["itemContainer",{"xmlns:xsi":"http://www.w3.org/2001/XMLSchema-instance","xsi:schemaLocation":"http://omeka.org/schemas/omeka-xml/v5 http://omeka.org/schemas/omeka-xml/v5/omeka-xml-5-0.xsd","uri":"https://www.johnntowse.com/LUSTRE/items/browse?output=omeka-json&page=15","accessDate":"2026-05-03T13:21:22+00:00"},["miscellaneousContainer",["pagination",["pageNumber","15"],["perPage","10"],["totalResults","148"]]],["item",{"itemId":"23","public":"1","featured":"1"},["fileContainer",["file",{"fileId":"5"},["src","https://www.johnntowse.com/LUSTRE/files/original/fc27f6fa5aa3b5c2ec188de4cbeefc44.pdf"],["authentication","2983d0be2c388322ede175f2da332d2c"]],["file",{"fileId":"6"},["src","https://www.johnntowse.com/LUSTRE/files/original/ae430f6c841f862e00a44f12d0df1e8a.pdf"],["authentication","b9bd1185b1ff26c600843d03fd22e71c"]]],["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":"874"},["text","Running Memory Span Development: The Input Mechanism and Hebb effect"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"875"},["text","Yu Xie"]]]],["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":"876"},["text","2013"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"877"},["text","It is unclear whether active strategy or passive strategy is used and whether the Hebb effect is elicited in the running memory task. The aim of this study was to explore the input mechanism and the Hebb effect in the running memory task via a developmental study. Children were asked to perform four working memory tasks: counting span task, free recall task, Hebb digit task, and running memory task. In order to explore the Hebb effect in the running memory task, the last three digits of every third list were repeated. The results suggested that running memory was a recency-based phenomenon and the Hebb effect is elicited in children. "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"878"},["text","running memory span development\r\ninput mechanism\r\nHebb effect\r\n"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"879"},["text","The experiment was presented using SuperLab 4.0 on a Sony Laptop with a 14-inch colour screen. The responses of participants were recorded by the tester on answer sheets. Every child completed a counting span task, a free recall task, a Hebb digit task, and a running memory task.\r\nCounting span task. The counting span arrays were developed from Towse and Hitch (1995) and consisted of equal number of target triangles and non-target squares. The target triangles were red, approximately 30 mm in length, and the non-target squares were blue, approximately 28 mm in length. The number of both target triangles and non-target squares varied from 3 to 9 (mean = 6). The counting span arrays were presented on the centre of the computer screen with a white background. The triangles and squares were randomly displayed at different positions in every display.  \r\nFree recall task. For this task, 144 Chinese high-frequent two-syllable nouns (see Appendix A) were recorded by in a male’s voice at rate of 1 word per second. The words were recorded using Adobe Audition 3.0. Two practice lists and ten test lists were presented, and every list included 12 words at the rate of 1 word per second. The words were played by a computer.\r\nHebb digit task. All digit lists were created had the digits 1 to 9 in random order, avoiding any repetition of digits (see Appendix B). The voice of digits was recorded by Adobe Audition 3.0 at the rate of 1 digit per second. There were 2 practice lists and 24 test lists, and each list contained nine digits. Among the test lists, 16 lists were different, and the other 8 were the same – termed as Hebb list – presented on every third trial beginning on Trial 3. The 24 test lists were divided into 8 blocks, which involved 2 different lists and a Hebb list. \r\nRunning memory task. The lists included 12, 14, 16, 18, or 20 random digits from 1 to 9 (see Appendix C), which were recorded by voice. Two presentation rates were used in this task: 0.5 s per digit as the fast rate and 2.5 s per digit as the slow rate. In both conditions, there were 2 practice lists and 24 test lists. In order to test the Hebb effect in running memory task, the 24 test trials comprised 16 completely different lists, and 8 lists with the same last 3 digits which were the same and presented on every third trial. \r\nProcedure \r\nThe experiment lasted 45 min, and every child completed 4 tasks. Each participant was seated on a chair in front of the computer screen, at a distance of 65 cm. All tasks included two practice trials for helping children be familiar with the procedure. Once children completed the practice trials and understood the procedure, they could proceed to the test trials. When children were performing the tasks, the experimenter gave no feedback about the accuracy of the words or digits. The order effect was counterbalanced as shown in the Table 1, which is a Latin Square design. Because there were two conditions in the running memory task, the fast speed and slow speed running, the tasks were counterbalanced. Therefore, in all, there were eight orders in the present study, and all children were equally divided into eight groups based on the eight orders. When participants completed each task, they were given sufficient time to rest. \r\nTable 1\r\nTask Orders for Four Tasks\r\nTask\r\nOrders\r\n\r\na\r\nb\r\nc\r\nd\r\ne\r\nf\r\ng\r\nh\r\nCounting span task\r\n1\r\n2\r\n3\r\n4\r\n1\r\n2\r\n3\r\n4\r\nFree recall task\r\n2\r\n1\r\n4\r\n3\r\n2\r\n1\r\n4\r\n3\r\nHebb digit task\r\n3\r\n4\r\n1\r\n2\r\n3\r\n4\r\n1\r\n2\r\nRunning memory task\r\n4(FS)\r\n3(FS)\r\n2(FS)\r\n1(FS)\r\n4(SF)\r\n3(SF)\r\n2(SF)\r\n1(SF)\r\nNote. F = Fast-running memory task, S = Slow-running memory task.\r\nCounting span task. The children were informed to the counting and recall tasks. Before every trial, a fixation symbol was displayed on the centre of screen for 0.5 s. When the target triangles and non-target squares were presented, participants were required to count the red triangles aloud, and repeat the final number. Once the children repeated the last number, the experimenter pressed the keyboard to show the next display, and the counting speeds were recorded by the computer automatically. There were three trials in every level and every trial included the n + 1 displays in level n. For example, participants counted 2 displays in level 1 and 3 displays in level 2. The final level was level 4, which contained 5 displays. After 2 to 5 displays, children were asked to report all the final numbers of red target triangles in the previous displays. If a child failed to recall correctly for at least two of the three trials, the counting span task was ended at that level; otherwise, they could progress to the next level. \r\nFree recall task. Children were required to listen to some words, and repeat them as many as possible in any order, after the 12th word. The experimenter wrote down the responses of participants on answer sheets. If the children could not report a new word within 30 s, the experimenter would proceed to the next trial. \r\nHebb digit task. The procedure for the Hebb digit task was developed by Hebb (1961). Children were asked to listen to every list, and report all digits in the right order. Children reported the digits orally, and the experimenter recorded the response on an answer sheet. Because the running memory task also involved Hebb lists, 48 children were asked whether they were aware of any regular pattern in the digit tasks after they completed both Hebb digit task and running memory task. Only 5 participants noticed the repetition in the running memory and Hebb digit tasks.\r\nRunning memory task. Children were made to listen to some digits, different from those in the Hebb digit task; they were required to repeat the last three digits rather than all digits in the list. Two conditions were set to counterbalance the order effect: half of the children were administered the fast rate condition first and the other half were administered the slow rate condition first.\r\nScoring\r\nCounting span task. Counting errors and counting speed were recorded and the scoring method used is the partial-credit unit scoring prescribed by Conway et al. (2005). Firstly, the correct items in each sequence were counted. If all items were correct in a sequence, this sequence was given one point. Otherwise, the score of a sequence was based on the proportion of correct items. Finally, the counting span of a participant was calculated as the sum the scores for all sequences. \r\nFree recall task. The scoring method used was the one prescribed by Tulving and Colotla (1970), which involved the calculation of intratrial retention interval (ITRI). The ITRI value was the number of items between the presentation and the reported items. For instance, if the sequence is A, B, C, D, E, F, and G, and a participant reported G, F, and A. The ITRISs for the items were 0, 2, and 8, respectively. Before calculating the ITRI, the digit span of the Hebb non-repeating lists was calculated for every child. If the digit span of a child was 5, the item would be classified as a word from primary memory when the ITRI was 5 or less, whereas the item would be classified as a word from the secondary memory when the ITRI was 6 or more. \r\nHebb digit task. Every digit recalled correctly at the correct position was scored one point. The score of the non-repeating lists was the mean score of each non-repeating list, and the score of the repeating lists was the mean score of each repeating list. \r\nRunning memory task. The score for the running memory span was calculated using the mean number of digits in the right positions. If 3 digits were recalled in correct sequence, the score was 3; if the sequence of 2 digits (for example the first and second digit, the second and the third digit, or the first and third digit) was in the correct serial order the score was 2; if there was a single digit in the correct position, the score was 1. Similar to the Hebb digit task, the scores for non-repeating and repeating lists were separated.  "]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"880"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"881"},["text","data/SPSS.sav"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"882"},["text","Xie2013"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"883"},["text","John Towse"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"884"},["text","Open"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"885"},["text","English\r\nChinese"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"886"},["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":"887"},["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":"888"},["text","John Towse"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"889"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"890"},["text","Developmental Psychology\r\nCognitive Psychology"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"891"},["text","Fifty-seven Chinese primary school students (23 female, 34 male), aged between 7 and 13 years (Mean = 9 years 6 months; SD = 1.754) took part in the present study. The children were recruited from Grade one to Grade six at Tianyi School in Xuancheng City"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"892"},["text","ANOVA\r\nt-test"]]]]]]]],["item",{"itemId":"22","public":"1","featured":"0"},["collection",{"collectionId":"6"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"187"},["text","RT & Accuracy"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"188"},["text","Projects that focus on behavioural data, using chronometric analysis and accuracy analysis to draw inferences about psychological processes"]]]]]]]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"857"},["text","The effect of different question types during shared book reading on children’s narrative comprehension"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"858"},["text","Nicola Pooley"]]]],["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":"859"},["text","2010"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"860"},["text","This study investigated the effect of different question types on narrative comprehension in young children. Forty one five year olds participated in this study. One group (N=14) received three sessions of shared storybook reading in which they practised answering questions about literal information in the story, during the course of the storybook reading. A second group (N=13) practiced answering questions about information that had to be inferred. A third group of controls (N=14), did not receive any intervention. All groups completed two comprehension assessments before and after the intervention: one was a measure of general listening comprehension, the other included measures of both literal and inferential comprehension. Children’s engagement during the storybook reading was also assessed. Contrary to predictions, neither intervention benefitted post-test comprehension significantly. In addition engagement levels did not change over the course of the study. However, a consistent pattern was found for each comprehension measure: the group who received practice with answering inferential questions made the greatest gains. Implications for early literacy experiences are discussed."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"861"},["text","reading comprehension"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"862"},["text","Design\r\n\r\nThe study was an intervention design with three phases: a pre-test, training phase and post-test. There were three groups: two experimental groups who participated in all phases and a control group who only completed the pre and post tests. The design is shown in Table One. In the pre and post test sessions, participants completed a general measure of listening comprehension (adapted from the Neale Analysis of Reading Ability II, Neale, 1997) and a bespoke measure of listening comprehension with questions to tap literal and inferential comprehension. Participants were assigned to groups on the basis of their scores in the pre-test so that the three groups (two intervention and one control) did not differ in their performance on these measures (see Table Five). Children in the intervention conditions listened to three stories in separate sessions and either received practice at answering literal or inferential questions throughout the stories. In the post test all children were again assessed on alternate forms of the same measures used in the pre-test.\r\n\r\n\r\n\r\nTable 1. Intervention design used.\r\n\r\n\r\nGroup\r\n\r\n\r\nPre Test\r\n\r\n\r\n1\r\n\r\nTraining\r\n\r\n2\r\n\r\n\r\n3\r\n\r\n\r\nPost test\r\n\r\nControl\r\n\r\nGeneral + Bespoke Listening Comprehension.\r\n\r\nx\r\n\r\nx\r\n\r\nx\r\n\r\nGeneral + Bespoke Listening Comprehension.\r\n\r\nLiteral\r\n\r\nGeneral + Bespoke Listening Comprehension.\r\n\r\nLiteral\r\n\r\nLiteral\r\n\r\nLiteral\r\n\r\nGeneral + Bespoke Listening Comprehension.\r\n\r\nInferential\r\n\r\nGeneral + Bespoke Listening Comprehension.\r\n\r\nInferential\r\n\r\nInferential\r\n\r\nInferential\r\n\r\nGeneral + Bespoke Listening Comprehension.\r\n\r\n\r\nMaterials: Pre and Post test.\r\n\r\nGeneral Measure of Listening Comprehension. The following stories taken from the Neale Analysis of Reading Ability (NARA, Neale, 1997) were read to each participant in either the pre or post test: Toys, Tree house, Lost and Found, Road Safety. Toys or Lost and Found were used as practice tasks at the beginning of the pre/post test to help develop rapport. The stories were chosen so that the level of difficulty was consistent pre and post test. Comprehension questions that went with each story were asked at the end of the story to obtain the general measure of listening comprehension score. Table Two shows an example of a story and some of the questions given.\r\n\r\n\r\nTable 2. Example of general listening comprehension story used.\r\n\r\nGeneral Comprehension Example\r\n\r\nSample of Questions asked\r\n\r\nMy friend and I made a tree house. We like to hide in it. We climb up the rope and pull it up after us. Then no-one knows where we are. We play space-ships. At tea time we slide down fast and we are always first for tea.\r\n\r\nWhat would you say was the best name for that story?\r\n\r\nWho built the tree house?\r\n\r\nHow did the children always manage to be first for tea?\r\n\r\n\r\nBespoke Measure of Listening Comprehension. The stories used in this study were a series of books about a dog named ‘Harry’ written by Gene Zion. These stories were chosen as they were first published between 1956 and 1965 and so were suitable for this age group but the children were not likely to be familiar with them. The pictures from the stories were scanned then printed on A4 sheets and laminated to make a set of wordless picture books. The original text was retained for each story, however, small sections of some of the stories were omitted to try and keep each story the same length.\r\n\r\nTwo different types of questions were used in the bespoke measure of listening comprehension: literal and inferential questions. In the pre and post tests each child received eight literal questions and eight inferential questions after each story reading. The literal questions required the participants to recall facts from the text. The inferential questions tapped children’s ability to make inferences about information that was not stated explicitly in the text. These questions were designed to address: causality (why an event happened), emotions (how a character was feeling) and future events (what might happen next in the story). The Inferential questions in the pre and post test, however, consisted of four emotion and four causality questions as prediction questions could not be used at the end of the story. Table Three gives examples of literal and inferential questions used.\r\n\r\nTable 3. Examples of literal and inferential questions used.\r\n\r\nExtract\r\n\r\nQuestion\r\n\r\n1. Harry was a white dog with black spots who liked everything except having a bath. So one day when he heard the water running in the tub he took the scrubbing brush and buried it in the back garden.\r\n\r\n\r\n\r\nLiteral: What did Harry bury in the back garden?\r\n\r\nForced choice: the scrubbing brush/a sponge.\r\n\r\nCausal Inferential: Why do you think Harry buried the scrubbing brush in the back garden?\r\n\r\nForced choice: Because the family told him to/Because he did not want a bath.\r\n\r\n2. That night Harry slept in the dog house – again.\r\n\r\nLiteral Question: Where was Harry made to sleep again? In the Kitchen/in the dog house.\r\n\r\nEmotion Inference Question: How do you think Harry felt about sleeping in the dog house?\r\n\r\nForced choice: happy/sad.\r\n\r\n\r\n3. (After a sequence of events that lead to Harry being covered in seaweed and thinking the hot dog man was calling his name.) Harry still thought the man was calling his name. He barked and jumped with joy. He jumped so much that suddenly…\r\n\r\nLiteral Question: (before - he jumped so much…) What was the hot dog man really shouting? Hurry/Harry\r\n\r\nPrediction Inferential question*: What do you think happened next?\r\n\r\nForced choice: Everyone ran away/ the seaweed fell off him.\r\n\r\n\r\n*Please note. These were only used during the intervention sessions.\r\n\r\nMaterials: Intervention\r\n\r\nThree of the stories were used for the intervention sessions. Scripts were produced that incorporated the questions for the intervention sessions during the stories. In the inferential intervention group there were four of each question type: causal, emotion and prediction. The inferential and literal questions were always placed at the same point in the story.\r\n\r\nProcedure\r\n\r\nPhase One: Pre-test. Children in all groups completed the general listening comprehension measure and the bespoke measure of literal and inferential comprehension. Each child was tested individually in a quiet space away from the classroom. The pre-test session was audio and video recorded. The video recorder was set in front of the participant to capture their direction of eye gaze. The experimenter explained the task to the child and obtained verbal consent. In the pre-test the experimenter asked the child if they had heard any stories about Harry the dog while showing them the front cover. One child reported recognising the story, but could not remember any details.\r\n\r\nGeneral Listening Comprehension Measure. Each participant was read two stories, the first acted as a practice task to help develop rapport. Immediately after each story the children were asked the comprehension questions for that story. If a child could not answer a question then the experimenter offered the correct response and moved onto the next question. If the child gave the incorrect answer then the experimenter did not highlight that this was incorrect but simply moved onto the next question. The decision to respond to answers in this way was based on the pilot of the procedure. This age group seemed to become easily disengaged if they supplied no answer on a number of occasions or incorrect answers and it was felt that this way of responding helped to maintain their confidence and interest in the task. Responses were scored as correct or incorrect. Acceptable answers were provided in the NARA manual.\r\n\r\nBespoke Listening Comprehension Measure. After the assessment of general listening comprehension each child completed the bespoke listening comprehension task. The experimenter read out the story whilst the child followed the pictures in a wordless picture book version. At the end of the story sixteen questions were asked: 8 literal and 8 inferential, of which four were causal and four were emotion related. If the child could not answer a question or gave the wrong answer then s/he was offered a forced choice of two possible answers (examples in Table Three). One option was the correct target answer and one was incorrect. The forced choices were included in the pre/post test as they were also used during the intervention; however, answers based on a forced choice were not included in the analysis. In the pre and post-test if the child chose the correct response then the experimenter agreed with the child and moved onto the next question. If the child selected the incorrect option, the experimenter also continued with the next question. The decision was taken not to correct the child at this stage as if the child was still getting the answer incorrect despite assistance then giving them the correct answer may change the representation they had created of the story and also have an effect on their confidence as mentioned earlier. The forced choices were alternated so that the correct answer occurred equally in first and second positions across items. When scoring the responses if the child gave the correct answer unaided (i.e. without the forced choice option) then they were given one point. All other responses were scored zero.\r\n\r\nPhase two: Intervention (Intervention groups only). The intervention sessions took place the week after the selection phase, on three consecutive days. On each day, each child in the intervention groups was tested individually in a quiet space away from the classroom and the session was audio-recorded. Different stories were used in each session. As the stories were read to the participant they were asked questions (either literal or inferential depending on group assignment) about the story content. Children in the control group were not read to by the experimenter during this phase.\r\n\r\nLiteral Questions Intervention Group. Children in this condition were read one story in each of the three intervention sessions and asked twelve questions that assessed their understanding of explicit details in the story, e.g., ‘What did the lady next door sing louder than?’ The questions were positioned throughout the text and related directly to information that had just been given in the story. If the children gave no response or an incorrect response they were offered the forced choice. If a child still gave an incorrect answer after being given the forced choices then the experimenter corrected them and offered the correct answer. This was to try and ensure that the children were building accurate representations as they listened to the stories.\r\n\r\nInferential Questions Intervention Group. The same stories and question-response technique were used as outlined in the literal questions condition. Questions were also placed at the same position in the text, however, children in this condition were asked twelve inferential questions throughout each story that required them to think beyond the facts present in the text. In each story there were four causal inferential questions, e.g., ‘Why were Harry’s ears hurting?’ four prediction questions, e.g., ‘What do you think Harry did next?’ and four questions assessing understanding of the emotions of the characters. e.g., ‘How do you think Harry felt when the old lady told him to go away?’\r\n\r\nPhase three: Post-test. This session took place between five and seven days after the final intervention session and followed the same format as the pre-test. Children in all three groups completed the general listening comprehension story and the bespoke listening comprehension story with literal and inferential questions asked at the end of the story.\r\n\r\nMeasure of Engagement. The video recordings from the pre and post-test were analysed for the children’s level of engagement. This was only based on the child’s behaviour during the reading of the bespoke listening comprehension story. The coding scheme used for this analysis is shown in Table Four. A second rater scored 20% of the pre-test videos. There was 100% agreement between raters.\r\n\r\nTable 4. Coding scheme used to analyse level of engagement while listening to the bespoke story.\r\n\r\nCode\r\n\r\nDescription of Behaviour\r\n\r\n1\r\n\r\nLimited Engagement. The child appears off-task and makes a large number of unrelated comments or is distracted and looking away for a large part of the story reading.\r\n\r\n2\r\n\r\nEngaged- Quiet. The child looks at the pictures and listens well throughout the story but does not make any independent comments.\r\n\r\n3\r\n\r\nEngaged – Interactive. The child looks at the pictures and listens well throughout the story. They also make independent comments relating the events in the story to their lives/elaborate on the text/ ask questions about the text.\r\n\r\n\r\nGroup Assignment.\r\n\r\nScores on the pre-test measures were used to assign the children to groups to ensure an equal range of scores in each. One-way Analysis of Variance was carried out on the general comprehension scores, literal and inferential scores. All F<1.0 and all p>0.1. In addition, where possible, an equal number of boys and girls were assigned to each group. Table Five shows the ages, number of boys and girls and pre-test scores for each group.\r\n\r\nTable 5. Distribution of gender, age and pre-test scores across groups.\r\n\r\nVariable\r\n\r\nControl\r\n\r\nLiteral\r\n\r\nInferential\r\n\r\nGender Male\r\n\r\nFemale\r\n\r\n8\r\n\r\n6\r\n\r\n7\r\n\r\n7\r\n\r\n7\r\n\r\n6\r\n\r\nAge (years; months)\r\n\r\n5;5\r\n\r\n5;5\r\n\r\n5;4\r\n\r\nGeneral Comprehension (proportion)\r\n\r\n0.43\r\n\r\n0.46\r\n\r\n0.46\r\n\r\nBespoke Literal (max=8)\r\n\r\n3.79\r\n\r\n3.79\r\n\r\n4.15\r\n\r\nBespoke Inferential (max=8)\r\n\r\n5.0\r\n\r\n4.50\r\n\r\n4.77\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"863"},["text","Lancaster University"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"864"},["text","Pooley2010"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"865"},["text","John Towse"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"866"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"867"},["text","Project description"]]]],["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":"868"},["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":"869"},["text","Kate Cain"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"870"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"871"},["text","Cognitive Psychology"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"872"},["text","43 children (23 boys, 20 girls, mean age 5 years 4 months and range 4 years 9 months to 5 years 9 months) in their first year of primary school"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"873"},["text","Chi-squared\r\nMcnemar test"]]]]]]]],["item",{"itemId":"21","public":"1","featured":"0"},["collection",{"collectionId":"6"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"187"},["text","RT & Accuracy"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"188"},["text","Projects that focus on behavioural data, using chronometric analysis and accuracy analysis to draw inferences about psychological processes"]]]]]]]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"839"},["text","The Specificity of Inhibitory Impairments in Autism and Their Relation to ADHD-type Symptoms"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"840"},["text","Charlotte Sanderson"]]]],["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":"841"},["text","2010"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"842"},["text","Findings on inhibitory control in autism have been inconsistent. It is proposed that this may be partly task-related, with different ‘inhibition’ tasks tapping different classes of inhibitory ability. Thus, children with autism (CWA) (N = 31) and typically developing controls (TDC) (N = 28) matched for verbal and non-verbal mental age completed three tasks of inhibitory control, each representing different inhibition subcomponents: a Go/No-Go task (delay inhibition), the Dog-Pig Stroop task (conflict inhibition), and a Flanker task (resistance to distractor inhibition). Behavioural ratings of inattention and hyperactivity/impulsivity were also obtained for each child to consider a possible source of heterogeneity in inhibitory ability. It was predicted that the conflict task would be more problematic for CWA, and that higher ADHD-symptom ratings would predict poorer performance. On the Go/No-Go task, CWA showed superior inhibitory function to controls – making fewer false alarm errors and better task sensitivity. On the Dog-Pig Stroop, CWA showed impaired performance compared to controls – making more accuracy and speed related inhibitory errors. On the Flanker task, CWA showed equivalent inhibitory performance to TD children. Inhibitory impairments were predicted by high ratings of inattention in CWA, but only on the Dog-Pig Stroop. It is argued that CWA are perhaps impaired on tasks of conflict, but not delay or resistance to distractor inhibition. This may reflect the additional working memory demands of these tasks, and suggests that inhibitory difficulty is not a core executive deficit in autism. Symptoms of inattention may be an important predictor of inhibitory heterogeneity amongst CWA."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"843"},["text","inhibition\r\nStroop\r\nautism"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"844"},["text","Sessions were completed in a well-lit and quiet room, free of distractions. Participants were tested individually, and completed the three inhibitory control tasks (Go/No-Go task; Dog-Pig Stroop task; Flanker task) and two standardised measures (RCPM; BPVS) in counterbalanced order. Experimental session lasted approximately 40-60 minutes.\r\n\r\nAll three inhibition tasks were written using Psyscript, and run on a computer using an OS X 10.6 operating system.\r\n\r\n\r\nGo/No-Go Task\r\n\r\nTask Design.On each trial, a shape (O, ∆, ⧠, or ◊) would appear centrally on the computer screen. The shapes were simple black line-drawings, subtending approximately 5° vertically and horizontally. Prior to the task, children were instructed to respond to three of the shapes by pressing a large external “star” button (i.e. “Go” stimuli), but to resist responding to a fourth shape (i.e. the “No-Go” stimulus). The shape designated as the “No-Go” stimulus was counterbalanced between participants. To generate a prepotent response, 75% of trials were “Go” trials requiring a button press, and 25% of trials were “No-Go” trials where the response should be withheld.\r\n\r\nThe maximum inter-stimulus interval (ISI) (i.e. from stimulus onset to stimulus onset) was 2500ms. At the start of each trial, a fixation cross would appear at the centre of the screen for 200ms. This was then replaced by the stimulus, which remained on-screen for 200ms. After the stimulus offset, participants had a further 1000ms to respond, at which point the trial automatically terminated. Stimulus presentation was followed by a 1100ms pause before the next trial commenced. An error tone (“bleep”) was played immediately if the child made an omission error (i.e. failed to respond on a “Go” trial), or a false alarm (i.e. pressed the star button on a “No-Go” trial). A positive feedback-noise (“ping”) was played if the participant made a correct response.\r\n\r\nProcedure. Before starting the task, each child completed a warm up session to familiarize with the “Go” and “No-Go” stimuli. Training was terminated only when the child could correctly identify the required response for each shape. Children then completed a short practice block of eight trials containing all four stimuli presented in a fixed, but superficially random order. Then followed 144 experimental trials split into three 48-trial blocks, each separated by a short break. Stimulus presentation was randomised throughout each half block to avoid clustering of “No-Go” trials. The task (including training) lasted approximately ten minutes.\r\n\r\n\r\nFour measures of task performance were obtained:\r\n\r\n1. Number of false alarms (or commission errors): “No-Go” trials on which the button was pressed. This is the main measure of inhibitory control, with false alarms representing failure to inhibit the prepotent button-press response.\r\n\r\n2. Number of hits: “Go” trials on which the child responded. This is not a main measure of inhibitory control performance, but indicates how reliably participants detect targets when present and suggest the strength of the prepotent response generated. Hit-rates are also used for calculations of task sensitivity (see below).\r\n\r\n3. Task Sensitivity: Estimates of participants’ task sensitivity can be calculated using signal detection theory (A0) and probability estimates of False Alarms and Hits. This permits differentiation between participants who make fewer false alarms, but also fewer hits (poor task sensitivity), and those who make fewer false alarms despite a good hit rate (good task sensitivity). This is important because a low false alarm rate could be due to a generally low response rate (for both “Go” and “No Go” stimuli). Task sensitivity (A0) is a nonparametric measure which ranges from 0.5 (chance performance) to 1 (perfect sensitivity), and is calculated as follows (Grier, 1971):\r\n\r\n\r\n\r\n\r\nA = 0.5 (H-FA) (1+H-FA) / [4H (1-FA)]\r\n\r\n\r\nWhere, H = probability (Hits), FA = probability (False Alarms).\r\n\r\n\r\n\r\n\r\n\r\n4. Hit Trial Reaction Time (RT): Although not a measure of inhibitory control per se, this might indicate between-group differences in processing speed and/or task-strategy.\r\n\r\n\r\nDog-Pig Stroop Task.\r\n\r\nTask Design. The stimuli used in this task were two simple line drawings of a dog and a pig (see Appendix 4). Stimuli were presented centrally on the computer screen, subtending approximately 6° vertically and 9° horizontally. Two experimental conditions, each containing 32 trials were administered. In the control (baseline) condition, children were simply instructed to say “dog” when they see the dog-image, and “pig” when they see a pig as quickly possible. In the Stroop (i.e. inhibition) condition, children were instructed to say \"dog\" to pig images, and \"pig\" to dog-images, as quickly and accurately as possible.\r\n\r\nChildren’s responses were recorded by an assistant during the task, and also audiotaped so that manuscripts could be subsequently checked by the experimenter. If a child made a mistake on a trial and then corrected themselves, their initial response was recorded. To estimate response latency on each trial, the experimenter would press a large external button as soon as the child made their initial response. Although this measure of reaction time is relatively crude, many of the children taking part would not have been testable with throat microphones which measure voice-onset. These technologies are highly sensitive to all sounds including subtle body movements, lip-smacks and vocalizations, reducing their reliability for use with participants who might have difficulty minimizing task-irrelevant movement or vocalizations. It is also notable that the additional error in reaction-time estimates induced by this method would be constant across groups.\r\n\r\nOn each trial, the stimulus remained centrally on-screen until a response had been registered (i.e. the response button had been pressed). If no response had been registered after 3000ms had elapsed, the trial automatically terminated, and the message “Too Slow” was presented for 500ms. Stimulus presentation was followed by a 2000ms pause (inter-trial interval) before the next trial commenced. The maximum ISI was thus 5500ms.\r\n\r\nProcedure. All children completed the control condition first to provide a measure of baseline picture naming speed and accuracy[2]. After the control condition had been completed, children were presented with training slides to familiarise them with the Stroop naming procedure. After successfully completing the four practice trials, children would commence the 32-trial Stroop condition block. The task (including training) lasted approximately 7 minutes.\r\n\r\n\r\nFlanker Task\r\n\r\nTask Design. For this computer task, children were presented with two large arrow-shaped buttons – one pointing left and one pointing right. There were three experimental conditions: baseline, congruent, and incongruent. Children were asked to respond by pressing the arrow-button pointing the same way as the white target arrow, which was positioned centrally, subtending approximately 4° vertically and 6° horizontally. On baseline trials, the white target arrow was presented on its own. On congruent trials, the white target arrow was flanked by four red ‘distractor’ arrows pointing the same way as the target (e.g. ààààà). On incongruent trials, the white target arrow was flanked by four red ‘distractor’ arrows facing in the opposite direction to the target arrow (e.g. ßßàßß). It is thus only on incongruent trials that the distractors must be actively inhibited/suppressed for correct target identification.\r\n\r\nThe maximum ISI was 2900ms. A fixation cross would appear centrally on-screen for 200ms. This was then replaced by the stimulus (neutral, congruent or incongruent), which remained on-screen until a button-press had been registered. If no response had been registered after 1200ms had elapsed, the trial automatically terminated. An error-tone (“bleep”) was played if the participant pressed the wrong arrow-button . If the child failed to respond before the trial terminated, an error-tone was played and a “Too-Slow” message was briefly displayed. When the child responded correctly, a positive feedback-noise was given (a “ping”). There was a 1100ms pause (inter-trial interval) between trials.\r\n\r\nProcedure. Each child first completed a series of familiarisation trials. This was followed by three blocks of 30 trials separated by a short break (90 trials in total). Each block contained ten baseline, ten congruent and ten distractor trials, which were distributed randomly. Error-rates and mean reaction times (RT) for neutral, congruent and incongruent trials were recorded.\r\n\r\n\r\n[1] Although a cut-off of 30-points is typically used with younger children, a slightly lower cut-off score is thought to be more accurate for use with older children/adolescents (Mesibov et al., 1989). This is due to the inclusion of one or two items on which older children with autism tend not to score highly (e.g. imitation).\r\n\r\n[2]Condition-order was fixed because a pilot study showed that if children completed the experimental (i.e. Stroop) condition first they had difficulty forgetting the ‘opposite’ rule in order to name the pictures normally for the control condition. This was shown by elevated error-rates and poorer naming speeds. Therefore, in order to obtain a realistic measure of ‘automatic’ (i.e. control-condition) picture naming speed and accuracy, and a stronger prepotent response, it was decided appropriate to fix the order of condition presentation (Control, then Stroop). Although this may lead to practice effects, this effect is constant across groups.\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"845"},["text","Lancaster University"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"846"},["text","sanderson2010"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"847"},["text","John Towse"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"848"},["text","Open"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"849"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"850"},["text","project description"]]]],["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":"851"},["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":"852"},["text","Melissa Allen"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"853"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"854"},["text","Developmental Psychology"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"855"},["text","Autism group. Thirty-five individuals with autism, aged between 6 and 18 years\r\nControl group. Thirty typically developing (TD) children, aged between 6 and 11 years, were recruited from three state primary schools "]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"856"},["text","ANOVA\r\nMANOVA\r\nChi squared\r\ncorrelation"]]]]]]]],["item",{"itemId":"20","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":"820"},["text","Factors Related to Burnout in Arab Social and Community Development Workers"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"821"},["text","Bshr Dayani"]]]],["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":"822"},["text","2017"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"823"},["text","The nature of social and community development work leaves the workers at the risk of experiencing burnout and emotional difficulties. The aim of this study was to explore the relationships between burnout and empathy, emotional dissonance, self-compassion and type of work (voluntary, paid) amongst social and community development workers. We hypothesised that high levels of empathy, high levels of self-compassion, low levels of emotional dissonance and fewer hours of paid work would be significant predictors of low levels of burnout. The sample consisted of 315 participants from Syria, Egypt, Lebanon, Jordan and Tunisia. Participants completed an online survey that includes the following measures: Maslach Burnout Inventory, Interpersonal Reactivity Index, Self-compassion Scale, and Emotional Dissonance Subscale from Frankfurt Emotion Work Scale. Correlation and regression analyses were performed to examine the relationships between the variables. The findings showed that empathy was not significantly correlated to burnout, however a positive correlation was observed between personal accomplishment and perspective taking. Self-compassion was strongly and negatively correlated with burnout. Emotional dissonance was negatively correlated with burnout, and it was the strongest predictor of burnout amongst the studied variables. Paid work hours were positively related to emotional exhaustion, depersonalisation and personal accomplishment while voluntary work hours were not related to any of burnout components. The present study indicates novel findings, and contributes to the literature by highlighting the key role of personal emotional regulation in predicting burnout amongst social and community development workers."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"824"},["text","personal emotional regulation\r\nburnout"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"825"},["text","Participants completed an online Qualtrics-based survey which includes the following four measures:\r\nBurnout. The scores of burnout were assessed by the Maslach Burnout Inventory Human Services Survey (MBI-HSS). The MBI-HSS is a 22-item self-reported measure that comprises three subscales: Emotional Exhaustion (9 items), Depersonalisation (5 items) and Personal Accomplishment (8 items). Emotional Exhaustion (EE) refers to the feeling of being drained emotionally and physically. Depersonalisation (DP) stands for the negative inordinately attitude towards job-related aspects. Personal Accomplishment (PA) refers to the feelings of efficiency, productivity and competence achievements in the job. (Maslach et al., 2001; Maslach, & Jackson, 1996). All answers are rated on a seven-point scale that ranges from 0 “never” to 6 “every day”. Subscales produce separate scores that are calculated as the following: for EE and DP scores the high scores represent high levels of burnout. For PA the high scores represent low levels of burnout (Maslach & Jackson, 1981).\r\nEmpathy. The scores of empathy were assessed by Interpersonal Reactivity Index (IRI) scale. The IRI is a multidimensional scale that has 28 items rated on a 5-point Likert scale that ranges from 1 “Does not describe me well” to 5 “Describes me very well”. The measure comprised of four 7-item sub-scales. Only three subscales were used for the study. These subscales are Perspective Taking (PT) which represents the ability to conceive the psychological perspective of others. Empathic Concern (EC) measures the feelings of warmth and compassion and towards others. Personal Distress (PD) looks into \"self-oriented\" feelings of stress and apprehension as a reaction to the miserable conditions of others (Davis, 1980). Previous studies have reported high levels of validity and reliability of the scale (Davis, 1983; 1994; Fernández, Dufey, & Kramp, 2011).\r\nEmotional dissonance. The scores of emotional dissonance were measured using the subscale of the Frankfurt Emotion Work Scale. This scale has been extensively validated, and it is a five-item Likert scale ranging from 1 (never) to 5 (always). A sample item is: “How often in your job do you have to display emotions that do not agree with your true feelings?” (Zapf, Vogt, Seifert, Mertini, & Isic, 1999). The Cronbach alpha for the scale was .848 (Kundu, S., & Gaba, 2017).\r\nSelf-compassion. The scores of self-compassion were measured using the Self-Compassion Scale (SCS)which consisted of 26 items rated on a 5-point Likert scale ranging from “Almost never” (1) to “Almost always” (5). The scale asks the participants on how often do they behave in the stated manner. An example statement is “I’m disapproving and judgmental about my own flaws and inadequacies”. The scale has six subscales: Self-Kindness, Self-Judgment, Common Humanity, Isolation, Mindfulness and Over-identified scales. The instrument has high inter-correlations between each of the six subscales, and it has an excellent internal consistency reliability and a good test-retest reliability. The coefficient alpha of the scale was .92 (Neff, 2003a).\r\nTo ensure the maximum validity of the responses, a safety question was added to each questionnaire to ensure that the respondent is paying attention and not providing random answers. A sample item “Some people might provide random answers for this survey, which effects the research results very negatively. Just to make sure that you are not answering randomly, please select the answer number 1 (Never). Thank you”. \r\nFor the purpose of the study, both Arabic and English versions were used in all the measures. The original language of the instruments was English. For the MBI-HSS the Arabic version was adopted from Hamaideh, (2011) who translated the entire instrument into Arabic and reported high internal consistency, the Cronbach’s alpha coefficient was .84 for the total scale, .91 for EE, .84 for DP and .88 for PA. For the current study, the internal consistency was .86. Emotional dissonance, IRI and self-compassion scales were translated into Arabic by a professional English/Arabic translator. Additionally, a backward translation was done by another professional English/Arabic translator, and the two versions were compared by the researcher. All the translated measures were accurate and correspondent with the original English scales. The translated forms reported high internal consistency which was calculated by the Cronbach’s alpha coefficient. The internal consistency was .86 for self-compassion, .76 for IRI and .70 for emotional dissonance.\r\nDesign \r\nThe study was comprised of one online Qualtrics-based survey that was sent to all the participants. Based on the study hypotheses the independent variable is burnout, and the dependent variables are self-compassion, empathy, emotional dissonance and type of work.\r\nProcedure \r\nEthical approval for the study was acquired from the ethics committee at Lancaster University. Participants were initially told that the study was designed to investigate what pressures do workers in social and community development field face, and how do they feel about their work, themselves, people they work with and others in general. The actual aim was hidden initially to ensure maximum genuine and unbiased answers. Information sheets included the study objectives, description of the measures and how much time each one takes, the confidentiality of the data, participation eligibility, the voluntary participation, and the researcher contact information. \r\nConsent forms were displayed on the online survey before the initiation of the measures. Additionally, debriefing forms were given to the participants following the completion of the survey. Debriefing forms stated the actual purpose of the study as well as the study design. The survey was completed within 20-30 minutes approximately.  \r\nAnalysis\r\nPearson’s Correlation and regression analysis were conducted to examine the study’s hypotheses. Regression analysis was chosen according to the nature of the variables which were continuous variables. Additionally, the number of paid and voluntary work hours were included as covariates, since dividing the participants into two groups (volunteers and workers) was not possible because most of the participants were doing both voluntary and paid work at the same time. All statistical analyses were conducted using IBM SPSS Statistics software (Version 23)."]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"826"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"827"},["text","data/SPSS.sav"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"828"},["text","Dayani2017"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"829"},["text","John Towse"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"830"},["text","Open"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"831"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"832"},["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":"833"},["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":"834"},["text","Elena Geangu"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"835"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"836"},["text","Social Psychology"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"837"},["text","366 responses were collected, 349 were valid responses after screening the safety questions (which are explained in the measures section). Responses from non-Arabic countries were excluded, and only 315 responses were considered for the study to ensure the maximum homogeneity of the sample. Participants were 226 (71.7%) from Syria, 25 (7.9%) from Egypt, 23 (7.3%) from Lebanon, 22 (7.0%) from Tunisia, and 19 (6.0%) from Jordan. The sample comprised of 315 participants, 119 of them were males (37.8%), and 196 were females (62.2%). "]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"838"},["text","Correlation\r\nregression.\r\n"]]]]]]]],["item",{"itemId":"18","public":"1","featured":"0"},["collection",{"collectionId":"8"},["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":"191"},["text","Ratings"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"192"},["text","Studies where participants make a series of ratings or judgements when presented with stimuli"]]]]]]]],["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":"781"},["text","The Decoy Effect on Choosing Branded and Non-Branded Alcohol-related Products"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"782"},["text","Wang Li"]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"783"},["text","alcohol purchasing\r\ndecoy effect "]]]],["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":"784"},["text","2017"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"785"},["text","The decoy effect describes a phenomenon that the introduction of a third choice, usually an asymmetrically dominated one, would change the distribution of people’s preferences for the original two options. Monk et al. (2016) found a basic decoy effect on alcohol purchasing decisions. Extending this, the current study examined the impact of the decoy effect on alcohol-related purchasing decisions and whether the addition of brand names would further impact this. A total of 106 participants were asked to make decisions amongst four types of branded and unbranded drinks by completing an online questionnaire. They also completed the AUDIT, assessing problem drinking patterns, and a measure of trait effortful control. Results showed that the decoy appeared to affect alcoholic relative to non-alcoholic drinks, and affected branded products more than non-branded products. The results suggest that the decoy effect might affect alcohol-related purchasing decisions differently to non-alcoholic purchasing decisions, which might have managerial implications for marketers and health implications for hazardous alcohol consumptions."]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"786"},["text","All the stimuli were pictures of bottles presented with text descriptions including the number of bottles and the total prices. Participants viewed a total of 80 deals, with 40 alcoholic products and 40 non-alcoholic products. Half of the products were branded and half unbranded. With regards to branded stimuli, pictures of bottles similar to those presented in supermarkets were shown (see Figure 2), whilst unbranded ones used similar unbranded bottles in terms of colour and shape. This allowed the products to correspond with both the diversity of goods in real supermarket but also to avoid unnecessary brand association (e.g. red glass bottles always remind consumers of Coca-Cola; Underwood, 2003). \r\nIn the control condition, participants were shown products with two options, one with less bottles but cheaper, and the other with a greater quantity of bottles but more expensive. As such, option 1 represented the competitor option, which was cost-effective, and option 2 represented the target option, which was moderately cost- \r\n\r\neffective. The order of cost-effective and moderate-cost effective products was randomised throughout the experiment. In comparison, the experimental conditions also included a decoy option, which presented a product that was the least cost-effective. Although the decoy option itself was unlikely to be selected, it was expected to result in a different distribution of selections from the output of the control group. The sequences of the choice A (cost-effective), B (moderate cost-effective), and the C (decoy) were set randomly.\r\nAlcohol Use Disorders Identification Test (AUDIT). This questionnaire was made up of 10-items concerning personal drinking habits, drinking frequency and amount (Saunders et al., 1993). On a scale of one to over 30, articipants responsed to the questions such as “How many units of alcohol do you drink on a typical day when you are drinking?” and a total AUDIT score was computed.  The scores of each question were accumulated and coded. The output of the AUDIT test showed great reliability of this study, M = 15.09, SD = 4.60, Cronbach’s α = .79. It should be noted that although the figure for the AUDIT test was way above eight which was  the hazardous cut-off, indicating a possible harmful alcohol use (Babor et al., 2001), this was in line with student’s drinking cultures in UK.\r\n\tAdult Temperament Questionnaire (ATQ). This questionnaire assessed self-reported effortful control (c.f., Evans & Rothbart, 2007) and comprised of 34-items, such as “When interrupted or distracted, I usually can easily shift my attention back to whatever I was doing before”. Participants were asked to answer the questions by selecting a 7-point Likert Scale (1 = extremely untrue, 7 = extremely true). Their responses were recorded and coded. A small amount of missing data (caused by unexpected errors on the web) was replaced by the mean of the sample on that specific item. The result of the ATQ test revealed internal consistency as well, M = 146.34, SD = 22.82, Cronbach’s α = .85.\r\nDesign and Procedure\r\n\tThis study conducted a 4 Stimuli (Beer, Cider, Orange Juice and Water) x 2 Brading (Branded vs unbranded) x 2 Selection (Cost-effectiveness vs. Moderate Cost-effectiveness) within-subjects research design, to examine the possible shifts of selections with the addition of the decoy. Participants were instructed to look at online supermarket choice sets and asked to make a choice out of two (control condition) of three product options (the experimental condition, with the decoy product added). At the beginning, they were asked to imagine that they were in a real supermarket, and they were told that their selections would be dependent on their own preferences. No other information was provided either in oral or on the screen in order to prevent demand characteristics. \r\nThe main questionnaire had 80 questions, consisting of 80 trials of stimuli (i.e., 20 trials for beer, water, orange juice, and cider). Also 40 groups of bottles were branded and the other 40 were non-branded. The main questionnaire comprised four web pages, with 20 questions in each page and took approximately 30 minutes to complete. Participants were allowed to take short breaks when they finished one page of questions. There was no time limit for each of the questions as the pressure caused by time constraints has been found to affect one’s decision-making process (Dhar & Nowlis, 1999). Subsequently, participants completed a self-report measure of hazardous drinking behaviour (AUDIT) and the effortful control scale (ATQ). These questionnaires were completed at the end of the experiment to make sure the alcohol-related behaviours were not primed (Monk et al., 2016). At the end of the experiment, participants completed a manipulation check to ensure that they were able to accurately distinguish the cost-effectiveness and the quantity of the products set and that they fully understood the requirements of this study. They were then asked to report if they had consumed alcohol on the day of testing, as alcohol consumption has been shown to affect decision-making and may therefore affect the findings of the experiment (Steele & Josephs, 1990). Therefore, participants who had consumed alcohol before participating in the test were excluded when analysing the decoy effect (n = 8). Finally, participants were fully debriefed after they had finished the whole experiment, and were informed about the true aims and hypotheses of the study."]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"787"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"788"},["text","data/ xlsx"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"789"},["text","John Towse"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"790"},["text","Open"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"791"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"792"},["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":"793"},["text","LA1 4YF"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"794"},["text","Li2017"]]]]]],["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":"795"},["text","Charlotte Pennington"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"796"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"797"},["text","Psychology of Advertising"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"798"},["text","106? participants were recruited. Thirty of them were male participants and 70 were females"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"799"},["text","ANOVA"]]]]]]]],["item",{"itemId":"17","public":"1","featured":"0"},["collection",{"collectionId":"11"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"987"},["text","Secondary analysis"]]]]]]]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"755"},["text","Persuasion within Advertising:  Metaphorical Expressions vs. Literal Expressions"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"756"},["text","Helen Vale"]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"757"},["text","Metaphor\r\nliteral\r\npersuasion\r\nadvertising\r\nmarketing\r\nfigurative language\r\nemotion\r\n"]]]],["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":"758"},["text","2015"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"759"},["text","The present research built upon research conducted by Citron and Goldberg (2014) on figurative language, emotion, and the brain. This study examined the three different data sets: sentences, stories and sentences with taste metaphors collected by Citron and Goldberg (2014).  It examined three different data sets: sentences, stories and sentences with taste metaphors. Metaphorical and literal sentences, stories and taste metaphors were rated on emotional valence, imageability, emotional arousal, metaphoricity and similarity in meaning. Familiarity was rated within sentences and taste metaphors and understandability and naturalness were rated within stories. This study explored relationships among variables, relationships between metaphors and literal counterparts, relationships between each data set and lastly, relationships between each data set when split by type: metaphor and literal. Findings from this investigation provide evidence for marketers, of the benefits of using metaphors within advertising to increase persuasion and consumer buying behaviour. A company who wants to portray imagination, develop images within a consumer’s mind and evoke emotional arousal should use metaphorical sentences within their advertisements. Additionally, the more arousing a sentence the more imaginable, therefore, marketers should specifically employ emotionally arousing material to further engage a consumer. This study can add to literature on figurative language and persuasion. Also, provide evidence for marketers who want to increase their sales and further persuade consumers with an effective approach"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"760"},["text","Lancaster University"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"761"},["text","John Towse"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"762"},["text","Open"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"763"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"764"},["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":"765"},["text","LA1 4YF"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"766"},["text","Vale2015"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"769"},["text","All metaphorical sentences and stories were created in German with words that would obtain a metaphorical interpretation. Then each word was replaced with its literal counterpart, which created: one hundred and twenty non-taste related sentences, sixty metaphorical “The bride was very moved by her wedding” and sixty literal “The bride was very happy about her wedding”. Sixty-four stories, thirty-two metaphorical “Lisa was sitting in her physics class and was still digesting the stuff from the lesson before when her teacher announced a task to bite your teeth out on.” and thirty-two literal “Lisa was sitting in her physics class and was still having problems with the stuff from the lesson before when her teacher announced a really difficult task.” Finally, seventy-four taste metaphors, thirty-seven metaphorical “She received a sweet compliment” and thirty-seven literal “She received a nice compliment”.\r\nSpecific instructions were created by Francesca Citron for each variable to be rated (See Appendix A). Sentences, stories and taste metaphors were rated on emotional valence, imageability, emotional arousal, metaphoricity and similarity in meaning. Emotional Valence refers to how positive or negative the stimulus is which was rated on a scale from -3 (very negative) to + 3 (very positive) through 0 (neutral). All other variables were measured on a scale of 1 to 7. Imageability is the ability to evoke a mental picture rated: 1 “not imaginable at all” and 7 “very imaginable”. Emotional arousal describes to what extent the stimulus is emotionally stimulating rated: 1 “not intense at all” and 7 “very intense”. Metaphoricity describes the figurativeness of the stimulus rated: 1 “literal” and 7 “very metaphorical”. \r\nLastly, similarity in meaning which refers to how similar the meaning of both metaphorical and literal counterparts are with regard to contents. For instance, the metaphorical sentence “He praised her to the skies” compared to the literal sentence “He praised her fulsomely”. These have the same meaning, thus the meaning similarity between metaphorical and literal sentence is high. This was rated 1 “not similar at all” and 7 “very similar/equal in meaning”.\r\nFamiliarity was rated within sentences and taste metaphors, which describes how familiar the stimulus is rated: 1 “not familiar at all” and 7 “very familiar”. Additionally, taste relatedness was measured for taste metaphors which refers to the extent a sentence is associated with degustation. It was rated as 1 “not taste-related at all” and 7 “very taste-related”. Lastly, understandability and naturalness were rated within stories. Understandability is about the easiness of grasping what the content means rated: 1 “very difficult to understand” and 7 “very easy to understand”. Naturalness is how normal and daily a story or its parts are rated: 1 “not natural at all” and 7 “very natural”.\r\nTo evaluate complexity, several measurable parameters were created. For each parameter one “complexity point” was given, therefore, creating one overall complexity score.  For all data sets all 9 characteristics were the same: subordinate clauses, relative clauses, passive forms, compound nouns, appearing persons, adverbs and adverbial phrases, conjunctive forms, analytically-formed tenses/infinitive constructions and marked/deviating structure of sentence. For sentences and taste metaphors alone the number of words was also a characteristic and within stories the number of metaphors. (See Appendix B).\r\n\r\nProcedure\r\nParticipants were each provided with a consent form to sign if they agreed to partake in the study. Once completed, participants were provided with a URL via E-mail to access the questionnaire. General instructions were shown first, followed by the specific instructions for the first variable to be rated. The words were then presented, each one at the centre of the page immediately followed by the 7-point scale. When all words had been rated for one variable, instructions for the next variable rating appeared. The order of variables were random for each participant. This procedure was the same for all sentences, stories and taste metaphors. \r\n\r\nData Analysis\r\nAll the means and standard deviations were calculated and used for the analyses for all sentences, stories and taste metaphors. Independent sample t-tests were then used to look at the differences between metaphors and literal counterparts of each variable within the three data sets. When there was a specific hypothesis a one tailed t-test was implemented however, when there was no hypothesis a two tailed t-test was applied. \r\nNext, the variable emotional valenced squared was computed to represent the quadratic relationship between all other variables and then used within the following data analyses. Firstly, a multiple regression was then used to analyse any quadratic or linear relationships between emotional valence and other variables within each data set. In each regression, features of no interest were partialled out by entering them as predictors in the first step; then valence and valence squared entered in the second step. Additionally, partial correlations were conducted within each data set to look at linear relationships between pairs of variables within metaphors and literal counterparts by controlling for other variables. Lastly two types of analyses of variances were conducted, firstly, one-way between subjects ANOVAs to look at the difference between datasets: sentences, stories and taste and their impact on emotional arousal, imageability, emotional valence and metaphoricity. Then one-way between subjects ANOVAs to look at the differences between datasets when split by type, metaphors and literal counterparts and their impact upon variables."]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"780"},["text","The rating data had been gathered already by Francesca Citron during her research in Berlin and ethical approval had been obtained at that time. The present study has been approved by the Department’s Research Ethics committee at Lancaster University."]]]]]],["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":"767"},["text","Francesca Citron"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"768"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"770"},["text","Psychology of Advertising"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"771"},["text","Sentences were rated by thirty-five males and seventy-eight females aged between twenty-one and sixty-seven (M = 35 years, SD = 12.23 years). Stories were rated by fifty-nine males and one hundred and forty-two females aged between seventeen and seventy-eight (M = 36 years, SD = 15.00 years). Lastly, taste metaphors were rated by seven males and nineteen females aged between twenty-two and seventy-four (M = 27 years, SD = 4.9 years). All participants were native German speakers from the Berlin area. "]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"772"},["text","t-tests\r\nregressions\r\ncorrelations\r\npartial correlations"]]]]]]],["tagContainer",["tag",{"tagId":"3"},["name","Secondary analysis"]]]],["item",{"itemId":"16","public":"1","featured":"0"},["collection",{"collectionId":"8"},["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":"191"},["text","Ratings"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"192"},["text","Studies where participants make a series of ratings or judgements when presented with stimuli"]]]]]]]],["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":"684"},["text","Cortical Hyper Excitability correlating with Visual Distortions and Hallucinations"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"685"},["text","Nishtha Bakshi"]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"686"},["text","visual distortions\r\ncortical hyper excitability\r\nPattern Glare Task"]]]],["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":"687"},["text","2017"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"688"},["text","Background: The primary focus of our study is how the abnormalities in the visual experiences such as the visual distortions or hallucinations result in the increase in the cortical hyper excitability. The aberrant neural activity causes visual distortions. Susceptibility to such visual distortions reflects elevated levels of cortical hyper excitability. \r\nMethods: Forty-eight individuals completed the \"Pattern Glare Task\" (where they viewed certain striped grating patterns with different spatial frequencies). Participants also completed the Cortical Hyperexcitability Index (Chi) and the Cambridge Depersonalization Scale (CDS). \r\nResults: Pattern glare task showed that individuals experienced more visual distortions in the Medium Frequency (3 cpd). A very small sample of the population showed effects of depersonalisation disorder. Based on our results, we can say that individuals did show an elevated level of cortical hyperexcitability. \r\nConclusion: The study suggests that non-clinical population also experiences a certain level of increase in cortical hyper excitability. It only establishes the utility of pattern glare with regards to CHi and CDS to add to our existing knowledge."]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"689"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"690"},["text","Data/data spreadsheet.xlsx"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"691"},["text","John Towse"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"692"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"693"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"694"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"695"},["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":"696"},["text","LA1 4YF"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"738"},["text","Bakshi2017"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"779"},["text","Pattern Glare Test\r\nThe pattern glare task includes stripy patterns on three separate cards each with different spatial frequencies; low spatial frequency baseline grating (approx. 0.5 cycles per degree), high spatial frequency baseline grating (approx. 12 cpd), and the crucial medium spatial frequency grating (approx. 3 cpd). The computerised version of the pattern glare task was modified for this experiment, as we were using a paper-based version (Wilkins, 1995; Wilkins et al., 1984) for the same. The stimuli used in the experiment are given in FIGURE 1. The individuals are asked to stare at the white dot in the center of each pattern for approximately 10-15 seconds, while holding each pattern at arm's length. Following, a series of questions are asked to the participant i.e. if they experienced any blurring of lines, bending of lines, fading, shimmering, flickering or shadowy shapes. The participants on the basis of their experience on viewing each pattern, rate the above questions from a score of 0-7 where, 0-minimum and 7-maximum (Wilkins et al., 1984; Conlon et al., 1999). The score is obtained for each pattern and the difference between Pattern 2 and Pattern 3 is recorded, which is called as the '3-12 difference'; in other words, the difference between high frequency and the medium frequency (3cpd – 12cpd). \r\n Cambridge Depersonalisation Scale\r\nThe CDS is a self-reporting questionnaire and is used to measure the duration and frequency of any depersonalisation symptoms that individual experiences in the time frame of the past six months. (Sierra and Berrios, 1999). The CDS is an instrument containing 29 items. Each of the items in the scale are rated on the basis of Likert-scale both for frequency (0-4; where, 0=never, 1=rarely, 2=often, 3=very often, and 4=all the time) and duration based on its average on how much the experiences last (1-6; where 1=few seconds, 2=few minutes, 3=few hours, 4=about a day, 5=more than a day, and 6=more than a week). Its global score is the sum of all items (0-290). Sierra et al., (2005) established four well determined factors to dictate the different symptoms of depersonalisation as single or underlying dimensions they were, ‘Anomalous Body Experience’, ‘Emotional Numbing’, ‘Anomalous Subjective Recall’, and ‘Alienation from Surroundings.’ This questionnaire addresses the complexity of depersonalisation and uncovers its symptoms, which can be directed towards distinct psychopathological domains. \r\nCortical Hyperexcitability Index\r\nThe CHi was designed to provide an index that discovers the visual irritability, discomfort and the associated visual distortions that individual’s experience (Braithwaite, Merchant, Dewe and Takahashi, 2015). The above-mentioned experiences are well linked to the increase of cortical hyperexcitability. A major advantage of the CHi’s design is that it unveils three broad factors which are (1) heightened visual sensitivity and discomfort, (2) negative aura-type visual aberrations, and (3) positive aura-type visual aberrations. The items present in the questionnaire picture a vast selection of visual experiences that have been previously reported through hallucinations based experimental studies on patients, control groups, non-clinical populations; aura and its underlying dimensions. The CHi uses a fine-grained 7-point Likert response scales, where in the test each question has two response scales i.e. frequency (1-7; where 1=not at all frequent and 7=very frequent) and intensity (1-7; where 1=not at all intense and 7=extremely intense). In terms of scoring, both the scales are summed to provide an overall CHi index for each question. However, a value of 1 is subtracted from each response on frequency and intensity, as the scale was transformed from 1-7 to a 0-6 Likert-scale. This was done for individuals who responded with 1 in every question would still have a score of 54. \r\nDesign and Procedure\r\nAll the participants were forwarded a brief explanation about the purpose of the study and how they can contribute to it. If the participants agree, later schedule a time for the voluntary study. The experiment was conducted in the Social Hub of the Graduate College, Lancaster University. The participants were seated comfortably on the right side of the researcher. The individuals were asked to read the Participant Information sheet carefully, later if they agree; they may sign their respective consent form. It was made clear to the participants that the confidentiality of their personal information will be ensured and that they could at any point (1) can ask questions during the experiment, (2) stop the experiment, if they are uncomfortable at any point during the conduction (3) participants have the right to withdraw themselves from the study with no further adverse consequences however, they need to inform the researcher about this via email. Participants were again asked if they suffered from any neurological disorder specially migraine, migraine (aura), or photo sensory epilepsy and if they had any severe incidences of alcohol and drug abuse. The first phase of the experiment included the pattern glare task. Individuals were handed over with the first pattern with low frequency (LF) and were asked to stare at the white dot in the centre of the pattern for 10-15 seconds. After this, they were asked to rate the questions based on their experience on a scale of 0-7 (0-minimun, 7-maximum). The questions included if they experienced any blurring of lines, bending of lines, shimmering or flickering, fading or if they could see any shadowy shapes. Before handing over the second pattern, it was made sure that the participant is comfortable with proceeding further with the experiment and is not experiencing any kind of visual stress. The same steps were repeated for both the other two patterns with medium frequency (MF) and high frequency (HF). The order in which the participants viewed the patterns was randomised for each one of them. Individuals who are prone to pattern glare can be quantified for such a criterion based on their sum of distortions in 3cpd (MF) or as the difference between 3 and 12 cpd, also called the '3-12 cpd difference'. After a two-minute break, the second phase of the experiment included participants to answer 29 questions on the Cambridge Depersonalisation Scale, which are based on the frequency and duration of any 'strange or funny experiences' that they felt in the past six months. Lastly, the third phase, the second questionnaire was introduced to the participants. The Cortical Hyper Excitability Index. Similar to the patterns, the questionnaires presented to the participants were also randomised in order to obtain a variety in the responses of the participants. The total time taken to conduct the experiment was about 20 minutes or less. Post conduction the individuals were thanked for their time and effort.  "]]]]]],["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":"739"},["text","Jason Braithwaite"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"746"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"747"},["text","Perception"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"748"},["text","n=48"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"749"},["text","correlation\r\nfactor analysis"]]]]]]]],["item",{"itemId":"15","public":"1","featured":"0"},["collection",{"collectionId":"9"},["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":"499"},["text","Behavioural observations"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"500"},["text","Project focusing on observation of behaviours.\r\nIncludes infant habituation studies"]]]]]]]],["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":"644"},["text","Four-Dimensional Ultrasound Analysis of Fetal Independent Oculomotor Control"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"645"},["text","Amy Jane Cunliffe-Penman"]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"646"},["text","Four-dimensional Ultrasound Imaging\r\nFetal Visual Development\r\nThird Trimester\r\nLight Stimuli\r\nIndependent Oculomotor Control"]]]],["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":"647"},["text","2017"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"648"},["text","This dissertation seeks to enhance the present understanding of elicited fetal independent ocular-motor control during late gestation. Independent ocular-motor control refers to the ability to more the eyes independently from the head when fixating on a visual stimulus. Whilst there is a wealth of information regarding fetal visual development and responsiveness to light stimulation, there is a paucity of research investigating elicited fetal visuo-motor abilities. Therefore, the current research aims to utilsise four-dimensional ultrasound imaging to view fetal responsiveness when exposed to a custom-made light source. To assess fetal independent ocular movement, light was presented through the maternal abdomen (N=54) towards the peripheral of the fetal head to elicit directed purposeful eye and head movements. Ultrasound scans were recorded and later coded for frequency of eye and head movements at each stage of light exposure (before, during and after light). The primary experimental hypothesis suggested that the fetus would exhibit independent ocular-motor control when exposed to a light stimulus and that, the fetus would produce behavioural responses more often during light stimulation, than in the absence of light stimulation. Analysis of results indicated that the fetus was able to make independent, directed ocular movements towards stimuli during late gestation. Eye movements were more frequent during and after light exposure, in comparison to before light exposure. Head movements were more common during light exposure; however, head movements were more commonly performed by the fetuses than eye movements overall. The results suggest that the fetal visual system maybe more advanced than previously thought and may provide clinical implications, as independent ocular movement may be utilised as a neurological diagnostic tool"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"649"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"650"},["text","data/SPSS.sav"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"651"},["text","John Towse"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"652"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"653"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"654"},["text","English"]]]],["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":"655"},["text","LA1 4YF"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"656"},["text","CunliffePenman2017"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"778"},["text","Experimental Design\r\nThe study employed a repeated-measures, within-subjects design, in which one sample of participants were exposed to a light stimulus and assessed for behavioural responses before, during and after light exposure. The independent variable manipulated light stimuli presentation time (before stimulation, during stimulation and after stimulation). The dependent variable measured the frequency of behavioural responses (head movements and eye movements) elicited at each stage of light exposure. The participants were counterbalanced in regards to the presentation of two forms of light exposure (constant beam and intermittent beam, described below) to avoid the introduction of confounding variables and reduce the possibility of order effects.\r\nThree extraneous variables were identified however; this included maternal abdominal thickness, fetal positioning and external room illumination. Maternal abdominal thickness was controlled for by first assessing maternal thickness before the experimental procedure and then altering the light strength dependant on this factor. Therefore, if the thickness was greater, a stronger light strength would be used to ensure light reached the fetal retina in accordance to Del Giudice’s (2011) model of light penetration. There were three different light strengths employed within this study, as will be discussed below. \r\nFurthermore, fetal positioning was considered an extraneous variable as the location of light exposure on the maternal abdomen was dependant on the fetus’s position within the womb. To ensure light was presented to the same location for each participant, an initial examination was conducted to determine the orientation of the fetus. Then, the light source was positioned towards the peripheral of the fetus head. Conducting this initial examination increased research validity as each fetus experienced the light similarly and was able to perform horizontal eye and head movements.\r\nLastly, external room illumination was an important factor to consider, as if the room was not dark, it was possible the light stimulus would not have had an experimental effect. Room illumination was controlled for by conducting the experimental procedure only in complete darkness to ensure no other light could reach the fetus and influence fetal responsiveness. \r\nMaterials\r\nLight Stimulus. The light stimuli employed within the current study was a customised, ethically approved light source which emitted light at 650nm. The light stimulus was specially constructed to ensure extraneous variables, such as light strength and maternal thickness, could be controlled for. The stimulus was assembled using a custom-made semiconductor laser torch. The torch was created with a triangular shape at the end, which included three dots, each distanced 15mm apart. Three dots were used to provide a smaller light guide, as this has been described to provide better fetal response rate (Dunn et al, 2015). Utilising Del Giudice’s (2010) model of light penetration, the light source was adjustable to ensure 0.1-1% of light reached the fetus and was within the range of the fetal visual system. In addition, red spectrum lumen levels were used, as this wavelength penetrates tissue most successfully when compared to other colour spectrums (Dunn et al., 2015). An advantage of employing red spectrum wavelengths means lower levels of light can be presented, without reducing the amount of light reaching the fetal retina. \r\nAn important component of the light stimulus was the ability to alter light strength depending on maternal abdominal thickness. More specifically, the light was calibrated at output optical powers of 0.5mW, 1mW or 5mW for thickness (t) below 1.5cm, between 1.5cm and 3cm and above 3cm. To control for variations in light stimulation in regards to maternal thickness, and to ensure a constant level of light was experienced by every fetus, dependent optical powers were delivered. \r\nUltrasound Machinery. Observations of eye and head movements were recorded during experimental ultrasound scans, located at either Cumbria University Medical Imaging Unit or Blackpool Victoria Hospital. At Cumbria University Medical Imaging Unit, a GE Healthcare Voluson iBT07 4D live ultrasound scanner and 4D probe, model RAB4-8-RS was used. Also, at Blackpool Victoria Hospital using a GE Healthcare Voluson E8 Expert BT13 advanced 4D HD live ultrasound scanner and 4D probe, model RM66. The ultrasound recordings were streamed onto a laptop during the scans and then saved on to an external hard drive, which contained no previous data. The external hard drive was used for coding of eye and head movements offline, at a private location on Lancaster University campus. \r\nProcedure \r\nOn arrival at one of the two medical clinics, either located at Blackpool Victoria Hospital or Cumbria University Medical Imaging Unit, the participant was greeted by a researcher and taken into a room containing an ultrasound imaging machine. The participant was introduced to the sonographer and then asked to remove all items of clothing covering the abdomen and to lie down on a medical bed. When the participant voiced their comfort, the sonographer proceeded in applying a lubricating jelly to the area of examination on the abdomen. The lubricating jelly was used to ensure smooth movement of the probe against the skin during the ultrasound scan. The sonographer then placed the probe onto the abdomen and began the first 2D ultrasound scan to assess the maternal tissue thickness (in millimetres) and to determine the fetal head position. \r\nThese assessments were undertaken to inform the experimenter of where the light stimulus should be presented and the strength of the light needed, in order to reach the fetal retina. Tissue thickness was measured from maternal skin to uterine wall and ranged between 1cm and 5cm thick. Del Guidice’s (2010) model of light penetration was employed to determine the strength of light needed. During the ultrasound assessment and experimental procedure, the 3D and 4D scans were broadcasted simultaneously to both the ultrasound machine and a laptop which recorded the scans onto an external hard drive. Once it was concluded, there were no fetal abnormalities and the light strength and fetal orientation had been established, the participant was asked to remain motionless to preserve image acuity and light source position. The lights in the room were then switched off, and the experimental study began.  The custom-made light source was presented to the participant’s abdomen, showing a three dotted red light in two stages of light exposure. The times in which the light source was turned on and off, as well as the minutes measured, were noted and recorded by the experimenter on a data collection sheet and were controlled using a digital stop watch. The two stages of light exposure were randomised between participants to counterbalance the sample and reduce order effects. When the experimenter was ready to switch on the light source and begin testing, they would signal the sonographer so that both the 4D scan recording, the light source, and stopwatch were all started at the same time. In the first stage of light exposure, light was presented to the fetus in a constant stationary beam for 3 minutes, presented to the periphery to the side of the fetus. There was then a break period between the two stages of light exposure, to allow the participant, sonographer, and researchers to readjust their positions. The second stage of light exposure consisted of 10 intermittent beams of light, in which timing between each light beam was again controlled by an experimenter using a digital stopwatch. This stage of light was created according to the procedure of Johnson and Morton (1991), in which a light stimulus was slowly presented to the fetus along the arc of a protractor. The light was presented at a rate of around five degrees per second when the fetal head was positioned on the protractor mid-line at zero degrees. Therefore, the present study decided the second form of light would be presented to the side of the fetal head and then moved away from the head position horizontally across the abdomen for approximately five seconds, at a rate of 1 centimetre per second. After the assigned five seconds, the light source was temporarily switched off and the 4D scan turned to a 2D scan for around 20 seconds, following which the 5 second light exposure would then begin again. As aforementioned, this stage was repeated 10 times over a 3 minute period. On completion of both stages of light exposure, the experiment was finished, and the participants were thanked for their cooperation. Each scan recording ranged from between 8 to 22 minutes, corresponding to safety standards (Harr, 2011). All recordings were saved onto a specific file on an external drive and stored in a filing cabinet in the Lancaster University Psychology Department. The hard drive was kept separate from the light presentation times and mothers personal details, which were stored elsewhere in the department to retain maximum confidentiality and security. \r\nData Coding \r\nData was gathered from the participants by recording and coding 4D ultrasound real-time videos for fetal movements in response to a light stimulus. Consequently, a specific coding process needed to be established to certify all researchers were coding matching responses and ensuring research validity. The ultrasound recordings were coded using an external hard-drive and Mac computer. During a research team meeting, the experimenters agreed on four specific behavioural responses that would be coded for, before stimuli, during stimuli, and after stimuli.  Coding for before stimuli was conducted for only the first three minutes before the first light exposure stage began, meaning if light stimulation began at eight minutes on the ultrasound recording, only five minutes onward would be coded for potential ‘before stimuli’ movement. The short break between the two light exposure stages was coded as after stimuli, despite additional stimulation being presented after a short interval. A timed approach was decided as the fetus had previously been exposed to light, therefore, possible continued fetal activation could influence behavioural response. Initially, the researchers observed several scans to better understand the procedure and to examine the characteristics of the data, in which four behaviours were clearly demonstrated. These four behaviours were used as the categories for coding movement. The first response was named ‘head movement, with eye movement’; the second response was ‘head movement, eyes move first’; the third response was ‘head movement, cannot depict eye movement' and the fourth response was ‘independent eye movement’. An excel spreadsheet was used to code the frequency of behavioural responses in three columns, before, during and after stimuli. Within these columns were a further four columns with each of the four possible behavioural responses. When a movement was observed, the participant number and time was noted in a row and a number one was placed in the corresponding behavioural column located on the same row.  \r\nTo reduce subjectivity during coding it was agreed that eye movements were to be coded when the probe was stationary and the light stimulus (displayed as a white dot on the 2D image scan) moved in any direction over the abdomen. Head movements were coded only when the centre position of the head moved clearly either right or left and up or down. This is important as the fetus often made small movements or moved their limbs, which may cover and/or reposition the head. Such movements could be confused with a singular head movement; therefore, only centre position movements were included in the coding data sheet. In addition, other non-fetal movements the researchers needed to be aware of included movement of the probe, as the probe was occasionally moved to gain greater image acuity. To identify this, the researchers agreed that the surrounding environment in utero must remain motionless as the head moves, such as the line representing the edge of the maternal uterus wall. Similarly, this rule was implemented when the mother breathed, as the fetus can appear to move, potentially causing further coding confusion. Thus, fetal head movements were only included in the data set if the external image was unmoving.\r\nData Reduction\r\nData clearing was conducted in an effort to increase internal research validity. Participant data was not submitted for behavioural coding if the fetal position could not be established or clearly seen during the ultrasound procedure. Visual acuity was particularly important during the experiment to determine where the light stimulus would be presented, therefore, if the fetal position was not clear, the light could not be accurately exposed to the peripheral of the fetus. Additionally, 12 individuals were later excluded from data analysis, as when coding for behavioural responses, the fetus was inactive and showed no movements. Inactivity meant a lack of any fetal actions available during behavioural coding, considered a sleep state in the fetal behavioural literature, therefore, the data was not included in the overall analysis."]]]]]],["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":"750"},["text","Vincent Reid"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"751"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"752"},["text","Developmental Psychology"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"753"},["text","Fifty-four participants were recruited, consisting of healthy pregnant women with singleton healthy fetuses"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"754"},["text","Wilcoxon Signed-Ranks test"]]]]]]]]]