["itemContainer",{"xmlns:xsi":"http://www.w3.org/2001/XMLSchema-instance","xsi:schemaLocation":"http://omeka.org/schemas/omeka-xml/v5 http://omeka.org/schemas/omeka-xml/v5/omeka-xml-5-0.xsd","uri":"https://www.johnntowse.com/LUSTRE/items/browse?output=omeka-json&page=9&sort_field=added","accessDate":"2026-05-03T08:37:57+00:00"},["miscellaneousContainer",["pagination",["pageNumber","9"],["perPage","10"],["totalResults","148"]]],["item",{"itemId":"122","public":"1","featured":"0"},["collection",{"collectionId":"6"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"187"},["text","RT & Accuracy"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"188"},["text","Projects that focus on behavioural data, using chronometric analysis and accuracy analysis to draw inferences about psychological processes"]]]]]]]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2622"},["text","Seeing helps our hearing: How the visual system plays a role in speech perception"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2623"},["text","Brandon O’Hanlon"]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2624"},["text","2021"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2625"},["text","Difficult listening conditions can result in a decrease in our ability to successfully discriminate speech. In these conditions, the visual system assists with speech perception through lipreading. Stimulus onset asynchrony (SOA) is used to investigate the interaction between the two senses in speech perception. Due to widely stimulus dependent effects, the exact timings for how far one stream can be asynchronized against the other drastically differs from account to account. Previous research has not considered viseme categories to ensure that selected speech phonemes are visually distinct. This study aims to create and validate a set of audiovisual stimuli that considers these variables for examining speech-in-noise, and to determine the SOA integration period for these stimuli. 27 online participants would be presented with either audio-only stimuli of a speaker speaking or audiovisual stimuli that also contained visuals of the speaker’s lip and mouth area as the speech were spoken. The speech was either clear or in-noise, and either displayed no stimulus onset asynchrony (SOA) or had SOA introduced at one of five different levels (200ms, 216.6ms, 233.3ms, 250ms, 266.6ms). Results indicate that, whilst the effect of visual information assisting with speech-in-noise is apparent, it is weaker of an effect than previous literature. Whilst response times imply that 250ms marks the integration window period for our stimuli, no significant accuracy changes corroborate this finding. In all, the study was successful in creating a more valid set of stimuli for testing. As power sufficiency was not met, more testing would be required to firmly cement the findings. "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2626"},["text","Linear mixed-effects modelling"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2627"},["text","connection, allowing for a direct, uninterrupted video feed at 1920x1080 resolution and 60 frames per second. The camera was mounted onto a stable tripod to reduce movement of the camera as much as possible during recording. DroidCam X software was used to aid the streaming of the video in real-time with little compression and loss whilst still retaining a 1080p@60fps quality level. OBS software was used for recording as it allowed the audio from the external microphone and the video from the camera to be encoded together in real-time as a single MKV file. This was beneficial, as it removed potential human error that can occur when manually stitching audio files and video files together. Therefore, we can be certain that there were no asynchronous anomalies between the audio and video streams during encoding. Another benefit of OBS software is that it reports how many frames of video are dropped when recording and encoding an MKV file, which was important to ensure that the home desktop was encoding the video in its entirely akin to a lab-calibrated desktop. No frames were reported to be dropped for all speech tokens recorded. All stimuli were recorded as MKV files initially to avoid lossy compression in the recording. A software-based x264 bit CPU encoding method was used for the recording, due to a lack of internal GPU encoding method (such as Nvenc encoding) on the home system. \r\nAfter the initial recording, the speech tokens were edited in length and converted to mp4 files at a resolution of 1280 x 720p and a frame rate of 60 frames per second. As the study would be completed on participant’s laptops or desktop systems and using their internet connection, we cannot ensure that all participants are using a device with a 1920 x 1080p resolution screen. By reducing the resolution of files to 720p, all potential participant resolution sizes can be accommodated whilst ensuring all participants view the files at the same resolution. For audio-only conditions, the video of the lips was overlayed with a plain black PNG image file. This kept the audio-only stimuli in video format rather than export the file as an mp3. Regarding the inability to control the internet connection speeds of each participant, the experiment was set to download all stimuli as browser cache before it began, ensuring that there were no latency differences.\r\nAudacity software (Audacity Team, 2021) was then used to rip the audio from the MKV files to be edited as WAV files in Praat software (Boersma & Weenink, 2021) for the creation of speech-shaped noise. First, a sentence using English words – ‘His plan meant taking a big risk’ - was recorded to provide a base for the speech-shaped noise. White noise was then produced using Praat’s white noise generator. The noise was brought down to an intensity tier, then an amplitude tier. This was then multiplied with the sentence above to create speech-shaped noise. Praat was then used to combine the speech-shaped noise with the speech-in-noise conditions at a speech to noise ratio of minus 16dB. This was done using a Praat script developed by McCloy (2021). Finally, Audacity was used again to ramp up the start and ramp down the ends of all audio files for every condition. The audio was then stitched back onto the MP4 files. \r\nFor the conditions where the onset of the stimuli was asynchronous, Lightworks was again used to displace the audio ahead of the onset of the speech token using exact frames of the video footage (12, 13, 14, 15, and 16 frames per second) which corresponded with the stimulus onset asynchrony levels of the relevant conditions. The result was 42 stimuli in MP4 format, representing three speech tokens (Ba, Fa, and Ka) for each of the 14 conditions presented to the participant. These were uploaded to a GitHub repository to be accessed by Pavlovia during the experiment. \r\nProcedure\r\nParticipants were first given a participant code and a link to the online Qualtrics consent and screening forms via email. A copy of the participant information sheet was displayed at the start of the Qualtrics questionnaire to remind participants of the study to ensure informed consent was given. Participants were also reminded at this stage to ensure that they were in a quiet room with no background noise, as well as to load the experiment on either Microsoft Edge, Google Chrome, or Mozilla Firefox internet browsers on a laptop or desktop computer. They were explicitly told not to open the experiment on any other browser, such as Safari, nor on a mobile or tablet device as these were incompatible. Once consent had been given and the participant had met the screening criteria based on their answers, they were automatically redirected to the experiment on Pavlovia. If a participant did not meet the criteria for the study, they were redirected to a message informing them of their ineligibility and they were prevented from proceeding to the rest of the experiment. To begin the experiment, participants were once again reminded of browser and device limitations and told to use headphones in a quiet room. If a participant was using an incompatible device or browser to load the experiment, they were instructed to close the experiment and re-open it on the correct device or browser before beginning. \r\nA volume check began, in which a constant A tone played, and participants were asked to adjust the volume of their device as necessary for a comfortable auditory experience and to ensure that the audio was playing correctly at a sufficient volume level. In a typical lab setting, a set volume would be decided for all participants. However, as the study was completed online on the participant’s own devices, settling for the participant’s preferred hearing volume was preferable instead. Once complete, the spacebar would be pressed, and the tone stopped. Participants were then given a brief explanation of the task to complete. They were informed that a video would play either showing no visual information or visual information of lips moving. Meanwhile, speech would be played. Participants were told to listen carefully to the speech sound spoken, and after hearing the sound to press one of three buttons on their keyboards that corresponded with the three available speech tokens. They were reminded before and after each trial to press 'z' on their keyboard if they heard \"Ba\", 'x' for \"Fa\", or 'c' for \"Ka”. Participants were told to answer as quickly as possible. If they were unsure, they were told to make a guess. \r\nTo begin, participants were given 6 practise trials to attempt the task before data was collected. This was using the clear, 0ms, audiovisual condition stimuli, with 2 trials for each of the 3 speech tokens (Ba, Fa, and Ka). A white crosshair would be displayed on the screen for 1000ms before the trial began to bring attention to the centre of the screen where the video trials would be displayed. Stimuli were shown for 2500ms, then the response screen would display. On this screen, the participants were reminded of the buttons to press for each of the three speech sounds. Only the three buttons could be pressed and pressing the buttons whilst the stimuli were still playing was not possible. The first key pressed after the stimuli were played was recorded and then would take the participant to a relay screen, where they would be informed to press the spacebar to continue. Upon pressing the spacebar, the white crosshair would return, and the next trial began.\r\nAfter completing the practice, the participant was reminded of the task details once more before the experiment began for real. A total of 546 trials (not including the practise trials) were completed. The order of the trials and conditions was completely random to counterbalance any potential order bias. Every 42 trials, a broken screen would appear. This screen told the participant to take a short break before continuing with a press of the spacebar. If the participant did not wish to take a break, they were permitted to continue with a spacebar press immediately. There was a total of 12 breaks in the experiment. After each break, participants were asked a basic mathematics question, for example: ‘What is 3 +2?’. Participants could only proceed to the next chunk of trials if they responded with the correct answer. This was put in place to ensure that participants were continuing to pay attention to the experiment. Upon reaching the end of the final trial, participants were shown an ending screen where they were informed that the experiment had ended. Participants were also informed to email the primary researcher for debriefing information. Upon completing the study, participants could close the browser tab or window down and all data would remain recorded on the Pavlovia system. \r\nIf a participant closed the browser tab or window during the experiment, partial data would be recorded up to the last trial that they responded to. If this was by mistake, participants could open the experiment again and restart. However, progress would not be saved, and the participant would have to start the experiment again from scratch. Using the same participant code would not overwrite the participant’s previous data, and instead created a new participant dataset. Full datasets were used over the partial dataset in this case, unless no full dataset was recorded for a participant. \r\nAnalysis\r\nDescriptive statistics were first gathered from each condition for both the accuracy ratings and the reaction times. The assumptions of linear and generalised linear mixed-effects models were tested, including residual plots to check for linearity, quantile-quantile plots for normality, assessing the levels of multicollinearity between stimuli type, speech type, and stimulus onset asynchrony levels using variance inflation factors, and ensuring the assumption of homoscedasticity is met. \r\nUsing both lmerTest (Kuznetsova et al., 2020) and lme4 packages, a combination of both linear mixed-effects regression model (LMER) analyses for the response time scores and generalized linear mixed-effects regression model (GLMER) analyses for the accuracy scores were conducted. LMERs were chosen instead of repeated measures generalised linear models like ANOVA tests because it considers random effects that may be present across all 546 trials on a participant-by-participant basis. As accuracy is inherently bound – due to either being accurate or inaccurate only – it can be argued to be categorical. Therefore, GLMERs were used for accurate analyses to ensure that assumptions of categorical dependent variables in mixed-effects models are met. For the LMER analyses, there were two models. Model 1 used response times as the dependent variable, modelled with stimuli type and speech type as fixed effects. The interactive effect between stimuli type and speech type was also included in the model. Model 2 used response times as the dependent variable, modelled with speech type and stimulus onset asynchrony timings as fixed effects. The interactive effect between speech type and stimulus onset asynchrony timings was also included in the model. \r\nThe GLMER analyses also had two models. Model 1 used accuracy as the dependent variable, modelled with stimuli type and speech type as fixed effects, including the interactive effects between the two fixed effects. Model 2 used accuracy as the dependent variable, modelled with speech type and stimulus onset asynchrony timings as fixed effects. Again, interactive effects were included. For all four analyses, the speech sound token used (Ba, Fa, or Ka), participant age, and the participant ID were all included as random effects in the respective models.\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2628"},["text","Lancaster University "]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2629"},["text","Excel File"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2630"},["text","O’Hanlon2021"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2631"},["text","Stephanos Mosfiliotis"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2632"},["text","Open (unless stated otherwise)"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2633"},["text","None (unless stated otherwise)"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2634"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2635"},["text","Data "]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"2636"},["text","LA1 4YF"]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"2637"},["text","Dr Helen E. Nuttall"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2638"},["text","MSC"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2639"},["text","Cognitive, Perception"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2640"},["text","48 participants (11 male, 14 female, 2 non-binary)"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2641"},["text","Quantitative"]]]]]]]],["item",{"itemId":"123","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"109"},["src","https://www.johnntowse.com/LUSTRE/files/original/0fdc3409fc1e66a7b426a712ec8d17d0.pdf"],["authentication","57616b84353b3000df68be550e7ca423"]],["file",{"fileId":"110"},["src","https://www.johnntowse.com/LUSTRE/files/original/c214bf10da976b5fadef65dac9e1e05e.csv"],["authentication","e0ba70228e4dc98ce27720026fbf84b6"]],["file",{"fileId":"111"},["src","https://www.johnntowse.com/LUSTRE/files/original/1ea0cfff55d6a45ade86081608112293.pdf"],["authentication","c1710cfeeb897adf8839a8c0ed3d2e33"]],["file",{"fileId":"112"},["src","https://www.johnntowse.com/LUSTRE/files/original/2eff799f6c8cf90bf634d8fccf555da7.pdf"],["authentication","558fbe9a3789e50c17f2513aae78e512"]]],["collection",{"collectionId":"5"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"185"},["text","Questionnaire-based study"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"186"},["text","An analysis of self-report data from the administration of questionnaires(s)"]]]]]]]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2650"},["text","The impact of retribution on perception of transgressor by others "]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2651"},["text","Olivia Wilson"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2652"},["text","Emotions play a key role in within society, behaviour and human life with moral emotions such as guilt, regret and shame being able to influence individuals’ judgments and actions. For example, a person who experiences guilt will want to fix their wrongdoing that has caused this. There are times where these efforts to repair ones transgression, can lead an individual to self-punish in order to repair bonds with others and reduce negative consequences of the situation. The present study experimentally investigated the effect of self-punishment intensity on perceptions of a transgressor. Participants were randomly assigned to one of three conditions of self-punishment intensity (low, correct and high). Vignettes were manipulated for each condition and presented for participants to read for them to answer questions on their judgments of the transgressor (perceptions of guilt, shame, regret, moral character, and trustworthiness, their willingness to forgive the transgressor, how likely they thought they would reoffend in the future) and rated this on a Likert scale of 0-5. Participants allocated to low self-punishment had more negative perceptions towards the transgressor overall when compared to correct self-punishment. However, this was not found beyond this as no differences were seen for those within the high self-punishment condition "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2653"},["text","Retribution, Transgression, Guilt, Vignette"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2654"},["text","Participants. Participants were recruited through the use of LU Sona system as well as opportunity sampling through use of social media and network platforms accessible. A total of 174 responses were collected via Qualtrics, of those 158 have been successfully completed through to the end whilst 16 have only been started and answered few questions at most. Therefore, the decision has been made to exclude any incomplete attempts. This resulted in a final sample of 158 of which 54 are in the high punishment condition, 52 in low punishment condition and 52 in correct punishment. \r\nDesign. This is a one-factor study with 3 levels (self-punishment: Low punishment, correct punishment, and high punishment) between-subjects design. Qualtrics randomly allocated participants to one of the three conditions. \r\nMaterials. A short hypothetical vignette was used to describe an event between two individuals; ‘Simon’ the transgressor and his friend, who he steals money from. With each of the punishment conditions, the vignette introduced the scenario with the same starting sentences to create the scene of someone performing a transgression against their friend with feelings of self-directed negative affect presented by the transgressor: \r\nSimon is out with his friends when he noticed that a member of his group has left their wallet unattended. Simon helps himself to the £40 that was in the wallet. His friend eventually realises that the money has been stolen and seems distressed. The next day, Simon feels bad for his actions and confesses to his friend that he took the money. \r\nThe final sentence of the vignettes was manipulated for each of the three conditions. The sentence stated the amount of money returned to Simon’s friend, which was either less than originally taken (low punishment, £20), same amount (correct punishment, £40) or more than originally taken (high punishment, £60). \r\nHe gives his friend all the money he has in his wallet, which came to £20 (or £40, or \r\n£60). \r\nHypothetical vignettes have been a popular method to explore social actions within research allowing actions to be explored in context to specific situations, people’s judgments, reactions and perceptions of the scenario being described and/or the individual people within the vignette. It allows this all to be clarified in the form of data collection and provides a less personal, and therefore less threatening way of exploring sensitive issues and topics in society (Barter & Renold, 1999; Hughs, 1998; Schoenberg & Ravdal, 2000). Vignettes are a valuable technique for exploring perceptions of situations and have been utilised previously in research on guilt and perceptions of a transgressor post-transgression (McLatchie, 2019; Manstead & Semin, 1981; Dijk, de Jong & Peters, 2009) and so have been utilised in this research of intensity of self-punishment post-transgression. \r\nEmpirical research has shown that emotions and perceptions of guilt specifically focuses attention on the behaviour and action that has occurred which has in turn elicited these feelings (Tangney & Dearing, 2002). This is why the vignette in the present study was written with a particular emphasis on presenting the transgressor to be feeling remorse/guilt after failing to adhere to a social standard, being explicitly stated through acceptance of responsibility. This was done through stating that Simon ‘felt bad for his actions’, intentionally presenting to participants that, regardless of the punishment, Simon did know his behaviour was wrong. It can also be seen in this study through the motivations and efforts to recompensate the wrongdoing through his self-punishment and returning of a quantity of money. Absence of this could imply to participants a lack of emotional response, this could have impacted judgments on Simon regardless of the presence of punishment or not. \r\nAs stated previously, other emotions can be used synonymously within conversation when referring to guilt, such as self-conscious emotions like regret and shame; it was important to ensure that guilt was specifically being portrayed. McLatchie (2019) ensured this in his study investigating punishment types (no punishment, self-punishment, and other punishment). McLatchie used a vignette that described interpersonal violations as these are primarily associated with guilt than the other emotions. This is because it includes other individuals and not merely directed at the self where the common emotion that would most likely be triggered would be shame instead. Due to this, the present study also used a vignette that described an interpersonal violation of moral and social standards with the last sentence manipulated to present three self-punishment conditions based on varying intensities. These terms are popularly used interchangeably within conversation due to multiple similarities between them (Shen, 2018; Bhushan, Basu & Dutta; 2020; Stearns & Parrott, 2012), \r\nParticipants were then asked a series of questions which gathered information on the participants judgments of Simon. Participants were asked to rate the extent of the perceived guilt, shame, and regret of the transgressor as a third-party observer which keeps in line with current research which provides evidence for a strong internal consistency of these measures (McLatchie, 2019). It is also consistent with previous research where the same elements were combined to calculate an overall guilt score. This emphasised the importance of these emotional responses and behaviours that an individual may present when judging overall guilt being experienced by the perpetrator. How much the participant thinks Simon (the transgressor) deserves to be forgiven was also measured. This was done with an adapted version of Zhu et al.’s (2017) way of measuring this and has proved to be effective in prior research related to guilt and self-punishment (McLatchie, 2019). The final questions were – how likely the participants thought Simon would reoffend, and to what extent they thought the punishment performed was sufficient for the transgression committed. All answers were presented and rated on a Likert scale with the question above. \r\nProcedure. Participants were invited to partake in a study aiming to evaluate a ‘social action’. Qualtrics was used to provide the survey to participants where they were asked to read through the vignette prior to moving through the questions and answers which measured their responses. As each question appeared, the vignette remaining at the top of the screen for reference throughout. Answers were presented on a 6-point Likert scale ranging from 0 (“Not at all”) to 5 (“Completely”) which they were required to choose their response through a rating. \r\nOnce participants completed this survey, a final section asked participants to provide demographic information with a full debrief. Demographic information included basic information such as the participants age and gender. Additional questions were included in order to gain an insight into the participants experience with situations such as the one described in the vignette and their personal experiences with guilt allowing any influences of the participants character to be seen when analysing results. These include being asked if they have ever had an experience as the protagonist (Simon in this case), someone who has been stolen from, and if they are prone to feelings of guilt. \r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2655"},["text","Lancaster University "]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2656"},["text","Data/Excel.csv"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2657"},["text","Wilson2022"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2658"},["text","Anastasija Jumatova & Annie Fountain\r\n \r\n"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2659"},["text","Open "]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2660"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2661"},["text","English "]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2662"},["text","Data "]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"2663"},["text","LA1 4YW"]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"2664"},["text","Tamara Rakic"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2665"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2666"},["text","Behavioural and Developmental "]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2667"},["text","158 Participants "]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2668"},["text","Quantitative: Correlational and Linear "]]]]]]]],["item",{"itemId":"124","public":"1","featured":"0"},["collection",{"collectionId":"11"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"987"},["text","Secondary analysis"]]]]]]]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2669"},["text","A Scoping Review of the Effects of Benzodiazepines on Emotions in Young People"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2670"},["text","Lewis Pares"]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2671"},["text","2021"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2672"},["text","Background: Benzodiazepines are primarily used to manage anxiety and agitation. While it is understood how benzodiazepines work physiologically it is not fully understood how these physiological changes cause the emotional changes. As this relationship is not fully understood, it maybe that benzodiazepines also affect emotions in ways not currently known, such as being a factor in emotional dysregulation.\r\nObjective: To conduct a scoping review into the effects of benzodiazepines on young people. To map the of the effects benzodiazepines have on emotions in young people and identify any links between benzodiazepines and emotional dysregulation.\r\nDesign: A scoping review was conducted. PRISMA protocols were followed but other sources such as Cochrane and Joanna Briggs Institute were consulted to develop a framework.\r\nResults: This review’s findings suggests that benzodiazepines do reduce anxiety and agitation. However, the research concerning children and adolescents is limited, and suggests benzodiazepines maybe less effective than in adults. There are many adverse effects but despite this prescription use remains relatively high. Non-prescription misuse in adolescents is evident and globally prevalent. Only one direct link was found to emotional dysregulation, but other possible links were also found. \r\nConclusions: More research into the areas of the efficacy of benzodiazepines in children and adolescents and the risks associated with paradoxical and adverse effects is needed. Possible links between emotional dysregulation and benzodiazepines misuse were made and research is needed to understand if this relationship exists and the effects. Any improvement in understanding this relationship will enable targeted interventions to be developed.\r\n\r\n"]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2673"},["text","Benzodiazpines, Young people, Children, Adolscents, Emotion/s, Emotional dsyregualtion, Non-prescription misuse."]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2674"},["text","The search was conducted using the following databases: Web of Science, PubMed, CINAHL, Psych Info, Medline and Embase. Searches were dependent on the functionality of the different databases such as different key terms, different abilities to expand search terms and different limiters or age groups, these are all shown in the search terms document in the OSF repository. All searches were limited to English language. No further sources were used to supplement the search. "]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2675"},["text","Lancaster UNiversity"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2676"},["text","Excel spreadsheet/.xlsx"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2677"},["text","Pares2021"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2678"},["text","Jiqian Chen; yemi oluwaleye"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2679"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2680"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2681"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2682"},["text","Date"]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"2683"},["text","LA1 4YF"]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"2684"},["text","Rob Davis"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2685"},["text","MSC"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2686"},["text","Clinical,Developmental; Cognitive,Developmental;Cognitive,Psychopharmacology;Developmental;Developmental,Neuropsychology;Psychopharmacology"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2687"},["text","N/A"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2688"},["text","Scoping Review"]]]]]]]],["item",{"itemId":"127","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"115"},["src","https://www.johnntowse.com/LUSTRE/files/original/ef7c4c4641dbd30c20af2c641ef0ff2b.zip"],["authentication","bb6e0b394e4a286abbe2cb4ca08e9a01"]]],["collection",{"collectionId":"5"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"185"},["text","Questionnaire-based study"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"186"},["text","An analysis of self-report data from the administration of questionnaires(s)"]]]]]]]],["itemType",{"itemTypeId":"14"},["name","Dataset"],["description","Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing."]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2705"},["text","Do trustworthiness judgements help people to recognise synthetic faces? "]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2706"},["text","Haisa Shan "]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2707"},["text","8 September 2021"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2708"},["text","Recent advances in digital image generative models have allowed for artificial creation of fake imagery such as synthesising highly photorealistic human faces. Style-based Generative Adversarial Networks (StyleGAN) is one of the most state-of-the-art generative models in this field, and has been widely used on facial image generation. However, with the increasing ease of using such image generative models, the security in many domains, such as forensic, border control and mass media, is vulnerable in front of the potential threats resulted from the misuse of image generative technologies. To date there has only been limited empirical research into the facial characteristics of StyleGAN-generated faces to support the design of detection methods against such synthetic faces. This study used StyleGAN2 (an improved version of StyleGAN) to generate faces and invited people to complete two facial image evaluation tasks, 1) Discrimination task, 2) Trustworthiness rating task. The study results demonstrated that, in the discrimination task, subjects had trouble recognising synthetic faces by direct/explicit judgement; while in the trustworthiness rating task, subjects perceived the synthetic faces as significantly more trustworthy than real faces. The study further analysed gender bias and ethnicity bias on the perception of facial trustworthiness, with results showing some differences between different levels of gender and ethnicity. In conclusion, people’s ability to recognise synthetic faces is poor, but it is possible that people rely on the perception of facial trustworthiness to discriminate synthetic from real faces. The findings in this study have implications for the development of detection methods against digitally generated faces."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2709"},["text","\r\nStyleGAN, synthetic face, trustworthiness perception, facial trustworthiness "]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2710"},["text","Subjects and design\r\nThree hundred and fifty-seven subjects (114 males, mean age = 25.2, SD = 5.8; 227 females, mean age = 25.0, SD = 6.3; 10 non-binary, mean age = 23.6, SD = 8.93) were recruited to complete an online survey test delivered on www.qualtrics.com. The responses of subjects who started but did not complete the online survey were eliminated to avoid distorting the research results. We used computer-synthesised facial images in this research as fake faces, mixed with real faces to examine people’s ability to detect fake faces and perceptual differences of trustworthiness between real/fake faces. Subjects did not get rewards for their participation, though they could see the test score of their performances at the end of the survey. The Qualtrics survey was based on a within-subjects design in which all subjects viewed the same two sets of adult facial images and completed each of the two tasks. To eliminate the effect of between-sets difference, the use of each image sets was counterbalanced in the individual test for each subject. Before the survey started, all subjects provided informed consent and completed a demographic questionnaire about their age, gender, ethnicity. In terms of the experimental power of 0.8 and significance level of 0.05, with a small effect, the power calculation indicated that the study needed at least 198 subjects.\r\nStimuli\r\nA total of thirty-two human facial images (1024×1024 resolution), including 16 real and 16 synthetic faces, were used as stimuli in the survey. All real faces were taken from a publicly available dataset for high-quality human facial images, Flickr-Faces-HQ (FFHQ), which is created as a benchmark for GAN (see https://github.com/NVlabs/ffhq-dataset), and all synthetic faces were gained from the dataset of the generative image modeling, StyleGAN2 (see https://github.com/NVlabs/stylegan2). To ensure a diverse dataset, in each of the two sets of faces, there were 4 Black, 4 East Asian, 4 South Asian, 4 White, and 2 males and 2 females for each ethnicity. Among the sixteen faces of each set, half of them were real and half were synthetic, but this was unknown to subjects.\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2711"},["text","Lancaster University "]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2712"},["text","data/Excel.csv"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2713"},["text","Cognitive, Perception\r\nForensic"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2714"},["text","Joanne Roe "]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2715"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2716"},["text","None "]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2717"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2718"},["text","Data "]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"2719"},["text","LA1 4YW"]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"2720"},["text","Sophie Nightingale"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2721"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2722"},["text","Cognitive, Perception\r\nForensic\r\nSocial\r\n"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2723"},["text","357 Participants "]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2724"},["text","ANOVA\r\nPower Analysis\r\nT-Test"]]]]]]]],["item",{"itemId":"128","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"116"},["src","https://www.johnntowse.com/LUSTRE/files/original/2c5a49439ff4e1f7d625881935e22557.docx"],["authentication","77e51c9ccecf6fcd08701781361a6ac1"]]],["collection",{"collectionId":"11"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"987"},["text","Secondary analysis"]]]]]]]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2725"},["text","A secondary data analysis: How will the effects on accuracy differ when measuring individual differences in word reading skill in Spanish?"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2726"},["text","Julianna Krol"]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2727"},["text","2021"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2728"},["text","A deficit in accuracy has been found to correlate to reading difficulties (Davies et al., 2007). Effects of psycholinguistic factors and differences in language orthographies contribute to reading skills, predominantly in children with reading impairments such as dyslexia. The present study is a secondary data analysis of the original research conducted by Davies et al. (2007). \r\nThe effects on accuracy of individual differences demonstrated by nonword reading skill and word property measures were examined in Spanish children. Participants were 110 students differing in reading ability from schools located in A Coruńa, Lugo, Orense and Pontevendra in northern Spain. The subjects were required to take standardized and experimental reading ability and intelligence tests. \t\r\n\tEight lists consisting of 15 words each were created.  The words were presented in five rows of three columns. Participants were asked to read the words as quickly and accurately as they could. Words which were incorrectly pronounced were identified as errors. Word property measures suggested to affect reading ability were selected and updated from an online database of Spanish words ‘EsPal’. Variables of frequency, length of words, neighbourhood size (Levenshtein distance), RAN, PROLEC-R nonword reading were investigated in the present analysis. Accuracy of reading scores was found to be significantly high for the sample. Effects of individual differences on accuracy were noted. Word property measures of frequency and neighborhood size were found to significantly affect reading accuracy. Effects of fluency (RAN) and nonword reading (PROLEC-R) were also observed. \r\n\tThe analysis provides insight into plausible factors which contribute to reading impairments in a rule governed orthography such as Spanish. Results suggest that perhaps nonword reading skill could serve as an marker for reading difficulties. \r\n"]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2729"},["text","Individual differences, Dyslexia, Word property effects, Language orthographies, Reading accuracy"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2730"},["text","Participants\r\n\tIn the original study (Davies et al.,2007) researchers selected and identified three groups of children from an initial sample of 110. Children who indicated clear reading disabilities (DYS/ dyslexia), a control group consisting of children matched by reading ability level (RA matched group) to the DYS group and a chronological age control group (CA matched group). The present analysis investigated the whole sample of 110 participants and no group selection was conducted. \r\n\tParticipants were students from schools located in A Coruńa, Lugo, Orense and Pontevendra in northern Spain. 110 children differing in reading ability and age were selected. These children did not obtain any prior diagnoses of impaired neurological or sensory-motor functioning. The sample of 110 children was required to take standardized and experimental reading ability and intelligence tests on different school days during a 3-month  time. Experimental data was gathered in a single session focusing primarily on the experimental test, whereas the standardized reading test was given in a separate session. \r\nMeasures\r\nReading performance was measured across a series of ability tests (PROLEC-R, RAN). \r\n\tPROLEC-R Battery Tests of Literacy Skills\r\n\tEvaluation of reading processes for children is assessed through the use of the PROLEC-R battery constructed by Cuetos, Rodriguez, Ruano & Arribas (1996). The battery consists of Spanish tests analyzing reading processes such as lexical, semantic etc. Subjects were required to read from a list of 40 words as quickly and accurately as possible. Words differed on properties such as frequency and length. The scores obtained consist of a score relating to accuracy and reading speed when assessing words and nonwords. It has been suggested that the results of the test provide significantly more information when combining the PROLEC-R scores of accuracy and PROLEC-R reading times. This is why PROLEC-R nonword reading was computed into a combined measure. This was done by dividing accuracy by time. \r\n\tRapid Automatized Naming Tests (RAN)\r\n\tRapid automatized naming (RAN) refers to how quickly a child can read aloud a set of previously known items. These items can include numbers, pictures, letters, colors etc. A child’s performance on the tests is assessed by comparing their reading times to the norm scores of children in the same age. RAN tests are designed to predominantly assess fluency of reading. It is suggested that RAN influences reading scores as it requires the retrieval of stored phonological information (Johnson & Eden, 2014). Children were presented with a sequence of rows consisting of sets with different items (colors, letters, pictures etc.). The subjects were required to read aloud all the items from the list starting from top to bottom. Accuracy of reading and time it took for the child to name the words were recorded. Children with reading difficulties  will be expected to present a delay in reading speed and accuracy, thus scoring low on the RAN tests. \r\n\tWord Property Measures \r\n\tIn the original study (Davies et al.,2007), words were chosen varying on lexical frequency (high or low frequency word), orthographic neighbourhood size (many or few neighboring words) as well as word length (short or long in length) (factorial design 2x2x2).  \r\n\tUpdated word property measures were derived from the EsPal (“Español Palabras” meaning “Spanish words”) repository consisting of properties for Spanish words. The new word property measures derived from the database (frequency, length of words and neighbourhood size) were compiled together with the old data. The system is able to process different corpora in the same way. It combines a corpus which is derived from movie subtitles and one from previously written text such as Web pages, fiction, nonfiction writing etc. The updated measure of frequency is reported within the analysis with the databases original name “esp.count”.  The ‘count’ refers to the number of times in which the word appears within the selected corpus. For orthographic neighbourhood size, all words are counted within EsPal and are in turn compared to other words within the corpus. Yarkoni et al (2008) argued that the orthographic neighbourhood metric (ON) developed by Coltheart et al.(1977) is limited due to the nature of its definition. ON is the number of words which can be developed by substituting one letter in the other word given that it is the same length. As a result, researchers have developed a new measure of orthographic neighbourhood size which is less restricted than the previous metric. The new measure is coded as Levenshtein distance 20 (Lev_N) (Duchon et al.,2013). Levenshtein distance refers to the average distance of 20 words which are found closest in text. LD is calculated as the number of edits to words (substitutions, insertions, deletions) which are needed to change one word into another. For example, the Levenshtein distance between the word “SMILE” to “SIMILES” is two, as it differs from the original by adding the letters “I” and “S” (Yarkoni et al., 2008). \r\n\tAn updated measure of length of words was also derived from the EsPal database and is coded as “esp.num_letters”. This refers to the word length which is expressed in number of letters. \r\nProcedure\r\n\tEight lists consisting of 15 words each were created. Participants were shown each list of words on a A4 sheet of paper. The words were presented in five rows of three columns. Participants were tested individually and were asked to read the words as quickly and accurately as they could. Words which were incorrectly pronounced were identified as errors. Three types of errors were identified: word substitution, nonword and stress errors.  An example of word substitutions would be the word “nube” (cloud) which would turn into \"neuve “(nine). For nonwords: “bigote” (mustache) would be “bixote”. For errors relating to stress “cáfe” would be “café”. All responses from 110 participants were computed and are present in the file: “SpanishR”. Accuracy is presented as the subject responses scored as correct and incorrect (0,1).\r\nAnalysis \r\n\tItem level and subject level data about word properties and subject attributes were extracted. An analysis of the accuracy of responses as well as the effects of word properties on reading was conducted. Errors were scored as 0,1; correct and incorrect.\r\nRandom and experimental variables were identified. Random effects were specified as “palabra” (words) and “subject identifier” (participant name). The experimental/fixed effects were specified as frequency, length, neighbourhood size, RAN, PROLEC-R nonword reading.  To investigate correlations between the experimental variables a correlation matrix was constructed.\r\n\tGeneralized linear mixed effects modeling (GLMM; Baayen, 2007) was used in order to analyze the accuracy of responses made by children to reading words. The distribution of variables included in the model relate to person characteristics and word characteristics. \r\n\tMoreover, GLMM was used to capture the randomness of the sample  to increase accuracy of estimates for the effects of individual differences on word properties. The model explains the variation of accuracy by incorporating experimental and random variables. Model development followed a stepwise process, adding one variable to each model at a time.  The primary model specification was as follows: accuracy~(1|palabra) + (1|subj_identifier), data = spanishr. \r\nA table of estimates of both random and fixed effects were created and analyzed in order to assess the variation in the models.\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2731"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2732"},["text","Data/Excel. csv"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2733"},["text"," Krol2021"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2734"},["text","Florine Causer, Siri Sudhakar"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2735"},["text","Data set belongs to Robert Davies who is the author of the original published study (Davies et al.,2007, “Reading development and dyslexia in a transparent orthography: a survey of Spanish children”.)"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2736"},["text","The present work is a secondary data analysis of the original research conducted by Davies et al. (2007), “Reading development and dyslexia in a transparent orthography: a survey of Spanish children”. "]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2737"},["text","English and Spanish (Spanish participants, words, database) "]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2738"},["text","Data"]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"2739"},["text","LA1 4YF"]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"2740"},["text","Robert Davies"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2741"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2742"},["text","Cognitive, Developmental"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2743"},["text","110 participants "]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2744"},["text","Generalized Linear Mixed Effects Modelling \r\nANOVA\r\nCorrelations \r\n"]]]]]]]],["item",{"itemId":"130","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"125"},["src","https://www.johnntowse.com/LUSTRE/files/original/8084b44115d59813660e075ffce6d2ea.doc"],["authentication","f1a23c86f34e4f68a5974dbcff0f1e50"]],["file",{"fileId":"126"},["src","https://www.johnntowse.com/LUSTRE/files/original/262025a38e591b0c3482ff3dae927560.doc"],["authentication","b70dc83ed90fba9c6c24a6b32ae6b3de"]]],["collection",{"collectionId":"10"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"819"},["text","Interviews"]]]]]]]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2765"},["text","Understanding the psychological, perceptual and emotional impact signage has on residents in a local community. "]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2766"},["text","Alexander Wootton"]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2767"},["text","2021"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2768"},["text","The placement of signage, street furniture and advertisements can have a profound impact on the appearance of a built environment. They play a vital role in shaping the cultural, physical and social identities that impact the perceptions that residents and other stakeholders hold towards local communities, which in turn impacts on behaviours. Adopting a qualitative approach, this study will examine the impact of signage and other visual features that can contribute to the psychological, perceptual and emotional impact that these elements can have on residents in a local community. A number of semi-structured interviews were conducted amongst residents in One Manchester property areas, One Manchester place officers and residents near these areas. Participants were shown a variety of visual images of signage and were prompted to discuss their emotional response and thoughts, and propose suggestions to improve signage. A thematic analysis was conducted using the interview data and indicated the following four themes: signage design, reputation, community engagement and impact of signage. Reflecting upon these themes, the results suggested that existing signage was psychically ill-fitted and visually dull, lacking positive influential stimuli and evocative colours and that it lacked the authenticity and character needed to emotionally resonate with passers-by. This negatively impacted the reputation of the communities, leading them to be categorised as economically poor with high crime rates, resulting in stakeholders feeling alienated and some fearful. The results highlighted that the signage needs to be revitalised as a part of a wider placemaking strategy to rejuvenate local environments, perceived to be run down. This should support the ongoing evolution of these areas and engage community members to instal signage that is both influential and reflects an overall collective vision.  "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2769"},["text","signage, placemaking, community engagement, qualitative research, community reputation"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2770"},["text","Design\r\nDue to the need to gain an in-depth understanding of the psychological, perceptual, and emotional impact signage has on residents in a community and factoring in the Covid-19 pandemic, a qualitative approach was adopted consisting of semi-structured interviews. This style of interviews was considered the most suitable method as they provide rich data on the participant’s thoughts which are not constrained by the bounds of tick box exercises or strict discussion guides. They enable researchers to “assess, confirm, validate, refute, or elaborate upon existing knowledge and the discovery of new knowledge” (Mcintosh & Morse, 2015, p. 1). This enables the discussion between the moderator and participant to flow more smoothly and naturally (Roulston et al., 2003) yet, a flexible guide at the moderators disposal keeps the conversation on topic. Interviews in the project were conducted using Microsoft Teams and telephone communication. The data was then assessed using Braun and Clarke’s (2006) six step thematic analysis.\r\nBraun & Clarke’s (2006) six-steps thematic analysis: \r\nFamiliarisation: Getting to know the overall data collected through re-reads of transcripts. \r\nCoding: Reducing sentences and phrases into small fragments of meaning or “codes”.  \r\nGenerating themes: Identifying patterns among codes. \r\nReview themes: Assuring that the meanings identified are relevant to the representation of data collected (research objectives). \r\nDefine themes: Refine themes developed by establishing their essence and significance. \r\nAnalysing themes: Highlight the frequency of themes and meanings derived from qualitative data analysis. Generate conclusions agreed-upon by all researchers.\r\n\r\nParticipants\r\nA sample of 24 participants was originally agreed, however, only 14 participants were interviewed for the project. Participants were either recruited by One Manchester or the lead researcher from areas across south, east and central Manchester. Participants were made up of the following:\r\n\r\nEight One Manchester residents \r\nThree One Manchester Place Coordinators who worked in specific patch areas\r\nThree Local residents living in areas where One Manchester own property \r\n\r\nThe lead researcher conducted site visits around areas of Manchester, this was done so the lead researcher could physically inspect communities to identify signage which were used to aid the discussion guide. The sites visits were conducted in Rusholme, Openshawe and Clayton. \r\n\r\nVisiting these locations first to view all the signage, symbols and other visual features was invaluable both to generating stimulus material for the interviews and the discussion guides. The aim of the sample was to gain a diverse range of viewpoints from a variety of demographics across Manchester to generate a rich data. Participants were recruited from: Clayton, Droysden, Fallowfield, Gorton, Hulme, Openshawe, Rusholme and Whalley range. A £20 shopping voucher was put forward to incentivise participation in the study. \r\n\r\n\r\nMatierials \r\nInterview guide \r\n\r\nTo obtain the most effective feedback from participants, a discussion guide was created, which provided a structured framework to guide discussions (See Appendix A, see Appendix B for discussed images). When formatting the discussion guide, the lead researcher took into consideration current literature on signage and sought to examine resident’s attitudes, perceptions and behaviours in connection to signage in their local community. \r\n\r\nThe discussion guide was composed of four sections:\r\nSection 1:  Was a general introduction to the subject area and participants’ current awareness of signage and other visuals in their area.\r\nSection 2: Heavily focussed on signage and other visuals gathered from site visits  In all of the interviews, participants were shown the images in the order reflected in Appendix B, and they will be asked the same set of questions in relation to each image in order to generate an in-depth discussion on such images. One Manchester and the lead researcher agreed participants would not be informed figures 1-4 were the perceived negative images and figures 5-8 were the perceived positive images.\r\nSection 3: Focused on the future trajectory for signage and symbols. Participants were asked how their perceptions would be impacted if any of the discussed signage was placed in their areas now and in the future. Following this, participants were invited to share any recommendations into the designs of signage.\r\nSection 4: This was only for One Manchester residents. They were asked questions about One Manchester’s performance and potential future actions with their communities. The section was designed to give residents an active voice in how One Manchester can strengthen their relations with residents and enact positive change to protect the future of local communities.\r\n\r\nEach question in the discussion guide was designed to be open-ended, to allow participants to have a wider scope and openly share their opinions. The guide was configured to offer flexibility to discuss topics, therefore when required the lead researcher altered the order and wording of questions to maintain the natural flow of discussion with participants.\r\n\r\nProcedure\r\n\r\nInterviews were carried out between June and August 2021. Participants were requested to share their opinions around a variety of topics concerning how signage in local communities impact a resident psychological, perceptual and emotionally. Before embarking with interviews, participants were provided an information sheet outlining the study procedure, purpose, confidentiality and their right to withdraw at any time of the study’s duration. If participants accepted the conditions to being interviewed and part of the project, a time was then arranged to administer the interview at the convenience of the participant. Nine of the interviews were overseen through Microsoft Teams, the remaining five were facilitated by telephone at the request of the participants. Before proceeding with the interview, the lead researcher pointed out again the aims of the project and received verbal permission to go ahead with the discussion. Interviews were expedited using the discussion guide to ensure interviews remained structured whilst probing concepts tied to the research question. Attention was devoted to each interview to give participants adequate flexibility to discuss matters significant to them not included in the discussion guide. When required, to guarantee ample depth, follow-up questions and prompts were employed to stimulate participants to delve deeper on essential and intriguing answers (DeJonckheere & Vaughn, 2019). Field notes were developed during discussion, underlining both relevant and vital points, which enabled the researcher to refer to any major points and subsequently, assist them with data analysis (Rapley, 2004). As soon as all the questions had been completed, participants were promptly asked to share any other matters they deemed crucial. If participants were then satisfied with the feedback provided, the moderator would end the interview, and debrief participants about the study which was sent electronically. Discussions typically ranged between 30 minutes – 1 hour which were then all transcribed.\r\n\r\nAnalysis \r\n\r\nAs previously mentioned, Braun and Clarke’s (2006) six step thematic analysis was used to detect themes and patterns underpinning residents’ psychological perceptions, attitudes and behaviours towards signage in local communities. To support Braun and Clarke’s (2006) thematic analysis, a bottom-up analysis was utilised due to the project’s exploratory nature and this facilitates identification of themes that arise from consistent patterns within the data set. Firstly, after each interview was completed, the researcher instantly made notes of the key concepts and beliefs and then transcribed the discussion. To guarantee preciseness of the transcript and the lead researchers’ familiarity with the data content, audio recordings and transcripts were reviewed several times. Subsequently, the process to create codes began, the lead researcher analysed the data set and identified key extracts from the data on the basis of their significance and relevance which led to the creation of the codes. Thereafter, provisional themes were produced through a thorough examination of the coded data set, when shared patterns were discovered and judged to be similar or unified under a core notion. All codes were integrated into a central theme. From this, the provisional themes then were revised and reviewed to ensure the themes had remained articulated and unique. During this period, the coded excerpts linked to a core theme was re-examined to verify it could reinforce the central theme and they featured no inconsistencies with that theme (Braun and Clarke, 2006). By which time, a number of themes were either excluded or merged due the lack of sufficient data to uphold the theme. The procedure was repeated several times to consolidate relevancy of the themes to the research question whilst rigorously ensuring they mirrored the patterns found in the data set (Braun and Clarke, 2006). Ultimately, the final themes had been selected and a meticulous account of each theme was supplied. Once the thematical analysis process had been completed, extracts from the content were chosen to illustrate and support the relevant themes in the report."]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2771"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2772"},["text","Word doc."]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2773"},["text","Wootton2021"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2774"},["text","Reva Maria George"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2775"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2776"},["text","Consultancy - Commercial report "]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2777"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2778"},["text","Text"]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"2779"},["text","LA1 4YF"]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"2780"},["text","Leslie Hallam"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2781"},["text","MSc."]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2782"},["text","Psychology of Advertising"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2783"},["text","14"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2784"},["text","Qualitative (Thematic Analysis)"]]]]]]]],["item",{"itemId":"131","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"128"},["src","https://www.johnntowse.com/LUSTRE/files/original/108cecf7f7179778b4560e89499d451a.pdf"],["authentication","ed2fe5669f2c0eaba484d72e312d7831"]]],["collection",{"collectionId":"10"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"819"},["text","Interviews"]]]]]]]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2789"},["text","Does Advertising Truly Represent the LGBTQ+ Community? An Analysis of Intersectionality and Consumer Responses to LGBTQ+ Advertising "]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2790"},["text","Layton Edgington"]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2791"},["text","September 2021"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2792"},["text","Depictions of sexual and gender minorities in advertising are becoming increasingly common and diverse. Yet, numerous intersections within these portrayals are still invisible. Previous research has found mixed results regarding consumer responses to LGBTQ+ identities in advertising. The current study aimed to obtain a further understanding into how a diverse range of consumers respond to heteronormative versus LGBTQ+ imagery in ads. This was assessed using semi-structured interviews to examine sexual and gender minority consumer (n = 13) and non-LGBTQ+ consumer (n = 6) reactions to three distinct IKEA ads. In addition to this, LGBTQ+ character depictions in 286 worldwide mainstream ads from 2016-2020 were analysed for measures of intersectionality across the dimensions of race, age and specific LGBTQ+ membership, extending the previous findings of Nölke (2018). Results indicated that non-LGBTQ+ participants showed similar responses and subsequent brand evaluation regardless of ad theme. Sexual and gender minority participants were found to show preference towards the ad featuring LGBTQ+ identities, though were often found to be sceptical of such portrayals. Intersectionality analysis uncovered that 47 out of a possible 96 intersections were completely invisible from 2016-2020, although representation of minorities within the community has increased substantially since the original findings. Results demonstrate the importance of character depictions in advertising, highlighting why intersectionality of such portrayals needs to increase in the future. Findings further denote how and why different consumers react to specific ad imagery, making recommendations to marketers regarding their inclusion of LGBTQ+ identities in advertising. "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2793"},["text","LGBTQ+ advertising, prosocial advertising, intersectionality, consumer attitudes"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2794"},["text","Participants\r\nThe sample consisted of 19 participants aged between 18-53 at their time of interview; Mage = 23.5 years, SDage = 7.6. Of this sample, 13 participants stated that they identified as LGBTQ+ (2 White lesbian females, 1 Mixed-Race lesbian female, 2 White gay males, 1 Asian gay male, 2 White bisexual females, 1 Black bisexual female, 1 Asian bisexual male, 1 White transgender female, 1 White transgender male and 1 White transgender non-binary individual). A further 6 participants stated that they did not identify as LGBTQ+ (3 White males and 3 White females). Participants were recruited in a purposive manner through social media sites such as Instagram and WhatsApp and comprised mainly of acquaintances of the researcher. A high proportion of LGBTQ+ participants were utilised in an effort to ensure intersectionality of responses, which has been shown to provide a strong methodological framework within which to investigate underrepresented groups (Rodriguez, 2018).\r\n\r\nDesign\r\nThe study consisted of two distinct elements; semi-structured interviews and a content analysis of existing global advertisements that feature LGBTQ+ characters from 2016-2020. Semi-structured interviews were the chosen method of qualitative data gathering, as the style allows for analysis according to the basis of grounded theory (Glaser & Strauss, 1967) and gives scope for probing questions to supplement the richness of answers given. The combination of quantitative (quantified content analysis) and qualitative research employed in the study through separate investigations was undertaken in attempt to provide a rigorous understanding of LGBTQ+ diversity in advertising and its effects upon observers. \r\n\r\nInterviews\t\r\nAll participants individually took part in an in-depth semi-structured interview with the researcher over Microsoft Teams. Due to the inductive nature of the exploration, no independent and dependent variables were implemented. The research broadly assessed the following measures across populations in the sample: the importance of character depictions, prosociality views, representation significance, brand attitudes, and purchasing likelihood succeeding exposure to three IKEA advertisements. The same brand was used for all ads in order to eliminate brand biases. The order in which advertisements were shown to participants was random in an effort to counterbalance order effects. Each interview lasted for approximately 45 minutes. \r\n\r\nAd Intersectionality\r\nThis additional component of the study involved conducting a content analysis of all global advertisements that feature LGBTQ+ identities from 2016-2020. This design mirrored that initially used by Nölke (2018), continuing their longitudinal analysis of intersectionality in LGBTQ+ advertising depictions which scoped the years 2009-2015. Identical to the original study, the source for these ads was AdRespect (http://adrespect.org), a website which comprehensively includes any advertisement featuring LGBTQ+ inclusion from around the world. The independent variable was time, as adverts which aired within each individual year were grouped together. Dependent measures included counts of different intersectionality measures, an approach first used by Gopaldas & DeRoy (2015) in their intersectional analysis of Gentlemen’s Quarterly covers, and were further investigated by Nölke (2018). In the present study these measures consisted of age, race and specific LGBTQ+ membership.\r\n\r\nMeasures\r\n\r\nInterviews\r\nThe semi-structured interview completed by each participant was devised entirely by the researcher and involved seven different sections which addressed questions surrounding the significance of character portrayals in advertising. The interview primarily consisted of open-ended questions, though some close-ended questions were also asked where definitive answers were required. Questions often had multiple sub-questions within them in order to probe more detailed responses from participants. In total the interview asked 31 unique questions, with nine of these questions repeated three times (in sections four, five and six).\r\nThe first section was an overview which told participants what the interview would entail whilst it also asked general ad watching questions to prime the interviewee for more detailed questions to follow. An example question from section one includes “would you say in general that you watch many ads?”. \r\nSection two was focused on the participant’s views towards representation in advertising, particularly focusing on LGBTQ+ representation and its significance to them. Example questions include: “if you are to view an advertisement that openly features LGBTQ+ identities, how would it make you feel?” and “do the character depictions in adverts matter to you? What characteristic(s) are most significant to you? Why is this?”.\r\nThe third section addressed identity formation, asking interviewees questions about advertising from when they were growing up in an attempt to investigate the impact of negligible LGBTQ+ depictions in the past. It asked questions including: “Do you ever remember seeing LGBTQ+ identities in advertising when you were younger? How did this make you feel?”. In addition to this, it attempted to gain an understanding of how characters in advertising impact the formation of identity from a retrospective viewpoint. \r\nThe subsequent three sections all asked the same set of questions to participants after showing them three different IKEA adverts in a random order (https://bit.ly/2VkBCQs), (https://bit.ly/3yHXouV) and (https://bit.ly/2WVyElD). All ads were published to mainstream audiences on television by IKEA within the past two years and were matched closely in terms of length. The first ad (Ads of Brands, 2020) titled ‘next generation’ featured only heteronormative White characters, within a nuclear family unit. It was selected as it acted as a non-representative example which showcased very little intersectionality and no LGBTQ+ identities. The second ad ‘change a bit for good’ (IKEA UK, 2021) displayed identity neutral robots who attempt to tackle climate change. This ad acted as a control for participants, as it still addresses a prosocial topic whilst portraying no identifying elements of its characters. The final ad ‘be someone’s home’ (IKEA USA, 2020) showed a wide variety of diversity across intersections within the LGBTQ+ community, which functioned as an inclusive example to interviewees.\r\nQuestions asked after exposure to each ad included items assessing the participant’s attitude towards the brand, their subsequent purchasing intentions and the believed importance of the identities portrayed. Example items include: “after watching this ad, would you feel more or less inclined to spend money with IKEA? Why is this?” and “do you believe the identities shown in the ad are important to others? Why do you think this?”.\r\nThe last component of the interview asked participants about their general spending behaviour, brand evaluation and concluding questions about how LGBTQ+ visibility in  advertising makes them feel. Sample items include: “would seeing an ad that positively depicts someone similar to you make you value the brand more? How come? Would this also make you more likely to buy?” and “is there anything that you would like to change in modern advertising? Less of something? More of something? Why?”.\r\n\r\nAd Intersectionality\r\nCoding Scheme. The present study followed the coding scheme of Nölke (2018), but chose to exclude class as a coding dimension, due to an absence of representation in this area. The coding dimensions analysed within the study were LGBTQ+ membership, age and race. Each portrayal was coded across all three dimensions.\r\nLGBTQ+ Membership. Items within this dimension were coded accordingly: ‘lesbian female’, ‘gay male’, ‘bisexual’, ‘trans-female’ (MtF) which included drag queens, ‘trans-male’ (FtM) and ‘gender neutral/non-binary’. Nölke (2018) did not code gender neutral or non-binary identities due to the absence of such portrayals. The current study implemented this additional measure as it saw the need to recognise the additional membership which is becoming increasingly prevalent in modern depictions. Transgender depictions were either explicitly labelled as such within the ad, overtly presented (for example, in terms of top-surgery scarring) or for celebrity depictions, publicly accessible data on their identity was used. Gender neutral/non-binary coded characters were either stated as such within the ad, their gender was indiscernible, or in celebrity cases, publicly available information on their identity was again utilised.\r\n\r\nAge. Based upon Gopaldas & DeRoy’s (2015) scheme, age was determined by estimations to the nearest multiple of five based upon observation. The following codes were used: “teen” (aged 13+), “young adult” (20+), “middle-aged” (35+) and “mature” (50+). \r\n\r\nRace. The race of characters was coded according to visual appearance, language and ad text. Codes included “White”, “Black”, “Asian” and “Latinx”. It is important to note that these terms differ from those used by Nölke (2018), in accordance to APA’s guidance on inclusive language regarding racial and ethnic identity (American Psychological Association, 2019).\r\n\r\nProcedure\r\nEthical approval for this study was acquired through the project supervisor and ethics partner at Lancaster University, as the proposed research was deemed low risk.\r\n\r\nInterviews\r\nParticipants were each given an electronic information sheet, consent form and short demographic questionnaire which included LGBTQ+ membership status questions to complete through Qualtrics (https://www.qualtrics.com). To ensure participants were comfortable, all questions in this form were optional to answer. After consent was obtained, participants were contacted to arrange a suitable interview date and time, which was conducted via Microsoft Teams. During each interview, the researcher asked questions according to the interview schedule in a semi-structured manner. These interviews were recorded and transcribed for analysis. Throughout the interviews, participants were reminded that they did not need to answer any questions that they did not want to and that they were free to leave at any point should they wish. Any identifying data was removed during transcription to maintain participant confidentiality. After interviews had finished, all participants were sent a debriefing form via email.\r\n\r\nAd Intersectionality\r\nAd Selection. Ads published between 2016-2020 on AdRespect were selected according to the same principles utilised by Nölke (2018). To begin, the 531 ads submitted to AdRespect during the years 2016-2020 were evaluated. AdRespect states the audience in which each ad was published to and those that were exclusively published to LGBTQ+ audiences were excluded from analysis. Additionally rejected from analysis were ads where the character’s LGBTQ+ status was not evident, ads that showed no explicit depiction of people and ads for non-profit organisations. This exclusion criteria left 284 ads. As AdRespect is a crowdsourced platform, a further search for ads that met the inclusion criteria was conducted across the internet in case any were left out by the online database. This search found a further two ads, producing a total of 286 ads within the final dataset. These ads were then coded according to the dimensions of age, race and LGBTQ+ membership. Ads were coded for every LGBTQ+ portrayal shown, thus often multiple characters were displayed within each ad and were analysed per individual depiction.\r\n\r\nAnalysis\r\n\r\nQualitative Analysis of Interviews\r\nAfter transcription, all interviews were analysed through inductive thematic analysis due to the exploratory nature of the research (Braun & Clarke, 2006). This process adhered to their six phases of analysis: familiarization of the data, initial code generation, theme search, theme review, defining and naming themes and report production, which allowed the researcher to identify the themes that underpin consumer responses and attitudes towards LGBTQ+ portrayals. This analysis was conducted through NVivo 12 qualitative data analysis software.\r\n \r\nQuantitative Analysis of ad Intersectionality \r\nQuantitative analyses of the dataset were conducted through collation of codes ascribed to portrayals across time. The depictions were summarised across intersectional and unidimensional measures according to which year they belonged to. This was analysed as a singular project as well as comparatively against the original findings from Nölke (2018), which allowed to researcher to demonstrate how portrayals of the LGBTQ+ community in advertising have transformed from 2009-2020. In addition to the researcher, a secondary coder was randomly assigned 25 ads from the dataset in order to test inter-rater reliability, which stood at 100% across all coding dimensions.\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2795"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2796"},["text","Data/Excel.csv\r\nText/Nvivo"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2797"},["text","Edgington2021"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2798"},["text","Laura Meek"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2799"},["text","Open (Unless stated otherwise) "]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2800"},["text","None (Unless stated otherwise)"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2801"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2802"},["text","Data"]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"2803"},["text","LA1 4YF"]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"2809"},["text","Leslie Hallam"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2810"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2811"},["text","Social, Marketing"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2812"},["text","The sample consisted of 19 participants aged; Mage = 23.5 years, SDage = 7.6. Of this sample, 13 participants stated that they identified as LGBTQ+ (2 White lesbian females, 1 Mixed-Race lesbian female, 2 White gay males, 1 Asian gay male, 2 White bisexual females, 1 Black bisexual female, 1 Asian bisexual male, 1 White transgender female, 1 White transgender male and 1 White transgender non-binary individual). A further 6 participants stated that they did not identify as LGBTQ+ (3 White males and 3 White females)."]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2813"},["text","Qualitative\r\nANOVA"]]]]]]]],["item",{"itemId":"134","public":"1","featured":"0"},["collection",{"collectionId":"10"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"819"},["text","Interviews"]]]]]]]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2814"},["text","Does Advertising Truly Represent the LGBTQ+ Community? An Analysis of Intersectionality and Consumer Responses to LGBTQ+ Advertising "]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2815"},["text","Layton Edgington"]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2816"},["text","September 2021"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2817"},["text","Depictions of sexual and gender minorities in advertising are becoming increasingly common and diverse. Yet, numerous intersections within these portrayals are still invisible. Previous research has found mixed results regarding consumer responses to LGBTQ+ identities in advertising. The current study aimed to obtain a further understanding into how a diverse range of consumers respond to heteronormative versus LGBTQ+ imagery in ads. This was assessed using semi-structured interviews to examine sexual and gender minority consumer (n = 13) and non-LGBTQ+ consumer (n = 6) reactions to three distinct IKEA ads. In addition to this, LGBTQ+ character depictions in 286 worldwide mainstream ads from 2016-2020 were analysed for measures of intersectionality across the dimensions of race, age and specific LGBTQ+ membership, extending the previous findings of Nölke (2018). Results indicated that non-LGBTQ+ participants showed similar responses and subsequent brand evaluation regardless of ad theme. Sexual and gender minority participants were found to show preference towards the ad featuring LGBTQ+ identities, though were often found to be sceptical of such portrayals. Intersectionality analysis uncovered that 47 out of a possible 96 intersections were completely invisible from 2016-2020, although representation of minorities within the community has increased substantially since the original findings. Results demonstrate the importance of character depictions in advertising, highlighting why intersectionality of such portrayals needs to increase in the future. Findings further denote how and why different consumers react to specific ad imagery, making recommendations to marketers regarding their inclusion of LGBTQ+ identities in advertising. "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2818"},["text","LGBTQ+ advertising, prosocial advertising, intersectionality, consumer attitudes"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2819"},["text","Participants\r\nThe sample consisted of 19 participants aged between 18-53 at their time of interview; Mage = 23.5 years, SDage = 7.6. Of this sample, 13 participants stated that they identified as LGBTQ+ (2 White lesbian females, 1 Mixed-Race lesbian female, 2 White gay males, 1 Asian gay male, 2 White bisexual females, 1 Black bisexual female, 1 Asian bisexual male, 1 White transgender female, 1 White transgender male and 1 White transgender non-binary individual). A further 6 participants stated that they did not identify as LGBTQ+ (3 White males and 3 White females). Participants were recruited in a purposive manner through social media sites such as Instagram and WhatsApp and comprised mainly of acquaintances of the researcher. A high proportion of LGBTQ+ participants were utilised in an effort to ensure intersectionality of responses, which has been shown to provide a strong methodological framework within which to investigate underrepresented groups (Rodriguez, 2018).\r\nDesign\r\nThe study consisted of two distinct elements; semi-structured interviews and a content analysis of existing global advertisements that feature LGBTQ+ characters from 2016-2020. Semi-structured interviews were the chosen method of qualitative data gathering, as the style allows for analysis according to the basis of grounded theory (Glaser & Strauss, 1967) and gives scope for probing questions to supplement the richness of answers given. The combination of quantitative (quantified content analysis) and qualitative research employed in the study through separate investigations was undertaken in attempt to provide a rigorous understanding of LGBTQ+ diversity in advertising and its effects upon observers. \r\nInterviews\t\r\nAll participants individually took part in an in-depth semi-structured interview with the researcher over Microsoft Teams. Due to the inductive nature of the exploration, no independent and dependent variables were implemented. The research broadly assessed the following measures across populations in the sample: the importance of character depictions, prosociality views, representation significance, brand attitudes, and purchasing likelihood succeeding exposure to three IKEA advertisements. The same brand was used for all ads in order to eliminate brand biases. The order in which advertisements were shown to participants was random in an effort to counterbalance order effects. Each interview lasted for approximately 45 minutes. \r\nAd Intersectionality\r\nThis additional component of the study involved conducting a content analysis of all global advertisements that feature LGBTQ+ identities from 2016-2020. This design mirrored that initially used by Nölke (2018), continuing their longitudinal analysis of intersectionality in LGBTQ+ advertising depictions which scoped the years 2009-2015. Identical to the original study, the source for these ads was AdRespect (http://adrespect.org), a website which comprehensively includes any advertisement featuring LGBTQ+ inclusion from around the world. The independent variable was time, as adverts which aired within each individual year were grouped together. Dependent measures included counts of different intersectionality measures, an approach first used by Gopaldas & DeRoy (2015) in their intersectional analysis of Gentlemen’s Quarterly covers, and were further investigated by Nölke (2018). In the present study these measures consisted of age, race and specific LGBTQ+ membership.\r\nMeasures\r\nInterviews\r\nThe semi-structured interview completed by each participant was devised entirely by the researcher and involved seven different sections which addressed questions surrounding the significance of character portrayals in advertising. The interview primarily consisted of open-ended questions, though some close-ended questions were also asked where definitive answers were required. Questions often had multiple sub-questions within them in order to probe more detailed responses from participants. In total the interview asked 31 unique questions, with nine of these questions repeated three times (in sections four, five and six).\r\nThe first section was an overview which told participants what the interview would entail whilst it also asked general ad watching questions to prime the interviewee for more detailed questions to follow. An example question from section one includes “would you say in general that you watch many ads?”. \r\nSection two was focused on the participant’s views towards representation in advertising, particularly focusing on LGBTQ+ representation and its significance to them. Example questions include: “if you are to view an advertisement that openly features LGBTQ+ identities, how would it make you feel?” and “do the character depictions in adverts matter to you? What characteristic(s) are most significant to you? Why is this?”.\r\nThe third section addressed identity formation, asking interviewees questions about advertising from when they were growing up in an attempt to investigate the impact of negligible LGBTQ+ depictions in the past. It asked questions including: “Do you ever remember seeing LGBTQ+ identities in advertising when you were younger? How did this make you feel?”. In addition to this, it attempted to gain an understanding of how characters in advertising impact the formation of identity from a retrospective viewpoint. \r\nThe subsequent three sections all asked the same set of questions to participants after showing them three different IKEA adverts in a random order (https://bit.ly/2VkBCQs), (https://bit.ly/3yHXouV) and (https://bit.ly/2WVyElD). All ads were published to mainstream audiences on television by IKEA within the past two years and were matched closely in terms of length. The first ad (Ads of Brands, 2020) titled ‘next generation’ featured only heteronormative White characters, within a nuclear family unit. It was selected as it acted as a non-representative example which showcased very little intersectionality and no LGBTQ+ identities. The second ad ‘change a bit for good’ (IKEA UK, 2021) displayed identity neutral robots who attempt to tackle climate change. This ad acted as a control for participants, as it still addresses a prosocial topic whilst portraying no identifying elements of its characters. The final ad ‘be someone’s home’ (IKEA USA, 2020) showed a wide variety of diversity across intersections within the LGBTQ+ community, which functioned as an inclusive example to interviewees.\r\nQuestions asked after exposure to each ad included items assessing the participant’s attitude towards the brand, their subsequent purchasing intentions and the believed importance of the identities portrayed. Example items include: “after watching this ad, would you feel more or less inclined to spend money with IKEA? Why is this?” and “do you believe the identities shown in the ad are important to others? Why do you think this?”.\r\nThe last component of the interview asked participants about their general spending behaviour, brand evaluation and concluding questions about how LGBTQ+ visibility in  advertising makes them feel. Sample items include: “would seeing an ad that positively depicts someone similar to you make you value the brand more? How come? Would this also make you more likely to buy?” and “is there anything that you would like to change in modern advertising? Less of something? More of something? Why?”.\r\nAd Intersectionality\r\nCoding Scheme. The present study followed the coding scheme of Nölke (2018), but chose to exclude class as a coding dimension, due to an absence of representation in this area. The coding dimensions analysed within the study were LGBTQ+ membership, age and race. Each portrayal was coded across all three dimensions.\r\nLGBTQ+ Membership. Items within this dimension were coded accordingly: ‘lesbian female’, ‘gay male’, ‘bisexual’, ‘trans-female’ (MtF) which included drag queens, ‘trans-male’ (FtM) and ‘gender neutral/non-binary’. Nölke (2018) did not code gender neutral or non-binary identities due to the absence of such portrayals. The current study implemented this additional measure as it saw the need to recognise the additional membership which is becoming increasingly prevalent in modern depictions. Transgender depictions were either explicitly labelled as such within the ad, overtly presented (for example, in terms of top-surgery scarring) or for celebrity depictions, publicly accessible data on their identity was used. Gender neutral/non-binary coded characters were either stated as such within the ad, their gender was indiscernible, or in celebrity cases, publicly available information on their identity was again utilised.\r\nAge. Based upon Gopaldas & DeRoy’s (2015) scheme, age was determined by estimations to the nearest multiple of five based upon observation. The following codes were used: “teen” (aged 13+), “young adult” (20+), “middle-aged” (35+) and “mature” (50+). \r\nRace. The race of characters was coded according to visual appearance, language and ad text. Codes included “White”, “Black”, “Asian” and “Latinx”. It is important to note that these terms differ from those used by Nölke (2018), in accordance to APA’s guidance on inclusive language regarding racial and ethnic identity (American Psychological Association, 2019).\r\nProcedure\r\nEthical approval for this study was acquired through the project supervisor and ethics partner at Lancaster University, as the proposed research was deemed low risk.\r\nInterviews\r\nParticipants were each given an electronic information sheet, consent form and short demographic questionnaire which included LGBTQ+ membership status questions to complete through Qualtrics (https://www.qualtrics.com). To ensure participants were comfortable, all questions in this form were optional to answer. After consent was obtained, participants were contacted to arrange a suitable interview date and time, which was conducted via Microsoft Teams. During each interview, the researcher asked questions according to the interview schedule in a semi-structured manner. These interviews were recorded and transcribed for analysis. Throughout the interviews, participants were reminded that they did not need to answer any questions that they did not want to and that they were free to leave at any point should they wish. Any identifying data was removed during transcription to maintain participant confidentiality. After interviews had finished, all participants were sent a debriefing form via email.\r\nAd Intersectionality\r\nAd Selection. Ads published between 2016-2020 on AdRespect were selected according to the same principles utilised by Nölke (2018). To begin, the 531 ads submitted to AdRespect during the years 2016-2020 were evaluated. AdRespect states the audience in which each ad was published to and those that were exclusively published to LGBTQ+ audiences were excluded from analysis. Additionally rejected from analysis were ads where the character’s LGBTQ+ status was not evident, ads that showed no explicit depiction of people and ads for non-profit organisations. This exclusion criteria left 284 ads. As AdRespect is a crowdsourced platform, a further search for ads that met the inclusion criteria was conducted across the internet in case any were left out by the online database. This search found a further two ads, producing a total of 286 ads within the final dataset. These ads were then coded according to the dimensions of age, race and LGBTQ+ membership. Ads were coded for every LGBTQ+ portrayal shown, thus often multiple characters were displayed within each ad and were analysed per individual depiction.\r\nAnalysis\r\nQualitative Analysis of Interviews\r\nAfter transcription, all interviews were analysed through inductive thematic analysis due to the exploratory nature of the research (Braun & Clarke, 2006). This process adhered to their six phases of analysis: familiarization of the data, initial code generation, theme search, theme review, defining and naming themes and report production, which allowed the researcher to identify the themes that underpin consumer responses and attitudes towards LGBTQ+ portrayals. This analysis was conducted through NVivo 12 qualitative data analysis software. \r\nQuantitative Analysis of ad Intersectionality \r\nQuantitative analyses of the dataset were conducted through collation of codes ascribed to portrayals across time. The depictions were summarised across intersectional and unidimensional measures according to which year they belonged to. This was analysed as a singular project as well as comparatively against the original findings from Nölke (2018), which allowed to researcher to demonstrate how portrayals of the LGBTQ+ community in advertising have transformed from 2009-2020. In addition to the researcher, a secondary coder was randomly assigned 25 ads from the dataset in order to test inter-rater reliability, which stood at 100% across all coding dimensions."]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2820"},["text","Lancaster University "]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2821"},["text","Data/Excel.csv\r\nText/Nvivo"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2822"},["text","Edgington2021"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2823"},["text","Yuxin Zhang"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2824"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2825"},["text","Qualitative analysis has no relation. Content analysis extends the work of Nölke (2018)"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2826"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2827"},["text","Data and Text"]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"2828"},["text","LA1 4YF"]]]]]]]],["item",{"itemId":"135","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"129"},["src","https://www.johnntowse.com/LUSTRE/files/original/d5d66fddce33099653308110f6ceed40.docx"],["authentication","a0c824eb4e49b092117cfb8fce8ce753"]]],["collection",{"collectionId":"5"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"185"},["text","Questionnaire-based study"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"186"},["text","An analysis of self-report data from the administration of questionnaires(s)"]]]]]]]],["itemType",{"itemTypeId":"14"},["name","Dataset"],["description","Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing."]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2829"},["text","Extending the Cortical Hyperexcitability Index"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2830"},["text","Haydn Farrelly"]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2831"},["text","27/05/2022"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2832"},["text","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."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2833"},["text","Perceptual Aberrations, Cortical Hyperexcitability, Migraine, Aura, Tinnitus, Auditory Perception, Visual Perception, Hallucinations"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2834"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2835"},["text","Data/Excel.csv"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2836"},["text","Farrelly2021"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2837"},["text","Haydn Farrelly"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2838"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2839"},["text","Braithwaite, Marchant, Takahashi, Dewe & Watson (2015)\r\nFong, Takahashi & Braithwaite (2019)"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2840"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2841"},["text","Data"]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"2842"},["text","LA1 4YF"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2848"},["text","Method \r\n\r\nParticipants \r\n\r\nForty-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%). \r\n\r\n \r\n\r\nAuditory Item Creation \r\n\r\nAs 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. \r\n\r\n \r\n\r\nAnalysis \r\n\r\nTotal 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. "]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"2843"},["text","Dr. Jason Braithwaite"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2844"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2845"},["text","Neuroscience"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2846"},["text","45"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2847"},["text","Factor Analysis"]]]]]]]],["item",{"itemId":"136","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"130"},["src","https://www.johnntowse.com/LUSTRE/files/original/d4dc1040e0bf719b8aac4376c7120bbf.pdf"],["authentication","85e88c85cf74d6343dfa510d9a909980"]]],["collection",{"collectionId":"5"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"185"},["text","Questionnaire-based study"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"186"},["text","An analysis of self-report data from the administration of questionnaires(s)"]]]]]]]],["itemType",{"itemTypeId":"14"},["name","Dataset"],["description","Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing."]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2849"},["text","Optimising the Use of Synaesthetic Metaphors in Advertising: The Roles of Metaphor Construction and Complexity"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2850"},["text","Emily Davenport"]]]],["element",{"elementId":"40"},["name","Date"],["description","A point or period of time associated with an event in the lifecycle of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2851"},["text","06/09/2021"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2852"},["text","Metaphors are commonly employed in advertising to increase its persuasive effects. Research suggests that metaphors are most effective when conveyed visually, however linguists believe that additionally providing a linguistic cue, designed to help metaphor interpretation, can increase their effectiveness. In addition, metaphors of medium complexity are believed to drive higher effectiveness than simpler or more complex metaphors. This research aims to investigate how these issues relate to synaesthetic metaphors, those that reference two sensory modalities. Participants were presented with print adverts, the visual and linguistic elements of which were adapted to contain literal messages or synaesthetic metaphors. Participants provided ratings of appreciation, purchase intentions, and perceived advert complexity. Synaesthetic metaphors were shown to produce significantly stronger persuasive effects, measured via appreciation and purchase intentions, when conveyed visually and when rated highly on complexity. Implications for advertisers, who wish to incorporate and optimise the use of synaesthetic metaphors in print advertising, are discussed. "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2853"},["text","Metaphors; Synaesthetic Metaphors; Advertising; Persuasiveness"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2854"},["text","Participants\r\nThis research recruited 122 participants via opportunistic sampling. Participants were native speakers of English aged 18 or over, with no history of disabilities in any of the sensory domains (sight, hearing, smell, taste and touch). Twelve participants were excluded due to incomplete survey responses and/or ineligibility according to the inclusion criteria, resulting in a sample of 110 participants (88 female, 20 male, 2 other; age: M = 38.11, SD = 18.60) who were randomly assigned to complete one of four surveys (see Design). The demographics per survey are detailed in Table 1. \r\n\r\n\r\nTable 1\r\nThe Sample Size and Demographics Per Survey\r\n\tN\tGender\tAge\r\n\t\tMale\tFemale\tOther\tMean\tSD\r\nSurvey 1\t28\t4\t24\t-\t43.68\t18.94\r\nSurvey 2\t29\t7\t21\t1\t32.90\t17.77\r\nSurvey 3\t28\t5\t22\t1\t35.07\t17.09\r\nSurvey 4\t25\t4\t21\t-\t41.32\t19.48\r\n\r\n\r\nMaterials \r\nAdvert Stimuli\r\nThe advert stimuli used in this research were gathered and modified by previous researchers at Francesca Citron’s laboratory (Chen, 2019; Pan, 2019). The researchers obtained real adverts containing synaesthetic metaphors from the dataset of Bolognesi and Strik Lievers (2018). These base adverts were labelled 1-8 (see Appendix A). The researchers produced three modified versions of each base advert. They edited the visual and linguistic elements, of product images and slogans respectively, to contain, or not contain, a synaesthetic metaphor,  in accordance with the ‘Metaphor Category’ they represented.\r\nOne version of each base advert conveyed a synaesthetic metaphor in both the visual and linguistic advert elements (Visual-Linguistic SM; labelled “VL”). One version contained a synaesthetic metaphor in the visual, but not linguistic, advert elements (Visual SM Only; labelled “V). One version contained a synaesthetic metaphor in the linguistic, but not visual, advert elements (Linguistic SM Only; labelled “L”). The final version served as a control as a synaesthetic metaphor did not appear in the visual or linguistic advert elements (No SM; labelled “N”). These metaphor categories are illustrated by the example of Advert 2 (see Figure 1). In 2VL, the image displays a lemon wearing a studded mask whilst the slogan writes “A PLEASINGLY SHARP TASTE”. This synaesthetic metaphor, conveyed by the image and slogan, attributes the lemonade as having a sharp taste, which references the sensory modalities of  touch (via “sharp” in the slogan, and the studded mask in the image) and taste (via “taste” in the slogan, and the lemon in the image). In 2V, the synaesthetic metaphor containing the image of 2VL is retained, however the slogan, “A PLEASINGLY SOUR TASTE”, no longer contains a synaesthetic metaphor since it a) is literal and b) only references one sense (via “sour taste”). In contrast, 2L retains the synaesthetic metaphor-containing slogan of 2VL (“A PLEASINGLY SHARP TASTE”) but contains a literal product image. The synaesthetic metaphor here therefore only appears in the linguistic advert elements. In 2N, the image of 2L and the slogan of 2V appear, meaning that a synaesthetic metaphor is not conveyed in either the visual or linguistic elements.\r\nThis process, of creating four versions per base advert, resulted in 32 advert stimuli. Within this, eight adverts, one per base advert, represented each metaphor category.  The advert stimuli were labelled according to their base advert number (1-8) and their metaphor category (VL; V; L; N). For example, 1VL presents the version of base advert 1 belonging to the visual-linguistic SM category. The full stimuli set can be viewed in Appendix A. The synaesthetic metaphors constructed in the stimuli, and the sensory domains referenced (see Table 2), are briefly explained in Appendix B. All adverts were written in English and printed in full colour.  \r\n\r\nOnline Survey\r\n\tThis research used a modified version of a Qualtrics (Provo, UT) survey produced by Chen (2019) and Pan (2019). The original survey featured 11 bipolar Likert scales per advert stimuli, all intended to contain 5-points but with some mistakenly containing 7-points. This was corrected in the present research, with all scales measured 0-5. The first four scales, measuring “Appreciation”, asked participants whether they liked the advert (Agree – Disagree) and whether they perceived it as “Bad”–“Good”; “Unpleasant”-“Pleasant”; and “Unappealing”-“Appealing”. The two following questions measured “Perceived Complexity” and concerned participants’ perception of the advert as “Unclear”–“Straightforward” and as “Difficult to Understand”– “Easy to Understand”. The next three questions measured “Purchase Intentions”. In the original survey, these focused on the purchase intentions of the respondent. This was modified in this research, following Pan (2019) and Chen’s (2019) finding that purchase intentions were merged with appreciation in PCA, and the belief that personal factors influence purchase intentions (Habich-Sobiegalla et al., 2019). The current survey instead asked respondents whether others would like to purchase the product, soon and in the future, and whether the advert would make others more likely to purchase the product (“Disagree”-“Agree”). On the final two questions, measuring “Perceived Realism”, participants rated the advert as “Unrealistic”–“Realistic” and “Fictitious”– “Real”. This question set was presented per advert stimulus, resulting in a total of 88 questions per survey.  \r\n\r\nFigure 1\r\nThe Four Versions of Advert 2\r\nTable 2\r\nThe Sensory Domains Referenced by Each Advert, When Sensory Metaphors Were and Were Not Present \r\n\tSensory Domains Referenced\r\n\tSM Present\tNo SM Present\r\n\tSource\tTarget\t\r\nAdvert 1\tAuditory\tTaste \tTaste\r\nAdvert 2\tTactile\tTaste \tTaste\r\nAdvert 3\tTactile\tTaste\tTaste\r\nAdvert 4\tVisual\tAuditory\tAuditory\r\nAdvert 5\tVisual\tAuditory\tAuditory\r\nAdvert 6\tVisual\tSmell\tSmell\r\nAdvert 7\tAuditory\tTaste\tTaste\r\nAdvert 8\tTactile\tTaste\tTaste\r\n\r\nDesign\r\nIn an independent groups design, participants were randomly assigned to complete one of four online surveys. The independent variable was the metaphor category of each advert. Each survey presented eight adverts, one belonging to each of the eight base adverts and two belonging to each of the four metaphor categories. For example, Survey 1 presented two Visual-SM only adverts (Adverts 1 and 5), two Linguistic-SM Only adverts (Adverts 2 and 6), two Visual-Linguistic SM adverts (Adverts 3 and 7), and two No-SM adverts (Adverts 4 and 8), with one version of each base advert appearing only once. Table 3 lists the advert stimuli presented per survey. The four dependent variables, of ‘Appreciation’, ‘Purchase Intentions’, ‘Perceived Realism’ and ‘Perceived Complexity’, are further detailed in Materials and Variable Construction.\r\n\r\n\r\n\r\n\r\n\r\n\r\nTable 3\r\nThe Adverts Displayed per Survey, In Order of Appearance\r\nSurvey 1\tSurvey 2\tSurvey 3\tSurvey 4\r\n1V\t3N\t5VL\t7L\r\n2L\t4V\t6N\t8VL\r\n3VL\t5L\t7V\t1N\r\n4N\t6VL\t8L\t2V\r\n5V\t7N\t1VL\t3L\r\n6L\t8V\t2N\t4VL\r\n7VL\t1L\t3V\t5N\r\n8N\t2VL\t4L\t6V\r\n\r\n\r\nProcedure\r\nThe entirety of this study was completed on Qualtrics (Provo, UT). Participants were informed of the researchers' background and requirements, and briefed of their anonymity, confidentiality and right to withdraw (Appendix C), before providing informed consent (Appendix D). Participants declared their age and gender and confirmed that English was their native language and that they did not suffer from any sensory inabilities. Participants viewed each of the eight adverts in turn and answered 11 five-point Bipolar Likert scales per advert (see Materials, Survey). Finally, participants were debriefed, reminded of their terms of participation, and provided with further reading (Appendix E). The study took 10 minutes to complete."]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2855"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2856"},["text","Data/Excel.xlsx"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2857"},["text","Davenport2021"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2858"},["text","Malcolm Wong"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2859"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2860"},["text","Follow up on previous research in Francesca Citron's lab"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2861"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2862"},["text","Data"]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"2863"},["text","LA1 4YF"]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"2864"},["text","Francesca Citron"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2865"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2866"},["text","Marketing"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2867"},["text","122, but 12 excluded so final sample of 110."]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2868"},["text","ANCOVA, ANOVA, Regression, and T-Test."]]]]]]]]]