Addictive Disorders

Biofeedback Interventions for Impulsivity-related Processes in Addictive Disorders

Abstract Purpose of Review Biofeedback is a promising technique that has been used as a treatment tool for different psychological disorders. In this regard, central (neurofeedback) and peripheral psychophysiological signals are presented as comprehensible stimuli with the aim of training specific processes. This review summarizes recent evidence about its use for the treatment of impulsivity-related processes in addictive disorders. Recent Findings Neurofeedback (NFB) protocols, based on electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have focused on substance use disorders. Biofeedback protocols using peripheral measures have been mainly based on heart rate variability and focused on behavioral addictions. EEG-NFB reported good results in the reduction of hyperarousal, impulsivity and risk taking in alcohol use disorder, and decreased rates of smoking and less craving in nicotine addiction. In fMRI-NFB, effective NFB performance has been related with better clinical outcomes in substance use disorders; however, its implication for treatment is still unclear. Heart rate variability biofeedback results are scarce, but some interventions have been recently designed aimed at treating behavioral addictions. Summary In addictive disorders, biofeedback interventions for impulsivity-related processes have shown promising results, although the literature is still scarce. Further research should aim at proving the effectiveness of biofeedback protocols as a treatment option for impulsivity in addictive disorders.

Neurofeedback Rehabilitation Reduces Anxiety in Methamphetamine Abusers

Addictive disorders are characterized by cognitive, behavioral, and neurological impairments caused by dysregulations of brain structure that can extend well beyond early withdrawal in the months and years of recovery. The present study aimed to examine the efficacy of neurofeedback rehabilitation on anxiety in methamphetamine abusers. The sample consisted of 14 male methamphetamine drug addicts who were randomly assigned to an experimental group (n = 7) and a control group (n = 7). Participants were assessed for Axis I disorders (SCID) and the Beck Anxiety Inventory (BAI). Mixed repeated ANOVA, independent t-tests, and chi-square were used for data analysis. The experimental group received 18 sessions of neurofeedback rehabilitation and standard psychological interventions treatment as usual, while the control group received only standard interventions. Results showed that neurofeedback significantly reduced anxiety in methamphetamine abusers at posttreatment and during a one-month follow-up. Along with other psychological interventions, neurofeedback rehabilitation is recommended for methamphetamine abusers

e-Addictology: An Overview of New Technologies for Assessing and Intervening in Addictive Behaviors

Background: New technologies can profoundly change the way we understand psychiatric pathologies and addictive disorders. New concepts are emerging with the development of more accurate means of collecting live data, computerized questionnaires, and the use of passive data. Digital phenotyping, a paradigmatic example, refers to the use of computerized measurement tools to capture the characteristics of different psychiatric disorders. Similarly, machine learning-a form of artificial intelligence-can improve the classification of patients based on patterns that clinicians have not always considered in the past. Remote or automated interventions (web-based or smartphone-based apps), as well as virtual reality and neurofeedback, are already available or under development. Objective: These recent changes have the potential to disrupt practices, as well as practitioners' beliefs, ethics and representations, and may even call into question their professional culture. However, the impact of new technologies on health professionals' practice in addictive disorder care has yet to be determined. In the present paper, we therefore present an overview of new technology in the field of addiction medicine. Method: Using the keywords [e-health], [m-health], [computer], [mobile], [smartphone], [wearable], [digital], [machine learning], [ecological momentary assessment], [biofeedback] and [virtual reality], we searched the PubMed database for the most representative articles in the field of assessment and interventions in substance use disorders. Results: We screened 595 abstracts and analyzed 92 articles, dividing them into seven categories: e-health program and web-based interventions, machine learning, computerized adaptive testing, wearable devices and digital phenotyping, ecological momentary assessment, biofeedback, and virtual reality. Conclusion: This overview shows that new technologies can improve assessment and interventions in the field of addictive disorders. The precise role of connected devices, artificial intelligence and remote monitoring remains to be defined. If they are to be used effectively, these tools must be explained and adapted to the different profiles of physicians and patients. The involvement of patients, caregivers and other health professionals is essential to their design and assessment.

Guidelines for psychosocial interventions in addictive disorders in India: An introduction and overview

While guidelines for psychosocial interventions in addictive disorders in India were earlier rooted in clinical experience and global empirical evidence, recently there have been efforts to develop guidelines for intervention based on the local needs assessments of specific populations and more appreciably, a testing of the effectiveness of the interventions. This supplement on psychosocial interventions for addictive disorders covers some of the important aspects of psychosocial interventions in five sections. Section I covers the general principles of management and specific assessment approaches, screening for cognitive dysfunction and assessment of co-morbidities. Section II focuses on specific psychosocial interventions including brief interventions, relapse prevention, cognitive behavioural interventions, psychoanalytical interventions, cognitive rehabilitation, interventions in dual disorders, marital and family therapy, psychosocial interventions for sexual dysfunction and sexual addictions. Section III describes innovative approaches including third wave therapies, video-based relapse prevention, digital technology as a tool for psychosocial interventions as well as psychosocial interventions in technological addictions. The latter part of this section also deals with psychosocial interventions in special populations including children and adolescents, women, sexual minorities and the elderly. Section IV pans into community based psychosocial interventions including community camps and workplace prevention. The need to develop task sharing through the involvement of trained health workers to deliver community and home-based interventions is highlighted. Section V underscores the ethical issues in different aspects of psychosocial intervention and the need for research in this area. Although there is a tendency to formulate addiction in either biomedical or psychosocial terms and to view interventions either as pharmacological or psychosocial, these dichotomies neither exist in the affected individual's mind, nor should be present in the treating clinician. A comprehensive understanding of addiction requires an understanding of the person in his/her environment and needs a personalised holistic approach that addresses the diverse physical/mental health, occupational, legal, social and aftercare needs.

Brainwave Biofeedback for Addictive Disorder

LORETA Neurofeedback for Addiction and the Possible Neurophysiology of Psychological Processes Influenced: A Case Study and Region of Interest Analysis of LORETA Neurofeedback in Right Anterior Cingulate Cortex

Introduction. This case study explores the efficacy of low-resolution electromagnetic tomographic (LORETA) neurofeedback (LNFB) in the right anterior cingulate cortex (ACC) as a method for addiction treatment and examines the frequency specific effects of this training in eight other regions of the cortex identified as playing an important role in substance use disorders. Methods. This case study was completed with one right-handed, 28-year-old female participant with 3 years of continuous abstinence from polysubstance abuse; her drugs of choice were heroin and alcohol, and she reported an 8-year history of alcohol abuse and a 4-year history of heroin use (IV). She completed 25 sessions of LNFB training in which she increased 14-18 Hz activity in the right ACC. We utilized electrophysiological measures to assess the increase or decrease in eight regions of interest (ROI): the right hippocampus, the right amygdaloid complex, the right orbitofrontal cortex (OFC), the right occipital lobe, the right insular cortex, the right uncus, and two regions in the left prefrontal cortex and compared them using complex linear mixed model and partial correlation procedures. Results. The data indicate significant associations between these limbic and cortical regions. The linear increase in the right ACC was in the desired direction; however, this will require more than 25 sessions to reach significance. The effects of training in the right ACC show significant increase and decrease for all frequencies in specific regions of interest.Conclusion. This is the first study of its kind to explore the relationship between these nine ROI as influenced by LNFB in the right ACC. The data suggest that these regions may play an intricate role in behaviors and characteristics involved in addiction; specific changes in the alpha frequency in limbic regions and increases in associations between regions in the theta frequency may influence personality and other behaviors associated with addictive traits. This case study illustrates the possible neural mechanisms involved in the negative self-reference associated with addiction even after a significant period of abstinence and possibly offers insight into antecedents to the onset of substance use disorders.