["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://johnntowse.com/LUSTRE/items?output=omeka-json&page=3&sort_field=Dublin+Core%2CTitle","accessDate":"2026-05-22T23:50:28+00:00"},["miscellaneousContainer",["pagination",["pageNumber","3"],["perPage","10"],["totalResults","148"]]],["item",{"itemId":"169","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"173"},["src","https://johnntowse.com/LUSTRE/files/original/707a658c88746eaa6d6045229abd375f.pdf"],["authentication","6efc0d8f0255892001bb9445f96155e7"]],["file",{"fileId":"174"},["src","https://johnntowse.com/LUSTRE/files/original/eda9526471de877c350991c0c8730d08.pdf"],["authentication","af9dc5ca50327bbfad5bf04de9777f11"]],["file",{"fileId":"175"},["src","https://johnntowse.com/LUSTRE/files/original/b1a36360dbc1fcdc7c691b80bc389aa8.pdf"],["authentication","6efc0d8f0255892001bb9445f96155e7"]]],["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":"3428"},["text","An investigation of the influence of individual differences on susceptibility to product placement. "]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"3429"},["text","Ellen Dimeck"]]]],["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":"3430"},["text","2022"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3431"},["text","Product placement increased in popularity in 1982 when Reese’s Pieces Chocolate was included in E.T. the film, which led to a 65% increase in sales. Still to this day product placement is omnipresent within our cultural climate and research has supported that it enhances our purchase intentions. However, what remains unknown is how individual differences may influence product placement susceptibility. To address this gap, the current study investigated whether individual differences in cognitive capabilities, inhibitory control, age, familiarity, gender and timepoint enhance/reduce the likelihood of individuals' purchasing intentions being influenced by product placement. To do this, 55 participants (23 younger adults (Mage = 61.62(8.70)) and 22 older adults (Mage = 21.75(0.68)) were presented with images of four cups of coffee and asked to rank their purchase intentions/familiarity with the products. Following this, participants watched three scenes from Coronation Street, with the second clip including a product placement (Costa Coffee). Approximately 48 hours later, participants completed another purchase intentions questionnaire on the same four cups of coffee. The results highlighted that purchase intentions increased immediately post-clip; however they decreased 48 hours post-clip. Therefore, advertisers may use this information to discover ways in which the consumer can easily purchase the product immediately post-clip e.g. through QR codes. In regard to all other variables, no other significant relationships were found. Thus, it cannot be suggested to advertising agencies that product placement targeted to individuals who fulfil a given criteria (e.g. older adults, etc) will achieve optimal results when compared to non-targeted product placement."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3432"},["text","Product placement, individual differences, cognitive capabilities, inhibitory control, age, familiarity, gender, timepoint, purchase intentions"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"3433"},["text","Design \r\n\r\nThe present quantitative study adopted a repeated measures design. There were several predictor variables: overall cognitive capabilities (including executive functioning; as assessed by the ACE-III; Hsieh et al., 2013), inhibitory control (as assessed by the Stroop effect), age, familiarity, gender, and timepoint. The dependent variable was susceptibility to product placement as measured by change in purchase intention.\r\n\r\nParticipants\r\n\r\nAt the time of the current studies design no published studies had investigated the influence of individual differences on product placement susceptibility, therefore the required sample size was modelled on the most comparable study the authors could source. Specifically, Hoek et al. (2022) investigated the influence of inhibitory control on advertising literacy activation and advertising susceptibility. Hoek et al. (2022) recruited 57 participants. Given the time restraints of data collection, the authors elected to recruit 55 participants.\r\n\r\nA total of 55 participants volunteered to participate in part one of the study. All participants were recruited via opportunity sampling through word of mouth and through advertisements placed on various Lancaster University Facebook pages (e.g. the Perception and Action Lab group).\r\n\r\nParticipants were either aged between 18-25 (younger adults) or aged 50 and over (older adults). Out of the 55 participants, there were 27 younger adults (19 women; Mage = 60.93; SDage = 8.26) and 28 older adults (18 women; Mage = 21.78; SDage = 0.85). \r\n\r\nNo participant had a known diagnosis of a psychiatric, neurological, or visual impairment, thus psychiatric, neurological, and visual impairments were not included in the analysis. All participants were White British/Irish. Therefore, there was no variation between ethnicities, thus ethnicity was not included in the analysis either. \r\n\r\nGiven that cognitive capabilities was a key predictor variable within this study, it was necessary to ensure that participants with a known cognitive impairment or probable indication of cognitive impairment were removed from the study. Subsequently, all participants were screened for the probable presence of mild cognitive impairment through the Addenbrookes Cognitive Examination (ACE-III; Hsieh et al., 2013). After applying the pre-validated cut off point, 10 participants were excluded. Therefore, 45 participants were included in the analysis.\r\n\r\nParticipants were either aged between 18-25 (younger adults) or aged 50 and over (older adults). Out of the 45 participants, there were 23 younger adults (16 women; Mage = 61.62; SDage = 8.70) and 22 older adults (17 women; Mage = 21.75; SDage = 0.68).\r\n \r\nMaterials \r\n\r\nInhibitory Control\r\n\r\nInhibitory control was measured through an online Stroop task developed and run through Psytoolkit (Stoet, 2010, 2017). Completion of this task required participants to ignore the meaning of the colour word and indicate the print colour. Participants were generally presented with a colour word and a print word that were incongruent to one another. Thus, participants needed to use their ability to inhibit a pertinent response (i.e. the print colour) and indicate the print colour, which would be done more efficiently by competent readers (von Hippel & Gonsalkorale, 2005). Previous scholars have chosen to use the Stroop task, as it offers a good measure of individual variation in inhibition (e.g., Long & Prat, 2002). \r\n\r\nAs this study was conducted remotely, via Microsoft Teams share screen function, participants were asked to verbally indicate the print colour and the researcher pressed the related keys (e.g. r for red, g for green, b for blue, and y for yellow). Participants first completed four practice trials followed by 40 test trials.\r\n\r\nCognitive Functioning \r\n\r\nCognitive capabilities were measured using an adaptation of the Addenbrooke’s Cognitive Examination (ACE-III; Hsieh et al., 2013). The original version assesses the participants’ attention, memory, fluency, language, and visuospatial abilities and has a combined score of 100. Although the adapted version examines the same five cognitive domains, it has a combined score of 77, the reason being that some questions were removed, as they were not deemed suitable for an online study – the first two questions on attention, the first two questions on language, and the first three questions on visuospatial abilities. The original version's pre-validated cut off point was 88 (88%) and therefore the adapted version's was 68 (88.31%). The participants who scored below the pre-validated cut off point were removed prior to analysis to ensure that the presence of cognitive impairment would not confound the subsequent analysis.\r\n\r\nDemographic and Health Characteristics \r\n\r\nDemographic information, including age, ethnicity, and gender, and background health information, including whether the participant had a current or history of a diagnosis of any cognitive, neurological, visual, or psychiatric impairments, was collected through an online Qualtrics Questionnaire. \r\n\r\nPurchase Intentions Questionnaire\r\n\r\nPrior to the questionnaire, participants were presented with the name and an image of each of the four cups of coffee. Purchase intentions of the four cups of coffee were then measured using a 7-point Likert scale. Participants were asked to rate on a scale of 1-7, 1 being ‘Extremely unlikely’ to 7 being ‘Extremely likely’, how likely they were to purchase a cup of coffee from: Caffè Nero, Costa Coffee, Greggs, and Starbucks. \r\n\r\nComparably, familiarity was also measured using a 7-point Likert scale. Participants were asked to rate on a scale of 1-7, 1 being ‘Extremely unfamiliar’ to 7 being ‘Extremely familiar’ with how familiar they were with each cup of coffee from Caffè Nero, Costa Coffee, Greggs, and Starbucks.\r\n\r\nPurchase intentions and familiarity were measured using a 7-point Likert scale, rather than the commonly used 5-point Likert scale, as the inclusion of several options enhances the likelihood of acquiring a more accurate response (Joshi et al., 2015). \r\n\r\nIt was important that purchase intention and familiarity of Costa Coffee was assessed alongside alternative brands, so that it was not made apparent that the study was focusing upon the participants' purchase intention ranking of Costa Coffee only. Therefore, Caffè Nero, Greggs, and Starbucks were chosen alongside Costa Coffee, because according to a survey conducted by Lock (2022), they are the UK’s top four leading coffee shop chains. The images were provided by Adobe Stock (2019) and Dreams Time (2019a, 2019b, 2019c).\r\n\r\nProduct Placement Video\r\n\r\nThe British TV Soap Coronation Street was selected, as prior research (e.g. Armstrong, 2018) suggests that it is popular amongst both younger and older adults (YouGov, 2011). The first clip chosen was a scene from 8th January 2018 Part 1, lasting 1 minute 16 seconds. The second clip chosen was a scene from 29th January 2018 Part 1, lasting 1 minute 15 seconds. The third clip chosen was a scene from 7th February 2018 Part 2, lasting 1 minute 23 seconds. It was the second scene shown that included the product placement (Costa Coffee). The researcher screen recorded each clip from https://www.dailymotion.com/gb and saved them into an encrypted file on a password-protected computer.\r\n\r\nProcedure\r\n\r\nA member of the psychology department research ethics committee approved the study before it was undertaken. Participants were invited to attend a 40–50-minute online Microsoft Teams meeting on a set date and time agreed on by the participant and the researcher. To commence, the researcher shared their screen and aided the participant in reading the participant information sheet and consent form via an online Qualtrics Questionnaire. At this time, participants were informed of their right to withdraw up to 2 weeks after participating without giving any reason and they were told their personal information would remain confidential and would be stored in encrypted files (that only myself and my supervisor have access to) on password-protected computers. The participants were only able to progress into the study on attainment of verbal consent. \r\n\r\nParticipants were then asked to disclose various demographic characteristics (e.g., age and gender) and details relating to their current health status (e.g., any cognitive or visual impairments). The participants were then presented with four images of cups of coffee from Caffè Nero, Costa Coffee, Greggs, and Starbucks. They were then asked to rank their purchase intentions and familiarity, on a seven-point Likert scale, with these products via an online Qualtrics Questionnaire. Following this, participants were asked to watch three short scenes from Coronation Street. The second clip shown included a product placement of Costa Coffee. The researcher then implemented an online Stroop task using Psytoolkit (Stoet, 2010, 2017). The participants were also screened for the presence of mild cognitive impairments through the ACE. After this, the participants were presented with the same four images and asked to rank their purchase intentions of these products via the online Qualtrics Questionnaire (see Figure 1).  \r\n\r\nApproximately 48 hours after completing the first part of the study, participants were sent an email invitation to complete another online Qualtrics Questionnaire. Participants were first asked to provide their participation number, which could be found in the email. They were then shown the same four images of cups of coffee and asked to rank their purchase intentions. Finally, the participants were provided with a debrief form at the end of the online Qualtrics Questionnaire (see Figure 2). This debrief disclosed the small degree of deception involved. Specifically, it was explained that participants were not informed at the start that the study considered product placement, as this might have influenced the subsequent data. Participants were reminded that they had the right to withdraw up to 2 weeks after participating and were provided with contact details in case they had any questions. \r\n\r\nThe participants' purchase intentions of the four cups of coffee were measured three times throughout the course of the two studies: pre-clip, immediately post-clip, and 48 hours post-clip. This was to see whether the participants' purchase intentions for the four cups of coffee, specifically Costa Coffee, had increased or decreased following the product placement clip and whether their ranking would withstand the test of time (48 hours post-clip). This is why the participant were asked to include their participant number in part two, so that the participants prolonged purchase intention (48 hours post-clip) could be traced back to their earlier purchase intention rankings (pre-clip and immediately post-clip).\r\n\r\nFigure 1. \r\n\r\nA flowchart of part one tasks. \r\n\r\nFigure 2. \r\n\r\nA flowchart of part two tasks. \r\n\r\nData Processing \r\n\r\nInhibitory Control\r\n\r\nParticipants raw Stroop data were downloaded from Psytoolkit into a Microsoft Excel file and saved in an encrypted files on a password-protected computer. From this raw data Stroop effect (the average incompatible conditions response time (ms) - compatible conditions response time (ms)) and percentage error rate (which involved adding the total of incorrect and timed out responses and dividing it by 40 (number of trials)) were calculated. Stroop effect and percentage error rate were used as an indicator of the participants inhibitory control capabilities. Specifically, a high Stroop effect would suggest less difficulty in inhibiting interference and a higher error rate would suggest reduced inhibitory capabilities.  \r\n\r\nCognitive Functioning \r\n\r\nThe scores of the ACE-III were added and entered into the Microsoft Excel file, which was saved in an encrypted files on a password-protected computer. A higher score was indicative of superior cognitive functioning. \r\n\r\nDemographic and Health Characteristics \r\n\r\nTo ensure all demographic and health data was readable by R-Studio all variables were dummy coded using numerical values. So, for instance, to determine the participants' gender, they were asked ‘What gender do you identify’ and given the option to choose from one of several responses. Each response was allocated a number, for example, 1 = Man, 2 = Woman, etc, and this was entered into the Microsoft Excel document.\r\n\r\nSusceptibility to product Placement (change in Purchase Intentions)\r\n\r\nTo investigate the susceptibility to product placement, two difference in purchasing behaviour score were calculated (one for short duration, one for prolonged duration). To calculate these values, the likelihood of purchasing the product value prior to watching the clip was subtracted from likelihood of purchasing the product value after watching the clip (either immediately post-clip or 48 hours after). A positive difference meant that purchase intentions had increased following placement clip. A negative difference meant that purchase intentions had decreased following placement clip. A difference of zero meant that the placement clip had failed to alter purchase intentions\r\n\r\nFamiliarity\r\n \r\nThe familiarity ratings of Costa Coffee were entered into the Microsoft Excel file, which was saved in an encrypted files on a password-protected computer. The higher the score, the more familiar the participant was with the product. \r\n\r\nData Analysis \r\n\r\nTo analyse the data, a linear mixed effects model was chosen. The reason being that the current study employs a repeated measures design, and a linear mixed effects model permits an analysis of hierarchically structured data (Baayen et al., 2008). \r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"3434"},["text","Lancaster University "]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3435"},["text","Data/RStudio.csv"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"3436"},["text","Dimeck2022"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3437"},["text","Alex Myroshnychenko"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"3438"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"3439"},["text","N/A"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3440"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3441"},["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":"3442"},["text","LA1 4YF\r\n"]]]]]],["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":"3443"},["text","Megan Readman"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"3444"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"3445"},["text","Marketing, Cognitive, Capabilities "]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"3446"},["text","55 participants (18 male and 37 females) "]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"3447"},["text","Linear Mixed Effects Modelling "]]]]]]]],["item",{"itemId":"35","public":"1","featured":"1"},["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":"1099"},["text","Analogical transfer beyond the analog"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"1100"},["text","Radhika Kuppanda"]]]],["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":"1101"},["text","2013"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1102"},["text","Analogical problem solving involves transferring the method used to solve the base analog onto the target analog based on the structural similarity they share. Studies have found that Experts have no difficulty in solving domain specific analogical problems. While, novice problem solvers fail to solve such problems due to their difficulty in retrieving the base analog. Failure to recollect the correct base analog forces the problem solver to solve the problem in an act first think later manner.  They use number of maximizing moves within the problem space to reach the goal state quickly. Use of such maximizing moves in solving analogical problems leads to an impasse, while alternative moves must be sought out. The current study tries to overcome the problem of retrieval of the correct base analog, by implementing an additional factor termed as extra constraint in solving analogical problem. These extra constraint acts in a manner which inhibit the problem solver from choosing problem moves that aim to maximizing their progress to reach the goal state which must essentially be avoided in analogical problem solving tasks. A secondary aim focuses on examining if there exists’ any difference between an adolescent problem solver and adult problem solver. Method: A total of 64 Participants within the age group of, 12-15 and 18-21 years were administered three problems (2 analogical and 1 non analogical). Results: Results demonstrate that the predictor variables (age or money) were not able to predict that participants from the older age category would perform better than the younger age group on any of the problems. Based on second aim, results showed that the older age group able to solve more problems successfully than the younger age group."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1103"},["text","analogical transfer\r\ninsight problem solving\r\nextra constraints \r\ndevelopmental differences\r\nmaximization of progress"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"1104"},["text","The test materials consisted of paper and pencil tasks (see appended booklet). Each Participant was provided with a booklet which consisted of a set of 5 problems, comprising three experimental tasks and two filler tasks.  The first problem was the analogical source problem (sheep dog problem), followed by a filler task (anagram solution). The second problem was the transfer problem (9 ball problem), followed by a second filler task (algebra solution). The last problem was the non-analog problem (cheap necklace problem). There was space provided under each of the problems to allow the participant to work out the solution to each problem. Solutions to each of the problems were also given for the participants. \r\n\r\n\r\nDesign and Procedure\r\n\r\nThe study design comprised of a two between-subjects factors. The first factor is Age (12-15; 18-21 years).  The second factor is Resource (£8 vs. £12). The dependent variable was the number of correct solutions. The aim of the research was to assess whether to two predictor variables, age and money would predict whether the participant would solve the problem correctly or incorrectly. \r\n\r\nAs per the BPS rules, confidentiality and anonymity of participants were strictly maintained. The study was conducted in a classroom setting with 16 participants being administered the problems at a time. Each participant from each age group was first assigned to low or high resource conditions. 50 % of the participants from older and younger age group received low resource condition (8 pounds) and other 50% high resource condition (12 pounds). Participants received the booklet containing the 3 problems and 2 filler tasks. Each participant was given 5 minutes to attempt each problem.  After five minutes, the solution to each problem is shown. The problems contained in the booklet are as follows:\r\n¥\tSource problem (killer dog)\r\n¥\tFiller task(anagrams)\r\n¥\tTransfer problem (ball problem- £8 or £12 versions); \r\n¥\tFiller task(algebra)\r\n¥\tNon-analogical problem (cheap necklace)."]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"1105"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1106"},["text","data/SPSS.sav"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"1107"},["text","Kuppanda2013"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"1108"},["text","John Towse"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"1109"},["text","Open"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1110"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1111"},["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":"1112"},["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":"1113"},["text","Tom Ormerord"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"1114"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"1115"},["text","Cognitive Psychology"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"1116"},["text","The study was conducted on a total of 64 participants divided into-\r\nAdolescents (12-15 years) - comprised of 32 participants recruited from schools.\r\nAdult age group (18-21 years) - comprised of 32 participants recruited from colleges. "]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"1117"},["text","logistic regression"]]]]]]]],["item",{"itemId":"160","public":"1","featured":"0"},["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":"3260"},["text","Assessing comprehension of health-related texts in non-native and native English speakers"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"3261"},["text","Khushboo Anup Agarwal"]]]],["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":"3262"},["text"," 13/09/2022"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3263"},["text","Background — Health written materials are more often complex to comprehend if they mismatch the reading ability of people in the target audience. We need to consider how to make text accessible, by considering individual differences that affect comprehension of written health materials. Surprisingly, there are very few studies that indicate how non-native English speakers and native English speakers differ in comprehension of written health texts. Methods — A total of 557 participants were studied in the present study. In the study, participants were asked to respond to multiple-choice questions that were designed to examine understanding of 25 health texts with different text properties. Each participant responded to tests measuring individual differences in demographics, reading strategy, vocabulary, and health literacy.  Findings —   Using mixed effects logistic regression analysis, we found that non-native English speakers and native English speakers have different accuracy of responses for written health texts. Effects of vocabulary skills and text readability were significant. These effects were different for different language groups. Native speakers of English with higher scores on vocabulary were more likely to make correct responses to written health texts. Native speakers of English were more likely to make correct responses to written health texts as text readability increased. Conclusion — In future, experimental studies should look at the effects of training to improve vocabulary on reading comprehension for different language groups. Alongside consider sources of variances due to individual differences and text properties for different language groups."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3264"},["text","reading comprehension, health literacy, individual differences, language groups."]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"3265"},["text","Design\r\nWe conducted experimental research on factors that influence the response to written health information, aiming to answer the research question:\r\nRQ.1 How does the reader’s attributes such as age, vocabulary skills, health literacy, reading strategy skills, along with text features, interact to predict the comprehension of health information in written texts for native language English speaker and non-native English speaker?\r\n\r\nWe conducted the study to test the hypotheses:\r\n1. Comprehension will be better for people with higher scores on reading skill, vocabulary and health literacy. Comprehension will be lower as age increases. \r\n2. Comprehension will be better for responses to texts which are higher on measures of readability, cohesion, word frequency, referential cohesion, and passive sentences.\r\n3. There will be differences between native and non-native speakers. Comprehension will be better for native speakers. The effect of age, reading strategy, vocabulary skills, and health literacy will be different for different language groups. The effect of cohesion, readability, word frequency, referential cohesion, and passive sentences will be different for different language groups.\r\n\r\nEthical approval. The data collection plan and study design were reviewed and approved by a member of the Psychology Department Research Ethics Committee. \r\nPre-registration. The study has not been pre-registered.  \r\n\r\nParticipants\r\n\tParticipants were recruited using primarily opportunity and snowball sampling. Participants were invited using social media such as Facebook, Instagram, and WhatsApp. We aimed at recruiting Bilingual/Multilingual Indian Residents (18+) who have access to the internet. We collected 201 responses, but only 112 participants were included in our analysis due to incomplete forms by other respondents. Our criterion for including participant data in analyses was that they had to complete 80 percent or more of the survey. We had 112 responses, but we did not test any of the respondents who were aged 100. We had three respondents who were aged 100 removed from our data set, leaving us with 109 observations. To enable a comparison between native and non-native speakers of English, we combined the data on responses from Indian and Chinese non-native speakers with data on responses from native speakers of English collected previously by supervisor Rob Davies. Thus, we had a large sample size of 557 participants for analysis. We did our final analysis on 557 participants with minimum age of 18 and maximum age of 81. Average age range in sample was 28, skewing towards younger population. The sample consisted of 392 females, 160 males, 1 non-binary, and 4 prefer not to say. There were 273 participants who spoke English as their first language and 284 participants who spoke English as their second language. \r\n\tAll participants were debriefed, and steps were taken to ensure confidentiality and anonymity. \r\n\r\nMaterials\r\n\tWe collected information on attributes of participants and linguistic properties of texts to see its influences on accuracy of responses made by participants to questions related health information. To measure participants attributes, we assessed demographic details, and participant’s vocabulary knowledge, health literacy, and reading strategy. Health texts differed in their linguistic properties, as measured by word frequency, readability (Flesch score and grade level), number of passive voice sentences, cohesion, and referential cohesion (Coh-Metrix).\r\nVocabulary knowledge.\r\n\tThe Shipley Vocabulary Test (Shipley et al., 2009) was used to test participants' vocabulary knowledge as it predicts 39-45% of variance in reading comprehension (Landi, 2010). The test includes questions in a multi choice question format, with incorrect and correct answers. Each question contains a word followed by four options—one of which is the correct meaning of the word. The higher the points, the higher the level of vocabulary. \r\nHealth Literacy. \r\nThe Health Literacy Vocabulary Assessment (HLVA) developed by Ratajczak (2020), adapted for online presentation by Chadwick (2020) was used to test participants’ health literacy. The adapted version of the HLVA contains 16 multiple-choice word items. The test consists of multiple-choice questions with incorrect and correct answers. Each question contains a word followed by four options. The participant must select the correct meaning of that word. High scores on HLVA indicate high health literacy vocabulary. \r\nReading strategy.\r\nTo determine participants’ motivation for reading and understanding reading strategies, we used Calloway’s (2019) third sub-test: Desire for Understanding and Reading Regulation Strategies. The items have been developed to measure the extent to which readers are willing to expend cognitive effort to understand a written text (Van den Broek et al., 2001). A higher score on this measure predicts better comprehension (Calloway, 2019). \r\nDemographics.\r\nWe collected participants’ demographic characteristics: gender (coded: Male, Female, non-binary, prefer not to say); education (coded: Secondary, Further, Higher); and ethnicity (coded: White, Black, Asian, Mixed, Other); age; native language.\r\nHealth information stimulus text sampling.\r\nComprehension passages are selected based on previous research paper by Davies and colleagues (in prep.) In total there are 25 comprehension passages. However, reading 25 passages in one sitting could lead to fatigue in the reader. Therefore, we created 5 sets of 5 comprehension passages. Each set contained 5 passages, which were randomly given to participants. The comprehension passages were then followed by questions in a multiple-choice question format. The response to each question is either right or wrong, which indicates whether the reader understands the passage. The questions have been constructed in ways to ensure that questions probed for the most important information in each text, such as who the information was relevant to, who was involved in diagnostic or treatment procedures, and the risks and benefits of different options. The questions were constructed in a manner that could not be answered by matching or referring to the text but required text-level and interpretation-level comprehension processing to correctly choose answer options (Kintsch, 1994).\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"3266"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3267"},["text","Excel spreadsheets - .csv \r\nR Script - .r\r\n"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"3268"},["text","Agarwal2022"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3269"},["text","Huzaifah Adam, Coco, Alex Myroshnychenko"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"3270"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"3271"},["text","This work is based on Kintsch, W. (1994). Text Comprehension, Memory, and Learning. American Psychologist, 10.\r\nWhite, S., Happé, F.M., Hill, E., & Frith, U. (2009). Revisiting the Strange Stories: Revealing \r\nMcNamara, D., & Magliano, J. (2009). Chapter 9 Toward a Comprehensive Model of Comprehension. Psychology of Learning and Motivation, 51, 297–384. https://doi.org/10.1016/S0079-7421(09)51009-2 \r\nO’reilly, T., & Mcnamara, D. S. (2007). Reversing the Reverse Cohesion Effect: Good Texts Can Be Better for Strategic, High-Knowledge Readers. Discourse Processes, 43(2), 121–152. https://doi.org/10.1080/01638530709336895\r\n"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3272"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3273"},["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":"3274"},["text","Developmental, Other"]]]]]]]],["item",{"itemId":"171","public":"1","featured":"0"},["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":"3463"},["text","Assessing comprehension of health-related texts in non-native and native English speakers "]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"3464"},["text","Khushboo Anup Agarwal"]]]],["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":"3465"},["text","2022"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3466"},["text","Background — Health written materials are more often complex to comprehend if they mismatch the reading ability of people in the target audience. We need to consider how to make text accessible, by considering individual differences that affect comprehension of written health materials. Surprisingly, there are very few studies that indicate how non-native English speakers and native English speakers differ in comprehension of written health texts. Methods — A total of 557 participants were studied in the present study. In the study, participants were asked to respond to multiple-choice questions that were designed to examine understanding of 25 health texts with different text properties. Each participant responded to tests measuring individual differences in demographics, reading strategy, vocabulary, and health literacy.  Findings —   Using mixed effects logistic regression analysis, we found that non-native English speakers and native English speakers have different accuracy of responses for written health texts. Effects of vocabulary skills and text readability were significant. These effects were different for different language groups. Native speakers of English with higher scores on vocabulary were more likely to make correct responses to written health texts. Native speakers of English were more likely to make correct responses to written health texts as text readability increased. Conclusion — In future, experimental studies should look at the effects of training to improve vocabulary on reading comprehension for different language groups. Alongside consider sources of variances due to individual differences and text properties for different language groups. "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3467"},["text","reading comprehension, health literacy, individual differences, language groups"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"3468"},["text","Design\r\nWe conducted experimental research on factors that influence the response to written health information, aiming to answer the research question:\r\nRQ.1 How does the reader’s attributes such as age, vocabulary skills, health literacy, reading strategy skills, along with text features, interact to predict the comprehension of health information in written texts for native language English speaker and non-native English speaker?\r\n\r\nWe conducted the study to test the hypotheses:\r\n1. Comprehension will be better for people with higher scores on reading skill, vocabulary and health literacy. Comprehension will be lower as age increases. \r\n2. Comprehension will be better for responses to texts which are higher on measures of readability, cohesion, word frequency, referential cohesion, and passive sentences.\r\n3. There will be differences between native and non-native speakers. Comprehension will be better for native speakers. The effect of age, reading strategy, vocabulary skills, and health literacy will be different for different language groups. The effect of cohesion, readability, word frequency, referential cohesion, and passive sentences will be different for different language groups.\r\n\r\nEthical approval. The data collection plan and study design were reviewed and approved by a member of the Psychology Department Research Ethics Committee. \r\nPre-registration. The study has not been pre-registered.  \r\n\r\nParticipants\r\n\tParticipants were recruited using primarily opportunity and snowball sampling. Participants were invited using social media such as Facebook, Instagram, and WhatsApp. We aimed at recruiting Bilingual/Multilingual Indian Residents (18+) who have access to the internet. We collected 201 responses, but only 112 participants were included in our analysis due to incomplete forms by other respondents. Our criterion for including participant data in analyses was that they had to complete 80 percent or more of the survey. We had 112 responses, but we did not test any of the respondents who were aged 100. We had three respondents who were aged 100 removed from our data set, leaving us with 109 observations. To enable a comparison between native and non-native speakers of English, we combined the data on responses from Indian and Chinese non-native speakers with data on responses from native speakers of English collected previously by supervisor Rob Davies. Thus, we had a large sample size of 557 participants for analysis. We did our final analysis on 557 participants with minimum age of 18 and maximum age of 81. Average age range in sample was 28, skewing towards younger population. The sample consisted of 392 females, 160 males, 1 non-binary, and 4 prefer not to say. There were 273 participants who spoke English as their first language and 284 participants who spoke English as their second language. \r\n\tAll participants were debriefed, and steps were taken to ensure confidentiality and anonymity. \r\n\r\nMaterials\r\n\tWe collected information on attributes of participants and linguistic properties of texts to see its influences on accuracy of responses made by participants to questions related health information. To measure participants attributes, we assessed demographic details, and participant’s vocabulary knowledge, health literacy, and reading strategy. Health texts differed in their linguistic properties, as measured by word frequency, readability (Flesch score and grade level), number of passive voice sentences, cohesion, and referential cohesion (Coh-Metrix).\r\nVocabulary knowledge.\r\n\tThe Shipley Vocabulary Test (Shipley et al., 2009) was used to test participants' vocabulary knowledge as it predicts 39-45% of variance in reading comprehension (Landi, 2010). The test includes questions in a multi choice question format, with incorrect and correct answers. Each question contains a word followed by four options—one of which is the correct meaning of the word. The higher the points, the higher the level of vocabulary. \r\nHealth Literacy. \r\nThe Health Literacy Vocabulary Assessment (HLVA) developed by Ratajczak (2020), adapted for online presentation by Chadwick (2020) was used to test participants’ health literacy. The adapted version of the HLVA contains 16 multiple-choice word items. The test consists of multiple-choice questions with incorrect and correct answers. Each question contains a word followed by four options. The participant must select the correct meaning of that word. High scores on HLVA indicate high health literacy vocabulary. \r\nReading strategy.\r\nTo determine participants’ motivation for reading and understanding reading strategies, we used Calloway’s (2019) third sub-test: Desire for Understanding and Reading Regulation Strategies. The items have been developed to measure the extent to which readers are willing to expend cognitive effort to understand a written text (Van den Broek et al., 2001). A higher score on this measure predicts better comprehension (Calloway, 2019). \r\nDemographics.\r\nWe collected participants’ demographic characteristics: gender (coded: Male, Female, non-binary, prefer not to say); education (coded: Secondary, Further, Higher); and ethnicity (coded: White, Black, Asian, Mixed, Other); age; native language.\r\nHealth information stimulus text sampling.\r\nComprehension passages are selected based on previous research paper by Davies and colleagues (in prep.) In total there are 25 comprehension passages. However, reading 25 passages in one sitting could lead to fatigue in the reader. Therefore, we created 5 sets of 5 comprehension passages. Each set contained 5 passages, which were randomly given to participants. The comprehension passages were then followed by questions in a multiple-choice question format. The response to each question is either right or wrong, which indicates whether the reader understands the passage. The questions have been constructed in ways to ensure that questions probed for the most important information in each text, such as who the information was relevant to, who was involved in diagnostic or treatment procedures, and the risks and benefits of different options. The questions were constructed in a manner that could not be answered by matching or referring to the text but required text-level and interpretation-level comprehension processing to correctly choose answer options (Kintsch, 1994).\r\n\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"3469"},["text","Lancaster University "]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3470"},["text","Excel spreadsheets - .csv \r\nR Script - .r\r\n"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"3471"},["text","Agarwal2022"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3472"},["text","Ashlynn Mayo"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"3473"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"3474"},["text","This work is based on Kintsch, W. (1994). Text Comprehension, Memory, and Learning. American Psychologist, 10.\r\nWhite, S., Happé, F.M., Hill, E., & Frith, U. (2009). Revisiting the Strange Stories: Revealing \r\nMcNamara, D., & Magliano, J. (2009). Chapter 9 Toward a Comprehensive Model of Comprehension. Psychology of Learning and Motivation, 51, 297–384. https://doi.org/10.1016/S0079-7421(09)51009-2 \r\nO’reilly, T., & Mcnamara, D. S. (2007). Reversing the Reverse Cohesion Effect: Good Texts Can Be Better for Strategic, High-Knowledge Readers. Discourse Processes, 43(2), 121–152. https://doi.org/10.1080/01638530709336895\r\n"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3475"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3476"},["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":"3477"},["text","LA1 4YT"]]]]]],["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":"3478"},["text","Professor Robert Davies"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"3479"},["text","Undergraduate"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"3480"},["text","Developmental, Psychlinguistics"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"3481"},["text","557"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"3482"},["text","Mixed effects logistic regression analysis."]]]]]]]],["item",{"itemId":"64","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"51"},["src","https://johnntowse.com/LUSTRE/files/original/d2dc5985e57b07e35905e64acb47b7b4.doc"],["authentication","3370ed59d929ffce6ca5d977ec62bb7f"]],["file",{"fileId":"52"},["src","https://johnntowse.com/LUSTRE/files/original/99408598e35363745a56c58e81430f29.doc"],["authentication","628eb1ba4a73e232e13333647109334e"]]],["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":"1558"},["text","Assessing Inference Making in Listening Comprehension in Children in Special Education"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"1559"},["text","Rebecca Hindle"]]]],["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":"1560"},["text","2018"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1561"},["text","Successful listening comprehension involves making accurate inferences to interpret the meaning of a story. We assessed inference making in listening comprehension of children in special education in years 4, 5, and 6 (n=12). Children listened to short stories and answered questions to assess local and global coherence inference after each story. Analysis of variance (ANOVA) revealed no significant main effects for children’s first responses for presentation type (whole, segmented) and inference type (local, global). However, after children had received prompts a significant main effect of inference type was shown with children performing better on global than local coherence inferences. Correlational analysis revealed no significant correlations between IQ and inference type but there was a stronger correlation between verbal IQ and inference type than non-verbal IQ and inference type. An independent t-test revealed no significant effect of diagnostic group on IQ or inference type but children in the Autism group performed better than children in the MLD group on both IQ measures and the MLD group scored better on both inference types. We conclude that inference type is important to consider when setting and asking comprehension questions along with the use of prompts to portray and assess children’s full comprehension ability. "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1562"},["text","Developmental Disorders"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"1563"},["text","\r\nParticipants\r\n\tThe participants were 12 children from years 4, 5 and 6 aged between 8 and 11 (N=12, 3 girls and 9 boys, M=9.67, SD=0.99) from a special needs school in the North West of England. All children had a statement of special educational needs including; Autism, Foetal Alcohol Syndrome, Moderate Learning Disability, Nonans Syndrome, Fetal Vulprate Syndrome and Speech and Language Impairment. All children were verbal with English as their first language. Consent was provided by parents/ carers, the Head of School and each class Teacher. \r\nMeasures\r\n\tIQ Task\r\n\tThe WISC IV was used to determine children’s IQ levels. Children completed one verbal and one non-verbal measure of IQ. The verbal measure was a vocabulary task, children were first shown pictures of items and asked what this is, progressing onto words asking, what does this mean? Children could score either 0, 1 or 2 points depending on the accuracy of their definitions according to the WISC IV manual. There were 36 items, increasing in difficulty, and testing stopped when children answered 5 questions incorrectly in a row. The non-verbal measure was a block design task, this comprised of 14 items starting with simple designs progressing to more difficult designs. Children had to copy patterns either demonstrated by the experimenter for the first 3 patterns or presented in picture format for the following items. There were time constraints for each pattern starting with 30s progressing in length for the more difficult items to 120s. Once children had failed to complete 3 patterns in a row, testing ended.\r\nListening comprehension task\r\n\tThe listening comprehension task was taken from Freed and Cain (2016) devised by the Language and Reading Research Consortium (LARRC) (2015). The full set of materials comprised 6 short stories however, for the current study only 4 stories were used: Grandma’s Birthday, The Game, New Pet and A Family Day Out. The stories were all topics appropriate to this age group. There were 8 questions paired with each story assessing both local and global coherence inferences; 4 of each. With questions either asked throughout the stories (segmented format) or at the end of the stories (whole format). In 2 of the sessions, stories were presented in a whole format and in the other 2 sessions, the stories were presented in a segmented format. All the stories were pre-recorded by Freed and Cain (2016) and delivered on PowerPoint presentation on the researcher’s laptop to ensure consistent delivery of the stories regarding pace and word emphasis. All stories were available in a whole and a segmented format. The format in which children listened to the stories was counterbalanced based on children’s IQ levels from low to high.  \r\n•\tWhole story format. Children listened to the full story and at the end were asked 8 comprehension questions. The delivery of each whole formatted story followed the same format. \r\n•\tSegmented story format. Children listened to the story in 5 segments. After each segment the child was asked either 1 or 2 questions with 8 questions in total. The delivery of each segmented story followed the same format. \r\n\tThe average length of the story was 157 words, there were no pictures included in the PowerPoint which the story recordings were presented on. This was to avoid children using the pictures to help them answer the questions. Children were provided with verbal prompts if incomplete answers were given to direct them to the correct answer. If children were still unable to answer full knowledge checks were provided, see Table 1. All prompts were pre-written to ensure all children received the same level of prompting.\r\nProcedure\r\n\tPre-test\r\n\tThe IQ assessments were implemented individually in a quiet room in two separate sessions. Each session lasted between 10 and 15 minutes depending on how many questions/ trials they completed. First children completed the vocabulary test then in a separate session completed the non-verbal measure, block design. \r\nMain assessment \r\n\tChildren were presented with 4 short stories on 4 separate occasions, each story paired with 8 questions. Each story had to be completed in a separate session due to the attention and engagement levels of the children being tested. Each session lasted approximately 10 minutes depending on children’s accuracy and speed of answering. The procedure was explained to the children at the beginning of each session using a script to ensure consistency. They were informed that they would either be asked questions throughout the story or at the end of the story. \r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"1564"},["text","Lancaster University"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"1565"},["text","Open"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1566"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1567"},["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":"1568"},["text","La1 4YF"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2133"},["text","Data/SPSS.sav"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2134"},["text","Hindle2018"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2135"},["text","Ellie Ball"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2136"},["text","None"]]]]]],["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":"2137"},["text","Professor Kate Cain"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2138"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2139"},["text","Developmental Psychology"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2140"},["text","12 Participants (9 boys and 3 girls- aged between 4-11)"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2141"},["text","ANOVA\r\nt-test\r\nCorrelation"]]]]]]]],["item",{"itemId":"164","public":"1","featured":"0"},["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":"3330"},["text","Can better linguistic fluency improve the memorability and credibility of a sentence?"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"3331"},["text","Hamish Bromley"]]]],["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":"3332"},["text","07.09.2022"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3333"},["text","Processing fluency is often defined as how easy information is to comprehend based on a range of characteristics. One form of processing fluency is linguistic fluency, which refers to how easy a sentence is to interpret, regardless of the information within it. Some research suggests that disfluency can increase the recall of material, but this is contested. Previous studies have also shown that the linguistic fluency of a sentence can be improved with literary devices, such as rhyme, and that this can result in better perceptions of credibility. Research has yet to investigate how alliteration, as an example of linguistic fluency, could improve perceptions of credibility and the memorability of a sentence. This research investigated this by operationalising lists of alliterating and non-alliterating aphorisms, alongside measures of self-reported credibility and memorability, in a between-subjects study. Results of two independent t-tests provided two significant results, suggesting that better linguistic fluency improves the credibility and memorability of a sentence. Implications for researchers, the legal system and advertising are discussed. "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3334"},["text","Linguistic Fluency, Alliteration, Advertising,Memory,Credibility"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"3335"},["text","Materials \r\nThe preliminary five aphorisms were provided by Astroten with five further aphorisms being added to increase the power of the study. Aphorisms that were selected came from various literary examples, such as quotes from English Literature (Williams, 2011). Alternatively, some aphorisms were created using the definition “a short clever saying that is intended to express a general truth” (Cambridge Dictionary, 2022). The most common alliterating aphorisms, such as “All roads lead to Rome”, were purposefully avoided so that the effect of familiarity had a reduced effect on the memorability self-report. When creating the non-alliterating aphorisms, alliterating words were exchanged for non-alliterating words using a thesaurus so that the change in alliterative properties did not affect the overall meaning. The alliterating and non-alliterating aphorisms were kept divided into two different lists and were counterbalanced in a random order for each participant (Appendix C). Participants were asked to rate the credibility of the aphorisms based on a Likert scale of 1-9, in parallel with the scale used by McGlone and Tofighbakhsh (1999). \r\nParticipants were asked to complete two games of Sudoku as a filler task (Appendix D). The grids were designed so that participants would begin with the easier version and move on to a more challenging version to ensure that the task occupied the full amount of time. Instructions were provided so that those who were unfamiliar with the game were still able to attempt the task. \r\n18 \r\nAdditionally, participants were given a piece of paper with 10 individual sections to write down as many of the aphorisms as they could remember at the end of the study. They were also provided with a pen, and time was kept using a watch. \r\nDesign \r\nThis study used a between-subjects design. This was chosen because there was a strong chance that order effects would impact the results of the memory test in a repeated measures design, due to the similarity between the alliterating and non-alliterating aphorisms. Choosing to mix the aphorisms could have resulted in demand characteristics affecting the results as the disparity between them would have been obvious to the participant. This is something that Oppenheimer and Frank (2008) were also keen to avoid. A quantitative data collection approach was taken because it was judged as the most appropriate way to measure memory, as well as facilitating comparison with other studies that have employed similar methods (McGlone & Tofighbakhsh, 1999; Kara-Yakoubian et al 2022). Participants were either part of the alliterating or non-alliterating aphorisms condition. \r\nProcedure \r\nEthical approval for this study was given by the supervisor of this research, in line with Lancaster University Psychology Department protocols (Appendix E). When participants were approached to take part in the study they were first asked to read an information sheet (Appendix F) followed by a consent form, completion of which evidenced their informed consent to take part. Participation began in a quiet room within the university library. It was ensured that they could spare 20 minutes to take part and that they had turned off their phones before the study began. They began the study by rating each aphorism in \r\n19 \r\ntheir list on a scale of 1-9 based on how credible they thought the aphorism was. The instructions were read to them, but they also had the opportunity to read them if they were unsure (Appendix G). They were then given three minutes to memorise as many of the aphorisms as possible. \r\nFollowing this, participants spent 10 minutes completing the Sudoku, with instructions again read to them and provided on the sheet. Once the 10 minutes were complete the participants were asked to spend five minutes trying to recall as many of the aphorisms from their list as possible by writing them down (Appendix H). They were given one point for every aphorism they could remember correctly. No points were given if the participants could only remember parts of the aphorism. As short-term memory is often described as being 7+/-2 (Miller 1956), memorisation of the entire list would likely have been impossible. Therefore, a prompt was added by reading the participant the first word from each of their aphorisms after three minutes. This aligns more closely with advertising research, which frequently measures prompted recall (Romaniuk, 2006; Charlesworth et al, 2022). On completion, participants were thanked for their participation in the research and given their £5 payment. They were also provided with a debrief sheet (Appendix I) that provided details of resources related to the study and the contact details of the researcher and supervisor. "]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"3336"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3337"},["text","Excel/xlsx."]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"3338"},["text","Bromley2022"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3339"},["text","Coco"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"3340"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"3341"},["text","Dissertation"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3342"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3343"},["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":"3344"},["text","Marketing"]]]]]]]],["item",{"itemId":"168","public":"1","featured":"0"},["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":"3408"},["text","Can better linguistic fluency improve the memorability and credibility of a sentence?"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"3409"},["text","Hamish Bromley"]]]],["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":"3410"},["text","07.09.2022"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3411"},["text","Processing fluency is often defined as how easy information is to comprehend based on a range of characteristics. One form of processing fluency is linguistic fluency, which refers to how easy a sentence is to interpret, regardless of the information within it. Some research suggests that disfluency can increase the recall of material, but this is contested. Previous studies have also shown that the linguistic fluency of a sentence can be improved with literary devices, such as rhyme, and that this can result in better perceptions of credibility. Research has yet to investigate how alliteration, as an example of linguistic fluency, could improve perceptions of credibility and the memorability of a sentence. This research investigated this by operationalising lists of alliterating and non-alliterating aphorisms, alongside measures of self-reported credibility and memorability, in a between-subjects study. Results of two independent t-tests provided two significant results, suggesting that better linguistic fluency improves the credibility and memorability of a sentence. Implications for researchers, the legal system and advertising are discussed."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3412"},["text","Linguistic Fluency, Alliteration, Advertising,Memory,Credibility"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"3413"},["text","Materials \r\nThe preliminary five aphorisms were provided by Astroten with five further aphorisms being added to increase the power of the study. Aphorisms that were selected came from various literary examples, such as quotes from English Literature (Williams, 2011). Alternatively, some aphorisms were created using the definition “a short clever saying that is intended to express a general truth” (Cambridge Dictionary, 2022). The most common alliterating aphorisms, such as “All roads lead to Rome”, were purposefully avoided so that the effect of familiarity had a reduced effect on the memorability self-report. When creating the non-alliterating aphorisms, alliterating words were exchanged for non-alliterating words using a thesaurus so that the change in alliterative properties did not affect the overall meaning. The alliterating and non-alliterating aphorisms were kept divided into two different lists and were counterbalanced in a random order for each participant (Appendix C). Participants were asked to rate the credibility of the aphorisms based on a Likert scale of 1-9, in parallel with the scale used by McGlone and Tofighbakhsh (1999). \r\nParticipants were asked to complete two games of Sudoku as a filler task (Appendix D). The grids were designed so that participants would begin with the easier version and move on to a more challenging version to ensure that the task occupied the full amount of time. Instructions were provided so that those who were unfamiliar with the game were still able to attempt the task. \r\n18 \r\nAdditionally, participants were given a piece of paper with 10 individual sections to write down as many of the aphorisms as they could remember at the end of the study. They were also provided with a pen, and time was kept using a watch. \r\nDesign \r\nThis study used a between-subjects design. This was chosen because there was a strong chance that order effects would impact the results of the memory test in a repeated measures design, due to the similarity between the alliterating and non-alliterating aphorisms. Choosing to mix the aphorisms could have resulted in demand characteristics affecting the results as the disparity between them would have been obvious to the participant. This is something that Oppenheimer and Frank (2008) were also keen to avoid. A quantitative data collection approach was taken because it was judged as the most appropriate way to measure memory, as well as facilitating comparison with other studies that have employed similar methods (McGlone & Tofighbakhsh, 1999; Kara-Yakoubian et al 2022). Participants were either part of the alliterating or non-alliterating aphorisms condition. \r\nProcedure \r\nEthical approval for this study was given by the supervisor of this research, in line with Lancaster University Psychology Department protocols (Appendix E). When participants were approached to take part in the study they were first asked to read an information sheet (Appendix F) followed by a consent form, completion of which evidenced their informed consent to take part. Participation began in a quiet room within the university library. It was ensured that they could spare 20 minutes to take part and that they had turned off their phones before the study began. They began the study by rating each aphorism in \r\n19 \r\ntheir list on a scale of 1-9 based on how credible they thought the aphorism was. The instructions were read to them, but they also had the opportunity to read them if they were unsure (Appendix G). They were then given three minutes to memorise as many of the aphorisms as possible. \r\nFollowing this, participants spent 10 minutes completing the Sudoku, with instructions again read to them and provided on the sheet. Once the 10 minutes were complete the participants were asked to spend five minutes trying to recall as many of the aphorisms from their list as possible by writing them down (Appendix H). They were given one point for every aphorism they could remember correctly. No points were given if the participants could only remember parts of the aphorism. 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"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"3414"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3415"},["text","Excel/xlsx."]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"3416"},["text","Bromley2022"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3417"},["text","Cyrus"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"3418"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"3419"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3420"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3421"},["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":"3422"},["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":"3423"},["text","Leslie Hallam"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"3424"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"3425"},["text","Marketing"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"3426"},["text","50"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"3427"},["text","T-Test"]]]]]]]],["item",{"itemId":"185","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"204"},["src","https://johnntowse.com/LUSTRE/files/original/b8f75dc1e1ab0f20a5a61b57fddeba52.doc"],["authentication","4d757be9d7867a128bce4cbedd7dbab9"]]],["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":"3687"},["text","Can We Reduce Childhood Obesity in the Community? A qualitative Perspective that Discusses the Barriers and Strategies to Childhood Obesity within Miles Platting and Newton Heath."]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"3688"},["text","Charlotte Graham"]]]],["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":"3689"},["text","2023"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3690"},["text","Childhood obesity (CO), which can have long-term negative health issues, has increased dramatically over the last thirty years. Given this, NHS Manchester has commissioned this study, with a particular focus on the Manchester boroughs of Miles Platting and Newton Heath, due to the high rates of CO in those areas, to explore the relevant dynamics involved, understand the barriers to healthier eating/lifestyles and derive strategies to combat CO. A semi-structured interview style was utilised, with healthcare professionals. Within these interviews, the healthcare professionals commented on their experiences of CO within their job roles and what they believe to be the barriers for parents to be for CO. Their thoughts based on parents' experience with CO were formed due to working with parents and discussing these barriers with them. It was found that a child's home life massively impacts the likelihood of a child's obesity, with parental education, motivations and poverty playing significant roles, along with a parent’s lack of skills, knowledge, money, and time. Based on these factors, strategies are discussed that have been successful or unsuccessful previously, as well as ideas for future strategies. Based on these findings, it is suggested that collaboration between the different services offered within the Manchester area offers scope for improvement, while strategies to help reduce CO need to focus on a ‘show and tell’ aspect whereby individuals receive immediate support, such as having access to healthy food, while gaining the practical skills to help them create a sustainable change, such as learning how to cook or budget. These strategies are discussed about the general community and specific goals for NHS Manchester to increase the likelihood of healthier lifestyles being adopted."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3691"},["text","Childhood Obesity. Poverty. Education. Barriers. Strategies. Recommendations."]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"3692"},["text","Sample \r\nNine people participated in the current study. Each of these participants were healthcare professionals over the age of 18. The term ‘healthcare professionals’ was a broad term for anyone in a professional capacity who dealt with CO in their job role. The initial participants were recruited from the contacts of the NHS Manchester Local Care Organisation, and then a snowball sample from these initial participants. The job roles presented in this sample included a business manager for a school, a school meal supervisor, a GP nurse, a bursary manager, and an array of service workers for the local community in different services, such as the Healthy Weight Team in Manchester. Each participant worked within Manchester, specifically Miles Platting and Newton Heath. \r\n\r\nDesign and Materials \r\nEthics\r\nData collected in this qualitative study was reviewed and approved by the Faculty of Science and Technology Ethics Committee at Lancaster University (see Appendix A). All the participants were provided with information about this study and knew their ethical rights, such as the right to withdraw, confidentiality, and data protection. \r\n\r\nProcedure\r\nThe initial participants were introduced to the researcher via email by a Manchester Local Care Communication member. Once this introduction had taken place, communication about the research and the arrangement of the interviews were discussed between the researcher and the participant through email. After completing their interview, these participants introduced the researcher to their other contacts through email (snowball sample). Email was the primary contact method for each participant and the recruitment process. \r\nEach interview was an online semi-structured interview, lasting between 30-60 minutes. The online software used was Microsoft Teams, which facilitated the discussion, recorded it and created a transcript. Due to the limitations of the software, the audio and visual information of the Microsoft Teams Meeting would be recorded. Therefore, the participants were informed of this limitation before the recording and asked if they would like to turn their cameras off.  While the interview was ongoing, a discussion guide and prompts for further elaboration on their answers were used.\r\n\r\nFootnote\r\nThe initial methodology planned to include interviews with parents who had children at a primary school age. However, the logistics, timing and lack of engagement made this impossible, meaning no parents were included in the sample. Due to this, a parental perspective from the viewpoint of healthcare professionals was asked in the interviews. The viewpoint was informative due to these healthcare professionals' interactions with the parents, which provided insight into parents' thoughts about CO. However, this is from a secondary source, so an element of accuracy needed to be considered. \r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"3693"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3694"},["text","Text/Word doc."]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"3695"},["text","Graham2023"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3696"},["text","Georgie Comerford\r\nKaty Nichol"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"3697"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"3698"},["text","None."]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3699"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3700"},["text","Interviews"]]]],["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":"3701"},["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":"3702"},["text","Leslie Hallam"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"3703"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"3704"},["text","Marketing, Developmental, Social."]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"3705"},["text","9"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"3706"},["text","Qualitative (Thematic Analysis)"]]]]]]]],["item",{"itemId":"45","public":"1","featured":"0"},["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":"1288"},["text","Carer adaptation to childhood epilepsy: The role of the Epilepsy Specialist Nurse."]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"1289"},["text","Kate Greene"]]]],["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":"1290"},["text","2013"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1291"},["text","Positive carer adaptation to childhood epilepsy is essential as poor adaptation can be detrimental to child behaviour outcomes. Fulfilment of carer psycho social and informational need is important to facilitate successful adaptation to childhood epilepsy. The role of the Epilepsy Nurse Specialists (ESN) is well suited to meet psychosocial need and so ESNs are hypothesised to improve carer adaptation and in turn child behaviour. This study investigated carer adaptation in geographical areas in the north of England with and without ESN provision using telephone interviews with carers of children with epilepsy. It was found that ESN provision had no significant effect on carer adaptation, psycho social needs of the carer, or child behaviour. Reasons for why no effect was found is attributed to the significant difference in condition severity and comorbidity between the groups that require more complex care needs. Limitations and future research directions are discussed."]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"1292"},["text","1. Parent Response to Child Illness (PRCI).  Participants were assessed in three outcome measures.\r\n2. Parent Report of Psychosocial Care Scale (PRPCS). The second area of assessment was carers' perceived need for information and support. \r\n3. Child Behaviour Checklist (CBCL).  The third measure is a measure of child behaviour using the CBCL (Achenbach & Rescorla, 2001). \r\n4. Hague Seizure Severity Scale (HASS).  Participants were also asked to provide information relating to their child's seizure severity, their mental health and demographic information so intergroup comparisons could be made. \r\n5. General Health Questionnaire (GHQ).  Mental health of the carer was assessed using the short form of the GHQ (Goldberg & Hillier, 1979). \r\n6. Demographic Information.  Additionally participants were asked to complete a questionnaire containing demographic information, and also information relating to age of seizure onset, time of last seizure, seizure frequency, anti-epileptic drug (AED)therapy and adherence to this medication. "]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"1293"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1294"},["text","data/SPSS.sav"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"1295"},["text","Greene2013"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"1296"},["text","Open"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1297"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1298"},["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":"1299"},["text","LA1 4YF"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"1308"},["text","Chen, Jhih-Ying"]]]]]],["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":"1300"},["text","Dina Lew"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"1301"},["text","MSC"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"1302"},["text","Participants in this study are parents or carers of children with a diagnosis of epilepsy aged between 6 and 16 years of age. This age was range was selected as it is the appropriate age range for the main measure of carer adaptation. Two NHS trusts were recruited for the study, one that provided an Epilepsy Specialist Nurse (ESN) for its service users (Bolton) and one that had no ESN provision (Pennine). Suitable participants were identified from these trusts and invited to take part in the study using either ESN or paediatrician with a special interest in epilepsy caseload lists. Parents who accepted the invitation to take part formed the sample for the study which consisted of 33 participants with access to an ESN and 17 participants without ESN provision."]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"1303"},["text","ANOVA"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"1389"},["text","Developmental Psychology\r\nDevelopmental Disorders"]]]]]]]],["item",{"itemId":"186","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"205"},["src","https://johnntowse.com/LUSTRE/files/original/42f25a4afae4681322de3eaca175d305.pdf"],["authentication","f34904e516c4c04821ec1e52402b3ea9"]]],["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":"3707"},["text","Cerebral Lateralisation for Emotion Processing of Chimeric Faces in Individuals with Autism Spectrum Disorder "]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"3708"},["text","Alexandra Crossley"]]]],["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":"3709"},["text","5th September 2023"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3710"},["text","Many studies have suggested that typical lateralisation for emotion processing tasks, such as facial emotion recognition, is lateralised to the right-hemisphere, with different emotions eliciting differing strengths of lateralisation (Bourne, 2010). However, there has been much debate as to the lateralisation of individuals with autism spectrum disorder (ASD) (Ashwin et al., 2005; Shamay-Tsoory et al., 2010). This study assessed the cerebral lateralisation of 30 adults with ASD, five children with ASD, 435 neurotypical adults and ten neurotypical children in a chimeric faces task, and aimed to identify whether the atypical lateralisation seen in children with ASD persists into adulthood (Taylor et al., 2012). Furthermore, the study aimed to identify whether lateralisation strength is affected by the emotion of the facial stimuli. No emotion- or age-related change in lateralisation was found, however, participants with ASD demonstrated a weaker right-hemispheric lateralisation compared to neurotypical participants. Therefore, this study supported the concept that individuals with ASD show atypical lateralisation which persists into adulthood, however, no evidence was found to support the concept that different emotions elicit different strengths of lateralisation."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3711"},["text","autism spectrum disorder, cerebral lateralisation, emotion processing, adults, children, chimeric faces task"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"3712"},["text","Method\r\nParticipants\r\nData from a total of 481 participants with native level English proficiency (or age expected language development in children), normal or corrected-to-normal vision and no history of neurological disease or hearing loss were analysed for the current study (Table 1). Participants in the group ‘adults with ASD’ (N = 30; age: M = 30.17, SD = 9.85) were recruited through adverts on social media, through Prolific Academic (www.prolific.co), and through word of mouth. Participants in the groups ‘children with ASD’ (N = 5; age: M = 6.8, SD = 1.48) and ‘neurotypical children’ (N = 11; age: M = 7.0, SD = 1.90) were recruited through primary schools and word of mouth (Brooks, 2023), and parents of potential child participants were required to \r\n \r\nemail a researcher to express their interest in participation. Participants in the group ‘neurotypical adults’ (N = 435; age: M = 29.44, SD = 8.03) were recruited through Prolific Academic (www.prolific.co) as part of a larger online behavioural laterality battery (Parker et al., 2021). Of the 481 participants who took part in the study, 32 were excluded during the data cleaning process (see Table 1 and Data Analysis for further information).\r\nMeasures\r\nAs part of the study, a series of questionnaires were administered to collect information about the participants to ensure that individual differences could be accounted for. Participants were asked to complete the study and its associated questionnaires and tasks prior to beginning the main chimeric faces task, and were requested to use a desktop or laptop computer for the entirety of the study. For the ‘neurotypical children’ and ‘children with ASD’ groups, parents were asked to complete the questionnaires on behalf of the children and were asked to be present for the tasks, which were completed during a Microsoft Teams call with a researcher.\r\nThe study was completed online using the Gorilla Experiment Builder (www.gorilla.sc), a cloud-based tool for collecting data in the behavioural sciences. \r\nDemographic Questionnaire\r\nThe demographic questionnaire asked participants their age, gender, length of time in education (in years), language status, two questions assessing handedness (“Which is your dominant hand? / Which hand do you prefer to use for tasks such as writing, cutting, and catching a ball?”) and footedness (“Which foot do you normally use to step up on a ladder/step?”), and two eye dominance tests (Miles, 1929; Porac & Coren, 1976). Participants were also asked whether they had a diagnosis of any developmental disorders, including ASD, dyslexia, attention deficit hyperactivity disorder or a language disorder (such as 'developmental language disorder' or 'specific language impairment'). For each diagnosis, participants had the option to answer “Yes”, “No”, or “Prefer not to say”, with the exception of ASD which also had the option to answer “No but I am self-diagnosed”. At this point, participants were sorted into their groups based on age (‘children’: five- to 11-years-old; or ‘adults’: 18- to 50-years-old) and ASD diagnosis (‘with ASD’, or ‘neurotypical’). Adults with a self-diagnosis of ASD were included in the ‘adults with ASD’ group.\r\nEdinburgh Handedness Inventory\r\nThe Edinburgh Handedness Inventory (EHI; Oldfield, 1971) was administered to provide a scaled score of handedness. Adult participants were asked to score ten daily tasks on a five-point Likert scale based on which hand they preferred to use during each task (“Left hand strongly preferred” = 2, “Left hand preferred” = 1, “No preference” = 0, “Right hand preferred” = 1, or “Right hand strongly preferred” = 2). These tasks included daily activities such as writing, brushing teeth, and opening a box. The EHI was scored by combining the direction and exclusiveness of the hand preference. Two totals were created: one of right-hand preference and one of left-hand preference. The difference was then found by subtracting the left-hand total from the right-hand total. This was then divided by the total score of both hand preference scores and multiplied by 100 (i.e., 100 x (right-hand total – left-hand total) / (right-hand total + left-hand total)). Final EHI scores ranged from -100 to +100, with positive scores indicating right-handedness, and negative scores indicating left-handedness. Child participants were not required to complete the EHI questionnaire.\r\nLexical Test for Advanced Learners of English\r\nA version of the Lexical Test for Advanced Learners of English (LexTALE; Lemhöfer & Broersma, 2012) was provided to assess the participants’ level of proficiency in English. Within this, adult participants were shown 60 written stimuli comprised of English words and pseudowords (words that follow the orthographical and phonetic rules of the English language and are pronounceable but are otherwise nonsense words, e.g. ‘proom’) and asked to assess whether each word was an existing English word or not. Scores of the test were collected by averaging the percentages of correct answers for English words and pseudowords, with final scores ranging from 0-100. Child participants were not required to complete the LexTALE task.\r\nAutism-Spectrum Quotient (Short Version)\r\nAn abridged version of the Autism-Spectrum Quotient (AQ-Short; Hoekstra et al., 2011) was used to provide a measure of ASD traits. Participants with ASD were asked to rate 28 statements on a four-point Likert scale based on their level of agreement, with each answer accruing a different number of points (“Definitely agree” = 1, “Slightly agree” = 2, “Slightly disagree” = 3, or “Definitely disagree” = 4). On items in which “Definitely agree” represented a characteristic of ASD, the scoring was reversed. The scores for each question were totalled, with potential scores ranging between 28 (no ASD traits) to 112 (full inclusion of all ASD traits). Scores above 65 indicated ASD traits to a diagnosable degree. Neurotypical participants were not required to complete the AQ-Short questionnaire.\r\nProcedure\r\nLateralisation for Facial Emotion Processing Task\r\nA chimeric faces task was used to assess lateralisation for facial emotion processing.\r\nStimuli. The chimeric faces stimuli were created by Dr Michael Burt (Burt & Perrett, 1997) and provided by Parker et al. (2021).\r\nA collection of 16 different facial stimuli were created by merging two photographs of a man’s face depicting one of four emotions (‘happiness’, ‘sadness’, ‘anger’, or ‘disgust’) vertically down the centre of the face and blended at the midline (see Figure 1 for an example). Each emotion was paired either with itself, causing both hemifaces of the facial stimuli to match in emotion (a ‘same face’), or with a differing emotion, causing both hemifaces of the facial stimuli to be different (a ‘chimeric face’). Of the 16 stimuli, 12 were ‘chimeric face’ and four were ‘same face’.\r\nTask. Each trial began with a fixation cross shown for 1000ms, followed by the face stimuli for 400ms. Participants then recorded which emotion they saw most strongly by clicking the corresponding button from a choice of the four emotions (Figure 2). For the children, emoticons were used instead of written words (Oleszkiewicz et al., 2017) (Figure 3). A response triggered the beginning of the next trial, with a time-out duration set at 10400ms after which the next trial was triggered automatically. Response choice and response times were recorded. \r\nThe task was split into four blocks of trials with a break between each block. Stimuli were presented in a random order and shown twice in each block, resulting in the participants being shown 32 stimuli per block and a total of 128 within the whole task. \r\n\r\n   \r\nParticipants were familiarised with the stimuli at the start of the task, with the ‘same face’ stimuli being shown alongside a label explaining which emotion was being presented, to ensure they could recognise the emotions. A practice block was given at the start of the task to ensure participants knew how to complete the task, using the emotions ‘surprise’ and ‘fear’. \r\nAdditional Measures\r\nAs data collection also included tasks for other studies, participants were also asked to complete a version of the Empathy Quotient – short (Wakabayashi et al., 2006), and undertake a dichotic listening task and its associated device checks (Parker et al., 2021). As these items were not part of the main study, participants were asked to complete these following the completion of the main study and its associated questionnaires and tasks, to ensure any findings from the study were not due to the additional measures.\r\nLaterality Index\r\nA laterality index (LI) for each participant was calculated using the same method as Parker et al. (2021) by finding the difference between the number of times the participant chose the right-hemiface emotion and the left-hemiface emotion. This was then divided by the total number of times they chose either the right- or left-hemiface emotion, and multiplied by 100 (i.e., 100 x (right hemiface – left hemiface) / (right hemiface + left hemiface)). Scores ranged between -100 and +100, with a negative LI indicating a left-hemiface bias, and thus, a right-hemispheric dominance, and a positive LI showing the opposite.\r\nData Analysis\r\nParticipants who scored less than 80 on the LexTALE task were removed as it was deemed their understanding of the English language was not strong enough and may cause issues with understanding the instructions (Parker et al., 2021). Furthermore, all trials with a response time faster than 200ms were removed as it was suggested that responses at this speed were too quick to have been based on the processing of the stimuli (Parker et al., 2021). In addition to this, outlier response times for each participant were removed using Hoaglin & Iglewicz's (1987) procedure. Within this, outliers were any response times 1.65 times the difference between the first and third quartiles, below the first quartile or above the third (e.g., below Q1 – (1.65 x (Q3-Q1)), and above Q3 + (1.65 x (Q3-Q1))). Following the removal of all outlying trials, any participant with less than 80% of trials remaining were removed. In addition to this, participants who scored less than 75% on ‘same face’ trials (trials in which both hemifaces depicted the same emotion) were noted, because emotion processing is an area of difficulty for individuals with ASD. Within this, three participants in the ‘children with ASD’ group (60%), three participants in the 'neurotypical children’ group (27.27%), four participants in the ‘adults with ASD group (13.33%), and 30 participants in the ‘neurotypical adults’ group (7.41%) scored less than 75% on ‘same face’ trials, suggesting they had difficulties identifying the emotions.\r\nTo address the hypotheses, a linear model was performed using LI as the outcome and group (‘ASD’ or ‘neurotypical’), age (‘adult’ or ‘child’) and emotion (‘happy’ and ‘angry’, or ‘sad’ and ‘disgust’) as the predictors, including interactions between each predictor (Group x Age; Group x Emotion; Age x Emotion; and a three-way interaction, Group x Age x Emotion).\r\n\r\n\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"3713"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3714"},["text",".csv"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"3715"},["text","Crossley2023"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3716"},["text","Alexandra Haslam \r\nAlexis McGuire\r\nxue guo"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"3717"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"3718"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3719"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3720"},["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":"3721"},["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":"3722"},["text","Margriet Groen"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"3723"},["text","MSC"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"3724"},["text","Developmental, Neuropsychology "]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"3725"},["text","481 participants with native level English proficiency, 164 Male, 240 female and 1 other."]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"3726"},["text","Linear Mixed Effects Modelling and T-Test"]]]]]]]]]