay in its ability to characterize multiple forms of psychopathology as well as its provision of well-delineated targets for clinical intervention.

Despite such early promise, further examination of “adaptive” versus “maladaptive” strategies yielded equivocal findings. That is, “adaptive” and “maladaptive” strategies did not uniformly function as such, especially when the outcome under investigation was defined functionally, for example, beyond intensity of emotional experience, to include concepts such as successful goal pursuit (Aldao et al., 2015). For example, the use of reappraisal (an “adaptive” strategy) to reframe negative experiences can lead to negative social consequences, such as acceptance of unfair treatment (van’t Wout, Chang, & Sanfey, 2010). Furthermore, some researchers have reported limited (Aldao & Mennin, 2012) or paradoxical (Dunn, Billotti, Murphy, & Dalgleish, 2009) effects of “adaptive” acceptance strategies. Conversely, the ability to use emotional suppression (generally conceptualized as “maladaptive”) can be adaptive in some situations (Sullivan, Helms, Kliewer, & Goodman, 2010). Short-term avoidance strategies (e.g., distraction) can even be effective in accomplishing particular goals (Dempsey, Stacy, & Moely, 2000; Edlynn, Gaylord-Harden, Richards, & Miller, 2008). For example, it can be useful for surgeons to avoid or suppress their anxiety in the middle of a difficult surgical operation. Thus, in some cases, there may be an advantage to short-term avoidance of experiences that are painful. Indeed, experiencing painful private events constantly and fully could interfere with goal-directed behavior in some contexts. Other researchers have found that while increased use of putatively maladaptive strategies is associated with psychopathology, use of putatively adaptive strategies appears to be protective only for those who also tend to use maladaptive strategies frequently (Aldao & Nolen-Hoeksema, 2010, 2012a). These equivocal findings suggest that teaching more adaptive emotion regulation strategies, even if it leads to increased use of them, may not be uniformly clinically indicated.

Taken together, this body of evidence suggests that the mere presence of adaptive versus maladaptive emotion regulation strategies may not be the key mechanism accounting for psychopathology. Some researchers have suggested that the lack of consideration of context may account for the current state of the emotion regulation literature (Aldao, 2013; Bonanno & Burton, 2013). That is, examining strategies in isolation of the context in which they are used provides limited information on the suitability or effectiveness of a given strategy in that situation. These researchers suggest that individuals who are able to employ a variety of emotion regulation strategies in a manner that is sensitive to changing contextual demands could be considered to demonstrate greater behavioral flexibility, and ultimately less psychopathology.

This new focus on flexibility has specifically shown promise in understanding a variety of anxiety disorders. For example, Lee and Orsillo (2014) found that participants with generalized anxiety disorder (GAD) showed less cognitive flexibility, as measured by the emotion Stroop test, compared with nonanxious controls. In another study, Palm and Follette (2011) found that lower cognitive flexibility, as measured by the Cognitive Flexibility Scale (Martin & Rubin, 1995), and greater experiential avoidance were associated with greater depression and posttraumatic stress disorder symptomatology in a sample of women reporting a history of interpersonal victimization. Other studies have suggested that flexible use of emotion regulation strategies and anxiety symptoms are related to physiological indices of adaptive emotional responding (i.e., heart rate variability; Aldao, Mennin, & McLaughlin, 2013; Di Simplicio et al., 2012; Svendsen et al., 2016). In sum, greater behavioral flexibility has been associated with indices of psychological health, and less behavioral flexibility has been related to greater anxiety-related psychopathology.

Despite these promising findings, this new line of research seems to be plagued by its own challenges. First, there are a number of inconsistencies in how various forms of behavioral flexibility have been defined, particularly with respect to the breadth of phenomena considered. Those working within an emotion regulation framework have continued working to operationalize a model specific to the flexible use of emotion regulation strategies (Aldao et al., 2015). Some have synthesized earlier work on “coping flexibility” with emotion regulation (Cheng et al., 2014), using the broader term of “regulatory flexibility” to accomplish this integration (Bonanno & Burton, 2013). Still others have taken an even broader approach to conceptualizing flexibility; for example, Kashdan and Rottenberg (2010) proposed an individual difference model presenting the possibility that a vast range of phenomena, including emotion regulation, may correlate with level of flexibility and influence on overall well-being. This model synthesizes evidence from a number of domains in which flexibility has been associated with functioning, citing physiological signs of flexibility as one future avenue for capturing overall regulatory flexibility (Kashdan & Rottenberg, 2010).

These varying conceptualizations have led to varied methods for measuring and examining these processes, and ongoing debate as to the most useful method for defining and capturing flexibility. Some studies have relied on self-report measures that have fostered individual difference interpretations of behavioral flexibility that exclude consideration of context (e.g., Dennis & Vander Wal, 2010; Fresco, Williams, & Nugent, 2006; Palm & Follette, 2011). Unfortunately, studies that rely on self-report measures of behavioral flexibility can lead to attributions that behaviors are due to individual characteristics that persist across situations, irrespective of emotional state or context.

A second challenge in current conceptualizations and measurement of behavioral flexibility is that their predictions have not necessarily aligned with findings from parallel lines of research. For example, research examining the social regulation of emotion (for a review, see Coan & Maresh, 2014) suggests that our perception and response to emotion varies depending on whether loved ones are in close proximity, an important contextual factor that is left out of individual difference, trait-level analyses. Other researchers have similarly emphasized the role of social and verbal contexts in the perception of and response to emotion (e.g., Barrett, 2012; Barrett, Lindquist, & Gendron, 2007).

The current confusion in the literature about the definition and measurement of behavioral flexibility has made it difficult to determine future research directions, with some even suggesting abandoning the pursuit of examining behavioral flexibility until the construct itself can be effectively measured (Aldao et al., 2015). We would like to propose an alternative route—that is, returning to our behavioral roots, and considering a CBS account of behavioral flexibility. Within a CBS framework, behavioral flexibility seems to be more of a functional outcome influenced by environmental and verbal contexts, and observed when individuals are functioning effectively. The main reasons to consider a CBS framework for understanding how behavioral flexibility relates to anxiety are twofold: First, theoretical constructs proposed and examined in the CBS literature may better explain what causes variation in behavioral flexibility. Second, a CBS framework may offer a more promising approach to measuring behavioral flexibility.

Contextual Behavioral Science Account of Behavioral Flexibility

Contextual behavioral science provides an account of how behavioral flexibility can manifest through the influence of environmental and verbal contexts. Hayes and colleagues (Hayes, Luoma, Bond, Masuda, & Lillis, 2006; Hayes, Wilson, Gifford, Follette, & Strosahl, 1996) have argued that such manifestation occurs largely because of negative reinforcement and the verbal context. In this section, we will articulate how negative reinforcement and the verbal context can influence behavioral flexibility. We will then describe the research and clinical implications of this analysis.

Negative Reinforcement

Several forms of psychological suffering have been conceptualized using negative reinforcement models, including depression, substance use disorders, and anxiety disorders (e.g., Baker, Piper, McCarthy, Majeskie, & Fiore, 2004; Behar, DiMarco, Hekler, Mohlman, & Staples, 2009; Hayes et al., 1996). Generally, negative reinforcement models posit that behavioral responses will increase if they function to escape or avoid aversive conditions. While positive reinforcement models have also been used to describe behavioral flexibility (Ono, 1997) and various forms of psychopathology (e.g., Glautier, 2004; Lewinsohn, 1974), we focus on negative reinforcement in the current analysis because of the focus on these models in understanding anxiety-related disorders. Indeed, there is an extensive literature illustrating the link between avoidance and increased psychopathology (e.g. Berking, Neacsiu, Comtois, & Linehan, 2009; Briggs & Price, 2009; Kashdan et al., 2009). Negative reinforcement models suggest that long-term, persistent use of avoidance strategies may increase the actual occurrence of negative experiences, thus exacerbating problems associated with it (Hayes & Gifford, 1997). Continuing to avoid these associated negative experiences as they intensify can create a “behavioral loop” (p. 170), such that the individual becomes insensitive to consequences outside of this loop and the individual exhibits behavioral inflexibility. It is when this rigid pattern of consistently avoiding painful stimuli develops, even under pressure not to do so, that psychological functioning deteriorates. This behavioral loop has been illustrated with overt behaviors, but also with cognition and emotion, particularly in the thought suppression and affective control literature. For example, deliberate attempts to control or change particular thoughts result in exactly the opposite phenomena. A series of studies examining thought suppression demonstrated that attempts to suppress or reduce the frequency of certain types of thoughts actually increase the occurrence of those thoughts (e.g., Wegner, 1997; Wegner & Zanakos, 1994). This “rebound effect” may produce a situation in which a person who tries to suppress a memory may experience an increased frequency of that same memory, resulting in further attempts to suppress that memory, and so on. As efforts to suppress unwanted thoughts continue and increase, the opportunity for other thoughts or competing consequences for having the thoughts are limited.

Negative reinforcement is also illustrated by a hallmark feature of several anxiety disorders: worry, which is an example of verbal behavior from a CBS perspective. The current Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association, 2013) diagnostic criteria for GAD include excessive worry occurring more days than not for 6 months, in other words, the more frequent the worry, the worse the symptomatology. However, more recent research has differentiated clinical and nonclinical subgroups of high worriers, showing that nonclinical high worriers view their worry as more controllable, less distressing and impairing, and less frequently associated with cognitive and physiological symptoms than do worriers diagnosed with GAD (Ruscio, 2002). Thus, the content or number of worries may be less relevant than the inflexible pattern of worry that functions simultaneously to alleviate short-term anxiety and prevent contact with broader range of outcomes. Borkovec’s avoidance model (Borkovec, Alcaine, & Behar, 2004) is in line with this claim. He posited that worry is a cognitive activity negatively reinforced by the short-term reduction of distress. Indeed, the tendency to worry to distract oneself from emotional arousal is the only self-reported reason that distinguishes a clinical population of worriers from a nonclinical population of worriers (Borkovec & Roemer, 1995). In addition, Roemer, Salters, Raffa, and Orsillo (2005) found that individuals with clinical levels of GAD had elevated scores on measures of experiential avoidance, as well as increased scores of emotional fear responding. Startup and Davey (2001) found that inducing negative mood led to increases in catastrophic worry, suggesting that worry may be a conditioned response to negative affect. Taken together, these data suggest that clinical worry can be conceptualized as the perseveration of a behavior (worrying) in response to negative affect, limiting alternative responses to negative affect, and thus preventing contact with alternative outcomes. In this way, consistent use of worry in this way can lead to decreased behavioral flexibility.

Verbal Context

A CBS framework extends traditional negative reinforcement accounts of anxiety to include a formulation regarding the role of verbal behavior (e.g., cognition, speech, etc.) and the verbal context (e.g., responses to and/or consequences of verbal behavior). Examining relational responding and rule governance may enhance our understanding of behavioral flexibility even further by providing an account of how behavioral flexibility serves as an outcome of these processes. While a complete account of relational frame theory (RFT) is beyond the scope of this article, we will briefly describe some of the core principles of relational responding as they relate to behavioral flexibility (see Hayes, Barnes-Holmes, & Roche, 2001). Relational responding is a process in which two or more events are verbally related along some dimension such as “same as,” “bigger than,” or “weaker than.” From this framework, the content of cognitions (“I’m going to have a panic attack”) is less important than the relating that an individual does with those cognitions (i.e., “I’m going to have a panic attack” EQUALS “I need to get out of here.”). In fact, direct attempts to change the content of cognitions (e.g., think about a soothing scene instead of “I’m going to have a panic attack”) may inadvertently associate the new thoughts (the soothing scene) with other unwanted thoughts (“I need to get out of here”). Instead, it may be more effective to alter the function of the thought/verbal behavior (“I’m going to have a panic attack”) rather than the form (or content of the thought). Numerous experimental studies have illustrated how altering the function of a thought through changing the response to the thought is beneficial in reducing distress (Healy et al., 2008; Levitt, Brown, Orsillo, & Barlow, 2004; Masuda, Hayes, Sackett, & Twohig, 2004). Accumulating research also suggests that relational responding has characteristics of an operant (Barnes-Holmes, Barnes-Holmes, Smeets, Strand, & Friman, 2004; Healy, Barnes-Holmes, & Smeets, 2000), and as such, traditional behavioral principles can apply to this behavior of responding relationally. Thus, as an operant, relational responding can be reinforced, punished, or extinguished in ways similar to other behaviors.

Complicating matters, humans appear to engage in derived relational responding, in which relational responding occurs with events that have not been trained directly and are not formally related. Events that are not physically present or aversive can become psychologically present and acquire aversive functions through relational responding. That is, not only can actual events cause pain, but self-reports of such events can also cause pain. For example, someone with clinical levels of worry may experience anxiety both in the presence of a stressor and while simply talking about a potential, future stressor. An RFT perspective suggests that a process akin to stimulus generalization can occur across verbal events via the transformation of stimulus functions, thus expanding the number of contexts that generate anxiety and anxiety responses quite quickly. As is the case in learning overt behavior, it may be difficult to unlearn relational responding. In fact, due to the transfer of stimulus functions, the relational network may become so extensive that it would be difficult (if not impossible) to develop new learning for every relation. As a result, even when responses are extinguished in one context, they are likely to reemerge in others (Garcia-Gutierrez & Rosas, 2003). In this way, the verbal context and the behavior of relational responding can lead to decreased behavioral flexibility.

Verbal contexts may also foster inflexible repertoires through rule governance. Whereas relational responding can be characterized as an operant, rule governance can be described as a form of stimulus control that can lead to greater avoidance behavior. As Hayes and Wilson (2003) explain, when human language dominates, people behave more in response to evaluative language than to actual contingencies. For example, parents may worry about and respond to imagined potential health hazards that their child encounters at the playground, instead of the actual circumstances related to the playground, and refuse to let their child play outside. We notice that behavioral flexibility decreases when verbal behavior interferes with contacting actual contingencies, such that individuals learn to respond to verbally constructed negative futures and pasts and their constructed contingencies (Walser & Hayes, 1998). Building on the functional model of worry in GAD, the increased feeling of control in response to the verbal behavior of worry may prevent the individual from feeling the natural anxiety over lack of control and the actual consequences (that they can tolerate the anxiety). Instead, this individual may respond to a verbally constructed future such as “I can’t tolerate the stress or anxiety about this situation and my lack of control over it” with increased verbal behavior of worry, resulting in an increased sense of control and decrease stress, creating an inflexible pattern. A key feature of rule-governed behavior is that it is insensitive to changing contingencies (Doll, Jacobs, Sanfey, & Frank, 2009; Lippman, 1994; Wulfert, Greenway, Farkas, Hayes, & Dougher, 1994)—a characteristic that also has been described in the emotion regulation and behavioral flexibility literature. Rule governance can also be established quickly. Evidence from instruction-based learning has demonstrated that the presentation of a stimulus can result in the automatic activation of a response that was established with that stimulus via instruction, even when the stimulus-response pairing was not previously executed (Liefooghe, De Houwer, & Wenke, 2013; Liefooghe, Wenke, & De Houwer, 2012; Meiran, Pereg, Kessler, Cole, & Braver, 2015). These findings suggest that verbal instructions can create associations that are almost reflexive in nature, and are strengthened with practice (Wenke, De Houwer, De Winne, & Liefooghe, 2015), such as the association between the presence of a stressor and the verbal behavior of worry. Rule governance also can be illustrated in how some people respond to their anxiety. For example, one can have the thought (or rule), “I must not feel anxious,” which can then itself develop stimulus properties that elicit a conditioned response of anxiety. Rather than contacting the actual contingencies, which could in theory include negative consequences (e.g., “taking the time to relax and deep breathe made me late for class and increased my anxiety overall”), people may learn to focus even more on the rule (e.g., “I must not feel anxious”) and their imagined consequences.

Rigid use of rules aimed at controlling or avoiding private experiences (i.e., thoughts, feelings, cravings, etc.) can be problematic. From a logical standpoint, it can be shown how rules that specify controlling private experience can lead to continued avoidance. First, such rules can paradoxically increase the likelihood of experiencing the aversive functions of the avoided event. For example, an individual may employ the rigid rule “I can’t deliver a speech in front of class” to avoid the naturally occurring anxiety that speaking in class may invoke. Repeated employment of this rule to avoid anxiety may generalize the feared stimuli of “giving a speech in class” to other stimuli such as answering a question in class, speaking in front of others, or engaging with strangers at all. Thus, the feared stimulus of “giving a speech in class” has expanded to include multiple stimuli to reduce the perceived threat of anxiety. According to this analysis, avoidance rules can foster more and more relations between neutral stimuli and a feared stimulus, thus increasing thoughts of that stimulus rather than decreasing them. Furthermore, to evaluate whether or not “think about something else” is effective at decreasing thoughts of a feared stimulus, one must necessarily think about that stimulus (Wilson & Hayes, 2000). Thus, rule-governed behavior, especially when under aversive control, has been shown to display inflexibility.

Implications of a Contextual Behavioral Science Model

We suggest that behavioral flexibility may be characterized better as a functional outcome of negative reinforcement and the verbal context. Behavioral flexibility can manifest when overt and verbal behaviors (including relational responding) are reinforced or rule-governed. Rather than defining behavioral flexibility as a new construct and developing new assessments, researchers could consider this CBS understanding of behavioral flexibility as a functional outcome, and that measurement might be better focused on capturing negative reinforcement, rule governance, and relational responding rather than behavioral flexibility per se.

From a CBS perspective, it is not useful to conceptualize behavioral flexibility as “adaptive” or “maladaptive” but rather as a functional outcome that occurs when an individual responds effectively to changing contexts. While self-report measures are efficient research tools, efforts to measure behavioral flexibility through self-report assessments have been problematic in that they encourage an individual difference interpretation and often neglect consideration of the functional influence of particular behaviors in given contexts. Such interpretations often lead to conclusions that a person is “behaviorally flexible” rather than a person uses a particular behavioral repertoire flexibly across contexts. In cases where researchers must rely on self-report measures, researchers could endeavor to include contextual and functional assessments. For example, when examining a particular behavior (e.g., an emotion regulation strategy), researchers should also assess the situation in which the behavior occurred, including environmental and verbal antecedents and consequences. That is, the current framework suggests that it is not simply the behavior-in-context, but rather the behavior-and-context that is the unit of analysis. Furthermore, from this perspective, behavioral flexibility should be interpreted as a functional outcome versus as a mechanism through which other outcomes (e.g., reduced anxiety) are achieved.

Experimental research should attempt to directly test the model described in this article by examining whether anxiety outcomes vary after controlled manipulations that target CBS factors (negative reinforcement, rule governance, and relational responding) and/or after manipulations that target behavioral flexibility directly. Furthermore, while we propose that behavioral flexibility is a functional outcome rather than a cause, it is possible that low behavioral flexibility facilitates a positive feedback loop that ultimately contributes to greater psychopathology. Longitudinal research examining how these processes relate to each other over time may shed light on these possible dynamic relationships.

Researchers could also include more modern assessments of verbal behavior and the verbal context, such as the Implicit Relational Assessment Procedure (IRAP; Vahey, Barnes-Holmes, Barnes-Holmes, & Stewart, 2009), which has demonstrated good effect sizes in clinical populations (Vahey, Nicholson, & Barnes-Holmes, 2015). This type of assessment could be used in conjunction with other suggestions from researchers examining behavioral flexibility; for example, Aldao and Nolen-Hoeksema (2012b) proposed including experimental designs to examine emotion regulation that assess multiple domains of emotion, including subjective, behavioral, and physiological domains. To these suggestions, we would add that it would be useful to examine the social and verbal context, with an eye toward the interaction of behavior and context (e.g., Coan & Maresh, 2014). While it can be challenging to capture this larger context and associated functional processes, such as negative reinforcement, rule governance, and relational responding, we believe that examining this larger unit of analysis has the potential to yield a better understanding of behavioral flexibility relative to existing measures.

There are important clinical implications to consider from this CBS perspective. Models that identify behavioral flexibility as a mechanism or individual trait seem to suggest that interventions should directly target behavioral flexibility to achieve particular outcomes (e.g., reduced anxiety symptoms). That is, increasing response variability or increasing the number of potential skills an individual has in their arsenal should lead to less anxiety. From a CBS perspective, interventions that target rule governance or negative reinforcement processes will lead to greater behavioral flexibility within and across contexts. Exposure-based interventions have long been acknowledged as efficacious treatments for anxiety-related disorders. Exposure-based treatments disrupt the negative reinforcement behavioral loops associated with many anxiety disorders. Acceptance and mindfulness-based interventions, such as acceptance and commitment therapy (ACT; Hayes, Strosahl, & Wilson, 1999, 2011), can function to both increase opportunities for exposure, alter the verbal context that functions to reinforce problematic verbal behavior, and increases awareness of the actual (versus perceived) environmental context to identify potential positive reinforcers.

Conclusion

In summary, converging lines of literature indicate that the use of adaptive and maladaptive emotion regulation strategies may not be as important as behavioral flexibility and the importance of context in the use of these strategies when considering their relationship with psychopathology. The challenges present in defining, investigating, and interpreting these constructs in relation to psychological outcomes have likely limited our advancement in understanding these relationships. We propose that considering a CBS perspective may provide a more productive analysis of these processes. Barnes-Holmes, Hussey, McEnteggart, Barnes-Holmes, and Foody (2015) similarly commented that “middle-level constructs,” including behavioral flexibility, may be better conceptualized as outcomes, because they do little to illustrate functional processes, which would have more direct implications for interventions. A CBS approach may explain the equivocal findings regarding the relationships between adaptive and maladaptive emotion regulation strategies and lead to a more productive examination of these processes.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Kathleen M. Palm Reed, PhD, is the associate director of clinical training and an associate professor at Clark University in Worcester, Massachusetts. She is the author or coauthor of over 40 articles or book chapters, and has been the principal investigator or co-investigator on four federally funded grants focusing on issues related to the prevention of and interventions for substance use disorders, posttraumatic stress disorder, and sexual and dating violence.

Amy Y. Cameron, PhD, is a psychologist in the Trauma Recovery Services Clinic at the Providence VAMC and an assistant professor in the Department of Psychiatry and Human Behavior at the Alpert Medical School of Brown University. She has received funding from the American Foundation for Suicide Prevention and has authored numerous papers and book chapters on issues surrounding psychopathology, with current work focusing on treatment development for Posttraumatic Stress Disorder in Veterans.

Victoria E. Ameral, MA, is a doctoral candidate at Clark University. Her clinical and research interests focus on contextual behavioral approaches to understanding and treating substance use and co-occurring disorders.

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