STRUDWICK Dissertation Document Misc Copy

Developing a reliable measure of frustration for an
Electroencephalogram study
Thomas David Richard Strudwick
Dr Mary-Ellen Large
BSc Psychology
University of Hull Psychology Department
May 2016

Table of Contents
1. Acknowledgements - Page 2
2. Abstract - Page 3
3. Introduction - Page 4
3.1 - Preface
3.2 - What is Frustration?
3.3 - Effects of Frustration on Education
3.4 - Effects of Frustration on Job Performance
3.5 - Measuring Frustration
3.6 - Aims and Rationale of Present Study
3.7 - Overview of Present Study
4. Method - Page 10
4.1 - Participants
4.2 - Apparatus and Materials
4.3 - Design and Procedure
4.4 - Ethical Considerations
5. Results - Page 15
6. Discussion - Page 20
7. References - Page 23
8. Appendices - Page 25
8.1 - Appendix 1: Ethics Application
8.2 - Appendix 2: Risk Assessment
8.3 - Appendix 3: Project Design Form & Statement of Ethical Considerations
8.4 - Appendix 4: Participant Information Sheet
8.5 - Appendix 5: Participant Consent Form
8.6 - Appendix 6: Participant Debriefing Information Sheet
8.7 - Appendix 7: UWIST Mood Adjective Checklist (UMACL)
8.8 - Appendix 8: SPSS Statistics Output
1

1 - Acknowledgements
I would like to take this opportunity to thank my supervisor, Dr Mary-Ellen Large for
her enthusiasm, expertise and continued support throughout this project. I would
also like to thank my father, David Strudwick for taking the time to proof read and
advise me during the compilation of this document and the many which have
preceded it. Lastly I would like to thank my family and friends for their unwavering
support and encouragement with a special mention to my mother, Alison Strudwick
and my girlfriend, Bethany Walton. 
2

Developing a reliable measure of frustration for an Electroencephalogram study
2 - Abstract
This pilot study aims to facilitate the identification and measurement of frustration via
electroencephalogram since current measures and neural correlates for frustration
exist only for functional magnetic resonance imaging (fMRI). Thirty participants
undertook an object selection task which aimed to induce frustration by giving false
feedback on responses at increasing rates as the task progressed through eight
blocks of experimental trials. Insight into affective state of the participants was
measured via a UWIST Mood Adjective Checklist (UMACL) and by observing the
behaviour of the participant during the task. The data showed that reaction times
increased as the percentage of false feedback increased. The results of the UMACL
coupled with the observations suggest that reaction times increased as a result of
frustration induced by the task.
3

3.1 - Preface
Frustration is a familiar emotional reaction relating to anger and disappointment
which follows the perceived failure to achieve a goal or objective. The greater the
cost of this failure, the more intense the feeling of frustration felt to the individual
(Miller, 1941). This is often characterised by physiological changes such as an
increase in heart rate and blood pressure and often coupled with behavioural
instances ranging from a sigh or expletive muttered under ones breath to
occurrences of verbal and even physical abuse towards objects and individuals alike
(Laceulle, Jeronimus, van Aken, & Ormel, 2015). The purpose of the present study is
to find a behavioural measure for frustration which will later allow for the identification
of a neural correlate and in-turn result in more robust exploration of this affective
phenomenon and increased applications of frustration-centred research.
3.2 - What is Frustration?
The term itself originates from the Latin word “Frustrare” - to disappoint and is the
direct opposite of satisfaction. This affective state often arises from thwarted
aspirations, unanticipated obstacles to progression and an inability to change or
improve ones situation and can include various emotional hallmarks such as that of
anger or sadness and can present additional physiological indicators such as
increases in heart rate and blood pressure (Laceulle et al., 2015).
Frustration can be easy to dismiss as a unwelcome step on the progress to a
goal state but researchers are increasingly considering it as a key part of what
motivates behaviour. Amsel’s frustration theory recognises that while frustration can
lead to feelings of annoyance and anger which impede progress if not properly
coached or controlled, this state can be also energising and could eventually
become a preliminary indicator for reward or success as a result of dispositional
learning (Amsel, 1992). The ubiquitous nature of frustration in almost all areas of life
means that this seemingly insignificant and quite unwelcome state of mind plays a
key role in teaching us how to deal with failure or impediment on the way to a goal in
a mature and adult manner (Killeen 1994). Needless to say that this ability to draw
benefit from such situations has been gained far better by some of us than others!
Historically, frustration has been tied closely to pain and fear within many
theories due to sharing many functional similarities. In early research, Gray, (1987)
advocated this similarity on the basis of fear and frustration share very similar
4

emotional and motivational properties. Further similarities can be found from the
behavioural and psychological evidence of the two emotional states. Both share the
same reactive ‘escape’ behaviours resulting from their occurrence and they both give
similar subjective effects of uncertainty (Pappini, Wood, Daniel & Norris, 2006).
Following on from the distinction of preparatory and consummatory
conditioning by Konorski, (1967), Gray, (1987) also proposed the idea that frustration
and fear can both be categorised as preparatory emotional states resulting from the
experience of unexpected non-reward or pain. These are categorised in this way
because fear and frustration are both emotional states which occur prior to obtaining
or interacting with the goal state and not after the goal state has been achieved
(which would therefore make them consummatory emotional states). This is the case
as the actual achievement of the goal state itself is a contraindication for the
experience of these emotional states. (Konorski, 1967).
3.3 - Effects of Frustration on Education
A reliable objective measure of frustration could be applied to many differing
contexts. One such context would be to aid the education of students in secondary
schools and colleges, environments in which frustration can pose a substantial
barrier to the students goal of understanding conveyed information and can result
classroom disruption and students needlessly underperforming in assessments.
Frustration measurements would allow for the development of teaching techniques
which may minimise frustration to students and even allow for the provision of
targeted learning masterclasses to teach students to ward-off the adverse effects of
frustration on their studies. Aforementioned application of frustration study is
currently being carried out by Lone and Srivastava, (2014) to discern the differences
in the effect of frustration on high and low academic achievers and also by Graesser
and D’Mello, (2012) in relation to frustration adversely affecting the learning of
increasingly complex material.
3.4 - Effects of Frustration on Job Performance
A measure of frustration could be further applied to occupational psychology with the
aim of reducing frustration in the workplace. This would result in a much more
motivated and mentally tough workforce which has benefits for employees and
employers alike. Employees would be more likely to enjoy their job and gain a much
greater job-satisfaction while employers will experience a much lower staff turn-over
5

which reduces the need to constantly recruit and train new staff cutting costs as a
result. They would also benefit from a higher productivity rate due to having a
happier, more skilled and experienced body of staff (Kahya, 2007). Clark, (2014) has
studied workplace frustration experienced by healthcare assistants working within
the NHS but has no objective measurement of frustration which has potentially
limited his findings due to only having used a self-report questionnaire which will
have been time consuming to interpret and generalise. An objective measure would
be equally useful to studies of frustration affecting impulsivity and decision-making.
This would better enable researchers such as Goldschmied et al., (2015) to detect
the onset of frustration in participants and analyse how it has affected the decisions
made, potentially reinforcing the relationship between high levels of frustration and
high degrees of impulsive behaviour.
3.5 - Measuring Frustration in Research
Measuring frustration has been attempted in may different ways and in relation to
many differing contexts. For example, Storms and Spector, (1987) studied frustration
in relation to the degree of control a participant has on the underlying cause in the
context of the workplace and the influence this has on emotional and behavioural
reactions. This showed that an external degree of control (such as an older model
computer) resulted in a more counter productive behaviours than an internal cause
(such as feeling tired or being under prepared). This research used a three item
questionnaire with a six-point scale to measure the frustration of the participants with
a higher score being indicative of a higher level of frustration (Storms & Spector,
1987).
A more recent study using a questionnaires as a measure of frustration is that
by Clark, (2014) who used one that measured frustration and a number of other
occupation-related qualities such as frustration in tandem. However, this research
also used an interview to follow up on responses given. This approach has many
useful applications such as analysing instances of frustration over a longer period
but would be unsuitable for immediate identification of contextual frustration which
would better benefit from an objective measure of frustration.
Research by Scheirer, Fernandez, Klein, and Picard, (2002) measured
number of mouse clicks as a frustration indicator during the use of a ‘faulty mouse’
program used while trying to solve a puzzle on the computer. This study found that
frequency of mouse clicking increases with feelings of building frustration.
6

Why and Foo, (2010) looked at frustration and control, finding a reliable
cardiac affect using a similar faulty mouse program. Here, an increased heart rate
was found to indicate increased feelings of frustration.
Abler, Walter and Erk, (2005) used fMRI to investigate frustration resulting
from omission of rewards, finding two effects, an allocentric effect which causes
behavioural changes and an egocentric effect which comprises of the internal
emotional effect - the actual feeling of frustration. They used a monetary incentive
task with a parametric variation of possible wins; a big win, a small win and no win.
In this task, participants had to react to a stimulus on the screen with a button click of
either the left or right hand (square - righthand, triangle - lefthand). If they made the
correct choice then they had a 60% chance of being rewarded. in 40% of the trials
they would not be rewarded for a correct choice. This study successfully identified an
fMRI neural correlate for frustration which is discussed further on (Abler et al., 2005).
A frustration tolerance task was used as an indication of frustration by
Goldschmied et al., (2015) in their research into the effect of a 60 minute nap on
emotional processing and impulsivity. In this study, participants would be presented
with four geometric designs were presented to the participants with the instructions
that they must copy each design onto a piece of paper without living the pen from the
paper and without crossing any line they had already drawn. The participants could
spend as long as they wanted on each design and have as many attempts as they
wanted, however, half of the designs given to them were impossible to complete.
Therefore the time spent on the impossible copying tasks was taken as the indication
of persistence. In this case, the less time spent on the tasks, the more frustrated they
had become and the lower the participants frustration tolerance. This research found
a nap increased frustration tolerance and reduced impulsivity in participants
(Goldschmied et al., 2015).
Frustration has also been studied with the aim of finding methods to reduce
and control frustration and conserve the patience of a user hopefully resulting in a
longer, less stressful interaction. Klein, Moon and Picard, (2002) used a manipulated
computer game which worked fine for 3 minutes and then slowed right down
eventually becoming almost unplayable. The method used to reduce frustration was
the provision of an ‘affect-support modules’ which acted as an emotional vent for the
user, allowing them to type their feelings of frustration and anger caused by the
deliberately slow application. It would then respond with a number of preset
sentiments of sympathy, apologies or witty responses/jokes dependant on what was
7

typed. This study measured frustration by time it took participants to use a ‘quit’
button on the computer game and showed that the game time was significantly
longer with the use of the affect-support module. (Klein et al., 2002).
3.6 - Aims and Rationale of the Present Study
As of current research, the possible existing neural correlates of frustration are the
right ventral prefrontal cortex and right anterior insular as discovered via fMRI by
Abler et al., (2005). While this is a significant finding, the practicality of performing
fMRI examinations in contextually relevant arenas such as a work place or school is
very limited and greatly lacks ecological validity. Whereas neither of these are
limitations for the Electroencephalogram (EEG), a method which would only require
a small number of electrodes to gain a sufficient amount of data to distinguish
between a frustrated and non-frustrated participant. This would therefore increase
the variability of activities and contexts in which frustration can be researched (such
as those mentioned in the preceding subsections) leading to a better understanding
of this affective state. This could then in-turn lead to further applications of research
findings, such as computer-programme and application development, occupational
streamlining and methodological education technique improvements. However, a
neural correlate for frustration has not yet been identified via EEG. The aim of this
study is therefore to devise an experiment which gives rise to a sufficient threshold of
observable frustration in participants. If identified, the intention is that the observed
frustration could then be meaningfully analysed and pinpointed via an EEG
experimental methodology.
3.7 - Overview of the Present Study
To achieve the aforementioned aims, it is necessary to find a measurable dependent
variable which correlates to increasing frustration levels. The present study uses a
task similar to that used by Abler et al., (2005), which will present participants with a
visual stimulus and ask them to identify whether or not the visual stimulus is an
animal or not. As participants proceed further into the trial blocks they will receive
false feedback on the choices they have made. The chances of receiving false
feedback will increase from 10% up to 60% in an attempt to give rise to the emotion
of frustration although we anticipate that participants will ask to terminate the
experiment before this point is reached. Reaction times and accuracy rates will be
recorded to see if there is a relationship between these and reported frustration as it
8

is anticipated that reaction times will become slower as they progress though the
trials due to becoming more frustrated and losing confidence in their decisions.
Participants are also asked to fill out a UWIST Mood Adjective Checklist (UMACL)
after the experiment to give further insight into the effects of the task on the
participants affective state.
9

4 - Method
4.1 - Participants
In this study, 30 participants were tested, all of whom were students at the
University of Hull between the ages of 19 and 33 with a mean age of 22.2 years
(SD=0.7). Of these, 11 were male and 19 were female. These participants were
recruited via a convenience sample from the social groups of the experimenter and
all who volunteered to take part in the experiment did so without payment. Approval
was received from the Department of Psychology Ethics Committee and informed
consent was received by every participant before the experiment began. Further
information surrounding ethical procedures can be found in the Ethical
Considerations section, below.
4.2 - Apparatus and Materials
The task used a computer to run an ePrime program which displayed the
visual stimulus. This program also recorded response-related data including
accuracy rate of the participants response and the participant's reaction times to
stimuli. On completion of data collection, IBM SPSS Statistics was employed to
analyze the data and MS Excel for presentation.
The study used a total of 792 colour images with a maximum size of 400x400
pixels and a minimum of 200x400 pixels: 24 for the practise trials and 96 images for
each of the 8 experimental blocks with no images repeated at any point in the task.
These images were sourced from the internet and fall into three different categories;
animal, vehicle and landscape. Images featuring animals only had one type of
animal in the picture but often included many of this animal in the image. Images
from the vehicle category only featured a single object but included a vast array of
land, sea and air examples (See Figure 1 for examples).
The UWIST Mood Adjective Checklist (UMACL) used by Why and Foo,
(2010). This mood scale has been shown to have limited interference from
demographic correlates of mood such as sex differences, social-economic class,
education level and age. Personality types also do not confound measurement of
mood via this method making it a highly reliable measurement of mood (Matthews,
Jones & Chamberlain., 1990). The UMACL requires participants to use a four-point
scale to rate how closely their current affective state matched 15 different descriptive
items. These items fit into four categories; hedonic tone which includes pleasant
mood indications such as happiness, anger items including moods equated to anger,
10

tense arousal which includes items relating to anxiety level such as relaxed, and
energetic arousal which includes items relating to energy level of the participant such
as alert. On This scale 1, the lowest end of the scale, corresponded to Definitely not
feeling like this, and 4, the highest end of the scale implied Definitely feeling like this.
The completed mood inventory can be found in Appendix 7.
4.3 - Design and Procedure
This experiment took place within a research lab at the University of Hull
Psychology Department and has been reviewed and accepted by the Department of
Psychology Ethics Committee and informed consent was received by every
participant before the experiment began. Further information on ethical
considerations can be found in the ethical considerations section, below. (see
appendix 1 and 2 for ethics application, approval letter and risk assessments).
Participants completed a practice block, consisting on 24 trails and then 8
blocks of 96 trials. Between these blocks they were given a break, the length of
which was determined by each participant. The design of this study also allowed for
11
Figure 1: Examples of the animal, vehicle and landscape images displayed in the
ePrime programme.

the termination of the experiment without the completion of all 8 blocks due to the
potentially stressful nature of the task. Further information on the rationale of this
feature is provided in the ethical considerations section below.
As the experimental blocks progress, the ePrime program was modified to give
increasing rates of incorrect feedback to the participant with the aim of inducing
feelings frustration in participants. However, the practise block and the first
experimental block were unaltered to give the participant confidence in their
responses. The alteration percentages for each block can be found in table 1.
Table 1: Percentage of trials giving incorrect feedback for each block.
A within-groups experimental design was used in the present study where the
proportion of modified trials in each block was the independent variable. The
dependent variables included change in reaction times for (correct response) trials,
mood questionnaire scores, accuracy rates for untampered trials and finally,
observed behaviours of participants throughout the experiment (such as forceful key
presses, vocalised objections etc.). These observations were made via experimenter
note taking with the most common behaviour occurrences reported with the results.
All participants read the participant information sheet and signed the consent
form (see appendices 4 and 5) after clarifying any questions arising. Before the trials
began, the participants were asked to provide demographic information (age and
gender) and to read the on-screen instructions for the task. These instructions were
then reiterated, with the additional information that (for the sake of the task, and to
avoid any confusion) insects were to be regarded as animals and that humans
Block Number Percentage of False Trials
Practise Block 0%
1 0%
2 5%
3 10%
4 20%
5 30%
6 40%
7 50%
8 60%
12

should not. It was also emphasised that participants would receive trial feedback
related to their performance, indicating cumulative accuracy and reaction time.
Participants were instructed to respond as quickly and as accurately as possible to
each trial. A final opportunity was then offered to resolve any new queries prior to
commencement of the experiment.
During the task, a fixation cross was displayed in the centre of the screen in
between stimuli. This would then be replaced by a picture (either an animal or non-
animal) presented in the centre of the screen for 50 m/s and then a mask of the
same size and position presented for 100m/s (See figure 2). These images were
presented in the same order for every participant. The participant was then required
to press a corresponding computer key once the image disappeared depending on
which picture they have been presented, in this case it was “S” if an animal was
present in the picture and “L” if there was no animal present. Participants were given
one second to respond, after which they were presented with a measurement of their
reaction time, their cumulative accuracy rate and a message of whether or not they
made the correct selection (“Correct!” for a correct response, “Incorrect” or an
incorrect response and “No Response” text feedback if they did not respond).
Upon completion of the 8 blocks and the false resulting feedback, and/or
indeed, the participant's request for early termination of the experiment, they were
asked to fill out the UMACL (see appendix 7) reflecting their feelings on their
respective achievements. After this, they were given the participant debriefing
information sheet (see appendix 6) and the true purpose of the experiment was
explained to them. Participants were extended another opportunity to resolve
queries. The student welfare information was also specifically pointed out to every
participant before they departed.
4.4 - Ethical Considerations
There are two major ethical difficulties with this study, the first inducing
frustration, a negative emotional state. The aim of this study is to only induce mild
frustration which should not exceed a level commonly experienced via using
technology such as computers on a day-to-day basis. However, this cannot be
guaranteed as different people react to different levels of frustration in different ways.
The second major ethical issue is deception. This comes in the form of deceiving the
participant about the true purpose of the experiment. This is necessary as if the
participant knew beforehand that the experiment was investigating frustration they
13

would be able to work out for themselves that the feedback was not real and thus
confound the data gathered.
To safeguard against high levels of stress the experiment has been designed
so that it can be discontinued when the participant shows behaviour associated with
frustration – e.g. hitting keys hard, making comments, expletives or non-verbal
utterances, increased fidgeting or should the participant themselves request to stop
the experiment easy. The participant will be told immediately after the experiment
concludes or is discontinued that the feedback they received was false. They will
then be given the debriefing sheet which explains the purpose of the experiment. It is
expected that the task will not induce high levels of frustration because there is no
cost to the participant associated with a poor performance but these safeguards are
in place to cover this eventuality.
 
14
Figure 2: Sequential order, timings and screen locations of fixation cross, visual
stimuli and mask for trials: Screen 1 shows the fixation cross displayed between
stimuli. Screen 2 shows the screen with a stimulus being displayed to the participant.
This is displayed for 50m/s. Screen 3 shows the screen with the mask which is
displayed immediately after the stimulus with no time delay. This is displayed for
100m/s. Screen 4 then shows the fixation cross which is displayed on screen while
the participant responds to the stimulus. This is displayed for 1 second before the
feedback is displayed on the screen.
2.1. 3. 4.

5 - Results
In this analysis, an alpha value of .05 was used. From the data analysed, 382
outliers were excluded (2.08% of the total data set). All of these pieces of data were
more than two and a half standard deviations either above or below the
corresponding block mean reaction time. Instances where participants did not give a
response were also excluded. The following analysis uses data from blocks one to
five as a majority of participants did not complete blocks six, seven and eight. In this
particular study 14 out of the 30 participants either elected to terminate the
experiment early or were subject to the experimenter intervening and prematurely
terminating their experiment due to signs of excess frustration. This data set includes
only the reaction times of instances where participants made the correct selection
(regardless of whether they received incorrect feedback). The data was analyzed via
Repeated Measures ANOVA using two factors; block number with 5 levels (one for
each block analysed) and category of stimuli with 2 levels (one for target stimuli and
one for distractor stimuli) The mean reaction times start off lower for target stimuli
compared to distractor stimuli in block one but are then higher for the remaining
blocks two, three, four and five. These results described above for target and
distractor stimuli within each block are displayed in table 2 and figure 3. The data
sets are also displayed separately for additional clarity with figure 4 displaying target
stimuli reaction times and in figure 5 displaying distractor stimuli reaction times.
Table 2. Mean and standard deviation of reaction time of participants in milliseconds
for target and distractor conditions in blocks 1 to 5
Reaction Time
Block
Number
Target Distractor
Mean SD Mean SD
1 308.58 52.13 319.32 47.31
2 320.50 69.68 321.11 64.85
3 314.86 68.24 307.80 72.76
4 329.20 109.31 320.58 98.95
5 344.07 96.71 342.50 94.87
15

!
Figure 3. Mean(SE) reaction time of participants in milliseconds for target and
distractor conditions in blocks 1 to 5.
!
Figure 4. Mean(SE) reaction time of participants in milliseconds for target stimuli
data in blocks 1 to 5.
16

!
Figure 5. Mean(SE) reaction time of participants in milliseconds for distractor stimuli
data in blocks 1 to 5.
A repeated measures ANOVA using two factors; block number with 5 levels
(one for each block analysed) and category of stimuli with 2 levels (one for target
stimuli and one for distractor stimuli) did not show a significant effect of block number
(F[2.65,60.87] = 1.693, p=0.158 (NS), η=0.35) or a significant interaction between
category of stimuli (target or distractor) and block number (F[3.13,72.08] = 2.426,
p=0.054 (NS), η=0.47). This has been analysed by two further one-way repeated
measures ANOVA’s due to how narrowly the result is not significant. These were
conducted on the target and distractor reaction time data independently to
investigate the interaction. The analysis found no main effect of block number for
target reaction time data (F[2.59,59.59] = 1.859, p=0.154 (NS), η=0.44) but a
significant linear effect of block number was found for target reaction time data
(F[1,23] =5.608, p<0.05, η=0.70). Analysis of the distractor reaction time data found
no main effect of block number (F[2.85,65.62] = 1.611, p=0.197 (NS), η=0.14) and no
linear effect of block number (F[1,23] = 1.877, p=0.184 (NS), η=0.31). The analysis
of within subjects contrasts did not show a main effect of block number (F[1,23] =
3.649, p=0.69 (NS), η=0.75) but did show a significant linear interaction between
category of stimuli and block number (F[1,23] = 6.176, p<0.05, η=0.85).
The UWIST Mood Adjective Checklist was administered after the task
concluded to gain an indication of the affective state of the participants following task
17

completion to further analyse how effective the false feedback had been at inducing
frustration. The results of the mood questionnaire resulted in a mean hedonic tone
percentage score of 72.08%, a mean anger item percentage score of 48.67%, a
tense arousal percentage score of 44.44% and a mean energetic arousal score of
60% (Shown in Table 3). This shows a higher than expected hedonic tone
percentage and a lower than expected anger item percentage than would be
expected from a frustration-inducing task. Tense arousal percentage score is also
lower than would be expected after a frustration inducing task with energetic arousal
similarly scoring too highly. This analysis is based on the assumption that a score of
50% corresponds to an average level of the corresponding emotion as no
normalised data could be sourced for the UWIST Mood Adjective Checklist.
Table 3. Mean, Standard Deviation and Percentage of UWIST Mood Adjective
Checklist post-test administration scores
Table 4 shows the behavioural observations of participants after receiving
false feedback on responses. These are all the behaviours which were observed by
more than one participant. These results show that just over half of the participants
did not make it to the end of the experiment meaning that the task was sufficiently
frustrating to make participants either ask to stop or for the experimenter to intervene
in a majority of cases. This intervention would be performed at the discretion of the
experimenter when obvious signs of excess frustration were displayed by the
participant. Hard key presses after false feedback were observed in 13 of 30
participants and verbal disagreement was observed in 12 out of 30 participants.
Cursing and swearing, the most severe reaction to false feedback was only observed
in 3 participants. These 3 behaviours are the most severe responses observed and
all of them were only observed in a minority of participants. This allows the
Mood Score
Hedonic Tone
(Max:16, Min:4)
Anger Item
(Max:20, Min:5)
Tense Arousal
(Max:12, Min:3)
Energetic Arousal
(Max:12, Min: 3)
Average 11.53 9.73 5.33 7.20
Percentage 72.08% 48.67% 44.44% 60.00%
SD 2.52 4.79 2.14 2.01
18

speculation that the task was not sufficient enough to cause an overly high level of
frustration in most participants.
Table 4: Observed behavioural indicators of frustration identified in more than
one participant and the frequency of presentation. N = 30
Behavioural Indicator Frequency
Cursing/Swearing 3
Head Shaking 5
Tutting 6
Sighing 7
Verbal Disagreement/Protest 12
Hard Key Press 13
Early Termination 17
19

6 - Discussion
Although the present study did not have a direct experimental hypothesis, the
results obtained were partially supportive of the long term aims of this pilot in finding
a reliable measure of frustration via EEG. These data showed that reaction times
increased as the percentage of false feedback increased. The results of the UMACL
and the observed behavioural indicators allow for the speculation that this increase
in reaction times occurs as a result of frustration.
From these results, the task used in the present research could be
meaningfully implemented into EEG research. This would be done by adding
stimulus and response markers into the ePrime program at the points where stimuli
are presented to participants and at the point when feedback is received. This allows
the researchers to identify the points of interest on the EEG feed for data analysis.
These markers would be coded differently for target and distractor stimuli so the
researchers can distinguish between the two conditions, allowing for comparative
data analysis.
The increase in reaction times as the false feedback increases (and the
blocks progress) does have potential alternate causal factors, one of which is that
the increase may simply be down to fatigue of participants as the experiment is very
long and the task is monotonous in nature. Future research in this area might
consider replication with a shorter task incorporating a higher number of more
frequent breaks to better avoid the possibility of participant fatigue from the task.
Fatigue as alternative explanation to increased reaction times is both supported and
discredited by the UMACL data which does not show overly high anger item or tense
arousal scores, both of which are associated with frustration presence. While the
study only aimed to induce moderate moderate frustration levels, concerns arise
from the other areas of UMACL data which shows high levels of hedonic tone and
energetic arousal. These levels would be too high for a frustrated participant and
similarly too high for indications of boredom or fatigue in the participants, leaving this
wide open for further interpretation and replication. This analysis is based on a score
of under 25% for a low level of the corresponding emotion and over 75% indicating a
high level of corresponding emotion due to the lack of normalising data for the
UMACL.
The speculation around the data from the UMACL could have been avoided if
a measurement had been performed before the start of the task. Unfortunately, this
risked confounding the experiment by revealing to participants that we were
20

investigating mood, a detail which was withheld from them until the end of the task.
However, this would have provided us with a before and after comparison of mood
allowing much more clarity surrounding the effect of the task on participants mood.
The lack of normalising data for the UMACL has also hindered interpretation of the
data. Future researchers may consider using a different method of measuring the
affective state of participants.
Future research might also consider reducing the increments of false
feedback increase between each block. This recommendation comes as a result of
participants feedback which stated that although the false feedback initially made
them frustrated, this feeling did not last long as they reached a point where they
knew they where making the correct response and therefore the program had to be
incorrectly feeding back. As this was of no cost to them, this did not result in
frustration and instead gave feelings of emotional neutrality. Making the blocks
shorter would mean that the actual number of instances of false feedback are also
reduced making the underlying workings of the task harder to workout. Once this is
implemented with reduced increments of increasing false feedback which start at a
higher percentage rate, construct validity of the experimental task should be
increased yielding clearer, more statistically significant results. In extension to this,
adapting the present task to make it more difficult would make the manipulated false
feedback more plausible to participants as they would be more likely to believe that
they had made a mistake and result in the frustration from participants lasting longer.
This could be done by adding more types target stimuli requiring different button-
press responses from participants. This would then further increase construct validity
by combating the limitation stated above of the task which only causes brief feelings
of frustration due to participants realising their feedback is false.
These adaptations should also make it easier to impose a minimum threshold
of participant progress through the task before participants request to end the task or
before intervention is required by the experimenter to avoid excessive frustration
being experienced by the participant. This will be of great value as the present
research has suffered from limited analysis due to the high number of participant
termination early on in the task. This has meant that response accuracy in terms of
block progression or reaction time could not be meaningfully analysed or reported in
this study. Having a minimum progress threshold would guarantee the researcher a
minimum amount of data to analyse while preserving a minimum ethical risk to the
21

participants and in turn, guarantee a level of depth and quality of analysis which can
then be carried out.
The actual experimental task itself when used in future replications and/or
applications should avoid the use of pictures which feature insects in place of
animals as this has caused confusion to participants in the present research who
were asked to target animals and (incorrectly) did not include insects in the subset of
target stimuli. The same can also be said for pictures including humans (such as a
human driving a car or walking in a field) which similarly caused confusion to our
participants who (again, correctly) included them in the subset of target stimuli when
they were not meant to. This will prevent unnecessary data loss and participant
confusion in future replications.
In conclusion, these findings show future potential for developing a reliable
measure of frustration via EEG by analysis of response reaction times to stimulus
despite the many limitations of the present methodology and the limited clarity of
some of the results obtained. A better understanding of the cause of increasing
reaction times and whether or not this is actually an indication of frustration in
participants will be able to be better established once the present study is replicated
with shorter experimental blocks featuring reduced increments of increasing false
feedback and a comparative before and after measurement of affective state. These
findings showed increasing reaction times as blocks progressed and false feedback
increased. They also demonstrated that emotions associated with frustration (such
as anger) were of at least average level after the task but this is coupled with higher
levels of more positive emotional states being similarly indicated.
22

7 - References
Abler, B., Walter, H., & Erk, S. (2005). Neural correlates of frustration. Neuroreport,
16(7), 669–672.
Amsel, A. (1992). Frustration Theory: An Analysis of Dispositional Learning and
Memory. Cambridge University Press.
Clark, I. (2014). Health-care assistants, aspiration, frustration and job satisfaction in
the workplace. Industrial Relations Journal, 45(4), 300–312.
Goldschmied, J. R., Cheng, P., Kemp, K., Caccamo, L., Roberts, J., & Deldin, P. J.
(2015). Napping to modulate frustration and impulsivity: A pilot study.
Personality and Individual Differences, 86, 164–167.
Graesser, A. C., & D’Mello, S. (2012). Emotions During the Learning of Difficult
Material (Vol. 57).
Gray, J. A. (1987). The Psychology of Fear and Stress. CUP Archive.
Kahya, E. (2007). The effects of job characteristics and working conditions on job
performance. International Journal of Industrial Ergonomics, 37(6), 515–523.
Killeen, P. R. (1994). Frustration: Theory and practice. Psychonomic Bulletin &
Review, 1(3), 323–326.
Klein, J., Moon, Y., & Picard, R. W. (2002). This computer responds to user
frustration: Theory, design, and results. Interacting with Computers, 14(2),
119–140.
Konorski, J. (1967). Integrative activity of the brain: an interdisciplinary approach.
University of Chicago Press.
Laceulle, O. M., Jeronimus, B. F., van Aken, M. a. G., & Ormel, J. (2015). Why Not
Everyone Gets Their Fair Share of Stress: Adolescent’s Perceived
Relationship Affection Mediates Associations Between Temperament and
Subsequent Stressful Social Events. European Journal of Personality, 29(2),
125–137.
Lone, A., & Srivastava, A. (2014). Study the impact of frustration and anxiety on high
and low academic achievers among college students - ProQuest. Indian
Journal of Health and Wellbeing, 5(1), 155–157.
23

Matthews, G., Jones, D., M., & Chamberlain, A. G. (1990). Refining the
measurement of mood: the UWIST Mood Adjective Checklist. British Journal
of Psychology, 81, 17–42.
Miller, N. E. (1941). I. The frustration-aggression hypothesis. Psychological Review,
48(4), 337–342.
Papini, M. R., Wood, M., Daniel, A. M., & Norris, J. N. (2006). Reward Loss as
Psychological Pain. International Journal of Psychology & Psychological
Therapy, 6(2), 189–213.
Scheirer, J., Fernandez, R., Klein, J., & Picard, R. W. (2002). Frustrating the user on
purpose: a step toward building an affective computer. Interacting with
Computers, 14(2), 93–118.
Storms, P. L., & Spector, P. E. (1987). Relationships of organizational frustration with
reported behavioral reactions: The moderating effect of locus of control.
Journal of Occupational Psychology, 60(3), 227–234.
Why, Y. P., & Foo, Y. (2010). The impact of task controllability on perceived control
and cardiovascular processes. Psychophysiology, 47(4), 669–672.
24

8 - Appendices
8.1 - Appendix 1: Ethics Application Form and Approval Letter
University of Hull Psychology Ethics Application
Ethics Checklist for Research Projects Involving Human Participants
NAME OF STUDENT/ASSISTANT (Supervised projects only). Thomas Strudwick
RESEARCHER CLASSIFICATION !
NAME OF RESEARCH SUPERVISOR Dr Mary-Ellen Large
TITLE OF PROJECT: Change in frequency distributions of frustration
NOTE This checklist should be completed by the investigator prior to beginning any research projects
in which human participants will be employed. The checklist is intended to provide a general guide as
to the ethical status of the project and whether or not a full application should be made to the
Psychology Department Ethics Committee. It should be used in conjunction with the ethical guidelines
published by the British Psychological Society. http://www.bps.org.uk/system/files/documents/
code_of_ethics_and_conduct.pdf
Please complete all sections by ringing the appropriate answer.
3rd year student
25

1. RISKS
If you have answered YES in this section, make sure you provide enough details for the
committee to assess your application.
1) Do any aspects of the study pose a possible risk to participant's physical
wellbeing (e.g. use of substances such as alcohol, extreme situations such as
sleep deprivation, collecting data in potentially dangerous situations)?  
If YES, please specify: Click here to enter text.
2) Are there any aspects of the study that participants might find humiliating,
embarrassing, ego-threatening, in conflict with their values, or be otherwise
emotionally upsetting?*  
If YES, please specify: We will be invoking frustration via deception and false
feedback to the input of the participant. When the participant makes a selection
between two choices, we will provide automated feedback which states it is
incorrect regardless of input. The frequency of this false feedback will increase
as the study progresses in an attempt to provoke frustration in the participant
3) Are there any aspects of the study that might threaten participants' privacy
(e.g. questions of a very personal nature, observation of individuals in situations
which are not obviously 'public')?*  
4) Does the study require access to confidential sources of information (e.g.
medical records)?  
5) Could the intended participants for the study be expected to be more than
usually emotionally vulnerable (e.g. medical patients, bereaved individuals)?  
6) Will the study take place in a setting other than the University campus or
student accommodation?  
7) Does the researcher of this study require a Disclosure and Barring Service
(DBS) check? 
This is required if research involves children or vulnerable adults, if required
specify if obtained or applied for  
If YES, please specify (obtained or applied): Click here to enter text.
8) Will the intended participants of the study be individuals who are not
members of the University community?
If YES describe who will be tested Click here to enter text.
*Note: if the intended participants are of a different social, racial, cultural, age or sex group
to the researcher(s) and there is any doubt about the possible impact of the planned
procedures, then opinion should be sought from members of the relevant group.
!
NO
!
NO
!
NO
!
NO
!
YES
!
NO
!
NO
!
NO
26

2. DECEPTION
3. INFORMED PARTICIPATION AND CONSENT
1) Does the study involve the use of non-trivial deception, either in the form of
withholding essential information about the study or intentionally misinforming
participants about aspects of the study? (See Debriefing section).  
 
If YES add additional information: Participants will be deceived via not
telling them about our aims regarding inducing frustration as not to
confound the study. This will be done via giving them misleading
feedback to the sections they make between two image types.
Participants will be debriefed immediately after the experiment ends.
If you have answered 'YES' please make sure you address this issue in the informed consent
and debriefing documents.
!
YES
1) Participants in the study should be given written information outlining:
1. the general purpose of the study,
2. what participants will be expected to do
3. individuals' right to refuse or withdraw participation with impunity
If NO, please specify: Click here to enter text.
2) If the study involves physically unpleasant or emotionally upsetting
procedures (e.g. viewing scenes of violence; working in loud noise), will
participants be explicitly informed of this in writing?
3) Will all participants in the study be able to understand the information given
and its implications for them?
4) Will participants have an opportunity to ask questions prior to agreeing to
participate?*
5) Have appropriate authorities (e.g. head teachers, classroom lecturers, shop
managers) given their permission for participants to be recruited and tested, or
for data to be collected on their premises?
If YES attach a copy of the letter or email granting permission at the end of this
application form.
6) Please complete an information sheet (Ctrl+click will take you to page 6 of
this document) and consent form (Ctrl+click will take you to page 8 of this
document)
!
YES
!
N/A
!
N/A
!
YES
!
YES
27

4. DEBRIEFING
5. ANONYMITY AND CONFIDENTIALITY
* Note: ‘N/A’ would be appropriate for some purely observational studies.
1) Do the planned procedures include an opportunity for participants to ask
questions and/or obtain general feedback about the study after they have
concluded their part in it?*
2) If deception has been used, does the procedure include a specific time for
debriefing?
3) Please complete a debrief form (Ctrl+click will take you to Page 9 of this
document)
If you have answered NO to either question, make sure you address these issues
in the informed participation/consent document and in the debriefing document
!
YES
!
YES
1) If anonymity has been promised, do the general procedures ensure that
individuals cannot be identified indirectly?
2) Have participants been promised confidentiality?*
3) If confidentiality has been promised, do the procedures ensure that the
information collected is truly confidential (e.g. questionnaire responses cannot
be overseen by other participants; questionnaires are returned to the researcher in
sealed envelopes)?
4) Will non-anonymous data be stored in a secure place which is inaccessible to
people other than the researcher? (N/A if study is anonymous)
5) If participants' identities are being recorded, will the data be coded (to
disguise identity) before computer data entry? (N/A if study is anonymous)
!
N/A
!
YES
!
N/A
!
YES
!
YES
28

6. DETERMINATION OF CLASSIFICATION
7. PROJECT CLASSIFICATION
If any of the boxes above in section 6 are answered with ‘Exceptional’, then the
project should be classified as ‘Exceptional’.
Normal !
Exceptional !
Exceptional but a simple change to pre-approved study !
Exceptional but only because the research involves research in schools or
Outside organizations !
Attached Documentation (these documents are mandatory)
• Information sheet !
• Consent Form !
• Debrief Form !
• Permission Letter (if research is conducted in a school, or an institution outside of
University of Hull)
!
THE ETHICS APPLICATION NEEDS TO UPLOADED AT
http://psy.hull.ac.uk/Committees/Ethics/Checklist/
Researcher/Supervisor’s Name Dr Mary-Ellen Large Date 25/11/15
Students Name Thomas Strudwick Date 25/11/15
If you have answered ‘YES’ to any of the questions in Section 1
(risks), please select ‘Exceptional’ on the right
If you have answered ‘YES’ to the question in Section 2
(deception), please select ‘Exceptional’ on the right
If you have answered ‘NO’ to any of the questions in Section 3
(consent), please select ‘Exceptional’ on the right
(debriefing), please select ‘Exceptional’ on the right
(confidentiality), please select ‘Exceptional’ on the right
!
Normal
!
Exceptional
!
Normal
!
Normal
!
Exceptional
NO
Exceptional
NO
NO
YES
YES
YES
N/A
29

From: administrator@psynet.hull.ac.uk [mailto:administrator@psynet.hull.ac.uk]  
Sent: 28 November 2015 21:42 
To: Mary-Ellen Large <M.Large@hull.ac.uk> 
Subject: Ethics Application approved (463033-1448458020)
!
Dear Dr M Large,
Ethics Application Approved
The following ethics application has been approved
Reference
463033-1448458020
Title
Change in frequency distributions of frustration
Classification
Exceptional
Researcher
T Strudwick (t.d.strudwick@2013.hull.ac.uk)
Principal (PI)
Dr M Large (m.large@hull.ac.uk)
Use the reference 463033-1448458020 in any correspondence about this application.
http://psy.hull.ac.uk/Committees/Ethics/Apply/
Best Regards,
!
Ethics Applications
Department of Psychology
University of Hull.
**************************************************
To view the terms under which this email is
distributed, please go to
http://www2.hull.ac.uk/legal/disclaimer.aspx
************************************************** 
30

8.2 - Appendix 2: Risk Assessment Form
RISK ASSESSMENT FORM – Department of Psychology University of
Hull
Name _Thomas Strudwick ___________ Supervisor _Mary-Ellen Large_____________
Title of Project: Change in frequency distributions of frustration
1. Where will the data be collected?
In the Department __X__
On the Campus _____
Outside _____ Please state location__________________________
2. Will any of the data collection take place outside of normal working hours?
Yes _____ No __X__ Sometimes _____
If yes conditions and precautions to be taken
___________________________________________________________________________
3. Who will be the subjects (e.g. Students, Patients)?
Students of the Univeristy of Hull
4. Will Psychometric test material be used?
Yes __X__ No __
5. Does any procedure being used involve drugs, chemicals, blood or abrasions of
the skin?
Yes _____ No __X__
If yes a COSHH assessment is required.
6. Please state test procedures to be used:
Participants will see a fixation cross closely followed by a picture. Participants are
required to press a corresponding computer key once the image disappears
depending on what they have been presented. After this they will be presented with a
measurement of their reaction time and a message of whether or not they made the
correct selection.
This continues until either all trials have been completed or the participant becomes
sufficiently frustrated with the programme that they no longer wish to continue or the
researchers stop the experiment.
After this, participants are asked to fill out a mood questionnaire designed to
measure how frustrated the task made them. This is done via the participant rating
possible emotions on a scale of 1 to 4 (1 being not experienced, 4 being definitely
experienced).
31

7. Will this project involve the carrying or movement of equipment?
Yes _____ No __X__
If yes please state what kind of equipment: _________N/A_____________________
8. Please state if there are any harmful effects in the test procedure or the
administration of test materials for the subject or experimenter and what
precautions will need to be taken
We are trying to invoke feelings of frustration in our subjects by making it
appear as if the keyboard is not working properly. The level of frustration will
be no more than a level associated with normal day-to-day use of
technology. To prevent extreme frustration, the experimenter will be present
during data collection and will stop the experiment immediately when the
frustration is observable (complaint, sighing, hitting key hard).
9. State training or instruction received for all methods or procedures in this
project:
Instruction received on what frustration cues to look for in the subjects so no
excessive frustration is experienced by the subjects.
Supervisors Assessment:
Risk associated with inducing frustration. The precautions in place are adequate and the
supervisor will be present during the pilot stage of this experiment to make sure there is no
harm (beyond normal frustration with equipment) to the participant or the student
experimenter.
Student signature ________________________________________ Date _______
Supervisor signature _____________________________________ Date ________
A PROJECT SHOULD NOT COMMENCE UNTIL A RISK ASSESSMENT
HAS BEEN CARRIED OUT
32

8.3 - Appendix 3: Project Design Form + Statement of Ethical Considerations
Project Design
Name of Student: Thomas Strudwick
Name of Supervisor: Dr Mary-Ellen Large
Provisional Title: Change in frequency distributions of frustration
Introduction and Background
There has been research concerning frustration in terms of the degree of control a
participant has on the cause in the context of work related frustration and the
influence this has on emotional and behavioural reactions. This showed that an
external cause of control resulted in a more counter productive action to the
frustration than an internal cause (Storms & Spector, 1987). Frustration has also
been research with a view of reducing frustration caused to the user. This was
completed with a view to conserve the patience of a user and result in a longer, less
stressful interaction. This was done via providing ‘affect-support modules’ which
acted as an emotional vent for the user. This study measured frustration by time it
took participants to use a ‘quit’ button on the programme (Klein, Moon, & Picard,
2002). Scheirer, Fernandez, Klein, and Picard, (2002) undertook similar research
using number of mouse clicks as a frustration indication along side a ‘faulty mouse’
program. This is an idea we liked but feel that a mouse movement would be too
disruptive to an EEG measurement and a track-ball would take too long for our
participants to get use to making the idea unviable. Why and Foo, (2010) looked at
frustration and control, finding a reliable cardiac affect using a similar faculty mouse
program but again, we feel mouse movement would disrupt EEG measurements.
Seeing as EEG research around frustration is limited, pilots must be carried out to
find out how and when participants become frustrated so we can meaningfully
identify, measure and analyse EEG traces for frustration.
Aims
The aim of this study is to devise an experiment which gives rise to an appropriate
level of frustration which could then be meaningfully analysed and tested via an EEG
experimental methodology.
Hypotheses / Research Questions
Hypothesis: Frustration with malfunctioning hardware will produce a change in
observable behaviour
Research questions: How quickly will frustration arise?
Will there be a sex difference in onset time of frustration?
Will a more difficult task make effect onset time of frustration?
33

Methodology
Task:
Participants will see a fixation cross closely followed by a picture (either an animal or
a landscape presented quickly and for only a brief period.
Participants are required to press a corresponding computer key once the image
disappears depending on which picture they have been presented. After this they will
be presented with a measurement of their reaction time and a message of whether
or not they made the correct selection.
As the blocks progress, the task will be modified so that incorrect feedback is given
no matter what the input of the participant. The ratio of normal to modified trials will
increase in successful blocks to placate frustration and allow the identification of a
frustration threshold. This continues until either all trials have been completed or the
participant becomes sufficiently frustrated with the programme that they no longer
wish to continue.
Materials and Equipment:
96 Images per block - 768 images in total plus 24 in practise trials (no image is
repeated). Computer required to display stimuli and record responses. SPSS
required to analyse data. Eprime used to present images.
Participants:
40 in total. Various ages, 18 or over.
Design:
Within Groups experimental design
Independent variables: Proportion of modified trials in each block and Block
sequence
Dependent variables: Questionnaire scores, Observed behaviour of participant
(forceful key presses, vocal objection etc.), Change in reaction time for ‘normal’ trials
Statistical Procedures
Repeated Measures ANOVA. t-tests then used to identify where the effect lies if a
significant direction is found.
Ethical / Risk Issues & Project Costs
We will be inducing a level of frustration in our participants but we aim for this to be
no more than what we would experience day-to-day via our use of technology and
computers. We will also be deceiving our participants by not telling them about our
aims regarding inducing frustration as not to confound the study. Participants will be
debriefed immediately after the experiment ends. This project has no costs.
34

References
Klein, J., Moon, Y., & Picard, R. W. (2002). This computer responds to user
frustration: Theory, design, and results. Interacting with Computers, 14(2),
119–140.
Scheirer, J., Fernandez, R., Klein, J., & Picard, R. W. (2002). Frustrating the user on
purpose: a step toward building an affective computer. Interacting with
Computers, 14(2), 93–118.
Storms, P. L., & Spector, P. E. (1987). Relationships of organizational frustration with
reported behavioral reactions: The moderating effect of locus of control.
Journal of Occupational Psychology, 60(3), 227–234.
Why, Y. P., & Foo, Y. (2010). The impact of task controllability on perceived control
and cardiovascular processes. Psychophysiology, 47(4), 669–672.
35

8.4 - Appendix 4: Participant Information sheet
Title: Object selection and decision-making
Researcher name: Thomas Strudwick & Dr Mary-Ellen Large
Purpose of Study
The Purpose of this study is to act as a pilot study to see if we can measure the differences
in neural frequencies involved in the selection and decision-making processes via EEG.
However little research has yet to be conducted in this area and as a result we need to
devise a robust method of facilitating the decision making process which we are interested
in. This could lead to developments in the understanding of the decision making process and
how emotion might affect this process.
Procedures
You will be presented with a stimulus on a computer screen for a short time (around 50m/s)
and then will be asked to identify whether the stimuli is an animal or otherwise by pressing
corresponding buttons on the keyboard. The stimuli will be presented in 8 blocks of 96
images with short breaks in between.
After this, we will require you to fill out a short questionnaire regarding how the pictures you
have observed have made you feel and some other aspects to your emotional state upon
completion of the task.
How much of your time will participation involve? 
The experiment should take approximately 45 minutes.
Will your participation in the project remain confidential? 
If you agree to take part, your name will not be recorded anywhere on the questionnaires or
your responses to the stimuli. Your data will be used for the purpose of this project only. You
will remain anonymous if you take part in the project and the information will not be
disclosed to other parties
Payment
There will be no payment for completion of this study
Potential Risks and Ethical Consideration
The main risk is associated with the questionnaire which may cause some discomfort when
answering some of the personal questions.
Benefits
Participation in the study might result in greater psychological understanding of the selection
and decision-making process. Upon request, the investigator will update you on the findings
of this study.
What happens now?
If you are interested in taking part in the study you are asked to complete and sign the
consent form. Then you will be given more specific instructions. Do not sign if you do
not wish to take part.
Please feel free to ask any questions that you may have at this point.
Contact for Further Information
Thomas Strudwick – t.d.strudwick@2013.hull.ac.uk
Dr Mary-Ellen Large – m.large@hull.ac.uk
If you have any concerns about the way in which the study has been conducted, you should
contact the Chair of the Department of psychology Ethics Committee on
ethics@psynet.hull.ac.uk
36

8.5 - Appendix 5: Participant Consent Form
Object selection and decision-making
Investigators: Thomas Strudwick & Dr Mary-Ellen Large
Department of Psychology, University of Hull
The participant should complete the whole of this sheet himself/herself. Please
cross out as necessary
• Have you read and understood the participant information sheet
YES/NO
• Have you had the opportunity to ask questions/discuss the study
YES/NO
• Have all the questions been answered satisfactorily
YES/NO
• Have you received enough information about the study
YES/NO
• Do you understand that you are free to withdraw from the study
at any time without having to give a reason
YES/NO
• Do you agree to take part in the study
YES/NO
This study has been explained to me to my satisfaction, and I agree to take part. I
understand that I am free to withdraw at any time.
Signature of the Participant :_______________________________________
Date: __________________
Name (in block capitals):
______________________________________________________
I have explained the study to the above participant and he/she has agreed to take
part.
Signature of researcher:
_______________________________________________________
Date: __________________
37

8.6 - Appendix 6 - Participant Debriefing Information
Title: Object selection decision-making
Principal Investigator and Researcher: Thomas Strudwick & Dr Mary-Ellen Large
Background and Research Question:
The aim of this study is to devise an experiment which gives rise to an appropriate
level of frustration similar to what may be experienced by using information
technology tools in a workplace or day-to-day life. We then want to use the findings
in this study to see if frustration could then be meaningfully analysed and tested via
an EEG experimental methodology. To do this we need to find an objective measure
of frustration as one does not yet exist due to limits of research around frustration
with the only indicator being heart rate and blood pressure of the subject (increased
heart rate/blood pressure = increased stress). Most of this research revolves around
the relationship between control over frustration cause and the level of frustration
caused. Here, the broad finding is that frustration level experienced increases with
amount of control the subject has. The main benefit of this research would be to
identify causes of stress to develop mitigations and use these to reduce stress in the
work place.
Anticipated findings:
Frustration with malfunctioning hardware will produce a change in observable
behaviour
Further information:
In this pilot study we have deliberately given you false feedback on your selections
between an animal and other images with the purpose of provoking a feeling of
frustration.
This has been done to find out exactly how much (or how little) input is needed on
our part to induce frustration in our participants. We are doing this to ensure we are
able to create enough of a frustrating situation to invoke the appropriate response
but not so much that our participants become unnecessarily frustrated. All of this will
enable us to decide if we can detect frustration via EEG and if this test can be used
in a future EEG study. It will also allow us to decide how many blocks of trials we will
need to run to reach an appropriate threshold of frustration.
If you are uncomfortable with having been deceived, you are free to withdraw your
data from the sample. Your results are confidential to us, experimenters, and all
results are published anonymously as a group of data.
If the frustration induced today or any other adverse emotions have arisen as a
result of this study you can contact the Hull University Student Wellbeing
Learning and Welfare Support Team on 01482 462020.
If you have any complaints, concerns, or questions about this research, please feel
free to contact, Dr Mary-Ellen Large (m.large@hull.ac.uk) or Thomas Strudwick
(t.d.strudwick@2013.hull.ac.uk)
Due to the deceptive nature of this research study it is necessary that you do not talk
to anyone about the content of this study or its real function as this would confound
the results of this study. Thank you in advance for your cooperation on this matter.
38

8.7 - Appendix 7: UWIST Mood Adjective Checklist (UMACL)
Mood Questionnaire
(-) Denotes a reverse score for this item
Hedonic Tone (H) Score: ___/16
Anger Item (A) Score: ___/20
Tense Arousal (T) Score: ___/12
Energetic Arousal (E) Score: ___/12
Cat. Definitely Not =
1
Slightly Not =
2
Slightly =
3
Definitely =
4
Happy H
Relaxed (-) T
Calm (-) T
Annoyed A
Tired (-) E
Energetic E
Irritated A
Satisfied H
Angry A
Sad (-) H
Anxious T
Impatient A
Cheerful H
Alert E
Grouchy A
39

8.8 - Appendix 8: SPSS Statistics Output
General Linear Model
Within-Subjects Factors
Measure: MEASURE_1
CatDT Block
Dependent
Variable
1 1 DBlock1
2 DBlock2
3 DBlock3
4 DBlock4
5 DBlock5
2 1 TBlock1
2 TBlock2
3 TBlock3
4 TBlock4
5 TBlock5
Descriptive Statistics
Mean Std. Deviation N
DBlock1 319.3179 47.30668 24
DBlock2 321.1100 64.84921 24
DBlock3 307.7971 72.76319 24
DBlock4 320.5771 98.95244 24
DBlock5 342.4971 94.86912 24
TBlock1 308.5796 52.13135 24
TBlock2 320.4913 69.68134 24
TBlock3 314.8625 68.24028 24
TBlock4 329.2025 109.30918 24
TBlock5 344.0650 96.70787 24
40

Mauchly's Test of Sphericitya
Measure: MEASURE_1
Within Subjects
Effect
Mauchly'
s W
Approx.
Chi-
Square df Sig.
Epsilonb
Greenhous
e-Geisser
Huynh-
Feldt
Lower-
bound
CatDT 1.000 .000 0 . 1.000 1.000 1.000
Block .289 26.598 9 .002 .662 .756 .250
CatDT * Block .601 10.894 9 .284 .783 .921 .250
Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent
variables is proportional to an identity matrix.
a. Design: Intercept
Within Subjects Design: CatDT + Block + CatDT * Block
b. May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are
displayed in the Tests of Within-Subjects Effects table.
Tests of Within-Subjects Effects
Measure: MEASURE_1
Source
Type III
Sum of
Squares df
Mean
Square F Sig.
Partial Eta
Squared
CatDT Sphericity
Assumed
83.591 1 83.591 .093 .763 .004
Greenhouse-
Geisser
83.591 1.000 83.591 .093 .763 .004
Huynh-Feldt 83.591 1.000 83.591 .093 .763 .004
Lower-bound 83.591 1.000 83.591 .093 .763 .004
Error(CatDT) Sphericity
Assumed
20702.119 23 900.092
Greenhouse-
Geisser
20702.119
23.00
0
900.092
Huynh-Feldt
20702.119
23.00
0
900.092
Lower-bound
20702.119
23.00
0
900.092
Block Sphericity
Assumed
30611.309 4 7652.827 1.693 .158 .069
Greenhouse-
Geisser
30611.309 2.647
11563.59
5
1.693 .183 .069
Huynh-Feldt
30611.309 3.023
10125.04
0
1.693 .176 .069
41

Lower-bound
30611.309 1.000
30611.30
9
1.693 .206 .069
Error(Block) Sphericity
Assumed
415816.89
4
92 4519.749
Greenhouse-
Geisser
415816.89
4
60.88
6
6829.443
Huynh-Feldt 415816.89
4
69.53
7
5979.834
Lower-bound 415816.89
4
23.00
0
18078.99
5
CatDT * Block Sphericity
Assumed
2826.060 4 706.515 2.426 .054 .095
Greenhouse-
Geisser
2826.060 3.134 901.800 2.426 .070 .095
Huynh-Feldt 2826.060 3.685 766.864 2.426 .059 .095
Lower-bound 2826.060 1.000 2826.060 2.426 .133 .095
Error(CatDT*Bl
ock)
Sphericity
Assumed
26796.945 92 291.271
Greenhouse-
Geisser
26796.945
72.07
7
371.780
Huynh-Feldt
26796.945
84.76
0
316.151
Lower-bound
26796.945
23.00
0
1165.085
Tests of Within-Subjects Contrasts
Measure: MEASURE_1
Source
Cat
DT Block
Type III
Sum of
Squares df
Mean
Square F Sig.
Partial Eta
Squared
CatDT Line
ar
83.591 1 83.591 .093 .763 .004
Error(CatDT) Line
ar
20702.119 23 900.092
Block Linear
18902.559 1
18902.55
9
3.649 .069 .137
Quadr
atic
7289.464 1 7289.464 1.944 .177 .078
Cubic 2147.952 1 2147.952 .306 .585 .013
Order
4
2271.334 1 2271.334 1.062 .313 .044
42

Error(Block) Linear 119137.27
7
23 5179.882
Quadr
atic
86228.208 23 3749.053
Cubic 161265.95
7
23 7011.563
Order
4
49185.451 23 2138.498
CatDT * Block Line
ar
Linear 1375.529 1 1375.529 6.176 .021 .212
Quadr
atic
1404.425 1 1404.425 4.706 .041 .170
Cubic 45.862 1 45.862 .136 .716 .006
Order
4
.245 1 .245 .001 .978 .000
Error(CatDT*Bl
ock)
Line
ar
Linear 5122.876 23 222.734
Quadr
atic
6863.795 23 298.426
Cubic 7781.637 23 338.332
Order
4
7028.637 23 305.593
Tests of Between-Subjects Effects
Measure: MEASURE_1
Transformed Variable: Average
Source
Type III Sum
of Squares df Mean Square F Sig.
Partial Eta
Squared
Intercep
t
25015709.400 1 25015709.400 569.624 .000 .961
Error 1010072.581 23 43916.199
43

Within-Subjects Factors
Measure: MEASURE_1
Block Dependent Variable
1 TBlock1
2 TBlock2
3 TBlock3
4 TBlock4
5 TBlock5
Measure: MEASURE_1
Within Subjects
Effect
Mauchly'
s W
Approx.
Chi-
Square df Sig.
Epsilonb
Greenhous
e-Geisser
Huynh-
Feldt
Lower-
bound
Block .274 27.724 9 .001 .648 .737 .250
Within Subjects Design: Block
Measure: MEASURE_1
Source
Type III Sum
of Squares df
Mean
Square F Sig.
Block Sphericity Assumed 18280.744 4 4570.186 1.859 .124
Greenhouse-Geisser 18280.744 2.591 7056.386 1.859 .154
Huynh-Feldt 18280.744 2.948 6200.110 1.859 .146
Lower-bound 18280.744 1.000 18280.744 1.859 .186
Error(Block
)
Sphericity Assumed 226186.444 92 2458.548
Greenhouse-Geisser 226186.444 59.585 3796.009
Huynh-Feldt 226186.444 67.814 3335.372
Lower-bound 226186.444 23.000 9834.193
44

Measure: MEASURE_1
Source Block
Type III Sum
Block Linear 15238.163 1 15238.163 5.608 .027
Quadratic 1147.335 1 1147.335 .545 .468
Cubic 783.046 1 783.046 .228 .638
Order 4 1112.201 1 1112.201 .705 .410
Error(Block) Linear 62501.215 23 2717.444
Quadratic 48396.982 23 2104.217
Cubic 79004.874 23 3434.995
Order 4 36283.372 23 1577.538
Measure: MEASURE_1
Source
Type III Sum
Intercep
t
12553624.970 1 12553624.970 529.764 .000
Error 545022.248 23 23696.619
45

Within-Subjects
Factors
Measure: MEASURE_1
Bloc
k
Dependent
Variable
1 DBlock1
2 DBlock2
3 DBlock3
4 DBlock4
5 DBlock5
Measure: MEASURE_1
Within Subjects
Effect
Mauchly'
s W
Approx.
Chi-
Square df Sig.
Epsilonb
Greenhous
e-Geisser
Huynh-
Feldt
Lower-
bound
Block .390 20.189 9 .017 .713 .825 .250
Within Subjects Design: Block
46

- End of Document -
Measure: MEASURE_1
Source
Type III Sum
of Squares df
Mean
Square F Sig.
Block Sphericity Assumed 15156.626 4 3789.156 1.611 .178
Greenhouse-Geisser 15156.626 2.853 5312.508 1.611 .197
Huynh-Feldt 15156.626 3.299 4593.807 1.611 .190
Lower-bound 15156.626 1.000 15156.626 1.611 .217
Error(Block
)
Sphericity Assumed 216427.395 92 2352.472
Greenhouse-Geisser 216427.395 65.619 3298.234
Huynh-Feldt 216427.395 75.885 2852.034
Lower-bound 216427.395 23.000 9409.887
Measure: MEASURE_1
Source Block
Type III Sum
Block Linear 5039.925 1 5039.925 1.877 .184
Quadratic 7546.554 1 7546.554 3.883 .061
Cubic 1410.768 1 1410.768 .360 .554
Order 4 1159.378 1 1159.378 1.338 .259
Error(Block) Linear 61758.938 23 2685.171
Quadratic 44695.020 23 1943.262
Cubic 90042.721 23 3914.901
Order 4 19930.716 23 866.553
Measure: MEASURE_1
Source
Type III Sum
Intercep
t
12462168.022 1 12462168.022 590.074 .000
Error 485752.451 23 21119.672
47

STRUDWICK Dissertation Document Misc Copy

Recommended

Recommended

More Related Content

What's hot

What's hot (14)

Viewers also liked

Viewers also liked (11)

Similar to STRUDWICK Dissertation Document Misc Copy

Similar to STRUDWICK Dissertation Document Misc Copy (20)

STRUDWICK Dissertation Document Misc Copy