Features and Impact of Sleep Disturbances and Efficacy of Neurofeedback for Symptom Improvement in Patients with Fibromyalgia(2/3)

Project: A - Government Institutionb - National Science and Technology Council

Project Details


The proposed grant entails a series of three studies. First, we will conduct a meta-analysis to determine the differences in sleep characteristics in patients with fibromyalgia compared with healthy controls (Aim 1). Second, we will determine the impact of insomnia on symptom severity and health resources utilization in patients with fibromyalgia by conducting a population-based study in a cohort of fibromyalgia patients (Aim 2). Third, we will examine the efficacy of sensorimotor rhythm (SMR) neurofeedback training for improvements of pain, overall symptom severity, sleep quality and cognitive function in patients with fibromyalgia using a randomized controlled trial (RCT) design (Aim 3). For Aim 1, 6 databases including PubMed, Medline, Embase, PsychINFO, CINAHL and Web of Science will be searched from inception until December 31, 2016 using fibromyalgia AND sleep as keywords. The inclusion criteria are studies including patients with fibromyalgia and healthy participants as the comparison group; studies that measured sleep characteristics by using polysomnography, the Pittsburgh Sleep Quality Index, an actigraph, or a sleep diary; and case–control study designs. The quantitative data will be entered into Comprehensive Meta-Analysis software, version 2.0 (Biostat, Englewood, NJ), and two-sided tests will be used. For Aim 2, we will analyze data retrieved from the Longitudinal Health Insurance Database 2010. Patients with fibromyalgia diagnosed between 2000 and 2001 will be divided into two groups: patients with comorbid insomnia and patients without insomnia. The relationship between insomnia and the odds (OR) of fibromyalgia-indicated pharmacotherapies use from the index date to the end of 2013 will be examined using the multivariable logistic regression while adjusting for age, sex, insurance premium, and the Charlson Comorbidity Index (CCI). The OR and associated 95% confidence interval will be reported. The association between insomnia and the ambulatory care visits tracked from the index date to the end of 2013 will be examined using the multivariate generalized linear models with the adjustment of age, sex, insurance premium, and CCI. For Aim 3, eligible participants (N = 80) will be randomized to receive 8 weeks of SMR neurofeedback (SMRG) or 8 weeks of telephone support (CG). The primary outcomes include the average pain score determined by the Brief Pain Inventory and the revised Fibromyalgia Impact Questionnaire score and the secondary outcomes include sleep quality and cognitive function which will be measured before and after treatment. To determine the effectiveness of SMR training on primary and secondary outcomes, differences in outcome variables will be analyzed with mixed-effects linear regression models with the covariance structure unstructured. We will perform statistical analyses according to the intention-to-treat principle. All missing vales will be imputed using the last value carry-forward method. The between-group differences at the two post-test assessments will be examined using a mixed-model in which group and time interaction will be included. We will adjust for the baseline score on the outcome variable and for demographics and comorbidities that differ significantly between the SMRG and CG at baseline. By completing the proposed meta-analysis and the population-based observation study, the role played by sleep in fibromyalgia can be demonstrated. Insomnia or sleep difficulty can therefore be used both as a clinical indicator for risk stratification and a target for treatment in patients with fibromyalgia. Findings from the RCT will provide empirical evidence to support the efficacy of SMR neurofeedback for fibromyalgia.
Effective start/end date8/1/177/31/18


  • Fibromyalgia
  • Sleep
  • Neurofeedback
  • Cognitive Function


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.