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                <text>Facts May Care About Your Feelings:  The Effects of Empirical and Anecdotal Evidence in the Perception of Climate Change </text>
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                <text>Constance Jordan-Turner</text>
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                <text>Although the effects of humanmade climate change become ever more potent, the consensus gap between climate scientists and the public is as wide as ever. It is critical that climate change communication is improved to try and close this gap. There are several strategies that can be implemented, including using anecdotes alongside or instead of empirical evidence to elicit emotions. In this study, 74 members of the public completed a survey.  Participants were randomly assigned to one of four conditions which dictated the type of evidence they received: no evidence, empirical evidence, anecdotal evidence, or both empirical and anecdotal evidence.  Results suggest that, in general, there was no effect of evidence on participants’ perceptions of climate change. This result held even after controlling for worldview and ideology. These findings have implications for the theory of inserting emotion into climate change communication.</text>
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                <text>Participants and design&#13;
There were 74 participants (26 male; 46 female; one non-binary; one preferred not to say). The mean age of the participants was 37.99 (SD = 16.93). Participants were recruited via advertising the study on the researcher’s social media accounts (Facebook and Instagram) using a standardised advertisement (see Appendix A) and through word of mouth. Participants were all members of the general public. The study manipulated two independent variables in a between-participants design: anecdotal evidence (without-anecdotal vs. with-anecdotal) and empirical evidence (without-empirical vs. with empirical), resulting in four conditions. Participants were randomly allocated to one of the four conditions, subject to the constraint of equal cell numbers. &#13;
&#13;
This study gained ethical approval from the Faculty of Science and Technology Research Ethics Committee.&#13;
Participants and design&#13;
There were 74 participants (26 male; 46 female; one non-binary; one preferred not to say). The mean age of the participants was 37.99 (SD = 16.93). Participants were recruited via advertising the study on the researcher’s social media accounts (Facebook and Instagram) using a standardised advertisement (see Appendix A) and through word of mouth. Participants were all members of the general public. The study manipulated two independent variables in a between-participants design: anecdotal evidence (without-anecdotal vs. with-anecdotal) and empirical evidence (without-empirical vs. with empirical), resulting in four conditions. Participants were randomly allocated to one of the four conditions, subject to the constraint of equal cell numbers. &#13;
Evidence Passages&#13;
Empirical Evidence&#13;
The empirical evidence vignette included a statement explaining that human-induced carbon dioxide emissions and global average temperature have synchronously increased since pre-industrial times, accompanied with graphs demonstrating these upward trends.  The vignette also highlighted the scientific consensus that humanmade climate change is occurring and will have adverse consequences. Finally, the vignette explained that these adverse consequences had already begun to materialise.  The increase of extreme weather events was highlighted in a graph that showed the tripling of weather-related disasters between 1980 and 2010.  Finally, the vignette finished with references for the information it contained (see Appendix B).&#13;
Anecdotal Evidence&#13;
The anecdotal evidence vignette contained information about Storms Dudley, Eunice and Franklin which all made landfall in Britain in quick succession in 2022. The storms were a weather-related event that some scientists have linked to climate change (Barrett, 2022); Specifically, the vignette included information about the storms’ destructiveness, such as the cost of the damage they caused, and the number of people killed.  The destructiveness of the storms was highlighted with images of damage and flooding in Wells, Otley, and Brentwood, as well as an image from Blackpool demonstrating the height and power of the waves caused by the storms.  The vignette included a stock image of a man standing in a flooded living room and a short passage outlining the experience of a fictitious character named Matt Johnson whose family home had been severely flooded as a result of the storms. The vignette concluded with a statement from climate scientist Robert Klein who argued that the impact of the storm was exacerbated by climate change, which generated “super storm” conditions.  Finally, there was a reference to an article about the storms and their link to climate change (see Appendix C).&#13;
Measures&#13;
Table 1 contains an overview of the measures embedded in the questionnaire.  For the full questionnaire, please refer to Appendix D.&#13;
Disaster Belief&#13;
The disaster belief measure measured predicted estimates of the frequency of weather-related disasters that will occur in the listed years. Participants were given an approximate frequency for 2019 from the International Disaster Database. The measure consisted of six items: 2030, 2040, 2050, 2060, 2070 and 2080. Participants responded by typing in their estimated number next to the relevant year.&#13;
Harm Extent&#13;
The harm extent measure consisted of questions concerning how much harm that participants think climate change will cause themselves, their family, their community, Britain, other countries, and future generations. There were six items, such as ‘How much do you think climate change will harm you?’, and ‘How much do you think climate change will harm people in Britain?’ Responses were rated from (1) ‘not at all’ to (4) ‘a great deal’.&#13;
Harm Timing&#13;
	The harm timing measure consisted of questions concerning when participants thought climate change will cause harm to themselves, their family, their community, Britain, other countries, and future generations. There were only two items, ‘When do you think climate change will begin to harm Britain?’ and ‘When do you think climate change will begin to harm other countries?’. Responses were rated as (1) ‘Never’, (2) ‘100 years’; (3) ‘50 years’; (4) ‘25 years’; (5) ‘10 years’ and (6) ‘Right now’.&#13;
CO2 Attributions&#13;
	The CO2 attributions measure measured how much participants think human carbon dioxide emissions contribute to events such as heatwaves, rising sea levels, flooding, and Storms Dudley, Eunice, and Franklin. There were six items, such as ‘CO2 contribution to the observed increase in atmospheric temperature during the last 130 years’, ‘CO2 contribution to the European heat wave in 2022 that killed over 5,000 people’, and ‘CO2 contribution to storms Dudley, Eunice, and Franklin in the UK (2022)’. These responses were gathered using a sliding scale from 0 to 100%.&#13;
Intention&#13;
The intention measure consisted of questions asking about participants’ pro-environmental intentions. There were seven items. Examples of items include ‘I will take part in an environmental event (e.g., Earth hour)’, ‘I will give money to a group that aims to protect the environment’, and ‘I will switch to products that are more environmentally friendly’. The response options were simply ‘Yes’ or ‘No’.   &#13;
Mitigation&#13;
	The mitigation measure consisted of questions asking about participants’ support for mitigating policies. There were five items. Example items include, ‘Signing an international treaty that requires Britain to cut its carbon dioxide emissions by 90% by 2050’, ‘Adding a surcharge to electrical bills to establish a fund to help make buildings more energy efficient and to teach British citizens how to reduce energy use’, and ‘Providing tax rebates for people who purchase energy-efficient vehicles or solar panels’. Responses were rated from (1) ‘Strongly Oppose’ to (4) ‘Strongly Support’.&#13;
CO2 Adjustment&#13;
	The CO2 adjustment measure measures how much participants think Britain should adjust its CO2 emissions over the next 10 years. There was only one item: ‘How much should Britain adjust CO2 emissions during the next 10 years?’. Responses were rated from (1) ‘Not at all’ to (6) ‘Reduce by 50%’.&#13;
Free-Market Support&#13;
	The free-market support measure consisted of questions asking about participants’ support for the free market. There were five items. Examples items include, ‘An economic system based on free-markets, unrestrained by government interference, automatically works best to meet human needs’ and ‘The preservation of the free-market system is more important than localized environmental concerns’. Two items, ‘Free and unregulated markets pose important threats to sustainable development’ and ‘The free-market system is likely to promote unsustainable consumption’, required reverse coding upon analysis.&#13;
Table 1&#13;
Measures embedded within the questionnaire. The first column contains the name of the measures; the second column contains the instructions on how to respond to items in that measure; and the third column describes how answers to the items were coded.   &#13;
Measure Name	Questions	Coded Response&#13;
Disaster belief	Please provide an estimate of the frequency of weather-related disasters that will occur in each year (6 items).	Participants used the keyboard to type in a number for each year.&#13;
Harm extent	The following items examine your thoughts about the extent of harm that will be caused by climate change (6 items).	4-point scale: (1) ‘Not at all’; (2) ‘A little’; (3) ‘A moderate amount’; (4) ‘A great deal’.&#13;
Harm timing	The following items examine your thoughts about when climate change will begin to cause harm (2 items).	6-point scale: (1) ‘Never’; (2) ‘100 years’; (3) ‘50 years’; (4) ‘25 years’; (5) ‘10 years’; (6) ‘Right now’.&#13;
CO2 attribution	For each of the following questions, please estimate the contribution from human CO2 emissions to cause each event. For example, 0% would mean humans are not at all responsible, whereas 100% would mean that human CO2 emissions are fully responsible&#13;
	Participants used the mouse to place their response on a sliding scale. The sliding scale contained the numbers, ‘0’, ‘10’, ‘20’, ‘30’, ‘40’, ‘50’, ‘60’, ‘70’, ‘80’, ‘90’, and ‘100’. &#13;
&#13;
&#13;
&#13;
Pro-environmental intentions	Please indicate whether or not you will engage in the following actions (7 items).	0 = No&#13;
1 = Yes&#13;
Mitigation	How much do you support or oppose the following policies (five items).  	4-point scale; (1) ‘Strongly Oppose’; (2) ‘Oppose’; (3) ‘Support’; (4) ‘Strongly Support’.&#13;
CO2 adjustment	How much should Britain adjust CO2 emissions during the next 10 years?	6-point scale; (1) ‘Not at all’; (2) ‘Reduce by 10%’; (3) ‘Reduce by 20%’; (4) ‘Reduce by 30%’; (5) ‘Reduce by 40%’; (6) ‘Reduce by 50%’.&#13;
Free-market belief	Please indicate how much you agree with each statement (5 items).	5-point scale: (1) ‘Strongly Disagree’; (2) ‘Disagree’; (3) ‘Neutral’; (4) ‘Agree’; (5) ‘Strongly Agree’.&#13;
Demographic questions	What is your age?	Participants used the keyboard to type in a number.&#13;
	What is your gender?	1 = Male; 2 = Female; 3 = Non-binary; 4 = Other; 5 = Prefer Not to Say&#13;
&#13;
Procedure&#13;
All participants completed a questionnaire assessing their belief in and concern about humanmade climate change and their mitigation beliefs.  The questionnaire was administered online using Qualtrics survey software.  Participants responded to the questionnaire by using either the mouse to select answers or the keyboard to type in numbers. &#13;
At the beginning of the questionnaire, all participants received an information sheet about the aim of the study, the lack of risks associated with participating, and how participant information is stored. Participants were asked to indicate their informed consent. For the full participant information sheet and consent form, please refer to Appendix E. After participants gave their consent and continued onto the survey, they were asked their age and gender. They were then presented with evidence according to the condition they were assigned to.  There were four conditions: no evidence, empirical evidence, anecdotal evidence, and both empirical and anecdotal evidence.&#13;
After they had read one or both evidence passages, participants answered the disaster belief measure. Next, they answered the CO2 attribution measure. Then they answered the harm extent measure and the harm timing measure. After that was the intention measure, and then they answered the mitigation measure. In the final part of the questionnaire, they were asked how much Britain should cut its CO2 emissions over ten years, and then questions on their support for the free market. Participants were then asked demographic questions about their age and gender. Finally, the participants were given a debrief sheet (Appendix F).</text>
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                <text>Although the effects of humanmade climate change become ever more potent, the consensus gap between climate scientists and the public is as wide as ever. It is critical that climate change communication is improved to try and close this gap. There are several strategies that can be implemented, including using anecdotes alongside or instead of empirical evidence to elicit emotions. In this study, 74 members of the public completed a survey.  Participants were randomly assigned to one of four conditions which dictated the type of evidence they received: no evidence, empirical evidence, anecdotal evidence, or both empirical and anecdotal evidence.  Results suggest that, in general, there was no effect of evidence on participants’ perceptions of climate change. This result held even after controlling for worldview and ideology. These findings have implications for the theory of inserting emotion into climate change communication.</text>
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                <text>This study gained ethical approval from the Faculty of Science and Technology Research Ethics Committee.&#13;
Participants and design&#13;
There were 74 participants (26 male; 46 female; one non-binary; one preferred not to say). The mean age of the participants was 37.99 (SD = 16.93). Participants were recruited via advertising the study on the researcher’s social media accounts (Facebook and Instagram) using a standardised advertisement (see Appendix A) and through word of mouth. Participants were all members of the general public. The study manipulated two independent variables in a between-participants design: anecdotal evidence (without-anecdotal vs. with-anecdotal) and empirical evidence (without-empirical vs. with empirical), resulting in four conditions. Participants were randomly allocated to one of the four conditions, subject to the constraint of equal cell numbers. &#13;
Evidence Passages&#13;
Empirical Evidence&#13;
The empirical evidence vignette included a statement explaining that human-induced carbon dioxide emissions and global average temperature have synchronously increased since pre-industrial times, accompanied with graphs demonstrating these upward trends.  The vignette also highlighted the scientific consensus that humanmade climate change is occurring and will have adverse consequences. Finally, the vignette explained that these adverse consequences had already begun to materialise.  The increase of extreme weather events was highlighted in a graph that showed the tripling of weather-related disasters between 1980 and 2010.  Finally, the vignette finished with references for the information it contained (see Appendix B).&#13;
Anecdotal Evidence&#13;
The anecdotal evidence vignette contained information about Storms Dudley, Eunice and Franklin which all made landfall in Britain in quick succession in 2022. The storms were a weather-related event that some scientists have linked to climate change (Barrett, 2022); Specifically, the vignette included information about the storms’ destructiveness, such as the cost of the damage they caused, and the number of people killed.  The destructiveness of the storms was highlighted with images of damage and flooding in Wells, Otley, and Brentwood, as well as an image from Blackpool demonstrating the height and power of the waves caused by the storms.  The vignette included a stock image of a man standing in a flooded living room and a short passage outlining the experience of a fictitious character named Matt Johnson whose family home had been severely flooded as a result of the storms. The vignette concluded with a statement from climate scientist Robert Klein who argued that the impact of the storm was exacerbated by climate change, which generated “super storm” conditions.  Finally, there was a reference to an article about the storms and their link to climate change (see Appendix C).&#13;
Measures&#13;
Table 1 contains an overview of the measures embedded in the questionnaire.  For the full questionnaire, please refer to Appendix D.&#13;
Disaster Belief&#13;
The disaster belief measure measured predicted estimates of the frequency of weather-related disasters that will occur in the listed years. Participants were given an approximate frequency for 2019 from the International Disaster Database. The measure consisted of six items: 2030, 2040, 2050, 2060, 2070 and 2080. Participants responded by typing in their estimated number next to the relevant year.&#13;
Harm Extent&#13;
The harm extent measure consisted of questions concerning how much harm that participants think climate change will cause themselves, their family, their community, Britain, other countries, and future generations. There were six items, such as ‘How much do you think climate change will harm you?’, and ‘How much do you think climate change will harm people in Britain?’ Responses were rated from (1) ‘not at all’ to (4) ‘a great deal’.&#13;
Harm Timing&#13;
	The harm timing measure consisted of questions concerning when participants thought climate change will cause harm to themselves, their family, their community, Britain, other countries, and future generations. There were only two items, ‘When do you think climate change will begin to harm Britain?’ and ‘When do you think climate change will begin to harm other countries?’. Responses were rated as (1) ‘Never’, (2) ‘100 years’; (3) ‘50 years’; (4) ‘25 years’; (5) ‘10 years’ and (6) ‘Right now’.&#13;
CO2 Attributions&#13;
	The CO2 attributions measure measured how much participants think human carbon dioxide emissions contribute to events such as heatwaves, rising sea levels, flooding, and Storms Dudley, Eunice, and Franklin. There were six items, such as ‘CO2 contribution to the observed increase in atmospheric temperature during the last 130 years’, ‘CO2 contribution to the European heat wave in 2022 that killed over 5,000 people’, and ‘CO2 contribution to storms Dudley, Eunice, and Franklin in the UK (2022)’. These responses were gathered using a sliding scale from 0 to 100%.&#13;
Intention&#13;
The intention measure consisted of questions asking about participants’ pro-environmental intentions. There were seven items. Examples of items include ‘I will take part in an environmental event (e.g., Earth hour)’, ‘I will give money to a group that aims to protect the environment’, and ‘I will switch to products that are more environmentally friendly’. The response options were simply ‘Yes’ or ‘No’.   &#13;
Mitigation&#13;
	The mitigation measure consisted of questions asking about participants’ support for mitigating policies. There were five items. Example items include, ‘Signing an international treaty that requires Britain to cut its carbon dioxide emissions by 90% by 2050’, ‘Adding a surcharge to electrical bills to establish a fund to help make buildings more energy efficient and to teach British citizens how to reduce energy use’, and ‘Providing tax rebates for people who purchase energy-efficient vehicles or solar panels’. Responses were rated from (1) ‘Strongly Oppose’ to (4) ‘Strongly Support’.&#13;
CO2 Adjustment&#13;
	The CO2 adjustment measure measures how much participants think Britain should adjust its CO2 emissions over the next 10 years. There was only one item: ‘How much should Britain adjust CO2 emissions during the next 10 years?’. Responses were rated from (1) ‘Not at all’ to (6) ‘Reduce by 50%’.&#13;
Free-Market Support&#13;
	The free-market support measure consisted of questions asking about participants’ support for the free market. There were five items. Examples items include, ‘An economic system based on free-markets, unrestrained by government interference, automatically works best to meet human needs’ and ‘The preservation of the free-market system is more important than localized environmental concerns’. Two items, ‘Free and unregulated markets pose important threats to sustainable development’ and ‘The free-market system is likely to promote unsustainable consumption’, required reverse coding upon analysis.&#13;
Table 1&#13;
Measures embedded within the questionnaire. The first column contains the name of the measures; the second column contains the instructions on how to respond to items in that measure; and the third column describes how answers to the items were coded.   &#13;
Measure Name	Questions	Coded Response&#13;
Disaster belief	Please provide an estimate of the frequency of weather-related disasters that will occur in each year (6 items).	Participants used the keyboard to type in a number for each year.&#13;
Harm extent	The following items examine your thoughts about the extent of harm that will be caused by climate change (6 items).	4-point scale: (1) ‘Not at all’; (2) ‘A little’; (3) ‘A moderate amount’; (4) ‘A great deal’.&#13;
Harm timing	The following items examine your thoughts about when climate change will begin to cause harm (2 items).	6-point scale: (1) ‘Never’; (2) ‘100 years’; (3) ‘50 years’; (4) ‘25 years’; (5) ‘10 years’; (6) ‘Right now’.&#13;
CO2 attribution	For each of the following questions, please estimate the contribution from human CO2 emissions to cause each event. For example, 0% would mean humans are not at all responsible, whereas 100% would mean that human CO2 emissions are fully responsible&#13;
	Participants used the mouse to place their response on a sliding scale. The sliding scale contained the numbers, ‘0’, ‘10’, ‘20’, ‘30’, ‘40’, ‘50’, ‘60’, ‘70’, ‘80’, ‘90’, and ‘100’. &#13;
&#13;
&#13;
&#13;
Pro-environmental intentions	Please indicate whether or not you will engage in the following actions (7 items).	0 = No&#13;
1 = Yes&#13;
Mitigation	How much do you support or oppose the following policies (five items).  	4-point scale; (1) ‘Strongly Oppose’; (2) ‘Oppose’; (3) ‘Support’; (4) ‘Strongly Support’.&#13;
CO2 adjustment	How much should Britain adjust CO2 emissions during the next 10 years?	6-point scale; (1) ‘Not at all’; (2) ‘Reduce by 10%’; (3) ‘Reduce by 20%’; (4) ‘Reduce by 30%’; (5) ‘Reduce by 40%’; (6) ‘Reduce by 50%’.&#13;
Free-market belief	Please indicate how much you agree with each statement (5 items).	5-point scale: (1) ‘Strongly Disagree’; (2) ‘Disagree’; (3) ‘Neutral’; (4) ‘Agree’; (5) ‘Strongly Agree’.&#13;
Demographic questions	What is your age?	Participants used the keyboard to type in a number.&#13;
	What is your gender?	1 = Male; 2 = Female; 3 = Non-binary; 4 = Other; 5 = Prefer Not to Say&#13;
&#13;
Procedure&#13;
All participants completed a questionnaire assessing their belief in and concern about humanmade climate change and their mitigation beliefs.  The questionnaire was administered online using Qualtrics survey software.  Participants responded to the questionnaire by using either the mouse to select answers or the keyboard to type in numbers. &#13;
At the beginning of the questionnaire, all participants received an information sheet about the aim of the study, the lack of risks associated with participating, and how participant information is stored. Participants were asked to indicate their informed consent. For the full participant information sheet and consent form, please refer to Appendix E. After participants gave their consent and continued onto the survey, they were asked their age and gender. They were then presented with evidence according to the condition they were assigned to.  There were four conditions: no evidence, empirical evidence, anecdotal evidence, and both empirical and anecdotal evidence.&#13;
After they had read one or both evidence passages, participants answered the disaster belief measure. Next, they answered the CO2 attribution measure. Then they answered the harm extent measure and the harm timing measure. After that was the intention measure, and then they answered the mitigation measure. In the final part of the questionnaire, they were asked how much Britain should cut its CO2 emissions over ten years, and then questions on their support for the free market. Participants were then asked demographic questions about their age and gender. Finally, the participants were given a debrief sheet (Appendix F).&#13;
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                  <text>Electroencephalography (EEG) is a method for monitoring electrical activity in the brain. It uses electrodes placed on or below the scalp to record activity with coarse spatial but high temporal resolution</text>
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                <text>Effect of Attention and Noise on Echoic Memory as Indexed by the N1-Adaptation. </text>
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                <text>Ekenedilichukwu Tonia Osakwe</text>
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                <text>There are numerous studies that support the notion that echoic memory is indexed by the adaptation of the N1 peak in auditory event related potentials (ERPs). Although the number research on the effects of parameters like noise and attention on the amplitude of the N1 is immense, to date there are no studies on the effect of these parameters on the adaptation of the N1. Here, I investigated the effect of noise and attention on the adaptation of N1, P2 and N1-P2. Secondary analysis was conducted on data collected from 33 participants in three conditions:  passive recording condition (participant listen passively to stimulus while staring at a fixation cross); attention/oddball conditions (participant were task with counting the deviating tones); and noise condition where the tones are presented in white noise. Within each condition, two Stimulus onset intervals (SOI): 1.7 s and 3.5 were used in separate stimulus blocks and the ratio R = M1.7s / M3.5s was used as a dimensionless measure of adaptation. My results found no significant effect of noise an attention on the amplitudes and adaption of the N1, P2 and N1-P2. I propose that the lack of effect on the adaption of the ERPS might be due to noise and attention having a scaling effect on all of the amplitudes equally so that adaption lifetime is not affected. As this is the first study of its kind, further research will be needed to gain a better understanding of how adaptation is affected by these two factors. </text>
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                <text>Attention, Noise, N1-adaptation, auditory sensory memory</text>
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                <text>Participants&#13;
This project carries out secondary analysis on data from an EEG experiment with 33 human participants. The data  was received from supervisor, Patrick May.  The participants were all adult undergraduate and post graduate students at Lancaster University, with no self-reported hearing loss or neurological disorder. The experiment was approved by the research ethics procedures of the Department of Psychology, Lancaster University, and the participants provided written consent before the experiment began. &#13;
&#13;
Equipment and Procedure for EEG measurements&#13;
Three dry electrodes were attached at locations: Fpz, Fz, Cz. Reference and ground electrodes were attached to the right ear lobe. For this report, only the data acquired from the Fz location was used as this is the channel that recorded the best ERPs for all the participants. The participants were directed to passively listen to stimuli while staring at a fixation cross and moving and blinking as little as possible. The stimuli comprised of 500-Hz pure tones with a duration of 100ms, including 10-ms linear onset and offset ramps. The stimuli were presented in blocks of 100 isochronous stimuli. The stimuli were presented binaurally via Sennheiser headphones using laboratory laptop and MATLAB interfaced with the Enobio EEG device in a soundproof chamber. Data was collected in three conditions: baseline passive recording condition (participant listen passively to stimulus while staring at a fixation cross); attention/oddball conditions (participant were task with counting the deviating tones); and noise condition where the tones are presented in white noise. Withing each condition, two Stimulus onset interval (SOI): 1.7 s and 3.5 were used in separate stimulus blocks. The order of experiments were randomised across the participants. &#13;
Data Analysis&#13;
The data was passband filtered at 1-30 Hz and sectioned into epochs of single trial data. To remove artefacts (e.g., due to blinking) 15% of epochs with the largest absolute amplitudes were removed. Single trial epochs was then averaged to reveal the ERP. The average ERP in a 100ms time window immediately preceding stimulus onset was calculated and subtracted from the whole ERP (baseline correction). The N1 is not the only peak that shows adaptation in auditory ERPS. Although many of the research on adaption is focused on the N1 peak, different researchers have looked at other auditory ERP peaks in relation to adaptations such as the P2 and P3 peaks. In fact, Lanting et al. (2013)  found that the P2 was more very strongly affected by adaption than the N1. In addition, the peak-to-peak difference between the N1 and the P2 has been previously used to estimate adaptation in several studies as it provides a more reliable measure of activity in auditory cortex because as it has the advantage of not being dependent on the baseline activity which can be noisy (Lanting et al., 2013; Lavoie et al., 2008; Muller-Gass et al., 2008). Because of this, both the N1 and the P2 peaks were identified - the N1 was identified as the peak negativity at around 100ms and P2 peak positivity at around 200ms. The peak-to-peak difference between the N1 and the P2  was calculated and the N1 and P2 amplitude as well as the difference between the N1 and P2 amplitude was used to estimate the lifetime of adaptation. Statistical data analysis was conducted using Analysis of Variance (ANOVA). Specifically, three one-way (condition) and three two-way (SOI x condition) repeated measures ANOVAs was conducted of the N1, P2 and the difference between the N1 and P2 amplitudes and amplitude ratios respectively. &#13;
&#13;
Calculating the lifetime of adaptation (τ)&#13;
The recovery time constant for adaptation is usually calculated by fitting an exponentially saturating function to peak amplitudes plotted across SOIs (Lu et al., 1992). This curve is characterized by  as well as by two other fitting parameters: asymptotic magnitude and crossing point on SOI axis. The parameter  determines the steepness of the magnitude curve: the smaller its value, the quicker the curve approaches the asymptote (i.e., levels out) as SOI is increased. The SOIs where this levelling out has occurred represent stimulation where the silent period between two consecutive stimuli is large enough for adaptation to have died away. Therefore,  expresses the lifetime of adaptation: with low values, the curve levels out to its maximum value quicker; with high values, the amplitude rises slower as a function of SOI, meaning that adaptation is strongly present in a larger range of SOIs.&#13;
For fitting the exponential function reliably, a large number of SOIs should be employed, and the largest SOI should measure approximately 10s to ensure that adaptation has died away. Coupled with the requirements of data quality (large number of stimulus repetitions), this means long measurement times. In this experiment, this was bypassed by noting that the ratio between the magnitudes measured at two different SOIs is proportional to . Expressing the magnitudes of the brain responses measured at SOIs 1.7 s and 3.5 s by M1.7s, and M3.5s, respectively, the ratio R = M1.7s / M3.5s was used as a dimensionless measure of  and adaptation lifetime. The smaller R is, the shorter adaptation lifetime is. R was calculated separately for each participant for each of the experimental conditions and for each SOI. In addition, R was also calculated separately for the N1 and P2 peaks as well as the difference between these peaks. Note that the actual adaptation lifetime cannot be estimated by the use of this method.&#13;
&#13;
Results&#13;
18 participants’ data did not show identifiable ERP responses and were thus discarded from analysis. The ERPs obtained from the final sample of 15 were plotted as shown in Figure 1 for each participant. The means and standard deviations were then calculated for the identified N1, P2 and the difference between the N1 and P2 for each SOI and condition as shown in Table 1. Seeing as there is such a large variability across the conditions, it is predictable that no statistical differences were found by the ANOVA. &#13;
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                <text>Emily Dreyer&#13;
Paige Durnall</text>
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                <text>33 to start, 18 were removed so final number is 15</text>
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                <text>What impact does the model statement have on future intentions for liars and truth tellers?</text>
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                <text>Eleanor Evans</text>
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                <text>Current literature states that there is a marked difference between statements given by truth tellers in comparison to liars. This difference is seemingly determined from when the cognitive load for participants is increased and liars struggle more. There is also evidence from distinctions in the linguistic make-up of the statements. Thirty-six undergraduate participants took part in a study exploring the effect of the model statement on truth tellers compared to liars when discussing a future event. All participants gave their first statement, then listened to the model statement before giving their second statement. Participants also filled out a questionnaire after completing the interview. All interviews were transcribed and analysed using CBCA, WMatrix and ANOVA. Results indicated that while there was a clear effect of the model statement, there was no significant effect of veracity from the CBCA and ANOVA analysis. On the other hand, WMatrix indicated differences in veracity.  In conclusion, both truth tellers and liars were able to increase the amount of information between their first and second statements, thus providing an effect of the model statement. However, there were nevertheless distinct differences between the language used by participants under both conditions; suggesting that there are in fact marked differences between truth tellers and liars when discussing a future event.</text>
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                <text>liars&#13;
manipulation&#13;
model statement&#13;
truth tellers&#13;
veracity</text>
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                <text>The model statement (Appendix A) is a 734-word document and was replicated from Leal et al. (2015). It is known that the model statement had an effect in the Leal et al. (2015) experiment and therefore it seemed appropriate to remain consistent with using the exact same model statement for this study. The interview questions (Appendix B) were also adapted from the Leal et al. (2015) study. &#13;
Questionnaires (Appendix C and Appendix D) were fashioned for each condition. The material for the questionnaires was largely developed for this experiment with the questions specifically tailored to relate to the interview. Both questionnaires contained a total of nine questions, a mix of Likert-scale and open-ended questions. &#13;
A digirecorder was used to record all participant interviews. &#13;
This study is a 2 (within factor: the manipulation through using the model statement) x 2 (between factor: the veracity, participants are either in the truth telling condition or the lying condition) mixed effects ANOVA.  The experiment was carried out in two sections, the first being the interview and the second involving a questionnaire. &#13;
Procedure&#13;
Before completing the experiment, all participants were provided with an information sheet (Appendix E). Participants met with the researcher so that they could be briefed about their task: to discuss the day in which the participants would go and collect their degree results. In addition, the participants were given a consent form (Appendix F), which they were required to fill out in order to participate. Participants took part in the experiment individually. &#13;
Once consent was given the participants were further briefed about which condition they would be participating in – either the truth telling condition or the lying condition. Participants were randomly assigned to one of the conditions. All participants were told as a baseline for the interview that the normality for collecting their degree results was that they would go to their subject department on the day, show their library card, and be given an envelope with their degree results in. Those participants placed in the Truth Telling condition (N = 16) were told to answer the questions asked by the interviewer as truthfully as possible to the best of their knowledge. Participants in the Lying condition (N = 17) were informed to lie when answering the interviewer’s questions. Participants in the lying condition were told that they could either lie about one element of the intended event or all aspects of it. &#13;
A third party member, who was unaware of the participants’ veracity status, carried out the interview; this is how the interview was conduced in the Leal et al. (2015) experiment. During the interview the participants were asked the first question of “OK, just so I can understand, I am going to need you to take me to the day that you will collect your degree results, and tell me in as much detail as possible everything that will happen from before you collect your results through to you receiving your results”. Participants then gave their first statement in response to the question. Preceding this, all participants in both conditions were exposed to an example statement after the interviewer said, “I know that sometimes people are not sure just how much detail to include. In order to give you an idea of what I am looking for I'd like to play you an example of what we consider a detailed answer”. This example statement, known as the model statement was a recording of someone dictating the details of an event that has no relevance to what the participants were asked to talk about during the experiment. Following the model statement, the interviewer asked “OK, I know that wasn’t too relevant to your story but hopefully you have an idea of the amount of detail it takes for us to get a clear rounded idea of how the event will go! Could you now please tell me in as much detail as possible everything that will happen from before you collect your results through to you receiving your results” and the participants proceeded to give their second statement. &#13;
Once the participants had completed the interview section of the experiment, they were given a questionnaire to fill out. The questionnaire was tailored to whichever condition they were allocated – there was a separate questionnaire for the Truth Tellers and the Liars. All participants in the lying condition were asked as part of their questionnaire to state the element(s) they had lied about. &#13;
Data Analysis&#13;
After the data collection, the participants’ interviews were transcribed and a primary analysis was performed using Criteria-Based Content Analysis (CBCA). There are a total of 19 possible criteria for analysing statements, however only a certain number were selected for the purpose of this study. The chosen criteria can be seen in table 1. Each statement was given a score corresponding with each individual criterion, leading to an overall CBCA score. Each criterion was scored between 0 and 2: 0, if the criterion is not found in the statement; 1 if it is a present, but only a small amount; and 2, if the criterion was found frequently throughout the statement. Following CBCA coding, the scores were analysed in SPSS using a repeated measures ANOVA, in which the overall scores for each of the statements could be compared. &#13;
Table 1&#13;
List of criteria used for CBCA coding and the descriptions &#13;
General Characteristics&#13;
&#13;
1.Logical Structure&#13;
Coherency of the statement in terms of not containing logical inconsistences or contradictions&#13;
2. Unstructured Production&#13;
The presentation of the information in a (non) chronological order&#13;
3. Quantity of Details&#13;
The inclusion of specific descriptions of place, time, persons, objects and events&#13;
Specific Contents&#13;
&#13;
4. Contextual Embedding &#13;
Events being placed in time and location, and actions being connected with other daily activities and/or customs&#13;
5. Description of Interactions&#13;
Information that interlinks at least the alleged perpetrator and witness &#13;
7. Unexpected Complications During the Incident &#13;
Elements incorporated in the statement that are somewhat expected&#13;
8. Unusual Details&#13;
Details of people, objects or events that are unique, unexpected or surprising but meaningful in the context&#13;
9. Superfluous Details&#13;
Details in connection with the allegations that are not essential for the accusation &#13;
11. Related External Associations&#13;
Events are reported that are not actually part of the alleged offence but are merely related to the alleged offence&#13;
12. Accounts of Subjective Mental State&#13;
Development and change in feelings experienced at the time of the incident &#13;
Motivated-Related Contents&#13;
&#13;
14. Spontaneous Corrections&#13;
Corrections that are made or information that is added to material previously provided in the statement without having been prompted by the interviewer&#13;
15. Admitting Lack of memory&#13;
An unprompted interviewee admitting lack of memory either by saying “I don’t know” or “I don’t remember” &#13;
Note. This list of criteria was adapted from Vrij, A. (2005). Criteria-Based Content Analysis: A Qualitative Review of the First 37 Studies. Psychology, Public Policy and Law. 11(1), 3-41&#13;
&#13;
WMatrix (Rayson, 2008) was used in addition to CBCA and SPSS. All the statements were separated into files and uploaded onto WMatrix so that linguistic analysis could commence. WMatrix is a software program that allows for corpus linguistic analysis and comparison.  It provides frequencies and percentages of how the words are distributed in a given text; it also lists the concordances for reference. It produces tables from the output for each comparison and ranks the words based on their log-likelihood. The log-likelihood is an indicator based on the difference among frequencies, in this instance how often a particular word is used by participants. The word count and interview duration were also calculated and used in the analysis. &#13;
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                  <text>Understanding psychological processes though eye tracking</text>
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                <text>Lights, Camera, Action: Investigating Advertisement Susceptibility in Films Amongst Individuals with Parkinson’s Disease and Controls. </text>
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                <text>Elena Ball</text>
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                <text>Product placement is the merging of entertainment with advertising, and its presence in our daily lives is increasing. Despite this, there is an inherent lack of consideration of its influence amongst vulnerable populations such as individuals with Parkinson’s disease (PD). Research suggests that individuals with PD have reduced inhibitory control (IC) which may drive impulsive behaviours. A concernment, therefore, is the influence that product placement may have on the purchase behaviour of individuals with PD alongside a possible propensity to partake in risky and impulsive behaviours. Thus, this study aimed to examine whether reduced IC increases the likelihood that an individual with PD will be susceptible to product placement. The study adopted an experimental approach, recruiting 20 healthy younger controls, 20 healthy older controls, and 13 individuals with mild to moderate PD to participate in watching two films containing product placement; one featuring Coca Cola and the other an Audi. A pre and post product placement questionnaire was used to measure change in purchase behaviour before and after exposure to product placement, and an antisaccade eye tracking task and a Stroop task was used to measure IC. An ANOVA indicated that IC was significantly impaired in individuals with PD compared to healthy controls.  Despite this, linear mixed effects modelling suggested that IC may not be a factor that increases the likelihood that an individual will be more susceptible to product placement. Implications of these findings are discussed relative to other clinically vulnerable populations with similar cognitive impairment symptomology, and the consequent need for future research to continue to explore product placement susceptibility amongst vulnerable populations. &#13;
&#13;
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                <text>Parkinson’s Disease, Inhibitory Control, Product Placement Susceptibility &#13;
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                <text>Method&#13;
Participants&#13;
A voluntary sample of 54 participants were recruited, 20 healthy younger controls (YC) (16 females and four males, (Mage= 22.70, SDage= 2.42)), 20 healthy older controls of comparable age to those with Parkinson’s (OC) (females and males, (Mage= 66.85, SDage= 8.53)), and 15 adults with mild-moderate idiopathic PD (females and males, (Mage= 65.00, SDage= 7.84)). As this research area is entirely novel this sample size was modelled on comparable population studies that have explored IC (Meyer et al., 2020; Paz-Alonso et al., 2020).  YC were defined as young adults aged between 18 to 26 years old with no neurological or cognitive conditions (Stroud et al., 2015). OC were defined as adults aged between 50 to 85 years old with no neurological or cognitive conditions (Zhang et al., 2020). The participants with PD had been diagnosed with mild-moderate idiopathic PD, characterised by mild-moderate impairments of motor and cognitive functioning (DeMaagd &amp; Philip, 2015). &#13;
The exclusion criteria for both the healthy controls and individuals with PD were those who had a diagnosis of any additional neurological or cognitive conditions other than PD. Moreover, given that visual impairments may affect the visual experience of product placement, all participants were screened for red-green colour blindness using the Ishihara test. The standardised cut off for normal vision is 15 (Rodriguez-Carmona &amp; Barbur, 2017), therefore, participants who score 14 or less were excluded as this is indicative of the presence of red-green colour blindness. &#13;
All participants had normal or corrected-to-normal vision. The Addenbrooke’s Cognitive Examination-III (ACE) was used to screen for the presence of cognitive impairment (Bruno &amp; Vignaga, 2019). Participants’ data was only included in analysis if participants achieved a score within the normal range (≥ 82 out of 100). Following this exclusion criteria, one PD participant’s data was removed. Research has shown saccadic eye movements to be influenced by cognitive dysfunction (Hutton, 2008; MacAskill et al., 2012), thus cognitive impairments need to be screened for as this study is measuring saccadic eye movements as a measure of IC. Subsequently, following exclusion criteria, 53 participants’ data was included within analysis.  &#13;
PD participants were selected who were at a Hoehn and Yahr Stage three or less (see Table 1 for background characteristics for participants attached in the files below). The Hoehn and Yahr is used to give a summary of the laterality and severity of PD symptomology (Readman et al., 2021b). Five participants presented unilateral symptoms only (stage one), seven participants presented bilateral symptoms with no impairment of balance (stage two) and one participant presented bilateral symptoms with some postural instability but were not physically dependent (stage three). PD symptomology was assessed using the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) (Evers et al., 2019). All PD participants were tested under their usual medication regimes and were in a typical functioning ‘ON’ phase. Eight participants were taking a dopamine agonist (e.g., Ropinirole), eight participants were taking a combination drug (e.g., Madopar), six participants were taking a monoamine oxidase inhibitor (e.g., Rasagiline), and two participants were taking a Catechol-O-Methyl Transferase (e.g., Entacapone). &#13;
YC were recruited through the researcher’s social network. Whereas both OC and individuals with PD were recruited established research interest databases (OC C4AR database; PD MRR PD interest database (FST2005)).  &#13;
Materials&#13;
Health and Demographic Questionnaire&#13;
	The health and demographic questionnaire (HADQ) was developed and distributed using Qualtrics (Qualtrics, 2022), an online software that aids the process of building, distributing, and analysing surveys (Carpenter et al., 2019). The HADQ was comprised of four distinct subsections pertaining to both the participants general demographics, and more specific health related measures.&#13;
	Demographic Questions. For participant group allocation, participants were asked for their age, sex, and whether they held a diagnosis of PD. Information about participants’ age also afforded the opportunity for exploration into the possible effect of age as well as PD on product placement susceptibility.  &#13;
The Hospital Anxiety and Depression Scale (HADS). The HADS is a 14 item (7 items pertaining to anxiety and 7 items pertaining to depression) self-report assessment of anxiety and depression suitable for both psychiatric and non-psychiatric populations (Stern, 2014). All items are rated on a 4-point severity scale with a total score of 11 or more being indicative of probable anxiety and depression respectively (Caci et al., 2003; Edelstein et al., 2010). Literature has found HADS to be high in construct validity and very good internal consistency was observed when measuring anxiety (Cronbach’s α = .83) and depression (Cronbach’s α = .82) (Bjelland et al., 2002; Johnston et al., 2000; Mondolo et al., 2006). &#13;
	Edinburgh Handedness Inventory. The Edinburgh Handedness Inventory is a 10-item self-report questionnaire in which participants are asked to indicate a preference for which hand they would use when completing a range of daily activities (e.g., brushing teeth) (Robinson, 2013). Through this a handedness score ranging from 100 (strong right) to -100 (strong left) deduced.  Excellent internal consistency was observed in the 10-item Edinburgh Handedness Inventory (Cronbach’s α = .94) (Fazio et al., 2013). Previous literature suggests that handedness and eye-dominance are correlated because of hemispheric specialisation (McManus,1999; Willems et al., 2010), therefore establishing participants’ handedness was indicative of their dominant eye when measuring IC through saccadic eye movements. &#13;
PD Diagnosis questions. Participants with PD were asked to provide specifics relating to their diagnosis, including years since diagnosis, years since presumed onset, and what medication, and its dosage, they are prescribed. These items were necessary to investigate whether PD severity and medication type influence product placement susceptibility.&#13;
Screening Assessments&#13;
	Cognitive Impairments. The Addenbrooke’s Cognitive Examination-III (ACE) is a cognitive assessment that screens for the probable presence of cognitive impairments (Noone, 2015). The ACE is comprised of 24 items that analyse attention, memory, fluency, language, and visuospatial processing (Bruno &amp; Vignaga, 2019). Very good internal consistency was observed in the ACE (Cronbach’s α = .88) (Kan et al., 2019) and validity (Matias-Guiu et al., 2017; Takenoshita et al., 2019). &#13;
Visual Impairments. The Ishihara test is a reliable (Birch, 1997) 17 item assessment for red-green colour blindness that requires participants to read aloud a set of numbers on Ishihara plates that are made up of coloured dots (Marey et al., 2015). &#13;
PD Symptomology. MDS-UPDRS is a tool to measure the progression of PD symptomology (Evers et al., 2019). MDS-UPDRS is comprised of a series of tasks that assesses PD symptomology within the last week, in the domains of mentation, behaviour and mood, activities of daily life, motor abilities, and complications of therapy (Holden et al., 2018). Very good internal consistency was observed in the MDS-UPDRS (Cronbach’s α = .90) (Abdolahi et al., 2013) and valid assessment of PD symptomology severity (Goetz et al., 2008; Metman et al., 2004). &#13;
Measures of Inhibitory Control &#13;
	Eye Tracking Tasks. The prosaccade and antisaccade tasks were created using Experiment Builder Software Version 1.10.1630 and the data was extracted and analysed using Data Viewer Software. Eye movements were recorded via the EyeLink Desktop 1000 at 500 Hz. Whilst recording eye movements, participants were asked to place their chin on a chin rest to reduce their head movements. Participants sat approximately 55cm away from the computer monitor (monitor run at 60Hz). &#13;
Firstly, participants were asked to complete the 4-point calibration task to improve eye tracking accuracy (Pi &amp; Shi, 2019). In this task participants were asked to follow a red target around the screen as it moved up, down, left, and right. Next, participants completed the prosaccade eye tracking task. To centralise participants’ gaze, participants were instructed to look at a white fixation target displayed on a computer screen for 1000ms. Participants were then instructed to look towards a red lateralised target that appeared on screen for 1200ms at a 4o visual angle either to the left or to the right of where the white central dot had been located, as quickly and as accurately as possible (Readman et al., 2021a). The eye tracking equipment measured participants’ saccades and latencies (how long it took for participants to fixate on the red target). A total of 16 gap trials were presented with a blank interval screen displayed for 200ms between the extinguishment of the white fixation target and the initial appearance of the red target, which resulted in a temporal gap in stimuli presentation. The prosaccade task was incorporated to ensure that alternations in participants antisaccade task performance were not due to impaired prosaccades and rather are indicative of alterations in IC. &#13;
For the antisaccade task, participants were first asked to look at a central white fixation dot for 1000ms to centralise their gaze. Participants were then asked to direct their gaze and attention focus to the opposite side of the screen to where a green lateralised target was presented for 2000ms at a 4o visual angle either to the left or to the right of where the white central dot had been located, as quickly and accurately as possible (Derakshan et al., 2009). See figure 1 above for a visual display of an antisaccade task. The eye tracking equipment measured participants’ saccades, latencies (how long it took participants to fixate their gaze to the opposite direction to the green target), and error rates (how many time participants incorrectly looked at the green target). A total of 16 gap trials were presented with a blank interval screen displayed for 200ms between the extinguishment of the white fixation target and the initial appearance of the red target, which resulted in a temporal gap in stimuli presentation. &#13;
	Stroop Test. The Stroop test was conducted using PsyToolkit’s free online demonstration (PsyToolkit, 2022). Unlike in the original Stroop test whereby participants had to say the ink colour aloud (Stroop, 1935), using PsyToolkit’s online Stroop test allowed for a more accurate measurement of participant’s reaction time (ms) through pressing the key corresponding to the ink colour (Brenner &amp; Smeets, 2018). Participants completed the Stroop test on a HP ProBook 470 G5 17.3” laptop (HP, 2022), and were sat approximately 30cm away from the laptop. Presenting the Stroop test on this laptop enabled participants to view the test on a large screen, thus improving the accessibility of the test. The colour words presented to participants were ‘red’, ‘green’, ‘yellow’, and ‘blue’.&#13;
	Participants were instructed to press the key corresponding to the initial letter of the ink colour of the printed word presented on screen as quickly and accurately as possible. For example, the correct answer for RED would be if the participant pressed the key ‘B’ for blue. A total of 40 gap trials were presented. For each trial, a colour word was presented on screen for 2000ms. The colour word was either congruent (the colour word and the meaning are the same, e.g., GREEN) or incongruent (the colour word and the meaning is different, e.g., GREEN). There was a 100ms gap in presentation of the word in which a white cross was presented on a black interval screen. Participants’ congruent and incongruent reaction times (ms), correct Stroop score (correctly identified ink colour out of 40), and Stroop effect (incongruent reaction time (ms) minus congruent reaction time (ms)) were recorded.&#13;
The ease at which the Stroop test can be conducted in a non-laboratory environment and the simplicity at which the colour words can be translated into other languages, increases its accessibility and universality as a measure of IC (Gass et al., 2013). This assessment would, however, be an invalid measure of IC for individuals affected by colour blindness or dyslexia, limiting the populations the Stroop task can assess (Scarpina &amp; Tagini, 2017). &#13;
Product Placement Film Clips&#13;
The incorporation of film clips containing product placement was guided by the prominent use of film clips within previous research that had investigated product placement susceptibility (Kamleitner &amp; Jyote, 2013; Yang &amp; Roskos-Ewoldsen, 2007). Jurassic World featuring Coca Cola and Avengers Endgame featuring Audi were chosen as they were popular films that contained product placement that both younger and older adults would recognise (Malaj, 2022), minimising the effects of familiarity. Furthermore, these two film clips were chosen as they contained product placement of products of different monetary value products. Thus, controlling for the potential effects of monetary value on product placement susceptibility (McDermott et al., 2006). &#13;
	Both film clips were downloaded from Youtube and trimmed to last approximately one minute each to lessen the study length because of the propensity for individuals with PD to tire because of the symptomology they present with (see Appendix A for the screen shots of the two film clips). The two film clips were shown on a HP ProBook 470 G5 17.3” laptop because the large screen enhanced participants’ visual experience of product placement (HP, 2022).&#13;
Measure of Purchase Intention&#13;
	Separate pre and post product questionnaires for each clip were made using Qualtrics (Qualtrics, 2022). To measure purchase behaviour, participants were asked how strong their preference was to buy those drink/car brands on a Likert scale of one to seven (from one = “Extremely unlikely” to seven = “Extremely likely”). Literature has found 7-point Likert scales to be a more reliable scale because it allows for more accurate and differentiated responses than smaller scales like 5-point Likert scales (Cicchetti et al., 1985; Finstad, 2010). The use of a 7-point Likert scale therefore gained a more sensitive and accurate measurement of product placement susceptibility. Both the pre and post product placement questionnaires asked participants the same questions therefore enabling us to measure if there was a change in participants’ responses prior to and after exposure to product placement (Matthes et al., 2007).&#13;
Design&#13;
	The study used a 3 between (Participant Status: Healthy Young Controls vs. Healthy Older Controls vs. Individuals with Parkinson’s Disease) x 2 within (Product Placement Category: Drink vs. Car) mixed-subjects design.&#13;
Procedure&#13;
As this study recruited a vulnerable population, the information sheet was sent to participants via email 48 hours prior to the in-person study. This afforded participants the time to ask questions or express any concerns about the study before then being sent the consent form 24 hours prior to commencing the in-person study. Once participants had read and completed the digital consent form, participants were sent the digital HADQ. The HADQ took participants approximately 10 minutes.  &#13;
	Prior to the main study, participants were screened for cognitive impairment, using the ACE, and visual impairment, using the Ishihara test. At this time the severity of Parkinson’s symptomology was assessed using the MDS-UPDRS where appropriate.&#13;
	On completion of all pre-study screening, participants were asked to firstly complete a prosaccade eye tracking task and then an antisaccade eye tracking task which took approximately 10 minutes. &#13;
	Participants were then asked to complete a pre product placement questionnaire and then watch a short film clip. After watching the film clip, participants were asked to complete a post product placement questionnaire. Finally, participants were asked to complete the Stroop test which took approximately five minutes to provide a further measure of IC and to act as a buffer in time. &#13;
	This process was repeated for a second product category condition. The order of condition completion was randomly counterbalanced across participants to increase internal validity by minimising the potential for order effects (Corriero, 2017). The in-person study lasted approximately an hour for healthy controls and an hour and 30 minutes for PD. At the end of the study, participants were read and given a copy of the debrief sheet, thanked for their participation and time, and given £10 as a contribution towards travel expenses. All raw data was stored on the Lancaster University OneDrive, on a password-protected computer.&#13;
Data Analysis&#13;
	The raw data from the prosaccade and antisaccade tasks were extracted using the EyeLink DataViewer Software (Version 3.2) and processed using the bespoke software SaccadeMachine (Mardanbegi et al., 2019). Noise in the dataset was removed by filtering out frames with a velocity signal greater than 1,500 deg/s or with an acceleration signal greater than 100,000 deg2/s. The EyeLink Parser was used to detect fixations and saccadic events. Saccades were extracted alongside multiple temporal and spatial variables. Trials were excluded in cases when the participant did not direct their gaze to the central fixation target. The onset of target display was a temporal window of 80-700ms, thus anticipatory saccades made prior to 80ms and excessively delayed saccades made after 700ms were removed.&#13;
	To improve data analysis reproducibility, statistical analyses were conducted using RStudio (version 2022.09.0) (Quick, 2010). To prepare the Stroop test data for analysis, participants’ Stroop scores (correctly identified ink colour out of 40), congruent and incongruent trial reaction times (ms), and Stroop effect (incongruent trials reaction time (ms) minus the congruent trials reaction time (ms)) were downloaded from Psytoolkit into an Excel file. IC was operationalised as the Stroop effect (Kane &amp; Engle, 2003). &#13;
	To investigate the susceptibility to product placement, a difference in purchasing behaviour score was calculated for each product. To do so, the pre product placement ratings of the likelihood of purchasing each brand were subtracted from the post product placement ratings of the likelihood of purchasing each brand. A positive difference was indicative of participants being more likely to buy the featured product after exposure to product placement, a negative difference suggested that participants were less likely to buy the featured product, and a difference of zero indicated no change in purchase behaviour. &#13;
	First to confirm the assumption that is impaired in individuals with PD compared to healthy controls, three separate between-factor ANOVAs were performed to compare the main effect of group (YC, OC, and PD) on antisaccade latency, antisaccade error rate, and Stroop effect (See Appendix B for R code). A between-factor ANOVA was chosen because it compares three or more categorical groups to establish whether there is a significant difference on a dependent measure (Henson, 2015). As ANOVA results only identify a difference between groups, post hoc Tukey HSD tests for multiple comparisons were conducted to determine where the differences lie between groups (Abdi &amp; Williams, 2010). &#13;
	To investigate whether IC influences product placement susceptibility, a linear mixed effects modelling (LMM) was fitted. The LMM fitted incorporated difference in purchase behaviour scores (differencescore) as the outcome, and group (PD v Healthy older control v Healthy younger control) and measures of IC (antisaccade latency, antisaccade error rate, and Stroop) as the fixed effects. Given that IC is part of an individual’s executive function (Crawford et al., 2002), ACE score (as a measurement of the participants overall cognitive function; Noone, 2015) was also fitted as a fixed effect. As LMM allows for the analysis of fixed effects of independent variables, whilst also considering unexplained differences corresponding to random effects like participant variation (Baayen et al., 2008).  Random effects of both participants and product (Car or Drink) on intercepts were added (See Appendix C for R code). The LMM was fitted using the Satterthwaite adjustment method in lme4 package (Bates et al., 2014) in R (version 2022.09.0) (Quick, 2010). &#13;
Ethics&#13;
	This study received ethical approval from the Psychology Department Research at Lancaster University on the 22/06/2022 and complied to The British Psychological Society’s guidelines (2014).&#13;
&#13;
&#13;
&#13;
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                <text>Dr Megan Readman</text>
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                <text>53 Participants. 20 healthy younger controls, 20 healthy older controls, 13 individuals with mild-moderate Parkinson's disease</text>
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                <text>ANOVA&#13;
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                  <text>Projects that focus on behavioural data, using chronometric analysis and accuracy analysis to draw inferences about psychological processes</text>
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                <text>Contrast polarity of a stimulus does not affect the cueing effect</text>
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                <text>Eleni Sevastopoulou</text>
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                <text>According to the contrast polarity effect, people’s attention is sensitive to dark objects within light backgrounds. According to the gaze-cueing effect, a human gaze shift attracts people’s attention towards the direction of the darker region of the observed eyes, thus the gaze-cueing effect depends on the contrast polarity of the observed eyes. Therefore, a human gaze is perceived as a darker spot within a lighter background. In the present study, combining the contrast polarity effect and the gaze-cueing effect we examined whether the colour contrast between a black and a white square that suddenly flip on a computer screen can have a similar effect to that of gaze-cueing. The prediction was that participants would perceive the side where the black square moved after the flipping as attentional cue, therefore when an object appeared on the side that the black square moved, reaction times would be shorter compared to when the object appeared on the opposite side. The results showed that reaction times in the two conditions did not differ significantly. Thus, the contrast polarity of a stimulus does not affect the cueing effect. </text>
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                <text>Gaze cueing&#13;
Contrast polarity&#13;
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                <text>The experiment was conducted using a single within-subject design. The independent variable was the cue congruency, which consisted of two conditions: the object appeared either congruently or incongruently with the attentional cue. The dependent variable was the reaction times of the participants which were measured in millisecond (ms). &#13;
Procedure. Each participant was tested individually in a quiet room at the library of Lancaster University. Participants were tested at different days and times, including morning and evening hours. The only people present in the room during the conduct of the experiment were the participant and the experimenter.&#13;
In the beginning, participants were asked to read the experiment instructions from the computer screen and they were also given clarifications, if needed, by the researcher. Afterwards, the experiment started and two squares, one black and one white, sharing one side were presented on the screen for half a second. The side that the squares shared was located at the centre of the screen, therefore one square appeared on the left side of the screen and the other one on the right side of the screen. Then the squares flipped and changed position and the apparent motion of the two squares was the cue. One second after flipping, the squares disappeared and a picture of an object randomly appeared either on the left or on the right side of the screen for one more second. Afterwards, the object disappeared and the screen remained blank. &#13;
The task of the participants was to press the appropriate keyboard button as fast and as accurately as possible, depending on the side of the screen where the object appeared. So, they had to press the «Q» button on the keyboard when the object appeared on the left side of the screen or the «P» button when the object appeared on the right side of the screen. They were given one second to respond to the object appearance. The sequence of the trials was the same for every participant. Each one of the 6 objects appeared on total 30 times congruently with the cue and 30 times incongruently with it. Thus, the total number of trials for every participant was 360, 180 trials that the objects appeared congruently with the cue and  180 that they appeared incongruently with it. The experiment lasted for 20 minutes for each participant and at the end of every session, a message appeared on the screen which informed the participants that the experiment was over.&#13;
The prediction was that the side where the black square would move after the flipping would be perceived as an attentional cue by the participants. Their gaze would be attracted to the cue and an effect similar to the gaze-cueing effect would appear. So, their reaction times would be shorter for the trials where the objects would appear on the same side with the attentional cue compared to the trials where the objects would appear on the opposite side of the cue. The independent variable was the cue congruency which included two conditions, the congruent trials (when the object appeared on the same side with the cue) and the incongruent trials (when the object appeared on the opposite side of the cue). &#13;
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                <text>Ellie Ball</text>
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                <text>Dr. Eugenio Parise</text>
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                <text>The Social Functionality of Language Coordination: Linguistic Alignment in Children with and Without Autism.</text>
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                <text>Elizabeth Osborn</text>
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                <text>Linguistic alignment between conversationalists is a well documented phenomenon; however, the underlying motivational basis for this tendency remains to be established. This study explored the extent to which language convergence in terms of both lexical choice and syntactic structure is mediated by feelings of affiliation toward an interactional partner. In Experiment 1, children with Autistic Spectrum Disorder (ASD) and typically developing (TD) children completed a ‘Snap!’ game in which they alternated turns to name picture cards with a partner. In actuality, the partner was an experimental confederate who utilised non-preferred lexical choices to name the pictures. Results found that all children aligned their word choices with the lexical selections of the experimenter to an equivalent extent. However, evidence to link this tendency toward liking for an interactional partner could not be substantiated. Experiment 2 sought to further investigate evidence for syntactic convergence in children and employed a replication of the paradigm utilised by Allen et al. (2011). Again, there were no differences between the alignment abilities of children with ASD and the performance TD controls. Taken together, the results of this study add more support for the notion of automated low-level priming as one explanation of convergent functioning. Identified implications of these findings and proposals for future research are discussed. </text>
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autism</text>
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                <text>	Lexical Snap Cards&#13;
The experimental materials comprised of 16 paired experimental items and 50 filler picture cards. An initial pool of 55 items which could be named by two different lexical choices was compiled by images provided by Snodgrass and Vanderwart (1980) and experimental items utilised by Branigan et al. (2011). The images were presented in a list alongside two lexical choices to name each picture; one lexical choice was a highly preferred name for the picture which was paired with a second less-preferred but equally appropriate word to name the picture. For example, an image of a mushroom was presented adjacent to the names ‘Mushroom’ and ‘Toadstool’. Ten adult participants were then asked to individually rate the appropriateness of each lexical choice for naming the pictures on a seven point Likert scale, with ‘1’ indicative that the lexical choice was completely inappropriate for naming the picture and ‘7’ indicative that the lexical choice was completely appropriate for naming for the picture. Additionally, using a forced choice paradigm each participant was required to indicate their preferred word choice for naming the picture from the two options provided.  &#13;
	From this initial pool, twenty-four items were identified where both lexical choices had acceptability ratings above five and where there appeared a distinct majority preference for one word choice to name the picture (above 80%). Ten typically developing children (mean age: 9.7 years, range 9.2-10.1 years) were then asked to spontaneously provide names for these pictures in the absence of written or verbal prompts in order to further confirm the existence of a distinct lexical preference for each picture in child participants. A final list of 16 experimental items (see Appendix 1) was then selected where over 80% of children spontaneously used the word choices that had been preferentially indicated by adults to name the pictures. The final card set therefore comprised of 82 cards: the 16 paired experimental item picture cards (consisting of an experimenter prime card and subsequent matching participant target card), two sets of six matching filler ‘Snap!’ cards and 38 filler cards which pictured random objects.&#13;
	Each participant received the sixteen experimental items in a different order, split randomly each time between two experimental conditions that were introduced to assess both the presence and strength of language coordination over time and to eliminate the potential of immediate echolalia as an experimental confound in participants with ASD. In accordance with the design utilised by Slocombe et al. (2013), eight of the paired experimental items were split by two filler card interventions between the experimenter’s prime card and the participant’s target card, whilst the other eight paired experimental items were split by four filler card interventions between the prime and target cards (see Figure 1). Cards were also colour coded so that ‘Snap!’ was only possible when both the colour and the pictures on the experimenter’s prime and participant’s target cards matched, in order to avoid distractions in responses to the experimental items. The order of the filler and ‘SNAP!’ cards remained fixed throughout the trials. &#13;
          ‘Reading the Mind in the Eyes’ Task&#13;
The first fourteen experimental items from the official ‘Reading the Mind in the Eyes’ test (Baron-Cohen, 2001 – child version) were utilised as measures of emotion recognition and social sensitivity; abilities that have been recurrently taken as indicators of Theory of Mind (ToM) functioning in children. &#13;
ToM Book&#13;
Additional to the ‘Reading the Mind in the Eyes’ task, children were also given a higher -order ToM assessment in order to obtain a more advanced measure of both social understanding and the abilities of participant’s to make inferences about the mental states of others. The story ‘The School Football Team’ developed by Liddle &amp; Nettle (2006, story number 4) to investigate higher-order ToM functioning was presented pictorially to children in a story-book format and contained two scripted memory questions and a ToM question at the end (see Appendix 2).  &#13;
Shopping list game&#13;
A commercially available child-appropriate board game was selected where it was possible that the experimenter could systematically manipulate the resultant winner of the game. The ‘Shopping List’ game by Orchard Toys is a picture-matching game designed for children with Verbal Mental Ages between three and six years and served as a quick experimental task where the outcomes could be reliably manipulated. &#13;
	Liking Scale&#13;
	In order to assess the resultant outcomes of the positive and neutral conditions on children’s affiliation to the experimenter, a picture sorting task was employed. Ten photographs that varied in content to include food, animals, people and events (e.g. baked beans, Spiderman and a giraffe) were obtained from an online picture database and constituted filler card items. The experimental item in this task was a head and shoulders photograph of the experimenter. Five line-drawing pictures of faces that varied in degrees of emotion from one (very unhappy face) through to five (very happy face) were then utilised as a pictorial adaptation of a Likert scale that was understandable to child participants. All participants received the pictures in same order, with the experimental item being placed at number eight out of the ten picture cards.&#13;
Procedure&#13;
Each participant was tested individually in a quiet room, away from distractions. Testing was divided between two sessions that were held approximately twenty-one days apart. During the first session participants completed the BPVS which took approximately ten minutes to administer and required children to select (either verbally or via pointing) a picture from a choice of four that depicted a word spoken by the experimenter. During this session children also completed the two ToM assessment tasks. For the Baron-Cohen ‘Reading the Mind in the Eyes’ task (2001-child version) each participant was firstly shown a practice example sheet depicting a photograph of a pair of eyes with the names of four different emotions surrounding them. Each child was asked to look at the eyes whilst the experimenter read aloud the four names in turn and was then asked to choose the emotion that they thought best described the eyes. After the practice trial had been successfully completed the same procedure was repeated for the fourteen experimental items, taking approximately five minutes in total. &#13;
For the second higher-order ToM task, children were asked if they would like to read a story about two friends, Johnny and Bob. If the participant agreed then the experimenter and the child looked at the picture book together, with the experimenter reading the story aloud to each child. At the end of the story book children were then asked two scripted memory comprehension questions about the story in order to gain an indication of overall attention and comprehension of the story and a third scripted question that assessed higher-order ToM functioning. This task took less than five minutes to administer. &#13;
In the second session participants were asked if they would like to play some more fun games with the experimenter. If the child agreed they were informed that the first game they would be playing was a race to find all of the items on their ‘shopping list’ and that the winner of this game would receive a prize. In this board game task both the experimenter and participant received a ‘shopping list’ and alternated attempts to turn over cards from a pile in the middle of the table in order to correctly identify items on their list. The first person to complete their ‘shopping list’ and identify all of their items was determined the winner, however by removing a card either on the experimenter’s shopping list or on the participant’s shopping list meant that the ‘winner’ of the game could be systematically manipulated. Six children in both the ASD and TD groups were allowed to win, whereas the other six children in each group played and lost. When children ‘won’ the game they received positive verbal reinforcement and praise from the experimenter (e.g. “Wow! You were brilliant at that game! You must be very clever”) and were allowed to choose a sticker as a reward (positive affiliation condition). In contrast, when children ‘lost’ the game the experimenter retained a strictly neutral manner towards the child and continued with the next task (e.g. “okay, shall we play the next game?” neutral affiliation condition).  &#13;
Immediately following this game, children were asked to sort some photographs according to how much they liked the things depicted in the pictures. Five images of faces that displayed varying emotional expressions were placed in a line on the table, going from one (a really unhappy face) through to five (a really happy face). Children were then given three examples of picture sorting by the experimenter e.g. “This is a picture of broccoli, I really hate broccoli and so I would give it a number one and put it in this pile”, “This is a picture of a cupcake, I really like cupcakes and so I would give it a number five and put it in this pile” and finally “This is a picture of the Queen, I don’t really like or really dislike the Queen and so I will give her a number three and put her in this pile”. Each child was then asked to sort the ten photographs in turn according to how much they liked the things depicted in the pictures whilst the experimenter busied herself ‘preparing the next task’. &#13;
Finally, children were asked if they would like to play a fun game of ‘Snap!’ with the experimenter. If the child agreed then the experimenter explained the rules of the game; that ‘Snap!’ in this game occurred when cards were both the same picture and the same colour and that before deciding if it was ‘Snap!’ each player was firstly required to name the picture depicted on their card. In order to further establish these rules each child was then shown four sets of example picture cards; the first pair of cards had the same picture but were not the same colour (a pink penguin and a blue penguin), the second pair of cards were the same colour but did not have the same picture (a blue bell and a blue tie), the third pair had different colours and different pictures (a green carrot and a blue star) and the final pair had the same colour and the same picture (two green shoes) depicting ‘Snap!’. The child and the experimenter then played with these example cards until it became clear that the child understood the conditions that constituted ‘Snap!’ in this game.&#13;
Following indication that the participant understood how to play the game, the experimenter and child took turns in taking the top card from their pre-ordered card pile, naming the picture on the card, before placing the card on the table and deciding if it was ‘Snap!’ The experimenter always began the game and utilised pre-scripted non-preferred word choices to name the pictures on the sixteen experimental item prime cards. When both the experimenter’s prime card and participant’s target cards both had the same picture and were the same colour it was ‘Snap!’ and the first person to shout this won the cards. At the end of the game the person who had won the most cards was determined the winner (the experimenter let all children win the game). This task took 5-10 minutes dependent upon the participant’s age and concentration and was digitally recorded for later transcription.</text>
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                <text>Twelve participants with Autistic Spectrum Disorder (mean chronological age: 9.2 years, range 5.7 to 13.5 years) were recruited from a Special Educational Needs (SEN) school in the North West area of England&#13;
Participants with Autism were then paired with a group of twelve typically developing (TD) children (mean chronological age: 5.3 years, range 3.11 to 7.8 years) recruited from both a mainstream primary school and a pre-school centre in Lancashire. </text>
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                  <text>Primarily qualitative analysis based on forming focus groups to collect opinions and attitudes on a topic of interest</text>
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                <text>Use This or You’ll Lose That: Investigating Appropriate Psychological Theories to Market the Bogallme Tracking System.</text>
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                <text>Elizabeth Wardman</text>
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                <text>The Bogallme Tracking System is an anonymous ‘Lost and Found’ system which uses stickers with QR codes printed on them to facilitate the return of lost items. It is thought that the main motivations behind the purchasing of these stickers are fear appeal and loss aversion, as people fear losing their possessions and will do whatever they can to prevent this from occurring. This study aimed to investigate whether this is the case using focus groups consisting of primarily students - the target audience for this specific product. The research also explored Rogers’ (1962; 1976) Diffusion of Innovations Theory (DOI) in relation to this product as well as opinions regarding the product and brand. Findings suggested that all three of the above theories are relevant and useful in the development of this product and can be used to create an efficient marketing campaign whilst creating scope for further research which would benefit the development of the brand and product. </text>
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                <text>Marketing/Advertising&#13;
Qualitative (Thematic Analysis)</text>
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                <text>Methodology&#13;
Participants.&#13;
Sixteen participants took part in this study. Participants were recruited via opportunity sampling through various social media platforms and word of mouth. The age of participants ranged between 20 and 23. This age range was selected due to a market segmentation suggesting that over 50% of QR code users were aged between 18 and 34 and that 18 to 24 year olds were 36% more likely to scan them (14 Million Americans Scanned QR Codes on their Mobile Phones in June 2011., n.d.)&#13;
Materials. &#13;
The focus groups loosely followed a discussion guide (See Appendix D) which asked general questions corresponding to the product, brand and incentives as well as questions related to Fear, Loss Aversion and Diffusion of Innovations theory. The majority of questions within the Discussion Guide were open-ended as they encourage participants to express their views and opinions in full (Turner, 2010) and allow for any further elaboration. During the focus group participants were shown three potential names for the brand (Scannit, GlobalQR and the brand name Bogallme) and an example of the Diffusion of Innovations Model (Figure 1). Participants were each given prototypes of the product that they tested during the group and were allowed to keep these at the end of the study. &#13;
Procedure.&#13;
Focus Groups&#13;
Focus groups were used as the method of data collection for this study. Although focus groups cannot provide data as rich as that of individual interviews, they can allow for group discussions. These group discussions and interactions allow for comparisons between participant experiences and opinions which could otherwise only be inferred after proceedings with individual interviews (Morgan, 1997). &#13;
This study consisted of two focus groups which lasted approximately 60 minutes each. Within each focus group, eight participants sat facing one another around a circular table. After reading the information sheet and signing the consent forms, the focus group started with introductory questions to make participants feel more comfortable and able to voice their opinions. After this brief period, participants were asked questions which followed the discussion guide (See Appendix D), however elaboration was allowed and encouraged. Each participant was encouraged to answer all questions and to contribute to discussions as much as possible. Participants were also made aware that they did not have to answer anything that made them feel uncomfortable. Debrief sheets were handed out to participants at the end of each group and any further questions were answered.&#13;
Analysis&#13;
Both of the focus groups were audio recorded on an Edirol R-09HR recorder and then transferred to a computer so that they could be deleted from the device. Recordings were then transcribed verbatim using the app Audacity, with each participant being given an anonymous ID in case of withdrawal. From these transcriptions, thematic analysis was conducted using the software NVivo, which identified and inferred themes and opinions in order to draw conclusions regarding the discussed theories of Fear, Loss Aversion and Diffusion of Innovations. Other themes and inferences also came to light which will be outlined in the Results section. </text>
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                <text>Results&#13;
There were several overarching themes present in both focus groups which relate to the three discussed theories (Fear, Loss Aversion and DOI Theory) and the proposed areas for exploration, along with new themes which were not previously considered. In response to the second objective relating to participant motivations to buy and use the product, the main theme of ‘motivations’ was created to investigate motivations to buy and use the product. Under this theme came the categories ‘fear’, ‘loss aversion’ and ‘adoption’. Following this, further sub-categories were created for each category which each included ‘effective’ and ‘ineffective’. The ‘adoption’ category under this main theme also included the further sub-categories ‘explicit’ and ‘implicit’. The category ‘explicit’ was based on what participants said outright whereas the ‘implicit’ category was based on inferences and implications from the discussion. The next main theme was created in relation to the first objective which aimed to explore brand and product opinions and was named ‘brand ideas’ and contained the categories ‘name’, ‘product idea’, ‘incentives’ and ‘other opinions’. For the final and arguably most significant objective, the main theme of ‘development’ was created which contained the categories ‘audience’, ‘barriers’ and ‘ideas’ which aimed to assist in making informed suggestions as to how to proceed with product development. &#13;
Brand Name&#13;
The opinions relating to the brand name were very clear: participants did not like it. After being presented with three options of a possible brand name with no previous knowledge not one participant deemed ‘Bogallme’ appropriate for the product. Not one participant worked out that the word ‘Bogall’ was an anagram of the word ‘Global’ and the majority of participants chose the name ‘Scannit’ as the most appropriate for both the product and the brand. Many participants also had trouble in pronouncing the brand name correctly and it was pointed out in the first group that some individuals may have trouble reading it.&#13;
“It’s not compatible with my dyslexia that one! Not at all.” (PL: Age 22)&#13;
“The other two also worked like internationally, you’d have to think about that as even as people who speak English we didn’t get that.” (SD: Age 22)&#13;
Participants in both groups suggested that the name seemed quite childish and was trying too hard to be ‘down with the kids’ instead of being marketed at their age range. Another general consensus regarding the brand name was that it sounded similar to ‘Boggle’, the famous children’s board game, which again gave it a childish theme. &#13;
“It’s like the game Boggle you used to play when you were a kid.” (GP: Age 22)&#13;
Overall, it seems apparent that the brand name could have detrimental effects for the future development of the product.&#13;
Product Idea&#13;
Despite the brand name, after reading the product description, participants liked the concept of the product and agreed that it was something that they would use. &#13;
“I need this in my life (laughs)” (EG: Age 22)&#13;
The suggested uses for the stickers included: phones, keys, laptops, passports, luggage and notebooks. Participants said they were more likely to use the service in its current state (using Safari or another web browser) as opposed to downloading an app. However, some participants did have concerns surrounding the legitimacy of the product and would be wary when asked to fill in their details on the website. In terms of pricing, ideas of how much participants would pay for one sticker ranged from £1 to £10 with some participants suggesting that they would prefer to pay for a subscription service. The suggested subscription service consisted of paying a yearly fee for a certain number of stickers.&#13;
“Yeah you could subscribe for like a year and you get five stickers and you could use it on whatever you want” (RD: Age 22)&#13;
Despite this suggestion, many participants still disliked the idea of a subscription service and compared it to services such as Amazon Prime which continues to charge you if you forget to cancel it. As participants were all students or graduates, most liked the idea of paying per sticker best as it was affordable and not tying. However, another subscription idea came to light when participants were discussing potential problems with people forging the stickers. It was suggested that a subscription would include unlimited stickers and you would instead be paying to use the service as a whole. This would stop people from forging stickers because it would not be necessary once payment had already been made.&#13;
“Unless, if you do have a subscription then surely you’d be paying the same amount anyway no matter how many… so why would anyone copy theirs.” (GP: Age 22)&#13;
The issue of forging was quite a prominent topic within the second focus group. They suggested a variety of ways to overcome this: customisable stickers, laminated stickers and the creation of a unique QR code similar to that of Snapchat or Messenger. The idea of customisation was also popular in the first group. Several participants from this group said that they wouldn’t put the sticker on their mobile phone as it is currently for aesthetic reasons. They did however state that if the stickers came in different colours or were customizable, that they would be much more likely to purchase the product. &#13;
“I’d say make them customisable. If you could design your own stickers that would be… To match your phone case you could be like ‘ooh I’ll have it black with rose gold’ and then it would match and look cute” (GP: Age 22)&#13;
These participants did still agree that they would put the stickers on items other than phones, such as keys and passports, as it is not as important to participants for these items to be aesthetically pleasing. Stemming from this, the use of the stickers for travelling purposes was discussed in detail. Participants in the first group all agreed that it would be a useful addition to travelling supplies as the stickers could be placed on passports and luggage items. This was a very popular idea with the group for a number of reasons. Firstly, a passport doesn’t have the same sell-on value as a mobile phone, so you’d be much more likely to have it returned to you. Another suggested reason was the speed of having the item returned to you. If you are travelling across several different countries and using many different transportation methods, it may be difficult to continue without documents such as your passport and so a speedy return is very important. The final reason was that people often buy new products and innovations for when they travel due to excitement.&#13;
“You’re just looking for stuff to buy when you’re going travelling as well,  like ‘what do I need, what do I need’ so yeah I think that would work quite well.” (KR: Age 23)&#13;
&#13;
Fear and Loss Aversion&#13;
When asked how they would feel if they lost an item, most participants described feelings of stress and anxiety along with anger. Not all participants had the experience of losing an important item, but all at least had a friend or family member who had had this experience. Participants suggested that the feelings they experience when losing something would make them want to return an item and that they would be more likely to return an item of personal over financial value. &#13;
One of the main advantages of the product was discussed when participants compared the product to insurance. It was suggested that the product was a cheaper alternative that, although return is not guaranteed, is better than no back-up at all. In terms of product development, these findings suggest that there is potential to work with an insurance company to effectively market the Tracking System.&#13;
“It’s kind of like an insurance isn’t it? Like for your phone so… I’d pay like a tenner if it was a one off because people pay, I don’t know, I think mine…well I don’t pay insurance lol but I think it’s like sixty pounds” (AB: Age 22)&#13;
The time-saving of the product compared to insurance also produced positive comments about the product as it was explained how long it takes for an item to be replaced through insurance and how much effort this can be.&#13;
“Also, insurance is like an effort, like you have to file a claim and then it takes ages for them to get it back but if you could just like message someone you like might get it today. It’s easier” (TM: Age 20)&#13;
Another comparison to insurance was made in terms of the personal value of possessions. When discussing phones, participants pointed out that they’d prefer their original phone returned over a new phone of the same model as their original phone has all their photos, music and original settings on it which can often be difficult to retrieve if lost. &#13;
“(Be)cause you’ve got your photos and everything…like everything is set up on your phone in the way you like it. I hate setting up a phone when you first get it and you have to download everything and set it back up again.” (GP: Age 22)&#13;
Participants in the first group felt so strongly about the insurance aspect of the product that one attendee suggested that the brand partner up with a phone company and sell the product as an add-on for phone contracts. &#13;
“You need to have a partnership with like a phone company or something so when people start getting new phones and upgrades, say you partnership with O2 and you have it as part of your package on your phone or something.” (DF: Age 22)&#13;
&#13;
Incentives&#13;
The majority of participants stated that they would not require an incentive to use the service and to return an item and that empathy alone would be enough. Participants also suggested that the gratitude of the person who had lost the item could contribute towards them returning it. Some suggested that an incentive could add extra persuasion however it was quickly pointed out that there would be issues with monitoring any incentives. Examples of incentives discussed included: a lottery, money, and a points system whereby points could be collected to go towards a discount or a cash reward. Participants admitted that some of them would be likely to abuse the incentive as there would be no way to monitor whether people are actually finding items or are just working together with friends to make some money or have more chance in a lottery. Overall it was decided that any incentive would either be abused or would not encourage someone who was unlikely to return the item to return it. &#13;
“Yeah it would’ve been such a good idea saying five returns gets you a free sticker but people literally will just get each other’s items and be like oh” (BC: Age 22)&#13;
However, it is quite naïve of participants to expect all individuals to return items via the service with no incentive. They made good points surrounding the potential abuse of incentives, yet the use of incentives is not something that should simply be ignored because of this potential hurdle. It would be best to suggest plausible alternatives, such as the individual who lost the item having to pay an incentive to the returner in order to retrieve their item. &#13;
Adoption&#13;
When presented with the Diffusion of Innovations Model, all participants initially suggested that they would personally be in the centre of the model between Early and Late Majority or in the Late Majority. However, after asking what stage they thought they were at across different innovations such as iPhones and Apps this altered somewhat. From broader discussion it could be inferred that most participants would fit in the ‘Early Majority’ stage of the model as they would be more likely to buy the product if they could see it used successfully by someone else, but they also usually try new innovations earlier than the majority. &#13;
“I was probably an early majority. I’d say I’m between early and late majority.” (GP: Age 22)&#13;
“Yeah, I’d have to hear people like using it well, like see people all around using it” (RH: Age 22)&#13;
When questioned as to the type of person that would be situated in the first two stages of the model, there was a variety of answers. In the first group the most popular answer was people in an older age group, with many participants describing the habits and behaviours of their fathers. &#13;
“I actually feel like older people like my dad or someone, he’d totally buy into this” (EG: Age 22)&#13;
They suggested that due to the simplicity of the product and its purpose, this would be the first market to espouse. Many were surprised by their own responses to this question as they initially assumed that the product would be more popular with a younger audience. The second group also agreed on an older audience, with suggestions of ‘overprotective mothers’ buying the product to protect their children’s’ possessions. The second group also indicated that, whilst they didn’t think that students would be the Innovators or Early Adopters, businesses targeting students would still be very interested in the product. &#13;
“I think anyone who’s in the student-y industry. I reckon you could quite easily do this with like nightclubs. Anything to do with students people would want to get involved with.” (BC: Age 22)</text>
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                <text>An investigation of the influence of individual differences on susceptibility to product placement. </text>
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                <text>Product placement increased in popularity in 1982 when Reese’s Pieces Chocolate was included in E.T. the film, which led to a 65% increase in sales. Still to this day product placement is omnipresent within our cultural climate and research has supported that it enhances our purchase intentions. However, what remains unknown is how individual differences may influence product placement susceptibility. To address this gap, the current study investigated whether individual differences in cognitive capabilities, inhibitory control, age, familiarity, gender and timepoint enhance/reduce the likelihood of individuals' purchasing intentions being influenced by product placement. To do this, 55 participants (23 younger adults (Mage = 61.62(8.70)) and 22 older adults (Mage = 21.75(0.68)) were presented with images of four cups of coffee and asked to rank their purchase intentions/familiarity with the products. Following this, participants watched three scenes from Coronation Street, with the second clip including a product placement (Costa Coffee). Approximately 48 hours later, participants completed another purchase intentions questionnaire on the same four cups of coffee. The results highlighted that purchase intentions increased immediately post-clip; however they decreased 48 hours post-clip. Therefore, advertisers may use this information to discover ways in which the consumer can easily purchase the product immediately post-clip e.g. through QR codes. In regard to all other variables, no other significant relationships were found. Thus, it cannot be suggested to advertising agencies that product placement targeted to individuals who fulfil a given criteria (e.g. older adults, etc) will achieve optimal results when compared to non-targeted product placement.</text>
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                <text>Design &#13;
&#13;
The present quantitative study adopted a repeated measures design. There were several predictor variables: overall cognitive capabilities (including executive functioning; as assessed by the ACE-III; Hsieh et al., 2013), inhibitory control (as assessed by the Stroop effect), age, familiarity, gender, and timepoint. The dependent variable was susceptibility to product placement as measured by change in purchase intention.&#13;
&#13;
Participants&#13;
&#13;
At the time of the current studies design no published studies had investigated the influence of individual differences on product placement susceptibility, therefore the required sample size was modelled on the most comparable study the authors could source. Specifically, Hoek et al. (2022) investigated the influence of inhibitory control on advertising literacy activation and advertising susceptibility. Hoek et al. (2022) recruited 57 participants. Given the time restraints of data collection, the authors elected to recruit 55 participants.&#13;
&#13;
A total of 55 participants volunteered to participate in part one of the study. All participants were recruited via opportunity sampling through word of mouth and through advertisements placed on various Lancaster University Facebook pages (e.g. the Perception and Action Lab group).&#13;
&#13;
Participants were either aged between 18-25 (younger adults) or aged 50 and over (older adults). Out of the 55 participants, there were 27 younger adults (19 women; Mage = 60.93; SDage = 8.26) and 28 older adults (18 women; Mage = 21.78; SDage = 0.85). &#13;
&#13;
No participant had a known diagnosis of a psychiatric, neurological, or visual impairment, thus psychiatric, neurological, and visual impairments were not included in the analysis. All participants were White British/Irish. Therefore, there was no variation between ethnicities, thus ethnicity was not included in the analysis either. &#13;
&#13;
Given that cognitive capabilities was a key predictor variable within this study, it was necessary to ensure that participants with a known cognitive impairment or probable indication of cognitive impairment were removed from the study. Subsequently, all participants were screened for the probable presence of mild cognitive impairment through the Addenbrookes Cognitive Examination (ACE-III; Hsieh et al., 2013). After applying the pre-validated cut off point, 10 participants were excluded. Therefore, 45 participants were included in the analysis.&#13;
&#13;
Participants were either aged between 18-25 (younger adults) or aged 50 and over (older adults). Out of the 45 participants, there were 23 younger adults (16 women; Mage = 61.62; SDage = 8.70) and 22 older adults (17 women; Mage = 21.75; SDage = 0.68).&#13;
 &#13;
Materials &#13;
&#13;
Inhibitory Control&#13;
&#13;
Inhibitory control was measured through an online Stroop task developed and run through Psytoolkit (Stoet, 2010, 2017). Completion of this task required participants to ignore the meaning of the colour word and indicate the print colour. Participants were generally presented with a colour word and a print word that were incongruent to one another. Thus, participants needed to use their ability to inhibit a pertinent response (i.e. the print colour) and indicate the print colour, which would be done more efficiently by competent readers (von Hippel &amp; Gonsalkorale, 2005). Previous scholars have chosen to use the Stroop task, as it offers a good measure of individual variation in inhibition (e.g., Long &amp; Prat, 2002). &#13;
&#13;
As this study was conducted remotely, via Microsoft Teams share screen function, participants were asked to verbally indicate the print colour and the researcher pressed the related keys (e.g. r for red, g for green, b for blue, and y for yellow). Participants first completed four practice trials followed by 40 test trials.&#13;
&#13;
Cognitive Functioning &#13;
&#13;
Cognitive capabilities were measured using an adaptation of the Addenbrooke’s Cognitive Examination (ACE-III; Hsieh et al., 2013). The original version assesses the participants’ attention, memory, fluency, language, and visuospatial abilities and has a combined score of 100. Although the adapted version examines the same five cognitive domains, it has a combined score of 77, the reason being that some questions were removed, as they were not deemed suitable for an online study – the first two questions on attention, the first two questions on language, and the first three questions on visuospatial abilities. The original version's pre-validated cut off point was 88 (88%) and therefore the adapted version's was 68 (88.31%). The participants who scored below the pre-validated cut off point were removed prior to analysis to ensure that the presence of cognitive impairment would not confound the subsequent analysis.&#13;
&#13;
Demographic and Health Characteristics &#13;
&#13;
Demographic information, including age, ethnicity, and gender, and background health information, including whether the participant had a current or history of a diagnosis of any cognitive, neurological, visual, or psychiatric impairments, was collected through an online Qualtrics Questionnaire. &#13;
&#13;
Purchase Intentions Questionnaire&#13;
&#13;
Prior to the questionnaire, participants were presented with the name and an image of each of the four cups of coffee. Purchase intentions of the four cups of coffee were then measured using a 7-point Likert scale. Participants were asked to rate on a scale of 1-7, 1 being ‘Extremely unlikely’ to 7 being ‘Extremely likely’, how likely they were to purchase a cup of coffee from: Caffè Nero, Costa Coffee, Greggs, and Starbucks. &#13;
&#13;
Comparably, familiarity was also measured using a 7-point Likert scale. Participants were asked to rate on a scale of 1-7, 1 being ‘Extremely unfamiliar’ to 7 being ‘Extremely familiar’ with how familiar they were with each cup of coffee from Caffè Nero, Costa Coffee, Greggs, and Starbucks.&#13;
&#13;
Purchase intentions and familiarity were measured using a 7-point Likert scale, rather than the commonly used 5-point Likert scale, as the inclusion of several options enhances the likelihood of acquiring a more accurate response (Joshi et al., 2015). &#13;
&#13;
It was important that purchase intention and familiarity of Costa Coffee was assessed alongside alternative brands, so that it was not made apparent that the study was focusing upon the participants' purchase intention ranking of Costa Coffee only. Therefore, Caffè Nero, Greggs, and Starbucks were chosen alongside Costa Coffee, because according to a survey conducted by Lock (2022), they are the UK’s top four leading coffee shop chains. The images were provided by Adobe Stock (2019) and Dreams Time (2019a, 2019b, 2019c).&#13;
&#13;
Product Placement Video&#13;
&#13;
The British TV Soap Coronation Street was selected, as prior research (e.g. Armstrong, 2018) suggests that it is popular amongst both younger and older adults (YouGov, 2011). The first clip chosen was a scene from 8th January 2018 Part 1, lasting 1 minute 16 seconds. The second clip chosen was a scene from 29th January 2018 Part 1, lasting 1 minute 15 seconds. The third clip chosen was a scene from 7th February 2018 Part 2, lasting 1 minute 23 seconds. It was the second scene shown that included the product placement (Costa Coffee). The researcher screen recorded each clip from https://www.dailymotion.com/gb and saved them into an encrypted file on a password-protected computer.&#13;
&#13;
Procedure&#13;
&#13;
A member of the psychology department research ethics committee approved the study before it was undertaken. Participants were invited to attend a 40–50-minute online Microsoft Teams meeting on a set date and time agreed on by the participant and the researcher. To commence, the researcher shared their screen and aided the participant in reading the participant information sheet and consent form via an online Qualtrics Questionnaire. At this time, participants were informed of their right to withdraw up to 2 weeks after participating without giving any reason and they were told their personal information would remain confidential and would be stored in encrypted files (that only myself and my supervisor have access to) on password-protected computers. The participants were only able to progress into the study on attainment of verbal consent. &#13;
&#13;
Participants were then asked to disclose various demographic characteristics (e.g., age and gender) and details relating to their current health status (e.g., any cognitive or visual impairments). The participants were then presented with four images of cups of coffee from Caffè Nero, Costa Coffee, Greggs, and Starbucks. They were then asked to rank their purchase intentions and familiarity, on a seven-point Likert scale, with these products via an online Qualtrics Questionnaire. Following this, participants were asked to watch three short scenes from Coronation Street. The second clip shown included a product placement of Costa Coffee. The researcher then implemented an online Stroop task using Psytoolkit (Stoet, 2010, 2017). The participants were also screened for the presence of mild cognitive impairments through the ACE. After this, the participants were presented with the same four images and asked to rank their purchase intentions of these products via the online Qualtrics Questionnaire (see Figure 1).  &#13;
&#13;
Approximately 48 hours after completing the first part of the study, participants were sent an email invitation to complete another online Qualtrics Questionnaire. Participants were first asked to provide their participation number, which could be found in the email. They were then shown the same four images of cups of coffee and asked to rank their purchase intentions. Finally, the participants were provided with a debrief form at the end of the online Qualtrics Questionnaire (see Figure 2). This debrief disclosed the small degree of deception involved. Specifically, it was explained that participants were not informed at the start that the study considered product placement, as this might have influenced the subsequent data. Participants were reminded that they had the right to withdraw up to 2 weeks after participating and were provided with contact details in case they had any questions. &#13;
&#13;
The participants' purchase intentions of the four cups of coffee were measured three times throughout the course of the two studies: pre-clip, immediately post-clip, and 48 hours post-clip. This was to see whether the participants' purchase intentions for the four cups of coffee, specifically Costa Coffee, had increased or decreased following the product placement clip and whether their ranking would withstand the test of time (48 hours post-clip). This is why the participant were asked to include their participant number in part two, so that the participants prolonged purchase intention (48 hours post-clip) could be traced back to their earlier purchase intention rankings (pre-clip and immediately post-clip).&#13;
&#13;
Figure 1. &#13;
&#13;
A flowchart of part one tasks. &#13;
&#13;
Figure 2. &#13;
&#13;
A flowchart of part two tasks. &#13;
&#13;
Data Processing &#13;
&#13;
Inhibitory Control&#13;
&#13;
Participants raw Stroop data were downloaded from Psytoolkit into a Microsoft Excel file and saved in an encrypted files on a password-protected computer. From this raw data Stroop effect (the average incompatible conditions response time (ms) - compatible conditions response time (ms)) and percentage error rate (which involved adding the total of incorrect and timed out responses and dividing it by 40 (number of trials)) were calculated. Stroop effect and percentage error rate were used as an indicator of the participants inhibitory control capabilities. Specifically, a high Stroop effect would suggest less difficulty in inhibiting interference and a higher error rate would suggest reduced inhibitory capabilities.  &#13;
&#13;
Cognitive Functioning &#13;
&#13;
The scores of the ACE-III were added and entered into the Microsoft Excel file, which was saved in an encrypted files on a password-protected computer. A higher score was indicative of superior cognitive functioning. &#13;
&#13;
Demographic and Health Characteristics &#13;
&#13;
To ensure all demographic and health data was readable by R-Studio all variables were dummy coded using numerical values. So, for instance, to determine the participants' gender, they were asked ‘What gender do you identify’ and given the option to choose from one of several responses. Each response was allocated a number, for example, 1 = Man, 2 = Woman, etc, and this was entered into the Microsoft Excel document.&#13;
&#13;
Susceptibility to product Placement (change in Purchase Intentions)&#13;
&#13;
To investigate the susceptibility to product placement, two difference in purchasing behaviour score were calculated (one for short duration, one for prolonged duration). To calculate these values, the likelihood of purchasing the product value prior to watching the clip was subtracted from likelihood of purchasing the product value after watching the clip (either immediately post-clip or 48 hours after). A positive difference meant that purchase intentions had increased following placement clip. A negative difference meant that purchase intentions had decreased following placement clip. A difference of zero meant that the placement clip had failed to alter purchase intentions&#13;
&#13;
Familiarity&#13;
 &#13;
The familiarity ratings of Costa Coffee were entered into the Microsoft Excel file, which was saved in an encrypted files on a password-protected computer. The higher the score, the more familiar the participant was with the product. &#13;
&#13;
Data Analysis &#13;
&#13;
To analyse the data, a linear mixed effects model was chosen. The reason being that the current study employs a repeated measures design, and a linear mixed effects model permits an analysis of hierarchically structured data (Baayen et al., 2008). &#13;
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                  <text>Questionnaire-based study</text>
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                  <text>An analysis of self-report data from the administration of questionnaires(s)</text>
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                <text>An investigation of the influence of individual differences on susceptibility to product placement</text>
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                <text>Ellen Dimeck</text>
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                <text>14/09/2022</text>
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            <name>Description</name>
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                <text>Product placement increased in popularity in 1982 when Reese’s Pieces Chocolate was included in E.T. the film, which led to a 65% increase in sales. Still to this day product placement is omnipresent within our cultural climate and research has supported that it enhances our purchase intentions. However, what remains unknown is how individual differences may influence product placement susceptibility. To address this gap, the current study investigated whether individual differences in cognitive capabilities, inhibitory control, age, familiarity, gender and timepoint enhance/reduce the likelihood of individuals' purchasing intentions being influenced by product placement. To do this, 55 participants (23 younger adults (Mage = 61.62(8.70)) and 22 older adults (Mage = 21.75(0.68)) were presented with images of four cups of coffee and asked to rank their purchase intentions/familiarity with the products. Following this, participants watched three scenes from Coronation Street, with the second clip including a product placement (Costa Coffee). Approximately 48 hours later, participants completed another purchase intentions questionnaire on the same four cups of coffee. The results highlighted that purchase intentions increased immediately post-clip; however they decreased 48 hours post-clip. Therefore, advertisers may use this information to discover ways in which the consumer can easily purchase the product immediately post-clip e.g. through QR codes. In regard to all other variables, no other significant relationships were found. Thus, it cannot be suggested to advertising agencies that product placement targeted to individuals who fulfil a given criteria (e.g. older adults, etc) will achieve optimal results when compared to non-targeted product placement.</text>
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                <text>Marketing, Product placement, Individual differences, Cognitive capabilities, Inhibitory control, Age, Familiarity, Gender, Purchase intentions.</text>
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                <text>Method Design The present quantitative study adopted a repeated measures design. There were several predictor variables: overall cognitive capabilities (including executive functioning; as assessed by the ACE-III; Hsieh et al., 2013), inhibitory control (as assessed by the Stroop effect), age, familiarity, gender, and timepoint. The dependent variable was susceptibility to product placement as measured by change in purchase intention. Participants At the time of the current studies design no published studies had investigated the influence of individual differences on product placement susceptibility, therefore the required sample size was modelled on the most comparable study the authors could source. Specifically, Hoek et al. (2022) investigated the influence of inhibitory control on advertising literacy activation and advertising susceptibility. Hoek et al. (2022) recruited 57 participants. Given the time restraints of data collection, the authors elected to recruit 55 participants. A total of 55 participants volunteered to participate in part one of the study. All participants were recruited via opportunity sampling through word of mouth and through advertisements placed on various Lancaster University Facebook pages (e.g. the Perception and Action Lab group). Participants were either aged between 18-25 (younger adults) or aged 50 and over (older adults). Out of the 55 participants, there were 27 younger adults (19 women; Mage = 60.93; SDage = 8.26) and 28 older adults (18 women; Mage = 21.78; SDage = 0.85). No participant had a known diagnosis of a psychiatric, neurological, or visual impairment, thus psychiatric, neurological, and visual impairments were not included in the analysis. All participants were White British/Irish. Therefore, there was no variation between ethnicities, thus ethnicity was not included in the analysis either. Given that cognitive capabilities was a key predictor variable within this study, it was necessary to ensure that participants with a known cognitive impairment or probable indication of cognitive impairment were removed from the study. Subsequently, all participants were screened for the probable presence of mild cognitive impairment through the Addenbrookes Cognitive Examination (ACE-III; Hsieh et al., 2013). After applying the pre-validated cut off point, 10 participants were excluded. Therefore, 45 participants were included in the analysis. Participants were either aged between 18-25 (younger adults) or aged 50 and over (older adults). Out of the 45 participants, there were 23 younger adults (16 women; Mage = 61.62; SDage = 8.70) and 22 older adults (17 women; Mage = 21.75; SDage = 0.68). Materials Inhibitory Control Inhibitory control was measured through an online Stroop task developed and run through Psytoolkit (Stoet, 2010, 2017). Completion of this task required participants to ignore the meaning of the colour word and indicate the print colour. Participants were generally presented with a colour word and a print word that were incongruent to one another. Thus, participants needed to use their ability to inhibit a pertinent response (i.e. the print colour) and indicate the print colour, which would be done more efficiently by competent readers (von Hippel &amp;amp; Gonsalkorale, 2005). Previous scholars have chosen to use the Stroop task, as it offers a good measure of individual variation in inhibition (e.g., Long &amp;amp; Prat, 2002). As this study was conducted remotely, via Microsoft Teams share screen function, participants were asked to verbally indicate the print colour and the researcher pressed the related keys (e.g. r for red, g for green, b for blue, and y for yellow). Participants first completed four practice trials followed by 40 test trials. Cognitive Functioning Cognitive capabilities were measured using an adaptation of the Addenbrooke’s Cognitive Examination (ACE-III; Hsieh et al., 2013). The original version assesses the participants’ attention, memory, fluency, language, and visuospatial abilities and has a combined score of 100. Although the adapted version examines the same five cognitive domains, it has a combined score of 77, the reason being that some questions were removed, as they were not deemed suitable for an online study – the first two questions on attention, the first two questions on language, and the first three questions on visuospatial abilities. The original version's pre-validated cut off point was 88 (88%) and therefore the adapted version's was 68 (88.31%). The participants who scored below the pre-validated cut off point were removed prior to analysis to ensure that the presence of cognitive impairment would not confound the subsequent analysis. Demographic and Health Characteristics Demographic information, including age, ethnicity, and gender, and background health information, including whether the participant had a current or history of a diagnosis of any cognitive, neurological, visual, or psychiatric impairments, was collected through an online Qualtrics Questionnaire. Purchase Intentions Questionnaire Prior to the questionnaire, participants were presented with the name and an image of each of the four cups of coffee. Purchase intentions of the four cups of coffee were then measured using a 7-point Likert scale. Participants were asked to rate on a scale of 1-7, 1 being ‘Extremely unlikely’ to 7 being ‘Extremely likely’, how likely they were to purchase a cup of coffee from: Caffè Nero, Costa Coffee, Greggs, and Starbucks. Comparably, familiarity was also measured using a 7-point Likert scale. Participants were asked to rate on a scale of 1-7, 1 being ‘Extremely unfamiliar’ to 7 being ‘Extremely familiar’ with how familiar they were with each cup of coffee from Caffè Nero, Costa Coffee, Greggs, and Starbucks. Purchase intentions and familiarity were measured using a 7-point Likert scale, rather than the commonly used 5-point Likert scale, as the inclusion of several options enhances the likelihood of acquiring a more accurate response (Joshi et al., 2015). It was important that purchase intention and familiarity of Costa Coffee was assessed alongside alternative brands, so that it was not made apparent that the study was focusing upon the participants' purchase intention ranking of Costa Coffee only. Therefore, Caffè Nero, Greggs, and Starbucks were chosen alongside Costa Coffee, because according to a survey conducted by Lock (2022), they are the UK’s top four leading coffee shop chains. The images were provided by Adobe Stock (2019) and Dreams Time (2019a, 2019b, 2019c). Product Placement Video The British TV Soap Coronation Street was selected, as prior research (e.g. Armstrong, 2018) suggests that it is popular amongst both younger and older adults (YouGov, 2011). The first clip chosen was a scene from 8th January 2018 Part 1, lasting 1 minute 16 seconds. The second clip chosen was a scene from 29th January 2018 Part 1, lasting 1 minute 15 seconds. The third clip chosen was a scene from 7th February 2018 Part 2, lasting 1 minute 23 seconds. It was the second scene shown that included the product placement (Costa Coffee). The researcher screen recorded each clip from https://www.dailymotion.com/gb and saved them into an encrypted file on a password-protected computer. Procedure A member of the psychology department research ethics committee approved the study before it was undertaken. Participants were invited to attend a 40–50-minute online Microsoft Teams meeting on a set date and time agreed on by the participant and the researcher. To commence, the researcher shared their screen and aided the participant in reading the participant information sheet and consent form via an online Qualtrics Questionnaire. At this time, participants were informed of their right to withdraw up to 2 weeks after participating without giving any reason and they were told their personal information would remain confidential and would be stored in encrypted files (that only myself and my supervisor have access to) on password-protected computers. The participants were only able to progress into the study on attainment of verbal consent. Participants were then asked to disclose various demographic characteristics (e.g., age and gender) and details relating to their current health status (e.g., any cognitive or visual impairments). The participants were then presented with four images of cups of coffee from Caffè Nero, Costa Coffee, Greggs, and Starbucks. They were then asked to rank their purchase intentions and familiarity, on a seven-point Likert scale, with these products via an online Qualtrics Questionnaire. Following this, participants were asked to watch three short scenes from Coronation Street. The second clip shown included a product placement of Costa Coffee. The researcher then implemented an online Stroop task using Psytoolkit (Stoet, 2010, 2017). The participants were also screened for the presence of mild cognitive impairments through the ACE. After this, the participants were presented with the same four images and asked to rank their purchase intentions of these products via the online Qualtrics Questionnaire (see Figure 1). Approximately 48 hours after completing the first part of the study, participants were sent an email invitation to complete another online Qualtrics Questionnaire. Participants were first asked to provide their participation number, which could be found in the email. They were then shown the same four images of cups of coffee and asked to rank their purchase intentions. Finally, the participants were provided with a debrief form at the end of the online Qualtrics Questionnaire (see Figure 2). This debrief disclosed the small degree of deception involved. Specifically, it was explained that participants were not informed at the start that the study considered product placement, as this might have influenced the subsequent data. Participants were reminded that they had the right to withdraw up to 2 weeks after participating and were provided with contact details in case they had any questions. The participants' purchase intentions of the four cups of coffee were measured three times throughout the course of the two studies: pre-clip, immediately post-clip, and 48 hours post-clip. This was to see whether the participants' purchase intentions for the four cups of coffee, specifically Costa Coffee, had increased or decreased following the product placement clip and whether their ranking would withstand the test of time (48 hours post-clip). This is why the participant were asked to include their participant number in part two, so that the participants prolonged purchase intention (48 hours post-clip) could be traced back to their earlier purchase intention rankings (pre-clip and immediately post-clip). Figure 1. A flowchart of part one tasks. Figure 2. A flowchart of part two tasks. Data Processing Inhibitory Control Participants raw Stroop data were downloaded from Psytoolkit into a Microsoft Excel file and saved in an encrypted files on a password-protected computer. From this raw data Stroop effect (the average incompatible conditions response time (ms) - compatible conditions response time (ms)) and percentage error rate (which involved adding the total of incorrect and timed out responses and dividing it by 40 (number of trials)) were calculated. Stroop effect and percentage error rate were used as an indicator of the participants inhibitory control capabilities. Specifically, a high Stroop effect would suggest less difficulty in inhibiting interference and a higher error rate would suggest reduced inhibitory capabilities. Cognitive Functioning The scores of the ACE-III were added and entered into the Microsoft Excel file, which was saved in an encrypted files on a password-protected computer. A higher score was indicative of superior cognitive functioning. Demographic and Health Characteristics To ensure all demographic and health data was readable by R-Studio all variables were dummy coded using numerical values. So, for instance, to determine the participants' gender, they were asked ‘What gender do you identify’ and given the option to choose from one of several responses. Each response was allocated a number, for example, 1 = Man, 2 = Woman, etc, and this was entered into the Microsoft Excel document. Susceptibility to product Placement (change in Purchase Intentions) To investigate the susceptibility to product placement, two difference in purchasing behaviour score were calculated (one for short duration, one for prolonged duration). To calculate these values, the likelihood of purchasing the product value prior to watching the clip was subtracted from likelihood of purchasing the product value after watching the clip (either immediately post-clip or 48 hours after). A positive difference meant that purchase intentions had increased following placement clip. A negative difference meant that purchase intentions had decreased following placement clip. A difference of zero meant that the placement clip had failed to alter purchase intentions Familiarity The familiarity ratings of Costa Coffee were entered into the Microsoft Excel file, which was saved in an encrypted files on a password-protected computer. The higher the score, the more familiar the participant was with the product. Data Analysis To analyse the data, a linear mixed effects model was chosen. The reason being that the current study employs a repeated measures design, and a linear mixed effects model permits an analysis of hierarchically structured data (Baayen et al., 2008).</text>
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                <text>Lancaster University</text>
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                <text>Reece Graham</text>
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