Effectiveness Not Established

EEG Biofeedback

for Cognitive Impairment

EEG biofeedback, or neurofeedback, involves real-time display of brain electrical activity provided to the individual as visual or auditory information. Use of this feedback approach was studied in patients with cancer for its effect on cognitive impairment, sleep-wake disturbances, and fatigue.

Systematic Review/Meta-Analysis

Luctkar-Flude, M., & Groll, D. (2015). A systematic review of the safety and effect of neurofeedback on fatigue and cognition. Integrative Cancer Therapies, 14, 318–340. 

Purpose

STUDY PURPOSE: To explore the efficacy and safety of electroencephalograph (EEG) biofeedback, or neurofeedback, on fatigue and cognitive impairment
 
TYPE OF STUDY: Systematic review

Search Strategy

DATABASES USED: OVID MEDLINE (1946 to third week of November, 2013); EMBASE (1947 to the 44th week of 2013); PsycINFO (1967 to the first week of December, 2013); AMED (1985 to December 2013); CIHAHL (1978 to the first week of December, 2013); hand searches also were conducted of the major journals reporting on neurofeedback and reference lists of included studies
 
KEYWORDS: Neurofeedback, brain biofeedback, EEG biofeedback, fatigue, cognitive disorders, and cognition
 
INCLUSION CRITERIA: (1) Reported on adult cancer survivors, individuals with other chronic health conditions, or nonclinical populations seeking to decrease fatigue or enhance cognitive abilities; (2) reported results of randomized, controlled trials, nonrandomized, controlled trials, controlled before-and-after studies, cohort, case control, or descriptive studies that assessed effectiveness or safety of EEG biofeedback or neurofeedback therapy; and (3) written in English
 
EXCLUSION CRITERIA: Studies on children, editorials, reviews, expert opinion papers, and studies published as abstracts only

Literature Evaluated

TOTAL REFERENCES RETRIEVED: 197
 
EVALUATION METHOD AND COMMENTS ON LITERATURE USED: This systematic review was conducted using the Joanna Briggs Institute (JBI) methodology, including JBI critical appraisal and data extraction tools. Only two studies were deemed to be of high quality.

Sample Characteristics

  • FINAL NUMBER STUDIES INCLUDED = 17 (10 experimental and seven descriptive)
  • SAMPLE RANGE ACROSS STUDIES: 6–64 patients (experimental), 5–100 patients (descriptive)
  • KEY SAMPLE CHARACTERISTICS: Age range was 6–84 years; only one study reported on patients with cancer (n = 23)

Phase of Care and Clinical Applications

PHASE OF CARE: Late effects and survivorship

Results

Improvements were noted in fatigue in eight of 17 studies, and improvement was noted in cognition in 14 of the 17 studies reviewed. Neurofeedback interventions were well tolerated with only three studies reporting any side effects.

Conclusions

Insufficient evidence was presented to suggest that these complementary and alternative medicine therapies (neurofeedback) are useful in the management of cancer-related fatigue or cognition.

Limitations

  • Only one of the 17 studies included a population of cancer survivors (BCS, n = 23)
  • Heterogeneity of other samples; majority non-clinical samples
  • Majority of studies were low-quality

Nursing Implications

Additional research needs to be done before this type of therapy can be recommended.

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Research Evidence Summaries

Alvarez, J., Meyer, F. L., Granoff, D. L., & Lundy, A. (2013). The effect of EEG biofeedback on reducing postcancer cognitive impairment. Integrative Cancer Therapies, 12, 475–487.

Study Purpose

To determine the feasibility of using electroencephalography (EEG) biofeedback (neurofeedback) and identify its potential effects on cognitive impairment, sleep quality, fatigue, and psychological symptoms.

Intervention Characteristics/Basic Study Process

Neurofeedback was provided using an EEG system that detects and alerts the brain of phase changes to increase brain flexibility and resilience. Single EEG sensors, placed at the left C3 and right C4 for each brain hemisphere, analyze EEG activity for identification of phase state changes in the brain. During the session, the patient listened to music while sitting quietly; brief interruptions of the music signal alerted the patient that the software detected phase changes and was providing the brain feedback. No patient response or action was required because it is believed that the brain uses the feedback for its own self-organization without conscious action. Patients had twice weekly sessions for 10 weeks. Assessments were performed prior to beginning the sessions and during the fourth, seventh, and tenth week of sessions.

Sample Characteristics

  • The study included 23 Caucasian women with a median age of 56 years (range 43–70).
  • All patients were breast cancer survivors with self-reported cognitive impairment since diagnosis.
  • Median time since last chemotherapy was 24 months (range 9–59).
  • Of the patients, 26% were taking antidepressants and 39% were taking sleep medication.

Setting

The study was conducted at a single outpatient site in Ohio. 

Phase of Care and Clinical Applications

The study has clinical applicability for late effects and survivorship.

Study Design

The study used a feasibility quasiexperimental design.

Measurement Instruments/Methods

  • Functional Assessment of Cancer Therapy–Cognitive Function (FACT-C)
  • Functional Assessment of Chronic Illness Therapy–Fatigue (FACIT-F)
  • Pittsburgh Sleep Quality Index (PSQI)
  • Brief Symptom Inventory (BSI)

Results

Significant symptom presence and dysfunction were reported by this sample at baseline, as compared to normative data. Baseline comparisons to normative sample showed significant differences from the norms in all measures, indicating significant dysfunction. FACT, FACIT, and PSQI scores improved over time, although not at a constant rate over longitudinal time points. At study conclusion, symptom report of dysfunction no longer differed significantly from normative populations on three of four FACT-C subscales, FACIT, and PSQI. The proportion of patients using sleep medications declined from 39% to 17% by study conclusion. No adverse effects of the intervention were identified.

Conclusions

EEG neurofeedback was shown to be feasible and potentially beneficial for improving cognitive function, sleep, and fatigue in breast cancer survivors.

Limitations

  • The study had a small sample size, with less than 30 patients.
  • The study had risks of bias due to no control group, no blinding, and no random assignment.
  • Unintended interventions or applicable interventions were not described that would influence the results.
  • The intervention was expensive, impractical, or required training.
  • Findings were not generalizable.
  • This intervention requires specialized equipment, training, and setting to provide EEG feedback sessions.
  • It was not stated whether patients were receiving any other interventions aimed at these symptoms.
  • Cognitive function was measured only with self-report instruments with repeated measures design; thus, self-reported improvements may be because of testing effects.
  • No objective cognitive function instruments were used to determine cognitive impairment at time of baseline or improvement in cognitive function over time.
  • The sample was a homogenous group of patients, potentially limiting generalizability to other patient groups.

Nursing Implications

This study reported a potentially promising intervention that may have a positive effect on several symptoms experienced by breast cancer survivors. Additional well-designed clinical trials are needed to assess the efficacy of this approach.

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