Measuring inhibitory processes for alcohol-related attentional biases: Introducing a novel attentional bias measure

Wilcockson, Thomas; Pothos, Emmanuel M.

doi:10.1016/j.addbeh.2014.12.015

Cited by 34 publications

(50 citation statements)

References 39 publications

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“…Overall, these findings suggest that social drinkers may find it comparatively easier to detect both alcoholic and non-alcoholic appetitive targets when these are contrasted with non-appetitive distractors, perhaps because these stimuli are imbued with incentive value (see Monk et al 2017). Complementing previous research using indirect behavioural measures, the current research may therefore provide a more nuanced insight into unconscious AB processes (Jonides 1981;Mogg et al 2003;Wilcockson and Pothos 2015), suggesting further that AB towards alcoholic stimuli may generalise to other palatable non-alcoholic stimuli. The current research also included AUDIT and trait EC scores as covariates in light of research suggesting that individual differences in problem drinking and the inhibition of prepotent responding are related to alcohol-related AB (see Morales et al 2016;Posner et al 2014;Qureshi et al 2017;van Hemel-Ruiter et al 2015).…”

Section: Discussionsupporting

confidence: 52%

“…Moreover, drinkers have been shown to exhibit AB towards alcohol-related cues on the visual probe eye-tracking task (Fernie et al 2012;Miller and Fillmore 2010). Similarly, Wilcockson and Pothos (2015) found that increased alcohol use was related to the reallocation of attention from central fixation towards peripheral alcoholic stimuli (termed 'break frequency'). Research from both direct and indirect measures of AB therefore suggests that individuals who frequently consume alcohol might allocate attentional resources disproportionately towards alcohol-related stimuli.…”

Section: Introductionmentioning

confidence: 97%

“…beer, wine, spirits) are usually contrasted with non-appetitive neutral stimuli (e.g. stationary and household objects; Bruce and Jones 2004;Fernie et al 2012;Field et al 2011;Jones et al 2006;Townsend and Duka 2001;White et al 2014;Wilcockson and Pothos 2015). It is possible, however, that comparing responses between appetitive (alcohol) and non-appetitive (control) stimuli may exaggerate perceptions of the extent to which AB is exhibited towards alcoholic cues (Field and Cox 2008).…”

Section: Introductionmentioning

confidence: 99%

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Beer? Over here! Examining attentional bias towards alcoholic and appetitive stimuli in a visual search eye-tracking task

Pennington¹,

Qureshi²,

Monk³

et al. 2019

Preprint

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Rationale: Experimental tasks that demonstrate alcohol-related attentional bias typically expose participants to single-stimulus targets (e.g., addiction stroop, visual probe, anti-saccade task), which may not correspond fully with real-world contexts where alcoholic and non-alcoholic cues simultaneously compete for attention. Moreover, alcoholic stimuli are rarely matched to other appetitive non-alcoholic stimuli. Objectives: To address these limitations by utilising a conjunction search eye-tracking task and matched stimuli to examine alcohol-related attentional bias. Methods: Thirty social drinkers (Mage = 19.87, SD = 1.74) were asked to detect whether alcoholic (beer), non-alcoholic (water) or non-appetitive (detergent) targets were present or absent amongst a visual array of matching and non-matching distractors. Both behavioural response times and eye-movement dwell time were measured. Results: Social drinkers were significantly quicker to detect alcoholic and non-alcoholic appetitive targets relative to non-appetitive targets in an array of matching and mismatching distractors. Similarly, proportional dwell time was lower for both alcoholic and non-alcoholic appetitive distractors relative to non-appetitive distractors, suggesting that appetitive targets were relatively easier to detect. Conclusions: Social drinkers may exhibit generalised attentional bias towards alcoholic and non-alcoholic appetitive cues. This adds to emergent research suggesting that the mechanisms driving these individual’s attention towards alcoholic cues might ‘spill over’ to other appetitive cues, possibly due to associative learning.

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Section: Discussionsupporting

confidence: 52%

Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Beer? Over here! Examining attentional bias towards alcoholic and appetitive stimuli in a visual search eye-tracking task

Pennington¹,

Qureshi²,

Monk³

et al. 2019

Preprint

View full text Add to dashboard Cite

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“…In 12 articles, it was shown that dependent drinkers have a higher attentional bias towards alcohol cues than nondependent controls (Carrigan et al 2004;Dickter et al 2014;Fadardi & Cox 2006, 2009Fridrici et al 2013;Garland et al 2012a,b;Lusher et al 2004;No€ el et al 2007;Sharma et al 2001;Townshend & Duka 2001;Wilcockson & Pothos 2015). Only two studies found no or a negative difference between respondents who are alcohol dependent and respondents who are not (Ryan 2002;Townshend & Duka 2007).…”

Section: Attentional Biasmentioning

confidence: 99%

Identifying viable theoretical frameworks with essential parameters for real-time and real world alcohol craving research: a systematic review of craving models

Lier

Pieterse

Schraagen

et al. 2017

Addiction Research & Theory

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Background: Substance use is known to be episodic, dynamic, complex, and highly influenced by the environment, therefore a situational and momentary focus to alcohol craving research is appropriate. Current advances in mobile and wearable technology provide novel opportunities for craving research. However, the lack of consensus within craving theory impedes the identification and prioritization of parameters to be monitored. The aim of this study is to critically review current craving models in order to determine viable theoretical frameworks of alcohol craving and its essential parameters. Methods: Eighteen models of craving were reviewed by applying a literature search with a five-step strategy that accounted for the momentary nature of craving and included a snowballing search and a key term extraction algorithm. Based on this review, multiple decision criteria were defined upon which to evaluate the models. Results: Six models for alcohol craving were supported by sufficient empirical research to be eligible. The inferences drawn on these six models resulted in three decision criteria: the model should (1) incorporate negative affect as a predictor of relapse; (2) explain that dependent drinkers have a higher attentional bias towards alcohol cues than nondependent drinkers; (3) incorporate increased risk of relapse with heightened stress levels. Conclusions: The affective processing model of negative reinforcement, the cognitive processing model, the incentive sensitization theory of addiction and the theory of neural opponent motivation are classified as viable theoretical frameworks, resulting in negative affect and stress as relevant parameters to include in real-time craving monitoring research. ARTICLE HISTORY

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“…In an effort to understand the exact role of such biases, researchers have employed different cognitive tasks (e.g., Jones & Schulze, 2000;Cox et al, 2006;Wilcockson & Pothos, 2015). Such work has led to several key insights regarding the nature of cognitive biases.…”

Section: How Cognitive Biases Can Distort Environmental Statistics: Imentioning

confidence: 99%

How cognitive biases can distort environmental statistics

Wilcockson

Pothos²

2016

Behavioural Pharmacology

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link How Cognitive Biases Can Distort Environmental Statistics: Introducing the Rough Estimation Task AbstractThe purpose of this paper is to develop a novel behavioural method to explore cognitive biases. The task, called the Rough Estimation Task (REsT), simply involves presenting participants with a list of words, such that words can be in one of three categories: appetitive words (e.g. alcohol, food, etc), a category of neutral related words (e.g., musical instruments), and a category of neutral unrelated words. Participants read the words and are then asked to state estimates for the percentage of words in each category. Individual differences in the propensity to overestimate the proportion of appetitive stimuli (alcohol-or food-related words) in a word list were associated with behavioural measures (i.e. alcohol consumption, hazardous drinking, body mass index, external eating, and restrained eating, respectively) thereby providing evidence for the validity of the task. The task was also found to be associated with an eye-tracking attentional bias measure. The REsT is motivated in relation to intuitions regarding both the behaviour of interest and theory of cognitive biases in substance use.

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Measuring inhibitory processes for alcohol-related attentional biases: Introducing a novel attentional bias measure

Abstract: Results suggest that attentional bias is not just a process of stimuli becoming prioritised, but also stimuli becoming compulsory to attend and process.

Cited by 34 publications

References 39 publications

Beer? Over here! Examining attentional bias towards alcoholic and appetitive stimuli in a visual search eye-tracking task

Beer? Over here! Examining attentional bias towards alcoholic and appetitive stimuli in a visual search eye-tracking task

Identifying viable theoretical frameworks with essential parameters for real-time and real world alcohol craving research: a systematic review of craving models

How cognitive biases can distort environmental statistics

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