ArticlePDF Available

Open-Loop Neurofeedback Audiovisual Stimulation: A Pilot Study of Its Potential for Sleep Induction in Older Adults


Abstract and Figures

This pilot study tested the efficacy of a 30-min audio-visual stimulation (AVS) program for the treatment of chronic insomnia in older adults. Chronic insomnia has been conceptualized as entailing increased cortical high frequency EEG activity at sleep onset and during NREM sleep. We hypothesized that an AVS program gradually descending from 8 to 1 Hz would potentially reduce the excessive cortical activation that is thought to contribute to difficulties with initiating and maintaining sleep. Accordingly, we conducted an intervention study of AVS using a pre-post design. Eight older adults (88 ± 8.7 years) complaining of chronic insomnia self-administered a 30-min AVS program nightly at bedtime for one month. Sleep was assessed at baseline and throughout the 4-week intervention. After using AVS for 4 weeks, significant improvement was reported in insomnia symptoms (ISI, p = 0.002) and sleep quality (PSQI, p = 0.004); with moderate to large effect sizes (Partial Eta2: 0.20-0.55)(Cohen's d: 0.7-2.3). The training effect (self-reported sleep improvement) was observed at the end of week one and persisted through the 1-month intervention. The results from this pilot study suggest that further exploration of AVS as a treatment for insomnia is warranted.
No caption available
Content may be subject to copyright.
A Pilot Study of Audio–Visual Stimulation as a Self-Care
Treatment for Insomnia in Adults with Insomnia and Chronic
Hsin-Yi Tang Michael V. Vitiello
Michael Perlis Jun James Mao Barbara Riegel
ÓSpringer Science+Business Media New York 2014
Abstract This pilot study tested the efficacy of an audio–
visual stimulation (AVS) program for the promotion of
sleep in individuals with chronic pain. Insomnia and
chronic pain are common comorbid conditions and their
relationship has been viewed as bidirectional. Recent
studies suggest a relatively dominant role of sleep in this
dyad. The premise of this pilot study was that AVS
enhances low frequency while reducing high frequency
brain activity resulting in decreased hyperarousal and
improved sleep with potential consequent reduction in
pain. We conducted a pilot intervention study of AVS
using a pre–post design. Participants self-administered a
30-min AVS program nightly at bedtime for 1 month.
Sleep and pain were assessed at baseline and at the con-
clusion of the 4-week intervention phase. Nine adults
(mean age 33 ±15.8 years; female, 89 %) completed the
study. After using the AVS device for 4 weeks, significant
improvement was seen in reported insomnia (ISI,
p=0.003), pain severity (BPI, p=0.005), and pain
interference with functioning (BPI, p=0.001). Large
effect sizes (Partial g
0.20–0.94) (Cohen’s d 0.44–1.45)
were observed. The results of this pilot study suggest that
the AVS program may be efficacious in decreasing both
insomnia and pain symptoms. In order to better assess the
efficacy of AVS for sleep promotion and possible pain
reduction, more definitive randomized controlled trials will
be needed. These should include appropriate sample sizes,
objective measures of sleep and pain, and longitudinal
Keywords Audio–visual stimulation Light–sound
stimulation Insomnia Sleep Chronic pain
Chronic pain affects 1 in 3 Americans (Johannes et al.
2010), and 67–88 % of adults with chronic pain experience
some form of sleep disturbance (Morin et al. 2006). This
striking level of comorbidity has suggested to many that the
relationship between pain and sleep may be bi-directional
(Alsaadi et al. 2014; Finan et al. 2013; Jansson-Frojmark
and Boersma 2012; McCracken and Iverson 2002; Okifuji
and Hare 2011). That is, pain may serve to precipitate and
perpetuate sleep continuity disturbance; and that sleep ini-
tiation and maintenance problems and/or sleep loss may
serve to exacerbate or reduce the individual’s tolerance of
chronic pain. Further, chronic insomnia may increase the
risk for the development of other medical and psychiatric
conditions (Matteson-Rusby et al. 2010) which, in turn, as
comorbid conditions, increase the risk for the development,
or exacerbation, of chronic pain. These issues, when taken
together, strongly suggest that sleep disturbance, in the
context of chronic pain, should be targeted for treatment.
H.-Y. Tang (&)
Health Science Center, School of Nursing, University of
Washington, 1959 NE Pacific St., Box 357263, Seattle,
WA 98195-7263, USA
M. V. Vitiello
Psychiatry and Behavioral Sciences, School of Medicine,
University of Washington, Seattle, WA 98195, USA
M. Perlis J. J. Mao
School of Medicine, University of Pennsylvania, Philadelphia,
PA 19106, USA
B. Riegel
School of Nursing, University of Pennsylvania, Philadelphia,
PA 19106, USA
Appl Psychophysiol Biofeedback
DOI 10.1007/s10484-014-9263-8
Sleep and Chronic Pain
As noted above, the relationship between insomnia and
chronic pain has been viewed as bi-directional. Recent
studies provide laboratory based evidence that individuals
with primary insomnia and insomnia comorbid with
chronic pain process pain abnormally (Haack et al. 2012).
For example, those with primary insomnia experienced
spontaneous pain more frequently and intensely, exhibited
a higher sensitivity to evoked heat and pressure pain, and
had a dysfunctional pain inhibition system. These findings
are consistent with the emerging hypothesis that insomnia
is associated with increased pain perception and/or ampli-
fication. Importantly, findings from a recent systematic
review show that sleep impairment not only predicts new
onset and the continuation of chronic pain; sleep is a
stronger predictor of chronic pain than chronic pain is to
sleep impairment (Finan et al. 2013). This hypothesis is
further supported by a longitudinal 13-year study in which
sleep disturbances at baseline strongly predicted chronic or
onset of radiating low back pain over the course of longi-
tudinal follow up (Lusa et al. 2014). Finally, results from a
recent study show that short-term improvements in sleep
predicted long-term improvements in chronic pain,
insomnia symptoms, and fatigue (McCurry et al. 2014;
Vitiello et al. 2014). Taken together these findings suggest
that improving sleep might improve pain outcomes (Finan
et al. 2013; Smith and Haythornthwaite 2004; Turk and
Cohen 2010).
Current treatment options for sleep include pharmaco-
logical treatment and Cognitive Behavioral Therapy for
Insomnia (CBT-I) (Perlis et al. 2008; Schutte-Rodin et al.
2008). Medical treatment with hypnotics (e.g., benzodi-
azepines and benzodiazepine receptor agonists) has been
shown to have good efficacy, safety, and durability for up
to 12 months. Clinical benefits, however, do not persist
after treatment discontinuation and some patients may
experience loss of effectiveness and/or psychological
dependence with extended use of hypnotics (Nowell et al.
1997; Roth et al. 2005). CBT-I is considered a gold stan-
dard non-pharmacological treatment, yielding treatment
effects comparable to or exceeding those observed for
medications (Jungquist et al. 2010; Mitchell et al. 2012;
Smith et al., 2002; Wang et al. 2005). Further, there is
evidence that CBT-I for insomnia comorbid with chronic
pain is as, or more, efficacious than when the treatment is
applied to patients with ‘‘Primary Insomnia’’ (Jungquist
et al. 2010,2012; Vitiello et al. 2009).
One area in insomnia research that has remained under
studied is use of self-care approaches that people can use at
the home setting to promote sleep. Specifically, brainwave
entrainment through light and sound stimulation is an
intervention that may have potential to promote relaxation
and sleep, but its potential efficacy for improving sleep has
not been well explored.
Audio–Visual Stimulation (AVS)
The study of the audio–visual stimulation (AVS) can be
traced back to 1930s. The term AVS is often used inter-
changeably with ‘‘light and sound stimulation’’ and ‘‘audio
photic stimulation.’’ In 1934, with the availability of
encephalogram, the impact of photic stimulation on brain
activity was documented in a study in which increased
brain activity was found to correspond to the frequency of a
given photic stimulation (Adrian and Matthews 1934).
During the following decade, several investigators reported
brain activity changes in response to photic stimulation,
noting that the rhythm of brain activity tended to assume
the rhythm of the photic stimulus, which was termed
‘entrainment’’ (Bartley 1937; Jasper 1936).
Brain activity AVS entrainment to slow frequencies to
promote deep relaxation has been reported clinically and in
several older studies. In 1980, one of the biofeedback/
neurofeedback pioneers, Dr. Thomas Budzynski reported
using light and sound stimulation (stimulation frequency
unspecified) to assist his clients in successfully achieving
and maintaining theta state (3–6 Hz, pre Stage 1 sleep
state) during psychotherapy sessions (Budzynski 1992;
Hutchison 1990). A study by Harris demonstrated that light
and sound stimulation (frequency undefined) promoted
better sleep for his AIDS/HIV patients (Hutchison 1990).
In addition, a study by Hauri found that AVS closed-loop
training, discussed further below, in the sensory motor
rhythm (SMR, 12–15 Hz) promoted sleep in people who
were physically relaxed but cognitively preoccupied (Hauri
1981; Hauri et al. 1982). Of note, Harris’ and Hauri’s
studies are two of the few in the AVS literature that doc-
ument an effect of AVS on sleep.
Audio–visual stimulation (AVS) is a promising self-care
intervention option for insomnia that uses preprogrammed
light and sound patterns to potentiate sleep-related EEG
activity (dh1–8 Hz) (Budzynski et al. 2011). The AVS
devices are inexpensive and readily available without a
prescription. Although the AVS mechanism is not fully
understood, it is thought that the auditory and visual ele-
ments of AVS stimulation modulate endogenous brain
activity by activating retinal cells in the eyes and pressure-
sensitive cilia within the cochlea of the ears. The evoked
electrical potential is then transmitted via neural pathways
(audio signals via the medial geniculate; visual signals via
the lateral geniculate) to the thalamus where audio and
visual sensory information is processed. From the thala-
mus, the entrained electrical activity is propagated through
the cortical thalamic loop to the rest of limbic system and
the cerebral cortex (Budzynski et al. 2011; Collura and
Appl Psychophysiol Biofeedback
Siever 2008) (Fig. 1). Importantly, reported adverse effects
are minimal; the only known contraindication for adults is
a history of a seizure disorder (Rodin et al. 1955). While
the neural mechanism for AVS remains in debate, a study
with six healthy adults demonstrated that repetitive training
over a period of 2 months (25 sessions of AVS ramping
from 18 down to 2 Hz over 20 min, with subjects laying in
darkened room with eyes closed) significantly reduced beta
and gamma activities and increased the h/aratio (a
brainwave state that is conducive for sleep onset). The
findings suggested that with repeated training, AVS culti-
vates an adaptive self-regulation process and provides
exogenous signals to entrain cortical activity to slower
frequencies (Teplan et al. 2006,2011).
One current line of thought about the ethology and
pathophysiology of insomnia, is that chronic insomnia is a
hybrid state (hyperarousal) wherein the subject is less
disengaged from the environment owing to conditioned
cortical arousal and/or local neuronal wakefulness (Buy-
sse et al. 2011; Perlis et al. 1997). This hypothesized state
suggests that interventions that facilitate EEG slowing
(via feedback, entrainment, conditioning, etc.) may pro-
mote improved sleep induction and maintenance. The
purpose of this study was to examine the feasibility of a
30 min self-administered AVS program for sleep promo-
tion in adults with insomnia and chronic pain in the
community setting.
This was a pilot intervention study using a pre- and post-
design. Thirteen participants were recruited from the
community sites in Philadelphia and Seattle, through flyers
posted at community centers and advertisement placed in
the local newspaper. Inclusion criteria were adults 21 years
and older, having nonmalignant pain most days for more
than 6 months, difficulty sleeping at least 3 nights per week
for 3 months, a score of 8 or higher on the Insomnia
Severity Index (ISI), and a score between 3 and 10 on the
‘worst pain’ item of the Brief Pain Inventory (BPI).
Exclusion criteria were seizure disorder, night shift worker,
known photosensitivity, cognitive impairment (assessed
through in-person interview by trained research staff),
severe psychiatric disorder, and history of a sleep disorder
other than insomnia, such as restless leg syndrome, sleep
apnea or narcolepsy. Sleep apnea was self-reported or
presumed based on a score higher than 0.5 on the Multi-
variate Apnea Prediction (MAP) index (Maislin et al.
1995). Restless Leg Syndrome was assessed with the four
item simplified version of International Restless Legs
Syndrome Scale (IRLS) (Walters et al. 2003; Wunderlich
et al. 2005). This pilot study was approved by the Uni-
versity of Pennsylvania and Seattle University Institutional
Review Boards. Inform consent was obtained prior to data
Fig. 1 AVS auditory and visual
pathways. In AVS, the visual
stimulation (flickering light)is
delivered through goggles with
light-emitting diodes (LEDs)
and the audio stimulation is
delivered through headphones
Appl Psychophysiol Biofeedback
Insomnia Severity Index (ISI)
The ISI is a validated seven-item (0–4) scale that measures
insomnia severity. Norms are: 0–7 =no clinically signifi-
cant insomnia; 8–14 =sub threshold insomnia; 15–21 =
clinical insomnia (moderate severity); 21–28 =clinical
insomnia (severe). The ISI has internal consistency
(a=0.90), sensitivity (86 %) and specificity (87 %); the
scale is well-established and sensitive to changes with
intervention (Bastien et al. 2001; Morin et al. 2011).
Sleep Diary
The diary is a two-page log with standard questions about
the quantity and quality of the previous night of sleep,
including Time to Bed, Sleep Latency, Number of Awak-
enings, Wake After Sleep Onset time (WASO), Total Sleep
Time, and Time out of Bed. The diary also includes
questions about the causes of sleep difficulties if any,
caffeine and alcohol consumption, daytime napping, exer-
cise, health issues, hypnotic use and the AVS adherence.
The 1-week sleep diary was completed once at baseline and
again upon completion of the intervention.
Brief Pain Inventory (BPI)
The BPI (short form) is a 9-item assessment of pain
severity, impact of pain on daily function, location of pain,
pain medications and amount of pain relief in the past 24 h.
Administration takes 5 min. The scoring of the pain data
yields 2 categories: (1) Pain Severity which is a combi-
nation of the four pain items (pain now, average pain, worst
pain and least pain in the last 24 h) (0 =no pain,
10 =pain as bad as you can imagine), and (2) Pain
Interference with 7 daily activities/functioning including
general activity, walking, work, mood, enjoyment of life,
relations with others, and sleep (0 =pain does not inter-
feres, 10 =pain completely interferes). Reliability is ade-
quate (Cronbach a=0.77–0.91). The BPI has been tested
in various pain conditions such as cancer pain, depressive
disorders, fibromyalgia, osteoarthritis, etc. In addition, BPI
is available in more than 36 languages and has been vali-
dated by confirming the consistency of its 2-factor structure
(Cleeland and Ryan 1994; Keller et al. 2004).
Patient Health Questionnaire (PHQ-9)
The PHQ-9 is a well-established scale measuring mood
state. The items ask how often in the past 2 weeks the
individual has been bothered by symptoms of depression.
Scores on the PHQ-9 range from 0 to 27 (1–4 minimal
depression; 5–9 mild depression; 10–14 moderate depres-
sion; 15–19 moderately severe depression; and 20–27
severe depression (Kroenke et al. 2001).
Multivariable Apnea Prediction Index (MAP)
The MAP is a 13 items survey that screens for prediction of
apnea. The survey assesses common symptoms of apnea
such as loud snoring, gasping during sleep, breathing dif-
ficulty, and excessive daytime sleepiness. Participants were
asked to rate the frequency of these identified symptoms on
a numeric scale (0 =never; 4 =always, 5–7 times/week;
and do not know). The score is then entered into a formula
along with covariates (age, gender, and body mass index)
for further computation. A MPA score higher than 0.5
suggests likelihood of sleep apnea (Maislin et al. 1995). In
this study, the MPA was assessed at the initial interview.
People who scored higher than 0.5 on MPA were excluded
from participating in this study.
International Restless Legs Syndrome Scale (IRLS)
The IRLS (short form) is a 4 item questionnaire that
indexes typical symptoms of restless leg syndrome during
the day and sleep (i.e., discomfort sensation in legs,
urgency to move or rub legs to relieve discomfort, symp-
toms worsen when resting). The response option for each
item is yes or no (Walters et al. 2003). The IRLS (short
form) was used as a screening tool in this study. If a par-
ticipant answered yes to all 4 questions, then they were not
eligible to participate in this study.
Demographic data, brief health history (i.e., smoking,
alcohol, drug use) and medication data (name, dosage,
frequency, duration, indication, and medication changes)
were also collected and used to describe the sample.
At the initial meeting, participants completed the ISI, BPI,
and PHQ-9 and were instructed to record their sleep pat-
terns (sleep diary) for 1 week during the baseline period;
which is a typical length of baseline observation in sleep
research. After a 1-week baseline, they were trained to use
the AVS program at bedtime and to record their sleep
pattern in a sleep diary for 1 month. The AVS program
[Procyon by MindPlace] consists of 30-min of light flick-
ering (goggles) and sound pulsing (headphones) that
gradually descends from a(8 Hz) to d(1 Hz) frequencies.
Weekly phone calls were used to address participants’
questions and assess frequency of usage. The ISI, BPI, and
PHQ-9 were measured again upon completion of the
1 month intervention.
Appl Psychophysiol Biofeedback
Data Analysis
The raw data were screened for accuracy, missing values,
outliers, and distributional properties prior to analysis
(SPSS V21). The sample was characterized using
descriptive statistics of demographic and baseline vari-
ables. Repeated paired sample Ttests were used to examine
pre- and post-intervention differences. The effect size was
examined using both ANOVA partial g
and Cohen’s d.
Thirteen adults were enrolled and nine (mean age 33 ±16,
89 % women) (seven from Seattle, two from Philadelphia)
completed the study. Of the four participants who withdrew
from the study, one reported sensitivity to the light stim-
ulation even at the dimmest intensity, two did not like to
wear any foreign object (goggles and ear buds) during
sleep, and one declined to give a reason. None of the
withdrawn participants reported serious adverse effects.
There were no significant differences on the demographic
characteristics and baseline measures between those who
completed and those who withdrew.
Data were collected between November 2012 and
March 2013. At baseline, the mean insomnia severity score
(ISI) at was 19.2 ±3.9, in the clinical insomnia moderate
range. The total sleep time by self-reported sleep diary was
403.4 ±70.2 min. Mean ratings for worst pain in the last
24 h (7.0 ±1.1), pain interference with sleep (8.0 ±1.6),
pain interference with the ability to enjoy life (5.4 ±1.8),
and the impact of pain on mood (5.2 ±2.3) were all ele-
vated . The majority of the participants reported having
back pain (67 %); the rest reported pain that was disease
related (i.e., congenital abdominal condition (11 %),
fibromyalgia (11 %), and arthritis (11 %). The mood
measure (PHQ-9) at baseline was 11.9 ±5.6, in the
moderate depression range.
After the 1-month AVS intervention (with self-reported
adherence to the AVS of 94 %) significant improvement
was observed for insomnia (ISI, p=0.003). The sleep
diary measures (sleep latency, WASO, total sleep time, and
sleep efficiency), although not statistically significant,
showed trends in the direction of improvement (Table 1).
Before Bonferroni adjustment for multiple comparisons,
significant improvement in pain severity (BPI, p=0.005),
pain interference with daily functioning (BPI, p=0.001),
worst pain (BPI, p=0.004), ability to sleep through pain
(BPI, p=0.015), pain interference with the mood (BPI,
p=0.012), the degree to which pain interfered with the
enjoyment of life (BPI, p=0.043), and depression (PHQ-
9, p=0.035) were observed. These findings suggested
large effect sizes (Partial g
, range 0.20–0.94) (Cohen’s d,
range 0.44–1.45). When Bonferroni correction was per-
formed, ISI and BPI Pain Interference Functional remained
statistically significant (Table 1).
The results of this pilot study of a small sample with
comorbid insomnia and pain suggest that the AVS program
ramping from 8 to 1 Hz over the course of 30 min may be
efficacious in decreasing insomnia symptoms. In addition
to the positive changes in sleep, improvements were also
observed in pain although pain was not directly treated.
This result indirectly supports the emerging hypothesis that
sleep may have a more prominent role than pain in the
comorbid dyad (Finan et al. 2013) and illustrates the fea-
sibility of this intervention approach.
While the results of this preliminary study were encour-
aging, taking into account that sleep and pain are highly
Table 1 AVS for sleep
promotion in adults with
chronic pain (N=9)
Mean scores at baseline
compared with mean scores in
post-testing 4 weeks later
* Significance after Bonferroni
adjustment—pvalue at 0.05/8
items: 0.006
Pre-test Post-test Significance Partial g
Cohen’s d
Insomnia Severity Index 19.2 ±3.9 12.8 ±5.0 0.003* 0.79 1.45
Sleep diary sleep latency 68.8 ±27.3 56.6 ±28.3 0.456 0.20 0.44
Sleep diary wakes after sleep
onset (WASO)
35.7 ±17.2 22.6 ±19.6 0.090 0.47 0.71
Sleep diary total sleep time 403.4 ±70.2 444.0 ±106.5 0.463 0.11 0.45
Sleep diary sleep efficiency 80.5 ±6.6 88.5 ±4.2 0.129 0.48 1.45
BPI pain severity
(four severity items)
5.0 ±1.2 4.0 ±1.6 0.047 0.50 0.71
BPI pain interference items
(seven functional items)
5.39 ±1.9 3.8 ±2.0 0.001* 0.94 0.84
PHQ-9 depression 11.9 ±5.6 9.0 ±2.8 0.035 0.80 0.66
Appl Psychophysiol Biofeedback
subjective phenomena, the interpretation of the findings is
limited by the small sample size, lack of a control group,
the lack of objective measures of sleep and pain, and the
pre–post design. In addition, the high self-reported adher-
ence rate for AVS usage could be indicative of highly
committed subjects or social desirability effects. To further
the understanding of the AVS intervention in sleep pro-
motion and pain reduction, we recommend that future
study include a randomized controlled design with a larger
sample size, an objective measure of sleep and pain, and
longitudinal follow up.
This pilot study is the first to examine the efficacy of a
30 min self-administered portable in-home AVS self-care
intervention for sleep induction in adults with chronic pain.
Considering that treatment options for insomnia are
somewhat limited, AVS could serve as an initial inter-
vention in a stepped care approach for the management of
insomnia in people with chronic pain.
Acknowledgments This project was conducted with the support of
(1) John A. Hartford Foundation Claire M. Fagin Fellowship—
National Hartford Center of Gerontological Nursing Excellence, (2)
National Institute of Nursing Research T-32 Post-doctoral fellowship
(NINR 5-T32-NR009356) from the NewCourtland Center for Tran-
sitions and Health, School of Nursing University of Pennsylvania, (3)
the pilot study fund from the Biobehavioral Research Center, School
of Nursing University of Pennsylvania, (4) the Sinegal Faculty
Development Fund, College of Nursing, Seattle University, and (5)
Center for Research on the Management of Sleep Disturbances (P30
NR011400), University of Washington. Special thanks to Akiko
Miller, Yip-Han Lee, Taylor Goulding, Cara Mcguinness, and Regina
Belche for their exceptional assistance and contribution on the
Adrian, E., & Matthews, B. (1934). The Berger rhythm: Potential
changes from the occipital lobes of man. Brain, 57, 355–385.
Alsaadi, S. M., McAuley, J. H., Hush, J. M., Lo, S., Bartlett, D. J.,
Grunstein, R. R., et al. (2014). The bidirectional relationship
between pain intensity and sleep disturbance/quality in patients
with low back pain. Clinical Journal of Pain,. doi:10.1097/ajp.
Bartley, S. (1937). Some observations on the organization of the
retinal response. American Journal of Physiology, 120, 184–189.
Bastien, C. H., Vallieres, A., & Morin, C. M. (2001). Validation of the
insomnia severity index as an outcome measure for insomnia
research. Sleep Medicine, 2(4), 297–307.
Budzynski, T. (1992). Clinical considerations of sound/light. Seattle,
WA: Synetics.
Budzynski, T., Budzynski, H., Sherlin, L., & Tang, H. Y. (2011).
Audio–visual stimulation: Research and clinical practice. In J.
Berger & G. Turow (Eds.), Music, science, and the rhythmic
brain (pp. 137–153). New York: Routledge.
Buysse, D. J., Germain, A., Hall, M., Monk, T. H., & Nofzinger, E. A.
(2011). A neurobiological model of insomnia. Drug Discovery
Today: Disease Models, 8(4), 129–137. doi:10.1016/j.ddmod.
Cleeland, C. S., & Ryan, K. M. (1994). Pain assessment: Global use
of the Brief Pain Inventory. Annals of the Academy of Medicine,
Singapore, 23(2), 129–138.
Collura, T., & Siever, D. (2008). Audio–visual entainment in relation
to mental health and EEG. In T. Budzynski, H. Budzynski, J.
Evans, & A. Abarbanel (Eds.), Introduction to quantitative EEG
and neurofeedback: Advanced theory and applications (2nd ed.,
pp. 193–223). Boston: Elsevier.
Finan, P. H., Goodin, B. R., & Smith, M. T. (2013). The association
of sleep and pain: An update and a path forward. The Journal of
Pain, 14(12), 1539–1552. doi:10.1016/j.jpain.2013.08.007.
Haack, M., Scott-Sutherland, J., Santangelo, G., Simpson, N. S.,
Sethna, N., & Mullington, J. M. (2012). Pain sensitivity and
modulation in primary insomnia. European Journal of Pain,
16(4), 522–533. doi:10.1016/j.ejpain.2011.07.007.
Hauri, P. (1981). Treating psychophysiologic insomnia with biofeed-
back. Archives of General Psychiatry, 38(7), 752–758.
Hauri, P. J., Percy, L., Hellekson, C., Hartmann, E., & Russ, D.
(1982). The treatment of psychophysiologic insomnia with
biofeedback: A replication study. Biofeedback and Self-Regula-
tion, 7(2), 223–235.
Hutchison, Michael. (1990). The megabrain report special issue on
sound and light technologies Megabrain Report (Vol. 1).
Sausalito, CA: Megabrain Inc.
Jansson-Frojmark, M., & Boersma, K. (2012). Bidirectionality
between pain and insomnia symptoms: A prospective study.
British Journal of Health Psychology, 17(2), 420–431. doi:10.
Jasper, H. H. (1936). Cortical excitatory state and synchronism in the
control of bioelectric autonomous rhythms. Cold Spring Harbor
Symposia on Quantitative Biology, 4, 320–332. doi:10.1101/sqb.
Johannes, C. B., Le, T. K., Zhou, X., Johnston, J. A., & Dworkin, R.
H. (2010). The prevalence of chronic pain in United States
adults: Results of an Internet-based survey. The Journal of Pain,
11(11), 1230–1239. doi:10.1016/j.jpain.2010.07.002.
Jungquist, C. R., O’Brien, C., Matteson-Rusby, S., Smith, M. T.,
Pigeon, W. R., Xia, Y., et al. (2010). The efficacy of cognitive–
behavioral therapy for insomnia in patients with chronic pain.
Sleep Medicine, 11(3), 302–309. doi:10.1016/j.sleep.2009.05.
Jungquist, C. R., Tra, Y., Smith, M. T., Pigeon, W. R., Matteson-
Rusby, S., Xia, Y., et al. (2012). The durability of cognitive
behavioral therapy for insomnia in patients with chronic pain.
Sleep Disorders, 2012, 679648. doi:10.1155/2012/679648.
Keller, S., Bann, C. M., Dodd, S. L., Schein, J., Mendoza, T. R., &
Cleeland, C. S. (2004). Validity of the brief pain inventory for
use in documenting the outcomes of patients with noncancer
pain. Clinical Journal of Pain, 20(5), 309–318.
Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001). The PHQ-9:
Validity of a brief depression severity measure. Journal of
General Internal Medicine, 16(9), 606–613.
Lusa, S., Miranda, H., Luukkonen, R., & Punakallio, A. (2014). Sleep
disturbances predict long-term changes in low back pain among
Finnish firefighters: 13-year follow-up study. International
Archives of Occupational and Environmental Health,. doi:10.
Maislin, G., Pack, A. I., Kribbs, N. B., Smith, P. L., Schwartz, A. R.,
Kline, L. R., et al. (1995). A survey screen for prediction of
apnea. Sleep, 18(3), 158–166.
Matteson-Rusby, S. E., Pigeon, W. R., Gehrman, P., & Perlis, M. L.
(2010). Why treat insomnia? Primary Care Companion to The
Appl Psychophysiol Biofeedback
Journal of Clinical Psychiatry, 12(1), PCC.08r00743. doi: 10.
McCracken, L. M., & Iverson, G. L. (2002). Disrupted sleep patterns
and daily functioning in patients with chronic pain. Pain
Research and Management, 7(2), 75–79.
McCurry, S. M., Shortreed, S. M., Von Korff, M., Balderson, B. H.,
Baker, L. D., Rybarczyk, B. D., et al. (2014). Who benefits from
CBT for insomnia in primary care? Important patient selection
and trial design lessons from longitudinal results of the
Lifestyles trial. Sleep, 37(2), 299–308. doi:10.5665/sleep.3402.
Mitchell, M. D., Gehrman, P., Perlis, M., & Umscheid, C. A. (2012).
Comparative effectiveness of cognitive behavioral therapy for
insomnia: A systematic review. BMC Family Practice, 13, 40.
Morin, C. M., Belleville, G., Belanger, L., & Ivers, H. (2011). The
Insomnia Severity Index: Psychometric indicators to detect
insomnia cases and evaluate treatment response. Sleep, 34(5),
Morin, C. M., LeBlanc, M., Daley, M., Gregoire, J. P., & Merette, C.
(2006). Epidemiology of insomnia: Prevalence, self-help treat-
ments, consultations, and determinants of help-seeking behav-
iors. Sleep Medicine, 7(2), 123–130. doi:10.1016/j.sleep.2005.
Nowell, P. D., Mazumdar, S., Buysse, D. J., Dew, M. A., Reynolds, C.
F, 3rd, & Kupfer, D. J. (1997). Benzodiazepines and zolpidem
for chronic insomnia: A meta-analysis of treatment efficacy.
JAMA, The Journal of the American Medical Association,
278(24), 2170–2177.
Okifuji, A., & Hare, B. D. (2011). Do sleep disorders contribute to
pain sensitivity? Current Rheumatology Reports, 13(6),
528–534. doi:10.1007/s11926-011-0204-8.
Perlis, M., Gehrman, P., & Riemann, D. (2008). Intermittent and
long-term use of sedative hypnotics. Current Pharmaceutical
Design, 14(32), 3456–3465.
Perlis, M. L., Giles, D. E., Mendelson, W. B., Bootzin, R. R., &
Wyatt, J. K. (1997). Psychophysiological insomnia: The behav-
ioural model and a neurocognitive perspective. Journal of Sleep
Research, 6(3), 179–188.
Rodin, E. A., Daly, D. D., & Bickford, R. G. (1955). Effects of photic
stimulation during sleep; A study of normal subjects and
epileptic patients. Neurology, 5(3), 149–159.
Roth, T., Walsh, J. K., Krystal, A., Wessel, T., & Roehrs, T. A.
(2005). An evaluation of the efficacy and safety of eszopiclone
over 12 months in patients with chronic primary insomnia. Sleep
Medicine, 6(6), 487–495. doi:10.1016/j.sleep.2005.06.004.
Schutte-Rodin, S., Broch, L., Buysse, D., Dorsey, C., & Sateia, M.
(2008). Clinical guideline for the evaluation and management of
chronic insomnia in adults. Journal of Clinical Sleep Medicine,
4(5), 487–504.
Smith, M. T., & Haythornthwaite, J. A. (2004). How do sleep
disturbance and chronic pain inter-relate? Insights from the
longitudinal and cognitive–behavioral clinical trials literature.
Sleep Medicine Reviews, 8(2), 119–132.
Smith, M. T., Perlis, M. L., Park, A., Smith, M. S., Pennington, J.,
Giles, D. E., et al. (2002). Comparative meta-analysis of
pharmacotherapy and behavior therapy for persistent insomnia.
The American Journal of Psychiatry, 159(1), 5–11.
Teplan, M., Krakovska, A., & Stolc, S. (2006). EEG responses to
long-term audio–visual stimulation. International Journal of
Psychophysiology, 59(2), 81–90. doi:10.1016/j.ijpsycho.2005.
Teplan, M., Krakovska, A., & Stolc, S. (2011). Direct effects of
audio–visual stimulation on EEG. Computer Methods and
Programs in Biomedicine, 102(1), 17–24.
Turk, D. C., & Cohen, M. J. (2010). Sleep as a marker in the effective
management of chronic osteoarthritis pain with opioid analge-
sics. Seminars in Arhritis and Rheumatism, 39(6), 477–490.
Vitiello, M. V., McCurry, S. M., Shortreed, S. M., Baker, L. D.,
Rybarczyk, B. D., Keefe, F. J., et al. (2014). Short-term
Improvement in insomnia symptoms predicts long-term
improvements in sleep, pain, and fatigue in older adults with
co-morbid osteoarthritis and insomnia. Pain,. doi:10.1016/j.pain.
Vitiello, M. V., Rybarczyk, B., Von Korff, M., & Stepanski, E. J.
(2009). Cognitive behavioral therapy for insomnia improves
sleep and decreases pain in older adults with co-morbid insomnia
and osteoarthritis. Journal of Clinical Sleep Medicine, 5(4),
Walters, A. S., LeBrocq, C., Dhar, A., Hening, W., Rosen, R., Allen,
R. P., et al. (2003). Validation of the International Restless Legs
Syndrome Study Group rating scale for restless legs syndrome.
Sleep Medicine, 4(2), 121–132.
Wang, M. Y., Wang, S. Y., & Tsai, P. S. (2005). Cognitive
behavioural therapy for primary insomnia: A systematic review.
Journal of Advanced Nursing, 50(5), 553–564. doi:10.1111/j.
Wunderlich, G. R., Evans, K. R., Sills, T., Pollentier, S., Reess, J.,
Allen, R. P., et al. (2005). An item response analysis of the
international restless legs syndrome study group rating scale for
restless legs syndrome. Sleep Medicine, 6(2), 131–139.
Appl Psychophysiol Biofeedback
... The frequencies associated with SMR vary between studies but they usually are around 12 to 15 Hz, sometimes including higher or lower frequencies. Some studies uses the inhibition of higher frequencies, such as high beta frequencies (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35), to reduce alertness, whereas others enhance slower frequencies, from delta (less than 4 Hz) to alpha frequencies (8-12 Hz), to promote deep relaxation [36]. ...
... At initial assessment, all participants had higher absolute power for high-beta (21-34 Hz) and gamma waves (35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45) Hz) than the database. After the experimental session, participants in the AVE group had a significant increase in the absolute power of delta waves on all 19 EEG channels, while participants of the placebo group had no significant EEG power change in any band frequency. ...
Background: Chronic insomnia affects about 6%-13% of the Canadian population. Although treatments already exist, they each have their own issues. Neurofeedback is a neuromodulation technique that specifically targets abnormal brain activity and is gaining attention as a possible insomnia treatment. Aim: To review the latest studies pertaining to the use of neurofeedback in the treatment of insomnia. Methods: In this non-systematic review, only experimental studies assessing the effects of neurofeedback on patients with insomnia were targeted across four bibliographic databases. Results: A total of 12 studies were retained. All neurofeedback studies included in this study showed a clear improvement of subjective sleep. However, data concerning objective improvement are contradictory. Most studies regarding surface and z-score neurofeedback show that neurofeedback targeting the sensorimotor rhythm in the sensorimotor cortex may help improve subjective sleep. A placebo effect seems also to be present in some studies. Several limitations were present in each study. Conclusion: While studies concerning neurofeedback as a treatment for insomnia are encouraging, many methodological barriers remain to be resolved to prove its efficacy unequivocally. More studies using robust design parameters, as well as the replication of existing studies, are necessary to support neurofeedback as an effective treatment for insomnia.
... Those stimuli in turn are adapted by the brain (so-called brain entrainment) and thus can stimulate brain waves into desired stimulation frequencies which induce relaxation and consciousness [20,21]. Fundamental research into audiovisual stimulation has already shown positive effects on anxiety [22][23][24], depression [25,26], headache [27][28][29][30], and sleep disorders [31][32][33]. ...
... Due to the fact that audiovisual stimulation can be used as a measure to induce relaxation [20][21][22][23][24][25][26][27][28][29][30][31][32], we hypothesized that an association exists between usage and mental states, respectively health. As the results show, associations between audiovisual stimulation and the mental health of employees are significant. ...
Full-text available
Due to the COVID-19 pandemic, health education programs and workplace health promotion (WHP) could only be offered under difficult conditions, if at all. In Germany for example, mandatory lockdowns, working from home, and physical distancing have led to a sharp decline in expenditure on prevention and health promotion from 2019 to 2020. At the same time, the pandemic has negatively affected many people’s mental health. Therefore, our goal was to examine audiovisual stimulation as a possible measure in the context of WHP, because its usage is contact-free, time flexible, and offers, additionally, voice-guided health education programs. In an online survey following a cross-sectional single case study design with 393 study participants, we examined the associations between audiovisual stimulation and mental health, work engagement, and burnout. Using multiple regression analyses, we could identify positive associations between audiovisual stimulation and mental health, burnout, and work engagement. However, longitudinal data are needed to further investigate causal mechanisms between mental health and the use of audiovisual stimulation. Nevertheless, especially with regard to the pandemic, audiovisual stimulation may represent a promising measure for improving mental health at the workplace.
... The initial results have demonstrated that audio brain entrainment alone can improve sleep quality, especially for sleep latency. This has also been seen in other studies (Tang et al., 2016;Tang et al., 2015) with different groups of people showing positive effects of audio brain entrainment. However, more experiments need to be done to elucidate exactly how the pulse tones affect the brain. ...
Full-text available
Sleep health has become an important healthy lifestyle. Research has shown that almost one-fifth of the Korean adult population does not have sufficient sleep. The lack of sleep is associated with significant medical, psychological, social, and economic issues. People are not only yearning for sufficient sleep but the quality of sleep as well. Usually, the obvious choice will be the use of pharmaceuticals however, these often have various side effects, and the lasting use of these medications could become a concern. Therefore, new non-drug alternatives are sought after. Audio brain entrainment is a procedure that modules neural activities by synchronizing brainwave frequency with pulse tones. By producing frequency tones for the deep sleep stage, it promotes a good night’s sleep. In this paper, we developed a pillow integrated with the audio speakers that produce alpha and theta beats that should help improve sleep. Sleep polysomnography was performed on 10 people to compare the effects of the audio stimulus. Initial results showed a positive effect on sleep onset latency, indicating that sleep induction happened. This noninvasive stimulation technique can be a promising candidate for wearable bioelectronics medicine and further neuroscience research.
... One of the promising means of this kind is acous tic (sound) stimulation. At present, acoustic influ ence to improve sleep is realized in commercial devices with feedback [1], in devices of light and sound stimulation (so called "mind machines", [2]), and is also declared in audio recordings of psychotherapeutic orientation [3,4] and some online applications. ...
Full-text available
“Binaural beats” (BB) is a type of sound stimulus being studied as non�invasive tools to promote sleep. BB is a sensation occuring when two monotonous sounds of slightly different pitch are supplied to the listener’s right and left ear separately. This type of stimulation has the advantage to be perceived even at very low sound volumes essentially bordering the hearing threshold, so such a stimulus creates little disturbance to sleep. However, the patterns of its effect are difficult to study due to the weakness of electric brainwave response. The purpose of present paper is to check applicability of the brainwave entrainment hypothesis to auditory stimuli with embedded BB delivered during short-term human nap. The results demonstrate variability of auditory steady state response (ASSR) depending on BB frequency of the stimulus as well as on sleep stage that is not envisaged by the above hypothesis. It should be taken into account when predicting the effect of BB�based noninvasive sleep aids. Furthermore, the analysis of ASSR spectra allows the hypothesis to be put that the human brain falling asleep is a self�adjusting system in relation to incoming sound stimuli, for it strengthens the elements of auditory response which contribute to deepening of naturally evolving sleep.
... 28 Furthermore, a virtual third wave is perceived by the brain as a binaural beat with the frequency difference between the two sounds. [29][30][31] For instance, when a sinusoidal 250-Hz pure tone is supplied to the left ear and a 256-Hz tone is simultaneously presented to the right ear, the brain perceives an amplitude variation with a frequency rate of 6 Hz. 28 As a result, different studies have focused on the psychological effects of the binaural beats of various frequencies and reported substantial evidence in this regard. ...
Full-text available
Background: Although previous evidence confirms the effects of sleep deprivation on mental health and wellbeing, due to the interaction effects of sleep and mood on each other, the influence of sleep improvement has received less attention. Objective: This study aimed to find whether binaural beat technology can enhance sleep quality and thus post-sleep mood. Methods: Twenty healthy students participated in this pilot study. All subjects were investigated for two weeks (a baseline week and an experimental week). In the first week, there was no intervention, but in the second week, all subjects were exposed to a 90 min binaural beat in the delta frequency range. The individuals' sleep was monitored for two weeks using a sleep diary form, and a Profile of Mood State questionnaire was employed to assess their mood at the end of the first and second weeks. Results: Auditory stimulation with delta binaural beat enhanced sleep parameters such as sleep failure, the number of awakenings, real duration of sleep, sleep quality, and feeling following the waking of the individuals. Finally, students' moods improved by reducing anxiety and anger, but other mood parameters did not indicate a significant difference. Conclusion: The findings of this study confirmed that auditory stimulation with a delta binaural beat seems to be a low-cost and alternative method for medicine and other treatment methods with side effects. Application: This study demonstrates the use of technology with a neuroergonomics approach to improve sleep and mood disorders.
... This activation included areas of brain function related to sleep. Sleep begins in the brainstem and enters the thalamus, where auditory sensory information is processed through sensory neural pathways (Tang et al., 2015). Ultimately, it is believed that auditory signals in the thalamus may influence the sleep regulatory system (Lee et al., 2019). ...
Full-text available
Background: Autonomous sensory meridian response (ASMR) is used by young people to induce relaxation and sleep and to reduce stress and anxiety; it comprises somatosensation caused by audiovisual stimuli (triggers) that lead to positive emotions. Auditory stimuli play the most important role among the triggers involved in ASMR and have been reported to be more triggering than visual stimuli. On the other hand, classical music is also known to have a relaxing effect. This is the first study to clarify the difference in brain activation associated with relaxation effects between ASMR and classical music by limiting ASMR to auditory stimulation alone. Methods: Thirty healthy subjects, all over 20 years of age, underwent fMRI while listening to ASMR and classical music. We compared the differences in brain activation associated with classical music and ASMR stimulation. After the experiment, the subjects were administered a questionnaire on somatosensation and moods. After the experiment, the participants were asked whether they experienced ASMR somatosensation or frisson. They were also asked to rate the intensity of two moods during stimulation: “comfortable mood,” and “tingling mood”. Result: The results of the questionnaire showed that none of the participants experienced any ASMR somatosensation or frisson. Further, there was no significant difference in the ratings given to comfort mood, but there was a significant difference in those given to tingling mood. In terms of brain function, classical music and ASMR showed significant activation in common areas, while ASMR showed activation in more areas, with the medial prefrontal cortex being the main area of activation during ASMR. Conclusion: Both classical music and the ASMR auditory stimulus produced a pleasant and relaxed state, and ASMR involved more complex brain functions than classical music, especially the activation of the medial prefrontal cortex. Although ASMR was limited to auditory stimulation, the effects were similar to those of listening to classical music, suggesting that ASMR stimulation can produce a pleasant state of relaxation even if it is limited to the auditory component, without the somatic sensation of tingling. ASMR stimulation is easy to use, and appropriate for wellness purposes and a wide range of people.
... The use of auditory stimuli to induce specific brain states, more specifically, its applications for a variety of mental wellbeing measures, has been a vastly explored topic in academic literature. A study conducted on a senior citizen population by Tang et al. (2015) found that 30 min of daily audiovisual stimulation for a month was seen to improve sleep quality (PSQI), insomnia, and depression. A more time-intensive study on a similar age demographic to that of our study involved 8 weeks of auditory stimulation for adolescent soccer players, also finding positive changes in sleep quality (Abeln et al., 2014). ...
Full-text available
Teenagers are highly susceptible to mental health issues and this problem has been exacerbated by the quarantine restrictions of COVID-19. This study evaluated the use of Heartfulness Meditation and Audio Brainwave Entrainment to help teenagers cope with mental health issues. It used 30-min Heartfulness meditation and 15-min brainwave entrainment sessions with binaural beats and isochronic tones three times a week for 4 weeks. Using a pretest-posttest methodology, participants were asked to complete a survey battery including the Pittsburgh Quality of Sleep Index, Perceived Stress Scale, Patient Health Question-9, Profile of Mood States, and Cambridge Brain Health assessment. Participants (n = 40) were divided into four experimental groups: the control group (n = 9), Audio Brainwave Entrainment group (n = 9), Heartfulness Meditation group (n = 10), and a combined group (n = 12), for a 4-week intervention. Data were analyzed with paired t-tests. The singular Audio Brainwave Entrainment group did not see statistically significant improvements, nor did any of the intervention groups for brain health (p > 0.05). This study, however, proved the efficacy of a 4-week Heartfulness Meditation program to regulate overall mood (p = 0.00132), stress levels (p = 0.0089), state depression (POMS; p = 0.0037), and anger (p = 0.002). Results also suggest adding Audio Brainwave Entrainment to Heartfulness Meditation may improve sleep quality (p = 0.0377) and stress levels (p = 0.00016).
... In another study performing neurofeedback AVS on eight elderly people, the severity of insomnia decreased to the sub-critical insomnia range after one month of AVS intervention. Significant changes were observed in the PSQI subscales of daytime dysfunction (p = 0.048) and sleep quality (p = 0.004), and the Patient Health Questionnaire-9 (PHQ-9) score decreased in five out of eight subjects with a reference score of 5 or more (p = 0.004) [18]. ...
Full-text available
Sleep is a crucial factor for human health and is closely related to quality of life. Sleep disturbances constitute a health problem that should be solved, especially when it affects the elderly. This study aims to examine the effectiveness of information and communication technologies (ICT) interventions in managing sleep disturbances in the elderly. The study used a systematic review of three databases: Ovid-Medline, Ovid-EMBASE, and the Cochrane library database for papers published till 15 April 2021. Two authors independently selected and screened relevant studies based on predefined inclusion criteria. The meta-analysis of randomized controlled trials (RCTs) was carried out using Review Manager 5.4. Two authors independently screened the titles and abstracts of 4297 studies considering both inclusion and exclusion criteria. The complete texts of 47 articles were then evaluated, 31 articles were excluded, and finally, 16 articles were selected. Our meta-analysis showed that the cognitive-behavioral therapy for insomnia (CBT-I) group had a significantly reduced Insomnia Severity Index (ISI) compared to the control group (−4.81 [−5.56, −4.06], p < 0.00001, I2 = 83%) in RCTs, with a significant reduction in ISI (3.47 [1.58, 5.35], p = 0.0003) found in quasi-experimental studies. A significant improvement was found in total sleep time in the CBT-I group compared to the control group (29.24 [15.41, 43.07], p
Sleep is essential for optimal health, well-being and performance, with NREM and REM sleep each playing a role in maintaining optimal brain states. Slow wave sleep (SWS) is the deepest and most restorative stage of NREM sleep and is critical for cognitive function and aspects of brain and physical health. Advancing age, some psychiatric conditions, and challenging/diminished sleep opportunities lead to a reduction of SWS levels. Recent technologies have thus been developed to restore or enhance SWS using non-invasive brain stimulation techniques. This article explores the use of these technologies in enhancing SWS, and the potential benefit on physiological and psychological functioning, across different populations. Although other aspects of sleep remain important for optimal function (e.g., REM sleep), technologies focused on these aspects of sleep are fewer and in their infancy. While current technological approaches to enhancing sleep are promising, more research is needed to understand their long-term effects and potential benefits.
Osteoarthritis is commonly comorbid with insomnia in older adults. While cognitivebehavioral therapy for insomnia is the recommended first-line treatment for insomnia, alternative efficacious non-pharmacological options are needed. This study examined sleep and pain in 30 community-dwelling older adults with comorbid insomnia and osteoarthritis pain randomized to two weeks of 30 minutes of bedtime active (n=15, mean age 66.7 ± 5.2) or placebo control (n=15, mean age 68.9 ± 5.0) Audiovisual Stimulation (AVS). After AVS use, improvements in sleep, pain, and depression were reported for both groups but between-group comparisons were non-significant. A posthoc analysis examined the effects of AVS in the 11 subjects who reported sleep latency complaints (≥30 minutes). No significant group differences were found for this small sleep latency subsample; however, the pre-post effect sizes (ES) of active AVS versus placebo were greatly increased for the subsample relative to the total sample for sleep (ES=.41 versus .18 for the Insomnia Severity Index, and .60 versus .03 for the Pittsburgh Sleep Quality Index, respectively). A similar enhanced effect pattern was found for pain (ES=.41 versus .15 for the Brief Pain Inventory). Study findings suggest that the 30-minute AVS program may have potential to improve sleep in older adults with sleep onset but not sleep maintenance difficulty. Despite study limitations of a small sample size and lack of follow-up, results offer valuable insights into the functionality of AVS treatment. Future research should focus on subjects with sleep onset complaints, who are most likely to receive benefit from this treatment modality.
Full-text available
This pilot study tested the efficacy of an audio-visual stimulation (AVS) program for the promotion of sleep in individuals with chronic pain. Insomnia and chronic pain are common comorbid conditions and their relationship has been viewed as bidirectional. Recent studies suggest a relatively dominant role of sleep in this dyad. The premise of this pilot study was that AVS enhances low frequency while reducing high frequency brain activity resulting in decreased hyperarousal and improved sleep with potential consequent reduction in pain. We conducted a pilot intervention study of AVS using a pre-post design. Participants self-administered a 30-min AVS program nightly at bedtime for 1 month. Sleep and pain were assessed at baseline and at the conclusion of the 4-week intervention phase. Nine adults (mean age 33 ± 15.8 years; female, 89 %) completed the study. After using the AVS device for 4 weeks, significant improvement was seen in reported insomnia (ISI, p = 0.003), pain severity (BPI, p = 0.005), and pain interference with functioning (BPI, p = 0.001). Large effect sizes (Partial η(2) 0.20-0.94) (Cohen's d 0.44-1.45) were observed. The results of this pilot study suggest that the AVS program may be efficacious in decreasing both insomnia and pain symptoms. In order to better assess the efficacy of AVS for sleep promotion and possible pain reduction, more definitive randomized controlled trials will be needed. These should include appropriate sample sizes, objective measures of sleep and pain, and longitudinal follow-up.
Full-text available
Purpose To investigate the prevalence of low back pain among Finnish firefighters and to examine whether sleep disturbances predict membership of low back pain trajectories. Methods In this prospective study, 360 actively working firefighters responded to a questionnaire in 1996, 1999 and 2009. The outcome variables were radiating and local low back pain during the preceding year. Using logistic regression modeling, the likelihood of membership of pain trajectories was predicted by sleep disturbances at baseline. Results During the 13-year follow-up, the prevalence of radiating low back pain increased from 16 to 29 % (p < 0.0001) and that of local low back pain from 28 to 40 % (p < 0.001). The following trajectories were identified: “pain free,” “recovering,” “new pain,” “fluctuating” and “chronic.” More than one-fifth of the participants belonged to the new pain trajectory as regards both pain types, 6 % of the participants belonged to the chronic radiating and 12 % to the chronic local low back pain trajectory. Those with sleep disturbances at baseline had a 2.4-fold risk (adjusted OR 2.4; 95 % CI 1.2–4.7) of belonging to the new pain or chronic radiating pain cluster compared to pain-free participants. Conclusions This is the first prospective study to show that low back symptoms are common and persistent among firefighters and that sleep disturbances strongly predict membership of a radiating pain trajectory. Occupational health and safety personnel, as well as the firefighters themselves, should recognize sleep problems early enough in order to prevent back pain and its development into chronic pain.
Excerpt The analysis of the action potential of the axon, especially as regards the spike, describes quite completely and accurately the phasic, all-or-none, aspects of the electrical activity of the axon. Since the recent work of Gasser and his associates (1) on after-potentials and the work of Levin (2) and Furusawa (3) on the retention of negativity in crustacean axons, more attention has been directed to a different type of electrical change in the axon occurring as a result of its activity. This slow summated depolarization which does not behave in an all-or-none manner, and which is very slow in recovery compared to the spike and negative after-potential, represents the more “tonic” change in the steady state of the axon, a process with which we are greatly concerned in any discussion of the electrical activity of the central nerve cells. There is some evidence from the work of Monnier and Jasper...
If the language of the brain lies in its neuronal coding, then the expression of the brain lies in its rhythmicity and timing. The rhythmicity is due to the selective synchronization and desynchronization of the encoding within billions of pools of neurons which provide the sensory activity of everything that is sensed, thought, or done. Berger (1929) observed all four main rhythms-the alpha, beta, theta, and delta-in his very first EEG recording. It should come as no surprise, therefore, that since the earliest EEG studies, interest has turned toward rhythmic sensory stimulation, and its possible effects on brain function. A large and growing body of research and clinical experience demonstrates that audio-visual entrainment (AVE) quickly and effectively modifies conditions of high autonomic (sympathetic and parasympathetic) activation and over- and under-aroused states of mind, bringing about a return to homeostasis. AVE exerts a powerful influence on brain/mind stabilization and normalization by means of increased cerebral flow, increased levels of certain neurotransmitters, and by normalizing EEG activity. AVE is proving to be a safe and cost-effective treatment, especially for the large numbers of disorders associated with dysfunctions of the central and autonomic nervous system.
Background: There is a need for an easily administered instrument which can be applied to all patients with restless legs syndrome (RLS) to measure disease severity for clinical assessment, research, or therapeutic trials. The pathophysiology of RLS is not clear and no objective measure so far devised can apply to all patients or accurately reflect severity. Moreover, RLS is primarily a subjective disorder. Therefore, a subjective scale is at present the optimal instrument to meet this need. Methods: Twenty centers from six countries participated in an initial reliability and validation study of a rating scale for the severity of RLS designed by the International RLS study group (IRLSSG). A ten-question scale was developed on the basis of repeated expert evaluation of potential items. This scale, the IRLSSG rating scale (IRLS), was administered to 196 RLS patients, most on some medication, and 209 control subjects. Results: The IRLS was found to have high levels of internal consistency, inter-examiner reliability, test-retest reliability over a 2-4 week period, and convergent validity. It also demonstrated criterion validity when tested against the current criterion of a clinical global impression and readily discriminated patient from control groups. The scale was dominated by a single severity factor that explained at least 59% of the pooled item variance. Conclusions: This scale meets performance criteria for a brief, patient completed instrument that can be used to assess RLS severity for purposes of clinical assessment, research, or therapeutic trials. It supports a finding that RLS is a relatively uniform disorder in which the severity of the basic symptoms is strongly related to their impact on the patient's life. In future studies, the IRLS should be tested against objective measures of RLS severity and its sensitivity should be studied as RLS severity is systematically manipulated by therapeutic interventions.
Objective: While considerable attention has focused on improving the detection of depression, assessment of severity is also important in guiding treatment decisions. Therefore, we examined the validity of a brief, new measure of depression severity. Measurements: The Patient Health Questionnaire (PHQ) is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders. The PHQ-9 is the depression module, which scores each of the 9 DSM-IV criteria as "0" (not at all) to "3" (nearly every day). The PHQ-9 was completed by 6,000 patients in 8 primary care clinics and 7 obstetrics-gynecology clinics. Construct validity was assessed using the 20-item Short-Form General Health Survey, self-reported sick days and clinic visits, and symptom-related difficulty. Criterion validity was assessed against an independent structured mental health professional (MHP) interview in a sample of 580 patients. Results: As PHQ-9 depression severity increased, there was a substantial decrease in functional status on all 6 SF-20 subscales. Also, symptom-related difficulty, sick days, and health care utilization increased. Using the MHP reinterview as the criterion standard, a PHQ-9 score > or =10 had a sensitivity of 88% and a specificity of 88% for major depression. PHQ-9 scores of 5, 10, 15, and 20 represented mild, moderate, moderately severe, and severe depression, respectively. Results were similar in the primary care and obstetrics-gynecology samples. Conclusion: In addition to making criteria-based diagnoses of depressive disorders, the PHQ-9 is also a reliable and valid measure of depression severity. These characteristics plus its brevity make the PHQ-9 a useful clinical and research tool.
Unlabelled: In a primary care population of 367 older adults (aged ⩾60 years) with osteoarthritis (OA) pain and insomnia, we examined the relationship between short-term improvement in sleep and long-term sleep, pain, and fatigue outcomes through secondary analyses of randomized controlled trial data. Study participants, regardless of experimental treatment received, were classified either as improvers (⩾30% baseline to 2-month reduction on the Insomnia Severity Index [ISI]) or as nonimprovers. After controlling for treatment arm and potential confounders, improvers showed significant, sustained improvements across 18 months compared with nonimprovers in pain severity (P<0.001, adjusted mean difference=-0.51 [95% CI: -0.80, -0.21), arthritis symptoms (P<0.001, 0.63 [0.26, 1.00]), and fear avoidance (P=0.009, -2.27 [-3.95, -0.58]) but not in catastrophizing or depression. Improvers also showed significant, sustained improvements in ISI (P<0.001, -3.03 [-3.74, -2.32]), Pittsburgh Sleep Quality Index Total (P<0.001, -1.45 [-1.97, -0.93]) and general sleep quality (P<0.001, -0.28 [-0.39, -0.16]) scores, Flinders Fatigue Scale (P<0.001, -1.99 [-3.01, -0.98]), and Dysfunctional Beliefs About Sleep Scale (P=0.037, -2.44 [-4.74, -0.15]), but no improvements on the Functional Outcomes of Sleep Questionnaire or the Epworth Sleepiness Scale. We conclude that short-term (2-month) improvements in sleep predicted long-term (9- and 18-month) improvements for multiple measures of sleep, chronic pain, and fatigue. These improvements were not attributable to nonspecific benefits for psychological well-being, such as reduced depression. These findings are consistent with benefits of improved sleep for chronic pain and fatigue among older persons with osteoarthritis pain and comorbid insomnia if robust improvements in sleep are achieved and sustained. Trial registration: Identifier: NCT01142349.