What is the analgesic effect of EEG neurofeedback for people with chronic pain? A systematic review

Researchers: A/Prof Sylvia Gustin, Dr Negin Hesam-Shariati, Dr Wei-Ju Chang, A/Prof James McAuley, Dr Andrew Booth, A/Prof Toby Newton-John, Prof Chin-Teng Lin, A/Prof Zina Trost Chronic pain is a global health problem, affecting around one in five individuals in the general population. The understanding of the key role of functional brain alterations in the generation of chronic pain has led researchers to focus on pain treatments that target brain activity. Electroencephalographic (EEG) neurofeedback attempts to modulate the power of maladaptive EEG frequency powers to decrease chronic pain. Although several studies provide promising evidence, the effect of EEG neurofeedback on chronic pain is uncertain. This systematic review aims to synthesise the evidence from randomised controlled trials (RCTs) to evaluate the analgesic effect of EEG neurofeedback. The search strategy will be performed on five electronic databases (Cochrane Central, MEDLINE, Embase, PsycInfo, and CINAHL) for published studies and on clinical trial registries for completed unpublished studies. We will include studies that used EEG neurofeedback as an intervention for people with chronic pain. Risk of bias tools will be used to assess methodological quality of the included studies. RCTs will be included if they have compared EEG neurofeedback with any other intervention or placebo control. The data from RCTs will be aggregated to perform a meta-analysis for quantitative synthesis. In addition, non-randomised studies will be included for a narrative synthesis. The data from non-randomised studies will be extracted and summarised in a descriptive table. The primary outcome measure is pain intensity assessed by self-report scales. Secondary outcome measures include depressive symptoms, anxiety symptoms, and sleep quality measured by self-reported questionnaires. Further, we will investigate the non-randomised studies for additional outcomes addressing safety, feasibility, and resting-state EEG analysis.