DOI

  • Юрий Геннадьевич Павлов
The paper provides a review of publications in neurofeedback for treatment of addictive disorders. We performed a comprehensive analysis of the effectiveness and restrictions of existing varieties of neurofeedback in treatment of addiction. In the second part of the article we have considered problems arising in the evaluation of the effectiveness of training with biofeedback and possible ways to resolve them. Efficacy criteria adapted by the Association for Applied Psychophysiology and Biofeedback (AAPB) and the International Society for Neurofeedback and Research (ISNR) were used. Peniston Training Protocol (Alpha/Theta Training) is described. The influence of the placebo effect, the complex nature of the treatment and comorbid diagnosis to analyze the effectiveness of its use are explained. The effect of the Scott-Kaiser Protocol in psycho-stimulant abusers. The author describes the Alpha-Stimulation Training Protocol, a wide range of its applications with respect to other protocols, and provides a weak evidence base. The perspectives of neurometric approach application in the development of biofeedback protocols and approach to objective evaluation of the effectiveness of training by detecting the gamma rhythm reactivity in response to specific stimuli associated with addiction are considered. We offered recommendations how to improve the quality of the research in the field of clinical applications of neurofeedback. The quality can be achieved in the observational group by independent groups of researchers, as well as improved procedures for description of the experiment, a careful selection of subjects and selection criteria for successful session and training as a whole.
Translated title of the contributionEfficacy of Addiction Treatment by EEG biofeedback
Original languageRussian
Pages (from-to)80-90
Number of pages11
JournalНациональный психологический журнал
Issue number2(10)
DOIs
Publication statusPublished - 2013

    GRNTI

  • 15.21.00

    Level of Research Output

  • VAK List

ID: 7716177