The Appraisal Bias Model of Cognitive Vulnerability to Depression

Abstract

Models of cognitive vulnerability claim that depressive symptoms arise as a result of an interaction between negative affect and cognitive reactions, in the form of dysfunctional attitudes and negative inferential style. We present a model that complements this approach by focusing on the appraisal processes that elicit and differentiate everyday episodes of emotional experience, arguing that individual differences in appraisal patterns can foster negative emotional experiences related to depression (e.g., sadness and despair). In particular, dispositional appraisal biases facilitating the elicitation of these emotions more frequently and more intensely. This, in turn, is likely to have a negative influence on cognitive processing and emotion regulation in general.

Keywords

appraisal bias cognitive vulnerability depression despair sadness

Several decades ago, the cognitive revolution provided the impetus to integrate the theoretical and empirical developments in the cognitive sciences into the fields of clinical psychology and psychiatry. Although this led to impressive advances with respect to new theoretical models, new studies, and new therapy techniques, further progress can be made by integrating cognitive approaches to emotion (Moors, Ellsworth, Scherer, & Frijda, 2013) into the landscape of psychopathology. So far emotion and cognition have been considered separate entities, and most cognitive models of psychopathology focus exclusively on cognitive reactions to emotional phenomena. In contrast, the approach advocated here fully integrates cognition with the emotional processes that lead to affective disorders. Emphasizing the relevance of appraisal theories of emotion (Ellsworth & Scherer, 2003; Roseman & Smith, 2001) for psychopathology, we argue that cognition plays a central role not only in the regulation of emotional processes (e.g., Aldao, Nolen-Hoeksema, & Schweizer, 2010; Gross & Muñoz, 1995), but also in the generation of the affective states that fail to be regulated. Although this article focuses on the analysis of a relatively specific diagnostic category (depression) such an approach is compatible with the growing interest in transdiagnostic approaches to further the understanding of the mechanisms underlying psychopathology including the frequent occurrence of comorbidity (Sanislow et al., 2010; see also Watkins, 2015), as cognitive appraisal is at the root of emotion processes in general.

This article builds on previous theoretical work on the relationship between appraisal bias and affective disorders (see Kaiser & Scherer, 1998; Roseman & Kaiser, 2001; Scherer, 2015; Scherer & Brosch, 2009). More specifically, our goal is to identify and elaborate on the appraisal biases associated with depression, in line with the latest theoretical development in emotion research, in particular cognitive approaches to emotions (Moors et al., 2013). We then provide a brief review of the literature on cognitive biases involved in depression and compare the appraisal bias model (ABM) with earlier models of cognitive vulnerability to depression.

Cognitive Appraisal and Appraisal Bias

Since the pioneering contributions of Arnold (1960) and Lazarus (1968), the individual’s cognitive evaluation of the situations encountered is recognized as a major determinant in the psychobiological responses and action tendencies shown in that situation. Cognitive evaluation, more commonly termed cognitive appraisal in the psychological literature, is considered as the central factor in the generation of stress responses (Lazarus & Folkman, 1984), but also in the unfolding of emotional experience (see chapters in Scherer, Schorr, & Johnstone, 2001). Cognitive appraisal can be seen as an adaptive psychological mechanism that allows organisms to optimize responses to a particular situation by decoupling stimulus and response (Scherer, 1984).

Cognitive appraisal is particularly adaptive in an environment that fluctuates continuously, as it allows organisms to weigh the different aspects of a situation and to provide the response that is most appropriate to the context, given an organism’s capacities for response (Scherer, 2001). Such flexibility implies that the organism has a number of response patterns available and that these responses turned out to be effective in the past. The flexibility afforded by appraisal patterns may also be reflected in how appraisal drives the different components of emotion to fine-tune an individual’s response to the specificities of a situation (Kuppens, 2013). Within the remit of this special section’s central topic on normal and abnormal emotions, our approach emphasizes the need to study the range of appraisal patterns related to emotional experience to provide a “background map” to locate the different cognitive appraisal styles associated with psychopathology.

Once appraisal is recognized as an important mechanism that allows individuals to flexibly adapt to different situations, we still need to define what we mean by bias. Our use of the term bias does not directly address the “accuracy” of cognitive processing as this obviously depends on the respective context. Rather, it denotes a disposition to evaluate situations in a way that consistently produces similar emotional responses independently of the context (see also Mathews & MacLeod, 2005), which tends to be caused by privileging particular appraisal alternatives such as external or internal attribution of causality (Harvey, Town, & Yarkin, 1981). Two important aspects have to be considered in assessing appraisal bias: context-related flexibility, and extent or extremeness. Flexibility refers to the ability to take into account the different nuances of a situation, for example, by considering many different aspects of a situation and their interaction. Flexible appraisal patterns differ from situation to situation to reflect small differences between them, despite apparent similarities. Nonflexible, rigid appraisal patterns do not allow to recognize small, but important, differences between situations resulting in similar evaluation outcomes for different situations. Such rigidity in appraisal structure leads an individual to consistently experience the same emotion in different situations that would, if appraised more flexibly, result in more varied emotional responses and increase the potential for adaptation.

The second factor to consider in appraisal bias is the extent, magnitude, or extremeness of the evaluation. The extent of appraisal refers to the tendency to make moderate to extreme cognitive evaluations in a situation. For example, one might expect an event to have greater negative consequences than it normally would, or lead to serious underestimation of one’s coping abilities.

Making extremely strong appraisals may lead to emotional reactions that are disproportionate to the demands of a situation, with negative consequences for the individual such as depletion of psychophysiological resources or aversive reactions from the social environment (e.g., ostracism). Appraisal variables have been shown to positively correlate with emotion intensity (Ellsworth & Smith, 1988), suggesting that the magnitude of the emotional reaction to an event may depend on the way the event is evaluated. In turn, emotional intensity presents a reciprocal relationship with emotion regulation (Sonnemans & Frijda, 1995): While more intense emotion requires increased regulation efforts, regulation efforts have the goal to decrease emotion intensity. Because intense emotions place a greater demand on regulation efforts than less intense emotions, they are more likely to lead to emotion-related disturbances, like depression, if regulation is impaired. Some authors have also suggested that the relationship between intense emotion and depressive symptoms may be due to the fact that intensity of affect prevents the use of more efficient coping strategies (Flett, Blankstein, & Obertynski, 1996). Therefore, strong appraisals may result in intense emotional responses that are more difficult to regulate, which could ultimately lead to psychopathology.

Conversely, making appraisals of extremely low magnitudes may lead to a failure to detect and emotionally respond to challenges, threats, and opportunities that are inherent to a situation. The emotion context-insensitivity hypothesis (Rottenberg, Gross, & Gotlib, 2005) indeed proposed that depressed individuals typically show low emotional reactivity to a wide range of environmental events. In a related manner, the ABM suggests that making appraisals of low magnitudes may be part of a person’s cognitive style that characterizes vulnerability to depression. In some cases, the absence of emotional response results in the inability to change a situation to one’s own advantage, and to an aggravation of negative circumstances. In sum, the ABM suggests that appraisal bias can jeopardize adaptation by making individuals oversensitive or insensitive to events. This leads to the production of extremely intense emotional responses or to the absence of a response when one is needed.

Appraisal Bias, Trait Affect, and Depression

Kaiser and Scherer (1998) argued for the utility of applying models of normal emotions to a variety of clinically salient affect disturbances, demonstrating how affective disorders can be conceptualized as malfunctions of intraindividual and interindividual regulation. The former involves inadequate appraisal of situations and events, as well as dissociation of the relationships between the different emotion components; the latter comprises inappropriate expression of affect and major deficiencies in the interpersonal adjustment of affect in social interaction. Roseman and Kaiser (2001) extended the argument, showing that specifying the patterns of appraisal that give rise to a variety of emotions can provide insights into how maladaptive emotional responses are generated. Given the wide range of genetic variation and developmental experiences that characterize individuals, we can expect stable individual differences in the ways situations are evaluated. These individual differences in cognitive evaluations may be at the origin of individual differences in trait affect (Scherer & Brosch, 2009), that is, the stable dispositions people have to show a particular emotion rather than another in response to particular social or environmental events (Revelle, 1995). The postulated relationship between cognitive appraisal and trait affect implies that the former is an important factor in the vulnerability to emotional disorders (Roseman & Kaiser, 2001; Scherer & Brosch, 2009).

The appraisal bias associated with particular affective disorders is likely to reflect the appraisal patterns that give rise to the normal emotions associated with the respective disorder (see Table 2 in Scherer & Brosch, 2009, p. 275 [reproduced in Supplemental Material]). For example, since the central emotion in depression is sadness, one should expect bias in the appraisal pattern that is typical of sadness. Different models have been proposed to describe appraisal–emotion relations. For example, Roseman and Kaiser (2001) argued that sadness is generated by the following appraisal pattern: motive inconsistency, appetitive motivation, certainty, and low-control potential. According to this model, perceiving events as being inconsistent with one’s motives (e.g., unwanted events), as being related to a goal or a desire to get more of something rewarding, and as having outcomes that are certain, as well as thinking that nothing can be done to change the event, directly contributes to the emotion of sadness and, potentially, to depressive symptoms. Similarly, Scherer and Brosch (2009) proposed that the propensity to experience sadness, also called trait sadness, is based on the motivation to develop strong attachment to people (or material property) and on the cognitive tendency to evaluate self-esteem as low and to underestimate control, coping, and adjustment potential.

The ABM that we develop here is based on the appraisal sequence of the component process model (Scherer, 2001, 2009), which postulates four major categories expected to unfold in this order: (a) relevance (intrinsic pleasantness and goal relevance); (b) implication (goal conduciveness, discrepancy from expectation, outcome probability, causal attribution, and urgency); (c) coping potential (estimation of control and power); and (d) normative significance (estimation of whether the event is compatible with internal and external standards). Scherer (2001) predicts that sadness and despair are associated with the specific patterns of cognitive appraisal presented in Table 1.

Table 1.

Predicted appraisal patterns for sadness and despair.

Appraisal domains	Appraisal criteria	Sadness	Despair
Relevance	Novelty
	Suddenness	Low	High
	Familiarity	Low	Very low
	Predictability	Open	Low
	Intrinsic pleasantness	Open	Open
	Goal relevance	High	High
Implication	Cause: agent	Open	Other/natural
	Cause: motive	Chance/negligence	Chance/negligence
	Outcome probability	Very high	Very high
	Discrepancy from expectation	Open	Dissonant
	Goal conduciveness	Obstruct	Obstruct
	Urgency	Low	High
Coping	Control	Very low	Very low
	Power	Very low	Very low
	Adjustment	Medium	Very low
Normative significance	Internal standards	Open	Open
	External standards	Open	Open

Note. Adapted from Scherer (2001).

We suggest that when such biased appraisals are consistently performed in a large number of situations (i.e., many different situations are evaluated in this inflexible way), people experience sadness or despair more frequently and find themselves at higher risk for developing depressive symptoms. The assumption is that there is a cumulative effect of repeatedly experiencing sadness or despair that produces the risk for the development of affective disturbance. The absence of flexibility in appraisal patterns leads to a lack of diversity in emotional responding across these situations. In addition, the lack of flexibility characteristic of appraisal bias should lead to a failure to experience, in other situations, emotions that could have the power to relieve an individual from depressive symptoms (e.g., positive emotion). Finally, when the evaluation on particular appraisal criteria is extremely strong (high or low, depending on the appraisal criteria), people are likely to experience more intense sadness or despair and, as a result of the emotion being more intense, experience more difficulties in regulating the emotion. Our aim is therefore to acquire knowledge about the range of variation that can be expected, in the absence of psychological pain (i.e., in what is considered “normal” emotional experience), with respect to the connections between appraisal patterns and the duration and intensity of emotion (see also Scherer, 2015).

Our approach to emotional disorders follows the idea that biases in appraisal do not always represent serious errors of evaluations, but suboptimal judgments. Cognitive appraisal is functional in that it provides a way for the individual to consider different aspects of a situation and to respond adaptively. This provision, however, should not imply that there is, in absolute terms and for every situation, a correct response to adopt. For example, among the circumstances that determine whether a response is adaptive, or not, are the actual capabilities of an individual to deal with the situation. In some situations, the individual may have the capacities to cope and in other situations he or she may not. Whether a cognitive evaluation is appropriate or optimal will therefore depend on an interaction between the actual coping capabilities and the situation. Consequently, our approach focuses on how particular cognitive evaluations fit the situation in which people find themselves and the consequences of these evaluations in terms of adjustment, suggesting that appraisal biases endanger the appropriate consideration of all pertinent factors.

Cognitive Models of Vulnerability to Depression

Depression is classified in different diagnostic systems (Diagnostic and Statistical Manual of Mental Disorders; International Classification of Diseases) as an emotional or psycho-affective disorder. It involves the loss of interest or pleasure in everyday activities, low energy, and negative thoughts about the self, about life, and about the future. Depression entails a cohort of symptoms such as sleep disturbances; loss of appetite; fatigue; loss of concentration; feelings of guilt, worthlessness, and self-blame; and thoughts of death. One of the key symptoms in depression is persistent sadness and low mood (see Bondolfi, Mazzola, & Arciero, 2015). Emotional experiences such as sadness, deep sorrow, and despair are core symptoms of depression.

Cognitive models of emotional pathology have flourished in the last 40 years, usually with a range of empirical data to support them (Mathews & MacLeod, 2005). We present here four influential models that describe the relationship between cognitive style and depression: The helplessness model (Abramson, Seligman, & Teasdale, 1978; Seligman, 1975), the hopelessness theory (Abramson, Metalsky, & Alloy, 1989), the response styles theory (Nolen-Hoeksema, 1991), and the differential activation hypothesis (DAH; Teasdale, 1988). We then compare these models with the ABM, emphasizing the similarities and identifying how key differences between the models can be used to build a framework of cognitive vulnerability to depression that integrates the latest development in appraisal theories of emotion.

Helplessness Model of Depression

The central idea of the helplessness model is that when people learn that outcomes are uncontrollable, they tend to develop motivational, cognitive, and emotional deficits (Seligman, 1975). In this model, cognitive processes play a major role because it is the expectation that consequences are not controllable that leads to psychological deficits, rather than the mere exposure to uncontrollable situations. In a reformulation of the helplessness model, Abramson et al. (1978) further elaborate on different types of helplessness (e.g., universal and personal helplessness) and on the concepts of stability and generality of attributions. Stability refers to the time course of helplessness: It is called chronic (or stable) when it is long-lasting or recurrent, but transient when it is short-lived and nonrecurring (Abramson et al., 1978). Generality entails the generalization of helplessness to situations beyond the one in which it first developed, which results in psychological deficits in a wide range of situations. On the other hand, helplessness deficits that occur in a narrow range of situations are characterized as specific. The different combinations among internality/externality, stability/instability, and global/specific dimensions have different implications for the generation and development of depressive symptoms (Abramson et al., 1978).

Hopelessness Theory

The hopelessness theory (Abramson et al., 1989) is an extension of the helplessness model and postulates that depressive symptoms represent the consequences of a chain of events, beginning with the occurrence of negative events. When confronted with these events, individuals make three kinds of inferences: causal attributions, possible consequences, and inferred characteristics about the self. The theory argues that some individuals are more vulnerable to depression because they evaluate events as being the result of stable and global causes (i.e., causes that are enduring and likely to affect many outcomes), as being important and likely to result in other negative consequences, and when they see themselves as being deficient or unworthy (Abramson et al., 1989).

Response Styles Theory

This theory (Nolen-Hoeksema, 1991) postulates that people’s tendency to constantly analyze themselves, their own problems, and their negative feelings—a mental process that has been called depressive rumination—is an important factor in the development and the maintenance of depressive symptoms. Depressive rumination is a stable trait that predisposes an individual to repetitively engage in self-focus. This trait is also involved in the generation of other forms of psychopathology such as anxiety disorder, eating disorder, and substance abuse (Ehring & Watkins, 2008), suggesting that rumination plays a role in psychopathology in general. Rumination is considered a habit of thought (Hertel, 2004; Watkins & Nolen-Hoeksema, 2014) that is triggered automatically, without conscious awareness or voluntary effort. The repetitive focus on upsetting events and on emotional distress may have unconstructive consequences for the unfolding of emotional experience (Watkins, 2008). More specifically, abstract processing of negative information was found to amplify emotional reactivity (Watkins, Moberly, & Moulds, 2008) and to limit access to alternative coping strategies (Watkins & Moulds, 2005), which could lead to aggravation of depressive symptoms.

Rumination itself is not always detrimental, as it can also be constructive when oriented towards reducing the discrepancy between goals and the current state (Martin & Tesser, 1996). In this view, rumination is seen as an adaptive response to unresolved goals. The occurrence of depressive rumination is contingent on sad mood, which is characterized by reduced coping options (Watkins & Nolen-Hoeksema, 2014). Therefore, it appears that the dimension that makes habitual rumination develop into a maladaptive strategy is the repetitive absence of coping strategies, passive responding style, or reduced perceived power in the face of goal-relevant events.

Differential Activation Hypothesis

Inspired by Beck’s (1967) cognitive model, the differential activation hypothesis (DAH; Teasdale, 1988) suggests that vulnerability to severe and persistent depression is related to differences in patterns of thinking that are activated during the depressed state. This suggests that people’s interpretation of their depressed state in particularly negative ways results in the aggravation of that state. The particular cognitive dimensions underlying these interpretations are influenced by the nature of the mental representations in memory. The DAH postulates that vulnerability to depression is characterized by the associations that are made, during early episodes of depression, between negative mood and negative thinking styles. According to the DAH, individual differences in the nature of thinking patterns are activated by depressive mood. In some individuals, these information-processing patterns tend to become more strongly negative and this is what leads to major depressive episodes. It is the interaction between depressive mood and a particular type of cognitive processing that results in the positive feedback loop that maintains and aggravates depression (see also Lau, Segal, & Williams, 2004). This implies that the maintenance of depression can be mostly attributed to a failure in the regulation of depressive or sad mood. The DAH assumes that when these vulnerable patterns of cognitive processing are not established in early instances of depressed moods, depressive symptoms are not maintained and recovery occurs.

Comparison of Cognitive Models With the ABM

The general idea underlying most models of cognitive vulnerability to depression is that dysfunctional attitudes and negative inferential style in response to negative emotional states increase the likelihood that depressive symptoms will occur (Hankin & Abramson, 2001). When people experience negative events, their emotional reactions to these events are amplified by cognitive factors such as attribution style (helplessness and hopelessness models), depressive rumination (response styles theory), or negative mental representations (DAH). The ABM overlaps with earlier theories in that it also postulates that individual differences in information processing account for the vulnerability to experience depression. For example, the ABM and the helplessness and hopelessness models all postulate that incoming information related to an event is processed and influenced by attributional style, which in turn influences subsequent affect and behavior. Like the helplessness and hopelessness models, the ABM postulates that perceived low coping potential is a major determinant in the generation of depression. Nonetheless, a small difference between the ABM and the hopelessness model is that the latter does not necessarily assume that emotions such as sadness and despair are intermediate affective states that occur between the triggering events and depression (Haeffel et al., 2008), whereas the ABM does.

The main difference between the ABM and other models lies in the temporal position—within the flow of events leading from life challenges to depressive symptoms—of the cognitive processes that we focus on. Whereas earlier models emphasize the role of individual differences in information processing after the negative emotional experience is initiated, our model argues that consistent appraisal biases in the way events are processed in the first place increase the tendency to experience episodes of sadness and despair and thus increase the risk of developing clinically relevant depression. In other words, there is a slow build-up of an ever increasing tendency of “sadness orientation,” progressing from normal to pathological. While earlier models of cognitive vulnerability posit that the emotion triggered by negative events influence cognitive processes like attention, memory, and interpretation, the focus of the ABM is on the cognitive responses to events rather than on the cognitive response to the emotional experience that follows such events (see Figure 1). This does not deny the importance of individual differences in cognitive aspects of emotion regulation for the development of depressive symptoms. On the contrary, the ABM can be integrated with the other models, as its focus of research is different in that it emphasizes biased emotion production. Rather than reformulating cognitive vulnerability to depression in a different fashion, the ABM aims at adding a piece to the puzzle of cognitive mechanisms involved in depression and psychopathology in general.

Figure 1.

Comparison between cognitive models of vulnerability to depression (A) and the appraisal bias model of cognitive vulnerability to depression (B).

With the exception of the concept of attribution (as postulated by the hopelessness model), most cognitive models of depression focus on the content of mental representations and on their schematic nature (Segal, 1988), rather than on modes and efficiency of information processing. The ABM more strongly reflects how individual differences in the processing of incoming information may be risk factors for psychopathology; it is less concerned with how the organization of prior knowledge influences emotion regulation. Fiske and Linville (1980) have argued that schematic and attributional types of analyses can be complementary. In this respect, the ABM nicely complements the concept of “cognitive distortions” developed by Beck (1979), as the latter are the products of misinterpretation or misperception of objective reality. Appraisal bias could be considered a theoretical elaboration of the mechanisms leading to cognitive distortions, as it represents a mode of information processing rather than a representational structure with specific content. As such, different forms of appraisal bias may lead to different types of psychopathological symptoms (Kaiser & Scherer, 1998), making our argument compatible with endeavors to understand the common underlying dimensions of mental disorders (as in the transdiagnostic approach, e.g., Watkins, 2015).

One of the strengths of the ABM is that it allows for a number of events, not only explicitly negative ones, to trigger emotions that, if not regulated, may increase the risk to develop to symptoms for depression. Although some events are more objectively negative than others (i.e., events that would cause harm to most people), many everyday events can be interpreted either positively or negatively and therefore constitute potential sources of negative affect, depending on the interpretation that is made by the individual. Consider the following example: Silvia noticed that one of her colleagues takes great pleasure in preparing an e-mail invitation for a dinner she’s organizing at her holiday house this weekend. If Silvia is a very altruistic and empathic person she may well appraise this positively, empathizing with her colleague’s anticipation of the good time she will have. On the other hand, if she tends toward external attribution and self-depreciation, Silvia may interpret the event negatively as she might not be invited, and thus experience sadness as a result. We postulate that a particular appraisal bias will lead individuals to consistently experience negative emotions in the face of a variety of events, even those that are not clearly negative in nature. Felt emotion also influences subsequent cognitive processing that can further aggravate dysphoric mood, ultimately leading to depressive symptoms (Lau et al., 2004). Therefore, appraisal bias in the first interpretation of events may be a determining factor in triggering or reinforcing the feedback loop between dysphoric mood and negative cognitions.

According to the ABM, depressive mood can result from (a) an unregulated abnormally intense emotion following the biased evaluation of an acute event, or (b) chronic exposure to challenging events (such as daily hassles) that are consistently perceived as aversive. In the first case, appraisal bias leads to an emotion so intense that it is detrimental to the cognitive processes involved in emotion regulation. Our model posits that, since appraisal is also involved in the regulation of emotion (e.g. Gross, 1998), appraisal bias can also influence the cognitive component of emotion regulation. Consider the following example: Shortly after coming home from work, Maria receives a phone call from the hospital announcing that her husband was victim of a serious car accident. Though his life is not in danger, it is most likely that Maria’s husband will have to spend the rest of his life in a wheel chair. In this situation, the event may be evaluated as being sudden, not familiar, and unpredictable. The event may also be appraised as highly relevant to Maria’s goals (e.g., her relationship goals) and as being caused by another agent (someone else may have caused the accident). The event could be perceived as uncontrollable and Maria may estimate that she lacks the resources necessary to cope with it. According to the ABM, this appraisal process triggers a number of changes in Maria’s tendencies to act, in her physiological activity, and in her motoric responses. Finally, the changes in these different components are reflected in subjective feelings of an emotional experience that she may label “despair.” If the different evaluations described before are extreme, it is likely that the intensity of the emotion felt by Maria would be high. At this stage, the intense emotion may influence other cognitive processes such as attention, memory, interpretation, and repetitive thoughts, which in turn affect her ability to reappraise the situation in ways that would decrease emotion intensity. This may ultimately lead to depressive symptoms. The latter stages of this chain of events are accounted for by earlier models of cognitive vulnerability, but the first steps, that the intense emotion results from appraisal bias (e.g., underestimation of coping potential) in Maria’s evaluation of the situation is specific to the ABM.

The next example describes a route to depression that does not necessarily include an intense emotional response to an acute stressful event but an accumulation of negative emotional episodes following chronic exposure to life challenges that are consistently evaluated in ways described in Table 1. This would lead to an increase in the frequency of negative emotional episodes that would trigger the feedback loop described in theoretical models of cognitive vulnerability. The example goes as follows: Yvan is the manager of the retail unit in a large telecommunication company and the father of three children. The daily commute through a big city leads him to experience the typical traffic-related annoyances. At work, Yvan is faced with a fair amount of competition with colleagues to keep his manager position and his superior regularly feeds him with difficult tasks to complete within tight deadlines. When Yvan comes home in the evening, he often finds two of his children arguing over which TV program to watch before going to bed. At the dinner table, Yvan’s wife complains that he works too much and does not spend enough time with the family. After a couple of years with this life, Yvan starts feeling dull and negative about himself, future prospects, and the world in general. Depressive symptoms are looming. Yvan’s brother-in-law, although in a very similar life situation for many years, appears to be completely fine. In this example, the ABM model would predict that Yvan consistently evaluates the daily hassles he experiences with the appraisal structure described in Table 1. This would result in more frequent episodes of sadness (or despair) in response to everyday events. Such a buildup of negative emotion, if not regulated, would lead to the withdrawal from active life that is typical of major depression.

To summarize, the ABM posits that individual differences in the way people evaluate events (before they feel particular types of emotion) explain why certain people experience (a) more intense emotional experiences than others in response to similar events, and (b) higher frequencies of negative emotions than other individuals, despite exposure to comparable amounts of life challenges. In both instances, the cognitive appraisal process mediates the relationship between life events and emotion and is responsible for the generation of the negative emotional experience that is at the basis of the emotion–cognition interactions central to most models of cognitive vulnerability to psychopathology.

Conclusion

This article proposes an extension and clarification of the nature of what has been called “emotional processing” (e.g., Mathews & MacLeod, 2005), which is based on the cognitive processes involved in the generation of emotion (Moors et al., 2013). Our approach adopts a focus that is different from earlier work on cognitive vulnerability to emotional disorders. Several of the earlier approaches focus on how traditional executive functions (attention, memory, planning, and interpretation) are “contaminated” by emotional experience. Such approaches tend to imply the existence of a relatively clear separation between cognitive and emotional processes, a separation that is not easy to justify on either theoretical or empirical grounds (Moors, 2009).

The theoretical model that forms the basis of our approach suggests that appraisals (evaluations on different levels of cognitive processing) mediate the relationship between life events and emotional experience. Stable individual differences in these cognitive evaluations may produce dispositions to feel particular emotions and, ultimately, vulnerability to mental disorder. Our approach extends and complements earlier cognitive approaches to psychopathology, which focus on the influence of negative emotion on cognitive processes that occur further along the chain of events that lead to depressive symptoms. Our argument is that individual differences in patterns of appraisal (biases) may predispose some individuals to experience sadness more frequently and more intensely than other emotions in response to a variety of events, which in turn negatively influences subsequent cognitive processes. At that stage, individual differences in reactivity to emotional experience (e.g., Teasdale, 1988) and individual differences in emotion regulation (Aldao & Nolen-Hoeksema, 2010) contribute to the development of depressive symptoms. We argue that the key to understanding cognitive vulnerability to depression also lies in exploring the range of cognitive processes involved in the generation of “normal” emotional experiences and their adaptive value in evolutionarily relevant situations (see also Gilbert, 2015; Stein, & Nesse, 2015). In this respect, the limit between normal and abnormal emotion is likely to vary across individuals, as it reflects the irregular landscape of evolved affective strategies present in humans.

Footnotes

Author note:

This work was supported by funds granted to K. R. Scherer under Swiss National Science Foundation grant (100014-122491) and European Research Council (ERC) Advanced grant PROPEREMO (No. 230331).

Declaration of Conflicting Interests

None declared.

References

Abramson

L. Y.

Metalsky

G. I.

Alloy

L. B.

(1989). Hopelessness depression: A theory-based subtype of depression. Psychological Review, 96, 358–372.

Abramson

L. Y.

Seligman

M. E.

Teasdale

J. D.

(1978). Learned helplessness in humans: Critique and reformulation. Journal of Abnormal Psychology, 87, 49–74.

Aldao

Nolen-Hoeksema

(2010). Specificity of cognitive emotion regulation strategies: A transdiagnostic examination. Behaviour Research and Therapy, 48, 974–983.

Aldao

Nolen-Hoeksema

Schweizer

(2010). Emotion-regulation strategies across psychopathology: A meta-analytic review. Clinical Psychology Review, 30, 217–237.

Arnold

M. B.

(1960). Emotion and personality: Vol. I. Psychological aspects. New York, NY: Columbia University Press.

Beck

A. T.

(1967). Depression: Clinical, experimental, and theoretical aspects (Vol. 32). Philadelphia: University of Pennsylvania Press.

Beck

A. T.

(1979). Cognitive therapy and the emotional disorders. New York, NY: Penguin.

Bondolfi

Mazzola

Arciero

(2015). In between ordinary sadness and clinical depression. Emotion Review, 7, 216–222.

Ehring

Watkins

E. R.

(2008). Repetitive negative thinking as a transdiagnostic process. International Journal of Cognitive Therapy, 1, 192–205.

10.

Ellsworth

P. C.

Scherer

K. R.

(2003). Appraisal processes in emotion. In Davidson

R. J.

Scherer

K. R.

Goldsmith

(Eds.), Handbook of the affective sciences (pp. 572–595). New York, NY: Oxford University Press.

11.

Ellsworth

P. C.

Smith

C. A.

(1988). From appraisal to emotion: Differences among unpleasant feelings. Motivation and Emotion, 12, 271–302.

12.

Fiske

S. T.

Linville

P. W.

(1980). What does the schema concept buy us? Personality and Social Psychology Bulletin, 6, 543–557.

13.

Flett

G. L.

Blankstein

K. R.

Obertynski

(1996). Affect intensity, coping styles, mood regulation expectancies, and depressive symptoms. Personality and Individual Differences, 20, 221–228. doi:10.1016/0191–8869(95)00163–8

14.

Gilbert

(2015). An evolutionary approach to emotion in mental health with a focus on affiliative emotions. Emotion Review, 7, 230–237.

15.

Gross

J. J.

(1998). The emerging field of emotion regulation: An integrative review. Review of General Psychology, 2, 271–299.

16.

Gross

J. J.

Muñoz

R. F.

(1995). Emotion regulation and mental health. Clinical Psychology: Science and Practice, 2, 151–164.

17.

Haeffel

G. J.

Gibb

B. E.

Metalsky

G. I.

Alloy

L. B.

Abramson

L. Y.

Hankin

B. L.

. . . Swendsen

J. D.

(2008). Measuring cognitive vulnerability to depression: Development and validation of the cognitive style questionnaire. Clinical Psychology Review, 28, 824–836.

18.

Hankin

B. L.

Abramson

L. Y.

(2001). Development of gender differences in depression: An elaborated cognitive vulnerability–transactional stress theory. Psychological Bulletin, 127, 773–796.

19.

Harvey

J. H.

Town

J. P.

Yarkin

K. L.

(1981). How fundamental is “the fundamental attribution error”? Journal of Personality and Social Psychology, 40, 346–349.

20.

Hertel

P. T.

(2004). Habits of thought produce memory biases in anxiety and depression. In Yiend

(Ed.), Cognition, emotion and psychopathology: Theoretical, empirical and clinical directions (pp. 109–129). Cambridge, UK: Cambridge University Press.

21.

Kaiser

Scherer

K. R.

(1998). Models of “normal” emotions applied to facial and vocal expressions in clinical disorders. In Flack

W. F.

Laird

J. D.

(Eds.), Emotions in psychopathology (pp. 81–98). New York, NY: Oxford University Press.

22.

Kuppens

(2013). Comment: Appraisal affords flexibility to emotion in more ways than one. Emotion Review, 5, 176–179.

23.

Lau

M. A.

Segal

Z. V.

Williams

J. M. G.

(2004). Teasdale’s differential activation hypothesis: Implications for mechanisms of depressive relapse and suicidal behaviour. Behaviour Research and Therapy, 42, 1001–1017.

24.

Lazarus

R. S.

(1968). Emotions and adaptation: Conceptual and empirical relations. In Arnold

W. J.

(Ed.), Nebraska Symposium on Motivation: Vol. 16 (pp. 175–266). Lincoln: University of Nebraska Press.

25.

Lazarus

R. S.

Folkman

(1984). Stress, appraisal, and coping. New York, NY: Springer.

26.

Martin

L. L.

Tesser

(1996). Some ruminative thoughts. Advances in Social Cognition, 9, 1–47.

27.

Mathews

MacLeod

(2005). Cognitive vulnerability to emotional disorders. Annual Review of Clinical Psychology, 1, 167–195.

28.

Moors

(2009). Theories of emotion causation: A review. Cognition and Emotion, 23, 625–662.

29.

Moors

Ellsworth

P. C.

Scherer

K. R.

Frijda

N. H.

(2013). Appraisal theories of emotion: State of the art and future development. Emotion Review, 5, 119–124.

30.

Nolen-Hoeksema

(1991). Responses to depression and their effects on the duration of depressive episodes. Journal of Abnormal Psychology, 100, 569–582.

31.

Revelle

(1995). Personality processes. Annual Review of Psychology, 46, 295–328.

32.

Roseman

I. J.

Kaiser

(2001). Applications of appraisal theory to understanding, diagnosing, and treating emotional pathology. In Scherer

K. R.

Schorr

Johnstone

(Eds.), Appraisal processes in emotion: Theory, methods, research (pp. 249–267). London, UK: Oxford University Press.

33.

Roseman

I. J.

Smith

C. A.

(2001). Appraisal theory: Overview, assumptions, varieties, controversies. In Scherer

K. R.

Schorr

(Eds.), Appraisal processes in emotion: Theory, methods, research (pp. 3–19). London, UK: Oxford University Press.

34.

Rottenberg

Gross

J. J.

Gotlib

I. H.

(2005). Emotion context insensitivity in major depressive disorder. Journal of Abnormal Psychology, 114, 627–639.

35.

Sanislow

C. A.

Pine

D. S.

Quinn

K. J.

Kozak

M. J.

Garvey

M. A.

Heinssen

R. K.

. . . Cuthbert

B. N.

(2010). Developing constructs for psychopathology research: Research domain criteria. Journal of Abnormal Psychology, 119, 631–639.

36.

Scherer

K. R.

(1984). On the nature and function of emotion: A component process approach. In Ekman

(Ed.), Approaches to emotion (pp. 293–317). Hillsdale, NJ: Lawrence Erlbaum Associates.

37.

Scherer

K. R.

(2001). Appraisal considered as a process of multilevel sequential checking. In Schorr

Johnstone

(Eds.), Appraisal process in emotion: Theory, method, research (pp. 92–120). London, UK: Oxford University Press.

38.

Scherer

K. R.

(2009). The dynamic architecture of emotion: Evidence for the component process model. Cognition and Emotion, 23(7), 1307–1351.

39.

Scherer

K. R.

(2015). When and why are emotions disturbed? Suggestions based on theory and data from emotion research. Emotion Review, 7, 238–249.

40.

Scherer

K. R.

Brosch

(2009). Culture-specific appraisal biases contribute to emotion dispositions. European Journal of Personality, 23, 265–288.

41.

Scherer

K. R.

Schorr

Johnstone

(Eds.). (2001). Appraisal processes in emotion: Theory, methods, research. London, UK: Oxford University Press.

42.

Segal

Z. V.

(1988). Appraisal of the self-schema construct in cognitive models of depression. Psychological Bulletin, 103, 147–162.

43.

Seligman

M. E. P.

(1975). Helplessness: On depression, development and death. San Francisco, CA: Freeman.

44.

Sonnemans

Frijda

N. H.

(1995). The determinants of subjective emotional intensity. Cognition & Emotion, 9, 483–506.

45.

Stein

Nesse

R. M.

(2015). Normal and abnormal anxiety in the age of DSM-5 and ICD-11. Emotion Review, 7, 233–239.

46.

Teasdale

J. D.

(1988). Cognitive vulnerability to persistent depression. Cognition & Emotion, 2, 247–274.

47.

Watkins

E. R.

(2008). Constructive and unconstructive repetitive thought. Psychological Bulletin, 134, 163–206.

48.

Watkins

(2015). An alternative transdiagnostic mechanistic approach to affective disorders illustrated with research from clinical psychology. Emotion Review, 7, 250–255.

49.

Watkins

Moberly

N. J.

Moulds

M. L.

(2008). Processing mode causally influences emotional reactivity: Distinct effects of abstract versus concrete construal on emotional response. Emotion, 8, 364–378.

50.

Watkins

Moulds

(2005). Distinct modes of ruminative self-focus: Impact of abstract versus concrete rumination on problem solving in depression. Emotion, 5, 319–328.

51.

Watkins

E. R.

Nolen-Hoeksema

(2014). A habit–goal framework of depressive rumination. Journal of Abnormal Psychology, 123, 24–34.