The Analgesic Effect of Electroencephalographic Neurofeedback for People With Chronic Pain: Protocol for a Systematic Review and Meta-analysis

Evaluating the effectiveness of neurofeedback in chronic pain management: a narrative review

The prevalence and impact of chronic pain in individuals worldwide necessitate effective management strategies. This narrative review specifically aims to assess the effectiveness of neurofeedback, an emerging non-pharmacological intervention, on the management of chronic pain. The methodology adopted for this review involves a meticulous search across various scientific databases. The search was designed to capture a broad range of studies related to neurofeedback and chronic pain management. To ensure the quality and relevance of the included studies, strict inclusion and exclusion criteria were applied. These criteria focused on the study design, population, intervention type, and reported outcomes. The review synthesizes the findings from a diverse array of studies, including randomized controlled trials, observational studies, and case reports. Key aspects evaluated include the types of neurofeedback used (such as EEG biofeedback), the various chronic pain conditions addressed (like fibromyalgia, neuropathic pain, and migraines), and the methodologies employed in these studies. The review highlights the underlying mechanisms by which neurofeedback may influence pain perception and management, exploring theories related to neural plasticity, pain modulation, and psychological factors. The results of the review reveal a positive correlation between neurofeedback interventions and improved pain management. Several studies report significant reductions on pain intensity, improved quality of life, and decreased reliance on medication following neurofeedback therapy. The review also notes variations in the effectiveness of different neurofeedback protocols and individual responses to treatment. Despite the promising results, the conclusion of the review emphasizes the need for further research. It calls for larger, well-designed clinical trials to validate the findings, to understand the long-term implications of neurofeedback therapy, and to optimize treatment protocols for individual patients.

The analgesic effect of electroencephalographic neurofeedback for people with chronic pain: A systematic review and meta-analysis

BACKGROUND

Electroencephalographic (EEG) neurofeedback has been utilized to regulate abnormal brain activity associated with chronic pain.

METHODS

In this systematic review, we synthesized the evidence from randomized controlled trials (RCTs) to evaluate the effect of EEG neurofeedback on chronic pain using random effects meta-analyses. Additionally, we performed a narrative review to explore the results of non-randomized studies. The quality of included studies was assessed using Cochrane risk of bias tools, and the GRADE system was used to rate the certainty of evidence.

RESULTS

Ten RCTs and 13 non-randomized studies were included. The primary meta-analysis on nine eligible RCTs indicated that although there is low confidence, EEG neurofeedback may have a clinically meaningful effect on pain intensity in short-term. Removing the studies with high risk of bias from the primary meta-analysis resulted in moderate confidence that there remained a clinically meaningful effect on pain intensity. We could not draw any conclusion from the findings of non-randomized studies, as they were mostly non-comparative trials or explorative case series. However, the extracted data indicated that the neurofeedback protocols in both RCTs and non-randomized studies mainly involved the conventional EEG neurofeedback approach, which targeted reinforcing either alpha or sensorimotor rhythms and suppressing theta and/or beta bands on one brain region at a time. A posthoc analysis of RCTs utilizing the conventional approach resulted in a clinically meaningful effect estimate for pain intensity.

CONCLUSION

Although there is promising evidence on the analgesic effect of EEG neurofeedback, further studies with larger sample sizes and higher quality of evidence are required.