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An Investigation into the effects of Binaural Beat
phenomena on Cold Pain Endurance
Goldsmiths College, University of London
Student: Peter D. Bryant (33258242)
Supervisor: Prof. Joydeep Bhattacharya
12/09/13
Word Count = 9,999
Thesis submitted in partial fulfilment of an MSc in Music, Mind and Brain
Binaural Beat Study Music, Mind and Brain Goldsmiths College
Acknowledgements
I am immensely grateful to Robert Davies for all his help and support with the preparation,
testing and amending of the equipment required for this study. I also wish to thank Matt
Kendall of ‘Interesting Talks London’ who assisted in the participant recruitment process by
promoting the study website (www.bbstudy.co.uk) to over five thousand people across
London. I am grateful to Dr. Daniel Müllensiefen and Dr. Lauren Stewart who have provided
assistance and support throughout the experimentation phase – thank you. I also wish to
thank all of the fifty-one participants who took part and withstood a painful experience for
effectively no reason other than to (hopefully!) further scientific understanding into binaural
beats. Finally, I wish to thank Professor Joydeep Bhattacharya for all his help and support
with this project. His guidance, knowledge and influence was essential to its completion and
success.
List of Tables
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
Table 1: Dependent and Independent Variables......................................................................16Table 2: Descriptive Statistics of Normalised Data for all reaction time conditions...............24Table 3: Descriptive Statistics for Raw Score Reaction Time Conditions..............................25Table 4: Normality tests for non-normalised reaction time data..............................................26Table 5: Descriptive Statistics for Normalised Reaction Time Scores....................................27Table 6: Descriptive statistics for Binaural Beats against Monaural Beats.............................28Table 7: Descriptive statistics for Beat Frequency..................................................................28Table 8: Descriptive Statistics for control conditions (Music, Silence and White Noise).......29Table 9: Pairwise comparison of control conditions showing a main effect of Music against Silence and White Noise..........................................................................................................30Table 10: Descriptive Statistics for subjective measures of Liking.........................................31Table 11: Estimated means for subjective measures of Liking................................................31Table 12: Normality test for Liking data (Non-Normalised)...................................................31Table 13: Normality tests of Liking for Normalised data........................................................32Table 14: Pairwise comparisons for all Liking data according to condition (only significant main effects shown).................................................................................................................34Table 15: Normality tests for measures of Pain Reduction (Non-Normalised).......................35Table 16: Normality tests for Pain Reduction (Normalised Data)...........................................35Table 17: Descriptive statistics for subjective measures of Pain Reduction............................36Table 18: Mean Estimates for subjective measures of Pain Reduction...................................36Table 19: Pairwise Comparisons for subjective measures of Pain Reduction demonstrating a host of significant differences, in particular for the control conditions of Music and White Noise........................................................................................................................................38Table 20: Descriptive statistics for Gender showing a significant difference of means according to Mean Reaction Time...........................................................................................39Table 21: Descriptive Statistics for Anxiety against Mean Reaction Time (in Seconds)........43Table 22: Normality tests for Goldsmiths Musical Sophistication Index Scores....................47Table 23: Descriptive statistics for Goldsmiths Musical Sophistication Index.......................47Table 24: Descriptive statistics for Body Vigilance Scale scores after a median split............48Table 25: Descriptive statistics for measures of heart rate......................................................49Table 26: Normality tests for heart rate...................................................................................49
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
List of Figures
Figure 1: Depiction of the experimental design.......................................................................16Figure 2: Depiction of the warm water tank with surface and depth thermometers................19Figure 3: Depiction of the ice tank complete with ice chamber, circulatory pump, surface and depth thermometers and air compression button.....................................................................19Figure 4: Depiction of the two warm tank thermometers........................................................20Figure 5: Depiction of the two cold tank thermometers..........................................................20Figure 6: Sennheiser HD 202 Closed Back On-ear Stereo Headphones used throughout the experiment................................................................................................................................20Figure 7: The temperature and humidity monitor used throughout the experiment................20Figure 8: Blood pressure monitor used throughout experiment...............................................20Figure 9: A Comparison of means across all raw reaction time conditions showing a main effect for the music condition..................................................................................................25Figure 10: Depiction of means of normalised reaction time data showing a main effect for the Music condition........................................................................................................................27Figure 11: Comparison of reaction time means across control conditions showing a main effect of Music.........................................................................................................................29Figure 12: Comparison of mean liking data across all conditions showing a main effect for the Music condition/.................................................................................................................33Figure 13: Comparison of means for subjective measures of pain reduction across all conditions showing a main effect of Music with silence being significantly the ‘worst’ condition against all other conditions......................................................................................37Figure 14: Mean reaction time against Gender........................................................................39Figure 15: Correlation figure of r .42 for pain threshold against liking rating (pooled across all participants and all conditions) showing a significant effect for liking in improving reaction time duration..............................................................................................................40Figure 16: Correlation figure of r = .53 for pain threshold against pain reduction rating (polled across all participants and conditions) indicating that participants who rated a condition as ‘less painful’ showed increased reaction time scores..........................................41Figure 17: Correlation figure of r = .70 for pain reduction rating again liking rating (pooled across all participants and all conditions) indicating that the two measures of liking and pain reduction rating are highly correlated......................................................................................42Figure 18: Significance test of correlations of subjective measures (Liking, Pain Reduction and Reaction Time) showing a strong significant difference between the correlations of subjective measures..................................................................................................................43Figure 19: A correlation figure of Zung general anxiety rating against mean reaction time demonstrating that the higher a participants initial anxiety score, the less their mean reaction times were across all conditions...............................................................................................44Figure 20: Comparison of first and last conditions of the experiment according to mean reaction time.............................................................................................................................45Figure 21: Comparison of blocks examining correlation. They are highly correlated showing that participants show a maintained performance across all nine trials...................................46Figure 22: Median spilt of Gold-MSI data against mean reaction time...................................48Figure 23: A 9 Way ANOVA of mean heart rate against experimental condition..................50Figure 24: Pairwise comparisons for reaction time data..........................................................63Figure 25: Pairwise comparison data by condition (non-normalised data)..............................65Figure 26: Complete pairwise comparisons for liking and pain reduction..............................66
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
Table of Contents
Acknowledgements....................................................................................................................2
List of Tables..........................................................................................................................3
List of Figures........................................................................................................................4
Abstract......................................................................................................................................6
Introduction................................................................................................................................7
What are Binaural Beats?...................................................................................................7
The Study of Pain.............................................................................................................11
Anxiety.............................................................................................................................12
Musicians and Non-Musicians.........................................................................................13
The Binaural Beat Study..................................................................................................14
Design......................................................................................................................................16
Participants...............................................................................................................................17
Materials and Stimuli...............................................................................................................18
Procedure..................................................................................................................................22
Results......................................................................................................................................24
Reaction Times.....................................................................................................................24
Subjective Measures.........................................................................................................30
Subjective Measure Correlations.....................................................................................40
Gold MSI..............................................................................................................................46
Body Vigilance Scale...........................................................................................................48
Biological Measures.........................................................................................................49
Stimuli Detection.............................................................................................................51
Discussion................................................................................................................................52
Bibliography.............................................................................................................................58
Appendix A: Non-significant Data..........................................................................................62
Appendix B: Anxiety Questionnaires (BVS and ZARS).........................................................67
Appendix C: Participant information documentation..............................................................70
Appendix D: Calculations........................................................................................................73
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
Abstract
Binaural beats have anecdotally been claimed to decrease the perception of pain and,
therefore, increase pain endurance. This repeated measures: double blind study examined
three frequencies of binaural beat against three identical monaural beats along with three
control conditions, music, silence and white noise utilising a cold pressor pain task. There
was no main effect for binaural beats against any of the conditions; however, there was a
main effect for music against silence F (2, 100) = 7.36, p < .001. Furthermore, musicians
performed significantly better at the cold pain task than non-musicians t = 3.52, p < .001.
Further significant results were found in anxiety scores, gender differences in reaction time
and participant’s inability to detect the stimuli as binaural (particularly in non-musicians).
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
Introduction
What are Binaural Beats?
In 1839, H. W. Dove, a physicist and meteorologist, discovered the phenomenon of
binaural beats (Dove, 1839) (Oster, 1973). These beats are illusionary auditory artefacts
created by the interference of two independently pitched sine tones, both of which are in the
frequency range of 100 (Kasprzak, 2011) to 1000 hertz (Licklider, Webster, & Hedlun, 1950)
(Perrott & Nelson, 1969). When presented simultaneously and bilaterally, (each tone is
presented independently to each ear) these tones generate the sensation of beating when no
objective beating is taking place in physical reality. This is because when the difference
between the two independent frequencies is between one and thirty hertz the auditory
mechanisms within the human brain fail to separate out the two sounds and fuse them
together as if they had fused in physical reality rather than subjectively inside the listener’s
neural pathway (Turow & Lane, 2011). These tones can vary in frequency by a specific
margin (of up to thirty hertz difference between the base tone and the fluctuating tone at
frequencies between two hundred to five hundred hertz (Gu, Wright, & Green, 1995; Slatky,
1992). Any pitch difference larger than this and the cocktail party effect begins to take place
with each note being treated as a separate sound source. These artefacts exist partly due to the
size of the human head and the auditory processing mechanisms which are specifically
designed to detect sound pressure differences in this range; this is the same auditory
mechanism which allows us to locate a sound with a high degree of accuracy; it is, therefore
essential for the survival of the human species. It just so happens that this evolutionary
development can be exploited in order to create the best desired perceptual beating effect for
application in a number of domains (Gelfand, 2009). Between 1839 and the mid-nineteenth
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
century, the phenomenon had largely been regarded as a scientific and perceptual curiosity
with remarkably few studies conducted in their possible application (which may have been
down to a misunderstanding of their functioning) (Oster, 1973). Today, however, binaural
beats are gaining in popularity, particularly with the rise of the internet where many
downloads, apps and related paraphernalia can be found which claim to use binaural beats in
the treatment of a host of mental and physical problems including anxiety, sleep difficulties
and even erectile dysfunction. The plausibility of these claims is highly disputed with
exceedingly few studies published (some domains have no published evidence at all) whilst
the majority of papers report on the use of binaural beats as a panacea for stress and anxiety.
Anecdotal evidence, however, appears to be rife among this online community with claims of
miraculous cures and quick fix solutions to genuine mental health issues. The entire industry
rests on a single hypothesis; that of brainwave entrainment.
Brainwave entrainment is an early theory that was developed alongside the invention
of the EEG machine in the early 20th century (Oster, 1973). A theory of brainwave
entrainment was first postulated as a supporting theory for evidence from the visual domain
in that the corresponding visual stimuli to binaural beats (such as highly brief flashes of light
at the same frequency rates as binaural beats – one to thirty hertz) can entrain brain waves
and thus influence the conscious state of the participant (Herrmann, 2001; Budzynski, 2006).
This theory was later extrapolated into the auditory medium and applied to the phenomena of
binaural beats (Foster, 1990). Most of the ‘modern’ day studies on binaural beats were
conducted in the latter half of the 20th century - possibly due to their demand for synthetic
audio technology (the phenomena, owing to the use of pure sinusoidal tones do not normally
exist in the natural environment (Oster, 1973). The results of these studies have been mixed,
some showing effectiveness in the application of binaural beat technology for stress
management, pain reduction, and behavioural improvement (Huang & Charyton, 2008) along
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
with affect vigilance (attention) and improvement of mood (Lane, Kasian, Owens, & Marsh,
1998) whilst others have shown none or very little effects, for example, with pain perception
(Wahbe, Calabrese, Zwickey, & Zajde, 2007; Stevens, et al., 2003). This lack of research on
the topic has not stopped the phenomena being claimed to be able to induce a change in
consciousness state along with a large amount of other desirable mental affects and even used
an ‘auditory drug’ (gethightnow.com, 2013). Their use in this domain has been supported by
claims such as ‘years of research and development, and unmatched standards’ when a total of
three ‘papers’ can be found on the so called leading researcher’s website (I-Doser.com,
2012). This is anecdotally regarded as being a feature of brainwave entrainment although the
supporting evidence and research for brainwave entrainment, contrary to popular opinion is
severely lacking in research and, therefore, supporting evidence (Turow & Lane, 2011).
There are several contrasting theories of how binaural beats may entrain neural networks
within the brain and produce neural ‘rhythms’ within the cortex. One popular hypothesis is
that binaural beat signals influence the brain’s reticular activating system, a network of
systems which control nervous system arousal. This in turn, over time, may stimulate the
thalamus and cortex to alter arousal states in accordance with the reticular activating system
and, therefore, consciousness utilizing neurotransmitters and other inter-cortical signals
(Turow & Lane, 2011). Other theories have included the ‘trapping’ of periodic frequencies by
event related potentials (Kaernbach, Schroger, & Gunter, 1998) with brainwaves
synchronising to non-binaural phenomena with repetition rates between one and forty hertz
(Will & Berg, 2007).
Perhaps the most notable contributor to the research field on binaural beats has been
the Monroe Institute, which was specifically established to investigate binaural beat
phenomena and consciousness by the late Robert Monroe (1915 – 1995) in 1956 (The
Monroe Institute, 2013). The centre has claimed a number of successes with binaural beat
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
technology with its website offering products supported by the institute’s research. However,
it remains a highly mysterious company considering its unique status, publishing only three
books in over forty years and around fifty papers (the vast majority published before 2000)
on a range of pseudoscientific topics including Remote Viewing, Reiki and Neuro-Linguistic
Programming among others (The Monroe Institute, 2013). Indeed, the centre has claimed that
binaural beats are in themselves, not particularly effective and that it is the accompanying
music, noise and even linguistic suggestion which is actually responsible for the overall
effects (Turow & Lane, 2011). However, binaural beats are genuine, observable phenomena
which can be experienced by anyone with a correctly functioning auditory pathway and
bilaterally functioning ears (Fitzpatrick, Roberts, Kuwada, Kim, & Filipovic, 2009; Zeng,
Kong, Michaelwski, & Starr, 2004; Altenmuller, 1989) and even in other species such as cats
(Kuwada, Yin, & Wickesberg, 1979). It is the claims which surround them that are lacking in
empirical research and subject to considerable hyperbole. Some of these claims (such as
anxiety reduction and mood alteration) have been subject to examination – but not one of the
claims has been subjected to meta-analytical scrutiny, simply because there is a significant
lack of published studies within this area. However, of the studies which have been
published, researchers have found binaural beats to be effective at maintaining alertness
(Lane, Kasian, Owens, & Marsh, 1998), to treat attention deficit disorder (ADD) (Kliempt,
Ruta, Ogston, Landeck, & Martay, 1999), to relax (Le Scouarnec, et al., 2001), to meditate
(Padmanabhan, Hildreth, & Laws, 2005), and to (possibly) manage pain (Wahbeh, Calabrese,
Zwickey, & Zajdel, 2007). However, these studies are considerably small, for example; the
Wahbeh pain study had only eight participants, and have yet to be replicated which represents
a considerably uncertain evidence base for the application of binaural beats to genuine
medical issues.
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
The Study of Pain
The perception of pain is now widely acknowledged as a highly subjective
phenomenon (Koyama, McHaffie, Laurienti, & Coghill, 2005). Pain perception can be
significantly affected by the placebo and expectation effects such as with the injection of a
saline solution (Melzack & Wall, 1996) and by social features, for example, whether you
suffer alone or with a friend (Eisenberger & Lieberman, 2005). Furthermore, the theories and
history of pain perception is anything but straightforward, with a range of ideas as to how
pain is created, transmitted, and perceived (Meldrum, 2011). There is also evidence to
suggest that pain perception varies according to gender (Paulson, Minoshima, Morrow, &
Casey, 1998) with women in particular demonstrating heightened experience to pain when
anxious.
One of the most common methods of inducing pain in a clinical or research setting is
by employing a cold pressor test as it is thought to mimic the effects of chronic pain
conditions effectively (Mitchell, MacDonald, & Brodie, 2004). However, it does suffer from
weaknesses such as the need to ensure a constant temperature (set generally between one to
five degrees Celsius) and has been reported to produce different results depending on the
gender of the participant (Mitchell, MacDonald, & Brodie, 2004). In order to achieve internal
validity, I needed a method of inducing pain that would be highly repeatable, non-invasive
and most importantly, safe. The cold pressor test is a cardiovascular test where participants
immerse their arm or hand into ice water for as long as possible up to a pre-specified time
limit (most often one minute). It has been used as a mechanism of inducing pain for
psychological experiments since it was first used for an experiment in 1936 (Mitchell L. A.,
2013). The technique operates by stimulating the sympathetic nervous system as the heat
from blood entering the arm is rapidly lost to the surrounding water. This causes a
constriction of blood vessels in the submerged limb with the participant’s blood pressure and
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
heart rate increasing in order to maintain homeostasis. It can, therefore, be used as an
objective and highly repeatable method of recording a participant’s pain endurance and
threshold. It is also extremely safe, with the participant remaining in full control of how long
they undergo the pain stimulus with no potential for damage to body tissues. Cooling body
tissue is regarded by experts as comparatively better for it than heating body tissue. The
process of cooling actually slows down cell decay and death in patients who have suffered a
cardiac arrest and is now used regularly as a method of preserving a patient’s vital organs
whilst resuscitation attempts are performed (Parnia, 2013, pp. 74-77).
Anxiety
Anxiety is defined in the OED as ‘a feeling of worry, nervousness, or unease about
something with an uncertain outcome’ (Oxford English Dictionary Online, 2013). It is
associated with a range of somatic, emotional, cognitive, and behavioural components
(Seligman, Walker, & Rosenhan, 2001). There have been a number of scales designed to
measure anxiety. Each scale has been designed for a different setting, usually in a clinical
environment. This study shall use the Zung Anxiety Self-Assessment Scale (see appendix B)
since it is one of the most applicable to the participant’s anxiety at the present time and does
not ask them to focus ‘on the previous two weeks', unlike some other scales (Hamilton,
1959). The Zung Anxiety Self-Assessment Scale is a twenty item checklist which rates a
participant’s general level of anxiety out of a possible maximum score of one hundred. The
test uses a four point Likert-type rating system similar to other anxiety tests such as the
Hamilton Anxiety Rating System (HAM-A) and the Modified Dental Anxiety Scale (MDAS)
(Hamilton, 1959; Humphris, Morrison, & Lindsay, 1995). First developed in 1971: this scale
has been heavily validated as a clinical tool for the assessment of the anxiety level of
outpatients (Zung, 1971; Zung, 1974). The application of this scale may shine light on a
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
possible selection bias within this study since it is unlikely that someone with extreme
anxiety would apply to be a participant for an experiment involving significant amounts of
pain. Indeed, there were a number of participants who refused to participate when they
discovered that the application of pain was an essential part of the study. This fact is reflected
in the results, by which the majority of participants demonstrated scores in the lower half of
the anxiety scale – there were no scores above sixty one.
Musicians and Non-Musicians
I am also looking at the differences in musical sophistication in participants and their
ability to cope with the pain endurance task. Previous research has uncovered differences in
neural activation of musicians and non-musicians although this was in the gamma frequency
range which is outside the frequency range of my study (Ioannou & Bhattacharya, 2011).
Nevertheless, there are a host of phenomena which musicians exhibit as a result of their
neural plasticity by way of their skills and training – a typical example would be absolute
pitch which has been suggested to be the result of a hyper-connectivity of neuronal structures
giving rise to its synaesthesia-like properties (Loui, Li, Hohmann, & Schlaug, 2011). I wish
to see if these effects exhibit themselves at a behavioural level and want to discover whether
musical training affects a participant’s ability to utilize binaural beats (or indeed, music) to
help cope with or otherwise alleviate the pain possibly due to differences in cortical wiring. It
has been shown that practising music – and even listening to it can promote brain plasticity
across a human’s entire life span (Wan & Schlaug, 2010) along with shaping structural brain
development on a macroscopic scale (Hyde, et al., 2009). I also wish to discover if musicians
are better at identifying binaural beats than non-musicians.
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
The Binaural Beat Study
In this experimental study, I shall attempt to answer several hypotheses regarding the
application of binaural beat technology in cold pain endurance. I shall examine whether the
presence or absence of binaural quality to the beating effect has any effect on the duration of
pain endurance to which participants expose themselves. I shall examine whether the
frequency (Delta – 4 hertz, Theta – 8 hertz and Alpha – 14 hertz) of the beat makes any
difference to a participant’s pain threshold and whether any of these conditions are more
effective than Music, Silence or White Noise. I shall also examine the effect of general
anxiety, musical sophistication and body vigilance on the reaction times of the participants
and across all conditions. Furthermore, I shall examine a participant’s ability to identify
whether the beats are binaural thereby examining expectation effects which have been shown
to be considerably likely to contribute to the effects of binaural beats in other studies – in
particular a small pain study conducted on eight participants where it was argued that
expectation effects were responsible for the overall effect of the experiment (Wahbeh,
Calabrese, Zwickey, & Zajde, 2007). Participants will undergo a moderately painful
experience by submerging their arm in 0oC water for a specified duration (3 minutes) – or as
long as they can – whilst continuously listening to binaural beats. I have chosen this timing in
order to reduce the possibility of ceiling effects and to ensure that even participants with
unusually high pain tolerances feel sufficiently challenged. Before commencing with the
experimental procedure with any participants, full ethical approval was granted by the
Goldsmiths Psychology Department Ethics Committee. Given the scope and uncertainty of
the literature, I am hesitant about finding an effect for binaural beats against other conditions
other than silence. I believe that music will perform favourably with silence being the worst
condition, followed shortly by white noise. I believe that the lower frequency binaural beats
will outperform the other higher conditions in this situation as they are more likely to
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
contribute towards a relaxation effect and have shown similar results in previous studies
(Wahbeh, Calabrese, Zwickey, & Zajde, 2007; Kliempt, Ruta, Ogston, Landeck, & Martay,
1999). Furthermore, I expect that participants will not be able to identify which sound is
binaural – this is somewhat crucial to the validity of the experimental procedure which has
been designed to reduce effects due to expectation as much as possible. If participants are
able to identify the binaural or monaural stimuli, it seriously threatens the internal validity of
the experiment; participants can consciously choose how long they keep their hands in the
water according to how much they believe binaural beats to be effective.
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
Design
This study was a repeated measures, double blind trial with each condition lasting a
maximum of three minutes. There were five dependent variables and five independent
variables which are shown below:
Table 1: Dependent and Independent Variables
Dependent Variable Independent Variable
Reaction time of hand in water Detection of Stimuli (Binaural or Monaural)
Heart Rate Frequency of Beat
Blood Pressure Musical Sophistication Score
Liking Rating (1 to 10) BVS Score
Pain Reduction Rating (1 to 10) General Anxiety Rating
A repeated measures ANOVA will be used to analyse the data to examine the relationship (if
any) between the control conditions against both monaural and binaural beats and then
monaural beats against binaural beats. Microsoft Excel (2013) and IBM SPSS statistics (19)
shall be used for the statistical analysis. Every participant will partake in all nine conditions
including three control conditions, music, silence and white noise which will be randomised.
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
Figure 1: Depiction of the experimental design
Participants
There were fifty-one participants for this study recruited over a three month period
(June – August 2013). Twenty five males and twenty six females between the ages of
eighteen and sixty-three with an average age of thirty-one. Participants were recruited by
several methods the most prolific of which was via the dedicated study website
(www.bbstudy.co.uk) which went live in March 2013. As many participants, from as varied a
background as possible were encouraged to apply. The experiment had remarkably few
qualifying standards other than an ability to hear in both ears and a willingness to undergo a
moderately uncomfortable experience. The website was promoted via a social media
campaign and 1,500 business cards to over 5,000 people in the London area via a
meetup.com group called ‘Interesting Talks London’. This was to ensure that as broad a
range of participants was selected as possible. No participants were paid for their contribution
to the study, although a free hour of hypno-psychotherapy (worth £100) was offered (to be
provided by PB) to anyone who took part. This hypno-psychotherapy was to be delivered in
the month after the study had concluded. The participants were from a diverse range of
backgrounds, professions and nationalities. They were a mix of musicians and non-musicians
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
of varying skill level, and no participant had hearing difficulties in either ear. Thirty
participants had anxiety scores that were within the normal range (M = 34.6, SD = 3.57) with
twenty showing minimal to moderate anxiety (M = 50.5, SD = 4.63). One participant showed
marked anxiety (61) with this participant showing the highest score. All participants who
entered the experimental phase of the study completed it. There was one participant who
dropped out when reading the information sheet (appendix C) who did not consent to the
application of pain.
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
Materials and Stimuli
The stimuli for this experiment consisted of nine different sound tracks which were all
prepared simultaneously. A piece of software called Gnaural was used to create all of the
binaural and monaural conditions (http://gnaural.sourceforge.net/). This is an open source
software environment exclusively for the creation of binaural beats. In order to create the
binaural beats, I chose a carrier frequency of 330 hertz (which is between A3 at 220 hertz,
which I felt was too low and A4 440 hertz, which I felt was too high) and decided that in
order to improve the likelihood of finding an effect that the binaural beats would not be static.
Rather, they would perform 4 second gyrations over a 4 hertz frequency around the carrier
frequency. Thus, a binaural beat of 330-334 hertz would contain both the carrier frequency
(in the right ear) and an oscillating frequency in the left ear (332-336 hertz). In order to
produce, edit and normalise these sounds to their desired length, volume level and duration, I
used the audio editor Reaper (http://www.cockos.com/reaper/). This is an open source audio
editor with capabilities which match professional audio editors such as Logic, Pro Tools or
Cubase. Reaper allowed me to make sure that no one stimuli stood out against any of the
others in order to ensure internal validity over all conditions. It also allowed me to create the
monaural stimuli by simulating the effects of the binaural beats using sound processing and
audio engineering tools. To create the ‘mock’ binaural beats, I created two of the binaural
tracks and fed them through both ears simultaneously in order to create the illusion that they
were genuinely binaural whilst they were, in reality monaural. The only way for participants
to identify whether the stimuli were binaural or not would be to listen to only one speaker or
headphone which was forbidden during any part of the experimental procedure. The three
control conditions were music, silence and white noise. These were created using the first
three minutes of Mozart K448: Sonata for two pianos (movement one) – Allegro con Spirito,
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
recorded silence for a three minute duration and an online white noise generator
(http://simplynoise.com/). White noise was used as opposed to ‘brown’ or ‘pink’ noise as it
covers all of the possible frequency ranges at equal power and is, therefore, the reciprocal of
the silent condition (Oxford English Dictionary Online, 2013).
The experimental equipment was partly provided by Goldsmiths and partly provided
from my own funds. The experimental software (timing and randomisation of stimuli), tanks,
electronics (air pressure button) and pump system were kindly designed and provided by
Robert Davies, Systems Developer at Goldsmiths College. This consisted of a small piece of
software (written in the programming
language C) which recorded the duration
of depression of the button at the bottom
of the tank, randomised the stimuli for
each participant (without repetition) and
recorded the data in a .dat file for later
analysis. Also provided were the two
tanks; one for the cold water (fig. 3) with
a separate ice chamber with a pump at the
bottom feeding water to the surface of
the tank and another which was for
warm water (fig. 4) to aid the recovery
of participants’ arms. In addition to
this, I provided four digital aquatic
thermometers (two for each tank –
20
Figure 2: Depiction of the ice tank complete with ice chamber, circulatory pump, surface and depth thermometers and air compression button.
Figure 3: Depiction of the warm water tank with surface and depth thermometers.
Figure 7: Blood pressure monitor used throughout experiment
Binaural Beat Study Music, Mind and Brain Goldsmiths College
surface and depth) in order to account for changes in temperature between the surface and the
bottom of the tank,
(fig. 4 and fig. 5), headphones (- fig. 6, Sennheiser HD 202 Closed Back On-ear Stereo
Headphones), ‘Pure’ distilled water ice (average of two kilograms per
participant – sourced from the supermarket Iceland) a combined blood
pressure and heart rate monitor (fig. 8) (Omron M2 Basic Blood Pressure
Monitor) along with the ambient monitoring equipment (for analysing ambient temperature,
humidity fig. 7) and sound levels – monitored using a Samsung Galaxy S3).
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Figure 4: Depiction of the two cold tank thermometers. Figure 5: Depiction of the two warm tank thermometers
Figure 6: Sennheiser HD 202 Closed Back On-ear Stereo Headphones used throughout the experiment
Figure 8: The temperature and humidity monitor used throughout the experiment
Binaural Beat Study Music, Mind and Brain Goldsmiths College
In addition to this equipment, three questionnaires were used to screen participants
prior to the testing phase of the experiment. This was done so that the results were not
affected by the experiment itself with the questionnaires always being administered in a
‘neutral’ environment outside of the experiment laboratory. These were the self-report
questionnaire from the Goldsmiths Musical Sophistication Index (Gold MSI) (Goldsmiths,
University of London, 2013), Body Vigilance Scale (BVS) (appendix B) and a Zung General
Anxiety Rating Scale (appendix B). All three took the form of a self-administered
questionnaire and were to be taken in any order that the participant wanted as they are all
independent. The Gold MSI assessed a participant’s musical sophistication using thirty-six
Likert-scale responses between ‘1’ (strongly disagree) to ‘7’ (strongly agree) taking into
account their listening habits along with any musical training they be currently undergoing or
had previously achieved (Müllensiefen, 2012). The body vigilance scale is a measure
designed to assess a participant’s conscious attendance to internal cues (such as heart
palpitations etc.). The scale utilized eighteen questions rated between one and ten as to how
much a participant worried about each of a number of bodily sensations providing a
maximum score of one-hundred and eighty with a minimum score of eighteen (Olatunji,
Deacon, Abramowitz, & Valentiner, 2007). The Zung Anxiety Rating Scale was previously
explained in the introduction on page: 10. It provided a rating of general anxiety out of one
hundred (Zung, 1971; Zung, 1974).
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Procedure
Participants filled in a form at www.bbstudy.co.uk requesting their desire to
participate in the experiment. PB liaised with the participant for a suitable date and time of
participation which was confirmed with the participant. Participants arrived at the Ben
Pimlott Building at the date and time of their experimental session. Participants were asked to
read an information sheet (appendix C) which detailed what the experiment was about, how
many conditions there would be, and what they were expected to do during the study. They
were asked to complete a disclosure form indicated that they consented and understood what
was expected of them and how the study would operate henceforth. Participants were then
asked to complete three questionnaires; an anxiety rating scale (appendix B), body vigilance
scale (appendix B) and the GOLD-MSI prior to being shown to the experiment room. On
completion of these questionnaires, the nature of the experiment was verbally explained to
them in full, and they were asked if they had any further questions not explained thus far.
Once in the experiment room, the participant’s blood pressure and heart rate were measured
in their left arm which represented their resting blood pressure and heart rate. This was
recorded on the experiment form. The participants were then asked to wear headphones and
were performed a short test track (five to ten seconds of Mozart K448) in order to ensure they
knew what to expect in terms of volume. The participants were then asked to place their left
arm in the water (keeping the blood pressure equipment on their upper arm) and depress the
button at the bottom of the tank. Once their arm entered the water, the experimenter pressed
an ‘OK’ button on the computer. This activated a computerised timer with the stimuli
performed as soon as the button at the bottom of the tank was depressed. The participants
kept their arm in the water for as long as possible without causing significant discomfort. As
soon as a participant withdrew their hand – either because the condition had ended or they
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had reached their pain tolerance limit, they dried their arm on a towel and had their blood
pressure and heart rate taken as soon as possible. This was repeated for all nine conditions,
using alternating arms with the blood pressure and heart rate equipment always on the arm
which had been submerged in the tank. In order to ensure internal validity, a number of
measures were taken to ensure that sufficient recovery time and counterbalancing took place
across participants on all conditions. All conditions were randomised in order to account for
any fatigue effects across all participants. Both arms were also used throughout the
experiment, in an alternating fashion in order to account for any effects of handedness and to
reduce fatigue effects. This procedure also allowed the cooled arm from a previous trail to
recover to room temperature before the commencement of a subsequent condition. The
experiment took place in the same room and the same environment across all participants and
for all conditions. Furthermore, both the ambient room temperature and ambient noise level
were controlled for (via air conditioning and constant monitoring of extraneous noise levels
using a decibel meter application on a Samsung Galaxy S3 smartphone).
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Results
Firstly, the data was normalised in order to compare each participant against their own
performance using the formula (X−M )
S where X is the actual data point, M is the mean of all
nine data points and S is the standard deviation of all nine data points. Then this entire data
set was deemed to be normal using the Shapiro-Wilkes measure of normality (Table 2).
Table 2: Descriptive Statistics of Normalised Data for all reaction time conditions
Tests of Normality for all normalised Reaction Time Scores
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
BB_4 .057 51 .200* .990 51 .950BB_8 .082 51 .200* .979 51 .490BB_14 .111 51 .167 .962 51 .098MB_4 .118 51 .073 .962 51 .100MB_8 .109 51 .178 .969 51 .201MB_14 .151 51 .005 .959 51 .079Music .108 51 .190 .962 51 .106Silence .094 51 .200* .974 51 .327White Noise .099 51 .200* .975 51 .346
a. Lilliefors Significance Correction
*. This is a lower bound of the true significance.
Reaction Times
Sound against Silence
The raw score reaction time data is shown below (fig. 11) for all nine conditions. For
each condition, 95% confidence intervals are also identified. This graph uses raw data.
Descriptive statistics (Table 3) and normality plots are shown below (Table 4). All the data at
this stage is significantly non-normal due it being the raw data and, therefore, not normalised
to account for each participant’s individual performance as judged against themselves.
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Figure 9: A Comparison of means across all raw reaction time conditions showing a main effect for the music condition.
Table 3: Descriptive statistics for raw score reaction time conditions.
Descriptive Statistics for Raw Score Reaction Times
N Range Minimum Maximum Mean Std. Deviation
BB4 51 183.47 5.38 188.85 46.91 48.48BB8 51 186.33 5.53 191.87 51.6 54.93BB14 51 199.41 8.38 207.79 44.15 46.97MB4 51 183.83 7.37 191.19 51.3 53.33MB8 51 189.50 6.33 195.83 50.33 49.29MB14 51 187.30 6.30 193.60 52.88 57.18Music 51 194.87 6.94 201.81 60.71 60.11Silence 51 199.31 1.37 200.68 44.21 48.2White Noise 51 183.73 2.94 186.67 44.75 49.86
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Table 4: Normality tests for non-normalised reaction time data.
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
BB4 .212 51 .000 .711 51 .000BB8 .237 51 .000 .726 51 .000BB14 .276 51 .000 .673 51 .000MB4 .289 51 .000 .718 51 .000MB8 .251 51 .000 .790 51 .000MB14 .286 51 .000 .711 51 .000Music .232 51 .000 .762 51 .000Silence .276 51 .000 .755 51 .000White Noise .263 51 .000 .704 51 .000
a. Lilliefors Significance Correction
Now examining the normalised data, three ANOVA were used in order to determine
the overall effect of condition. The first was a 9 way ANOVA which accounted for all
experimental conditions and produced a main effect for the presence or absence of a sound in
total reaction time duration. Mauchly’s test indicated that the assumption of Sphericity had
not been violated, X2 (35) = 33.108, p > .05, therefore, there was no need to correct the
degrees of freedom. The results show that the reaction times of participants were significantly
affected by the presence or absence of sound F (8,400) = 2.97, p = .003. This resulted in a
moderate effect size of r = .19. Bonferroni post-hoc tests for pairwise comparisons revealed
no significant main effects between any of the conditions on both the normalised and non-
normalised data sets (all > .05) (see appendix A). The graph below (fig. 12) depicts the
difference in means between the different conditions using the normalised data set followed
by descriptive statistics (Table 5). Normality plots were shown in table 2.
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Figure 10: Depiction of means of normalised reaction time data showing a main effect for the Music condition.
Table 5: Descriptive Statistics for normalised reaction time scores.
Descriptive Statistics for normalised scores
MeanStd.
Deviation N
BB_4 -.09080 .7457 51BB_8 .01951 1.0407 51BB_14 -.05778 .7576 51MB_4 .01875 .8585 51MB_8 .18206 .8076 51MB_14 .11565 .8535 51Music .43520 1.1654 51Silence -.37063 1.0782 51White Noise -.25186 .9224 51
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Binaural Beats against Monaural Beats
A 3 X 2 ANOVA comparing the binaural beats with the monaural beats produced the
following descriptive statistics as identified in table 6.
Table 6: Descriptive statistics for binaural beats against monaural beats.
1. Binaural against MonauralMeasure: Binaural Beats against Monaural Beats (all values in seconds).
Binaural/Monaural Mean Std. Error
95% Confidence Interval
Lower Bound Upper Bound
Binaural Beat 47.552 6.590 34.316 60.788Monaural Beat 51.486 6.767 37.895 65.077
Table 7: Descriptive statistics for beat frequency.
2. FrequencyMeasure: Frequency timings (all values in seconds).
Frequency Mean Std. Error
95% Confidence Interval
Lower Bound Upper Bound
4 Hertz 49.083 6.538 35.952 62.2148 Hertz 50.961 6.848 37.206 64.71714 Hertz 48.512 7.089 34.272 62.751
The assumption of Sphericity had not been violated,x2=(2 )=0.71, p>.05. However
the results of a 3 x 2 ANOVA demonstrate that there is no significant main effect for binaural
beats against monaural beats (p < .05). Furthermore, there is no significant effect or
interaction for beat frequency (p < .05).
Control Conditions (Music, Silence and White Noise)
A 3 X 1 ANOVA of the three control conditions (Music, Silence and White Noise)
produced the following descriptive data (Table 8). A comparison of means, along with 95%
confidence intervals can be seen in Figure 13.
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Table 8: Descriptive statistics for control conditions (Music, Silence and White Noise).
Estimate Marginal MeansMeasure: Reaction time durations for the control conditions (all values in seconds).
Control Condition Mean Std. Error
95% Confidence Interval
Lower Bound Upper Bound
Music 60.708 8.418 43.801 77.615Silence 44.213 6.749 30.657 57.769White Noise 44.748 6.982 30.725 58.771
Figure 11: Comparison of reaction time means across control conditions showing a main effect of Music.
Mauchly’s test indicated that the assumption of Sphericity had been violated,
x2 (2 )=32.152 , p<.05, therefore degrees of freedom were corrected using the Greenhouse-
Geisser estimates of Sphericity (ε=.675). The results show a main effect for condition F (2,
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100) = 7.36, p < .001), due to the larger mean of the music condition. Bonferroni post-hoc
tests (Table 9) revealed no significant difference between the three conditions (p < .05).
Table 9: Pairwise comparison of control conditions showing a main effect of Music against Silence and White Noise.
Pairwise ComparisonsMeasure:MEASURE_1
(I) Control (J) Control
Mean Difference
(I-J)Std.
Error Sig.a
95% Confidence Interval for Differencea
Lower Bound Upper Bound
Music Silence 16.495 7.553 .101 -2.215 35.205
White Noise 15.960 7.890 .145 -3.586 35.506
Silence Music -16.495 7.553 .101 -35.205 2.215
White Noise -.535 3.706 1.000 -9.715 8.645
White Noise Music -15.960 7.890 .145 -35.506 3.586
Silence .535 3.706 1.000 -8.645 9.715
Based on estimated marginal means
a. Adjustment for multiple comparisons: Bonferroni.
Subjective Measures
Here is an examination of the subjective measures which were provided by the
participants as to how much they ‘liked the sound’ and felt it ‘helped them cope with the
discomfort’. Descriptive statistics are shown for the liking measures (Table 10) along with
estimates of marginal means (Table 11) along with normality tests and a graph depicting the
difference in means graphically (fig. 14). Furthermore, normality tests are provided for both
the liking and the pain reduction scores for each condition (.
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Liking
Table 10: Descriptive Statistics for subjective measures of Liking
Descriptive Statistics for Liking
MeanStd.
Deviation N
BB4 5.00 1.980 51BB8 5.04 2.126 51BB14 4.67 2.188 51MB4 5.25 2.087 51MB8 4.75 1.937 51MB14 4.43 2.013 51Music 7.51 2.043 51Silence 3.04 2.457 51
Table 11: Estimated means for subjective measures of Liking
EstimatesMeasure:MEASURE_1
Condition Mean Std. Error
95% Confidence Interval
Lower Bound Upper Bound
1 (BB4) 5.000 .277 4.443 5.5572 (BB8) 5.039 .298 4.441 5.6373 (BB14) 4.667 .306 4.051 5.2824 (MB4) 5.255 .292 4.668 5.8425 (MB8) 4.745 .271 4.200 5.2906 (MB14) 4.431 .282 3.865 4.9977 (Music) 7.510 .286 6.935 8.0848 (Silence) 3.039 .344 2.348 3.7309 (White Noise) 3.471 .327 2.814 4.127
Table 12: Normality test for Liking data (non-normalised).
Tests of Normality (Non-Normalised Data)
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig.
Statistic df Sig.
BB4 .127 51 .038 .944 51 .019BB8 .140 51 .014 .933 51 .007BB14 .121 51 .060 .936 51 .008
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MB4 .132 51 .027 .939 51 .011MB8 .154 51 .004 .961 51 .093MB14 .134 51 .023 .948 51 .025Music .186 51 .000 .895 51 .000Silence .232 51 .000 .810 51 .000White Noise .168 51 .001 .884 51 .000
a. Lilliefors Significance Correction
Table 13: Normality tests of Liking for normalised data.
Tests of Normality for Liking (Normalised Data)
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig.
Statistic df Sig.
BB4 .062 51 .200* .988 51 .880BB8 .080 51 .200* .962 51 .104BB14 .076 51 .200* .973 51 .288MB4 .064 51 .200* .995 51 .999MB8 .109 51 .178 .969 51 .201MB8 .080 51 .200* .988 51 .895MB14 .087 51 .200* .976 51 .376Music .166 51 .001 .892 51 .000Silence .212 51 .000 .832 51 .000White Noise .062 51 .200* .975 51 .354
a. Lilliefors Significance Correction
*. This is a lower bound of the true significance.
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Figure 12: Comparison of mean liking data across all conditions showing a main effect for the Music condition/
The results indicated a main effect of liking against condition F (8, 400) = 22.14, p
< .001. A pairwise comparison analysis indicated further significant main effects for
condition which can be seen in Table 12. Non-significant comparisons can be seen in
appendix A (page 66).
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Table 14: Pairwise comparisons for all Liking data according to condition (only significant main effects shown).
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Pain Reduction
Participants responses as to how much they felt each experimental condition helped
them to deal with the discomfort are shown below. Normality plots for both the normalised
(table 16) and non-normalised (table 15) are shown, along with descriptive statistics (table
17) and estimates of means (table 18). Furthermore, a graph is provided to demonstrate the
effects of each condition according to its mean (fig. 15) with a Bonferroni-corrected pairwise
comparison analysis to demonstrate significant main effects. A table of non-significant
relationships can be seen in appendix A (page 66).
Table 15: Normality tests for measures of pain reduction (Non-Normalised).
Tests of Normality for measures of Pain Reduction (Non-Normalised)
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
BB4 .179 51 .000 .928 51 .004BB8 .144 51 .010 .931 51 .006BB14 .182 51 .000 .908 51 .001MB4 .154 51 .004 .940 51 .013MB8 .116 51 .084 .947 51 .024MB14 .192 51 .000 .907 51 .001Music .181 51 .000 .936 51 .008Silence .353 51 .000 .665 51 .000White Noise .239 51 .000 .830 51 .000
a. Lilliefors Significance Correction
Table 16: Normality tests for pain reduction (normalised data).
Tests of Normality for Pain Reduction (Normalised Data)
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
BB4 .063 51 .200* .985 51 .759BB8 .109 51 .182 .968 51 .174BB14 .102 51 .200* .949 51 .028MB4 .101 51 .200* .957 51 .062
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MB8 .094 51 .200* .974 51 .325MB14 .167 51 .001 .894 51 .000Music .157 51 .003 .911 51 .001Silence .241 51 .000 .789 51 .000White Noise .138 51 .016 .942 51 .015
a. Lilliefors Significance Correction
*. This is a lower bound of the true significance.
Table 17: Descriptive statistics for subjective measures of pain reduction.
Descriptive Statistics for Pain Reduction
MeanStd.
Deviation N
BB4 4.29 2.119 51BB8 4.51 2.693 51BB14 4.04 2.236 51MB4 4.24 2.320 51MB8 4.06 2.204 51MB14 3.71 2.239 51Music 5.80 2.706 51Silence 2.29 2.157 51White Noise 3.06 2.370 51
Table 18: Mean estimates for subjective measures of pain reduction.
EstimatesMeasure: Pain Reduction according to condition.
Condition Mean Std. Error
95% Confidence Interval
Lower Bound Upper Bound
1 (BB4) 4.294 .297 3.698 4.8902 (BB8) 4.510 .377 3.752 5.2673 (BB14) 4.039 .313 3.410 4.6684 (MB4) 4.235 .325 3.583 4.8885 (MB8) 4.059 .309 3.439 4.6796 (MB14) 3.706 .313 3.076 4.3367 (Music) 5.804 .379 5.043 6.5658 (Silence) 2.294 .302 1.688 2.9019 (White Noise). 3.059 .332 2.392 3.725
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Figure 13: Comparison of means for subjective measures of pain reduction across all conditions showing a main effect of Music with silence being significantly the ‘worst’ condition against all other conditions.
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Table 19: Pairwise Comparisons for subjective measures of pain reduction demonstrating a host of significant differences, in particular for the control conditions of Music and White Noise.
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Effect of Participant Data
Across all reaction time conditions, there was a main effect of gender with female
participants outperforming male participants t = 3.52, p = .001. There was no significant
correlation for the effect of age against reaction time (p > .05).
Table 20: Descriptive statistics for gender showing a significant difference of means according to mean reaction time.
Descriptive Statistics (in Seconds)
Mean NStd.
DeviationStd. Error
Mean
Pair 1 Male RT 42.12 25 47.5 3.166
Female RT 57.20 26 55.16 3.702
Figure 14: Mean reaction time against Gender
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Subjective Measure Correlations
The subjective ratings of the participants for how much they liked the sound and felt it
contributed towards pain reduction were all positively correlated and highly significant.
These scores were pooled across all conditions and all participants’ reaction times.
Furthermore, they were highly correlated with one another indicating that liking accounts for
increased subjective comfort.
Figure 17 plots the pain threshold rating (reaction time) for all conditions against the
liking rating supplied by the participants producing a moderate and highly significant
correlation coefficient (r = .42, p < .001). Therefore, the higher the participant liked a sound,
the more likely they were to leave their arm in the water.
Figure 15: Correlation figure of r .42 for pain threshold against liking rating (pooled across all participants and all conditions) showing a significant effect for liking in improving reaction time duration.
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Pain reduction against pain threshold.
Pain threshold (Reaction Times) against Pain Reduction Rating were also moderately
positively correlated (r = .53, p < .001). Therefore, the higher a participant scored the pain
reduction rating the longer their arm remained in the water.
Figure 16: Correlation figure of r = .53 for pain threshold against pain reduction rating (polled across all participants and conditions) indicating that participants who rated a condition as ‘less painful’ showed increased reaction time scores.
Pain Reduction rating against Liking.
Both the pain reduction rating and liking ratings are highly correlated (r = .70, p
< .000) meaning that participants who liked a sound also believed it to be beneficial towards
reducing their perception of the cold pain stimulus.
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Figure 17: Correlation figure of r = .70 for pain reduction rating again liking rating (pooled across all participants and all conditions) indicating that the two measures of liking and pain reduction rating are highly correlated.
In order to determine if these correlations are significantly different from one another,
Stiger’s test (also known as William’s test) was performed to identify the strength of the
relationship between these correlations (Fig 20). All correlation relationships were highly
significantly different from each other (p < .002).
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Hotelling William’s and Steigers Z test for correlation relationships.Measure: Correlations
Correlations t ZMean
DifferenceStd.
Error Sig.a
95% Confidence Interval for Differencea
Lower Bound
Upper Bound
0.7 – 0.526 4.944 4.871 0.174 27.079 .000 0.1016 0.2464
0.7 – 0.423 8.353 7.93 0.277 27.249 .000 -0.2051 0.3489
0.526 – 0.423 3.339 3.302 0.103 31.609 .001 0.041 0.165
Figure 18: Significance test of correlations of subjective measures (Liking, Pain Reduction and Reaction Time) showing a strong significant difference between the correlations of subjective measures.
Questionnaire Scores
The Anxiety rating showed a significant (p = .025) correlation of r = -.314 against reaction
time.
Table 21: Descriptive Statistics for Anxiety against mean reaction time (in seconds)
Descriptive Statistics for Anxiety against Mean RT
Mean Std. Deviation N
Anxiety Scale 41.35 9.169 51Mean RT 49.6424 45.07728 51
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Figure 19: A correlation figure of Zung general anxiety rating against mean reaction time demonstrating that the higher a participants initial anxiety score, the less their mean reaction times were across all conditions.
This indicated that participants with a lower anxiety rating at the beginning of the
experiment were able to perform longer than those with higher initial anxiety ratings. There
not have any extremely high anxiety scores (Lower bound: 28, Upper bound: 61, Range = 33)
so to perform a median split of the data seemed inappropriate. Instead, an analysis over time
was conducted in order to examine if participants anxiety reduced over the course of the
experiment. The results (fig. 22) show that there is a significant difference between the first
two blocks and the last two blocks according to their mean reaction time, t = 3.1, p = .003.
Furthermore, there is a significant effect of Anxiety score as a between subjects factor F (1,
26) = 4.91, p > .05.
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Figure 20: Comparison of first and last conditions of the experiment according to mean reaction time.
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 First two blocks 41.4252 51 42.49068 5.94988
Final two blocks 55.0580 51 49.98071 6.99870
Furthermore, the scores were blocks were highly correlated with one another, r = .78, p
< .000) as shown in figure 23.
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Figure 21: Comparison of blocks examining correlation. They are highly correlated showing that participants show a maintained performance across all nine trials.
Gold MSI
The level of Musical Sophistication from the Goldsmiths Musical Sophistication
Index showed a significant correlation with reaction time scores. Although this score did not
correlate significantly with any of the individual conditions. Performing a median (63) split
on the data produced twenty-five ‘low’ scoring musicians and twenty six ‘high’ scoring
musicians. A paired samples t-test was conducted to compare the Gold-MSI to mean reaction
time values. There was a significant difference in the reaction times of the high Gold-MSI
group (M = 78.34, SD = 10.15) and the scores for the low Gold-MSI group (M = 49.48, SD =
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9.08); t = (11.024), p < .001. Performing a 3 x 2 x 2 repeated measures ANOVA with Gold-
MSI as a between-subjects factor produced no significant effect across conditions.
Furthermore, conducting a 3 x 1 x 2 ANOVA with the Gold-MSI as a between-subjects factor
produced no significant effect either.
Table 22: Normality tests for Goldsmiths Musical Sophistication Index (Gold-MSI) scores
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
Low GMSI .146 25 .180 .923 25 .059High GMSI .134 25 .928 25 .079
a. Lilliefors Significance Correction
*. This is a lower bound of the true significance.
Table 23: Descriptive statistics for Goldsmiths Musical Sophistication Index (Gold-MSI) scores.
Descriptive Statistics for Goldsmiths Musical Sophistication Index
Mean NStd.
Deviation Std. Error Mean
Pair 1 Low GMSI 49.4800 25 9.08350 1.81670
High GMSI 78.3400 25 10.15373 2.03075
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Figure 22: Median spilt of Gold-MSI data against mean reaction time.
Body Vigilance Scale
Performing a median split on the data from the Body Vigilance Scale showed no
significant effect for reaction times across any condition.
Table 24: Descriptive statistics for BVS scores after a median split.
Mean Reaction Time
Median Spilt/BVS Mean N Std. Deviation
0 52.1046 27 40.720731 46.8723 24 50.27644Total 49.6424 51 45.07728
Furthermore, this score did not significantly correlate with any of the individual conditions.
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Biological Measures
Heart Rate
A participant’s heart rate measure showed no significant effect against their individual
reaction time. However, the difference in the mean heart rate compared to the resting heart
rate was significant t = 2.48, (p < .05). A 9 way ANOVA across all conditions showed a
significant main effect of F (1, 50) = 6.56, p = .013. Bonferroni post-hoc comparisons
showed no significant effect of condition across any condition.
Table 25: Descriptive statistics for measures of heart rate.
Descriptive Statistics
MeanStd.
Deviation N
BB4 69.49 11.914 51BB8 69.12 10.897 51BB14 69.24 11.155 51MB4 69.43 10.847 51MB8 69.25 11.061 51MB14 69.80 11.908 51Music 70.39 11.973 51Silence 71.41 11.897 51White Noise 69.86 11.407 51
Table 26: Normality tests for heart rate
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
BB4 .136 51 .020 .965 51 .133BB8 .145 51 .009 .944 51 .019BB14 .139 51 .015 .968 51 .181MB4 .108 51 .197 .978 51 .450MB8 .088 51 .200* .984 51 .738MB14 .062 51 .200* .991 51 .959Music .102 51 .200* .962 51 .101Silence .088 51 .200* .980 51 .528White Noise .099 51 .200* .982 51 .644RHR .132 51 .027 .968 51 .182
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a. Lilliefors Significance Correction
*. This is a lower bound of the true significance.
Figure 23: A 9 Way ANOVA of mean heart rate against experimental condition.
Blood Pressure Measures
A participant’s blood pressure was not significantly raised during the experiment. No
significant effect could be found from a nine way ANOVA according to condition for the
blood pressure measurement.
Stimuli Detection
The responses from participants being asked to identify whether a given stimuli had
been binaural or not were converted into a binary response of 1 (hit), 0 (false alarm). Z scores
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
were then generated from this data for each participant and converted into D’ scores (Zhit –
Zfalse alarm). These D’ scores were then averaged across all participants to generate an
average D’ score of -0.000002. Combining the median split Gold-MSI data with the detection
rate, musicians showed a higher D’ score mean than the non-musicians. Non-musicians
demonstrated a D’ score close to zero (0.03), whereas musicians were higher with 0.173.
However, this was not a significant difference (p = .088).
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
Discussion
The results paint a somewhat disappointing picture for the application of binaural
beats in improving cold pain endurance. In refutation to my stated hypothesis, no effect could
be found for the application of binaural beats against monaural beats with the binaural beats
performing worse (although not significantly) than the monaural conditions (fig. 9). The most
effective condition was music (fig. 11) which was also reflected by the liking (fig. 12) and
pain reduction scores (fig, 13). Likewise, the least effective condition was silence with white
noise performing a little better (although, only slightly). Furthermore, no effect of frequency
could be found between either the binaural or monaural conditions (Table 7). The subjective
ratings of liking and pain reduction were highly correlated with the reaction time scores
indicating that a participant’s reaction time performance may be due to how much a
participant likes a sound rather than any other quality or mechanism for influencing pain
endurance (fig. 17). Thus, the results indicate that it may be subjective liking of a sound
which influences a participant’s willingness to undergo a continued pain experience rather
than any mechanism of entrainment resulting in subjective pain reduction. However, there
seems to be an effect of musical sophistication on cold pain tolerance with participants who
scored highly on the self-rating Gold-MSI questionnaire outperforming those who scored
lower on the test of musical sophistication (fig. 22). Despite this large effect across all
conditions, the effect did not show itself at individual conditions, possibly indicating that the
musical participants were using a different coping strategy to the non-musicians in order to
cope with the pain. This is supported anecdotally with the majority of musical participants
describing their coping mechanism as ‘focusing’ on the sound, whereas non-musical
participants utilised strategies such as counting, deep breathing or staring at objects within the
experiment room. The Body Vigilance Scale scores showed no significance across a median
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
split. Anxiety scores showed a main effect of decreasing reaction time with higher initial
anxiety levels (fig. 19). This is to be expected as participants with higher anxiety may worry
more about the pain and also be expecting more pain (therefore making the experience
subjectively worse) leading to reduced reaction times. Pain is a subjective phenomenon
which is highly affected by the anxiety level of each individual participant as they go through
the painful experience (Sternbach, 1968) (Melzack, 1973) (Grachev, Fredickson, & Apkarian,
2001). Recent findings have found that this exacerbation of pain by anxiety is associated with
activity in the hippocampus and, therefore, highly likely to involve memory (Ploghaus, et al.,
2001). It is therefore true that those who are more anxious after having experienced a painful
experience genuinely feel more pain than those who are less anxious, therefore, highly
anxious participants are more likely to show reduced reaction times. Furthermore, an analysis
of the effects of anxiety over time included comparing the first two conditions (1 and 2,
whatever they may be – they were all randomised) with the last two conditions (8 and 9)
respectively (fig. 20). This demonstrated a main effect of anxiety and was a statistically
significant difference across the two sides of the median spilt (table 24). This demonstrated
that the anxiety measure was accurate across all participants and was an accurate predictor of
success at the reaction time task. Furthermore, these two blocks were highly correlated
indicating that if a participant started with a high reaction time (due to a low anxiety rating),
they tended to keep this high score throughout the remainder of the experiment (fig. 21). This
indicates that the cold pressor technique is a reliable method of detecting and working with a
participant’s pain threshold and tolerance. Participant heart rate and blood pressure
recordings showed mixed results with no main effect for the blood pressure readings but a
main effect of heart rate (fig. 23). This may be due to heart rate being more sensitive than
blood pressure – perhaps not enough of the body was immersed in the water to affect blood
pressure readings significantly.
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
Overall, this study presents an intriguing portrayal of the ability for sound to affect
pain endurance. Unfortunately, despite considerable effort, there were not enough
participants to demonstrate a significant main effect for the binaural beat conditions against
the monaural beats. This may be due to the effect size being extremely small, or it may mean
that the phenomenon is largely based on individual differences and the subjective experience
of listeners. A more likely hypothesis is that participants kept their hand in the water simply
depending on how much they liked, enjoyed or were otherwise being distracted by the sound.
Evidence for this hypothesis is demonstrated by the plot of liking against perceived pain
reduction which showed a strong correlation at a very high significance (fig. 17). The most
‘complex’ sound – Mozart K448 is the condition with the highest mean value followed by the
monaural then binaural beats. Binaural beat phenomena have been shown to be especially
prone to expectation effects and the placebo effect. Therefore, I felt it was necessary to
identify whether participants could tell the difference between the sound of the monaural beat
and the binaural beat. The D’ score of -0.000002 reflects a general inability for participants to
identify the sounds or to differentiate them during the experiment. The slight negative value
demonstrates that there is a slight tendency to report a binaural beat over a monaural beat,
otherwise known as a false positive. This is likely to be because the entire study is called a
‘binaural beat study’ and participants are therefore primed to expect a larger prevalence of
binaural beats rather than monaural ones. This effect exists even though all participants have
been informed that there are exactly three conditions of each (despite this information, some
participants answered ‘binaural beat’ for almost every condition (5/6) whilst no one answered
monaural beat for every condition). Furthermore, musicians are not significantly better at
deciding which stimuli were binaural against which stimuli were monaural, which is not what
I expected. However, I feel that with more statistical power, this would prove to be a
significant result (p = .088). This may mean that musicians show a higher level of confidence
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
in their ability to determine whether a sound is binaural or not. Either that, or musicians can
actually detect differences in the sound that non-musicians cannot detect due to their training,
practice and neural plasticity in a similar way that experienced audio engineers can
differentiate audio equipment. Furthermore, musicians did show an increased ability to
withhold their arm in the cold water for longer than non-musicians. There has been anecdotal
as well as empirical evidence to support the idea that music is a strong tool to use for
motivation (Dwyer, 1995). It is likely that it is this which is fuelling the participants in their
attempts to keep their hand in the water for as long as possible since the Mozart condition is
the only sound which resembles ‘real music’. This may also explain why highly musical
participants seem to be better able to use the musical condition to aid their performance in the
cold water; they may use music for other tasks where motivation is required (such as studying
or writing dissertations) which may mean they have become used to the application of music
to help motivate them. It may also be the case that participants feel the need to listen to the
music for a certain duration due its construction. On more than one occasion (after the
experiment had concluded), musical participants verbally stated that during the music
condition they had felt a strong desire to hold their arm in the water until the next perfect
cadence or other musicological feature which implied closure and had become frustrated
when there did not appear to be many.
The heart rate and blood pressure recordings were attempting to find unconscious
preferences for a sound condition. The high mean heart rate (fig. 23) for the silent condition
reflects the unconscious anxiety experienced by participants as they possibly felt they needed
to work harder to keep their arm in the water. Unfortunately, this effect did not show in the
blood pressure readings. Throughout all of the trials, the 8 hertz condition has shown to be
the most likely frequency to demonstrate an eventual effect with enough participants,
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
however, in the analysis, this relationship proved to be non-significant. No effect was found
for a correlation analysis of pain tolerance against a participant’s age.
In terms of improving this study, it may have been beneficial to screen participants
based on their most painful experience (e.g. broken bones, childbirth) as it is widely believed
that experiences such as these, or at least regular exposure to moderate to severe pain may
increase pain tolerance (Woolf & Salter, 2000). This would ensure that participants with an
unusually high pain tolerance were not given an unfair advantage over other participants who
may have an average pain tolerance. Furthermore, it may have been beneficial to control for
the effects of the menstrual cycle for female participants as it has been demonstrated in many
studies that pain tolerance, perception and endurance along with body temperature can
seriously fluctuate during this time (Riley, Robinson, Emily, & Price, 1999). However, in a
recently published study, examining the effects of noxious stimuli such as the cold pressor
technique, no effect of the menstrual cycle was found across pain stimuli (Thompson, Keogh,
French, & Davis, 2008). However, I was presented with a lot of anecdotal evidence from my
female participants during the experiment who were surprised I that had not been controlling
for the effect of hormonal and psychological changes during menstruation.
In order to ensure that there is no brainwave entrainment possibility for this effect, it
would have been necessary to collect EEG data from these fifty-one participants. Therefore, I
cannot out rule the hypothesis of brainwave entrainment entirely, and conclude that these
effects are entirely down to how much the participants liked or enjoyed the sounds. I can only
point out that this hypothesis is unlikely, given the results of this experiment.
In conclusion, it appears that there is no overall main effect for binaural beats either
against monaural beats, music, silence or white noise. However, a number of significant
effects were found for Anxiety, Gold-MSI against reaction time in addition to a main effect
of Music, for reducing the perceived pain or otherwise increasing pain endurance, especially
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Binaural Beat Study Music, Mind and Brain Goldsmiths College
in musicians. It seems increasingly likely that participants were influenced by their liking for
the sound, as opposed to any brainwave entrainment or other binaural beat mechanism
contributing or influencing their performance.
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Appendix A: Non-significant DataPairwise ComparisonsMeasure: Reaction time by condition (Normalised Data).
(I) Condition
(J) Condition
Mean Difference
(I-J) Std. Error Sig.a
95% Confidence Interval for Differencea
Lower Bound
Upper Bound
1 2 -.110 .184 1.000 -.733 .513
3 -.033 .147 1.000 -.529 .463
4 -.110 .165 1.000 -.670 .451
5 -.273 .164 1.000 -.827 .282
6 -.206 .170 1.000 -.783 .370
7 -.526 .207 .510 -1.227 .175
8 .280 .196 1.000 -.384 .944
9 .161 .171 1.000 -.419 .741
2 1 .110 .184 1.000 -.513 .733
3 .077 .188 1.000 -.558 .713
4 .001 .209 1.000 -.707 .709
5 -.163 .192 1.000 -.812 .487
6 -.096 .210 1.000 -.807 .615
7 -.416 .233 1.000 -1.206 .375
8 .390 .236 1.000 -.408 1.188
9 .271 .196 1.000 -.393 .936
3 1 .033 .147 1.000 -.463 .529
2 -.077 .188 1.000 -.713 .558
4 -.077 .159 1.000 -.614 .461
5 -.240 .150 1.000 -.749 .269
6 -.173 .159 1.000 -.711 .364
7 -.493 .211 .836 -1.206 .220
8 .313 .204 1.000 -.378 1.004
9 .194 .191 1.000 -.454 .842
4 1 .110 .165 1.000 -.451 .670
2 -.001 .209 1.000 -.709 .707
3 .077 .159 1.000 -.461 .614
5 -.163 .177 1.000 -.763 .436
6 -.097 .173 1.000 -.683 .489
7 -.416 .212 1.000 -1.133 .300
8 .389 .214 1.000 -.336 1.115
9 .271 .181 1.000 -.343 .884
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5 1 .273 .164 1.000 -.282 .827
2 .163 .192 1.000 -.487 .812
3 .240 .150 1.000 -.269 .749
4 .163 .177 1.000 -.436 .763
6 .066 .182 1.000 -.548 .681
7 -.253 .222 1.000 -1.006 .500
8 .553 .184 .148 -.069 1.175
9 .434 .180 .705 -.175 1.043
6 1 .206 .170 1.000 -.370 .783
2 .096 .210 1.000 -.615 .807
3 .173 .159 1.000 -.364 .711
4 .097 .173 1.000 -.489 .683
5 -.066 .182 1.000 -.681 .548
7 -.320 .204 1.000 -1.011 .372
8 .486 .205 .775 -.208 1.180
9 .368 .186 1.000 -.263 .998
7 1 .526 .207 .510 -.175 1.227
2 .416 .233 1.000 -.375 1.206
3 .493 .211 .836 -.220 1.206
4 .416 .212 1.000 -.300 1.133
5 .253 .222 1.000 -.500 1.006
6 .320 .204 1.000 -.372 1.011
8 .806 .240 .054 -.006 1.618
9 .687 .236 .190 -.111 1.485
8 1 -.280 .196 1.000 -.944 .384
2 -.390 .236 1.000 -1.188 .408
3 -.313 .204 1.000 -1.004 .378
4 -.389 .214 1.000 -1.115 .336
5 -.553 .184 .148 -1.175 .069
6 -.486 .205 .775 -1.180 .208
7 -.806 .240 .054 -1.618 .006
9 -.119 .203 1.000 -.806 .569
9 1 -.161 .171 1.000 -.741 .419
2 -.271 .196 1.000 -.936 .393
3 -.194 .191 1.000 -.842 .454
4 -.271 .181 1.000 -.884 .343
5 -.434 .180 .705 -1.043 .175
6 -.368 .186 1.000 -.998 .263
7 -.687 .236 .190 -1.485 .111
8 .119 .203 1.000 -.569 .806
Based on estimated marginal means
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a. Adjustment for multiple comparisons: Bonferroni.Figure 24: Pairwise comparisons for reaction time data
Pairwise ComparisonsMeasure: Reaction Time by Condition (non-normalised). (In seconds).
(I) Condition
(J) Condition
Mean Difference
(I-J) Std. Error Sig.a
95% Confidence Interval for Differencea
Lower Bound
Upper Bound
1 2 -4.683 5.006 1.000 -21.633 12.267
3 2.764 2.567 1.000 -5.927 11.455
4 -4.342 5.722 1.000 -23.716 15.032
5 -3.415 4.925 1.000 -20.090 13.259
6 -5.964 4.235 1.000 -20.302 8.375
7 -13.796 6.495 1.000 -35.788 8.196
8 2.699 5.090 1.000 -14.535 19.933
9 2.164 4.386 1.000 -12.687 17.014
2 1 4.683 5.006 1.000 -12.267 21.633
3 7.448 4.798 1.000 -8.797 23.692
4 .342 6.367 1.000 -21.218 21.901
5 1.268 5.097 1.000 -15.989 18.524
6 -1.280 5.379 1.000 -19.492 16.931
7 -9.113 7.175 1.000 -33.408 15.182
8 7.382 5.604 1.000 -11.592 26.356
9 6.847 5.045 1.000 -10.233 23.927
3 1 -2.764 2.567 1.000 -11.455 5.927
2 -7.448 4.798 1.000 -23.692 8.797
4 -7.106 5.936 1.000 -27.204 12.991
5 -6.180 4.540 1.000 -21.553 9.193
6 -8.728 3.705 .808 -21.271 3.815
7 -16.561 6.425 .466 -38.313 5.192
8 -.066 5.025 1.000 -17.079 16.948
9 -.601 4.386 1.000 -15.452 14.251
4 1 4.342 5.722 1.000 -15.032 23.716
2 -.342 6.367 1.000 -21.901 21.218
3 7.106 5.936 1.000 -12.991 27.204
5 .926 5.002 1.000 -16.011 17.863
6 -1.622 6.378 1.000 -23.217 19.973
7 -9.454 7.753 1.000 -35.705 16.797
8 7.041 5.660 1.000 -12.123 26.204
9 6.506 5.860 1.000 -13.336 26.348
5 1 3.415 4.925 1.000 -13.259 20.090
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2 -1.268 5.097 1.000 -18.524 15.989
3 6.180 4.540 1.000 -9.193 21.553
4 -.926 5.002 1.000 -17.863 16.011
6 -2.548 4.977 1.000 -19.399 14.303
7 -10.381 7.005 1.000 -34.100 13.339
8 6.114 4.534 1.000 -9.239 21.467
9 5.579 3.996 1.000 -7.951 19.110
6 1 5.964 4.235 1.000 -8.375 20.302
2 1.280 5.379 1.000 -16.931 19.492
3 8.728 3.705 .808 -3.815 21.271
4 1.622 6.378 1.000 -19.973 23.217
5 2.548 4.977 1.000 -14.303 19.399
7 -7.832 6.653 1.000 -30.359 14.694
8 8.663 5.078 1.000 -8.532 25.857
9 8.128 4.643 1.000 -7.592 23.847
7 1 13.796 6.495 1.000 -8.196 35.788
2 9.113 7.175 1.000 -15.182 33.408
3 16.561 6.425 .466 -5.192 38.313
4 9.454 7.753 1.000 -16.797 35.705
5 10.381 7.005 1.000 -13.339 34.100
6 7.832 6.653 1.000 -14.694 30.359
8 16.495 7.553 1.000 -9.078 42.068
9 15.960 7.890 1.000 -10.755 42.675
8 1 -2.699 5.090 1.000 -19.933 14.535
2 -7.382 5.604 1.000 -26.356 11.592
3 .066 5.025 1.000 -16.948 17.079
4 -7.041 5.660 1.000 -26.204 12.123
5 -6.114 4.534 1.000 -21.467 9.239
6 -8.663 5.078 1.000 -25.857 8.532
7 -16.495 7.553 1.000 -42.068 9.078
9 -.535 3.706 1.000 -13.082 12.012
9 1 -2.164 4.386 1.000 -17.014 12.687
2 -6.847 5.045 1.000 -23.927 10.233
3 .601 4.386 1.000 -14.251 15.452
4 -6.506 5.860 1.000 -26.348 13.336
5 -5.579 3.996 1.000 -19.110 7.951
6 -8.128 4.643 1.000 -23.847 7.592
7 -15.960 7.890 1.000 -42.675 10.755
8 .535 3.706 1.000 -12.012 13.082
Based on estimated marginal meansFigure 25: Pairwise comparison data by condition (non-normalised data)
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68Figure 26: Complete pairwise comparisons for liking and pain reduction.
Binaural Beat Study Music, Mind and Brain Goldsmiths College
Appendix B: Anxiety Questionnaires (BVS and ZARS)
Body Vigilance Scale
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Please complete the following questions according to the following scale:
1 2 3 4 5 6 7 8 9 10
None Slight Moderate Substantial Extreme
I pay close attention to internal body sensations:
1 2 3 4 5 6 7 8 9 10
I am very sensitive to changes in my internal bodily sensations.
1 2 3 4 5 6 7 8 9 10
How much time do you spend "scanning" your body for sensations?
1 2 3 4 5 6 7 8 9 10
How much attention do you pay to each of the following sensations?
Heart palpitations:
1 2 3 4 5 6 7 8 9 10
Chest pain and discomfort:
1 2 3 4 5 6 7 8 9 10
Numbness:
1 2 3 4 5 6 7 8 9 10
Tingling:
1 2 3 4 5 6 7 8 9 10
Shortness of breath:
1 2 3 4 5 6 7 8 9 10
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Faintness:
1 2 3 4 5 6 7 8 9 10
Vision changes:
1 2 3 4 5 6 7 8 9 10
Feelings of unreality:
1 2 3 4 5 6 7 8 9 10
Feelings of detachment from self:
1 2 3 4 5 6 7 8 9 10
Dizziness:
1 2 3 4 5 6 7 8 9 10
Hot flushes:
1 2 3 4 5 6 7 8 9 10
Sweating or clammy hands:
1 2 3 4 5 6 7 8 9 10
Stomach upset:
1 2 3 4 5 6 7 8 9 10
Nausea:
1 2 3 4 5 6 7 8 9 10
Choking or throat closing:
1 2 3 4 5 6 7 8 9 10
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Appendix C: Participant information documentation.
INFORMATION SHEET FOR PARTICIPANTS
YOU WILL BE GIVEN A COPY OF THIS INFORMATION SHEET
Investigating the Enhancement of Pain Tolerance in Musicians and Non-Musicians utilizing Binaural Beats.
We would like to invite you to take part in this original postgraduate research project. You should only participate if you want to; choosing not to take part will not disadvantage you in any way. Before you decide whether you want to take part, it is important for you to understand why the research is being done and what your participation will involve. Please take time to read the following information carefully and discuss it with others if you wish. Ask us if there is anything that is not clear or if you would like more information.
The research aims to investigate whether binaural beats (BB) can improve pain tolerance. By taking part in this study, not only will you be able to improve the understanding of binaural beats, but you could learn how to increase your own pain tolerance! There is an optional compensation of one hour of hypno-psychotherapy for all participants. The project is being run by Peter Bryant as a component of his research masters in Music, Mind and Brain and is being supervised by Professor Joydeep Bhattacharya.
We are recruiting individuals aged 18 and over. To take part, the following should not apply to you: an existing pain condition, a history of heart disease, epilepsy, high blood pressure, recent injury, circulatory disorders, and current pregnancy. If you agree to take part, we will require you to visit the Ben Pimlot Building in New Cross Gate (SE14 6NW) once on an arranged date for no more than one hour and a half. You will be randomly allocated to proceed with a series of nine experimental conditions and asked to complete a “cold pressor task”, which involves placing part of one arm in cold water for each of these nine conditions. Your blood pressure and heart rate will be recorded during the exercises via non-invasive clinical equipment. This will involve you wearing a heart rate monitor on your chest and a blood pressure sleeve on your upper arm. It is advised that you wear loose clothing (preferably with short sleeves) for ease and comfort when using this equipment. Both arms will be used in this experiment in alternate trials.
You will be in the presence of a fully qualified first aider at all times in the unlikely event of any complications arising from the experimental procedure. The cold pressor task can be uncomfortable, but it is a reliably and demonstrably safe method for inducing pain. The equipment used is a container of cold water, and the task involves placing your arm in the water, saying on a scale of one to ten how much pain you are experiencing at certain times, and then removing your arm after 3 minutes or when it becomes too uncomfortable. You can end the task at any time. All measures possible will be taken to minimise any possible risk, and all personally identifiable data will be completely anonymised. The data shall be recorded by the depression of an electronic pad placed at the bottom of the tack. If you give us your permission, we will record your session using a video camera (angled on the water tank – only your arm will be filmed). These recordings will be deleted once they have been written up. Should you take part, you will be compensated by a free hour of hypno-psychotherapy if you wish, we will direct you to a final copy of the report and you will be invited to attend a public talk of the results in August/September 2013.
Binaural beats are an auditory phenomena which some claim allow you to alter your mood, anxiety level or performance on cognitive tasks just by listening to two, slightly differently pitched tones. Two tones will be presented, one to each ear for the duration of three minutes. These tones will differ slightly in pitch so that they create a subjective ‘beating’ effect. This is what is known as a binaural beat. They are entirely safe and the most you are likely to feel is a little more relaxed when the binaural beats are performed. In order to accommodate for expectation effects this study also uses an identical set of monophonic beats which are perceptually identical to the binaural ones. You will not know which stimuli are the real binaural beat stimuli are as they have been disguised. You will be asked to guess which conditions you thought were the binaural beat stimuli at the conclusion of the experiment.
Should you wish to withdraw from participation in this study or should you wish to withdraw your data, you may do so at any time. You are also entitled to request a break (or breaks) from the experimental procedure at any point in the experiment.
All personally identifiable data will be destroyed after your visit and the data has been written up. While held, all data will be kept on encrypted devices and will only be accessible by the primary researcher. The data collected from the study will be anonymised, and will only be figures relating to pain tolerance and various questionnaire scores. With your permission we will archive this data for use by future researchers. We plan to publish our findings in a peer reviewed journal, and a final report from the study will be distributed via the internet to participants.
The primary researcher in this project will be Peter Bryant. Contact: [email protected], or write to Peter Bryant, Psychology Department, Goldsmiths College, University of London, New Cross, London SE14 6NW
It is up to you to decide whether to take part or not. If you decide to take part you are still free to withdraw from the study at any time and without giving a reason.
If you have any questions or require more information about this study, please contact the project supervisor using the following contact details Joydeep Bhattacharya. Contact: [email protected], or write to Joydeep Bhattacharya, Room 1-14 Ben Pimlott Building, Department of Psychology, Goldsmiths, University of London, New Cross, SE14 6NW, London, United Kingdom
Just in case you experience any difficulties after the experiment has taken place, the nearest doctors surgery to Goldsmiths College can be found at 40 Goodwood Road, New Cross, London, SE14 6BL. Telephone: 020 3049 2249.
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CONSENT FORM FOR PARTICIPANTS IN RESEARCH STUDIES
Please complete this form after you have read the information sheet and/or listened to an explanation about the research and asked any questions you might have had.
Title of Study: Investigating the Enhancement of Pain Tolerance in Musicians and Non-Musicians utilizing Binaural Beats.
Thank you for considering taking part in this research. The person organising the research must explain the project to you before you agree to take part. If you have any questions arising from the information sheet or any verbal explanation already given to you, please ask the researcher before you decide whether to participate. You will be given a copy of this consent form to keep and refer to at any time.
I understand that if I decide at any time during the research that I no longer wish to participate in this project, I can notify the researchers involved and withdraw from it immediately without giving any reason. Furthermore, I understand that I will be able to withdraw my data up to the point of publication.
I understand that confidentiality and anonymity will be maintained and it will not be possible to identify me in any publications. Furthermore, I permit my anonymised data to be published once this study is completed.
I understand that I must not take part if the following apply to me: an existing pain condition, a history of heart disease, epilepsy, high blood pressure, recent injury, circulatory disorders, or current pregnancy.
Participant’s Statement:
I _____________________________________________________________________ hereby agree that the research project named above has been explained to me to my satisfaction and I agree to take part in the study. I have read both the notes written above and the information sheet about the project, and understand what the research study involves.
Signed Date / /13. (DD/MM/YY).
Investigator’s Statement:
I, Peter Bryant, confirm that I have carefully explained the nature, demands and any foreseeable risks (where applicable) of the proposed research to the participant and that they have understood them to the best of my knowledge.
Signed Date: / /13. (DD/MM/YY).
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Please tick or initial
Yes
Yes
Binaural Beat Study Music, Mind and Brain Goldsmiths College
Participant Debriefing Form
Thank you very much for taking part in this experiment into the effects of binaural beats on the perception of pain. You have just participated in an experiment which presented nine experimental conditions three of which were binaural beats, three were monotone beats which were included for experimental blinding purposes. The other three conditions were controls and were silence, music and white noise. If you have any further questions please feel free to email the principal researcher at [email protected] or telephone 07909 449 445.
I agree that I have no further questions at the present time, but should I in the future, I know who to contact. I also confirm that I am happy with the way the experiment was executed and feel comfortable after participating. I am happy for my experimental information provided today to be published anonymously at the conclusion of this study.
If you have any questions or require more information about this study, please contact the project supervisor using the following contact details Joydeep Bhattacharya. Contact: [email protected], or write to Joydeep Bhattacharya, Room 1-14 Ben Pimlott Building, Department of Psychology, Goldsmiths, University of London, New Cross, SE14 6NW, London, United Kingdom.
Once again, I would like to thank you for taking part in this study.
Signed _________________________________ (Participant). Date: / /13. (DD/MM/YY).
Print: __________________________________
Signed_________________________________ (Researcher). Date: / /13. (DD/MM/YY).
Print: Peter Bryant.
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Appendix D: Calculations
The following formula was used to calculate all effect sizes:
ω2=MS M−MSR
MS M+¿¿
ωSound2 = 2.863−0.963
2.863+((51−1 ) x 0.963)
ωSound2 = 1.9
51.013
ωSound2 =0.03725
ωsound=.193
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