Attentional bias modification training for insomnia: A double-blind placebo controlled randomized trial

Comparative Analysis of LORETA Z Score Neurofeedback and Cognitive Rehabilitation on Quality of Life and Response Inhibition in Individuals with Opioid Addiction

Background. Previous studies has shown that conventional neurofeedback and cognitive rehabilitation can improve psychological outcomes in people with opioid use disorders. However, the effectiveness of LORETA Z-score neurofeedback (LZNFB) and attention bias modification training on quality of life and inhibitory control of these people has not been investigated yet. LZNFB targets deeper brain structures with higher precision, compared to conventional neurofeedback that typically focuses on surface EEG activity. The present study aims to compare the effect of these two methods on quality of life and response inhibition in men with opioid use disorders under methadone maintenance therapy (MMT). Methods. In this randomized controlled clinical trial with a pre-test, post-test, follow-up design, 30 men with opioid use disorders under MMT were randomly assigned into three groups of LZNFB, attention bias modification training, and control (MMT alone). The LZNFB and Cognitive Rehabilitation groups received 20 and 15 sessions of treatment, respectively. The Persian versions WHO Quality of Life-BREEF questionnaire and the Go/No-Go test were completed by the participants before, immediately after, and one month after interventions. The collected data were analyzed in SPSS v.22 software. Results. Both intervention groups showed a significant improvement in quality-of-life score and a significant reduction in response time at the post-test phase (P < .05), where LZNFB group showed more improvement in quality of life and more reduction in response inhibition. After one month, the increase in quality of life continued in both groups, while the decrease in response time continued only in the LZNFB group. Conclusion. Both LZNFB and attention bias modification training are effective in improving quality of life and response inhibition of men with OUD under MMT, however, LZNFB is more effective.

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.

Sleep-related attentional and interpretive-bias in insomnia: A systematic review and meta-analysis

Cognitive models of insomnia highlight internal and external cognitive-biases for sleep-related "threat" in maintaining the disorder. This systematic review of the sleep-related attentional and interpretive-bias literature includes meta-analytic calculations of each construct. Searches identified N = 21 attentional-bias and N = 8 interpretive-bias studies meeting the inclusion/exclusion criteria. Seventeen attentional-bias studies compared normal-sleepers and poor-sleepers/insomnia patients. Using a random effects model, meta-analytic data based on standardized mean differences of attentional-bias studies determined the weighted pooled effect size to be moderate at 0.60 (95%CI:0.26-0.93). Likewise, seven of eight interpretive-bias studies involved group comparisons. Meta-analytic data determined the weighted pooled effect size as moderate at .44 (95%CI:0.19-0.69). Considering these outcomes, disorder congruent cognitive-biases appear to be a key feature of insomnia. Despite statistical support, absence of longitudinal data limits causal inference concerning the relative role cognitive-biases in the development and maintenance of insomnia. Methodological factors pertaining to task design, sample and stimuli are discussed in relation to outcome variation. Finally, we discuss the next steps in advancing the understanding of sleep-related biases in insomnia.

Attentional Bias for Sleep-Related Words as a Function of Severity of Insomnia Symptoms

Attentional bias to sleep-related information is thought to be a core feature for developing and/or maintaining insomnia. This study used a hallmark measure of attentional bias, the dot-probe task, to determine whether this bias toward sleep-related stimuli was a function of the severity of insomnia symptoms. A sample of 231 volunteers (175 females; mean age of 26.91 ± 8.05 years) participated in this online study, filling out the Insomnia Severity Index (ISI) and performing a visual dot-probe task. After categorizing individuals based on the ISI score into normal, subclinical, and moderate/severe sleep groups, we only found a marginally significant interaction between sleep groups and the type of stimuli on RTs, suggesting that subclinical and moderate/severe sleep groups reported slower RTs for sleep-related words than for neutral words. When we calculated the attentional bias score (ABS), we found that ABS significantly differed from zero in the moderate/severe sleep group only, suggesting a disengagement for sleep-related information as a function of the severity of insomnia symptoms. This finding seems to suggest that insomnia is related to greater difficulties in shifting away from sleep-related stimuli.

Chronic Pain, Insomnia and their Mutual Maintenance: A Call for Cognitive Bias Research

Chronic pain and insomnia are highly comorbid: Approximately 50% of those with chronic pain experience insomnia or clinically significant sleep disturbances, and 50% of those with insomnia experience chronic pain. Further, these conditions can be extremely disabling, particularly when they co-occur. There is increasing recognition of the need to tackle both chronic pain and insomnia together, as evidenced by growing empirical research in this area. Cognitive processing biases have been independently implicated in both chronic pain and in insomnia. Given their trans-diagnostic status, cognitive biases may therefore have a role in explaining the co-occurrence and mutual maintenance of these conditions. These biases also represent novel, potentially modifiable targets for treatment. However, the role of cognitive biases has not been adequately explored in comorbid chronic pain and insomnia. Here, we describe the state of cognitive bias research in chronic pain and insomnia, considering evidence for the roles of attentional bias, interpretation bias, expectancy bias, and memory bias. In reviewing the literature, it is apparent that similar cognitive biases operate in insomnia and chronic pain, with preliminary, albeit sparse, evidence of pain-related cognitive biases influencing sleep-related outcomes. On the basis of current findings and separate theoretical models, we present a novel, testable cognitive model of comorbid chronic pain and insomnia, to guide future research in this area. Key recommendations for the future of this relatively new field are provided. PERSPECTIVE: Chronic pain and insomnia are highly co-morbid, suggesting an overlap in causal mechanisms. Empirical research, although sparse, suggests that cognitive biases may play a role in their development and mutual maintenance. Our novel cognitive model generates research avenues of clinical importance for treating co-morbid chronic pain and insomnia.

Attention and interpretation cognitive bias change: A systematic review and meta-analysis of bias modification paradigms

This systematic review and meta-analysis examines the effect of Cognitive Bias Modification for attention (CBM-A) and interpretation (CBM-I) on reducing the targeted biases and investigates moderators of each approach. PsycINFO, PsychArticles, and PubMED databases were searched for randomized-controlled studies published before March 2020 with pre- and post-CBM cognitive bias outcome measures, resulting in 91 CBM-A (n = 5914 individuals) and 70 CBM-I samples (n = 4802 individuals). Random-effects models and Hedge's g calculation showed significant medium overall effects of bias reduction with moderate to high heterogeneity (CBM-A g = 0.49 [0.36, 0.64], I² = 85.19%; CBM-I g = 0.58 [0.48, 0.68], I² = 70.92%). Effect sizes did not differ between approaches and remained significant after trim-and-fill adjustment for possible publication bias. Moderator variables were investigated with meta-regression and subgroup analyses. Participant age, symptom type, control condition and number of trials moderated CBM-A; student and clinical status moderated CBM-I effect size. Results support attention and interpretation modification in controlled laboratory and variable (online) training settings for non-clinical and clinical samples across various symptom types (anxiety, depression, substance use, eating disorders). Further empirical evidence is necessary to determine optimal sample and methodological combinations most strongly associated with adaptive behavioral outcomes.

Sleep disorders and attention: a systematic review

ABSTRACT Background: Sleep is a special physiological state that occurs cyclically. The probable role of sleep in our organic functions remains to be explored to clarify the impact of sleep on brain functions. Sleep deprivation is known to affect all parts of the brain separately and independently, but further research is needed on the impact of sleep disorders on attention, particularly the specific types of attention that are most affected, and whether there is such a correlation. Objective: To conduct a systematic review of the possible correlation between sleep disorders and attentional performance. Methods: A systematic review and search at PubMed, SciELO, and Cochrane scientific databases for articles published in the last 10 years was carried out using the following keywords: sleep, attention, and attentional performance. Inclusion criteria were the use of attention tests and sleep disorders. Of the 1398 articles found, 15 were selected and included in this review. Results: The number of publications evaluating sleep and sleep disorders has increased, but is still limited. Of all the functions normally assessed, patients with sleep disorders perform worse on attention tasks, especially with sustained attention. However, these data require further investigation due to the complexity and diversity of the disorders, the small sample size of the included studies, and the fact that few studies used standardized tests. Conclusions: Our findings indicate that the correlation between sleep and attention is strong but limited. Few studies are devoted exclusively to the extent to which sleep disorders interferes with attention.

Comparing LORETA Z Score Neurofeedback and Cognitive Rehabilitation Regarding Their Effectiveness in Reducing Craving in Opioid Addicts

Introduction

Previous studies have shown that conventional neurofeedback and cognitive modification treatments have numerous psychological benefits for patients with substance use disorders. However, the effectiveness of LORETA (Low-Resolution Brain Electromagnetic Tomography) Z Score Neurofeedback (LZNFB) and cognitive rehabilitation therapy in reducing opioid craving has not been investigated. Thus, the present study aimed to compare the effectiveness of LZNFB and cognitive rehabilitation therapy with Methadone Maintenance Treatment (MMT) in reducing craving in patients with opioid use disorder.

Methods

Thirty patients with opioid use disorder undergoing MMT were randomly assigned into three groups: LZNFB with MMT, cognitive rehabilitation with MMT (as experimental groups), and MMT alone control group. The LZNFB and cognitive rehabilitation groups received 20 and 15 sessions of treatment, respectively. The three groups were assessed using several questionnaires and dot-probe task at pretest, posttest, and one-month follow-up.

Results

The results showed that both experimental groups accomplished a significantly greater reduction in opioid craving than MMT alone group at posttest and follow-up (P<0.05). The LZNFB plus MMT group showed a greater decrease in opioid craving than the cognitive rehabilitation plus MMT group. In addition, the cognitive rehabilitation plus MMT group experienced greater improvement in attentional bias towards craving cues than the LZNFB with MMT group at posttest and follow-up. Finally, the LZNFB plus MMT group and cognitive rehabilitation plus MMT group got higher scores on the recovery assessment scale than MMT alone group at posttest and follow-up. According to study results, LZNFB training is more effective than cognitive rehabilitation in decreasing cravings and improving the quality of life in addiction to opioids.

Conclusion

The current study's findings provided preliminary support for the effectiveness of LZNFB and cognitive rehabilitation in reducing opioid craving, improving attentional bias towards craving cues, and the quality of life among Iranian opioid use patients.

Highlights

LZNFB training showed higher decrease in opioid craving than the Cognitive rehabilitation in opioid addicts.Cognitive rehabilitation group experienced greater improvement on attentional bias towards craving cues than LZNFB.LZNFB and Cognitive rehabilitation with MMT group got higher scores on the recovery assessment scale than MMT alone group.LZNFB training is more effective than Cognitive Rehabilitation in decreasing of craving in addiction. opioids.

Plain Language Summary

Addiction is a chronic relapsing disease that makes many problems for human society. Routine medical treatments are not completely effective and they have relapse. New forms of non-medical treatments such as neurofeedback and cognitive rehabilitation are effective and safe without impressive side effects . This article shows the efficacy of above mentioned interventions for decrease craving and control of this problem.

Conceptual Framework for Insomnia: A Cognitive Model in Practice

Insomnia is a widespread neuropsychological sleep-related disorder known to result in various predicaments including cognitive impairments, emotional distress, negative thoughts, and perceived sleep insufficiency besides affecting the incidence and aggravation of other medical disorders. Despite the available insomnia-related theoretical cognitive models, clinical studies, and related guidelines, an evidence-based conceptual framework for a personalized approach to insomnia seems to be lacking. This study proposes a conceptual cognitive framework (CCF) providing insight into cognitive mechanisms involved in the predisposition, precipitation, and perpetuation of insomnia and consequent cognitive deficits. The current CCF for insomnia relies on evaluative conditional learning and appraisal which generates negative valence (emotional value) and arousal (cognitive value). Even with the limitations of this study, the suggested methodology is well-defined, reproducible, and accessible can help foster future high-quality clinical databases. During clinical insomnia but not the neutral one, negative mood (trait-anxiety) causes cognitive impairments only if mediating with a distorted perception of insomnia (Ind-1 = 0.161, 95% CI 0.040–0.311). Further real-life testing of the CCF is intended to formulate a meticulous, decision-supporting platform for clinical interventions. Furthermore, the suggested methodology is expected to offer a reliable platform for CCF-development in other cognitive impairments and support the causal clinical data models. It may also improve our knowledge of psychological disturbances and complex comorbidities to help design rehabilitation interventions and comprehensive frameworks in line with the “preventive medicine” policies.

Methods to split cognitive task data for estimating split-half reliability: A comprehensive review and systematic assessment

Estimating the reliability of cognitive task datasets is commonly done via split-half methods. We review four methods that differ in how the trials are split into parts: a first-second half split, an odd-even trial split, a permutated split, and a Monte Carlo-based split. Additionally, each splitting method could be combined with stratification by task design. These methods are reviewed in terms of the degree to which they are confounded with four effects that may occur in cognitive tasks: effects of time, task design, trial sampling, and non-linear scoring. Based on the theoretical review, we recommend Monte Carlo splitting (possibly in combination with stratification by task design) as being the most robust method with respect to the four confounds considered. Next, we estimated the reliabilities of the main outcome variables from four cognitive task datasets, each (typically) scored with a different non-linear algorithm, by systematically applying each splitting method. Differences between methods were interpreted in terms of confounding effects inflating or attenuating reliability estimates. For three task datasets, our findings were consistent with our model of confounding effects. Evidence for confounding effects was strong for time and task design and weak for non-linear scoring. When confounding effects occurred, they attenuated reliability estimates. For one task dataset, findings were inconsistent with our model but they may offer indicators for assessing whether a split-half reliability estimate is appropriate. Additionally, we make suggestions on further research of reliability estimation, supported by a compendium R package that implements each of the splitting methods reviewed here.

The therapeutic potential of attentional bias modification training for insomnia: study protocol for a randomised controlled trial

Background

The efficacy of attentional bias modification (ABM) as a treatment for anxiety and depression has been extensively studied with promising results. Despite some evidence of sleep-related attentional biases in insomnia, only a small number of studies, yielding mixed results, have examined the application of ABM in insomnia. This study specifically aims to determine whether ABM can reduce (i) the presence of an attentional bias for sleep-related threatening words; (ii) insomnia symptom severity; (iii) sleep onset latency; and (iv) pre-sleep cognitive arousal amongst individuals with insomnia compared to a non-treatment control group of individuals with insomnia.

Methods/design

We propose a randomised controlled trial of 90 individuals from the general population who meet the criteria for Insomnia Disorder. Following an initial examination for the presence of a sleep-related attentional bias using the dot-probe paradigm, participants will be randomised to an online attentional bias modification training condition, or to a standard attentional bias task (non-treatment) control condition. Both conditions will be delivered online by a web platform. All participants allocated to the non-treatment control group will be offered ABM training once the study is complete. The primary outcome will be the attentional bias indices of vigilance and disengagement and self-reported insomnia symptoms, sleep onset latency and pre-sleep cognitive arousal. Attentional bias and insomnia symptoms will be assessed at baseline (day 1) and post-treatment (2 days after the final training session: day 9). Insomnia symptoms will be again assessed at follow-up (day 16). Secondary outcomes include examining whether sleep associated monitoring and worry are related to a sleep-related attentional bias in insomnia, and whether such reports reduce following ABM. All main analyses will be carried out on completion of follow-up assessments. The trial is supported by the Department of Psychology, Sociology and Politics at Sheffield Hallam University.

Discussion

This study will extend the research base examining the efficacy of attentional bias modification for insomnia.

Trial registration

ISRCTN (ISRCTN11643569, registered on 5 June 2018).

Pre-sleep arousal can be associated with efficient processing of sleep-related information

BACKGROUND AND OBJECTIVES

Cognitive bias to sleep-related information is thought to be a core feature of sleep disturbances. The bias may enhance pre-sleep arousal, such as excessive worry about sleeplessness, which prevents people from initiating normal sleep onset. The present study focused on (a) attention bias toward sleep-related stimuli and (b) difficulty in updating working memory for sleep-related stimuli as two possible mechanisms underlying pre-sleep cognitive arousal.

METHOD

Participants (n = 61, a community sample) completed a dot-probe task (with sleep-related and matched control word stimuli) and a 1-back and 2-back task (with sleep-related and non-sleep-related pictorial stimuli).

RESULTS

For the dot-probe task, the results showed no significant association between pre-sleep cognitive arousal and sleep-related attention bias. However, the results of the 2-back task suggest that pre-sleep arousal is associated with decreased interference by sleep-related stimuli in maintaining non-sleep-related information. That is, individuals with higher levels of pre-sleep arousal are more efficient at processing sleep-related materials.

LIMITATIONS

The non-clinical nature of the sample may limit the clinical implications of the findings.

CONCLUSIONS

Although the current results cannot be explained by the extant cognitive theories of insomnia, we offer an alternative explanation based on the idea of worry as mental habit: mental processes that occur frequently (e.g., repetitive thoughts about sleep) require less cognitive resource. Therefore, sleep-related information may be processed easily without consuming much cognitive effort.

Cognition As a Therapeutic Target in the Suicidal Patient Approach

The current considerations about completed suicides and suicide attempts in different cultures call the attention of professionals to this serious public health problem. Integrative approaches have shown that the confluence of multiple biological and social factors modulate various psychopathologies and dysfunctional behaviors, such as suicidal behavior. Considering the level of intermediate analysis, personality traits and cognitive functioning are also of great importance for understanding the suicide phenomenon. About cognitive factors, we can group them into cognitive schemas of reality interpretation and underlying cognitive processes. On the other hand, different types of primary cognitive alterations are related to suicidal behavior, especially those resulting from changes in frontostriatal circuits. Among such cognitive mechanisms can be highlighted the attentional bias for environmental cues related to suicide, impulsive behavior, verbal fluency deficits, non-adaptive decision-making, and reduced planning skills. Attentional bias consists in the effect of thoughts and emotions, frequently not conscious, about the perception of environmental stimuli. Suicidal ideation and hopelessness can make the patient unable to find alternative solutions to their problems other than suicide, biasing their attention to environmental cues related to such behavior. Recent research efforts are directed to assess the possible use of attention bias as a therapeutic target in patients presenting suicide behavior. The relationship between impulsivity and suicide has been largely investigated over the last decades, and there is still controversy about the theme. Although there is strong evidence linking impulsivity to suicide attempts. Effective interventions address to reduce impulsivity in clinical populations at higher risk for suicide could help in the prevention. Deficits in problem-solving ability also seem to be distorted in patients who attempt suicide. Understanding cognitive changes in patients who attempt suicide open an important perspective in the approach of patients with mental disorders. Identifying cognitive deficits in these patients, along with personality traits, depressive symptoms, and suicidal cognitive schemas may indicate to the psychiatrist the need for emergency care. Behavioral and cognitive interventions have been associated with reductions in suicide ideation, as well as suicide attempts in different populations.