Internet-based attentional bias modification training as add-on to regular treatment in alcohol and cannabis dependent outpatients: a study protocol of a randomized control trial

Effectiveness of Low-Resolution Brain Electromagnetic Tomography Z Score Neurofeedback Comparison with Cognitive Rehabilitation in Depression and Anxiety in Opioid Use Disorder

Background: Previous studies have shown that conventional neurofeedback (NFB) and cognitive rehabilitation can improve psychological outcomes in people with opioid use disorders (OUDs). However, the effectiveness of Low-Resolution Brain Electromagnetic Tomography (LORETA) Z-score neurofeedback (LZNFB) and attention bias modification training (ABMT) on depression and anxiety of these people has not been investigated yet. The present study aims to compare the effect of these two methods on depression and anxiety of men with OUD under methadone maintenance therapy (MMT). Methods: In this randomized controlled clinical trial with a pre-test, post-test, and follow-up design, 30 men with OUD under MMT were randomly assigned into three groups of LZNFB, ABMT, and control (MMT alone). The LZNFB group underwent LZNFB at 20 sessions. The ABMT using the dot-probe task was provided individually to the second group for 2 weeks at 15 sessions. The Beck Anxiety Inventory and the Beck Depression Inventory were completed by the participants before, immediately after, and 1-month after interventions. The collected data were analyzed in SPSS v.22 software. Results: Both intervention groups showed a significant reduction in anxiety and depression at the post-test phase (p < 0.05), where LZNFB group showed more decrease in anxiety and depression than the ABMT group. This decrease continued in the follow-up period. Conclusion: Both LZNFB and ABMT with the dot-robe task are effective in reducing depression and anxiety of men with OUD under MMT. However, LZNFB is more effective. These findings add to the growing body of literature supporting the effectiveness of NFB and cognitive rehabilitation therapy in treating addiction-related comorbidities.

Control interventions in randomised trials among people with mental health disorders

BACKGROUND

Control interventions in randomised trials provide a frame of reference for the experimental interventions and enable estimations of causality. In the case of randomised trials assessing patients with mental health disorders, many different control interventions are used, and the choice of control intervention may have considerable impact on the estimated effects of the treatments being evaluated.

OBJECTIVES

To assess the benefits and harms of typical control interventions in randomised trials with patients with mental health disorders. The difference in effects between control interventions translates directly to the impact a control group has on the estimated effect of an experimental intervention. We aimed primarily to assess the difference in effects between (i) wait-list versus no-treatment, (ii) usual care versus wait-list or no-treatment, and (iii) placebo interventions (all placebo interventions combined or psychological, pharmacological, and physical placebos individually) versus wait-list or no-treatment. Wait-list patients are offered the experimental intervention by the researchers after the trial has been finalised if it offers more benefits than harms, while no-treatment participants are not offered the experimental intervention by the researchers.

SEARCH METHODS

In March 2018, we searched MEDLINE, PsycInfo, Embase, CENTRAL, and seven other databases and six trials registers.

SELECTION CRITERIA

We included randomised trials assessing patients with a mental health disorder that compared wait-list, usual care, or placebo interventions with wait-list or no-treatment .

DATA COLLECTION AND ANALYSIS

Titles, abstracts, and full texts were reviewed for eligibility. Review authors independently extracted data and assessed risk of bias using Cochrane's risk of bias tool. GRADE was used to assess the quality of the evidence. We contacted researchers working in the field to ask for data from additional published and unpublished trials. A pre-planned decision hierarchy was used to select one benefit and one harm outcome from each trial. For the assessment of benefits, we summarised continuous data as standardised mean differences (SMDs) and dichotomous data as risk ratios (RRs). We used risk differences (RDs) for the assessment of adverse events. We used random-effects models for all statistical analyses. We used subgroup analysis to explore potential causes for heterogeneity (e.g. type of placebo) and sensitivity analyses to explore the robustness of the primary analyses (e.g. fixed-effect model).

MAIN RESULTS

We included 96 randomised trials (4200 participants), ranging from 8 to 393 participants in each trial. 83 trials (3614 participants) provided usable data. The trials included 15 different mental health disorders, the most common being anxiety (25 trials), depression (16 trials), and sleep-wake disorders (11 trials). All 96 trials were assessed as high risk of bias partly because of the inability to blind participants and personnel in trials with two control interventions. The quality of evidence was rated low to very low, mostly due to risk of bias, imprecision in estimates, and heterogeneity. Only one trial compared wait-list versus no-treatment directly but the authors were not able to provide us with any usable data on the comparison. Five trials compared usual care versus wait-list or no-treatment and found a SMD -0.33 (95% CI -0.83 to 0.16, I² = 86%, 523 participants) on benefits. The difference between all placebo interventions combined versus wait-list or no-treatment was SMD -0.37 (95% CI -0.49 to -0.25, I² = 41%, 65 trials, 2446 participants) on benefits. There was evidence of some asymmetry in the funnel plot (Egger's test P value of 0.087). Almost all the trials were small. Subgroup analysis found a moderate effect in favour of psychological placebos SMD -0.49 (95% CI -0.64 to -0.30; I² = 53%, 39 trials, 1656 participants). The effect of pharmacological placebos versus wait-list or no-treatment on benefits was SMD -0.14 (95% CI -0.39 to 0.11, 9 trials, 279 participants) and the effect of physical placebos was SMD -0.21 (95% CI -0.35 to -0.08, I² = 0%, 17 trials, 896 participants). We found large variations in effect sizes in the psychological and pharmacological placebo comparisons. For specific mental health disorders, we found significant differences in favour of all placebos for sleep-wake disorders, major depressive disorder, and anxiety disorders, but the analyses were imprecise due to sparse data. We found no significant differences in harms for any of the comparisons but the analyses suffered from sparse data. When using a fixed-effect model in a sensitivity analysis on the comparison for usual care versus wait-list and no-treatment, the results were significant with an SMD of -0.46 (95 % CI -0.64 to -0.28). We reported an alternative risk of bias model where we excluded the blinding domains seeing how issues with blinding may be seen as part of the review investigation itself. However, this did not markedly change the overall risk of bias profile as most of the trials still included one or more unclear bias domains.

AUTHORS' CONCLUSIONS

We found marked variations in effects between placebo versus no-treatment and wait-list and between subtypes of placebo with the same comparisons. Almost all the trials were small with considerable methodological and clinical variability in factors such as mental health population, contents of the included control interventions, and outcome domains. All trials were assessed as high risk of bias and the evidence quality was low to very low. When researchers decide to use placebos or usual care control interventions in trials with people with mental health disorders it will often lead to lower estimated effects of the experimental intervention than when using wait-list or no-treatment controls. The choice of a control intervention therefore has considerable impact on how effective a mental health treatment appears to be. Methodological guideline development is needed to reach a consensus on future standards for the design and reporting of control interventions in mental health intervention research.

Effectiveness of attentional bias modification training as add-on to regular treatment in alcohol and cannabis use disorder: A multicenter randomized control trial

Background

Attentional bias for substance-relevant cues has been found to contribute to the persistence of addiction. Attentional bias modification (ABM) interventions might, therefore, increase positive treatment outcome and reduce relapse rates. The current study investigated the effectiveness of a newly developed home-delivered, multi-session, internet-based ABM intervention, the Bouncing Image Training Task (BITT), as an add-on to treatment as usual (TAU).

Methods

Participants (N = 169), diagnosed with alcohol or cannabis use disorder, were randomly assigned to one of two conditions: the experimental ABM group (50%; TAU+ABM); or the control group (50%; split in two subgroups the TAU+placebo group and TAU-only group, 25% each). Participants completed baseline, post-test, and 6 and 12 months follow-up measures of substance use and craving allowing to assess long-term treatment success and relapse rates. In addition, attentional bias (both engagement and disengagement), as well as secondary physical and psychological complaints (depression, anxiety, and stress) were assessed.

Results

No significant differences were found between conditions with regard to substance use, craving, relapse rates, attentional bias, or physical and psychological complaints.

Conclusions

The findings may reflect unsuccessful modification of attentional bias, the BITT not targeting the relevant process (engagement vs. disengagement bias), or may relate to the diverse treatment goals of the current sample (i.e., moderation or abstinence). The current findings provide no support for the efficacy of this ABM approach as an add-on to TAU in alcohol or cannabis use disorder. Future studies need to delineate the role of engagement and disengagement bias in the persistence of addiction, and the role of treatment goal in the effectiveness of ABM interventions.

Attentional Bias in Alcohol and Cannabis Use Disorder Outpatients as Indexed by an Odd-One-Out Visual Search Task: Evidence for Speeded Detection of Substance Cues but Not for Heightened Distraction

Current cognitive models of addiction imply that speeded detection and increased distraction from substance cues might both independently contribute to the persistence of addictive behavior. Speeded detection might lower the threshold for experiencing craving, whereas increased distraction might further increase the probability of entering a bias-craving-bias cycle, thereby lowering the threshold for repeated substance use. This study was designed to examine whether indeed both attentional processes are involved in substance use disorders. Both attentional processes were indexed by an Odd-One-Out visual search task in individuals diagnosed with alcohol use disorder (AUD; n = 63) and cannabis use disorder (CUD; n = 28). To test whether the detection and/or the distraction component are characteristic for AUD and CUD, their indices were compared with matched individuals without these diagnoses (respectively, n = 63 and n = 28). Individuals with CUD showed speeded detection of cannabis cues; the difference in detection between AUD and the comparison group remained inconclusive. Neither the AUD nor the CUD group showed more distraction than the comparison groups. The sample size of the CUD group was relatively small. In addition, participants made relatively many errors in the attentional bias (AB) task, which might have lowered its sensitivity to detect ABs. The current study provided no support for the proposed role of increased distraction in CUD and AUD. The findings did, however, provide support for the view that speeded detection might be involved in CUD. Although a similar trend was evident for AUD, the evidence was weak and remained therefore inconclusive.

Attentional bias for alcohol cues in visual search-Increased engagement, difficulty to disengage or both?

Cognitive models emphasise the importance of attentional bias in addiction. However, many attentional bias tasks have been criticised for questionable psychometric properties and inability to differentiate between engagement and disengagement processes. This study therefore examined the suitability of two alternative tasks for assessing attentional bias within the context of alcohol use. Participants were undergraduate students (N = 169) who completed the Visual Search Task and Odd-One-Out Task, the latter of which is designed to differentiate between engagement and disengagement processes of attention, at baseline and one week later. Participants also completed baseline measures of alcohol consumption, craving, and alcohol use problems. Internal consistency was adequate for the Visual Search Task index, and weak for the Odd-One-Out Task indices. Test-retest reliability was weak for both tasks. The Visual Search Task index and the disengagement (but not the engagement) index of the Odd-One-Out Task showed a positive association with alcohol consumption. This study was restricted to a non-clinical student sample. The relatively high error rate of the Odd-One-Out Task might have reduced its sensitivity as an index of attentional bias. Both tasks showed some merit as attentional bias measures, and results suggested that attentional disengagement might be particularly related to alcohol use. However, the reliability of the current measures was inadequate. One potential explanation for the low reliability is that non-clinical samples may have weak and unstable attentional biases to alcohol. Future efforts should be made to improve the psychometric qualities of both tasks and to administer them in a clinical sample.

Brain activation to cannabis- and alcohol-related words in alcohol use disorder

Cannabis abuse commonly co-occurs with alcohol use disorder (AUD). With increased acceptance and accessibility to cannabis in the US, it is imperative to understand the psychological and neural mechanisms of concurrent alcohol and cannabis use. We hypothesized that neural alcohol-cue conditioning may extent to other drug-related stimuli, such as cannabis, and underwrite the loss of control over reward-driven behavior. Task-activated fMRI examined the neural correlates of alcohol- and cannabis-related word cues in 21 abstinent AUD and 18 control subjects. Relative to controls, AUD showed behavioral attentional biases and frontal hypoactivation to both alcohol- and cannabis-related words. This cue-elicited prefrontal hypoactivation was related to higher lifetime alcohol consumption (pcorrected < 0.02) and modulated by past cannabis use histories (p ≦ 0.001). In particular, frontal hypoactivation to both alcohol and cannabis cues was pronounced in AUD without prior cannabis exposure. Overall, frontal control mechanisms in abstinent AUD were not sufficiently engaged to override automatic alcohol and cannabis-related intrusions, enhancing the risk for relapse and potentially for alcohol and cannabis co-use with the increased social acceptance and accessibility in the US.

A new approach to facilitating attentional disengagement from food cues in unsuccessful dieters: The bouncing image training task

This study tested the capacity of a modified Bouncing Image Training Task (BITT) to enhance unsuccessful dieters' attentional disengagement from food cues. Unsuccessful dieters were assigned to a training group performing daily BITT sessions for one week (n = 57) or a waitlist control group (n = 56). Change in attention was assessed using a visual search task and an odd-one-out task. Impact of the BITT on food craving and food intake were also assessed. Participants in the training group, compared to waitlist controls, showed reduced attention to food cues from pre-to post-training. Moreover, the reduction in AB to food cues exhibited by those who completed the BITT reflected the relative facilitation of attentional disengagement from food cues, rather than a reduction in attention engagement with food cues. The groups did not differ on food craving or intake post-training. It is concluded that the BITT is a promising procedure for directly manipulating individuals' attentional disengagement from food cues, though its capacity to enhance dieting success has not yet been established.

A review of gamification approaches in commercial cognitive bias modification gaming applications

BACKGROUND

Cognitive biases are mostly automatic processes that result in individuals giving increased attention to threatening stimuli, with the difficulties in disengaging from these stimuli. Recent reviews have reported the presence for attention bias in several psychiatric conditions and provided evidence that such biases could be subjected to modification. Web-based and mobile based bias modification have mixed efficacy and gamification techniques proposed as a solution. There remains a gap in knowledge pertaining to the gamified applications for bias modification that are commercially available.

OBJECTIVE

An analysis of their gamification approach will help in identification of common gaming elements adopted for use.

METHODS

To identify commercial applications, a manual cross-sectional search was conducted between 1 and 11 November 2017 on the Google Play store. The following search terminologies were used: "Attention bias" and "Cognitive bias". The classification of the gamification technique for both the published applications and commercial applications were based on the six approaches described by Wouter et al. [17] and the 17 gamification techniques described by Hoffman et al. [18].

RESULTS

A total of nine applications were included in the current review. Five out of the nine applications involved the addition of gaming elements to an evidence-based task, and three involved the usage of intrinsic integration while leaving the evidence-based task intact. Other common gamification strategies used are that of the inclusion of digital rewards (n= 8) and the provision of feedback (n= 7). The average number of gamification techniques across all the nine applications is 3.2.

CONCLUSIONS

Even though most commercial applications appear to have their basis on a validated gamification approach for the delivery of attention bias modification, there remains a need for further research in evaluating these applications clinically.

Comprehensive interventions for reducing cannabis use

PURPOSE OF REVIEW

Cannabis is globally the most commonly cultivated, trafficked and consumed illicit drug of abuse. The current article provides an updated overview of existing comprehensive interventions for preventing and reducing cannabis use.

RECENT FINDINGS

The PubMed database was searched for evidence regarding comprehensive interventions for preventing and reducing cannabis use from June 2016 to January 2018. The search resulted in 274 articles. Twenty-one studies were selected for assessment and 13 fulfilled the inclusion criteria. Six systematic reviews regarding preventive, psychosocial, pharmacological and risk reduction interventions were identified. Psychosocial interventions included therapist-assisted and computerized interventions. Four therapist-assisted, one computerized and two pharmacological clinical trials were published over the review period. Overall, considering the three different approaches (preventive, psychosocial or pharmacological) promising results have been found in certain interventions in reducing cannabis use among different types of users. In addition, recommendations to reduce adverse health outcomes related to cannabis use have also been reviewed.

SUMMARY

Although relevant findings have been found so far, further research with adequately powered trials assessing comprehensive interventions for reducing cannabis use remains a need before definitive treatment recommendations can be established.

A Systematic Review of Attention Biases in Opioid, Cannabis, Stimulant Use Disorders

Background: Opiates, cannabis, and amphetamines are highly abused, and use of these substances are prevalent disorders. Psychological interventions are crucial given that they help individuals maintain abstinence following a lapse or relapse into substance use. Advances in experimental psychology have suggested that automatic attention biases might be responsible for relapse. Prior reviews have provided evidence for the presence of these biases in addictive disorders and the effectiveness of bias modification. However, the prior studies are limited, as they failed to include trials involving participants with these prevalent addictive disorders or have failed to adopt a systematic approach in evidence synthesis. Objectives: The primary aim of this current systematic review is to synthesise the current evidence for attention biases amongst opioid use, cannabis use, and stimulant use disorders. The secondary aim is to determine the efficacy of attention bias modification interventions and other addictions related outcomes. Methods: A search was conducted from November 2017 to January 2018 on PubMed, MEDLINE, Embase, PsycINFO, Science Direct, Cochrane Central, and Scopus. The selection process of the articles was in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. A qualitative synthesis was undertaken. Risk of bias was assessed using the Cochrane Risk of Bias tool. Results: Six randomised trials were identified. The evidence synthesized from these trials have provided strong evidence that attentional biases are present in opioid and stimulant use disorders. Evidence synthesis for other secondary outcome measures could not be performed given the heterogeneity in the measures reported and the limited number of trials. The risk of bias assessment for the included trials revealed a high risk of selection and attrition bias. Conclusions: This review demonstrates the potential need for interventions targeting attention biases in opiate and cocaine use disorders.

Attention Bias in Individuals with Addictive Disorders: Systematic Review Protocol

Background

Globally, substance disorders, particularly that of opiate use, cannabis use, and stimulant use disorders, are highly prevalent. Psychological treatments are an integral aspect of intervention, but a proportion of individuals still relapse despite having received such an intervention. Recently, the dual-process theory proposed that the unconscious processes of attention biases are responsible for these relapses. Prior meta-analyses have reported the presence of attention bias in alcohol and tobacco use disorders. More recent research has examined attention bias and its effectiveness in opiate use, cannabis use, and stimulant use disorder. The evidence syntheses to date have not examined whether attention bias is present in these disorders and could be subjected to manipulation. This is important information and would support the introduction of psychological interventions for attention bias for such patients. Such psychological interventions would help individuals maintain their abstinence and minimize the risk of relapse.

Objective

This paper aims to undertake a systematic review to synthesize the existing evidence for the presence of attention bias in all the disorders mentioned above, and to determine the clinical efficacy of attention bias modification.

Methods

A systematic review will be conducted. A search will be conducted on the respective databases up till 2017. Selection of the studies will be determined by the Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines. Quality assessment of the included studies will be assessed using the Cochrane Risk of Bias tool. A narrative synthesis will be conducted, with a meta-analysis considered only if there are sufficient studies for statistical analysis.

Results

The results of the systematic review will be available 12 months after the publication of this protocol.

Conclusions

This review is important as it will support the introduction of psychological interventions for attention bias for such patients. Such psychological interventions would help individuals maintain their abstinence and minimize the risk of relapse.

Cognitive Biases in Cannabis, Opioid, and Stimulant Disorders: A Systematic Review

Background: Opiates, cannabis, and stimulants are highly abused and are prevalent disorders. Psychological interventions are crucial given that they help individuals maintain abstinence following a lapse or relapse into substance use. The dual-process theory has posited that while the repeated use of a substance leads to increased automatic processing and increased automatic tendencies to approach substance-specific cues, in addition to the inhibition of other normal cognitive processes. Prior reviews are limited, as they failed to include trials involving participants with these prevalent addictive disorders or have not reviewed the published literature extensively. Objectives: The primary aim of this review is to synthesize the evidence for cognitive biases in opioid use, cannabis use, and stimulant use disorders. The secondary aim of the review is to determine if cognitive bias could be consistently detected using the different methods. Lastly, this review will narratively synthesize the evidence of possible associations between cognitive biases and other addiction-related outcomes. Methods: A search was conducted from November 2017 to January 2018 on PubMed, MEDLINE, Embase, PsycINFO, Science Direct, Cochrane Central, and Scopus. Articles were included if participants had a primary diagnosis of opioid use, cannabis use, or stimulant use disorder. The selection process of the articles was in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. A qualitative synthesis was undertaken. Results: A total of 38 studies were identified. The main finding is the evidence that cognitive biases are present in the 38 studies identified, except for a single study on opioid use and stimulant use disorders. Cognitive biases were reported despite a variety of different methods being utilized. Synthesis of secondary outcome was not feasible, due to the varied outcomes reported. Conclusions: Cognitive biases have been consistently observed in opioid use, cannabis use, and stimulant use disorders, despite a range of assessment tools being utilized in the assessment for these biases.