A Systematic Review of the Safety and Effect of Neurofeedback on Fatigue and Cognition
Bibliographic record
Abstract
BACKGROUND: Many cancer survivors continue to experience ongoing symptoms, such as fatigue and cognitive impairment, which are poorly managed and have few effective, evidence-based treatment options. Neurofeedback is a noninvasive, drug-free form of brain training that may alleviate long-term symptoms reported by cancer patients. OBJECTIVE: The purpose of this systematic review of the literature was to describe the effectiveness and safety of neurofeedback for managing fatigue and cognitive impairment. METHODS: A systematic review of the literature was conducted using Joanna Briggs Institute (JBI) methodology. A comprehensive search of 5 databases was conducted: Medline, CINAHL, AMED, PsycInfo, and Embase. Randomized and nonrandomized controlled trials, controlled before and after studies, cohort, case control studies, and descriptive studies were included in this review. RESULTS: Twenty-seven relevant studies were included in the critical appraisals. The quality of most studies was poor to moderate based on the JBI critical appraisal checklists. Seventeen studies were deemed of sufficient quality to be included in the review: 10 experimental studies and 7 descriptive studies. Of these, only 2 were rated as high-quality studies and the remaining were rated as moderate quality. All 17 included studies reported positive results for at least one fatigue or cognitive outcome in a variety of populations, including 1 study with breast cancer survivors. Neurofeedback interventions were well tolerated with only 3 studies reporting any side effects. CONCLUSIONS: Despite issues with methodological quality, the overall positive findings and few reported side effects suggest neurofeedback could be helpful in alleviating fatigue and cognitive impairment. Currently, there is insufficient evidence that neurofeedback is an effective therapy for management of these symptoms in cancer survivors, however, these promising results support the need for further research with this patient population. More information about which neurofeedback technologies, approaches, and protocols could be successfully used with cancer survivors and with minimal side effects is needed. This research will have significance to nurses and physicians in oncology and primary care settings who provide follow-up care and counseling to cancer survivors experiencing debilitating symptoms in order to provide information and education related to evidence-based therapy options.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".