Skip to main content
  • Research note
  • Open access
  • Published:

Learning receptive awareness via neurofeedback in stressed healthcare providers: a prospective pilot investigation

Abstract

Objective

Because physicians and nurses are commonly stressed, Bispectral Indexâ„¢ (BIS) neurofeedback, following trainer instructions, was used to learn to lower the electroencephalography-derived BIS value, indicating that a state of receptive awareness (relaxed alertness) had been achieved.

Results

Ten physicians/nurses participated in 21 learning days with 9 undergoing ≤ 3 days. The BIS-nadir for the 21 days was decreased (88.7) compared to baseline (97.0; p < 0.01). From 21 wellbeing surveys, moderately-to-extremely rated stress responses were a feeling of irritation 38.1%; nervousness 14.3%; over-reacting 28.6%; tension 66.7%; being overwhelmed 38.1%; being drained 38.1%; and people being too demanding 52.4% (57.1% had ≥ 2 stress indicators). Quite a bit-to-extremely rated positive-affect responses were restful sleep 28.6%; energetic 0%; and alert 47.6% (90.5% had ≥ 2 positive-affect responses rated as slightly-to-moderately). For 1 subject who underwent 4 learning days, mean BIS was lower on day 4 (95.1) than on day 1 (96.8; p < 0.01). The wellbeing score increased 23.3% on day 4 (37) compared to day 1 (30). Changes in BIS values provide evidence that brainwave self-regulation can be learned and may manifest with wellbeing. These findings suggest that stress and impairments in positive-affect are common in physicians/nurses.

Trial Registration ClinicalTrials.gov NCT03152331. Registered May 15, 2017

Introduction

For nurses and physicians, concerns exist relative to emotional exhaustion, burnout, and job dissatisfaction. Among medical students, residents/fellows, and early career physicians, adverse manifestation rates were 30–40% for emotional exhaustion, 40–50% for burnout, 40–60% for depression, 7–9% for suicidal ideation, and 50–60% for fatigue [1]. The rate of emotional exhaustion, a risk for burnout, is substantial in nurses in the United States [2, 3]. Surveys have indicated that 20–35% of hospital-based nurses have expressed the intent to leave their current job in the near future [2, 4, 5].

Mindfulness is an attitudinal expression of receptive awareness (relaxed attention), wherein there is a distinction made between a direct experience occurring in the present moment as opposed to associated thoughts and interpretations about the experience [6]. Among physicians and nurses, a high mindfulness score was associated with less stress, greater wellbeing, and a positive emotional tone [7, 8]. Mindfulness training has been associated with reductions in stress or burnout risk in nurses [9,10,11] and physicians [10,11,12].

Neurofeedback (NFB) is a process in which an individual learns to intentionally alter their brainwave activity [13]. NFB is useful for decreasing anxiety [14,15,16] and for enhancing attention [17, 18], mood [19], memory [20], musical performance [21], and surgical technique [22]. Sensors are applied and an electroencephalography (EEG) device computes the power according to frequency bandwidths [13]. A reward bandwidth target is chosen, typically an intermediate range [13, 23]. A computer monitor screen produces visual symbolic images as a mechanism for providing moment-to-moment EEG feedback to the trainee.

Although combining mindfulness and NFB has been advocated [24], such a model has not been evaluated. The purpose of our study was to evaluate a model of mindfulness and NFB to facilitate learning receptive awareness (relaxed attention). As concerns with EEG artifacts and the fact that technologies for providing quantitative EEG analysis are continuously evolving [25], we selected the Bispectral Indexâ„¢ (BIS) monitor (Aspect Medical Systems, Newton, MA) to provide NFB signals [26, 27]. We hypothesized that receptive awareness or relaxed attention could be learned.

Main text

Physicians and nurses were welcomed to participate in the learning sessions. Each learning day consisted of two 12-min BIS monitor-NFB sessions. Immediately before session 1, specific instructions were given (Additional file 1). Immediately before session 2, additional detailed instructions were provided (Additional file 2).

Using the manufacturer’s instructions, the BIS sensor was applied to the participant’s left forehead and temporal fossa following a scrubbing of the skin with alcohol and then wiping with a dry cloth. The BIS monitor chart data function was set to 1-min intervals such that the BIS value would be recorded on the monitor hard drive. Awake BIS values were available from the literature and included 685 subjects [28]. The first BIS value (minute 1) on learning day 1 of the first session was also used as a baseline reference for the learners.

A wellbeing surveillance tool was developed after reviewing elements from 5 established systems [29,30,31,32,33]. The physician/nurse learner completed the wellbeing surveillance tool before session 1 on each day. The 7 stress indicators included irritation, nervousness, over-reaction, tension, feeling overwhelmed, feeling emotionally drained, and feeling that people demand too much. The learner rated each indicator based on the prior 3 days as follows: (1) extremely; (2) quite a bit; (3) moderately; (4) a little; and (5) very slightly or not at all. The non-stress score was the sum of each indicator with a range of 7–35.

The 3 positive-affect indicators included restful sleep, feeling energetic, and feeling alert. The learner rated each indicator based on the prior 3 days as follows: (1) very slightly or not at all; (2) a little; (3) moderately; (4) quite a bit; and 5, extremely. The positive-affect score was the sum of each indicator with a range of 3–15. The total wellbeing score was the sum of the non-stress score and the positive-affect score with a range of 10–50, such that a score of 10 suggested extreme stress and 50 suggested little to no stress (Additional file 3).

Statistical analyses

Data were entered into an Excel 2010 worksheet (Microsoft Corp., Redmond, WA, USA) and imported into the SAS System for Windows, release 9.2 (SAS Institute Inc., Cary, NC, USA). The level of significance was p < 0.05. Summary group average values are presented as the mean and standard deviation.

Results

Ten physician/nurse subjects participated in 21 learning days (May to October 2017). The distribution of subjects according to the number of learning days was as follows: 1 day, 2 subjects; 2 days, 6 subjects, 3 days, 1 subject; and 4 days, 1 subject. The BIS-nadir for the 21 learning days was substantially lower (88.7 ± 3.2) than the awake values described in the literature (96.6 ± 1.7; p < 0.0001). The BIS-nadir for the 21 learning days was also lower (88.7 ± 3.2) than the first BIS value on learning day 1 (97.0 ± 0.9; p < 0.0001).

Of the 7 stress indicators, moderate-to-extremely responses were as follows: irritation, 8 learners (38.1%); nervousness, 3 learners (14.3%); over-reaction, 6 learners (28.6%); tension, 14 learners (66.7%); overwhelmed, 8 learners (38.1%); drained, 8 learners (38.1%); and people being too demanding, 11 learners (52.4%). Of the 21 learning days, 17 (71.4%) had at least 1 stress indicator and 12 (57.1%) had ≥ 2 stress indicators scored as moderately-to-extremely. Of the 3 positive-affect indicators, quite a bit-to-extremely responses were as follows: restful sleep, 6 learners (28.6%); energetic, 0 learners (0%); and alert, 10 learners (47.6%). Of the 21 learning days, 19 (90.5%) learners had ≥ 2 positive-affects scored as very slightly or not at all-to-moderately. Summary results were as follows: total wellbeing score, 34.4 ± 5.8; non-stress score, 25.4 ± 5.4; and positive-affect score, 9.0 ± 1.6.

One subject underwent 4 learning days over a 19-day period. Mean BIS values were as follows: day 1, 96.8 ± 1.4; day 2, 96.4 ± 1.7; day 3, 95.3 ± 1.8; and day 4, 95.1 ± 2.5. Values were significantly different (p < 0.05) for day 1 compared to day 3; day 1 compared to day 4; day 2 compared to day 3; and day 2 compared to day 4. The wellbeing score increased 23.3% on day 4 (37) compared to day 1 (30). The non-stress score increased 30.4% on day 4 (30) compared to day 1 (23).

Discussion

The lowest BIS value reached during the 21 learning day NFB sessions was substantially decreased, when compared to individuals described in the literature and to the very-first BIS value for each learner. These observations indicate that the learners were effectively able to alter their brainwave activity and enter an attentional state of receptive awareness or relaxed attention by following the instructions.

Data from the 21 wellbeing surveys demonstrated that stress was a common manifestation among the physician-nurse learners. That is, a substantial proportion of learners had perceptions of irritability, over-reaction, tension, feeling overwhelmed, feeling drained, or that people were too demanding. The mean non-stress score for the learners (25.4) represents a 30% reduction relative to the best non-stress score (35). This was an anticipated finding and it suggests that the newly developed surveillance tool may be useful.

Relative to the positive-affect indicators, a large percentage had perceptions that they were deficient in restful sleep, energy, or alertness. The mean positive-affect score for the learners (9.0) is a 40% reduction relative to an ideal positive-affect score (15). Such deficiencies are likely to be manifestations of stress. The mean total wellbeing score, sum of the non-stress and positive-affect scores, for the learners (34.4) represents a 30% reduction relative to a perfect total wellbeing score (50).

Of substantial interest is the 1 learner who underwent 4 learning days. These data indicate that the ability to alter brainwave activity and enhance relaxed alertness is a progressively learned phenomenon. Similarly interesting was the increment in the total wellbeing and non-stress scores on learning day 4 when compared to day 1. These data are consistent with the notion that learning receptive awareness (relaxed attention) might have an influence on daily wellbeing.

Attentional focus and stress

Immediately before session 1, the learner was oriented to the BIS monitor screen and before session 2, the learner was told that they should not think too intensely or narrowly focus on the BIS number. Visual perceptual skills are largely influenced by attentional control which consists of executive, orienting, and alerting aspects [34]. Arousal, attention, and stress have an inverted U-shaped relationship with cognitive-motor performance, known as the Yerkes–Dodson law [35, 36]. That is, performance is low with inadequate arousal, attention, and stress but increases with greater arousal, up to a level, where execution efficiencies then decrease with intense focus and excess stress.

Investigators have espoused that narrow attentional visual focus can increase anxiety, muscle tension, autonomic arousal, and hypervigilance [37,38,39]. Widening the visual scope of attentional focus has been associated with relaxed attention, a balanced state of arousal and sympathetic and parasympathetic neural function [38] and improvements in anxiety [37, 40, 41] and athletic decision making [42]. Others have also provided evidence that enhancing one’s awareness of external space positively increases intermediate brainwave activity [38, 39, 43], relaxation [44], and perceptions of wholeness [45, 46].

BIS monitor

The Food and Drug Administration classifies the BIS monitor as a computer device that detects EEG signals and may be used for assessing the clinical and physiological effects of anesthetic and sedating agents. The credibility and validity of the device is supported by more than 2500 citations in the National Library of Medicine that includes publications in the New England Journal of Medicine [47] and Cochrane Systematic Review [48]. Several studies have demonstrated significant associations between BIS monitor values (0–100) and clinical status, using the Modified Observer’s Assessment of Alertness/Sedation Scale, in patients undergoing general anesthesia [49, 50] or conscious sedation [51]. Reductions in BIS values have also been found for conditions other than pharmacologic sedation and include acupressure [52], stage I sleep [53], and relaxation using guided imagery [54]. For BIS values between 60 and 100, the level highly-correlates (r = 0.90; p < 0.01) with the ratio of power in a brainwave band with high frequency (30–47 Hz) relative to an intermediate frequency band (11–20 Hz) [55]. That is, as the BIS value (the symbolic image being displayed) decreases, there is a relative linear reduction in the high frequency brainwave power relative to lower frequency brainwave power.

Conclusions

The BIS-nadir values provide objective evidence that the self-regulation of brainwave activity can be learned by altering attentional functions. The wellbeing surveys from the physician-nurse suggest that symptoms of stress were relatively frequent and punctuated with impairments in positive-affect. We are planning to provide participant compensation as a mechanism to incentivize learners to participate in at least 4 days of NFB to determine if learning receptive awareness is associated with improvement in wellbeing.

Limitations

The principal study limitation is that only 1 subject undertook 4 learning days of NFB. Thus, we cannot be certain that the decrease in BIS value and improvement in wellbeing over the 4 learning days will be replicated in a population of learners with similar participation. The wellbeing survey has not been validated using benchmark psychological testing.

Abbreviations

BIS:

Bispectral Indexâ„¢

EEG:

electroencephalography

NFB:

neurofeedback

References

  1. Dyrbye LN, West CP, Satele D, Boone S, Tan L, Sloan J, et al. Burnout among U.S. medical students, residents, and early career physicians relative to the general U.S. population. Acad Med. 2014;89:443–51.

    Article  PubMed  Google Scholar 

  2. Vahey DC, Aiken LH, Sloane DM, Clarke SP, Vargas D. Nurse burnout and patient satisfaction. Med Care. 2004;42:II57–66.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Poghosyan L, Clarke SP, Finlayson M, Aiken LH. Nurse burnout and quality of care: cross-national investigation in six countries. Res Nurs Health. 2010;33:288–98.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Lindqvist R, Smeds Alenius L, Griffiths P, Runesdotter S, Tishelman C. Structural characteristics of hospitals and nurse-reported care quality, work environment, burnout and leaving intentions. J Nurs Manag. 2015;23:263–74.

    Article  PubMed  Google Scholar 

  5. Chang EM, Bidewell JW, Huntington AD, Daly J, Johnson A, Wilson H, et al. A survey of role stress, coping and health in Australian and New Zealand hospital nurses. Int J Nurs Stud. 2007;44:1354–62.

    Article  PubMed  Google Scholar 

  6. Perlman DM, Salomons TV, Davidson RJ, Lutz A. Differential effects on pain intensity and unpleasantness of two meditation practices. Emotion. 2010;10:65–71.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Atanes AC, Andreoni S, Hirayama MS, Montero-Marin J, Barros VV, Ronzani TM, et al. Mindfulness, perceived stress, and subjective well-being: a correlational study in primary care health professionals. BMC Complement Altern Med. 2015;15:303.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Beach MC, Roter D, Korthuis PT, Epstein RM, Sharp V, Ratanawongsa N, et al. A multicenter study of physician mindfulness and health care quality. Ann Fam Med. 2013;11:421–8.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Smith SA. Mindfulness-based stress reduction: an intervention to enhance the effectiveness of nurses’ coping with work-related stress. Int J Nurs Knowl. 2014;25:119–30.

    Article  PubMed  Google Scholar 

  10. Goodman MJ, Schorling JB. A mindfulness course decreases burnout and improves well-being among healthcare providers. Int J Psychiatry Med. 2012;43:119–28.

    Article  PubMed  Google Scholar 

  11. Kemper KJ, Khirallah M. Acute effects of online mind-body skills training on resilience, mindfulness, and empathy. J Evid Based Complement Altern Med. 2015;20:247–53.

    Article  Google Scholar 

  12. Regehr C, Glancy D, Pitts A, LeBlanc VR. Interventions to reduce the consequences of stress in physicians: a review and meta-analysis. J Nerv Ment Dis. 2014;202:353–9.

    Article  PubMed  Google Scholar 

  13. Marzbani H, Marateb HR, Mansourian M. Neurofeedback: a comprehensive review on system design, methodology and clinical applications. Basic Clin Neurosci. 2016;7:143–58.

    PubMed  PubMed Central  Google Scholar 

  14. Dias AM, van Deusen A. A new neurofeedback protocol for depression. Span J Psychol. 2011;14:374–84.

    Article  PubMed  Google Scholar 

  15. Cheon EJ, Koo BH, Seo WS, Lee JY, Choi JH, Song SH. Effects of neurofeedback on adult patients with psychiatric disorders in a naturalistic setting. Appl Psychophysiol Biofeedback. 2015;40:17–24.

    Article  PubMed  Google Scholar 

  16. Michael AJ, Krishnaswamy S, Mohamed J. An open label study of the use of EEG biofeedback using beta training to reduce anxiety for patients with cardiac events. Neuropsychiatr Dis Treat. 2005;1:357–63.

    PubMed  PubMed Central  Google Scholar 

  17. Egner T, Gruzelier JH. EEG biofeedback of low beta band components: frequency-specific effects on variables of attention and event-related brain potentials. Clin Neurophysiol. 2004;115:131–9.

    Article  PubMed  CAS  Google Scholar 

  18. Wang JR, Hsieh S. Neurofeedback training improves attention and working memory performance. Clin Neurophysiol. 2013;124:2406–20.

    Article  PubMed  Google Scholar 

  19. Raymond J, Varney C, Parkinson LA, Gruzelier JH. The effects of alpha/theta neurofeedback on personality and mood. Brain Res Cogn Brain Res. 2005;23:287–92.

    Article  PubMed  Google Scholar 

  20. Escolano C, Aguilar M, Minguez J. EEG-based upper alpha neurofeedback training improves working memory performance. Conf Proc IEEE Eng Med Biol Soc. 2011;2011:2327–30.

    Google Scholar 

  21. Egner T, Gruzelier JH. Ecological validity of neurofeedback: modulation of slow wave EEG enhances musical performance. NeuroReport. 2003;14:1221–4.

    Article  PubMed  Google Scholar 

  22. Ros T, Moseley MJ, Bloom PA, Benjamin L, Parkinson LA, Gruzelier JH. Optimizing microsurgical skills with EEG neurofeedback. BMC Neurosci. 2009;10:87.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Gruzelier JH. Differential effects on mood of 12–15 (SMR) and 15–18 (beta1) Hz neurofeedback. Int J Psychophysiol. 2014;93:112–5.

    Article  PubMed  Google Scholar 

  24. Brandmeyer T, Delorme A. Meditation and neurofeedback. Front Psychol. 2013;4:688.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Simkin DR, Thatcher RW, Lubar J. Quantitative EEG and neurofeedback in children and adolescents: anxiety disorders, depressive disorders, comorbid addiction and attention-deficit/hyperactivity disorder, and brain injury. Child Adolesc Psychiatr Clin N Am. 2014;23:427–64.

    Article  PubMed  Google Scholar 

  26. Nunes RR, Chaves IM, de Alencar JC, Franco SB, de Oliveira YG, de Menezes DG. Bispectral index and other processed parameters of electroencephalogram: an update. Rev Bras Anestesiol. 2012;62:105–17.

    Article  PubMed  Google Scholar 

  27. Health Quality Ontario. Bispectral index monitor: an evidence-based analysis. Ont Health Technol Assess Ser 2004;4:1–70.

    Google Scholar 

  28. Dunham CM, McClain JV, Burger A. Comparison of Bispectral Index values during the flotation restricted environmental stimulation technique and results for stage I sleep: a prospective pilot investigation. BMC Res Notes. 2017;10:640.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Osman A, Wong JL, Bagge CL, Freedenthal S, Gutierrez PM, Lozano G. The Depression Anxiety Stress Scales-21 (DASS-21): further examination of dimensions, scale reliability, and correlates. J Clin Psychol. 2012;68:1322–38.

    Article  PubMed  Google Scholar 

  30. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24:385–96.

    Article  PubMed  CAS  Google Scholar 

  31. Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect: the PANAS scales. J Pers Soc Psychol. 1988;54:1063–70.

    Article  PubMed  CAS  Google Scholar 

  32. Cappelleri JC, Bushmakin AG, McDermott AM, Dukes E, Sadosky A, Petrie CD, et al. Measurement properties of the Medical Outcomes Study Sleep Scale in patients with fibromyalgia. Sleep Med. 2009;10:766–70.

    Article  PubMed  Google Scholar 

  33. Maslach C, Leiter MP. Early predictors of job burnout and engagement. J Appl Psychol. 2008;93:498–512.

    Article  PubMed  Google Scholar 

  34. Fan J, Gu X, Guise KG, Liu X, Fossella J, Wang H, et al. Testing the behavioral interaction and integration of attentional networks. Brain Cogn. 2009;70:209–20.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Price JS. Evolutionary aspects of anxiety disorders. Dialogues Clin Neurosci. 2003;5:223–36.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Ghazali DA, Ragot S, Breque C, Guechi Y, Boureau-Voultoury A, Petitpas F, et al. Randomized controlled trial of multidisciplinary team stress and performance in immersive simulation for management of infant in shock: study protocol. Scand J Trauma Resusc Emerg Med. 2016;24:36.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Birnbaum MH. Nearpoint visual stress: clinical implications. J Am Optom Assoc. 1985;56:480–90.

    PubMed  CAS  Google Scholar 

  38. Fehmi LG, Shor SB. Open focus attention training. Psychiatr Clin North Am. 2013;36:153–62.

    Article  PubMed  Google Scholar 

  39. Plotkin WB. On the self-regulation of the occipital alpha rhythm: control strategies, states of consciousness, and the role of physiological feedback. J Exp Psychol Gen. 1976;105:66–99.

    Article  PubMed  CAS  Google Scholar 

  40. Mortberg E, Hoffart A, Boecking B, Clark DM. Shifting the focus of one’s attention mediates improvement in cognitive therapy for social anxiety disorder. Behav Cogn Psychother. 2015;43:63–73.

    Article  PubMed  Google Scholar 

  41. Brzezicka A, Krejtz I, von Hecker U, Laubrock J. Eye movement evidence for defocused attention in dysphoria—a perceptual span analysis. Int J Psychophysiol. 2012;85:129–33.

    Article  PubMed  Google Scholar 

  42. Ryu D, Abernethy B, Mann DL, Poolton JM, Gorman AD. The role of central and peripheral vision in expert decision making. Perception. 2013;42:591–607.

    Article  PubMed  Google Scholar 

  43. Hinterberger T, Schmidt S, Kamei T, Walach H. Decreased electrophysiological activity represents the conscious state of emptiness in meditation. Front Psychol. 2014;5:99.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Birnbaum MH. Holistic aspects of visual style: a hemispheric model with implications for vision therapy. J Am Optom Assoc. 1978;49:1133–41.

    Article  PubMed  CAS  Google Scholar 

  45. Cowling WR 3rd, Smith MC, Watson J. The power of wholeness, consciousness, and caring a dialogue on nursing science, art, and healing. ANS Adv Nurs Sci. 2008;31:E41–51.

    Article  PubMed  Google Scholar 

  46. Jonas-Simpson C. Awakening to space consciousness and timeless transcendent presence. Nurs Sci Q. 2010;23:195–200.

    Article  PubMed  Google Scholar 

  47. Avidan MS, Zhang L, Burnside BA, Finkel KJ, Searleman AC, Selvidge JA, et al. Anesthesia awareness and the bispectral index. N Engl J Med. 2008;358:1097–108.

    Article  PubMed  CAS  Google Scholar 

  48. Punjasawadwong Y. Bispectral index for improving anaesthetic delivery and postoperative recovery. Cochrane Database Syst Rev; 2014. http://www.thecochranelibrary.com/. Accessed 10 June 2016.

  49. Glass PS, Bloom M, Kearse L, Rosow C, Sebel P, Manberg P. Bispectral analysis measures sedation and memory effects of propofol, midazolam, isoflurane, and alfentanil in healthy volunteers. Anesthesiology. 1997;86:836–47.

    Article  PubMed  CAS  Google Scholar 

  50. Zhong T, Guo QL, Pang YD, Peng LF, Li CL. Comparative evaluation of the cerebral state index and the bispectral index during target-controlled infusion of propofol. Br J Anaesth. 2005;95:798–802.

    Article  PubMed  CAS  Google Scholar 

  51. Haberland CM, Baker S, Liu H. Bispectral index monitoring of sedation depth in pediatric dental patients. Anesth Prog. 2011;58:66–72.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Fassoulaki A, Paraskeva A, Kostopanagiotou G, Tsakalozou E, Markantonis S. Acupressure on the extra 1 acupoint: the effect on bispectral index, serum melatonin, plasma beta-endorphin, and stress. Anesth Analg. 2007;104:312–7.

    Article  PubMed  Google Scholar 

  53. Dahaba AA, Xue JX, Xu GX, Liu QH, Metzler H. Bilateral Bispectral Index (BIS)-Vista as a measure of physiologic sleep in sleep-deprived anesthesiologists. Minerva Anestesiol. 2011;77:388–93.

    PubMed  CAS  Google Scholar 

  54. Hudetz JA, Hudetz AG, Reddy DM. Effect of relaxation on working memory and the Bispectral Index of the EEG. Psychol Rep. 2004;95:53–70.

    PubMed  Google Scholar 

  55. Morimoto Y, Hagihira S, Koizumi Y, Ishida K, Matsumoto M, Sakabe T. The relationship between bispectral index and electroencephalographic parameters during isoflurane anesthesia. Anesth Analg. 2004;98:1336–40.

    Article  PubMed  CAS  Google Scholar 

Download references

Authors’ contributions

CMD, AB, BMH, and EAC conceptualized and designed the study. BMH and EAC instructed the learners and performed the Bispectral Indexâ„¢ monitoring during the sessions. CMD performed the literature review and the data analysis. CMD, AB, BMH, and EAC reviewed and interpreted the data, were involved in drafting the manuscript, and critically revised the manuscript for important intellectual content. All authors read and approved the final manuscript.

Acknowledgements

The authors wish to thank Marina C. Hanes, BA, ELS for copyediting the manuscript.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

The datasets generated during and/or analyzed during the current study are not publicly available due to statutory provisions regarding data and privacy protection, but are available from the corresponding author on reasonable request.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Mercy Health Youngstown Institutional Review Board for human investigations approved the project on April 19, 2017 (#17-006). Written informed consent was required for study participation.

Funding

Mercy Health Foundation Mahoning Valley supplied the funding for the BIS sensors. The Foundation did not participate in the design of the study, data collection, data analysis, data interpretation, or writing the manuscript.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to C. Michael Dunham.

Additional files

Additional file 1.

Specific instructions given before session 1.

Additional file 2.

Pre-Session 1 Instructions. Specific instructions given before session 2.

Additional file 3.

Pre-Session 2 Instructions. Wellbeing surveillance tool and scoring system.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dunham, C.M., Burger, A.L., Hileman, B.M. et al. Learning receptive awareness via neurofeedback in stressed healthcare providers: a prospective pilot investigation. BMC Res Notes 11, 645 (2018). https://doi.org/10.1186/s13104-018-3756-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13104-018-3756-0

Keywords