Effect of Attention and Noise on Echoic Memory as Indexed by the N1-Adaptation.
Attention, Noise, N1-adaptation, auditory sensory memory
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.
Participants 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. Equipment and Procedure for EEG measurements 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. Data Analysis 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. Calculating the lifetime of adaptation (τ) 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. 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. Results 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.
Effects of service brands’ current marketing strategies on customer attitude and behaviour
This project investigated current marketing strategies used by service brands, including car insurance and household energy companies, on customer’s attitudes and behaviours. The investigation involved a nationally representative sample of 1,977 participants completing an online survey, along with 30 participants taking part in a supporting qualitative online community panel exploring customers’ attitudes in more depth. Descriptive analysis showed that although participants’ loyalty reasons and bad provider experiences were predominantly determined by price, service quality was also an important factor. When choosing service providers, participants showed no preference between price and service, however slightly preferred price over reputation. Furthermore, significant correlations were found for the majority of provider switching attitudes and switching behaviours. Segmentation analysis identified four types of customers based on awareness of offers and convenience to switch: ‘Passive Loyals’, ‘Sceptical Loyals’, ‘Loyal Opportunity Switchers’ and ‘Conditioned Switchers’. A pattern was found amongst age groups – the older the participant, the more likely they preferred new customer deals over loyalty offers, were more interested in price over service quality and brand reputation, and had more expertise in the service industry. Due to the importance of customer retention (Berry, 1983), results implied brands should focus on loyalty rewards, along with gaining customers’ trust in their service quality and reliability.
Materials and procedure The online survey included both closed and open questions, thus a mixture of quantitative and qualitative methods. Participants were asked a few demographic questions: their gender, age, employment status, type of residence, location, and how long they had been a UK resident. Those who had not been screened were quizzed on their switching and service provider behaviours and attitudes. The questions were repeated for each service type, depending on whether participants had confirmed to paying for, or making decisions on electricity, gas or car insurance, and whether they’re household energy was on a dual fuel package or organised separately. The questions that were repeated were a select few, which required separate data for each service type. These included inquiries into people’s prior switching behaviour, reasons for maintaining a relationship with their current provider, and any ‘bad’ experiences they had encountered with a service provider. This was then followed by general attitudinal scales concerned with loyalty and switching amongst service providers. The data was collected in Confirmit, a software used to create, monitor and analyse online surveys (http://www.confirmit.com/). The quantitative information was analysed in Reportal, Confirmit’s analysis feature. The qualitative answers were transferred into Microsoft Excel, and examined through the CIT (Flanagan, 1954). Stage 2: Method The second stage of the project involved segmenting participants into different groups, in order to identify different people’s needs and desires in regard to switching and loyalty, and how brands should consider different types of individuals in their marketing and advertising. First, segmentation dimensions were established, and every participants was assigned to a particular segmentation cluster. Secondly, the different segments were profiled to make each group as distinct as possible. Segmentation Identifying the segments was explorative, thus there were no set guidelines as to which dimensions to use. However, segmentation was based around the idea of switching and loyalty, and whether participants were able to be classed as different types of customers according to this. Attitudinal scales used in the online survey in stage 1 were either negatively or positively related to switching. Using k cluster means analysis on SPSS, the following variables were used as dimensions for the segmentation (along with the statements used in the online survey): Convenience of switching: I find that switching service providers is inconvenient Awareness of other deals: I’m not aware of offers available from other providers other than my current one The first variable determined how constrained individuals were from switching brands. This gave an idea of whether participants felt dedicated or constrained by service brands (constrained by brands: Stanley & Markman, 1992). If a person found switching convenient, they were not held by constraints to stay within the company, thus were more likely to remain with the provider due to their brand dedication. The second variable determined participants’ characteristics, whether they actively sought to evaluate other providers’ offers (awareness of other offers: Zeithaml, 1981). According to the research, if someone showed both awareness of other offers and convenience to switch, the individual felt they were more able to switch and were presumably more likely to switch. Both statements were answered on a 10 point scale in the online survey, thus when segmentation divisions were made according to these dimensions, the following cluster centres for each segment were identified: segments I find that switching service providers is inconvenient I’m not aware of offers available from other providers other than my current one 1 8 8 2 8 3 3 5 6 4 3 2 Table 4. Typical scores observed for each statement across the 4 segments identified Each participant who took part in the survey was assigned to one of the four segments according to their scores on the two dimensions. Whichever segment cluster centres were closest to their scores determined their segment group. The next phase of the segmentation process was profiling each group in order to make them as identifiable and different to the other groups as possible. This was carried out by comparing answers from the online survey by producing crosstabs across the four clusters. Once the variation of answers were cross tabbed, comparisons were able to be carried out. This gave an insight into how many people in a particular segment gave a certain answer to the questions. In order to find any significant differences from the overall mean, answers were indexed. Indexing Indexing was used to look at how over-represented or under-represented certain characteristics were for the four segments, relative to the base sample (1,977 participants). This was carried out by calculating an index score: Percentage incidence of the variable for the target group x 100 Percentage incidence of the variable for the base group The index score indicated whether the variables for the two groups were showing significant differences. Comparing them gave an idea of which variable was over indexing the most or least, giving a picture of what ‘ingredients’ may be making up the main differences between segments. Generally an index of less than 80 or greater than 120 was considered significantly statistically different. Supporting qualitative attitudes This was supported by a of the project involved an in-depth qualitative investigation, exploring participants’ attitudes on brand loyalty and switching, past experiences with household energy and car insurance providers, and attitudes on current loyalty and switching strategies. Participants were identified into 1 of the four segments and analysed through noting important themes and patterns of people’s attitudes in the data.
Examining the Effect of Anxiety on the Development of False Memory
memory, generalized anxiety disorder, confidence-accuracy calibration
Up till the late 70s, people believed their memory worked in similar to a video-recorder, accurately collecting and storing every information seen and heard. This belief was brought to question after researchers started thorough investigation on memory, and found that in actuality memory is highly impressionable and prone to numerous errors such as the formation of false memories. There now appears to have been found many causes for the formation of false memories. However, limited to no research exists on the effect of generalized anxiety disorder (GAD) on formation of false memories. The present study aimed to investigate the effect of GAD on the development of false memories by using the misinformation effect paradigm. Confidence-accuracy calibration (CAC) was assessed as a secondary analysis. Participants (N = 100) were recruited through online means and took part in a 15-45-minute-long experiment involving neutral stimuli. The experiment consisted of a video of an event and were subsequently asked to read a text description with misinformation after partaking in filler tasks. Afterwards their memory of the original event was tested. Results demonstrate that GAD and false memory are not significantly associated. CAC analysis revealed that participants were relatively aware of when their memory had been distorted by providing low confidence ratings to more inaccurate items and higher confidence ratings to accurately recalled answers. Additionally, false memories created due to misinformation was significantly observed, though GAD did have any influence over this. To conclude, GAD does not contribute to the formation of false memories.
A total of 100 participants were recruited and provided with an online link through social media sites, ages ranging from 18-50. Out of the recruited participants, 66 identified as females, 31 as males, two as non-binary and, one preferred not to say. The link begins with the consent sheet, and once the participants click to agree, they were then redirected to the start of the experiment. Participant’s anxiety was tested by administering a standardized and validated tool, the Generalized Anxiety Disorder Questionnaire (GAD-7) (Spitzer et al., 2006), (see Appendix B). GAD7 has seven rating scale questions, and the participant’s anxiety was calculated by assigning scores of zero (not at all), one (several days), two (more than half the days), and three (nearly every day). Samples questions include “worrying too much about different things?” and “becoming easily annoyed or irritable?”. For scores ten and above, GAD-7 has a specificity of 82% and sensitivity of 89% (Kroenke et al., 2007). Cut-off points for the scores are a score of five for mild anxiety, ten for moderate anxiety, and 15 for severe anxiety. For the present study, participants who scored nine and below were grouped under “low” anxiety, and participants who scored ten and above were grouped under “high” anxiety. The stimulus set developed by Okado and Start (2005) were used for this study. Two neutral stimuli were obtained, and each stimulus consisted of 50 coloured digital images. These were compiled into a short video, with each image displayed for 300ms, and the whole video lasting 150s. Out of the 50 slides, 12 of them were critical, meaning these slides consisted of an item that would later be altered in the text description of the event, hence providing the misinformation. The two stimuli are summarized below. Stimulus One is about a female named Rachel who was doing her work at home, then feels hungry and checks her refrigerator for food, sees that there is not much at hand, and so goes grocery shopping. She was seen viewing different aisles for grocery and sees a friend in there as well. She then pays the bill and takes the elevator back home and stores the food away. (See Appendix C for the critical images) Stimulus Two is about a male student named Nicholas who was just seen leaving his classroom to go sit on a bench in the hallway, studying between classes and runs into three friends: a male (Henry) who displays his new shirt, another male (Frank) who wanted to know when an exam was scheduled, and a female (Stephanie) whose conversation was interrupted by a phone call. (See Appendix F for the critical images) Text descriptions derived from Okado and Stark’s (2005) stimulus set were used for the present study. For both Stimulus One and Stimulus Two, 12 critical details from the original event were altered in the text description, with every other detail remaining true to the original event. To give an example of a critical detail, in stimulus One’s original event a woman was seen picking up two bananas, whereas in the text description it was written, “She started with the healthy items and picked up five bananas.” (See Appendix D and G). Recognition test involving three choice options derived from Okado and Stark (2005) were used for the present study. The test was composed of 18 detailed questions concerning the video presented at the beginning (the original event phase). Out of the 18 questions, 12 were critical questions (i.e., regarding the events that were changed in the text description), and six were control questions (i.e., regarding events that were consistent throughout the video and text description). After each question participants reported their confidence in their response on a scale of 0-100, where zero indicated not at all confident and 100 indicated extremely confident. A sample critical question was, “In the fruits section, how many bananas did Rachel pick up?” Participants were required to choose one answer out of the three: (1) one banana (filler option), (2) two bananas (as seen from the original event’s video), and (3) five bananas (altered detail presented in the text description). Control questions were also akin to critical questions, e.g., “Where does Rachel put her shopping bags in the kitchen?” For answers: (1) on the counter (as seen from the original event’s video), (2) on the floor (filler option), (3) on the table (filler option). (See Appendix E and H). The current research was designed as a 2x2x2 mixed factorial study. All participants had to complete all aspects of the experiment; henceforth, the memory accuracy for control and critical items were within-subject factors. The levels of anxiety (high and low) and stimulus (one and two), were between-subject factors. Participants were tested individually online and were informed they are partaking in a study concerning memory and mood. The experiment was created online in Qualtrics, and upon viewing, participants are first required to consent. The consent sheet had also explained that the study is completely voluntary and participants can withdraw at any point. Subsequently, participants were to either watch stimulus One or Two (the two videos were set to view randomly), and a timer was set to ensure no skipping was allowed. Immediately afterwards, participants had to fill in few demographic questions pertaining to their age, education, and employment (see Appendix A). Afterwards, they were required to complete the GAD-7. These two questionnaires served as a filler task to ensure sufficient time to allow some memory decay between watching the video of the event and reading the text description of the event. Next, participants read the altered text descriptions of the original event shown in the video. Participants were unaware of the changes brought and were told to read the text descriptions which had described the events from the original video. Akin to the video, a two-minute timer was set to ensure participants do not skip the text descriptions. Thereupon, participants were diverted to a game of sudoku, where they would spend at least five minutes playing it. They were instructed that we were interested in knowing how individuals play games and so were not aware of the true nature of the game, which was to serve as a second filler task. Lastly, participants completed the recognition memory test, where they had to choose the correct answer out of the three response options and to indicate their confidence for each answer to assess the C-A relationship. CAC layout is relatively simple by computing the accuracy for each level of confidence. When perfect calibration occurs, it is a straight line with the decisions being made at each level of confidence are all correct. Once completed, participants were thanked for their time spent on the experiment and presented with the debrief sheet explaining the true nature of the study The debrief sheet was provided with international and local numbers for people from different continents should they need to seek immediate assistance. Participants spent around an estimate of 15-45 minutes to complete the experiment.
Experiencing social acceptance and rejection through ‘likes’ and ‘dislikes’: Does sleep quality affect the processing of social rewards?
Adolescence Pupil dilation Social feedback Reward Rejection Sleep debt.
In adolescence, high importance is placed on peer evaluations and social rewards have increased salience during this developmental period. Sleep patterns also change in adolescence, as teenagers typically experience insufficient sleep. This research measured the pupil dilation of forty-four adolescents aged 16 to 18 using two tasks (audio and visual) to investigate whether sleep duration influenced the way social acceptance and rejection were processed. Sleep duration scores were obtained using the measure of sleep debt; this was calculated by subtracting sleep duration during the week from sleep duration at the weekend, plus weekday bedtime. It was expected that higher sleep debt would be linked to increased pupil reactivity towards social feedback and that there would be a greater pupil dilation in response to social rejection compared to social acceptance. In the visual task, it was found that sleep debt affected males and females differently when processing social rewards, as females with high sleep debt showed increased pupil dilation towards positive feedback compared to negative feedback, whereas males with low sleep debt showed a larger dilation towards positive feedback than females. It was also found that females with lower sleep debt gave more likes than dislikes when rating photos. This implies that sleep duration affects the social feedback adolescents provide. When a male voice was used in the audio task, more pupillary reactivity towards social acceptance was observed, however when a female voice was used, pupils dilated more in response to social rejection. Future research should further investigate these gender differences.
Participants Forty-four participants (N=44) were recruited from Haslingden High School and Sixth Form to participate in this research. The participants (35 female, 9 male) were all between the ages of 16 and 18 (Mage = 16.98, SDage = .63). Students in Psychology, Sociology and English classes were given the opportunity to participate in the research and contacted the researcher via email if they wished to participate. Each participant provided their informed consent before beginning the study. Materials Photo ratings. Firstly, the participants were shown a PowerPoint containing 40 photos, which had been previously collected by the researcher, and featured adolescents which the participants did not know. Each photo was displayed individually for four seconds, meaning that the presentation lasted two minutes and forty seconds in total. Participants were provided with a sheet of paper on which they had an option to tick either ‘like’ or ‘dislike’ for each photo on the PowerPoint (see Appendix A). The total number of likes was calculated for each participant. Eye tracker. An eye-tribe desktop eye tracker with a 30Hz sampling rate was used to measure the pupil dilation of the participants in response to stimuli on two tasks - a visual task and an audio task. A chin rest was used to ensure the participants kept their heads still. Visual task. The visual task involved showing the participants the same 40 photos which they had previously been shown in the photo rating task, however, each photo had either a ‘like’ symbol or ‘dislike’ symbol (see Figure 1) in the bottom right hand corner. Participants were informed prior to beginning the task that if a photo contained the ‘like’ symbol, it meant that the individual in the photo had liked the participant’s picture, however the ‘dislike’ symbol meant that the individual in the photo had disliked the participant’s picture. The presentation of photos was randomised across participants Audio task. The audio task involved the participants listening to forty voice recordings, which each lasted between six and seven seconds in length. Twenty of these recordings were nice comments and twenty were nasty comments, which were found on online social media platforms. An example of a nice comment is; ‘You look unreal and your outfit is amazing. You are a true inspiration to everyone’ and an example of a nasty comment is; ‘You are so fake, and you are such a liar. Every single thing you say is a lie’ (see Appendix B for the complete list of comments). A male voice read out half of the nice and half of the nasty comments, and a female voice featured in the other half of the recordings. The nice comments were characterised as positive social feedback, and the nasty as negative social feedback. The presentation of nice and nasty comments was randomised across participants. The audio material was rated for emotional valence and arousal; the former being how positive or negative the recordings were, and the latter being the intensity of this positivity or negativity (Citron, Gray, Critchley, Weekes, & Ferstl, 2014). See Appendix C for the emotional valence and arousal scores, which were rated by six individuals using Qualtrics. Presentation of the nice and nasty comments was randomised across participants. Questionnaires. Participants were asked to complete two questionnaires; one which was an adaptation of the MCTQ questionnaire (Munich ChronoType Questionnaire; Roenneberg, Wirz-Justice & Merrow, 2003), to identify the sleeping patterns of the participants (see Appendix D), and a questionnaire about their social media use (see Appendix E) which was used to maintain the ruse that the study was interested in the participants’ social media use. This study received ethical approval from Lancaster University on 05/04/2018. Design Variables. The dependent variable in this study was pupil size, which was measured in arbitrary units, using an eye tribe eye tracker. An average pupil diameter was calculated for each trial; each participant had 40 average pupil size measurements in the visual task and 40 average pupil diameter measurements in the audio task. The dependent variables of median and area under the curve were used. The independent variables in the study were; feedback valence, sleep debt, gender voice and gender. Feedback valence. The feedback was within subjects, as all forty-four participants experienced both positive and negative feedback in both tasks. In the visual task, all participants saw twenty people who had supposedly ‘liked’ their photo, and twenty people who had supposedly ‘disliked’ their photo. In the auditory task, all participants heard twenty positive comments and twenty negative comments. This was analysed to assess whether varying pupillary responses were elicited towards positive and negative social feedback. Sleep debt. Sleep debt was determined by the MCTQ (Roenneberg et al., 2003); a value of sleep debt was calculated by subtracting sleep duration during the week from sleep duration at the weekend, plus weekday bedtime. Participants were split into two groups; high sleep debt and low sleep debt. Those with a high sleep debt had less weekday sleep and greater weekend sleep, which is a marker of poor sleep quality. This was a between subject factor, as half of the participants were in the high sleep debt group, and half in the low sleep debt group. Voice Gender. In the audio task, half of the audio clips featured a male voice, and half featured a female voice, therefore this was a between subject factor. This was analysed to investigate whether the gender of the voice or pictured individual had an effect on the pupillary responses. Gender. In the visual task, the gender of the participants was investigated as a between subjects factor, as nine of the participants were male, and thirty-five were female. Audio task. The design of the audio task was a factorial design with a between subjects factor of sleep debt (which had two levels – low and high) and a within subjects factor of social feedback valence (two levels: positive and negative) and a second within subjects factor of voice gender (two levels: male and female). Visual task. The design of the visual task was a factorial design with a between subjects factor of sleep debt (which had two levels – low and high) and within subjects factors of social feedback valence (two levels: positive and negative) and participant gender (two levels: male and female). Procedure Approximately two weeks prior to the beginning of data collection, students in Psychology, Sociology and English classes at Haslingden Sixth Form were contacted and given the opportunity to participate in this research. Those who were interested in participating, and would provide consent, were asked to send a picture containing only themselves (eg. a Facebook profile picture) to the researcher via email for use in the study. The participants were informed that the photo they sent would be liked or disliked by students at another school, and that that during the study, there would be an opportunity to like or dislike photos of the individuals who rated their picture. No other information about the other ‘students’ was provided. The participants were led to believe that the study was investigating whether social media use affects responses to being judged online, and whether the use of social media affects sleep patterns in adolescence. All participants were tested in the same office in Haslingden High School and Sixth Form. Participants were invited into the office and invited to sit down a desk which featured an eye-tribe eye tracker, 24-inch iMac monitor and keyboard, and a chin rest was placed 50 cm away from the eye tracker. The computer had MatLab 2015 installed. Each participant was provided with an information sheet (see Appendix F), and was given the opportunity to ask any questions, before signing an informed consent form (see Appendix G) if they still wished to participate and consented to partake in the study. Once the consent form had been signed, the photo rating task was explained. This task involved presenting forty photos to the participants using Microsoft PowerPoint. The photos were shown individually; each photo was on an individual slide, and each one was presented for four seconds. The participants were asked to mark whether they ‘liked’ or ‘disliked’ each photo on a sheet of paper (see Appendix A). The presentation was on an automatic timer however, the participants were informed that if a slide moved on too quickly, the left arrow key would take them back to the previous slide, and the timed presentation would continue by pressing the right arrow key. The participants were led to believe that the photographs they were rating were of the individuals who had rated their photos. The eye tracker was not used during this task. Next, the participants were asked to place their head on the chin rest, and the eye tracker was calibrated. Participants were asked to keep their heads as still as possible, and to move their eyes towards the dots as they appeared on the screen. The calibration was accepted when three stars or above was achieved, and the eye tracker was used for both the visual and auditory tasks. The order in which the tasks were completed was counterbalanced, therefore half of the participants completed the visual task first, and half completed the auditory task first. The participants were informed what would happen during each task and were given the opportunity to ask any questions before the tasks began. The participants were told that, in the auditory task, they would hear forty voice clips; twenty nasty and twenty nice. They were asked to look at a black cross that was located in the centre of the screen whilst the voice clips were playing. Ten of the ‘nice’ clips and ten of the ‘nasty’ clips were read aloud by a female, and the remaining were read by a male voice. The nice and nasty comments which featured in the voice clips were found on online social media platforms (see Appendix B for the full list of comments used), however the participants were asked to imagine that the comments had been directed towards themselves. Participants were told that, in the visual task, they would view the photographs which they had previously ‘liked’ or ‘disliked’ in the photo rating task. However, this time, the photos would either have a ‘like’ thumb or a ‘dislike’ thumb in the bottom right hand corner (see Figure 2 and Figure 3 for examples). If a photo had a ‘like’ thumb, it meant that person had supposedly liked the participant’s photo, whereas a ‘dislike’ thumb meant the individual in the photo had disliked the participant’s photo. Half of the participants completed the visual task first, and half of the participants completed the audio task first; the tasks were counterbalanced to determine whether the order in which they were presented influenced the outcome. After finishing both the visual and auditory tasks, participants were asked to complete two questionnaires; the MCTQ (Roenneberg et al., 2003) to determine a sleep debt score and a questionnaire on social media use. After completing the questionnaires, participants were informed that their photo had not actually been seen or rated by pupils at another school, and that the ratings which they gave in the photo rating task wouldn’t be seen by the individuals in the photos. Participants were then provided with a debrief sheet (see Appendix H) and given the opportunity to ask any questions they may have had. Analysis Preliminary data analysis. In order to measure the magnitude of change in pupil dilation and compare across the conditions, each trial pupil size was baseline adjusted by subtraction of the mean pupil size in the 300ms prior to stimulus onset from each sampled value during the further 4 seconds of stimuli presentation. The area under the curve and median were then calculated from the trial level baseline adjusted data to provide the dependent variables in the analysis. These were used as dependent variables to show the magnitude and duration of the effects. The median was used as opposed to the mean because the median is less likely to be skewed by outliers. Two multilevel mixed effects general linear mixed models (GLMM) were used to analyse the data for the two tasks with participant included as a random effect with intercept. An AR(1) heterogeneous first order autoregressive structure with homogenous variances was selected because it was expected that the error variance would become less correlated as the trials became further apart. The total number of likes each participant gave on the photo rating task was calculated and a 2 (gender: male vs. female) x 2 (sleep debt: low vs. high) between factor analysis of variance (ANOVA) was carried out.
Guilt appeals are commonly used in charity advertising as a means of persuading a consumer to donate. This qualitative study uses an Indian sample to understand if there exists any differences in how they are perceived by individuals in a society that is not guilt based. Participants were exposed to 5 advertising campaigns in a focus group interview. The research also seeks to understand other factors that persuade a consumer to donate. It was found that guilt was only a supplementary factor in persuasion and factors of personal relevance and focus of action played a larger role in persuading with the sample used in this research. Guilt was effective in changing the attitude and beliefs of a consumer, but it was the factors of personal relevance and ease and convenience that were influential in changing donation intention into charitable behaviour. However, the small sample is also a limitation in generalising the responses to an entire culture.
The purpose of this research was to understand the effectiveness of charity advertisements using guilt appeals in an Indian sample. Content analysis was then used to find patterns and themes in the responses of the participants. Research Design Focus Group Interviews Since the research aimed to create a narrative of the participants opinions and views, focus groups were employed. Focus groups also enable for understanding and exploring a topic in depth and understanding the nuances of the thoughts and opinions of the participants and thus understand how they respond to guilt appeals. Interviewer The primary researcher was used as the interviewer on the basis of being well versed with the material and thus the quality of establishing rapport and guiding the focus group discussion. Discussion Guide The primary aim of this research was to understand the perception of guilt appeals in charity adverts and the factors used in the adverts that contribute to donation intention. A discussion guide was formulated in line with the aim of the research and to provide a structure to the direction of the interview. Some of the questions included: ‘How do you feel when you look at this advertisement’, ‘The advertisements intend to use guilt. Do you think that was effective’ and ‘Did you feel guilty when you were exposed to the advertisements?’ (See Appendix A). However the questions were not asked in order and were chosen based on the responses chosen by the participants. Participants A focus group with 7 participants was organised. All the participants were Indian by nationality and graduate students of Lancaster University. Of the 7 participants. There were 5 males and 2 females. The only criteria for choosing the sample was that they had to have lived in India for at least 10 years or identify as an Indian national The age of the participants ranged from 20 to 25 years old. There was no difference by gender and gender was not considered as a variable in this research. Materials Five advertisements were used in this research to understand guilt appeals. The advertisements chosen for this study were for causes ranging from child labour, poverty and housing for the poor. To bring some diversity into the advertisements, both online and billboard poster advertisements were used. The people in the advertisements also belonged to different race and age groups to understand if these factors played a role in the effectiveness of the advertisements to both groups. The last advertisement (Shelter) also alluded to shame and I was interested in understanding how this added variable would influence the participants evaluation. The advertisements were chosen from the internet and have been used as part of ad campaigns. The basis for choosing the advertisements was the framework used by Huhmann and Brotherton (1997): • The presence of comparison between the well-being of the consumer and the other • Placement of responsibility in the consumer • A call to action to the consumer which will aid the cause, failing which the affected group’s misfortune will prolong • Existence of violation of personal moral standards of the consumer The five advertisements below were used in the research can be found in Appendix A, B, C, D and E. Procedure Participants were recruited for the interviews through messages on Social Networking Sites such as Facebook and WhatsApp. A remuneration of 7 pounds was promised for participation and the interview was conducted in the library of Lancaster University. Participants then signed consent forms and were shown the adverts. The advertisements were shown consecutively, with participants providing their opinion on each advertisement before proceeding to the next. Questions were then asked regarding the advertisements and discussed. Finally, participants were debriefed about the nature of the research and paid. Ethical Standards The research conformed to the Market Research Society’s guidelines. Participation was voluntary and participants were asked to sign consent forms prior the interview. Participants were made aware that their voice would be recorded prior to the start of the interviews. However, for the purpose of anonymity, their names were not used in the study. The participants were also provided with the choice to opt out of the interviews at any given point should they wish to. Results Section: This research sought to understand the effectiveness of guilt appeal adverts in Indians and to understand their perceptions of the advertisements and campaigns. The factors in guilt appeals that contribute to a successful advert was also studied. The following results section has been organised in order of the five adverts shown in the interviews to participants and the responses are accounted. Some common themes found in the responses are also discussed following the responses. Responses to the first advert by People in Need (Appendix A) ranged from a participant feeling that the advert was a “sarcastic attempt” and trying to “make a parody of the poor living situation” of the model and his surroundings to claiming that “They are trying to sell the aftershave” “They are trying to show that the product is efficient and works well”. A participant also said that the advert was trying to “enter larger markets” and thus make the product more approachable. Most participants except two misinterpreted the advert into viewing it as an advert for the aftershave and not as a charity advertisement. Even after explanation for the advert was provided, the participants maintained that they felt no sense of guilt. Only one participant understood the mechanism of the guilt appeal used in the advertisement, identifying the underlying message of disparity the advertisement was trying to highlight, saying that the advert showed that “You are spending so much on yourself, (but) with a very little amount, you can help improve the lives of others and make an impact for those people” and said that the advert was simply asking the consumer to care about others. Participants also mentioned that the sparse and bare background “shows poverty and amplifies the situation of the person”. However, the themes the participants identified related to the efficiency of the product as the opinion was that the product worked well because it could be used by different people and the brand’s intention to show people across different nationalities and income levels. Participants were also provided the background of the campaign and a participant then said that she felt a deeper sense of guilt with this knowledge as she was not using her purchasing power to help others and instead for her own self. The impact of the advert on the participants was also varied with one claiming it had no impact and having a great impact on another. When presented with the second advert by Unicef against child labour (Appendix B), participants pointed out that the advert targeted Nike, saying that “It mocks Nike by making a direct comparison” and also that “Use of Nike makes it easy to understand to target the industry as a whole”. A participant also claimed that the obvious dig at Nike left him unable to focus on the intention of the advert that many brands are contributing to child labour because “All I am seeing is Nike and child labour”. Participants who had knowledge about the background about the advert said that they were able to understand the advert better since they could understand why the advert used Nike. The boy in the picture seemed to evoke some emotion, as participants said that the advertisement was basically the fight by “A small boy against a big corporation” and that he is “Helpless and poor” because he cannot fight the situation. They also maintained that the advert sends the message of “restriction and no freedom” as well as “children forced to do it” and children who need money being misused”. The participants also claimed that while they did feel bad for the child, their attention is drawn more towards Nike than cause of child labour. The participants also felt that the campaign should use more brands as the advertisement sends the message of targeting only Nike and not the overall problem with a participant even saying that “Maybe it would have been better not to mention Nike at all” With regard to the third advert by Feed SA (Appendix C), participants felt that the “language is strong”, “message is crisp and clear” and that it was “powerful because it shows an African child”. Conversation centred around the race of the child with participants saying that the advertisement would not have been as effective had the child not been Black and that “I would not have taken the advert seriously if it was an Asian kid”. The participants also said that had the advert emphasised on the race of the child and not the cause, they would have felt offended. Participants however said that they would donate if they saw this advert because the ad, which was stuck on shopping trolleys explicitly shows he process thereby making the job easier for the consumers. The participants said that the advert is effective in “making people aware of the ease of helping people” as it targets the ease of donation. The advert was seen as “direct, easy, fast, convenient”. On showing the fourth advert by Shelter (Appendix D), participants said that they would most likely not pause to read the entire advert due to it being word heavy. “That’s a big ad” said a participant, continuing that the advert “could have funnelled it down”. However, other participants disagreed saying that one could just read the highlighted text and understand the ad and that it does not demand too much attention. Some participants claimed that despite the size of the advertisement, the process of helping the cause was unclear and ambiguous. Others said that the advert would be effective should they want to donate because the problem is clearly highlighted, and the crux is conveyed with details of what they can do to help and the opinions on the effectiveness of the advert seemed divided. There appeared to be consensus with regard to the child in the picture as participants said that “emotion is instant when you see the girl” and the child would make them pause and read the advert. For the last advert by Amnesty (Appendix E), participants said that the advert makes a strong and powerful statement, immediately catching one’s eyes but felt directionless. A participant said that the advert “hits the emotions but I do not know what to do about it”. Another participant commented that their eyes were immediately drawn towards the word “deserve”. The advert, while impactful, was stated to be vague because it does not inform the viewer what they might be able to do except go on a website, which the participants said was forgettable. A participant said that “Other ads are more about the action; this ad asks for interest and energy” and that one would not bother to do so unless they had time or was personally invested in the cause. Discussion of race again came to the forefront as participants said that the advert resonated more with them given the ethnic unambiguity of the child in that the child could have belonged to an Indian or even Latino background just as easily as American and that “crying face, torn clothes, messy hair make an impact to which race is second”. Not clearly defining the child’s ethnicity was seen as a clever marketing strategy but participants said that they had difficulty relating to a cause from a developed nation. A participant also said that “I would rather pick an Indian child and help that child” in response to helping a cause in America. Participants were then told that all the adverts worked by using guilt appeals and were asked if they did feel guilty when they viewed the adverts. Some participants identified the Shelter and Amnesty advertisements to evoke emotion in them, whereas others maintained that while they did feel bad and also sad when they viewed the adverts, they could not identify their emotions specifically to say that it was guilt and a couple also admitted that the adverts did not evoke much feelings of guilt. “Unless I feel strongly about a cause, I would not donate to the cause regardless of how much the ad tries to guilt me or how powerful an ad is” maintained a participant who said that he would donate to the advert for poverty not only because the advert caught his attention, but also because he was more sensitive towards poverty, having grown up in a poor household. Another participant was of the opinion that he was more likely to donate to causes with adverts with a call for action. Participants also viewed adverts as a “reminder” or “trigger” to take action and that they were most likely to participate in a cause that is the easiest or most convenient to them. A different view was provided by another participant who said that unless he was personally invested to a cause, he would not feel guilt towards an advert for other causes due to the neutral perspective he maintained. Thus, there would be no response in any form towards the advert. A participant was also of the view that she would rather help other developing nations than a developed nation. She maintained that because she had seen so much poverty on the streets of India and that because of frequent donations to beggars, the child poverty advert did not evoke any guilt. Another participant revealed that his support only for causes that provided individuals with skills, regardless of the guilt the advert evoked, saying that “I will participate if I think the ad could solve the problem.” The participants were also asked if pictures or words had a greater impact on them and while the consensus was that pictures evoked more emotion, having only pictures could be detrimental and lead to not understanding the purpose of the advert and the greater risk of misinterpretation. Participants were finally asked if them being Indian or their culture had an effect on how they viewed the adverts. Growing up in a country with lots of poverty seemed to have had a great impact on the participants who said that they were more likely to help children in poverty. Religion also played a role for a participant who practised Islam who was of the opinion that he would have donated to any of the causes in the adverts had he seen them in the month of Ramzan. There were several themes that were identified through the analysis of the responses from the interviews. Firstly, while the adverts did elicit negative emotions in participants that persuaded donation intention and to undertake advocated behaviour, that emotion was not immediately identified as guilt by the participants. The general responses to the adverts were that they made one feel “bad” or that they were “hard hitting” and “powerful”. Verbal enunciation of guilty feelings was difficult and indirect. Additionally, while some advertisements did elicit feelings of guilt, the factors that persuaded an individual to support were different from those discussed below. “Unless I feel strongly about a cause, I would not donate to the cause regardless of how much the ad tries to guilt me or how powerful an ad is” An important factor that persuaded charitable behaviour was the personal relevance of the cause for the individual. Personal relevance is largely influenced by life experiences of an individual. Prior knowledge and circumstances had a significant impact on the perception of adverts. The Unicef campaign appealing against child poverty through Nike had a greater impact on individuals who were aware of the case against Nike in reinforcing their perception of the brand than it did on those who were unaware. In such cases where a brand is targeted, the inclusion of facts and background might have resulted in an increase of interest. Individuals who did not have an opinion on a particular cause or had a neutral perspective did experience negative emotions upon exposure to an advertisement, however, the strength of the emotions were not enough for them to consider acting on them. Religion also seemed to play a role in charity behaviour. Religions practises such as ‘zakat’ in Islam which requires one to donate a small share of their wealth to the poor and needy with the belief that such donation frees one from excessive greed and desires influenced those who practised the religion to donate during the time of Ramzan. “An advertisement to me is only a reminder” The role of an advertisement was seen as a trigger or a reminder of the cause an individual supports and did not create a new belief or attitude towards a cause. Rather, they seemed to reinforce prevailing ideas and strengthened them. For instance, a participant felt more strongly about the Unicef child labour advertisement because he was informed about the cause and aware of the controversy Nike found itself embroiled it. The advert remined the participant about the cause and his interest in the advert was more a product of personal research than because of the guilt appeal used. However, advertisements time and again seem to be very persuasive in shaping attitudes as well as changing behaviour and it is to be further researched if the opinions in this research are because of the advertisements used or due to individual differences in beliefs of participants. “I would rather support an African child than an American child” The willingness to help a cause also depended on the country the cause was addressed towards. There was a greater hesitancy and reluctance in supporting a cause from a “developed” country such America in comparison to developing countries or countries that had the same or lower level of economic growth as India. However, this seemed to be a key factor only when the country the advertisement originated from was explicitly stated. The Shelter advert was an advertising campaign from the United Kingdom, however, it was very persuasive and one of the most effective advertisements according to the participants. The advertisement made no mention of any location. There is a strong commitment in Indians to help extended family and friends or members of the same community, owing to the collectivistic nature of the society (Cantegreil, Chanana, & Kattumuri, 2013) and this is reflected in the responses from participants. This is an important factor to account for with an Indian population, where consumers might be reluctant to support causes from another state of India that is not their own.
Exploring the Effectiveness of Metaphors in Video Advertising - the Interaction Effect of Different Cultural Groups and Different Metaphors
Metaphors are often used in contemporary advertising, and previous research has confirmed that advertisements with metaphors are more effective than literal ones. At the same time, research into the role of metaphors has become more comprehensive, moving from traditional metaphor theories based solely on literal language to the study of the interactive effects of different modalities of metaphor (multimodal metaphor). The aim of this study was to understand the differences in the responses of different cultural groups when exposed to advertisements containing different types of metaphors (needs-highlighting metaphor vs. feature-highlighting metaphor). Based on this expectation, a 2 (cultures: British, Chinese) x 3 (advertisement types: feature-highlighting metaphors, needs-highlighting metaphors, and literal advertisements) designed experiment was conducted to test.
Design To obtain statistics on the extent to which creative metaphor in video advertising contribute to the effectiveness of advertisement, a quantitative research method was used in this study. To test if there was an interaction effect between cultural group and metaphor types, this experiment had a 3×2 mixed design, with a within-subjects factor of advertisement type (feature-highlighting metaphors, needs-highlighting metaphors, and literal advertisements), and a between-subjects factor of participants’ culture (British and Chinese). The dependent variables were attitude toward the product/advert and purchase intentions. Participants Fifty-three participants were recruited through convenience sampling and participated in the study by completing an online survey. The responses obtained from participants who either did not complete the consent form or did not answer all the questions were excluded from the analyses. This led to a total of 40 responses retained: 20 from Westerners, 10 men and 10 women; 20 from Chinese participants, 9 men and 11 women. Table 1 provides an overview of the participants’ information in this experiment. Most of the participants are currently studying at Lancaster University, some of the Chinese participants are currently living in China. As the aim of the experiment was to look at cultural differences, therefore, no specific age restrictions were set. Materials In the current experiment, the selection of stimulus classification conditions was based on the setting of Pan's study in 2020. However, in order to investigate the pattern and consistency of people's responses under different conditions, the number of stimuli under each condition classification was larger in this experiment. The stimuli consist of 9 video ads in total: 3 ads each for the literal, feature-highlighting metaphor, and needs-highlighting metaphor conditions. All ads featured tangible products: perfume, body wash and deodorant, with 3 ads per product covering all 3 conditions. The experimental manipulation was based on the metaphorical dimension of the advertisements. Table 2 provides an overview of advertisement conditions and the links to view them. The metaphor condition contained at least one metaphor in the stimuli, while the literal advertisement was used as a control condition. The length of the selected advertisements was controlled to be less than 120 seconds (about 2 minutes). Advertisements that have been created in recent years were chosen, between 2012 and 2021. Phau and Prendergast' study (2000) found that consumers associated the image of a brand with the image of its country of origin. In order to minimise the influence of consumers' previous perceptions of brand image, the advertisements chosen for this experiment were made for well-known brands, whose countries of origin were all developed countries, such as the USA, the UK and Japan. Advertisements created from different countries were chosen; therefore, the language of the original advertisements were Chinese, English and Japanese. All advertisements were translated into Chinese and English with subtitles, which were checked by native Chinese speakers with undergraduate degrees in Japanese translation and English translation. As the video exceeds the size of the attachments that could be added to the Qualtrics questionnaire, the video advertisements with bilingual subtitles were uploaded to OneDrive and the link was added to the questionnaire for participants to view. All selected video advertisements were sourced from internet platforms. To measure attitudes toward the ad and purchase intentions, questions were formulated based on questions previously used in marketing research (Jeong, 2008; Kim, Baek & Choi, 2012; Pan, 2020). Attitudes towards advertisement. Participants were asked to rate/evaluate the ad on 4 scales, i.e., to what extent they agreed that the ad is ‘good’, ‘favourable’, ‘pleasant’, and ‘appealing’; the scales ranged from 1 (Strongly disagree) to 7 (Strongly agree) (Jeong, 2008). Purchase intentions. Participants were asked to rate the value of the item being promoted, the probability of purchasing the promoted product, and the probability of recommending the products to their family or friends (Maheswaran & Meyers-Levy, 1990). The original questions above were in English and were translated into Chinese for Chinese participants who took part in this study. The translations were checked for equivalence of meaning by a native Chinese translator researcher in English. Variables and measures in this study are provided in Table 3. Procedure All ethical guidelines related to data collection, and informed consent were reviewed and approved by the Faculty of Science and Technology Research Ethics Committee at Lancaster University. The data collected were anonymised upon extraction from Qualtrics. no participant information beyond the critical data is included. All participants were asked to complete an online questionnaire. They could access the survey either via a QR code or via the shared link from Qualtrics. The questionnaire was set up on Qualtrics in English and Chinese versions. The first section included a participant information sheet and the consent form, followed by the experimental section. In this section, each video advertisement and the corresponding questions were grouped into a separate question block, each with a link to a specific advertisement for participants to view. This was to make sure participants focus on watching and evaluating one advertisement at a time. To move to the next block, participants had to complete the question evaluating the current video and press a button to access the next question block. Participants rated the properties of each advertisement immediately following exposure to it. The order of ads presented was fully randomised and differed for each participant. To prevent participants' overall liking of the advertised brand, product or brand spokesperson from influencing their assessment of each attribute of the advertisement and obtain valid data, participants were reminded in each question block of the cautions for rating the advertisement itself with a sentence, "If you have any knowledge of the brands or products, please try to rate the following ads, by excluding your liking of them (including the celebrity spokesperson) and your current purchasing needs. " At last, participants clicked the submit button, and were debriefed and thanked for their participation. The study took approximately 40 minutes and participants were paid £6.50 for their time. Statistical analysis The data was examined and analysed using SPSS software. A two-way mixed ANOVA (analysis of variance) was used to examine the two independent variables, i.e., advertisement condition, within-participants, with 3 levels (needs-highlighting metaphor, feature-highlighting metaphor, literal) and culture, between-participants, with 2 groups (Chinese, British), and their effects on two dependent variables, i.e., attitude towards the advertisement, and purchase intentions.
Exploring the impact of rewards on contextual cueing effect
contextual cueing effect, reward, selective attention
There is a huge amount of complex information about visual stimuli in the environment and the individual's visual processing system has a limited capacity to process this information, so selective attentional mechanisms prioritise the most valuable information. Fixed contextual cues in the environment help us to allocate attentional resources efficiently. In their study of context, Chun and Jiang proposed a contextual cueing effect (CC effect). This effect is likely to be an implicit learning resulting from selective attention. Specifically, subjects searched for the target faster in the repeated configuration than in the random configuration, as fixed contextual cues would help locate the target. It was found that this effect could be moderated by manipulating external motivation, i.e., reward. However, there is so far considerable debate as to whether high rewards can contribute to the cc effect, and whether rewards act on the cc effect or on the positional probability learning effect. The present experiment used a classical situational cueing task and a mixed between-*within group experimental design to explore the effect of reward on the contextual cueing effect. The experimental results show that high rewards did not contribute more significantly to the cc effect than low rewards, but high rewards did facilitate the target probability learning effect.
Participants Fifty-two Lancaster University students (20 identified as male and 32 as female; age M=23.9, SD=2.55 years, range: 19-33 years) participated in the experiment. Two participants were excluded from the final analysis (see below for details). All participants had normal or corrected normal vision. Participants were informed that the three participants with the highest scores in the experiment would receive a £20 Amazon voucher as a reward. At the end of the experiment, the three participants with the highest scores had received their £20 Amazon vouchers by e-mail. The experiment passed ethical review by the Department of Psychology at Lancaster University. All participants were shown a participant information sheet and signed a consent form to participate in this study prior to the start of the experiment. The Participant Debrief Sheet was presented to participants at the end of the experiment. Materials The materials were created and presented with the Psychophysics Toolbox Version 3 (Brainard, 1997) MATLAB (MathWorks, Sherborn, MA) toolbox. The stimuli were displayed on an MS-Windows machine on a screen with 1920 × 1080 pixels resolution and 60 Hz refreshing rate. Each display consists of 11 L-shaped and one T-shaped black 1.25° x 1.25° items, presented on a white background. The only T-shaped item in each display is the target, which has a 90° rotation clockwise (called left) or counterclockwise (called right). There were an equal number of times that the target was rotated to the left as it was rotated to the right across the experiment. The L-shaped distractors were randomly rotated by 0°, 90°, 180° or 270°. To increase the difficulty of the task (Jiang & Chun, 2001), the L-shaped items had a 4-pixel offset at the junction of the lines to make them similar to the T-shaped targets. In each display, all items were balanced within the quadrant of the display. This randomisation was carried out for each subject individually. Experiment design This experiment was conducted in a quiet testing room, with each subject alone in the room to complete the experiment. The experiment consisted of 20 training blocks. Each block consisted of 16 trials. Each trial began with a 0.5 second fixation cross, followed by a search display until the subject's manual response or reached the maximum response time limit of 6 seconds. Participants were asked to respond as quickly and accurately as possible, reporting the direction of the target by pressing C or N on the standard keyboard numeric keypad, respectively ("T" stems pointing left or right). Each of the 5 training blocks was divided into one epoch, for a total of four epoch, with subjects having a fixed 30 second rest period between epochs. The whole experiment will last about 40 minutes. Participants will be given a score (points) after each test based on their reaction time (correct response within 2 seconds), i. e. the 'reward' for the experiment. Each subject is informed before the experiment that they will have a final score at the end of the experiment and that the top three participants with the highest scores will receive a £20 voucher. The experiment will use two reward conditions, a high (score*10) and a low (score*1) reward. In the high reward condition, the correct answer will be scored as (2000 - reaction time) *10. In the low reward condition, the correct answer will be scored as (2000 - reaction time) *1. For each subject, eight positions in the imaginary ring were randomly selected as target positions. Each quadrant had an equal number of target positions. In each block, each target location was presented once in a repeated display and once in a new display in the same reward condition (twice in total). In the repeated display, the position and orientation of the distractor remained constant along with the target position, while in the new display both were changed randomly. In both the new and repeated displays, the target orientation was changed randomly so that no link could be made between the repeated configurations, target locations or reward values and specific responses. The eight target positions were divided into two different categories: (1) four target positions were always combined with a high reward (score*10) in both repeated and new displays; (2) the other four target positions were always combined with a low reward (score*1) in both repeated and new displays. Therefore, the configurations in the repeated trials were also only ever paired with high or low rewards. A mixed experiment design was used in this study, with the within-subjects factor being the feedback received after the subjects' responses. During the feedback phase of each trial, the score obtained for this experiment is displayed on the screen if the correct response is received within a time window of 2 seconds from the start of the display. The screen will also display whether this trial is a "10x bonus" one or a "normal trial". For trials with a correct response time of more than 2 seconds, no score is awarded, and the feedback is "too slow, 0 points" displayed in the centre of the screen. For trials with a reaction time of more than 6 seconds, 10,000 points will be deducted, and the feedback will be "Time out! Too slow, -10,000 points". For incorrect responses, 10,000 points will be deducted, and the feedback will be "Error! -10,000 points". The total number of points accumulated so far will be displayed below the feedback 1 second after feedback is presented. This experiment also had a between-subjects design in which subjects were randomly divided into two groups, with the odd-numbered participants being the “instructed group”, and those in the instructed group will see a prompt in the centre of the screen before the start of each trial, informing them that the trial is a high or low reward condition. For the high reward condition, "10x BONUS trial!" will be displayed in the centre of the screen in green. For the low reward condition, "Normal trial" will be displayed in the centre of the screen in white. Participants in the even numbered group are in the "not instructed group". Subjects in the “not-instructed group” will not see a prompt in the centre of the screen before the start of each trial and will only see if they have received 10x the reward for their score during the feedback phase.
Exporing the Effect of Visual Complexity on Recall
#visualcomplexity #recall #free-recall #cued-recall #advertisements #simple #complex
This study was conducted to explore the effect of visual complexity on an individuals` recall of product brands and their attributes in either simple or complex adverts . Within the field of visual complexity, there has been contradiction as to whether complexity helps or hinders recall, this study aims to resolve this question. A survey was conducted to measure their free and cued recall for adverts that varied in their visual complexity. The complex advertisements were defined as having three objects included whilst the simple advertisements had only one object included. This was decided to align with the industry standard for defining visual complexity as set by Attneave (1954), Snodgrass & Vanderwart (1980) and Chikhman et al., (2012). A percentage scoring system was used to compare overall memory performance. The data showed that those in the simple condition performed better compared to those in the complex condition. However, this was not the case for every individual. The results found the effects of complexity to be marginally significant (p < 0.09); however, the study had limited power, and a replication with a larger population could provide a more complete picture of the influence of the independent variable. Whilst this study does not provide a definitive conclusion towards the effect of visual complexity, it does explore and provide an insight into the effects of complexity on recall of product attributes in advertisements.
PARTICIPANTS The larger the number of participants in a study, the better-protected results will be from extraneous variables. For this reason, the participants were collected through random snowball sampling (Emerson, 2015). Each condition had 22 participants, a minimum age of 16 being the only participation condition. The participants were randomly allocated to each one of the four experimental conditions, providing 88 total participants (N= 88). There were no gender requirements for participation (Females (N = 47), Males (N = 31), Other (N = 4)). The majority of participants were born in the U.K. (N = 46) or Poland (N = 35). The majority are currently residing in England (N = 57) or Poland (N = 21), but responses were still collected from further afield, such as France and the U.S.A. (N = 10). The majority of participants fell into the two youngest age categories, 16 to 18-year-olds (N = 22) and 22 to 27-year-olds (N = 37). General demographic information provided insight into the advertisement exposure in participants' generic routines. The majority of participants were native English speakers (N = 49). The majority of participants use streaming services (N = 76), of which just under half of the respondents said their service had adverts (N = 38). Participants also use ad blockers (N = 49). Just over a quarter of participants use cable T.V. (N = 27). When asked whether they pay for premium applications, the majority said ‘never’ (N = 60), occasionally (N = 16), sometimes (N = 9), usually (N = 2), whilst only one participant always pays for premium applications (N = 1). MATERIALS Firstly, two product categories were chosen, bottled water and soap bars, four brands were then selected per category (see table 1). There were 16 advertisements in total, eight for the simple and complex conditions, respectively. (APPENDIX A) The editing software Gimp was used to design the advertisements to enable the selected products to be presented in the controlled advert setting. This 'controlled setting' ensured that the backgrounds were consistent across the adverts, e.g., they all used the same blue background. Additionally, no text or fonts were added, and the objects included had the same position as their counterparts. There were two experimental groups wherein participants were presented the advertisements. Within those two groups participants would view one of the product categories e.g., the water products. To account for confounding variables advertisements were counterbalanced, randomizing their order of appearance. Participants only saw one product category (e.g., soap or water) and one variation of the advert e.g., if they saw the simple A1 Aveeno advert, they were not be presented with the complex B1 Aveeno advert. If participants saw the complex B5 Buxton advert, they were not presented with the simple B1 Buxton version. If participants saw the soap adverts, they did not see the water and vice versa. The web-based software Qualtrics was used to create the surveys (APPENDIX B) and a generalized report of the results. After extracting the data, SPSS was used to dummy code and manipulate the data to measure the effect of visual complexity on recall. DESIGN This experiment used a between-group design wherein participants were allocated either the simple or complex condition to examine which level of complexity had the larger effect (Turkeltaub et al., 2011). The type of complexity, simple or complex, is the independent variable of the experiment. The dependent variable is the effect this has on participants' recall (Atinc et al., 2011). In this project, simple advertisements are defined by having only one object included in the background, whereas complex advertisements are defined by having three objects. Participants were first asked questions pertaining to free recall of product attributes before then being presented with the cued recall questions. This was to allow a distinction between non prompted (free) and prompted (cued) responses, enabling me to mark each survey and allocate a combined percentage recall score to each participant. To control for confounding variables, the surveys were counterbalanced. Participants were shown the adverts randomly within each experimental group so that I could isolate the sequence effects that participants are exposed to. However, I could not control for extraneous variables such as the time of day participants completed the survey, their emotional state, or their level of intelligence. Additionally, situational factors such as the location they were in, e.g., whether the room they were in was too loud, too hot, too cold, could not be accounted for. To prevent participants from rehearsing the material, distraction tasks were provided before requesting question responses (APPENDIX C). These were designed to be cognitively engaging by requiring participants to read sections of text and 'fill in' the missing words and select the 'odd word out' in a listing task. When completing these tasks, participants would not necessarily be aware that they were not an essential part of the study and thus, in processing their responses, would have to pause. For example, 'which word does not belong with the others?' had the response options of ‘Dog’, ‘Cat’, ‘Donkey’, and ‘Dragon’. There are actually two responses that could be deemed correct; however, participants are told to select one. The correct responses were ‘Cat’ as it is the only word beginning with the letter 'C' and ‘Dragon’ as it is the only creature with wings. Participants could not advance to the next section if there were any responses left blank. All of the advertisements had the same consistent blue background, no fonts were used, and all objects had the same positioning between the simple and complex conditions. For example, A2 and B2 Dove both had the blue ribbon object included in the same position. All simple advertisements had one object; all complex advertisements had three objects to allow a comparison of the effect of complexity on consumers' explicit recall. PROCEDURE Participants were found and randomly allocated to one of the experimental groups. They were first presented with the participant information sheet (APPENDIX D) in which general information about the experiment was explained without revealing that it was the level of complexity being measured. Participants were also required to complete the consent form. (APPENDIX E) Thus ensuring the participant is aware that their data will be collected anonymously and that they have the right to withdraw at any time should they please. Participants then viewed four advertisements for 30 seconds per advert. They were not able to advance to the next image until the timer ended . The counterbalancing of questionnaires meant that the adverts were viewed in random orders. The distraction task then engaged participants for a few minutes as they could not advance until the distraction tasks were complete. Participants were then asked the free recall questions in which they are expected to list the brands they can remember and list the product attributes for said brands. The soap category had 26 points available for free recall, and the water category had 15 points available. This is due to more attributes generally being included on the packaging of the soap comparatively to a generic product like water. Ergo, a more comprehensive list of features was able to be asked. Once the participant had submitted the free recall section, they moved onto the cued recall questions. This section provided prompts in the questions, for example, ‘name the products, if any, that were moisturizing?’ participants may not have been able to recall this attribute freely. Therefore, these questions had to be presented separately so as not to influence each other. Furthermore, the free recall had to be asked first for the same reason of not influencing responses. If participants had filled the cued responses first, this would invalidate any free recall questions which may have followed. The soap and water categories respectively had 16 points available for the cued recall questions. Once the survey was completed, participants were shown the debrief sheet (APPENDIX F) in which the aim of the study was fully explained, and they were provided with details should they have any questions about their role and wish to discuss it further.
Extending the Cortical Hyperexcitability Index
Perceptual Aberrations, Cortical Hyperexcitability, Migraine, Aura, Tinnitus, Auditory Perception, Visual Perception, Hallucinations
Anomalous perceptual experiences are associated with underlying excitation of neural activity in the cerebral cortex, known as cortical hyperexcitability (Wilkins, 1995). This can be measured behaviourally by the pattern glare test, where migraineurs consistently show greater susceptibility to anomalous visual percepts in response to grating patterns than control participants (for review see Evans & Stevenson, 2008). Based on these findings, Fong, Takahashi and Braithwaite (2019) developed a screening measure of visual cortical hyperexcitability, the Cortical Hyperexcitability Index (CHi-II), through exploratory factor analysis. This project aims to create auditory-based items for the CHi-II. We know cortical hyperexcitability in the auditory cortex is also associated with a number of auditory symptoms in migraine such as heightened auditory sensitivity and a range of anomalous auditory percepts, ranging from tinnitus-like tones to multiple conversing voices (Vingen, Pareja & Støren et al., 1998; Miller, Grosberg, Crystal & Robbins, 2015). As such we created seven auditory items through adaptation of related questionnaire items and generating unique items based on phenomenology of patient descriptions; these refer to experiences of hearing voices or unexplained sounds under various circumstances, as well as sensitivity to noise. Exploratory Factor Analysis will be conducted on the CHi-II alongside auditory items to test which factor each item best loads onto, as well as using Cronbach's Alpha to assess internal validity. Results are discussed in terms of the debate on global versus localised effects of patterns of hyperexcitability, as well as implications for our understanding of multisensory anomalous perceptual experiences.
Method Participants Forty-five participants age 18-24 (M = 19.24) took part either for research credits or without incentive. Of these, thirty-seven (82%) were female and thirty-seven (82%) were right-handed. Prior to the main questionnaire, a pre-screening survey asked participants to declare any history of neurosurgeries (8.22%), neurological conditions (2.22%), psychological conditions (17.78%), ocular conditions (15.56%), epilepsy (0%), migraine (24.44%), or tinnitus (15.56%). Auditory Item Creation As with the original CHi-II, items were based on previous questionnaires measuring anomalous perceptual experiences (Sierra & Berrios, 2000; Bell, Halligan & Ellis, 2006) alongside patient reports of auditory experiences in migraine (Miller, Grosberg, Crystal & Robbins, 2015; Vreeburg, Leijten, Sommer & Sommer, 2016). These items were split into two categories: voice-hearing, and noise-hearing. We distinguished between hearing a single voice in item one ‘Do you ever hear a single voice talking aloud in your head without a clear source?’, or multiple voices in item two ‘Do you ever hear 2 or more unexplained voices talking with each other?’, as these are delineated in patient reports (Miller et al., 2015; Vreebrug et al., 2016). We also distinguish between hearing instructing voices in item three ‘Do you ever hear voices telling you what to do?’, and hearing voices which comment on thoughts and actions in item four ‘Do you ever hear voices telling you what to do, or commenting on what you are thinking or doing?’, as suggested by the CAPS and CDS (Sierra & Berrios, 2000; Bell et al., 2006). The first noise item asked participants about the occurrence of anomalous sounds in item five ‘Do you ever notice sounds, such as ringing / buzzing , which other people around you cannot hear?’ as recommended by CAPS and CDS (Sierra & Berrios, 2000; Bell et al., 2006). The final noise items referred to volume of sounds in item six ‘Do you ever become annoyed or agitated by sounds that are too loud or uncomfortable for you?’, and distraction caused by sounds in item seven ‘Do you ever become distracted when surrounded by lots of noise?’ as these are common auditory complaints of migraine sufferers (Miller, Grosberg, Crystal & Robbins, 2015; Vreeburg, Leijten, Sommer & Sommer, 2016). As with the original CHi-II, participants respond to items in terms of their frequency on a zero (‘Never’) to six (‘All the time’) Likert scale, and their intensity on a zero (‘Not at all’) to six (‘Extremely intense’) Likert scale. Scores from these two scales are added to create a total score for each item. Informed consent was obtained from all participants. Analysis Total scores were collected from both the original CHi-II questionnaire (Braithwaite, Marchant & Takahashi et al., 2015; Fong, Takahashi & Braithwaite, 2019) and these additional auditory items to complete an EFA. Parallel analysis was also applied to statistically verify the loadings of the new items onto the underlying factor structure (Horn, 1965; Hayton, Allen & Scarpello, 2004). Cronbach’s alpha was used to test the internal consistency of each factor.
Braithwaite, Marchant, Takahashi, Dewe & Watson (2015) Fong, Takahashi & Braithwaite (2019)
Eye tracking and Attention Deficit Hyperactivity Disorder (ADHD): Can eye tracking identify the feigning of ADHD?
Eye-tracking, ADHD, Feigning, Prosaccade task, Anti-saccade task, latency, error rate, eye movements
When diagnosing adult ADHD, it has proven difficult for clinicians to detect deceptive behaviour. Diagnosis of ADHD comes with economic, academic, and recreational benefits, which may account for the increasing feigning of the disorder. Current diagnostic methods: clinical interviews and self-report scales can be easily manipulated for a positive diagnosis. Hence the present study evaluated the utility of eye tracking devices to detect the feigning of ADHD. Eye movements of 38 participants (7 ADHD, 15 healthy controls, and 16 healthy feigners) were captured throughout the prosaccade and anti-saccade task. The performance of the participants on the task was evaluated in terms of latency and the percentage of error rate. The findings of the study reveal a significant difference in the latency of anti-saccade tasks i.e., feigners have an increased latency compared to healthy controls and ADHD participants. Because of the limited sample size, study findings cannot be generalized. Further investigations are needed with a much larger sample.
Method Participants Previous studies explaining feigning in ADHD acquired data from around 90-100 samples (Booksh et.al., 2010; Frazier et.al., 2008; Harrison et.al., 2007). The study therefore aimed to recruit 90 participants, 30 each in ADHD, healthy controls, and healthy feigners faking the disorder. Participants with and without a clinical diagnosis of ADHD were selected using the opportunity sampling method. A total of 42 participants between the age of 18-35 volunteered and were recruited for the study through the university disability service (11%), posters (16%) and through word of mouth (73%). Data of two participants were removed as the eye tracker repeatedly lost the pupil during recording. All participants were rewarded with an equal chance to win one of 6 £25 vouchers. Thirty-one of the 42 participants were healthy younger adult controls. Of the healthy control participants 15 (7 females; Mage = 24.33; SDage=4.32) participated as healthy controls, and the remaining 16 (9 females; Mage = 24.25; SDage=1.88) as healthy feigners. Seven ADHD participants (6 females) with a mean age 22.71 (SD=2.22) completed the study. The severity of the ADHD symptoms was analysed using the Adult ADHD self-report scale (for more demographic details see Table 1). The exclusion criteria include participants: 1) with any visual (other than corrected-to-normal vision) impairment 2) with any cognitive impairment 3) with additional diagnosis of neurological conditions 4) without a proper clinical diagnosis of ADHD. The exclusion criteria were applied because these impairments may interfere with the participants performance in the task. Prior to data analysis, one of the participants was removed from ADHD group due to the lack of proper clinical diagnosis. Furthermore, a control participant was excluded with the assumption of having a probable mild cognitive impairment because the individual scored less than 82 (cut-off) in the Addenbrooke’s Cognitive Examination-III (ACE-III) (see Table 1 for further demographic details). Participants Previous studies explaining feigning in ADHD acquired data from around 90-100 samples (Booksh et.al., 2010; Frazier et.al., 2008; Harrison et.al., 2007). The study therefore aimed to recruit 90 participants, 30 each in ADHD, healthy controls, and healthy feigners faking the disorder. Participants with and without a clinical diagnosis of ADHD were selected using the opportunity sampling method. A total of 42 participants between the age of 18-35 volunteered and were recruited for the study through the university disability service (11%), posters (16%) and through word of mouth (73%). Data of two participants were removed as the eye tracker repeatedly lost the pupil during recording. All participants were rewarded with an equal chance to win one of 6 £25 vouchers. Thirty-one of the 42 participants were healthy younger adult controls. Of the healthy control participants 15 (7 females; Mage = 24.33; SDage=4.32) participated as healthy controls, and the remaining 16 (9 females; Mage = 24.25; SDage=1.88) as healthy feigners. Seven ADHD participants (6 females) with a mean age 22.71 (SD=2.22) completed the study. The severity of the ADHD symptoms was analysed using the Adult ADHD self-report scale (for more demographic details see Table 1). The exclusion criteria include participants: 1) with any visual (other than corrected-to-normal vision) impairment 2) with any cognitive impairment 3) with additional diagnosis of neurological conditions 4) without a proper clinical diagnosis of ADHD. The exclusion criteria were applied because these impairments may interfere with the participants performance in the task. Prior to data analysis, one of the participants was removed from ADHD group due to the lack of proper clinical diagnosis. Furthermore, a control participant was excluded with the assumption of having a probable mild cognitive impairment because the individual scored less than 82 (cut-off) in the Addenbrooke’s Cognitive Examination-III (ACE-III) Stimuli and Apparatus Addenbrooke’s Cognitive Examination-III (ACE-III) The ACE-III, developed by Hodges et.al, is an extended cognitive screening technique. The items of the test produce 5 sub-scores totalling 100, with each sub-score corresponding to a different cognitive domain, such as attention (18 points), memory (26 points), verbal fluency (14 points), language (26 points), and visuospatial skills (16 points) (Noone, 2015). Higher scores indicate superior cognitive functioning within the given domain. The validated cut-off point for normal cognitive functioning is 82/100, therefore individuals who yield a total score of < 82 are assumed to have probable mild cognitive impairment. The ACE-III has proven reliability (α= 0.88), sensitivity (0.93), specificity (1.0) and concurrent validity with alternative cognitive assessments such as the ACE-R (r= 0.99, p < 0.01; Hsieh, 2013). Ishihara Colour blindness test Ishihara colour blindness developed by Dr Shinobu Ishihara, was used to assess the colour vision deficiency of congenital origin, particularly red-green deficiency (Ishihara, 2011). It consists of 24 coloured plates containing a circle of dots with random colours and numbers. Each plate includes primary and secondary colour dots, with the primary colours appearing in patterns or numbers, while secondary colours appear as the background (Shaygannejad et.al., 2012). Plates 1–15 were utilised because of the fact that the main goal was to separate the colour defects from the normal colour appreciation simply. The participants were instructed to read out the numbers aloud, without more than three seconds' delay. A participant with an error in reading the numbers of two or more plates were considered to be having an impaired colour vision. Royal Air Force (RAF) ruler The RAF near point rule is a 50cm long square rule with a cheek rest and slider holding a revolving four-sided cube. One of the 4 sides has a vertical line with a central dot for convergence fixation. It is used for determining the near point of convergence (NPC) (Sharma, 2017). The participant is instructed to keep a direct gaze on the dot while the slider descends and to report when the dot's image breaks into two. The cut-off point for NPC break and NPC recovery is between 5 and 7 cm respectively (Pang et.al., 2010) Adult ADHD Self Report Scale (ASRS-v1.1; Kessler et al., 2005) The severity of ADHD symptoms presented by individuals with ADHD was assessed using the ASRS. The ASRS is an 18-item checklist, developed by the World Health Organization (WHO) work group together with the WHO World Mental Health (WMH) Survey Initiative (Kessler et al., 2005), to screen ADHD in adult patients. Completion of the ASRS requires participants to indicate how much they agree that the given statement relates to their behaviour over the past 6 months. The questions are divided into 2 parts: part A and part B. Part A contains 6 questions that are indicative of symptoms consistent with ADHD and are used for screening purposes. A score of 4 or above denotes symptoms typical with ADHD. The final 12 questions in Part B provide a more detailed breakdown of the specific symptoms an individual is presenting. The scale has high concurrent validity, and the internal consistency of the scale Cronbach’s α was found to be 0.88 (Adler et.al., 2006). Hospital Anxiety and Depression Scale (HADS) Hospital Anxiety and Depression Scale was developed by Zigmond and Snaith in 1983. It is a 14-item measure, used to detect the psychological distress of the participants (Zigmond & Snaith, 1983). Seven of the items measure anxiety (HADS-A), while the remaining seven measures the depressive symptoms (HADS-D). For each item, the participant is asked to indicate on a four-point scale the degree to which they feel a given statement relates to how they were feeling for the past week. The overall score for both anxiety and depression is 21. A score of 0-7 represents “normal”, 8-10 indicates “mild”, 11-14 “moderate and 15-21 indicates “severe” (Pais-Ribeiro et al., 2018). The scale is reliable and valid in measuring symptoms in both general and psychiatric patients (Bjelland et.al., 2002). Eye-Tracking Measurement Participants eye movements were recorded via the EyeLink Desktop 1000 at 500Hz. To minimize the head movements, a chin rest was used. Participants were seated approximately 55cm from the computer monitor (monitor run at 60 Hz). All the stimuli used for the study were created and controlled using Experiment Builder Software Version 1.10.1630. Two different computers are used for the eye-tracking system: a host PC which tracks the eye movements and determines their actual gaze positions and a display computer which shows the stimuli during the calibration and experimental trial. Calibration Prior to presenting the experimental stimuli participants completed a 4-point calibration to ensure the eye tracker was accurately tracking their eyes. During this trial, the participant will be asked to follow a red dot that will move to the four edges of a +. Prosaccade task Participants were asked to complete 16 gap trials as quickly and accurately as possible. At first the participants were instructed to look at a fixation point to centre their gaze. It was a white target displayed at the centre of the screen for 1000ms. Then they were told to focus on the appearing the red lateralised target, presented randomly to the left or right of the screen at 4° (visual angle) for 1200ms. The temporal gap in stimuli presentation is due to a 200ms blank interval screen which was displayed between the fading of the white fixation stimuli and the initial appearance of the red target. Anti-saccade task For anti-saccade task, the participants completed 24 gap trials with 4 practice trials. They were asked to look at the central white fixation presented for 1000ms before shifting their gaze and attentional focus to the opposite side of the screen from where the green target appeared. The green lateralised target was displayed randomly to the left or right side of the screen at 4° (visual angle) for 2000ms. There was a 200ms blank interval screen as a gap in between the fixation point and the target. Procedure The study was approved by the Lancaster University Psychology Department Ethics Committee. Prior to study commencement healthy younger adult volunteers were randomly to either the healthy control or healthy feigner (asked to feign ADHD) group. All individuals with a formal clinical diagnosis of ADHD were assigned to the ADHD group. The participants were required to visit the lab in order to participate. Before commencing the study, the participants provided informed consent. After taking the required demographic data, participants were then screened for the probable presence of mild cognitive impairment using the ACE-III. They were also screened for any visual impairments using the RAF rule and Ishihara colour blindness test. Then, the participants were asked to complete the HADS, to screen for any psychological distress. Additionally, the ADHD participants were asked to complete the ASRS questionnaire, to determine the severity of the disorder. On completion of the pre-study questionnaires, participants will be provided with Task information leaflet. At this time control and ADHD participants were presented with a vignette (Appendix B) detailing an individual trying to feign ADHD. Comparatively, those assigned to the feigning condition were presented with a vignette (Appendix C) that explained the symptoms of ADHD and were asked to imagine themselves in a situation where they were to feign ADHD. All participants were then asked to complete the two eye movement tasks and the associated calibration trials. Fundamentally, at this time healthy controls and those with ADHD were asked to complete the tasks honestly to the best of their ability. In comparison, those in the feigning condition were asked to complete these tasks whilst pretending to have ADHD (without any over-exaggeration). On completion of the tasks, all participants were informed that they will be entered into a lottery to win a £25 and were provided with a debrief sheet (Appendix H), which explains the details of the study. Data Analysis DataViewer Software Version 3.2 was used to extract and analyse the raw EyeLink data. The data was then analysed online using a bespoke software SaccadeMachine. With the software spikes and noise were removed by filtering out frames with a velocity signal greater than 1,500 deg/s or with an acceleration signal greater than 100,000 deg 2 /sec. Fixations and saccadic events were identified using the EyeLink Parser, and the saccades were extracted alongside multiple temporal and spatial variables. Trials were eliminated when the participant did not direct their gaze on to the central fixation. The temporal window of 80-700ms used and measured from the onset of the target display. Anticipatory saccades made prior to 80ms, and excessively delayed saccades made after 700ms were removed. The data thus formed consists of the latency and error rate. Latency is the time taken of the correct trial whereas the error rate is the percentage of trials the participant got wrong. Data of one individual participant from the control group was removed as their ACE score was low suggesting the probable presence of mild cognitive impairment. Due to the lack of a formal diagnosis, data of an ADHD participant was removed. All data was then assessed to ensure it met the assumptions required for statistical analysis. First, all data was assessed for the presence of any outliers (+/- 2SD). This analysis revealed there were 3 outliers for the both the pro- and anti-saccade measures. Given that these outliers may skew the subsequent analysis, all outliers were removed. The subsequent data was then checked to ensure it met the assumptions of normality. It was found that the prosaccade latency satisfied the normality condition (see Figure 1), hence one-way ANOVA was applied to investigate the difference in latency across the groups. As the data for prosaccade error rate was skewed (see Figure 2), Kruskal-Wallis H Test was used to determine the difference in data across the groups. Removing the outliers gave a data which satisfied normality condition for both anti-saccade latency (see Figure 3) and error rate (see Figure 4). Hence one-way ANOVA was used to test the difference for both the data across the groups and a post hoc Tukey’s Honest Significant Difference test was used to determine the significance of the difference in anti-saccade latency.
SPSS.sav for results Word.doc for demographic and data acquistion form PDF for consent form