The role of associative fear and avoidance learning in anxiety disorders: Gaps and directions for future research

Highlights

• Review demonstrating the role of fear acquisition, generalization, extinction, return, and avoidance learning for anxiety disorders.

• Basic research needs to target distinct mechanism such as extinction (generalization) and avoidance.

• Basic research needs to target individual differences pertinent to anxiety disorders such as comorbid depression, age, and sex.

• Basic research needs to target paradigms involving ambiguity and conflict.

• Clinical translation studies are needed to validate basic research strategies aiming at treatment optimization.

Abstract

Anxiety disorders are the most common mental disorders and are often chronic and disabling. Although exposure-based treatments are effective, a substantial number of individuals fail to fully remit or experience a return of symptoms after treatment. Understanding the critical processes underlying the development and treatment of anxiety disorders will help identify individuals at risk and optimize treatments. Aversive associative learning offers explanatory pathways through which fear and anxiety emerge, spread, persist, and resurge. This narrative review examines the advances made in our understanding of associative fear and avoidance learning in anxiety disorders. Overall, the extant literature supports a key role of aversive associative learning in the development and treatment of anxiety disorders. However, research targeting specific mechanisms such as extinction generalization and avoidance, the fragility of extinction, and moderating influences of individual differences pertinent to anxiety disorders (e.g., age, sex, depression) is needed. We discuss the need for more ecological valid and complex paradigms to model ambiguity and conflict as well as for clinical translation studies to optimize treatment.

Introduction

Aversive associative learning has played a major role in explaining the development and treatment of anxiety disorders as well as related disorders such as posttraumatic stress disorder (PTSD) or obsessive-compulsive disorder (OCD). However, despite the significant advances made, there are critical processes involved in the emergence, maintenance, and treatment of these disorders that are not understood. Such areas, for example, include sex differences in the prevalence of anxiety disorders, developmental pathways, the effect of comorbidity with depression, the role of avoidance, and ways of overcoming the fragility of extinction and enhancing the long-term effects of exposure-based treatments. The present review critically examines advances made to date, the gaps in the existing literature, and directions for future research, with the ultimate aim to improve prevention efforts and treatment effectiveness.

Fear, anxiety, and avoidance behavior are evolutionarily adaptive processes that are commonly experienced in everyday life. However, individuals with anxiety disorders are excessively fearful, anxious, or avoidant of perceived threats in their environment (e.g., social situations, unfamiliar locations) or within themselves (e.g., unusual bodily sensations, thoughts and mental images). The response to these stimuli is out of proportion to the actual threat or danger posed and often generalizes to a wide range of related stimuli. Excessive fear and anxiety in individuals with anxiety disorders is typically accompanied by excessive avoidance behaviors, which range from complete refusal to enter fear-relevant situations to more subtle reliance on objects, behaviors, or people to cope with subjective expectations of threat.

Anxiety disorders as a group represent the most common class of mental disorders (Kessler et al., 2010). A systematic review of prevalence studies across 44 countries estimates the current global prevalence at 7.3% (95% CI 4.8–10.9%), suggesting that about one in 14 people around the world at any given time are affected by a clinically significant anxiety disorder (Baxter et al., 2013). Furthermore, about one in nine (11.6%, 95% CI 7.6–17.7%) will experience an anxiety disorder in a given year (Baxter et al., 2013). Worldwide, middle-aged adults (35–54 years) are 20% more likely to have an anxiety disorder compared to older adults (55 years plus; Baxter et al., 2013). For specific anxiety disorders, most separation anxiety disorders and specific phobias develop in childhood and most social anxiety disorders in adolescence or early adulthood. The onset for panic disorder, agoraphobia, and generalized anxiety disorder is typically later and with greater dispersion (Kessler et al., 2010). Prospective studies of children and adolescents often yield even lower ages of onset (Beesdo-Baum and Knappe, 2012). Moreover, women are twice as likely to have an anxiety disorder as men (McLean et al., 2011), but sex differences remain poorly understood. These epidemiological findings highlight the importance to account for individual differences such as age or sex in the etiology of anxiety disorders. Finally, anxiety disorders frequently co-occur with depression (Kessler et al., 2005). In fact, anxiety disorders are one of the strongest known risk factors for and precursors of depression and linked to a more malignant course of depression (Beesdo et al., 2007; Meier et al., 2015). Models of anxiety disorders and their treatment should thus take into account the effects of co-occurring depression.

If untreated, anxiety disorders tend to be chronic, with a waxing and waning pattern of recurrence across the lifetime (Bruce et al., 2005; Kessler et al., 2010). Anxiety disorders are not only persistent, but also pervasive, with fear generalizing to broad array of stimuli (Dymond et al., 2015). The breadth of fear and avoidance contributes to functional impairments, with anxiety disorders being the sixth leading cause of disability in high and low income countries (Baxter et al., 2014). Impairment and disability may be greater for women than men with anxiety disorders (McLean et al., 2011). Etiological models therefore must be able to account for their persistence and spread.

Given the high prevalence, burden, and chronicity of anxiety disorders, the development and improvement of effective treatments is vital. Several pharmacological interventions are approved for anxiety disorders and demonstrate pre-to-post effectiveness (Bandelow et al., 2015), but many individuals do not remit, are unwilling to tolerate side effects, and/or prefer non-medication treatment options. Cognitive behavioral therapies for anxiety disorders, most of which incorporate exposure-based interventions, are highly effective. For example, relative to waitlist or passive control conditions, the effect size in adult samples is medium to large (Hedges g = 0.73; 95% CI = 0.56–0.90; Hofmann and Smits, 2008). Corresponding effects for childhood samples are large as well (SMD = −0.98; 95% CI = −1.21 to 0.74; James et al., 2013) and medium to large for late life samples (Hedges g = −0.66, 95% CI = −0.94 to −0.38; Gould et al., 2012). Direct comparisons to active treatment conditions are more limited but findings indicate benefits with medium effect sizes for exposure-based cognitive-behavioral therapies over other types of therapies such as psychodynamic treatments (Cohen’s d = 0.43; 95% CI = 0.14–.72; Tolin, 2010). As a result, exposure-based cognitive-behavioral therapies are a first line treatment in many international treatment guidelines for anxiety disorders.

Despite the high effectiveness of exposure-based cognitive-behavioral therapies, a number of essential shortcomings have been identified. First, a substantial number of individuals (11–27%) refuse to begin cognitive behavioral therapies when offered (Fernandez et al., 2015; Garcia-Palacios et al., 2007). Second, another substantial number (15–52%) drops out after beginning treatment (Fernandez et al., 2015; Haby et al., 2006). Third, the rate of clinically significant response to cognitive behavioral treatments is much less than ideal, averaging 50–60% (Loerinc et al., 2015; Rapee et al., 2009). And finally, individuals may exhibit a return of fear or full relapse following successful treatment (Craske and Mystkowski, 1999; Ginsburg et al., 2014). Short-term and long-term treatment effectiveness is likely to be improved by a better understanding of the critical pathways through which anxiety disorders emerge, spread and persist, and the moderating effects of age, sex, and comorbidity with depression. With this information at hand, we will be positioned to develop more targeted prevention and treatment efforts.

Associative learning refers to the process by which relationships among various stimuli, behaviors, and outcomes are learned (Rescorla, 1988). This learning involves representations and memories necessary for adapting to our environment and guides our understanding of what is threatening and what is safe; what is rewarding and what is not; when to approach and when to avoid; and when to repeat an action and when not to. For anxiety disorders, aversive associative learning (i.e., associative learning related to aversive stimuli or outcomes) is assumed to be a core underlying learning process. Aversive associative learning comprises different processes including learning regarding predictive relationships among stimuli and an aversive outcome (aversive Pavlovian learning), as well as associations among a response and an outcome (aversive instrumental or operant learning such as avoidance learning). For anxiety disorders, the validity of aversive associative learning as an underlying learning process and experimental model has been well documented and helps explain how maladaptive fear, anxiety, and avoidance are learned and maintained (Arnaudova et al., 2017; Krypotos et al., 2015; Scheveneels et al., 2016; Vervliet and Raes, 2013).

Most current research focuses on the role of aversive Pavlovian learning. Experimental procedures of aversive Pavlovian learning are known as fear or threat conditioning, which are overarching terms including procedures of fear acquisition, extinction, and return of fear (see Lonsdorf et al., 2017). In Pavlovian fear acquisition, a former neutral stimulus elicits a fear response due to its predictive relationship with an innately aversive stimulus (the aversive unconditional stimulus or US). Likewise, the reduction of conditioned fear when the feared stimulus is presented in the absence of an aversive stimulus (i.e., during fear extinction training) is seen as laboratory proxy for fear reduction during exposure treatment. Combined, these similarities between experimental and clinical phenomena provide face validity for the experimental model of fear conditioning (Scheveneels et al., 2016; Vervliet and Raes, 2013). The underlying associative learning processes are also assumed to be crucial mechanisms in the etiology of anxiety disorders (offering construct validity). For example, deficits in aversive Pavlovian learning predict both the emergence of post-traumatic stress disorder (e.g., Lommen et al., 2013), and the persistence of symptoms (Sijbrandij et al., 2013). Moreover, changes in aversive Pavlovian learning, and its neural substrates, following exposure therapy co-vary with symptom improvement (Helpman et al., 2016; Kircher et al., 2013; Lueken et al., 2013). Recent studies also provided first evidence that individual differences in aversive Pavlovian learning predict responses to exposure-based treatments (Ball et al., 2017; Forcadell et al., 2017; Waters and Pine, 2016). Although additional processes contribute to successful exposure therapy, these results offer predictive validity for aversive associative learning as one underlying mechanism of exposure.

Finally, individuals with anxiety disorders show distinct deficits in aversive Pavlovian learning models compared to healthy controls (diagnostic validity; e.g., Duits et al., 2015; Jovanovic et al., 2012; Lissek et al., 2005). Whereas this research mostly targeted the validity of aversive Pavlovian learning for anxiety disorders, research on the validity of avoidance learning, which also involves instrumental and other learning processes (see 5.), is still scarce (see also Scheveneels et al., 2016; Vervliet and Raes, 2013).

Treatments for anxiety disorders, beginning with Wolpe’s method of systematic desensitization (Wolpe, 1958) and extending to current day models of exposure therapy, were directly derived from associative learning models, in particular, the processes of fear extinction. However, treatment development has been stymied by lack of translation of advances in research on fear and avoidance learning to treatment and by the failure of basic science to fully model the complexity and essential features of anxiety disorders and naturalistic treatment conditions (see Craske et al., 2014, 2008a; Pittig et al., 2016; Richter et al., 2017). Thus, although aversive associative learning is perhaps one of the best examples of a science-driven model for understanding and treating psychopathology (Holmes et al., 2014), there is a strong need for more reciprocal and iterative investigations involving both basic and clinical science to advance our models and methods of treating anxiety disorders and related conditions (see also Richter et al., 2017).

Recent reviews on aversive associative learning focused on distinct mechanisms such as fear acquisition, generalization, extinction, and return of fear (e.g., Dymond et al., 2015; Haaker et al., 2014; Hermans et al., 2006; Vervliet et al., 2013a, 2013b), their neural substrates (e.g., Etkin and Wager, 2007; Fullana et al., 2016; Greco and Liberzon, 2016; LeDoux and Pine, 2016; Maren, 2001; Maren and Holmes, 2016; Mechias et al., 2010; Medina et al., 2002; Milad and Quirk, 2012; Sehlmeyer et al., 2009), and the general role of aversive Pavlovian learning for anxiety disorders (e.g., Craske et al., 2014, 2006; Duits et al., 2015; Kindt, 2014; Lissek et al., 2005; Mineka and Zinbarg, 2006; Pittig et al., 2016). In addition, recent reviews also focused on methodological issues of the corresponding experimental models (e.g., Beckers et al., 2013; Lonsdorf et al., 2017) and general overviews on individuals differences within these models (e.g., Lonsdorf and Merz, 2017). Few of these reviews have focused on clinical implications and most exclusively focused on aversive Pavlovian learning. Although avoidance is also a crucial mechanism for anxiety disorders, comprehensive overviews of avoidance learning are scarce.

To further advance our understanding of the involvement of aversive associative learning processes for anxiety and related disorders, this narrative review focused on the clinical relevance of associative learning processes involved in the acquisition, generalization, persistence, and return of fear and avoidance for the development, prevention, and treatment of anxiety and related disorders (see Fig. 1). To this regard, the present review aimed at:

• Reviewing extant evidence for alterations in distinct mechanisms of aversive associative learning in individuals with anxiety disorders or at-risk for anxiety disorders.

• Highlighting the impact of individual differences that are pertinent to the etiology and treatment of anxiety disorders, especially sex and age differences, developmental issues, and comorbid symptoms of depression.

• Providing an overview of the emerging research on avoidance learning and its clinical relevance.

In the following sections, we briefly describe associative learning processes and corresponding experimental models involved in the acquisition, generalization, persistence, and return of fear and avoidance. For each process, we then address the question whether anxious individuals show imbalances in the specific process and highlight the individual differences pertinent to anxiety disorders (i.e., sex, age, comorbid depression). In addition, we highlight methodological issues (“Paradigms”) and important gaps and future research directions relevant to each mechanism. In addition to the DSM-5 anxiety disorders (APA, 2013), the review also considers OCD and PTSD as disorders that have a strong fear-based component and associative learning theory-informed etiological and treatment models.