Edited by: Guy Cheron, Université libre de Bruxelles, Belgium
Reviewed by: Charles-Yannick Guezennec, Université de Perpignan Via Domitia, France; Katie Moraes de Almondes, Federal University of Rio Grande do Norte, Brazil
This article was submitted to Health Psychology, a section of the journal Frontiers in Psychology
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
The purpose of this study was to examine the effectiveness of a neuro-meditation program to support nurses during the COVID-19 pandemic. Forty-five (10 men and 35 women) nurses were classified into three groups based on their systolic blood pressure: normotensive (G-nor;
The study was conducted at Bioesterel, Sophia-Antipolis, France as a clinical trial: Neuro-meditation improves sleep quality,
Work-related stress and burnout are a common occurrence in health care employees (
The intense workload, uncertainty, and lack of resources during the COVID-19 (severe acute respiratory syndrome coronavirus 2) pandemic has placed all health care workers under extremely stressful conditions and at an increased risk of burnout (
Mindfulness-based interventions (MBI) may be an effective strategy to improve sleep quality and reduce the impact of stress-related symptoms (
As with any skill, it can be difficult for those who are inexperienced with meditation to develop the level of awareness and attention required to significantly benefit from the practice. By providing electroencephalogram biofeedback, neuro-meditation may speed the learning process and allow individuals to achieve and maintain the desired state of consciousness more quickly, thereby increasing the effectiveness of the program (
A convenience sample of 45 people (10 men and 35 women) aged 25–61 working as nursing staff in hospitals and assisted living facilities in the region were recruited. After being fully informed of the purpose and protocols, all participants gave informed consent. The study was approved by the University of Technology, Sydney (ETH21-6116) in accordance with the Declaration of Helsinki (1964; revised 2001) and registered with the German Clinical Trial Register (DRKS00025731). It conformed to the Committee on Publication Ethics (COPE) and the International Committee of Medical Journal Editors (ICMJE) recommendations. The investigation was conducted from June to August 2020 to examine strategies that can reduce stress and improve the health and wellbeing of nursing staff under extreme workloads during the initial wave of the COVID-19 pandemic. Immediately prior to the investigation, France was locked down in a state of health emergency from March to May 2020 with a peak in COVID-19-related visits to emergency departments (
During the initial visit to the laboratory (Bioesterel, Sophia Antipolis, France), each participant was examined by a cardiologist and a medical doctor. Participants were excluded if they showed premature heart beats, serious abnormal heart rhythms, suffered from muscular and/or joint disorders, were on hypertensive, antidepressant, psychotropic, or anxiolytic medication. Those who reported a current inflammatory disorder, sleep apnea, restless legs syndrome, autoimmune disease, type 1 diabetes mellitus, hepatitis C, cancer, or acute infection in the past 2 weeks were excluded. Participants that reported sleep apnea or restless legs syndrome were excluded as these conditions can influence sleep measures but are not related to sleep. Also excluded were people with narcolepsy, epilepsy, central disorders of hypersomnolence, irregular sleep–wake rhythm disorder, and parasomnia. These pathologies are known to influence actimetry and polysomnography values (
Participant gender, age, and body composition (mean ± SD).
Characteristic | G-con ( |
G-nor ( |
G-hyp ( |
---|---|---|---|
Gender (M/F) | 5/11 | 2/14 | 3/10 |
Age (years) | 44.9 ± 10.6 | 43.8 ± 11.0 | 45.2 ± 10.7 |
Body mass index (kg/m2) | 26.1 ± 5.6 | 25.6 ± 5.8 | 27.2 ± 5.3 |
Fat mass (%) | 30.1 ± 8.2 | 30.5 ± 8.4 | 32.0 ± 7.6 |
G-con, control group; G-nor, normotensive group; G-hyp, hypotensive group; M, male; and F, female.
A parallel randomized control trial was used to establish the effectiveness of a MBI using the Rebalance© Impulse (Rebalance Tech Corp., Miami, United States).
Experimental design. Baseline, 3-day data collection period prior to Rebalance© session 1; REB-1 −5, −10, Rebalance© session number 1, 5, and 10, respectively; REB-3 −6, −9, 3-day data collection period following Rebalance© session number 3, 6, and 9, respectively; Pre-REB: prior to Rebalance© Program; Post-REB: following Rebalance© Program. HRV, heart rate variability; HRmean, average heart rate during HRV measurement; SSQ, Spiegel Sleep Quality questionnaire; FIRST, Ford Insomnia Response to Stress Test.
The G-nor and G-hyp groups followed the same Rebalance© Program during the four-week intervention where 2–3 sessions were completed per week. Participants completed their session individually at a similar time of day on each occasion in the Rebalance© Impulse room at the laboratory in Bioesterel, Sophia Antipolis, France. The G-con group did not receive any treatment. Rebalance© Impulse is a non-invasive cognitive stimulation and mindfulness training device based on applied neuroscience (
Schematic representation of the Rebalance© Impulse.
Sleep was monitored across four, 3-day periods at Baseline (three nights prior to the Rebalance© Program), and for three nights following the third (REB-3), sixth (REB-6), and ninth (REB-9) Rebalance© session. These time points were chosen to ensure an appropriate baseline prior to commencement of the MBI (
During each monitoring period, participants completed daily sleep diaries to ensure reliable sleep–wake scoring (
Time in bed (h:min): the amount of time spent in bed attempting to sleep between bedtime and get-up time.
Bedtime (hh:mm): the self-reported clock time at which a participant went to bed to attempt to sleep.
Get-up time (hh:mm): the self-reported clock time at which a participant got out of bed and stopped attempting to sleep.
Sleep onset latency (min): the period between bedtime and sleep start.
Actual sleep time (h:min): the time asleep from sleep start to sleep end.
Sleep efficiency (%): sleep duration expressed as a percentage of time in bed.
Fragmentation index: a measure of restlessness during sleep, using the percentage of epochs where activity is >0.
Immobile time (min): the actual time spent immobile during time in bed.
The SSQ (
Heart rate data (OH1, Polar, Kempele, Finland) was collected in R–R interval mode for 4 min while the participant was lying quietly in the dedicated Rebalance© Impulse room. Data from the last 3 min of each sampling period were used for analysis, to allow the heart rate to stabilize. No particular breathing frequency was imposed (
HRV data were analyzed using specialized HRV analysis software (Kubios HRV analysis Software, Finland;
Blood was drawn and collected into one 6-ml serum tube and one 6-ml EDTA plasma tube (Becton, Dickinson and Company Vacutainer, Franklin Lakes, NJ). These were centrifuged at 3,000
All data were stored in an electronic database and analyzed using specialized statistical software (SPSS v20.0, Chicago, IL, United States). Results are expressed as mean ± standard deviation (SD). The normality of distribution for each variable was tested using the Shapiro–Wilk test. Statistical analysis was completed using a factorial ANOVA by group (G-con, G-nor, and G-hyp) and time (Pre-REB, Post-REB) for SBP, DBP, resting heart rate, SSQ, FIRST, and endocrine variables; and time (Baseline, REB-3, REB-6, and REB-9) for actimetry parameters; and time (REB-1, REB-5, and REB-10) for HRV and HRmean variables. If a significant time–group interaction effect was observed, Tukey’s Honest Significant Difference tests were performed as post-hoc analysis to further discern differences. When assumptions of normality or homogeneity of variances were not met, the data were log-transformed before analysis. Means were then de-transformed back to their original units. The criteria to interpret the magnitude of effect size was >0.2
All participants completed the entire study protocol. Calculated scores for the SSQ and FIRST are presented in
Changes in sleep quality, sleep reactivity, resting heart rate, and blood pressure before and after the Rebalance© Program (mean ± SD).
Parameter | Pre-REB | Post-REB | Change (%) |
|
Cohen’s |
|
---|---|---|---|---|---|---|
Sleep quality (SSQ) |
G-con | 18.8 ± 5.0 | 19.4 ± 3.7 | 3.2 | 0.74 | 0.14 |
G-nor | 19.5 ± 2.5 | 22.5 ± 3.3 | 15.4 | 0.061 | 1.02 | |
G-hyp | 16.1 ± 3.1 | 22.9 ± 3.1 | 42.2 | <0.01 |
2.19 | |
Sleep reactivity (FIRST) |
G-con | 23.8 ± 5.3 | 25.2 ± 5.7 | 5.8 | 0.53 | 0.25 |
G-nor | 26.6 ± 6.9 | 26.6 ± 5.7 | 0.0 | 1.00 | 0.00 | |
G-hyp | 28.1 ± 2.5 | 24.3 ± 5.5 | −13.5 | 0.062 | 0.89 | |
Resting heart rate (bpm) |
G-con | 75.2 ± 10.7 | 73.1 ± 11.4 | −2.8 | 0.63 | 0.19 |
G-nor | 72.4 ± 8.7 | 71.5 ± 8.7 | −1.2 | 0.77 | 0.10 | |
G-hyp | 81.1 ± 10.8 |
68.1 ± 9.2 | −16.0 | <0.01 |
1.30 | |
Systolic blood pressure (mmHg) |
G-con | 129.6 ± 17.0 | 127.8 ± 16.2 | −1.4 | 0.68 | 0.11 |
G-nor | 120.8 ± 9.3 | 117.7 ± 7.5 | −2.6 | 0.31 | 0.37 | |
G-hyp | 150.2 ± 8.3 |
130.8 ± 14.1 |
−12.9 | <0.01 |
1.68 | |
Diastolic blood pressure (mmHg) |
G-con | 75.5 ± 5.1 | 79.2 ± 9.3 | 4.9 | 0.98 | 0.49 |
G-nor | 74.6 ± 7.1 | 71.1 ± 7.0 | −4.7 | 0.18 | 0.50 | |
G-hyp | 86.4 ± 9.4 |
77.9 ± 10.0 |
−9.8 | 0.036 | 0.88 |
Pre-REB, prior to Rebalance© Program, Post-REB, following Rebalance© Program. G-con, control group; G-nor, normotensive group; G-hyp, hypotensive group. SSQ, Spiegel Sleep Quality questionnaire; FIRST, Ford Insomnia Response to Stress Test. The criteria to interpret the magnitude of the effect size were as follows: >0.2 small, >0.5 moderate, >0.8 large, and > 1.3 very large.
Interaction effect (
Interaction effect (
Significantly different from G-con (
Significantly different from G-nor (
Significantly different from G-nor (
Changes in perceived sleep quality throughout the Rebalance© Program. G-con, control group; G-nor, normotensive group; G-hyp, hypotensive group. Baseline, 3-day data collection period prior to Rebalance© session 1; REB-3, −6, −9, 3-day data collection period following Rebalance© session number 3, 6, and 9, respectively. Box plots represent median interquartile range (IQR, Q25–Q75), and error bars are maximal and minimal observations within 1.5 × IQR. Squares represent maximum and minimum observations above or below 1.5 × IQR. * and **Significantly different from Baseline (
Sleep actigraphy data at selected time points throughout the Rebalance© Program (mean ± SD).
Parameter | Baseline | REB-3 | REB-6 | REB-9 | |
---|---|---|---|---|---|
Time in bed (h:min) | G-con | 7:42 ± 0:24 | 7:48 ± 0:30 | 7:54 ± 0:30 | 7:48 ± 0:30 |
G-nor | 7:30 ± 1:06 | 7:36 ± 1:00 | 7:42 ± 0:42 | 7:30 ± 0:42 | |
G-hyp | 7:36 ± 0:48 | 7:36 ± 0:24 | 7:36 ± 1:00 | 7:12 ± 0:48 | |
Assumed sleep time (h:min) | G-con | 7:18 ± 0:30 | 7:24 ± 0:36 | 7:30 ± 0:24 | 7:30 ± 0:36 |
G-nor | 7:06 ± 1:06 | 7:18 ± 1:00 | 7:18 ± 0:42 | 7:06 ± 0:42 | |
G-hyp | 7:12 ± 0:48 | 7:12 ± 0:30 | 7:12 ± 1:00 | 6:48 ± 0:48 | |
Actual sleep time (h:min) | G-con | 6:06 ± 0:36 | 6:12 ± 0:30 | 6:18 ± 0:24 | 6:12 ± 0:30 |
G-nor | 6:00 ± 1:00 | 6:12 ± 0:54 | 6:12 ± 0:42 | 6:06 ± 0:42 | |
G-hyp | 6:06 ± 0:48 | 6:12 ± 0:36 | 6:06 ± 0:48 | 5:54 ± 0:48 | |
Sleep efficiency (%) | G-con | 83.7 ± 4.3 | 83.1 ± 2.9 | 83.9 ± 3.4 | 83.4 ± 4.6 |
G-nor | 85.4 ± 3.6 | 84.6 ± 3.2 | 85.1 ± 4.6 | 85.6 ± 4.0 | |
G-hyp | 84. 3 ± 5.6 | 85.1 ± 4.4 | 84.7 ± 4.8 | 86.5 ± 3.8 |
|
Immobile time (%) |
G-con | 84.1 ± 4.1 | 83.7 ± 2.5 | 84.8 ± 2.9 | 84.3 ± 3.9 |
G-nor | 85.2 ± 3.0 | 85.4 ± 2.3 | 85.5 ± 2.9 | 86.1 ± 2.5 | |
G-hyp | 85.9 ± 4.6 | 86.6 ± 3.3 | 85.9 ± 4.0 | 87.5 ± 2.9 | |
Fragmentation index |
G-con | 34.6 ± 10.0 | 33.5 ± 8.9 | 33.0 ± 8.9 | 34.1 ± 9.8 |
G-nor | 32.0 ± 6.1 | 31.6 ± 3.6 | 32.3 ± 6.8 | 29.0 ± 6.6 |
|
G-hyp | 30.3 ± 8.3 | 28.5 ± 7.1 | 32.7 ± 5.9 | 26.6 ± 7.0 |
Significant time–group interaction (
Significantly different from Baseline (
Significantly different from previous measure (
Significantly different from previous measure (
Resting heart rate and blood pressure values assessed before the Rebalance© Program were significantly higher in the G-hyp group compared to the G-con and G-nor groups (
A significant time–group interaction was reported in HRmean (
Changes in HRmean
Before and after the Rebalance© Program, cortisol blood concentrations were significantly higher in the G-nor and G-hyp groups compared with the G-con group (
Changes in cortisol
This study aimed to determine the effect of a MBI on stress-related parameters in nurses during the COVID-19 pandemic. The main finding of this study was that following 10, 30-min sessions of neuro-meditation using the Rebalance© Impulse the perceived sleep quality of all participants improved, and blood pressure was significantly reduced in those where it had been previously elevated. In participants that completed the MBI, cardiac regulation was also improved, as observed by a decrease in resting heart rate for the G-hyp group and an increase in HRV for the G-nor group. Combined, these results provide support for the implementation of neuro-meditation sessions to improve the health of nurses during periods of increased work stress.
While the effectiveness of MBI for nurses has been previously assessed with promising results, most studies have examined stress reduction
According to the FIRST scores, all participants in the study reported elevated levels of sleep reactivity and were at high risk of developing insomnia (FIRST score > 18;
Despite large effect sizes for the G-nor group, FIRST and SSQ scores were only improved in the G-hyp following the MBI. Previous studies have also provided preliminary, yet mixed evidence for the use of MBIs for sleep disturbances in adults (
There is accumulating evidence that low sleep efficiency (<85%;
Alongside reduced blood pressure, reduced sympathetic activity can also be reflected by a lower resting heart rate and increased HRV (
Electroencephalogram (EEG) studies suggest that increased alpha activity represents a calm mind and is a precursor for entering a meditative state (
Like other MBIs, the Rebalance© Impulse provides a potential non-pharmacological treatment for those under increased stress. Sleep disorders are often treated with pharmacotherapy (
Benefits of MBI are typically observed when participants complete both dedicated sessions and daily practice (
There are several limitations to the present investigation that should be acknowledged. An active treatment comparison group was not used and participants in the treatment groups were not blinded to the purpose of the intervention. This creates a potential for the benefits of the Rebalance© Program to be attributed to a placebo effect. Also, the age of the participants was heterogeneous and obese participants were not excluded. In addition, including participants with elevated blood pressure in the control group would have provided a direct comparison for the effectiveness of MBI on reducing blood pressure during periods of increased work-related stress. It is also recognized that a relatively small sample size was used. It is also unknown whether the acute changes after the neuro-meditation sessions were maintained as a follow-up at 6 and 12 months was not completed.
Neuro-meditation provided an effective, non-pharmacological treatment to combat increases in work-related stress symptoms in nurses during the COVID-19 pandemic. While future studies are required to fully elucidate the underlying mechanisms, initial evidence suggests that mindful meditation assists by reducing sympathetic activity, as demonstrated through enhanced sleep and the re-establishment autonomic control. These benefits were observed in participants who were previously untrained in meditative practices. This suggests that compared to other MBI, which often require a greater time commitment and training, the guided neuro-meditation and synchromotherapy accelerated the participants’ ability to achieve the desired meditative state. Collectively, these results support the use of neuro-meditation to promote health and wellbeing in nurses.
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
The studies involving human participants were reviewed and approved by the University of Technology, Sydney (ETH21-6116). The patients/participants provided their written informed consent to participate in this study.
CH: conceptualization, funding acquisition, methodology, research design, project administration, and writing. XN, AD, and FD: investigation and formal analysis. YR: resources, review, and editing. KS: writing and editing. All authors contributed to the article and approved the submitted version.
Financial support was provided to compensate the participants of the study and for the biochemical analyses. This study was conducted after the first lockdown due to COVID-19 in solidarity with the nursing staff.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.