Attentional Bias Components in Anxiety and Depression: A Systematic Review

Denise Rogersa, Edel Murphya, Sarah Jane Windersa & Ciara M. Greenea aSchool of Psychology, University College Dublin, Belfield, Dublin 4, Ireland

Corresponding author: Associate Professor Ciara M. Greene

Email: [email protected]

Postal address: School of Psychology, University College Dublin, Belfield, Dublin 4, Ireland

Tel: +353 1 7168334

1 Abstract

Attentional biases have been identified as a transdiagnostic cognitive process that may underlie a range of psychological disorders. They comprise three measurable and observable components; facilitation (rapid detection of concern-related stimuli), difficulty in disengagement (slower attentional shifting away from concern-related stimuli) and attentional avoidance (allocation of attention away from concern-related stimuli). Attentional biases to negative stimuli are common in anxiety and depression; however, their shared (i.e. transdiagnostic) and distinct components have not yet been systematically investigated. Literature searches were conducted on the PsychINFO, Embase, PubMed and Web of Science databases, yielding 560 articles after duplicates were removed. Articles were subject to abstract and full-text screening against study eligibility criteria. Twenty-five articles were included in the extraction phase. Data regarding population, experimental paradigm and attentional bias components were extracted. Results are suggestive of facilitation as a transdiagnostic attentional process across anxiety, depression and those with co- occurring anxiety and depression. There was strong evidence of avoidance in depression, with weaker evidence in anxiety, while delayed disengagement was observed in anxiety, but not in depression. Critical gaps in the literature were also identified. These findings provide support for the transdisagnostic nature of attentional biases, shedding light on the commonalities observed across diagnostic categories.

Keywords: Attentional bias; facilitation; avoidance; delayed disengagement; anxiety; depression

Funding: This work was supported by a scholarship to DR from the Health Services Executive of Ireland

Public significance: This systematic review suggests that attentional biases towards and away from concern-related stimuli are a feature of both anxiety and depression, and suggest considerable overlap in the cognitive processes underlying these two disorders.

2 Introduction

Mental health conceptualisation, research and treatment is currently in the midst of a paradigm shift. Traditional nosological systems, such as the Diagnostic Statistical Manual Fifth Edition (DSM- 5; American Psychiatric Association, 2013) and the International Statistical Classification of Diseases and Related Health Problems Tenth Edition (ICD-10; World Health Organization, 1993), assume that mental health disorders are distinct and independent categorical entities (Krueger & Eaton, 2015). However, these systems have been heavily criticised for their lack of validity, over- specification, internal heterogeneity and high comorbidity rates (Hyman, 2007, 2010; Wakefield, 2016). Alternatively, the transdiagnostic approach posits that common cognitive, behavioural and psychophysiological processes predispose and maintain symptoms across diagnostic boundaries (Garland & Howard, 2014; Mansell, Harvey, Watkins, & Shafran, 2008). The transdiagnostic approach calls for a shift in focus from disorder-specific symptoms to cross-disorder processes (Harvey, Watkins, & Mansell, 2004).

Attentional biases are an excellent example of a cognitive transdiagnostic process (Garland & Howard, 2014), as highlighted by the proliferation of attentional bias research over the past number of decades; reviews of this research have been conducted in relation to anxiety (Bar-Haim, Lamy, Pergamin, Bakermans-Kranenburg, & van Ijzendoorn, 2007), depression (Peckham, McHugh, & Otto, 2010), eating disorders (Dobson & Dozois, 2004), OCD (Muller & Roberts, 2005) and addictive disorders (Field & Cox, 2008).

Attentional bias refers to the systematic tendency to preferentially attend to concern-related stimuli over non-concern-related stimuli (Mansell et al., 2008). The ability to flexibly allocate attention towards and away from salient environmental cues is arguably essential for adaptive functioning. Deficits or biases in this ability contribute to the onset and maintenance of many mental health difficulties, including anxiety and depression (Bar-Haim et al., 2007; Peckham et al., 2010). Anxiety and depression are two of the most prevalent mental health disorders world-wide and have a comorbidity rate of up to 50% (Goldberg, Krueger, Andrews, & Hobbs, 2009; Hirschfeld, 2001). Given the magnitude of these comorbidity rates, investigation into transdiagnostic processes such as attentional bias is warranted and may be fruitful in informing future transdiagnostic treatments such as attentional bias modification training (ABM; Craske, 2012).

3 Although there is a wealth of disorder-specific attentional bias research, few studies have taken a transdiagnostic perspective or focused upon the individual components of the attentional bias effect. Research has shown that attentional biases are comprised of three observable and measurable components; ‘facilitation’ (also referred to as vigilance, engagement and attentional orienting), ‘difficulty in disengagement’ and ‘attentional avoidance’ (Cisler, Bacon, & Williams, 2009; Cisler & Koster, 2010; Fox, Russo, Bowles, & Dutton, 2001). Facilitation refers to the process by which attention is drawn towards a threatening stimulus more quickly than a non-threatening stimulus (Cisler & Koster, 2010). Difficulty in disengagement describes the process by which attentional shifts away from a threatening stimulus are slower than attentional shifts away froma non-threatening stimulus. Attentional avoidance, in contrast, describes the process whereby attention is directed away from a threatening stimulus and strategically allocated to an alternative location.

Theories Underlying Attentional Bias Components There are two main theories underlying the individual components of attentional bias; the vigilance-avoidance hypothesis and the delayed disengagement hypothesis. The vigilance- avoidance hypothesis has largely been investigated in anxious populations (Koster, Verschuere, Crombez, & Van Damme, 2005; Mogg, Bradley, Miles, & Dixon, 2004; Mogg, Bradley, De Bono, & Painter, 1997). The vigilance-avoidance hypothesis proposes that anxious individuals direct their attention towards threatening stimuli more quickly and more frequently during the early stages of processing (e.g. <500 milliseconds) and then direct their attention away from threatening stimuli during the later stages of processing (e.g. 1500 milliseconds; Mogg et al., 2004). The strategic re- direction of attention away from threatening stimuli alleviates distress in the short-term; however, persistent avoidance maintains distress overtime as it prevents habituation in the presence of threatening stimuli. Interestingly, research investigating the vigilance-avoidance hypothesis in depression is lacking. This may relate to the dominance of traditional models, such as Williams and colleagues’ (1988) model, which states that attentional biases in depression occur at later stages of processing only and are not detectable at shorter exposure durations.

In contrast, the delayed disengagement hypothesis has been investigated in both anxious (Fox et al., 2001; Koster, Crombez, Verschuere, & De Houwer, 2004) and depressed populations (Goeleven, De Raedt, Baert, & Koster, 2006; Koster, De Raedt, Goeleven, Franck, & Crombez, 2005b). It suggests that anxiety and depression are maintained by impairments in inhibiting and shifting attention away from threatening or negative stimuli (Fox et al., 2001). Such difficulties in

4 disengagement result in sustained processing of negative stimuli rather than flexible re- engagement with other environmental stimuli. The delayed disengagement hypothesis has typically been measured at longer stimulus exposure durations (see Cisler & Koster, 2010 for a review).

Attentional Bias Paradigms A number of experimental paradigms have been used to investigate the attentional bias effect. In order to elucidate the manner in which each paradigm investigates the attentional bias effect and how each paradigm differentiates between the different attentional bias components, a brief overview of the most commonly used tasks is provided below.

In the Dot Probe Task (DPT; MacLeod, Mathews, & Tata, 1986), two stimuli (e.g. words, pictures or facial expressions) are presented simultaneously for a brief period. One stimulus is emotional in content and the other is neutral in content. After both stimuli disappear, a probe appears in one of the previously occupied locations. Participants are instructed to respond to the spatial location of the probe. Reaction times on congruent trials (i.e. trials where probes replace emotional stimuli) are subtracted from incongruent trials (i.e. trials where probes replace neutral stimuli) to calculate an attentional bias index score (MacLeod et al., 1986). A positive bias score is suggestive of an attentional bias towards emotional stimuli and a negative bias score is suggestive of an attentional bias away from emotional stimuli (i.e. attentional avoidance). Importantly, a positive bias score on the DPT may reflect either facilitated engagement with stimuli or difficulty in disengagement. These two attentional bias components can be differentiated by including a baseline condition containing two neutral stimuli and comparing these with experimental conditions containing both an emotional and a neutral stimulus (Koster, De Raedt, et al., 2005b). Facilitation is reflected by faster reaction times on congruent emotional-neutral trials compared to neutral-neutral trials and difficulty in disengagement is reflected by slower reaction times on incongruent emotional-neutral trials compared to neutral-neutral trials (Koster, De Raedt, et al., 2005b).

The Exogenous Cueing Task (ECT), otherwise known as the Spatial Cueing Task or the Posner paradigm (Fox et al., 2001; Posner, 1980) is another commonly used attentional bias paradigm. Its design is quite similar to that of the DPT, except only one stimulus (either emotional or neutral) is presented at a time. After the stimulus disappears, a probe appears either in the location previously occupied by the stimulus (i.e. valid trials) or the location previously unoccupied by the stimulus (i.e. invalid trials). Participants are instructed to respond to the location of the probe.

5 Valid trials are subtracted from invalid trials to provide a measure of attentional bias. Facilitation is reflected by faster reaction times on valid emotional trials relative to valid neutral trials and difficulty in disengagement is reflected by slower reaction times on invalid emotional trials relative to invalid neutral trials (Cisler et al., 2009). Slower reaction times on valid emotional trials relative to valid neutral trials and faster reaction times on invalid emotional trials relative to invalid neutral trials is suggestive of attentional avoidance (Koster, Crombez, Verschuere, Van Damme, & Wiersema, 2006).

The Emotional Stroop Task (EST) is a modified version of the classic Stroop task (Stroop, 1935); instead of colour words (e.g. red), the EST uses emotional words (e.g. murder) and neutral words (e.g. table). Participants are instructed to name the colour in which the word is printed whilst simultaneously ignoring the semantic content of the word. Colour-naming reaction times on neutral trials are subtracted from reaction times on emotional trials to obtain an attentional bias index score. Positive attentional bias index scores reflect slower colour naming on emotional trials compared to neutral trials (i.e. an attentional bias towards emotional words; Williams, Mathews, & MacLeod, 1996). However, it has been argued that the EST cannot differentiate between the different components of attentional bias, as slower reaction times on emotional trials may reflect either delayed disengagement or a generic slowdown effect caused by the presence of a threatening stimulus (Algom, Chajut, & Lev, 2004; Fox, 2004). Instead, the term ‘interference inhibition’ is often used to refer to attentional bias effects observed in this paradigm (Dai & Feng, 2011; Fox, 1994; Martin, Williams, & Clark, 1991).

Lastly, the Negative Affective Priming Task (NAPT; De Raedt et al., 2012; Joormann, 2004) consists of consecutive trial pairs (i.e. a prime trial and a probe trial). Both prime and probe trials include a distracter and a target stimulus. In each trial, participants are instructed to evaluate the emotional content of the target stimulus as either negative or positive, whilst ignoring the distracter. In this sense, the NAPT differs from the previously discussed paradigms as participants are explicitly instructed to attend to the emotional content of the stimulus. In experimental conditions, the emotional content of prime trial distractors matches the emotional content of probe trial targets. However, in control conditions the emotional content of prime trial distracters and probe trial targets are unrelated. Faster reaction times on negative probe trial targets on experimental versus control conditions is suggestive of facilitation (Goeleven et al., 2006; Joormann, 2004). Due to its design, the NAPT does not assess difficulty in disengagement or attentional avoidance.

6 A further note on designs of attentional bias paradigms includes the use of backwards masking procedures to assess subliminal attentional bias effects. According to Williams and colleagues’ model (Williams et al., 1988), attentional biases operate at different stages of information processing in anxiety and depression. Attentional biases in anxiety are presumed to operate at an automatic, pre-attentive stage (i.e. where attentional resources are automatically drawn towards a negative or threatening stimulus before the stimulus has entered conscious awareness). However, in depression, the model states that attentional biases occur at a later, controlled stage of processing (i.e. where attentional resources are drawn towards a negative stimulus after the stimulus has entered conscious awareness). In order to investigate this theory, paradigms often include a subliminal exposure condition. In such conditions, stimuli are presented for durations considered to fall below the threshold of conscious perception (e.g. 33 milliseconds) before being replaced by a mask (e.g. a string of characters). Masks remain on screen for either an additional specified duration (e.g. 100 milliseconds) or until a response is registered, depending on the task design (Carlson & Mujica-Parodi, 2015; Lee & Knight, 2009; Mogg et al., 2000). Attentional biases detected in such exposure conditions are assumed to have occurred subliminally through automatic, pre-attentive processing of the stimulus.

Attentional Bias Components in Anxiety and Depression Previous narrative reviews have presented evidence for all three attentional bias components in clinical anxiety (e.g. Generalised Anxiety Disorder; GAD) and subclinical anxiety (e.g. High Trait Anxiety; HTA), using a range of experimental paradigms (Cisler et al., 2009; Cisler & Koster, 2010). However, by comparison, research investigating the presence of attentional bias components in clinical depression, subclinical dysphoria and comorbid depression and anxiety is lacking. This is surprising given such high rates of comorbidity between these two groups (Hirschfeld, 2001; Löwe et al., 2008) and evidence confirming negative attentional biases in a variety of clinical and subclinical depression groups (Peckham et al., 2010).

Of those studies which have investigated attentional bias components in depressed populations, evidence of facilitation at longer stimulus durations has been detected in Major Depressive Disorder (MDD; Leyman, De Raedt, Schacht, & Koster, 2007), previously depressed participants (Joormann & Gotlib, 2007) and subclinical dysphoria (Koster, De Raedt, et al., 2005b). The latter study also found evidence of difficulty in disengagement in their subclinical population. However, Mogg et al. (2005) failed to detect facilitation in their sample of clinically anxious participants with co-morbid depression. Hence, of the limited research investigating attentional bias components in

7 clinical and subclinical depression as well as comorbid depression and anxiety, results have been mixed and systematic evaluation is required.

The transdiagnostic approach advocates for the investigation of psychological processes that cut across diagnostic boundaries. In keeping with this premise, the current study aims to investigate the components of attentional bias common and distinct to anxiety and depression, specifically:  Which components of attentional bias are evident in anxiety?  Which components of attentional bias are evident in depression?  Which components of attentional bias are common to both anxiety and depression?  Which components of attentional bias are distinct to anxiety or depression alone?  Which components of attentional bias are found in co-occurring anxiety and depression?

8 Method

Protocol The aims, methods, study eligibility criteria, data extraction sheet and analysis plan for this review were specified in advance and documented in an unregistered protocol.

Literature Search Literature searches were conducted using four of the main relevant databases in this area; PsychINFO, Embase, PubMed and Web of Science. No other sources were included in the search. The final search was performed in January 2020 using the following search terms; ‘attentional bias’ AND ‘mechanism’ AND (‘depress*’ OR ‘dysthym*’ OR ‘anxiety’ OR phobi*’ OR ‘panic’); the asterisk is a wildcard Boolean search operator; if the asterisk follows the word, it will search any term that begins with the root of the word truncated by the asterisk. The search was confined to peer reviewed human articles published in English only; however, articles from any period were included. The search retrieved 931 articles from the databases searched (N = 560 after duplicates were removed). Two additional articles were also found manually.

Eligibility Criteria Retrieved articles were subject to an initial title and abstract screening and a further full-text eligibility assessment against the following predefined inclusion and exclusion criteria;

Inclusion criteria:  Articles including adult participants from clinical anxiety and/or clinical depressive populations (e.g. MDD, dysthymia, specific phobia, GAD)  Articles including adult participants from subclinical anxiety (e.g. HTA) and/or depressive populations (e.g. dysphoria), where a standard psychometric mood measure was administered and reported scores fell above standard minimum cut-off points (e.g. BDI > 13, STAI > 36)  Articles including standard attentional bias paradigms (e.g. DPT, ECT, EST, NAPT or modifications thereof)  Experimental paradigms including comparisons between negative stimuli and neutral stimuli

9  Articles reporting attentional bias scores for one or more attentional bias component (i.e. facilitation, difficulty in disengagement or attentional avoidance). Note; interference inhibition scores were included in EST articles  Articles reporting specific component bias scores or sufficient reaction time datafor component bias scores to be calculated

Exclusion criteria:  Articles including non-human participants or human participants under the age of 18  Articles including participants from clinical populations not listed under the DSM-5 anxiety and depressive disorder categories  Articles including subclinical populations where a standard psychometric measure was not used or where it could not be established whether participant scores fell above standard minimum cut-off points (e.g. where psychometric data not reported)  Articles in which participants were grouped by a variable other than psychiatric diagnosis or scores on a psychometric measure (e.g. 5-HTTLPR genotype)  Articles which did not focus upon attentional bias  Articles including attentional bias paradigms which did not include both negative and neutral stimuli  Articles where a bias score for one or more component of attentional bias was not reported and could not be calculated from the reported data  Articles in which attentional bias was induced or manipulated by medications (e.g. citalopram, oxytocin, SSRIs) and was not naturally occurring within the context of anxiety or depression  Neuroimaging articles (e.g. MRI, EEG) which did not include a behavioural experiment where a component bias score was reported or calculable from the reported data  Non-primary sources including systematic reviews, meta-analyses and narrative reviews

Study Selection The selection process was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines (PRISMA; Liberati et al., 2009). DR and CG performed the title and abstract screening. Independent reviewers (EM, SJW) screened a randomly selected 20% of titles and abstracts and an agreement rating of 95% was achieved between reviewers. Where agreement was not achieved, articles were included in the full-text eligibility assessment. A full-text eligibility assessment was conducted by DR and CG. Independent reviewers

10 (EM, SJW) assessed a randomly selected 25% of full-texts and an agreement rating of 85% was achieved. Disagreements between reviewers were resolved by consensus.

From the 560 articles identified in the database search, 373 were excluded after the initial title and abstract screening. A further 162 articles were excluded following the eligibility assessment. Inclusion and exclusion decisions were made using the previously described criteria. See Figure 1 for further details regarding articles excluded after the initial title and abstract screening and the full-text eligibility assessment. After the full-text eligibility assessment, 25 articles were included in the extraction phase.

[Insert Figure 1 here]

Risk of Bias Assessment and Quality of Evidence The Newcastle-Ottawa Quality Assessment Scale (NOS) was used to critique and analyse the methodological quality of each article. The NOS assesses the risk of bias and methodological quality of case-control, cohort articles and cross-sectional studies (Modesti et al., 2016; Wells et al., 2009). The NOS for cross-sectional studies was used in this review.

The NOS evaluates studies across seven items grouped into three categories; selection, comparability and outcome. Each article is scored using a star system out of a maximum of ten stars over the three categories. Articles scored well in the selection category if; 1) participants were considered representative or relatively representative of the average of the target population, 2) the sample size was justified and satisfactory, 3) comparisons were made between the characteristics of respondents and non-respondents and 4) if a validated or non-validated but widely available or well-described measurement tool was used to ascertain exposure. In the comparability section, articles scored well if one or more confounding factor was controlled for. Articles scored well in the outcome section if outcomes were assessed independently and blindly, through record linkage or self-report and if the statistical test used to analyse the data was clearly described, appropriate and measurement of the association (i.e. confidence intervals, probability level, etc.) was reported. NOS ratings were applied by DR and CG, and a randomly selected 25% were reviewed by independent reviewers (EM, SJW). An agreement rating of 95% was achieved and disagreements between reviewers were resolved by consensus.

Data Extraction

11 A data extraction sheet was developed and pilot-tested on ten articles, refined accordingly and applied to all articles. Data regarding participant characteristics were extracted and are listed in Table 1, including population type (e.g. clinical GAD/MDD, non-clinical HTA/dysphoria), sample size, age, gender, primary psychometric measure and score and secondary (i.e. comorbid) psychometric measure and score. Only co-morbidities relating to anxiety and depressive symptoms were extracted. The primary psychometric measures of interest were the Beck Depression Inventory (BDI; Beck, Steer, & Brown, 1996) and the State-Trait Anxiety Inventory (STAI; Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983). Other anxiety and mood measures were only extracted if the BDI and/or STAI were not available. Any version of the BDI or STAI was accepted. The latter information was extracted for each group in each article that met the specified inclusion criteria. This resulted in data being extracted from two or more groups in some articles (see Table 1 for details). Where two or more groups within an article were drawn from the same population at baseline but assigned to different intervention groups (e.g. in attentional bias modification paradigms), data were extracted from the baseline assessment only and were pooled across groups. Data regarding the experimental paradigm (e.g. EST, DPT etc.), stimulus type (e.g. words, faces, pictures), emotional content (e.g. fearful, sad, neutral) and presentation duration in milliseconds (ms) were also extracted and are listed in Table 2. Only information relating to negative and neutral stimuli were extracted. Positive stimuli were not reported as they did not relate to the topic under investigation (i.e. concern-related attentional biases).

As mentioned earlier, for consistency the term ‘facilitation’ will be used for the attentional bias component measuring faster detection of negative stimuli relative to neutral stimuli (also referred to as engagement, orienting or vigilance in the included articles). No synonyms were encountered during the extraction phase with regards to the terms ‘difficulty in disengagement’ and ‘attentional avoidance’. ‘Interference inhibition’ is an additional term reported in relation to the EST. Although it has been argued that the interference effect in the EST may relate either to delayed disengagement or a generic slowdown effect in the presence of emotional stimuli, it is a widely used attentional bias paradigm and hence, will be included in this review.

[Insert Table 1 here]

Data Analysis Plan Calculating component bias scores

12 Where component bias scores were reported in the article, they were extracted and recorded in Table 2. Where component bias scores were not reported, they were calculated from the reported reaction time data using the formula listed in the article. Component bias scores calculated in this way are indexed by a single asterisk in Table 2. If the authors did not report a specific formula, a standard formula from the literature was used (see Appendix B). Studies for which standard formulae were used are indexed by a double asterisk in Table 2.

[Insert Table 2 here]

Determining component presence Where component bias scores were directly compared against zero (i.e. no bias), reported p values were extracted and recorded in Table 2. However, p values were seldom reported for within-group component bias scores. If p values were not reported, but the mean and standard deviation of a component bias score were reported, a one sample t-test was performed to detect if the component bias score was significantly different from zero. Studies for which the p value was calculated by the reviewers are indexed by a triple asterisk in Table 2. Where p values were reported or calculated, the presence of a bias component was determined on the basis of a p value less than .05. Standard deviations of bias scores were however seldom reported in the included studies, and one-sample t-tests could therefore not be performed for every component bias score. In the absence of reported or calculated p values, the presence of a bias component was determined on the basis of a non-zero bias score in the expected direction. Unfortunately, the absence of published standard deviations for many of the bias scores listed in Table 2 precludes a meta-analysis of these data.

Determining component magnitude Component bias scores were reported as both positive and negative values; however, this often reflected the specific formula used rather than the direction of effect. For example, negative scores using the formula mean RT congruent - mean RT baseline on the DPT (Carlson & Mujica-Parodi, 2015) are suggestive of facilitation; however positive scores using the formula mean RT valid/neutral - mean RT valid/negative on the ECT (Koster, De Raedt, et al., 2005b) are also suggestive of facilitation. Hence, when discussing the magnitude of detected components, the absolute value of bias scores will be reported.

13 14 Results

Participant Characteristics Of the 25 articles included in the extraction phase, data were extracted from a total of 1,433 participants. Reported age means ranged from 19 to 49.4 years. The percentage of male participants in each study ranged from 0% to 50%. Eleven papers assessed individuals with anxiety disorders only, including 32 cases of clinical anxiety and 504 cases of sub-clinical anxiety. Three articles assessed individuals with depressive disorders only, totalling 29 cases of clinical depression and 383 cases of sub-clinical depression, including two samples of individuals in remission from MDD (De Raedt et al., 2012; Elgersma et al., 2018). Co-occurring symptoms were measured in 12 of the 25 included articles; eight articles measured co-occurring depressive symptoms in anxiety, including 142 cases of clinical anxiety and 185 cases of subclinical anxiety, and four measured co- occurring anxiety symptoms in depression, including 123 cases of clinical depression and 35 cases of subclinical depression. Note that this accounting includes one paper which separately assessed samples with ‘pure’ MDD and mixed MDD/anxiety disorde (Elgersma et al., 2018). See Table 1 for participant details.

Experimental Paradigm Characteristics Of the 25 included articles, 12 used the DPT or modifications thereof, nine used the ECT, four used the EST and one used the NAPT. One article (Mogg et al., 2000), used both the DPT and the EST.

The most commonly used stimulus type was words (N = 14), then faces (N = 6) pictures (N = 7) and sounds (N = 1). One article (Lee & Knight, 2009) used words, faces and pictures across different conditions of the DPT.

Many articles did not report the specific emotional content of stimuli used and instead made generic references to ‘negative’ stimuli. Of those articles which did specify the emotional content of their stimuli, the types of emotional content included angry, fearful, sad, disgusted, socially threatening, physically threatening, nonspecific threatening and neutral.

Stimulus presentation durations ranged from 20ms to 33ms in masked conditions and from 100ms to 1500ms in unmasked conditions. In three studies, stimuli were programmed to remain on screen until responses were registered (Dai & Feng, 2011; De Raedt et al., 2012; Mogg et al., 2000), and non-computerised methods were used in one (Martin et al., 1991).

15 Methodological Quality The methodological quality of all 25 articles was critiqued using the NOS. Summary scores are listed in Table 1, and details of category scores may be found in Appendix A. The included studies scored between four and seven stars out of a potential 10 stars.

Component Presence and Magnitude In order to investigate attentional bias components distinct and common to anxiety, depression and co-occurring anxiety and depression, articles included in the review were divided into four groups according to population type; 1) anxiety alone (i.e. where co-occurring symptoms were not measured), 2) depression alone, 3) anxiety where depressive symptoms were measured, and 4) depression where anxiety symptoms were measured.

Anxiety alone In this group, facilitation was assessed in eight articles and observed in five, all of which assessed populations with subclinical levels of anxiety. Facilitation towards negative or threatening stimuli was observed using both the DPT (Carlson & Mujica-Parodi, 2015; Lee & Knight, 2009) and the ECT (Li, Li, & Luo, 2005a; Sagliano, Trojano, Amoriello, Migliozzi, & D'Olimpio, 2014; Wang, Xiao, Luo, & Yang, 2019), using faces, words and picture stimuli with stimulus durations ranging from 20ms (Lee & Knight, 2009) to 1000ms (Wang et al., 2019) in both masked and unmasked conditions. Facilitation bias scores ranged from 1ms (Lee & Knight, 2009) to 32ms (Wang et al., 2019). In three of these papers (Carlson & Mujica-Parodi, 2015; Li et al., 2005a; Sagliano et al., 2014), the facilitation bias scores were reported or computed to be significantly different from zero (p < .05); statistical significance could not be determined for the bias scores reported in the remaining papers (Lee & Knight, 2009; Wang et al., 2019). While a relatively large effect (32ms) was observed by Wang and colleagues, the facilitation biases reported by Lee and Knight were of considerably smaller magnitude (all  6ms). Three papers failed to detect evidence of facilitation using the DPT (Chau, Tse, So, & Chan, 2019; Koster, Crombez, Verschuere, & De Houwer, 2006) and the ECT (Sagliano, D'Olimpio, Taglialatela Scafati, & Trojano, 2016); Chau and colleagues evaluated a population with clinical GAD, while the others employed subclinical samples. All presented threatening stimuli at durations ranging from 100ms (Sagliano et al. 2016) to 500 ms (Chau et al., 2019; Koster et al. 2006). P values greater than .05 were computed or reported for the attentional bias scores presented in all three papers.

16 Five papers sought evidence of avoidance in this population, but only one paper (Lee & Knight, 2009) reported evidence of it, using the DPT with a variety of negative stimuli at stimulus durations of both 20ms and 1500ms. No p values were reported or computed for this paper, and the attentional bias values reported are mostly small, with the exception of a 49ms bias away from briefly presented angry faces. Four other papers examined avoidance of threatening stimuli using the DPT (Booth, 2014; Chau et al., 2019) and ECT (Sagliano et al., 2016; Sagliano et al., 2014), with stimulus durations ranging from 100ms to 750ms; p values were reported or computed for each of these papers, but no statistically significant avoidance effects were observed.

Of the six papers which sought evidence of delayed disengagement in anxiety, four found evidence for it using the DPT (Carlson & Mujica-Parodi, 2015; Koster, Crombez, Verschuere, & De Houwer, 2006) and ECT (Sagliano et al., 2016; Wang et al., 2019). Negative or threatening stimuli were presented for durations ranging from the very brief (33ms) to very long (1000ms). Statistically significant effects were observed in three studies, with bias scores between 4ms (Carlson & Mujica- Parodi, 2015) and 37ms (Koster et al., 2006). Wang and colleagues did not provide p values for bias scores, and insufficient data were available to allow their calculation, however a delayed disengagement bias of 18ms was observed in this study. Two papers (Li et al., 2005a; Sagliano et al., 2014) did not observe statistically significant delayed disengagement in response to threatening stimuli presented in the ECT. All of these studies were conducted with individuals with subclinical levels of anxiety.

Only one paper (Fox, 1994) sought evidence of interference inhibition in this group, using the EST with a subclinical sample. The expected effects were not detected for either physical or social threat.

Depression alone Three papers examined individuals with symptoms of depression but no reported comorbid anxiety; two of these papers reported the presence of facilitation. Using the NAPT, De Raedt et al. (2012) found statistically significant evidence of facilitated engagement with negative pictures among a sample of remitted MDD patients, with a bias score of approximately 16ms. LeMoult, Arditte, D'Avanzato, & Joormann (2013) reported facilitated engagement with angry (but not sad) faces among dysphoric students; the magnitude of the effect was however very small (2.38ms) and no p values were reported or computed. Elgersma et al. (2018) also investigated this component in

17 both clinically depressed and formerly depressed samples using the ECT, but reported no significant facilitation effects.

Elgersma et al. (2018) did however observe significant avoidance of threatening stimuli among both currently and formerly depressed participants; specifically, they found evidence of negative (but not threatening) stimuli at long stimulus durations (1250ms) but not at briefer durations (500ms) among patients with MDD. The participants currently in remission demonstrated a similar avoidance of negative stimuli during long presentations, but also showed avoidance of threatening stimuli at both presentation durations. No other papers investigated avoidance among depressed patients without comorbid anxiety.

Only one study (LeMoult et al., 2013) investigated delayed disengagement among depressed participants. Using the ECT, some difficulty disengaging from angry faces was detected. The magnitude of the bias was small however (2.2ms), and statistical significance could not be computed.

No studies sought evidence for interference inhibition in this population.

Anxiety with co-morbid depression Nine papers examined the facilitation bias component within this population. Four papers, all using the DPT with threatening stimuli presented for between 500ms and 1200ms, reported evidence of facilitation (Bradley, Mogg, White, Groom, & de Bono, 1999; MacLeod et al., 1986; Sass, Evans, Xiong, Mirghassemi, & Tran, 2017; Teng, Hou, Chang, & Cheng, 2019). MacLeod et al (1986) employed a clinical GAD sample, while the remaining three papers observed facilitation effects in subclinical populations only. Sass et al. (2017) and Teng et al (2019) reported bias scores (approximately 10ms and 23ms respectively) that were significantly different from zero. Bradley et al. (1999) and MacLeod et al. (1986) reported mean bias scores ranging in magnitude from 9 to 59ms across different conditions, however it could not be determined whether these values differed significantly from zero. Five papers failed to find evidence of facilitation in this population, using the DPT (Chen, Clarke, Watson, MacLeod, & Guastella, 2015; Mogg et al., 2000; Taylor, Cross, & Amir, 2016), ECT (Heeren, Mogoase, McNally, Schmitz, & Philippot, 2015) and EST (Martin et al., 1991), with threatening stimuli presented for a minimum of 500ms. All of these studies were conducted with subclinical populations, with the exception of Heeren et al. (2015), who examined individuals with clinical social anxiety disorder.

18 Avoidance was observed in only one study within this population; Bradley et al. (1999) reported avoidance of angry faces among a clinical GAD population. No p values were reported or computed, but bias scores of 12ms and 10ms were reported at 500ms and 1250ms stimulus durations, respectively. Four other papers examined the avoidance component, but did not find evidence of it using the DPT with clinical (MacLeod et al., 1986) and subclinical samples (Chen et al., 2015), using the ECT in a sample with clinical social anxiety (Heeren et al., 2015) or in a sample of subclinically anxious students using the EST (Martin et al., 1991). All stimuli were presented for a minimum of 500ms.

Only one paper (Taylor et al., 2016) investigated delayed disengagement among anxious participants with comorbid symptoms of depression, but they did not find statistically significant effects.

Two papers reported interference inhibition in response to threatening stimuli in the EST. Martin et al. (1991) observed the effect among clinical GAD patients and medium trait anxiety students, but not high trait anxiety students; statistical significance could not be determined for this study. Mogg et al. (2000) reported significant levels of interference inhibition among high trait anxiety students. The magnitude of the bias detected by Mogg and colleagues (10ms) was considerably larger than those reported by Martin et al. (4.3ms for the GAD sample and 0.9ms for the student sample).

Depression with comorbid anxiety Four studies measured comorbid anxiety symptoms in depression. Of these, three sought evidence of facilitation, and one (Leyman et al., 2007) reported significant effects. Using the ECT, Leyman and colleagues reported a relatively small (9ms) but statistically significant bias towards angry faces among patients with clinical MDD and high trait anxiety. Elgersma et al. (2018) examined a similar population, but found no evidence of facilitated engagement with negative or threatening stimuli. Similarly, in a study of dysphoric students with comorbid anxiety, Koster et al. (Koster, De Raedt, et al., 2005b) did not observe facilitated engagement with negative words.

No studies reported avoidance of negative or threatening stimuli among this population. Elgersma et al. (2018) examined this component using an ECT with negative and threatening words, but found no evidence of avoidance in a mixed MDD/anxiety population.

19 Two studies examined delayed disengagement from negative stimuli in the ECT. Koster et al. (Koster, De Raedt, et al., 2005b) found evidence of delayed disengagement (with bias scores ranging between 12 and 22ms) among dysphoric students with anxiety, while Leyman et al. (2007) did not find any such effects among a clinical MDD population with comorbid anxiety.

Finally, one study (Dai & Feng, 2011) reported interference inhibition in this sample using the EST with negative words; a relatively large bias (~18ms) was observed, but no p values were reported or computed.

20 Discussion

This review aimed to investigate the components of attentional bias (i.e. facilitation, delayed disengagement and attentional avoidance) found in anxiety and depression. Specifically, the study aimed to establish which components of attentional bias were commonly found in anxiety and depression, which were distinct to anxiety and/or depression and which were common to both. Given reports of such high comorbidity rates between these two disorder groups (Goldberg et al., 2009; Hirschfeld, 2001) and research highlighting the transdiagnostic nature of attentional biases in mental health disorders (Garland & Howard, 2014), it was hypothesised that one or more components of attentional bias would be common to both anxiety and depression.

A total of 25 articles with 1433 participants were included in the review. The included articles reported the presence of facilitation, avoidance and delayed disengagement in anxiety alone, depression alone and in co-occurring anxiety and depression. Hence, there is preliminary evidence regarding the transdiagnostic nature of attentional bias components across anxiety and depression. However, the magnitude of component bias effects varied across and within disorder groups, depending on a number of experiment-related variables (e.g. paradigm, stimulus type, stimulus content, exposure duration). Most articles compared the magnitude of component bias scores across groups (i.e. differences between clinical/subclinical and control groups) rather than the magnitude of bias scores within groups (i.e. difference between bias scores and zero/no bias effect). These bias scores were computed from available data where possible, however statistical significance could not be determined for the bias scores from nine studies, due to insufficient data reported in the individual articles. Standard deviations of bias scores were only provided for ten out of the 25 studies included in the review; meta-analysis of these data was therefore precluded.

Hence, an overview of the findings will be outlined to highlight variations in presence and magnitude of component bias scores across and within groups with the caveat that significance could not be established for every effect (see Table 2 for details regarding significance of bias scores).

21 Facilitation (i.e. faster detection of concern-related stimuli relative to neutral stimuli) was detected in 34% of experimental conditions included in the review. Facilitation was evident across anxiety, depression and co-occurring anxiety and depression. Facilitation bias scores in anxiety alone were mostly rather small, with the exception of Wang et al. (2019), who reported a facilitation bias of 32ms in anxiety. This was the only study to use auditory stimuli, which may have affected overall response times. Unfortunately no data on variability were provided, so it is impossible to determine whether this effect was observed consistently across participants. Two out of three papers detected facilitation in depression, but one (LeMoult et al., 2013) reported very small effects (less than 3ms) and statistical significance could not be determined. A facilitation bias of 16ms was reported in a depressed sample by de Raedt et al. (2012); this was the only article to utilise the NAPT as all other articles utilised the DPT or ECT. It is therefore possible that the enhanced facilitation effects are due to the experimental task, but this explanation must remain speculative until further research using this task is published. In general, facilitation bias scores suggest that the rate at which anxious and depressed populations attend to concern-related stimuli is only marginally faster than the rate at which they attend to neutral stimuli. These effects are small and may not be clinically meaningful. Facilitation bias scores detected in co-occurring anxiety and depression ranged from 9ms (Leyman et al., 2007) to 59ms (MacLeod et al., 1986). This range is much larger, possibly suggesting that facilitation effects increase in-line with clinical complexity, but it should be noted that several of the larger effects were reported without information on variability. This finding requires further investigation from studies recruiting more heterogeneous and clinically representative populations, as it is widely acknowledged that comorbidity is the norm rather than the exception in clinical practice (Nemeroff, 2002).

Facilitation was detected at both short (e.g. 33ms; Carlson & Mujica-Parodi, 2015) and long stimulus durations (e.g. 1000ms; Wang et al., 2019) in anxiety. Facilitation was also detected at relatively short (200ms; LeMoult et al., 2013) as well as longer stimulus durations in depression (De Raedt et al., 2012). Previous theories have assumed that attentional biases operate at the early stages of information processing in anxiety and the later stages of processing in depression (Williams et al., 1988). Whilst some of the evidence in this review supports this longstanding theory (Carlson & Mujica-Parodi, 2015; De Raedt et al., 2012), results from other studies were inconsistent with these assumptions. For example, facilitation was detected at longer stimulus durations in anxiety (1500ms; Lee & Knight, 2009) and shorter stimulus durations in depression

22 (200ms; LeMoult et al., 2013). The latter results are in-line with a meta-analysis which found almost identical effect size estimates for studies using longer and shorter stimulus durations in depression (Peckham et al., 2010). Hence, there appears to be evidence in support of facilitation at both shorter and longer stimulus durations in both anxiety and depression and longstanding theories (Williams et al., 1988) may require revision to reflect these new findings. Importantly, only two studies (Carlson & Mujica-Parodi, 2015; Lee & Knight, 2009) investigated facilitation using subliminal stimulus durations (33ms and 20ms respectively), and both assessed anxious students with no reported comorbidities. There were no studies with very brief presentation times that assessed clinical anxiety or any form of depression. There is therefore insufficient evidence to support the idea that briefly presented stimuli have pre-attentive effects on performance in anxiety but not depression.

Attentional avoidance (i.e. allocation of attention away from concern-related stimuli) was detected in approximately 23% of experimental conditions investigating that component, across three papers. Statistically significant bias scores between 5ms and 17ms were observed in the depression alone group (Elgersma et al., 2018). The magnitude of attentional avoidance effects ranged from less than 3ms to 49ms in the anxiety alone group (all reported by Lee & Knight, 2009, without p values), and from 10ms to 12ms in the co-occurring anxiety and depression groups (Bradley et al., 1999, again reported without p values). These findings suggest that individuals with anxiety and depression may be inclined to direct their attention away from concern-related stimuli, but it is also important to note that a range of papers found no evidence of attentional avoidance in anxiety, with and without co-occurring symptoms of depression (Booth, 2014; Chau et al., 2019; Chen et al., 2015; Elgersma et al., 2018; Heeren et al., 2015; MacLeod et al., 1986; Martin et al., 1991; Sagliano et al., 2016; Sagliano et al., 2014).

It is nevertheless interesting that some of the larger effects were observed in subclinical rather than clinical groups, consistent with the theory that subclinical populations avoid threatening stimuli at shorter presentation durations as an adaptive mechanism to keep anxiety levels under control (Sagliano et al., 2014). However, avoidance of threatening stimuli at later stimulus presentations was also observed with a clinically anxious population (Bradley et al., 1999), consistent with the vigilance-avoidance hypothesis, which proposes that anxious individuals direct their attention towards threatening stimuli during the early stages of processing (e.g. <500ms) and direct their attention away from threatening stimuli during the later stages of processing (e.g. >500ms; (Mogg et al., 2004). Hence, attentional avoidance may play an adaptive role when

23 threatening stimuli are present for a short period of time and a more maladaptive role when stimuli are present for a longer period (i.e. as habituation does not occur and anxiety symptoms are maintained over-time). Avoidance of threatening stimuli presented for 1250ms was observed in both clinically and subclinically depressed populations (Elgersma et al., 2018), suggesting that these effects may not be specific to anxiety. Further research into the adaptive and maladaptive role of attentional avoidance in clinical and subclinical populations is required to shed light upon this complex phenomenon.

The third component of attentional bias, delayed disengagement (i.e. slower attentional shifting away from concern-related stimuli due to enhanced attentional capture), was detected in 40% of experimental conditions included in the review. Delayed disengagement was detected in the majority of papers in the anxiety alone group (Carlson & Mujica-Parodi, 2015; Koster, Crombez, Verschuere, & De Houwer, 2006; Sagliano et al., 2016; Wang et al., 2019). The magnitude of delayed disengagement effects ranged from approximately 4ms to 37ms, and p values were reported or computed for each of these studies. One of the three papers which examined this component in co-occurring anxiety and depression successfully detected it, and reported statistically significant bias scores of 12ms and 22ms (Koster, De Raedt, et al., 2005b). Only one article detected delayed disengagement in the depression alone group (LeMoult et al., 2013), and effects were marginal (2ms). These bias scores suggest slightly slower disengagement from concern-related stimuli in anxiety and in co-occurring anxiety and depression groups, but do not provide clear evidence for the presence of a delayed disengagement bias in depression. These findings only partially support the delayed disengagement hypothesis which suggests that symptoms of anxiety and depression are maintained due to difficulties in shifting attention away from negative stimuli (Koster, De Raedt, et al., 2005b).

Delayed disengagement effects were detected using the DPT and ECT paradigms (Carlson & Mujica-Parodi, 2015; Koster, Crombez, Verschuere, & De Houwer, 2006; Koster, De Raedt, et al., 2005b; LeMoult et al., 2013; Sagliano et al., 2016; Wang et al., 2019). They were detected at both short (33ms; Carlson & Mujica-Parodi, 2015; 100ms; Sagliano et al., 2016) and longer (>500ms; Koster, Crombez, Verschuere, & De Houwer, 2006; Sagliano et al., 2016; Wang et al., 2019) stimulus durations in anxiety, and at longer durations (1500ms; Koster, De Raedt, et al., 2005b) in comorbid anxiety and depression. These findings are interesting as previous reviews have associated delayed disengagement with the later stages of processing in anxiety (Cisler & Koster, 2010). One article in the review even detected delayed disengagement in subliminal conditions

24 (Carlson & Mujica-Parodi, 2015). The authors of the latter article advocate for further research into the time course of delayed disengagement using both masked and unmasked stimuli.

Interference inhibition is a term used in relation to the EST only, as it has been argued that slower reaction times on emotional trials relative to neutral trials in the EST may reflect either delayed disengagement or a generic slowdown effect in the presence of concern-related stimuli (Algom et al., 2004; Fox, 2004). Nonetheless, given the widespread use of the EST in attentional bias research, interference inhibition was reviewed. This component was detected in 36% of conditions assessed in co-occurring anxiety and depression (Dai & Feng, 2011; Martin et al., 1991; Mogg et al., 2000); it was not detected in anxiety alone and not measured in depression alone. The magnitude of effects ranged from approximately 2ms to 45ms, although it should be noted that the largest effects were observed in a study which used non-computerised methods, and thus can be assumed to have recorded response times with less precision (Martin et al., 1991). There were insufficient studies using the EST to state with any confidence whether interference inhibition is specific to co- occurring anxiety and depression, or whether it might also be detectable in less complex diagnostic categories.

To summarise, the included articles demonstrated reasonably strong evidence of facilitation and delayed disengagement in anxiety, consistent with existing evidence (see Cisler et al., 2009; Cisler & Koster, 2010 for narrative reviews). In contrast, only weak evidence for avoidance was observed in this population, with the majority of included studies not reporting substantial or significant avoidance effects (Booth, 2014; Chau et al., 2019; Sagliano et al., 2016; Sagliano et al., 2014). Facilitation and avoidance were both demonstrated in depression, albeit in a small number of papers (De Raedt et al., 2012; Elgersma et al., 2018; LeMoult et al., 2013), but only very weak evidence for delayed disengagement was observed (LeMoult et al., 2013). Among papers investigating co-occurring anxiety and depression, evidence for facilitation was very mixed, with almost half of the included studies reporting facilitated engagement with negative or threatening stimuli (Bradley et al., 1999; Leyman et al., 2007; MacLeod et al., 1986; Sass et al., 2017; Teng et al., 2019). There was some evidence for delayed disengagement among this group (Koster, De Raedt, et al., 2005b), but only very weak evidence for avoidance, with only one study out of six (Bradley et al., 1999) reporting significant effects. Figure 2 provides an illustration of results; note that as meta analyses could not be performed on these data, the relative strength of evidence for each bias component is based on a qualitative rather than quantitative synthesis of the data, based

25 on the number of papers assessing each component and the magnitude and statistical significance of the reported bias scores.

[Insert Figure 2 here]

The findings of this review are suggestive of the transdiagnostic nature of attentional biases across anxiety and depression. Although many of the effects observed in this review were relatively small and one might therefore question their clinical relevance, it could very well be that components of attentional bias have a stronger impact on the daily functioning of anxious and depressed individuals than the present results indicate. In many of the experimental paradigms included in this review, the concern-related stimulus did not require action (i.e. participants were instructed to attend to the probe location or word colour). It is plausible that in real life, concern-related stimuli often require action and may therefore pose stronger effects on the components of attention.

There were several limitations to this review. The articles included in the review were highly heterogeneous in terms of methodologies and experimental paradigms. A number of articles did not report p values or sufficient reaction time data for one sample t-tests to be calculated, and meta-analysis could not be performed. Hence, many of the conclusions of the review are made tentatively. In addition, although articles were grouped by population type (e.g. anxiety alone, depression alone etc.), it is important to note that the number of articles in each group was not equal and hence percentages regarding detection of components in specific groups must be interpreted cautiously; failure to detect a particular component in small number of papers is not necessarily indicative of the absence of that component in a particular population. Similarly, the articles included in the review may also reflect bias in terms of reported results, as null results (i.e. lack of component detection) are often not reported or published in the literature. Lastly, the quality of the articles included in the review as rated by the NOS quality rating scale for cross- sectional studies ranged from four to seven out of ten stars. It is particularly noteworthy that none of the included articles utilised random sampling, and only one justified their sample size; many of the studies employed relatively small samples and thus may have been underpowered.

Future attentional bias component research would benefit from establishing the presence or absence of bias effects within population groups (i.e. by performing one-sample t-tests against zero) as well as comparing bias scores across population groups (e.g. clinical versus control groups). Such research would aid our understanding of the possible dimensionality of bias effects

26 and investigate whether bias magnitude increases dimensionally across control, subclinical and clinical groups. Clinical studies should endeavour to recruit clinically representative populations which are truly reflective of the complexity and comorbidity rates observed in clinical settings. Additionally, future research should focus on clarifying the presence or absence of avoidance and delayed disengagement in depression, as very few studies included in the review addressed this population. More research utilising the NAPT is also required to decipher whether the larger facilitation effects detected in one article in this review are task-specific or related to population type. Finally, future studies would benefit from improving the quality of their methodology through random sampling techniques and providing justifications of sample sizes used through reporting power analyses.

The findings of this review shed light upon decades of attentional bias research, which to date has largely taken a disorder-specific approach and focused upon the attentional bias effect as a whole rather than its components (see Bar-Haim et al., 2007 for reviews; Peckham et al., 2010). Now that the attentional bias effect is well-established across anxiety and depression, it is important to understand how the effect occurs (i.e. its underlying mechanisms), as sensitised and rapid detection (i.e. facilitation) and poor attentional shifting/inhibition (i.e. delayed disengagement) are mechanistically different. An increased understanding of these components will also inform and enhance clinical interventions, such as attentional bias modification training (ABM). ABM has been demonstrated to successfully reduce attentional bias, symptoms and emotional vulnerability in anxious, depressed and healthy participants (Dai, Hu, & Feng, 2019; Mogoaşe, David, & Koster, 2014). However, one of its criticisms is that training-related changes in performance could be due to modulation of either facilitation or disengagement (Bar‐Haim, 2010). Additionally, it has been suggested that ABM may also act through the mechanism of attentional avoidance, which could later contribute to the longer-term maintenance of symptoms (Koster, Baert, Bockstaele, & De Raedt, 2010). Hence, future research which focuses upon the components of attentional bias will inform our understanding of the mechanisms underlying change in ABM and potentially enhance its clinical utility and efficacy.

27 References

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31 32 Tables and Figures

Table 1. Participant characteristics from each included study, split by primary diagnostic category

Study Population N Age Male Primary Score Co-morbidity NOS M (SD) N (%) Measure M (SD) M (SD) Score

Primary diagnostic category: Anxiety

1. Booth (2014) Anxious students 101 21.45 (3.78) 20 (19.80) STAI Trait 43.91 (9.82) - 4 State 36.56 (8.60)

2. Bradley et al. (1999) Clinical GAD 14 36.4 (9.6) 7 (50) STAI Trait 56.00 (7.3) Depression 6 State 48.2 (11.5) BDI-I 18.2 (10.6)

Anxious community 33 31 (11.6) 13 (39.39) Trait 41.1 (11.0) Depression State 36.40 (9.3) BDI-I 7.9 (6.0)

3. Carlson & Mujica- Anxious students 62 20.94 (2.61) 28 (45.16) STAI Trait 39.10 (8.67) - 4 Parodi (2015)

4. Chau et al. (2019) Clinical GAD1 32 46.69 (11.44) 15 (46.87) STAI Trait: 57.42 (9.81) - 7

5. Chen et al. (2015) Socially anxious 43 22.11 (6.2) 9 (20.93) STAI Trait: 42.99 (8.47) Depression 6 students1 DASS-D 8.84 (7.18) 6. Fox (1994) High trait anxiety 18 Not reported Not reported STAI Trait 50.01 (4.9) - 4 students

7. Heeren et al. (2015) Clinical SAD 18 24.72 (8.68) 5 (27.78) STAI Trait 42.89 (7.40) Depression 7 BDI-II 14.78 (7.01)

8. Koster et al. (2006) High trait anxiety 21 Not reported 4 (19.04) STAI Trait 54.76 (3.63) - 6 Study Population N Age Male Primary Score Co-morbidity NOS M (SD) N (%) Measure M (SD) M (SD) Score

students

9. Lee & Knight, 2009 High trait anxiety 103 19.95 (2.12) 16 (15.53) STAI Trait 40.17 (10.95) - 4 students

10. Li et al. (2005) High trait anxiety 15 20 (1.9) 7 (46.67) STAI Trait 59.5 - 4 students

11. MacLeod et al. (1986) Clinical GAD 16 32.16 Not reported STAI Trait 52.5 Depression 6 State 44.7 BDI-I 13.9

12. Martin et al. (1991); High trait anxiety 12 30.7 0 (0) STAI Trait 61.6 Depression 5 Experiment 1 students State 51.3 BDI-I 14.8

Medium trait anxiety 12 26.8 0 (0) Trait 43.5 Depression students State 40.7 BDI-I 9.5

Martin et al. (1991); Clinical GAD 12 36.3 3 (25) STAI Trait 55.4 Depression 6 Experiment 2 State 49.4 BDI-I 16.8

Anxious students 12 28.4 0 (0) Trait 54.7 Depression State 47.4 BDI-I 13.3

13. Mogg et al. (2000) High trait anxiety 16 19.4 8 (50) STAI Trait 52.4 Depression 6 students State 44.8 BDI-I 13.7

14. Sagliano et al. (2014) High trait anxiety 28 22.64 0 (0) STAI Trait 59.18 - 5 students State 46.68 Study Population N Age Male Primary Score Co-morbidity NOS M (SD) N (%) Measure M (SD) M (SD) Score

15. Sagliano et al. (2016) Anxious students 48 19 - 32 24 (50) STAI Trait 40.80 (8.28) - 4 State 41.04 (2.10) 16. Sass et al. (2017) Anxious students1 42 19.86 (2.35) 12 (28.57) MASQ-AA 32.0 (7.8) Depression 6 MASQ-AD 15.9 (2.6)

17. Taylor et al. (2016) Anxious students 75 20.66 (4.43) 34 (45.33%) LSAS-SR 44.58 (26.19) Depression 4 BDI-II - mean not reported

18. Teng et al. (2019) Subclinical GAD1 82 21.48 (1.82) 21 (25.61) STAI State: 52.23 (10.03) Depression: 6 Trait: 54.61 (9.44) BDI-I 19.76 (9.25)

19. Wang et al. (2019) High trait anxiety 33 21.3 (2.1) 13 (39.4%) STAI Trait: 49.30 (7.20) - 5 students

Primary diagnostic category: Depression

20. Dai & Feng (2011) Clinical MDD 17 27.59 (3.74) 8 (47.06) BDI-II 34.71 (7.46) Anxiety 6 BAI 18.76 (3.45)

21. De Raedt et al. (2012) Clinical MDD in 45 45.2 (9.8) 12 (26.67) BDI-II 17.64 (10.34) - 6 remission

Elgersma et al. (2018) Clinical MDD 29 43.76 (14.8) 10 (34.5) IDS-SR 23.71 (9.62) - 6 22. Mixed MDD/AD 86 43.34 (11.9) 28 (32.7) IDS-SR 32 (10.4) Anxiety CIDI scores not reported Clinical MDD in 294 44.50 (13.29) 105 (35.4) IDS-R 10.98 (7.58) - remission Study Population N Age Male Primary Score Co-morbidity NOS M (SD) N (%) Measure M (SD) M (SD) Score

23. Koster et al. (2005); High dysphoria students 15 19.07 5 (33.33) BDI-II 16.00 Trait anxiety 6 Experiment 1 STAI-T 46.33

Koster et al. (2005); High dysphoria students 20 22.08 0 (0) BDI-II 15.2 Trait anxiety 6 Experiment 2 STAI-T 52.60

24. LeMoult et al. (2013) High dysphoria students 44 19.48 (3.42) 17 (38.64) CES-D Not reported - 6

25. Leyman et al. (2007) Clinical MDD 20 45.50 (11.05) 5 (25) BDI-II 34.90 (8.83) Trait anxiety 6 STAI-T 55.20 (13.48)

Note: BDI = Beck Depression Inventory; BAI = Beck Anxiety Inventory; CES-D = Center for Epidemiologic Studies Depression Scale; CIDI = Composite International Diagnostic Interview; DASS-D = Depression, Anxiety and Stress Scales – Depression; GAD = Generalised Anxiety Disorder; IDS-SR = Inventory of Depressive Symptoms Self-Report; LSAS-SR = Liebowitz Social Anxiety Scale - Self-Report; MDD = Major Depressive Disorder; SAD = Social Anxiety Disorder; STAI = State and Trait Anxiety Inventory; MASQ-AA = Mood and Anxiety Symptom Questionnaire - Anxious Arousal; MASQ-AD = Mood and Anxiety Symptom Questionnaire - Anhedonic Depression;

1 Baseline data pooled across intervention groups drawn from the same population Table 2. Task characteristics and attentional bias scores from each included study, split by primary diagnostic category

Study Task Stimulus Emotional Component Formula Group† Stimulus Bias p Presence of Type Content Assessed Duration ms (SD) component (ms) Primary diagnostic category: Anxiety 1. Booth DPT Words Threat Avoidance Mean RT incongruent - 750 2.95 .42*** - (2014) mean RT congruent (36.22) Negative score = avoidance

2. Bradley et DPT Faces Angry Facilitation/ Mean RT incongruent - Clinical GAD 500 -12* Avoidance al. (1999) Avoidance mean RT congruent Positive score = 1250 -10* Avoidance facilitation, negative Community 500 9* Facilitation score = avoidance 1250 43* Facilitation

3. Carlson & DPT Faces Fearful Facilitation Mean RT congruent - 33 -4.17 .04 Facilitation Mujica- mean RT baseline (15.52) Parodi Negative score = 133 -6.02 <.01 Facilitation (2015) facilitation (12.75)

Delayed Mean RT incongruent - 33 4.34 .03 Delayed Disengagement mean RT baseline (14.88) Disengagement Positive score = delayed 133 6.31 <.01 Delayed disengagement (13.71) Disengagement Study Task Stimulus Emotional Component Formula Group† Stimulus Bias p Presence of Type Content Assessed Duration ms (SD) component (ms) 4. Chau, et DPT Faces Threat Facilitation/ [(Upper probe lower 500 -2.19 .41*** - al. (2019) Avoidance threat - upper probe (14.74) upper threat) + (lower probe upper threat - lower probe lower threat)]/2. Positive score = facilitation, negative score = avoidance

5. Chen, et DPT Words Social Facilitation/ Mean RT incongruent - 500 -4.78 .12*** - al. (2015) Threat Avoidance mean RT congruent (19.99) Positive score = facilitation, negative score = avoidance

6. Fox (1994) EST Words Physical Interference RT threat - RT neutral 200 - 6* - Threat Inhibition Positive score = interference inhibition** Social - 6* - Threat

7. Heeren, et ECT Words Social Facilitation Mean RT valid/neutral - 600 - 0.48* - al. (2015) Threat mean RT valid/threat Positive score = facilitation

8. Koster, et DPT Pictures Threat Facilitation Mean RT congruent - 500 18 >.05 - al. (2006) mean RT baseline Negative score = facilitation Study Task Stimulus Emotional Component Formula Group† Stimulus Bias p Presence of Type Content Assessed Duration ms (SD) component (ms) Delayed Mean RT incongruent - 37* >.05 Delayed Disengagement mean RT baseline Disengagement Positive score = delayed disengagement

9. Lee & DPT Faces Angry Facilitation/ Mean RT incongruent - 20 -49* Avoidance Knight Avoidance Mean RT congruent 1500 -3* Avoidance (2009) Sad Positive score = 20 -10* Avoidance facilitation, negative 1500 6* Facilitation Words Negative score = avoidance 20 1* Facilitation 1500 -3* Avoidance Pictures High 20 -10* Avoidance Threat 1500 2* Facilitation

10. Li et al. ECT Pictures Threat Facilitation Mean RT valid/neutral 600 6* .029 Facilitation (2005) cue - mean RT valid/emotional cue Positive score = facilitation **

Delayed Mean RT -1* .68 - Disengagement invalid/emotional cue - Mean RT invalid/neutral cue Positive score = delayed disengagement **

11. MacLeod DPT Words Threat Facilitation Mean RT Incongruent 500 Upper et al. Avoidance trials - mean RT probe Facilitation (1986) congruent trials 59.16* Positive score = Lower Facilitation facilitation, negative probe Study Task Stimulus Emotional Component Formula Group† Stimulus Bias p Presence of Type Content Assessed Duration ms (SD) component (ms) score = avoidance ** 31.95*

12. Martin et EST Words Physical Interference RT emotional words - High Trait Until -31.25* - al. (1991) Threat Inhibition RT neutral words Anxiety response Exp. 1 Social Positive score = -9.37*a - Threat interference **

Physical Medium -6.25* - Threat Trait Anxiety Social 9.37* Interference Threat Inhibition

Martin et EST Words Physical Interference RT emotional words - GAD Until -4.17* - al. (1991) Threat Inhibition RT neutral words = response Exp. 2 Social Positive score = Interference Threat interference ** 44.79* Inhibition

Physical Anxious - Threat Student -36.46* Social - Threat -16.67*

13. Mogg et DPT Words Social Facilitation/ Mean RT incongruent - 500 -6.3* >.05 - al. (2000) Threat Avoidance mean RT congruent Physical Positive score = 1.2* >.05 - Threat facilitation, negative score = avoidance

EST Words Social Interference Mean RT threat - mean Until 10.1* <.05 Interference Threat Inhibition RT neutral response Inhibition Physical Positive score = 2.5* >.05 - Threat interference Study Task Stimulus Emotional Component Formula Group† Stimulus Bias p Presence of Type Content Assessed Duration ms (SD) component (ms)

14. Sagliano et ECT Pictures Threat Facilitation/ Mean RT valid/neutral 100 5.6* .049 Facilitation al. (2014) Avoidance cue – mean RT 200 >.05 - valid/threat cue 1.88* Positive score = 500 >.05 - facilitation, negative -5.96* score = avoidance

Delayed Mean RT invalid/threat 100 13.65* .059 - Disengagement cue – mean RT 200 5.76* >.05 - / Avoidance invalid/neutral cue -7.21* >.05 - Positive score = delayed disengagement, 500 negative score = avoidance

15. Sagliano et ECT Pictures Threat Facilitation/ Mean RT valid/neutral 100 -0.36 .92*** - al. (2016) Avoidance −mean RT valid/threat (24.94) Positive score = 200 -2.64 .53*** - facilitation, negative (28.75) score = avoidance 500 -2.30 .66*** - (35.75)

Delayed Mean RT invalid/threat 100 21.78 .004 Delayed Disengagement − mean RT (49.39) Disengagement / Avoidance invalid/neutral Positive 200 -9.85 .13*** - score = delayed (43.44) disengagement, 500 -4.52 .55*** - negative score = (52.31) avoidance Study Task Stimulus Emotional Component Formula Group† Stimulus Bias p Presence of Type Content Assessed Duration ms (SD) component (ms)

16. Sass et al. DPT Words Threat Facilitation Mean RT incongruent - 500 9.69 .002** Facilitation (2017) mean RT congruent (18.78) * Positive score = facilitation

17. Taylor et DPT Faces Disgust Facilitation (Neutral top disgust 500 3.04 .83 - al. (2016) bottom; RT probe distal (117.03) *** disgust - RT probe proximal disgust) - (neutral top & bottom; RT probe top - RT probe bottom) Positive score = facilitation

Delayed (Disgust top neutral -3.77 .76 - Disengagement bottom; RT probe distal (106.45) *** disgust - RT probe proximal disgust) - (neutral top and bottom; RT probe bottom - RT probe top) Positive score = delayed disengagement

18. Teng et al. DPT Words Threat Facilitation Mean RT congruent - 500ms 22.67 <.001 Facilitation (2019) mean RT incongruent (12.25) Positive score = facilitation

19. Wang, et ECT Sounds Negative Facilitation Mean RT valid/neutral - 1000 32.01* Facilitation Study Task Stimulus Emotional Component Formula Group† Stimulus Bias p Presence of Type Content Assessed Duration ms (SD) component (ms) al. (2019) mean RT valid/negative Positive score = facilitation

Delayed Mean RT 17.82* Delayed Disengagement invalid/negative -mean Disengagement RT invalid/neutral Positive score = delayed disengagement

Primary diagnostic category: Depression

20. Dai & Feng EST Words Negative Interference Mean RT emotional - Until 17.64* Interference (2011) Inhibition mean RT neutral response inhibition Positive score = interference

21. De Raedt NAPT Pictures Negative Facilitation Mean RT experimental - Until -15.66 <.05 Facilitation et al. mean RT control response (71.77) (2012) Negative score = facilitation

22. Elgersma ECT Words Negative Facilitation/ (Median RT invalid MDD 500 -16.86 .13*** - et al. Avoidance emotional cue–median (57.79) (2018) RT valid emotional cue) 1250 -17.51 .04*** Avoidance – (median RT invalid (42.77) Threat neutral cue–median RT 500 -11.9 .14*** - valid neutral cue). (42.29) Positive score = 1250 -11.35 .11*** - facilitation, negative (37.52) Negative score = avoidance Mixed 500 -1.56 .80*** - Study Task Stimulus Emotional Component Formula Group† Stimulus Bias p Presence of Type Content Assessed Duration ms (SD) component (ms) MDD/AD (58.16) 1250 -3.14 .55*** - (48.15) Threat 500 -2.24 .71*** - (54.94) 1250 -5.45 .27*** - (45.53) Negative Remitted 500 1.79 .46*** MDD (41.39) 1250 -12.20 <.001* Avoidance (42.45) ** Threat 500 -5.54 .03*** Avoidance (44.67) 1250 -14.37 <.001* Avoidance (48.39) ** 23. Koster et ECT Words Negative Facilitation Mean RT valid/neutral - 1500 10 >.05 - al. (2005) mean RT valid/negative Exp. 1 Positive score = facilitation

Delayed Mean RT 12 <.05 Delayed Disengagement invalid/negative cue - Disengagement Mean RT invalid/neutral cue Positive score = delayed disengagement

Koster et ECT Words Negative Facilitation Mean RT valid/neutral - 250 15* >.05 - al. (2005) mean RT valid/negative 500 -6* >.05 - Exp. 2 Positive score = facilitation 1500 16* >.05 -

Delayed Mean RT 250 -10* >.05 - Disengagement invalid/negative cue - 500 18 .11 - Study Task Stimulus Emotional Component Formula Group† Stimulus Bias p Presence of Type Content Assessed Duration ms (SD) component (ms) Mean RT 1500 22 <.05 Delayed invalid/neutral cue Disengagement Positive score = delayed disengagement

24. LeMoult et ECT Faces Angry Facilitation Mean RT valid/neutral - 200 2.38* Facilitation al. (2013) mean RT valid/emotional Sad Positive score = -2.91* - facilitation

Angry Delayed Mean RT 2.2* Delayed Disengagement invalid/emotional cue - Disengagement Mean RT Sad invalid/neutral cue -0.05* - Positive score = delayed disengagement

25. Leyman et ECT Faces Angry Facilitation Mean RT valid/neutral 1000 9 .007 Facilitation al. (2007) cue - mean RT valid/emotional cue Positive score = facilitation **

Delayed Mean RT 1 >.05 - Disengagement invalid/emotional cue - Mean RT invalid/neutral cue Positive score = delayed disengagement ** Note: DPT = Dot Probe Task; ECT = Exogenous Cueing Task; EST = Emotional Stroop Task; NAPT = Negative Affective Priming Task † Group is provided where more than one sample/population was tested. See Table 1 for details of studied populations * Bias score calculated by reviewers from RT data reported in article ** Formula not reported in article. Standard formula used from Table 2 ***p value derived from one-sample t-test performed by reviewers a Response time data for this article were reported in seconds as the time taken to name the colours on a card with 96 words. Bias scores are estimated per word and recorded here in milliseconds Figure 1. PRISMA Flow diagram for selection of studies for review Figure 2. Relative strength of evidence for the presence of the three attentional bias components (facilitation, avoidance and delayed disengagement) in anxiety, depression and co- occurring anxiety and depression. Appendix A. Assessment of methodological quality using the Newcastle-Ottawa Quality Assessment Scale (NOS).

Quality ratings for each included study are provided across the three categories of selection, comparability and outcome in Table A-1. Two articles (Koster, De Raedt, et al., 2005b; Martin et al., 1991) contained two separate experiments; hence a total of 27 ratings are provided. The 27 experiments scored between four and seven stars out of a potential 10 stars.

Table A-1. Newcastle-Ottawa Quality Assessment Scale (NOS) Star Scores Selection Comparability Outcome Total score Article (5 stars) (2 stars) (3 stars) (10 stars) 1. Booth (2014) ** ** **** 2. Bradley et al. (1999) ** ** ** ****** 3. Carlson & Mujica-Parodi (2015) ** ** **** 4. Chau et al. (2019) *** ** ** ******* 5. Chen et al. (2015) ** ** ** ****** 6. Fox (1994); Experiment 1 ** ** **** 7. Heeren et al. (2015) ** ** *** ******* 8. Koster et al. (2006) ** ** ** ****** 9. Lee & Knight, 2009 ** ** **** 10. Li et al. (2005) ** ** **** 11. MacLeod et al. (1986) ** ** ** ****** 12. Martin et al. (1991); Experiment 1 ** * ** ***** Martin et al. (1991); Experiment 2 ** ** ** ****** 13. Mogg et al. (2000) ** ** ** ****** 14. Sagliano et al. (2014) ** * ** ***** 15. Sagliano et al. (2016) ** ** **** 16. Sass et al. (2017) ** ** ** ****** 17. Taylor et al. (2016) ** ** **** 18. Teng et al. (2019) ** ** ** ****** 19. Wang et al. (2019) ** * ** ***** 20. Dai & Feng (2011) ** ** ** ****** 21. De Raedt et al. (2012) ** ** ** ****** 22. Elgersma et al. (2018) ** ** ** ****** 23. Koster et al. (2005); Experiment 1 ** ** ** ****** Koster et al. (2005); Experiment 2 ** ** ** ****** 24. LeMoult et al. (2013) ** ** ** ****** 25. Leyman et al. (2007) ** ** ** ******

The selection category comprised four criteria. 26 experiments scored two out of a possible five stars, and one experiment scored 3 stars. All experiments were awarded two stars on the ‘ascertainment of the exposure’ criterion, as they all used validated measurement tools. None of the experiments met the ‘representativeness of the sample’ criterion, as none of the included samples were truly representative or somewhat representative of the average in the target population (i.e. participants selected through random or non-random sampling techniques). Most experiments used selected user groups (i.e. participants selected based on their diagnosis or psychometric score; N = 21). Others did not describe their sampling strategy at all (N = 6). One study (Chau et al., 2019) was awarded a star on the ‘sample size’ criterion for providing a satisfactory justification of their sample size; the remaining studies provided no justification at all. None of the experiments met the ‘non-respondents’ criterion, as there were no descriptions of the response rates or characteristics of responders versus non-responders in any of the included articles.

The comparability category contained one criterion and all experiments were scored out of a possible two stars. One star was awarded to articles controlling for one confounding factor through design or analysis and two stars were awarded to articles controlling for two or more confounding factors. Seven experiments did not receive a star, three experiments received one star and 17 experiments received two stars. Age and/or gender were the most commonly controlled for factors, with one article controlling for anxiety, one for vocabulary and one for attentional control.

The outcome category contained two criteria and all experiments were scored out of a possible three stars. One study was awarded three stars, while 26 received two stars. All experiments met the ‘assessment of outcome’ criterion through self-report (one star), aside from one experiment, which had an independent blind assessment (two stars). All 27 met the ‘statistical test’ criterion, as statistical tests used to analyse the data were appropriate, clearly described and the measurements of the associations were presented. Appendix B. Formulae for calculating attentional bias components

Table B11. Source of formulae for calculating attentional bias components Task Facilitation Delayed Disengagement Avoidance Interference Inhibition Source

DPT Mean RT incongruent cue Mean RT incongruent cue Bradley, Mogg, – mean RT congruent cue – Mean RT congruent cue White, Groom, & = positive score = negative score de Bono (1999)

ECT Mean RT valid/neutral cue Mean RT invalid/emotional cue Mean RT valid/neutral cue Koster, De Raedt, – mean RT – mean invalid/neutral cue = – mean RT et al. (2005b); valid/emotional cue = positive score valid/emotional cue = Koster, Crombez, positive score negative score Verschuere, Van Damme, et al. Mean RT (2006) invalid/emotional cue – mean RT invalid/neutral cue = negative score

EST Mean RT emotional Yovel & Mineka words – mean RT (2005) neutral words = positive score Note. RT = reaction time; DPT = Dot Probe Task; ECT = Exogenous Cueing Paradigm; EST = Emotional Stroop Task