Attentional bias predicts heroin relapse following treatment

Marissen, Marlies A.E.; Franken, Ingmar H.A.; Waters, Andrew J.; Blanken, Peter; Brink, Wim van den; Hendriks, Vincent M.

doi:10.1111/j.1360-0443.2006.01498.x

Cited by 248 publications

(229 citation statements)

References 33 publications

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“…Payne et al, 2006;Marissen et al, 2006;Krishnan-Sarins et al, 2007). The present study, however, is the first to have assessed the predictive relevance of all these variables concurrently in a prospective study controlling for level of dependence.…”

Section: Discussionmentioning

confidence: 99%

“…Lingford-Hughes, 2005). Heightened awareness of cigarette availability coupled with powerful craving, if experienced early in cessation, is likely to undermine attempts at abstinence; indeed, laboratory indices of attentional bias have predicted relapse in some studies (Waters et al, 2003a;Marissen et al, 2006) though not all (e.g. Waters et al, 2003b).…”

Section: Salience Attribution Attentional and Motivational Responsesmentioning

confidence: 99%

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Relapse to smoking during unaided cessation: clinical, cognitive and motivational predictors

et al. 2010

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Rationale: Neurobiological models of addiction suggest that abnormalities of brain reward circuitry distort salience attribution and inhibitory control processes, which in turn contribute to high relapse rates. Objectives:To determine whether impairments of salience attribution and inhibitory control predict relapse in a pharmacologically unaided attempt at smoking cessation.Methods: 141 smokers were assessed on indices of nicotine consumption / dependence (e.g. the FTND, cigarettes per day, salivary cotinine), and three trait impulsivity measures. After overnight abstinence they completed experimental tests of cue reactivity, attentional bias to smoking cues, response to financial reward, motor impulsiveness, and response inhibition (antisaccades). They then started a quit attempt with follow-up after 7 days, 1 month, and 3 months; abstinence was verified via salivary cotinine levels ≤ 20ng/ml. Results:Relapse rates at each point were 52.5%, 64% and 76.3%. The strongest predictor was pre-cessation salivary cotinine; other smoking / dependence indices did not explain additional outcome variance and neither did trait impulsivity. All experimental indices except responsivity to financial reward significantly predicted one week outcome. Salivary cotinine, attentional bias to smoking cues and antisaccade errors explained unique as well as shared variance. At one and three months, salivary cotinine, motor impulsiveness and cue reactivity were all individually predictive; the effects of salivary cotinine and motor impulsiveness were additive.Conclusions: These data provide some support for the involvement of abnormal cognitive and motivational processes in sustaining smoking dependence and suggest that they might be a focus of interventions, especially in the early stages of cessation.2

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Section: Discussionmentioning

confidence: 99%

Section: Salience Attribution Attentional and Motivational Responsesmentioning

confidence: 99%

Relapse to smoking during unaided cessation: clinical, cognitive and motivational predictors

et al. 2010

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“…While the relationship between craving and relapse during abstinence is complex, users typically report that cravings occur prior to and during the period of highly ritualized and automatic drug-taking behavior that follows an impulsive urge to use (Miller and Gold 1994). Recent studies have demonstrated that the extent of an individual users' attentional bias for drug-related stimuli can robustly predict the likelihood of successfully ceasing cigarette smoking (Waters et al 2003), or remaining abstinent during treatment for alcohol (Cox et al 2002), cocaine (Carpenter et al 2005), and heroin (Marissen et al 2006) dependence. The study by Cox et al (2002) measured attentional bias for alcohol-related stimuli over two time-points and demonstrated that levels of bias increased prior to relapse.…”

Section: Attentional Bias For Drug-related Stimulimentioning

confidence: 99%

The Role of Executive Control in Human Drug Addiction

Hester

Lubman

Yücel

2009

Current Topics in Behavioral Neurosciences

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“…Sharma, Albery & Cook, 2001;Field, Schoenmakers & Wiers, 2008), cannabis use (Field, Eastwood, Bradley & Mogg, 2006) and nicotine use (Mogg, Field & Bradley, 2005). Longitudinal designs have also demonstrated the association between attentional bias and risk of subsequent relapse in alcohol abusers (Cox, Hogan, Kristian & Race, 2002), tobacco smokers (Waters, Shiffman, Bradley & Mogg, 2003), heroin users (Marissen, Franken, Waters, Blanken, van den Brink & Hendriks, 2006) and cocaine users (Carpenter, Schreiber, Church & McDowell, 2006).…”

Section: Formulation Of Addictive Behaviorsmentioning

confidence: 99%

Metacognition in addictive behaviors

Spada

Caselli²,

Nikčević

et al. 2015

Addictive Behaviors

179

150

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Over the last twenty years metacognitive theory has provided a novel framework, in the form of the Self-Regulatory Executive Function (S-REF) model, for conceptualizing psychological distress (Wells & Matthews, 1994;1996) Metacognition in Psychopathology: The Self-Regulatory Executive Function ModelThe term 'metacognition', which is most often associated with the work of John Flavell (1979;1987), can be broadly defined as knowledge and cognitive processes that are involved in the appraisal, control, or monitoring of thinking. Theory and research in metacognition emerged in developmental psychology and has, over the last forty years, been applied across various domains including aging, education, forensic psychology, memory, and neuropsychology (Dunlosky & Metcalfe, 2009;Nelson & Narens, 1990;Pintrich, 2000).More recently, as a result of the work of Adrian Wells and his colleagues, metacognition has applied to conceptualizing and treating psychological distress. Wells and Matthews (1994;1996) have proposed a multi-process model, the Self-Regulatory and by the third level in the model: metacognitive knowledge. Metacognitive knowledge is conceptualised as information and beliefs about cognition that are positive and negative in content (e.g. "Worrying will help me cope" and "Some thoughts are dangerous") and

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Attentional bias predicts heroin relapse following treatment

Abstract: Attentional bias may tap an important component of drug dependence as it is a predictor of opiate relapse. However, CET does not specifically reduce attentional bias.

Cited by 248 publications

References 33 publications

Relapse to smoking during unaided cessation: clinical, cognitive and motivational predictors

Relapse to smoking during unaided cessation: clinical, cognitive and motivational predictors

The Role of Executive Control in Human Drug Addiction

Metacognition in addictive behaviors

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