Binaural Beats and Pain Endurance: A double blind, randomised study into the effectiveness of an...

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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http://www.bbstudy.co.uk/


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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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,

19

http://www.cockos.com/reaper/

http://gnaural.sourceforge.net/


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.

http://simplynoise.com/

Figure 7: Blood pressure monitor used throughout experiment


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).

21

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


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).

22


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

23



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).

24


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.

25


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

26


Table 4: Normality tests for non-normalised reaction time data.

Tests of Normality



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


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.

27


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

28


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



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.

29


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



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,

30


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


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 (.

31


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



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)


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

32


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


Table 13: Normality tests of Liking for normalised data.

Tests of Normality for Liking (Normalised Data)


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



33


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).

34


Table 14: Pairwise comparisons for all Liking data according to condition (only significant main effects shown).

35


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)



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


Table 16: Normality tests for pain reduction (normalised data).

Tests of Normality for Pain Reduction (Normalised Data)



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

36


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



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



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

37


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.

38


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.

39


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

40


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.

41


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.

42


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).

43


Hotelling William’s and Steigers Z test for correlation relationships.Measure: Correlations

Correlations t ZMean

DifferenceStd.

Error Sig.a


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

44


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.

45


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.

46


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 =

47


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



Low GMSI .146 25 .180 .923 25 .059High GMSI .134 25 .928 25 .079



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

48


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.

49


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



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

50




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

51


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).

52


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

53


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.

54


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

55


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,

56


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

57


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.

58


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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


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

63


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

64


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


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

65


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)

66


67


68Figure 26: Complete pairwise comparisons for liking and pain reduction.


Appendix B: Anxiety Questionnaires (BVS and ZARS)

Body Vigilance Scale

69


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

70


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

71


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


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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mailto:[email protected]


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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