Anxiety and depression: toward overlapping and distinctive features

ABSTRACT

This Special Issue of Cognition and Emotion addresses one of the cardinal concerns of affective science, which is overlapping and distinctive features of anxiety and depression. A central finding in the study of anxiety and depression is that they are moderately highly correlated with each other. This leads us to the question: What is behind this co-occurrence? Possible explanations relate to poor discriminant validity of measures; both emotional states are associated with negative affect; stressful life events; impaired cognitive processes; they share a common biological/genetic diathesis. However, despite a set of common (nonspecific) features, anxiety and depression are clearly not identical emotional states. Differences between them might be best viewed, for example, through their heterogeneous and multi-layered nature, adaptive functions and relations with regulatory processes, positive affect, and motivation or complex cognitive processes. In this introduction we consider several approaches (e.g. functional approach; tripartite model and content-specificity hypothesis) to which most research in this Special Issue is relevant. In addition, we have asked contributors to this Special Issue to indicate how their own studies on comparisons between anxiety and depression and models on anxiety and depression move this area of research to more mature science with applicability.

KEYWORDS:

• Anxiety
• depression
• overlapping and distinctive features
• major theoretical approaches

There has been considerable debate concerning the relationship between anxiety and depression within healthy and clinical populations. One complicating factor within healthy populations is that anxiety and depression measures typically correlate highly with each other (Clark & Watson, 1991). Within clinical populations, concurrent comorbidity of anxiety and depressive disorders is generally found in 20–40% of patients (Huppert, 2008).

We need to develop relevant theoretical frameworks to achieve full understanding of the similarities and differences between anxiety and depression. In this introduction, we consider several approaches (e.g. functional approach; tripartite model and content-specificity hypothesis). Most research in this Special Issue is directly relevant to one (or more) of these approaches.

Functions of anxiety and depression: past vs. future

We start with a theoretical framework focusing on the functions and adaptive value of anxiety and depression. A key assumption is that negative emotional states (including anxiety and depression) involve high short-term costs but often prove beneficial and adaptive long term (Del Guidice, & Ellis, 2015).

What major functions are associated with depression and anxiety? Sadness or depression is typically caused by goal loss (Johnson-Laird & Oatley, 1989). This leads to sustained analytical thinking focusing on the lost goal and the generation of a strategy to produce a new goal (Andrews & Thomson, 2009). Such thinking is associated with anhedonia (inability to experience positive affect) reducing the motivation to engage in other activities. Being in a depressed state has the following sequelae (Durisko, Mulsant, & Andrews, 2015, p. 315): “Biasing cognition to avoid losses, conserving energy, disengaging from unobtainable goals, signaling submission, soliciting resources, and promoting analytical thinking.”

In contrast, anxiety or fear typically occurs when an individual faces a threat to self-preservation (Johnson-Laird & Oatley, 1989). As a consequence, major functions of anxiety or fear involve selective attention to potential environmental threat and rapid detection of danger (e.g. Eysenck, 1992).

What are the implications of the above discussion? At the risk of oversimplification, the emphasis in depression on losses and disengagement from unachievable goals provides evidence depression is associated with a past orientation. In contrast, anxiety is more associated with a future orientation. Of course, this is a relative rather than an absolute distinction.

There is much support for the postulated links between anxiety and future orientation and depression and past orientation. Grupe and Nitschke (2013) proposed an Uncertainty and Anticipation Model of Anxiety in which the central theoretical assumption is that anxiety depends on uncertainty about possible future threats. Such uncertainty produces “heightened expectancies about the probability and cost of future threat” (p. 33) triggered in part by increased threat attention and hypervigilance. Grupe and Nitschke discussed the maladaptive cognitive, behavioural and affective responses of anxious individuals to future uncertainty.

Finlay-Jones and Brown (1981) studied patients with anxiety disorders or depression asked to identify life events in the months prior to disorder onset. Danger events (relating to future threats) were recalled by 77% of anxious patients but only 47% of depressed patients. In contrast, 65% of depressed patients reported loss events (relating to the past) compared to only 15% of anxious patients.

Eysenck, Payne, and Santos (2006) asked healthy individuals to identify personal events strongly associated with anxiety or depression. Anxious events related more to the future than the past whereas depressive events were much more associated with the past. Eysenck et al. also found hypothetical negative events occurring in the past were associated with more depression-related than anxiety-related symptoms. However, the opposite was the case for the same negative events located in the future. Pomerantz and Rose (2014) replicated these findings.

More evidence anxiety and depression differ in temporal orientation was reported by Rinaldi, Locati, Parolin, and Girelli (2017). Participants indicated the psychological distance of a past event occurring one month ago and an imagined event lying one month in the future. Anxious individuals showed a much stronger tendency than depressed ones to perceive the future as psychologically closer.

Cognitive biases

If anxiety is associated with a future orientation, we might expect anxious individuals to exhibit an attentional bias (selective attention to threat-related stimuli). In contrast, if depression is associated with a past orientation, we might expect depression to be associated with memory bias (disproportionate retrieval of negative information). Of course, several factors determine the extent to which anxiety is associated with attentional bias and depression with memory bias. For example, Williams, Watts, MacLeod, and Mathews (1997) distinguished between fast, “automatic” perceptual processes and slower, controlled conceptual processes. They argued anxiety is more associated with the former processes and depression with the latter so there are no simple relationships between cognitive biases and anxiety or depression.

We start with attentional bias. In a meta-analysis, Bar-Haim, Lamy, Pergamin, Bakermans-Kranenburg, and van IJzendoorn (2007) obtained convincing evidence that anxiety in healthy populations and clinical samples is associated with an attentional bias. The evidence concerning the existence of an attentional bias in depression is less consistent. Armstrong and Olatunji (2012) carried out a meta-analytic review of studies using eye tracking to assess attentional bias. Anxiety was associated with an attentional bias. Depression was not associated with an attentional bias in terms of initial orienting toward threat. However, it was associated with difficulty disengaging from dysphoric content. Other research (e.g. Duque & Vazquez, 2015; Kircanski & Gotlib, 2015) reported similar findings using stimuli relevant to depression. In contrast, Peckham, McHugh, and Otto (2010) found the presence or absence of attentional bias in depression depended on whether the negative stimuli were depression-relevant (discussed below).

We turn now to memory bias. It is common to distinguish between explicit memory bias (involving conscious recollection of information from long-term memory) and implicit memory bias (using implicit memory tests such as word completion). The prediction is that both forms of memory bias should be associated more strongly with depression than anxiety.

Blaney (1986) found in a meta-analytic review that depression was associated with a strong explicit memory bias. Mitte (2008) carried out a meta-analysis on anxiety and explicit memory bias. Anxiety was associated with an explicit memory bias on recall tests but not on recognition tests. Since recall depends more on recollection whereas recognition depends more on familiarity, these findings may indicate that anxiety affects the top-down processes associated with recollection more than the less effortful processes associated with familiarity.

The findings with respect to implicit memory bias are reasonably consistent. Phillips, Hine, and Thorsteinsson (2010) and Gaddy and Ingram (2014) carried out meta-analytic reviews of research on implicit memory bias and depression. In both studies, the findings indicated that depression was significantly associated with implicit memory bias. In contrast, Mitte (2008) found no relationship between anxiety and implicit memory bias in a meta-analysis.

Worry and rumination

It is generally assumed that rumination focuses on the past and the individual’s distress whereas worry focuses on the future and on potential negative outcomes. Watkins, Moulds, and Mackintosh (2005) reported findings consistent with those assumptions. Healthy participants produced a worry and a ruminative thought; there was a greater future orientation with the worry and a greater past orientation with the ruminative thought. Consistent with the time-orientation framework, clinical research has mostly considered rumination in the context of major depressive disorder whereas worry has mostly been studied in connection with generalised anxiety disorder.

Topper, Emmelkamp, Watkins, and Ehring (2017) showed the importance of worry and rumination in the maintenance of anxiety and depression. Adolescents and young adults with elevated levels of repetitive negative thinking (worry and rumination) received cognitive-behavioural training to reduce such thinking. This training reduced depression and anxiety, and the effects were mediated by the reductions in worry and rumination.

Special issue research

Kircanski, Thompson, Sorenson, Sherdell, and Gotlib (2017) used an experience-sampling method to assess the effects of everyday events on rumination and worry in patients with major depressive disorder, generalised anxiety disorder or both disorders. Their findings supported the validity of the distinction between rumination and worry: only rumination was increased by everyday events, and only elevated levels of rumination were followed by increased negative affect and decreased positive affect.

With respect to the time-orientation framework, we might predict the extent to which everyday events lead to worry would have been greater in generalised anxiety disorder than major depressive disorder, with the opposite being the case with rumination. However, most differences between the two groups of patients were non-significant. These non-significant findings essentially replicated the earlier findings of Kircanski, Thompson, Sorenson, Sherdell, and Gotlib (2015) using a very similar paradigm. It is unclear why the findings were inconsistent with predictions from the time-orientation framework.

Lewis, Yoon, and Joormann (2017) considered three emotion regulation strategies individuals might use habitually: worry (with a predominantly future focus); rumination (with a predominantly past focus); and reappraisal (where the emphasis is on the content of an individual’s thoughts rather than its temporal orientation). The relationship between these emotion regulation strategies and cortisol reactivity and recovery to a variant of the Trier Social Stress Test was assessed in healthy controls and patients with social anxiety disorder as a primary diagnosis (over 50% also diagnosed with major depressive disorder).

Across the entire sample, worry and rumination had different effects on cortisol reactivity: only worry was associated with increased cortisol reactivity. In contrast, both worry and rumination were associated with increased cortisol during recovery from the stressor across both groups (especially the patient group). Of interest, the control and patient groups did not differ in their habitual use of reappraisal, but high levels of reappraisal were only associated with greater cortisol recovery in the control group.

What do the above findings mean? First, they provide additional evidence there are important differences between worry and rumination. The precise reasons why only worry was associated with increased cortisol during recovery are unclear. However, this may reflect greater anticipatory anxiety associated with worry than rumination. Second, the high levels of cortisol during recovery associated with worry and rumination indicate these were inefficient emotion regulation strategies in response to a stressor. Third, the reappraisal strategy is used less efficiently by patients with social anxiety disorder than healthy controls.

Klein, de Voogd, Wiers, and Salemink (2017) studied a large sample of adolescents whose levels of anxiety and depression were assessed. They pointed out that most research on anxiety, depression and cognitive biases has involved the study of a single cognitive bias in isolation. Accordingly, they assessed attentional bias using the dot-probe and emotional visual search tasks and interpretive bias using the interpretation recognition task. A distinctive feature of Klein et al.’s study was an emphasis on investigating the extent to which cognitive biases can be used to predict levels of anxiety and depression.

Klein et al. (2017) obtained two main findings. First, anxiety and depression were both associated with attentional and interpretive biases but the associations were relatively small. Second, attentional bias and interpretive bias predicted unique variance in anxiety and in depression.

Summary and conclusions

Several lines of research support the theoretical assumptions that anxiety tends to be future-oriented whereas depression is past-oriented. Support has been obtained in research directly on past vs. future orientation, research on psychological distance of past and future events, research on cognitive biases (i.e. attentional and memory) and some research comparing worry and rumination.

As the research reported in this Special Issue indicates, however, the time-orientation framework is clearly oversimplified. Kircanski et al. (2017) and Lewis et al. (2017) both obtained evidence indicating worry and rumination differ in their effects on reactions to everyday events and cortisol responses to a stressor, respectively. However, there was no convincing evidence of specific associations between anxiety and worry and between depression and rumination. Below we consider possible reasons.

Much recent progress has been made in understanding the relationship between memory for past events and imagining future events. There are important commonalities in the processes involved in recalling past events and imagining future ones (Schacter et al., 2012). There is now much research focusing on anxiety, depression and prospection (mental representations of the future; see MacLeod, 2016, for a review). For example, MacLeod, Tata, Kentish, and Jacobsen (1997) asked anxious and depressed patients to generate positive experiences from the past and future. The findings were very similar with both time orientations: depressed individuals generate far fewer positive experiences regardless of whether those experiences lay in the past or future.

Speculatively, failures to obtain clear-cut associations between anxiety and worry and depression and rumination may depend in part on the similarity of the underlying processes generating worry and rumination. Alternatively, Papageorgiou (2006) suggested that many situations trigger “Why?” questions relating to the past and “What if?” questions relating to the future. Both explanations predict that individuals prone to rumination will also tend to experience much worry, and those prone to worry will experience much rumination.

As argued earlier, research on cognitive biases can enhance our understanding of the similarities and differences between anxiety and depression. Klein et al. (2017) added to our understanding by considering two cognitive biases (attentional and memory) in the same study. Their approach based on assessing the unique variance in anxiety and depression predicted by each cognitive bias has considerable potential for future research.

Tripartite model

Clark and Watson’s (1991) tripartite model of anxiety and depression (developed by Watson, 2009) provided an extremely influential account of the similarities and differences between anxiety and depression. In terms of similarity, anxiety and depression are both strongly associated with negative affectivity or the experience of distress and other negative emotional states. Clark and Watson also identified two other factors: (1) positive emotionality (involving energy and pleasurable engagement; it is orthogonal to negative emotionality; and (2) physiological hyperarousal. Depression (but not anxiety) is characterised by a relative absence of positive affect (or manifestation of anhedonia). In contrast, anxiety (but not depression) is characterised by hyperarousal.

Khazanov and Ruscio (2016) carried out a meta-analytic review of longitudinal studies focusing on the relationship between the trait of positive emotionality or extraversion to anxiety and to depression. Cross-sectionally, positive emotionality was negatively associated with anxiety and with depression, but the negative relationship was stronger with depression. Longitudinally, there were negative associations between positive emotionality and subsequent depression and anxiety, with the former association between slightly greater. Overall, the findings were consistent with the tripartite model. However, low positive emotionality was more weakly and less specifically related to subsequent depression than implied by the model.

Attentional bias

Research on attentional bias for positive stimuli (i.e. disproportionate attention to positive stimuli over neutral ones) is of relevance to the tripartite model. More specifically, if depression is associated with an absence of responsiveness to positive stimuli, then we might expect an absence of any attentional bias with positive plus neutral stimuli. In contrast, if anxiety is not associated with reduce responsiveness to positive stimuli, we might expect anxious individuals to exhibit an attentional bias for positive stimuli.

Meta-analyses have been reported by Armstrong and Olatunji (2012) and by Winer and Salem (2016). Armstrong and Olatunji reviewed studies using online eye tracking and found there was no attentional bias associated with anxiety but depression was associated with an opposite attentional bias (i.e. positive stimuli were avoided). Winer and Salem reviewed studies using the dot-probe task and obtained rather similar findings. Possible explanations of these findings are discussed below.

Special issue research

A considerable amount of research in recent decades has been strongly influenced by Clark and Watson’s (1991) attempt to identify the cognitive, emotional, and physiological components that are similar or dissimilar in anxiety and depression. There are several examples of such research in this Special Issue.

Jordan, Winer, Salem, and Kilgore (2017) focused on the relationship between depressive symptoms and anhedonia (lack of positive affect) using a longitudinal design. The study was based on their reward devaluation theoretical framework (Winer & Salem, 2016), according to which depressed individuals avoid positive material for two reasons: (1) lack of value associated with positive information and (2) an active process of inhibiting rewarding stimuli.

Jordan et al. (2017) related the above theoretical framework to the distinction between anticipatory anhedonia (not looking forward to pleasurable events) and consummatory anhedonia (lack of pleasure from current experiences). They assumed that anticipatory anhedonia (but not consummatory anhedonia) is associated with a lack of reward motivation in depressed individuals. As predicted, only anticipatory anhedonia mediated the relationship between fear of positive evaluation and subsequent depressive symptoms.

Podlogar et al. (2017) studied outpatients having many different diagnoses (e.g. major depressive disorder; generalised anxiety disorder and social anxiety disorder) who were administered several measures relating to anxiety and depression (e.g. Beck Depression Inventory; Beck Anxiety Inventory; Anxiety Sensitivity Index: Pennsylvania State Worry Questionnaire). Podlogar et al. focused on identifying factors relating to suicide risk.

What did Podlogar et al. (2017) find? Their main findings were consistent with the tripartite model on the assumption that high suicide risk will reflect the major components of anxiety and depression. More specifically, patients with a high suicide risk were more likely than those with a low suicide risk to have low positive affect, high negative affect, and high arousal. The combination of these three factors predicted suicide risk better than a diagnosis of depression or anxiety disorder. These findings resemble those of Subica, Allen, Frueh, Elhai, and Fowler (2016), who found a history of suicidal thoughts and behaviour was associated with high negative affect and low positive affect.

Renner, Hock, Bergner-Köther, and Laux (2017) used the tripartite model (Clark & Watson, 1991) as the starting point for their attempt to increase the discriminability of anxiety and depression in self-report measures. They argued the model was oversimplified in various ways. First, there is considerable evidence that factors specific to anxiety include worry as well as high physiological arousal or emotionality (Eysenck, 1992). Second, there are grounds for arguing that the two main characteristics of depression are dysthymia (depressed mood) and anhedonia (see American Psychiatric Association, 2013).

This line of thinking led Laux, Hock, Bergner-Köther, Hodapp, and Renner (2013) to develop the State-Trait Anxiety-Depression Inventory (STADI) comprising four subscales to assess emotionality, worry, anhedonia and dysthymia. Renner et al. (2017) administered the STADI and several other relevant scales including the NEO Five-Factor Inventory, the Beck Depression Inventory and Beck Anxiety Inventory to healthy and clinical samples.

Renner et al. (2017) obtained good support for their proposed four-variable model. However, there was a high correlation between worry (supposedly specifically related to anxiety) and dysthymia (supposedly specifically related to depression). How can we explain this finding? Papageorgiou’s (2006) argument (mentioned earlier) that worry is characterised by “What if?” questions whereas rumination (similar to dysthymia) is characterised by “Why?” questions may be of relevance. It is likely many stressful situations trigger “What if?” and “Why?” questions and this provide a partial explanation for the high association between worry and dysthymia.

Fajkowska, Domaradzka, and Wytykowska (2017a) argued that most conceptualisations of trait anxiety and depression have been oversimplified. According to Fajkowska (2015), the three-level compositional hierarchy of personality traits/types, personality traits/types comprises three levels: (1) behavioural markers; (2) components/structures and (3) complex inner mechanisms. This conceptualisation led to the development of the Anxiety and Depression Questionnaire (ADQ; Fajkowska, Domaradzka, & Wytykowska, 2017b). This questionnaire consists of four scales: arousal anxiety; apprehension anxiety; valence depression and anhedonic depression.

There is reasonable agreement between the four scales of the ADQ and the four scales contained in the STADI (Laux et al., 2013). More specifically, the ADQ’s arousal anxiety scale resembles the STADI’s emotionality scale; the ADQ’s apprehension anxiety scale resembles the STADI’s worry scale; the ADQ’s valence depression resembles the STADI’s dysthymia scale; and the ADQ’s anhedonic depression resembles the STADI’s anhedonia scale.

However, Fajkowska et al.’s (2017a) approach differs from that of Laux et al. (2013) in assuming the behavioural consequences of scores on the four scales of the ADQ depend on complex interactions among them. More specifically, they argue that the dominant function (reactive; regulative and mixed) of each personality type is of major importance. As a consequence, they Fajkowska et al.’s predicted there would be similarities in the attentional processing of emotional material between reactive arousal anxiety and valence depression and between regulative apprehension anxiety and anhedonic depression. They identified “pure types” and obtained strong support for the theoretical predictions made on the basis of these assumptions.

Kreitler (2017) addressed the issue of similarities and differences between anxiety and depression by using the psychosemantic approach based on the assessment of meaning. Young adults and older adults completed the Meanings Test (communicating the interpersonally shared and personal meanings of words) to identify thinking styles and self-report tests to assess anxiety and depression. There were several interesting differences in the meaning profiles (similar in both age groups) associated with anxiety and depression. More specifically, anxiety was associated with an enhanced focus on the individual’s own internal world whereas depression was associated with an enhanced focus on the personal (emotions, cognitions and evaluations) and interpersonally shared reality (e.g. location, time, and causes). Thus, the most clear-cut difference between the meaning profiles related to interpersonally shared reality: this was clearly associated with depression but not anxiety. Of importance, this finding identifies a limitation within the tripartite model.

Summary and conclusions

The tripartite model received considerable support, especially its assumption that depression differs from anxiety in being associated with much lower levels of positive affectivity. A reasonable expectation based on that model is that the greatest risk of suicide would be found among individuals who combine all three components (i.e. high negative affectivity/distress; low positive affectivity; and physiological hyperarousal). Support for that expectation was reported by Podlogar et al. (2017). However, the model is indisputably oversimplified and some of its limitations have been addressed in this Special Issue. First, depression is not simply associated with a lack of value attached to positive information; in addition, it is characterised by an active inhibition of positive information (e.g. Winer & Salem, 2016). Jordan et al. (2017) provided additional empirical support for this more complex conceptualisation.

Second, there is insufficient focus within the tripartite model on differences in content between anxiety and depression (see next section). For example, it is increasingly disputed that anxiety and depression are highly similar with respect to the negative affectivity/distress component of the tripartite model. Renner et al. (2017) sub-divided that component into worry (associated with anxiety) and dysthymia (associated with depression). In similar fashion, Fajkowska et al. (2017a) sub-divided that component into apprehension anxiety (resembling worry) and valence depression (resembling dysthymia). These four-component models represent a clear-cut advance on the tripartite model.

Third, research by Kreitler (2017) has identified another potential limitation with the tripartite model. More specifically, she found depression (but not anxiety) related to interpersonally shared reality, which may identify an important difference between anxiety and depression not contained within the tripartite model. This interesting finding deserves replication and extension.

Beck’s content-specificity hypothesis

One of the most influential theoretical approaches to understanding differences between clinical anxiety and depression was proposed by Beck (1976). In essence, he argued anxiety disorders are characterised by an excessive focus on the theme of danger; this involves exaggerating the extent of physical and psychological threat and also exaggerating the probability and cost of anticipated harm. In contrast, depressed patients focus excessively on the theme of self-depreciation; this leads to negative beliefs about themselves, the world, and the future. These beliefs and themes are represented in long-term memory by cognitive schemas (defined by Beck & Duzois, 2011, as “a well-organized cognitive structure of stored information and memories that forms the basis of core beliefs about self and others” (p. 598).

Beck’s (1976) theoretical approach led to the development of the Cognition Checklist by Beck, Brown, Steer, Eidelson, and Riskid (1987). This Checklist was based on the typical automatic reports of depressed and anxious patients. Themes relating to helplessness and hopelessness are present in items relating to depression rather than depression (e.g. “I will never overcome my problems”;“Life isn’t worth living”. This Checklist and the underlying theory have the advantage over the tripartite model that they focus explicitly on differences in cognitive content between anxiety and depression.

Research on attentional bias discussed earlier is consistent with the content-specificity hypothesis in two ways. First, there is clearer evidence for an attentional bias in depression when negative stimuli are relevant to the cognitive schemas of depressed individuals (Peckham et al., 2010). Second, the attentional bias involving avoidance of positive stimuli in depressed but not anxious individuals is consistent with the hopelessness and helplessness of depressed cognitive schemas.

Evidence consistent with the content-specificity hypothesis was reported by Epkins, Gardner, and Scanlon (2013) in a study on healthy female pre-adolescents. They considered associations between rumination and anxiety sensitivity on the one hand and depressive and anxiety symptoms on the other hand. After controlling for girls’ depressive symptoms, their anxiety sensitivity (but not their rumination) was associated with their anxiety level. In similar fashion, after controlling for girls’ anxiety symptoms, their rumination (but not their anxiety sensitivity) was associated with their depression.

Special issue research

Garnefski and Kraaij (2017) reported findings relevant to the content-specificity hypothesis. They used the SCL-90 (Symptom Check List; Derogatis, 1977) to identify the symptoms of anxiety and depression in healthy adolescents. They then tested Beck et al.’s (1987) content-specificity hypothesis with respect to use of cognitive emotion regulation strategies. When they controlled for comorbidity between anxiety and depression, depression was associated with rumination, self-blame, and lack of positive reappraisal and refusing. In contrast, when they controlled for depression, anxiety was associated with catastrophising and other-blame.

The study by Garnefski and Kraaij (2017) is important because it demonstrates the applicability of the content-specificity hypothesis to emotion regulation strategies. Since it is a cross-sectional study, further longitudinal research is required so that causal inferences can be drawn.

Summary and conclusions

Beck’s content-specificity hypothesis provides a useful theoretical framework within which to consider differences between anxiety and depression. The assumption that the differing negative thoughts of anxious and depressed individuals reflect differences in their underlying cognitive schemas is very plausible. Recent expansions of the three components of the tripartite model to four-component models (e.g. Fajkowska et al., 2017a; Renner et al., 2017) can be regarded as consistent with the content-specificity hypothesis in that such models attach much importance to differing cognitive content between anxiety and depression.

The content-specificity hypothesis is somewhat limited its explanatory power. For example, there is a danger of some circularity. More specifically, it is sometimes argued that key evidence for the existence of anxious and depressive cognitive schemas comes from patterns of automatic thoughts, and then these cognitive schemas are used to “explain” the patterns of automatic thoughts.

Future directions

There has been considerable progress in understanding the ways in which depression and anxiety resemble each other and the ways in which they differ. However, it is clear that much more research is needed. Here we will briefly indicate three possible directions for such research.

First, to our knowledge, there has been very little theorising or research designed to forget links between different theoretical conceptualisations. We illustrate the potential usefulness of forging such links by considering the temporal-orientation framework and the tripartite model. Depression starts with major losses which cannot be undone and this creates anhedonia. Since imagining the future involves similar processes to recalling the past, there is a pervasive absence of positivity. In contrast, anxiety starts with major future threats; since these are only threats, there is typically some probability they can be averted. As a consequence, anxiety is much less associated with anhedonia.

According to the tripartite model, anxiety and depression are both characterised by negative affectivity/distress. The temporal-orientation framework suggests it might be useful to distinguish between negative thoughts having a future orientation (e.g. worry) and those having a past orientation (e.g. rumination).

Second, too much theorising and research is at a descriptive level lacking explanatory power. For example, it has proved useful to discriminate between depression and anxiety in terms of the presence versus absence of anhedonia. However, we need to move beyond that to identify underlying mechanisms. A valuable start has been made by Winer and Salem (2016) and Jordan et al. (2017) in their reward devaluation theoretical framework, which distinguishes between a lack of value attached to positive stimuli and an active process of inhibiting such stimuli.

Third, there are undoubtedly more dynamic interactions between anxious and depressed mood, and between worry and rumination, than is generally recognised. What is required is short-term longitudinal research exploring these interactions in detail. For example, Starr and Davila (2012a) required anxious and depressed mood in patients with generalised anxiety disorder and a history of depressive symptoms to complete a daily mood diary. Anxiety on any given day strongly predicted depression 1, 2, 3 and 4 days later. In contrast, depression did not predict anxiety on subsequent days. This partial dependence of depressed mood on a preceding anxious mood is of potential importance.

Starr and Davila (2012b) explored interactions between anxious and depressed mood in more detail in patients with generalised anxiety disorder, again using a daily mood diary. Anxious mood was most predictive of subsequent depressed mood on days when patients experienced interpersonal problems and perceived rejection. They also found anxious and depressed mood were more highly correlated on days when patients ruminated about their anxiety or viewed their anxiety symptoms in a more negative way. In principle, such research could clarify the ways in which worry and rumination may trigger each other.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This paper was partly supported by a Grant 2012/07/E/HS6/04071 from Narodowe Centrum Nauki, Polska (the National Science Centre, Poland).