1 the Interplay Among Attention, Interpretation, and Memory Biases

1 the Interplay Among Attention, Interpretation, and Memory Biases

1 The interplay among attention, interpretation, and memory biases in depression: Revisiting the combined cognitive biases hypothesis Jonas Everaert and Ernst H.W. Koster Ghent University Introduction Depression is a prevalent and recurrent mental disorder causing a severe personal and societal burden (Kessler & Bromet, 2013). Identifying the mechanisms involved in depression is an integral part of efforts to improve prevention and treatment strategies for this burdensome disorder. Cognitive theories posit that depression symptoms are caused in part by negative biases in the processing of emotional information (Clark, Beck, & Alford, 1999; Ingram, 1984; Williams et al., 1997). Consistent with this hypothesis, extensive research has linked depression to negative biases in cognitive processes such as attention, interpretation, and memory. Specifically, empirical studies have found that (sub)clinically depressed individuals may exhibit an attention bias toward negative self-relevant information (Armstrong & Olatunji, 2012; Peckham, McHugh, & Otto, 2010; Winer & Salem, 2016; but see also Rodebaugh et al., 2016), an interpretation bias favoring negative explanations for ambiguous situations (Everaert, Podina, & Koster, 2017), and a memory bias featuring improved recollection of negative self-referential information (Gaddy & Ingram, 2014; Matt, Vázquez, & Campbell, 1992). Importantly, research suggests that biases of attention, interpretation, and memory may influence symptoms of depression (Hallion & Ruscio, 2011; Menne-Lothmann et al., 2014; Mogoaşe, David, & Koster, 2014; Vrijsen, Hertel, & Becker, 2016) and predict their longitudinal course (Johnson, Joormann, & Gotlib, 2007; Price et al., 2016; Rude, Durham-Fowler, Baum, Rooney, & Maestas, 2010). Together, current research findings indicate that attention, interpretation, and memory biases are not merely a by-product of depressed mood but may confer risk to experiencing depression. 2 While attention, interpretation, and memory biases have been investigated extensively in isolation, the interplay among these presumed risk factors has received only modest consideration. However, uncovering how these cognitive biases work together seems crucial to gain a comprehensive understanding of the cognitive mechanisms of maladaptation involved in depression. Indeed, researchers have repeatedly argued that it is unlikely that the heterogeneous symptoms of depression (e.g., sustained negative mood, anhedonia) would be caused or maintained by cognitive biases that operate in isolation (e.g., Hankin, 2012; Kraemer, Stice, Kazdin, Offord, & Kupfer, 2001; Wittenborn, Rahmandad, Rick, & Hosseinichimeh, 2016). Instead, theorists have proposed that it is much more likely that depression involves multiple causal chains involving cognitive biases that reinforce each other through mutual influences. This notion has been referred to as the Combined Cognitive Biases Hypothesis (CCBH; Hirsch, Clark, & Mathews, 2006). The CCBH, as originally formulated by Hirsch and colleagues, specifically states: “cognitive biases do not operate in isolation, but rather can influence each other and/or can interact so that the impact of each on another variable is influenced by the other. Via both these mechanisms we argue that combinations of biases have a greater impact on disorders than if individual cognitive processes acted in isolation” (p. 224; Hirsch et al., 2006). Although the CCBH was formulated in the context of social anxiety disorder, the hypothesis can be applied to other forms of psychopathology. Elaborating on the CCBH in the context of depression in a prior review (Everaert, Koster, & Derakshan, 2012), we outlined three broad categories of open research questions that required empirical consideration to further our understanding of how cognitive biases operate in the etiology, maintenance, and relapse depression. Specifically, we distinguished association, causal, and predictive magnitude questions. With association questions, we referred to research questions focusing on how biases of attention, interpretation, and memory are correlated across different stages of information-processing (e.g. 3 during encoding or retrieval of emotional information). Example association questions may concern whether negative attention bias during encoding is associated with improved memory for previously presented negative material or whether negative memory bias is related to attention biases toward matching emotional material. The second category of CCBH questions, the causal questions, focuses on the direction of the hypothesized influence of one cognitive bias on another bias. These questions concern unidirectional and bidirectional influences that may exist between two given cognitive biases. An example of a causal question is whether attention biases cause a congruent bias in interpretation and whether an interpretation bias in turn influences attention allocation toward stimuli that are congruent with the emotional interpretations. Finally, the third category of questions, the predictive magnitude questions, focuses on how multiple cognitive biases in concert influence the symptom course of depression over longer periods of time. Extending association and causal questions, predictive magnitude questions focus on the utility of a single cognitive bias vs. multiple cognitive biases in combination in predicting prospective changes in depression. For example, predictive magnitude questions may address whether cognitive biases have additive effects on depressive symptoms that extend beyond the isolated effect of each bias (see below). Recent years have witnessed an important upsurge of empirical studies addressing different aspects of the different CCBH questions in various forms of psychopathology. In light of the advances in research on the CCBH in depression, the purpose of this chapter is to review recent findings as well as both theoretical and methodological innovations since our review article (Everaert et al., 2012). We think that an updated review of theory and research on the CCBH in depression is both timely and necessary given the increasingly complex picture that is arising from the empirical research examining interactions among cognitive biases in depression. 4 Below, we start by describing theoretical contributions that can inform upon the interplay among cognitive biases in depression. Then, we discuss the major methods that have been used to investigate the association, causal, and predictive magnitude questions that originate from the CCBH. Next, we review findings from recent empirical work with respect to the different CCBH questions. Finally, we discuss limitations of current research on this topic and propose several ways in which this exciting area of research can be taken forward. Major theories in the field Influential theoretical models of depression such as Beck’s schema theory (Beck & Haigh, 2014; Clark et al., 1999), enhanced elaboration accounts (Ingram, 1984; Williams et al., 1997), and cognitive control accounts (Hertel, 1997; Joormann, Yoon, & Zetsche, 2007) have attributed a crucial role to cognitive biases in the etiology and maintenance of depressive symptoms. These dominant theoretical models have guided seminal research and led to important discoveries regarding the role of cognitive biases as (causal) risk factors for depression (for reviews, see Gotlib & Joormann, 2010; Mathews & Macleod, 2005). However, contemporary theoretical accounts often propose a number of cognitive biases without providing a detailed account of how these processes may influence one another and in concert influence the course of depression (for a review, see Everaert et al., 2012). It is only recently that specific ideas and hypotheses regarding the interplay between cognitive biases have begun to emerge in clinical research (Aue & Okon- Singer, 2015; Everaert et al., 2012; Hertel, 2004; Hertel & Brozovich, 2010; Hirsch et al., 2006; Wittenborn et al., 2016). In this section, we discuss novel conceptual contributions that have attempted to describe the interplay among cognitive biases in depression in a comprehensive manner. A discussion of the shared and unique predictions by traditional cognitive models with respect to the different CCBH questions can be found elsewhere (see Everaert et al., 2012). 5 The causal loop diagram of depression dynamics Wittenborn and colleagues recently proposed a causal loop diagram integrating cognitive, social, and environmental factors that may explain the etiology of depression (Wittenborn et al., 2016). Of particular relevance to the CCBH, this model specifies a reinforcing feedback loop involving attention, interpretation, and memory biases in the consolidation of negative cognitions. The model proposes that negative cognitive representations that are stored in long-term memory direct attention toward relevant information. Specifically, negative memory representations are hypothesized to both orient and maintain attention on negative material in the environment that matches the content of the memory representations. The resulting negative bias of attention is expected to increase one’s perceived stress level and produce negatively biased interpretations of the situation. This enhanced processing of negative material through biases of attention and interpretation is in turn expected to set the stage for increased negative affect and improved encoding of negative material into memory. This further consolidates the initial negative memory representations, which may

View Full Text

Details

  • File Type
    pdf
  • Upload Time
    -
  • Content Languages
    English
  • Upload User
    Anonymous/Not logged-in
  • File Pages
    34 Page
  • File Size
    -

Download

Channel Download Status
Express Download Enable

Copyright

We respect the copyrights and intellectual property rights of all users. All uploaded documents are either original works of the uploader or authorized works of the rightful owners.

  • Not to be reproduced or distributed without explicit permission.
  • Not used for commercial purposes outside of approved use cases.
  • Not used to infringe on the rights of the original creators.
  • If you believe any content infringes your copyright, please contact us immediately.

Support

For help with questions, suggestions, or problems, please contact us