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 -

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

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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.

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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.

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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

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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

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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.

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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

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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

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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.

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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,

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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

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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%

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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

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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.

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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

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! 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.

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! 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

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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

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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

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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

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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 Brit ish 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

http://www.bps.org.uk/system/files/documents/code_of_ethics_and_conduct.pdf






1. RISKSIf 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')?* If YES, please specify: Click here to enter text.

4) Does the study require access to confidential sources of information (e.g. medical records)? If YES, please specify: Click here to enter text.

5) Could the intended participants for the study be expected to be more than usually emotionally vulnerable (e.g. medical patients, bereaved individuals)? If YES, please specify: Click here to enter text.

6) Will the study take place in a setting other than the University campus or student accommodation? If YES, please specify: Click here to enter text.

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

http://psy.hull.ac.uk/Documents/Ethics/


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

If you have answered ‘NO’ to any of the questions in Section 4 (debriefing), please select ‘Exceptional’ on the right

If you have answered ‘NO’ to any of the questions in Section 5 (confidentiality), please select ‘Exceptional’ on the right

! Normal

! Exceptional

! Normal

! Normal

! Exceptional

NO

Exceptional

NO

NO

YES

YES

YES

N/A

�29

http://psy.hull.ac.uk/Committees/Ethics/Checklist/


From: [email protected] [mailto:[email protected]] Sent: 28 November 2015 21:42 To: Mary-Ellen Large <[email protected]>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 ([email protected]) Principal (PI)

Dr M Large ([email protected])

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

mailto:[email protected]





http://psy.hull.ac.uk/Committees/Ethics/Apply/

http://www2.hull.ac.uk/legal/disclaimer.aspx


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 DesignName 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 – [email protected] Dr Mary-Ellen Large – [email protected]

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 [email protected]

�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 ([email protected]) or Thomas Strudwick ([email protected])

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

Assumed83.591 1 83.591 .093 .763 .004

Greenhouse-

Geisser83.591 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

Assumed20702.119 23 900.092

Greenhouse-

Geisser20702.119

23.00

0900.092

Huynh-Feldt20702.119

23.00

0900.092

Lower-bound20702.119

23.00

0900.092

Block Sphericity

Assumed30611.309 4 7652.827 1.693 .158 .069

Greenhouse-

Geisser30611.309 2.647

11563.59

51.693 .183 .069

Huynh-Feldt30611.309 3.023

10125.04

01.693 .176 .069

�41


Lower-bound30611.309 1.000

30611.30

91.693 .206 .069

Error(Block) Sphericity

Assumed

415816.89

492 4519.749

Greenhouse-

Geisser

415816.89

4

60.88

66829.443

Huynh-Feldt 415816.89

4

69.53

75979.834

Lower-bound 415816.89

4

23.00

0

18078.99

5

CatDT * Block Sphericity

Assumed2826.060 4 706.515 2.426 .054 .095

Greenhouse-

Geisser2826.060 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

Assumed26796.945 92 291.271

Greenhouse-

Geisser26796.945

72.07

7371.780

Huynh-Feldt26796.945

84.76

0316.151

Lower-bound26796.945

23.00

01165.085

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

ar83.591 1 83.591 .093 .763 .004

Error(CatDT) Line

ar20702.119 23 900.092

Block Linear18902.559 1

18902.55

93.649 .069 .137

Quadr

atic7289.464 1 7289.464 1.944 .177 .078

Cubic 2147.952 1 2147.952 .306 .585 .013

Order

42271.334 1 2271.334 1.062 .313 .044

�42


Error(Block) Linear 119137.27

723 5179.882

Quadr

atic86228.208 23 3749.053

Cubic 161265.95

723 7011.563

Order

449185.451 23 2138.498

CatDT * Block Line

ar

Linear 1375.529 1 1375.529 6.176 .021 .212

Quadr

atic1404.425 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

atic6863.795 23 298.426

Cubic 7781.637 23 338.332

Order

47028.637 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

t25015709.400 1 25015709.400 569.624 .000 .961

Error 1010072.581 23 43916.199

�43


General Linear Model

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

t12553624.970 1 12553624.970 529.764 .000

Error 545022.248 23 23696.619

�45


General Linear Model 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

t12462168.022 1 12462168.022 590.074 .000

Error 485752.451 23 21119.672

�47

STRUDWICK Dissertation Document Misc Copy

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