["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=6&sort_field=added","accessDate":"2026-05-03T05:12:51+00:00"},["miscellaneousContainer",["pagination",["pageNumber","6"],["perPage","10"],["totalResults","148"]]],["item",{"itemId":"84","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"42"},["src","https://www.johnntowse.com/LUSTRE/files/original/c9e19b6f17b8828625b24445f16fd9a7.doc"],["authentication","a92b0ed9a4b24fba744c78d2798af442"]]],["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":"1933"},["text","Academic Resilience: Adversity and traumatic experience in an educational context at university"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"1934"},["text","Astthor Odinn Olafsson"]]]],["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":"1935"},["text","2018"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1936"},["text","Resilience is a process whereby individuals bounce back or beat the odds despite the significant threat that can jeopardise their development. Academic resilience pertains to student´s success after educational adversity and their coping behaviour in challenging circumstances. Recently academic resilience became a validated psychological construct, and the present study uses this Academic Resilience Scale (ARS) to measure students response to academic adversity in a university sample with three analysis. The primary analysis: estimated the Life Event Checklist (LEC) or traumatic experienced and academic resilience which is unresearched. The findings indicated that students´ who have experienced a traumatic life event(s) and stressful situations are showing slightly more academic resilience than those who have not experienced a traumatic life event and stressful situations. A second analysis: academic resilience in a relationship with the life event, brief resilience, self-esteem, self-efficacy, perceived stress, and academic performance. Both self-efficacy and brief resilience predicted academic resilience. Third analysis: same parameters from the second analysis was utilised but now in a relationship with traumatic experienced and displayed that traumatic students had a more tendency for brief resilience, self-efficacy, self-esteem but perceived more stress than nontraumatic student´s. These results show that the academic resilience could be used as an intervention in the educational environment to enhance student´s coping behaviour and facilitate them to adjust more effectively in challenging circumstances."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1937"},["text","academic resilience\r\n traumatic experience\r\nresilience\t\t\t                   nontraumatic experience\r\n stress\r\n self-esteem\r\n self-efficacy\r\n   academic performance"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"1938"},["text","Participants\r\n\tThe sample was based on an internet survey of 154 Lancaster University students from 29 different nationalities who enrolled either as an undergraduate at first year (n = 47), second year (n = 49), third year (n = 30), Master student (n = 19) or PhD student (n = 3). Subsequently, five participants were excluded because of not being a student. The final sample contained 149 participants between the ages of 18 and 52 years old (M = 21.21; SD = 3.66). Majority of participants ethnicity was 51.6% British, 10.5% Chinese, 3.3% Indian, 2,6% South Korean and 2.6% Cypriot and other nationalities were in the minority. The principal investigator was not able to obtain gender because of a technical problem.\r\nMaterials\r\n     Academic Resilience Scale-30 (ARS-30) \r\n\tARS-30 (Cassidy, 2016), measures academic resilience and is developed to estimate university students. Participants answer 30 statements of an imaginative vignette where a comment or feedback from a tutor about a low grade on an assessment that was presented. Participants imagine themselves being in that position and their response is confined to a statement: \r\n„You have received your mark for a recent assignment, and it is a ‘fail.’ The marks for two other recent assignments were also poorer than you would want as you are aiming to get as good a degree as you can because you have clear career goals in mind and don’t want to disappoint your family. The feedback from the tutor for the assignment is quite critical, including reference to ‘lack of understanding’ and ‘poor writing and expression,’ but it also includes ways that the work could be improved. Similar comments were made by the tutors who marked your other two assignments.“\r\n\t Responses were on a 5-point Likert scale 1 (very likely) to 5 (very unlikely). Items include, “ I would not accept the tutors´ feedback”; “I would just give up”; and” I would blame the tutor.” Following the guidelines provided by Cassidy (2016), 9 of the items were reverse-coded (e.g., “I would not accept tutors´ feedback”). The author of the scale report high internal consistency (Cronbach´s alpha = 0.90). The ARS-30 has a theoretical range of 30-150, with higher scores indicating greater academic resilience (Cassidy, 2016). The internal consistency of ARS-30 in the current study was (Cronbach's alpha = 0.85).\r\n     Life Event Checklist-17 (LEC-17)\r\n\tLEC-17 (Blake, Weathers, Nagy, Kaloupek, Charney, & Keane, 1995) is a measure of traumatic experiences and stressful situations which range from single stressful life experience to aggregates across multiple incidents. Participants respond to 17 items on 5-point nominal scale 1 (happened to me) 2 (witnessed it) 3 (learned about it) 4 (not sure) and 5 (does not apply). Example of questions, “Natural disaster (for example, flood, hurricane, tornado, earthquake)”; “Assault with a weapon (for example, being shot, stabbed, threatened with a knife, gun, bomb)”; “Sudden, unexpected death of someone close to you.” The measurement is usually used in a clinical setting to assess PTSD (Gray, Litz, Hsu, & Lombardo, 2004).\r\n\t In the present study, the measurement is merely utilised to examine if participants have experienced traumatic and stressful situations. Other than that, internal consistency of recent studies (Bae, Kim, Koh, Kim, & Park, 2008) is (Cronbach alpha = 0.66), LEC-17 also shows external reliability from r = .44 to r = .55, suggesting significant correlation with other measures that assess traumatic experiences and stressful situations in supporting of the scale´s construct validity (Gray, Litz, Hsu, & Lombardo, 2004). The internal consistency of LEC-17 in the current study was (Cronbach´s alpha = .90). \r\n\tSubsequently, the life event variable was divided into two variables (1 = Traumatic and 2 = Nontraumatic). Previous studies assigned participants who scored 1 (happened to me) as only traumatic individuals and 0 was assigned if any other responses option was endorsed and recorded as nontraumatic individuals (Gray et al., 2004). In the current study, participants who responded to 1 (happened to me) and 2 (witnessed) were combined as traumatic based on the effect of witnessing a traumatic event; it can not be ruled out how intense and excessive this experiences might be (American Psychiatric Associations, 2013). On the other hand, participants who based their responses on 3 (learned about it), 4 (not sure) and 5 (does not apply) was registered as nontraumatic.\r\n     \r\n     Brief Resilience Scale-6 (BRS-6) \r\n\tThe resilience of participants was assessed with the BRS-6 and participants responded to 6 items on a 5-point Likert scale ranging from 1 (Strongly disagree) to 5 (Strongly agree), on items such as “I tend to bounce back quickly after hard times”; “It does not take me long to recover from a stressful event”, and “I tend to take a long time to get over set-backs in my life.” Three items were reverse-coded (e.g., “I have a hard time making it through stressful events”) to follow the structure of prior studies. The internal consistency of (Cronbach alpha 0.80-0.91). A higher score indicating greater resilience (Smith, Dalen, Wiggins, Tooley, Christopher & Benard, 2008). The internal consistency of BRS-6 in the current study was (Cronbach´s alpha = 0.39).\r\n    Rosenberg Self-Esteem-10 (RSE-10)\r\n \tSelf-esteem was measured with RSE-10 (1965) by evaluating both positive and negative feeling about the self. Participants answer ten items on 4-point Likert scale 1 (Strongly agree) to 4 (Strongly disagree). Example of items are, “On the whole, I am satisfied with myself”; “I feel I do not have much to be proud of”; “I take a positive attitude toward myself.” Five items were reverse-coded (e.g., “At times I think I am no good at all”). Reported (Cronbach's alpha = 0.84-0.86) (Tinakon & Nahathai, 2012). A higher score indicates greater self-esteem. The internal consistency of RSE-10 in the current study was (Cronbach´s alpha = 0.87). \r\n     Student Self-Efficacy-10 (SSE-10)\r\n\tSelf-efficacy was assessed with SSE-10 which is an estimation of the student´s belief in their capabilities to carry out, organise and perform a task successfully. The previous study by (Rowbotham & Schmitz, 2013) used a different way to measure with a four-point response format 1 (Not at all true) to 4 (Exactly true). Participants in the current research respond to 10 items on 4-point Likert scale 1 (Strongly agree) to 4 (Strongly disagree). Item example, “ I am convinced that I am able to successfully learn all relevant subject content even if it is difficult”; When I try really hard, I am able to learn even the most difficult content”; “I know that I can stay motivated to participate in the course.” Reported (Cronbach´s alpha = 0.84), and external r = .70 reliability and implying that students self-efficacy correlates significantly with similar measures of self-efficacy showing construct validity (Martin & Marsh, 2006; Cassidy, 2016). Scores ranged from 10-40 with higher scores representing higher student self-efficacy (Rowbotham & Schmitz, 2013). The internal consistency of SSE-10 in the current study was (Cronbach´s alpha = 0.85).\r\n     Perceived Stress Scale-14 (PSS-14)\r\n \tPerceived stress was evaluated with PSS-14 which is a measure of stress quite general and consequently relatively free of content specific to any sub-population group. Participants respond to 14 items on 5- point Likert scale 0 (Never) to 4 (Very often). Related items are, “In the last month, how often have you been upset because of something that happened unexpectedly?”; In the last month, how often have you felt nervous and “stressed”?”; In the last month, how often have you felt that you were on top of things?”. Following the guidelines provided by Cohen, Kamarck & Mermelstein (1983), seven items were reverse-coded (e.g. “In the last month, how often have you felt confident about your ability to handle your personal problems”). Internal consistency of  previous studies is between (Cronbach´s alpha  = 0.70) (Lee, 2012) and (Cronbach´s alpha = 0.82) (Andreou, et al., 2011). A higher score indicates greater stress. The internal consistency of PSS-14 in the current study was (Cronbach´s alpha = 0.82).\r\n     \r\n\r\n     Academic Performance\r\n\t Academic performance derives from average grade from each participant, undergraduates at first year provided merely two marks at the second year and master students provided only part 1 mark. Both undergraduates at a second and third year offered part 1 mark and part 2 mark. These average grades were combined and used as a measure of their academic performance. Not all participants gave permission for obtaining their average grades, but hundred and three participants approved this inquiry. The undergraduate at first year with part 1 mark was (M = 62.6; SD = 10.0) and part 2 mark was (M = 71.9; SD = 2.33). The undergraduate at second year with part 1 mark with two participants was (M = 63.0; SD = 8.56 and part 2 mark (M = 63.5; SD = 9.42). The undergraduate at third year with part 1 mark was (M = 62.6; SD = 6.41) and part 2 mark (M = 63.7; SD = 7.05). Masters mark with merely part 1 mark (M = 68.7; SD = 5.41). The combination of these marks are measured as Academic Performance (See Table 1.).\r\n    Cronbach alpha threshold\r\n\t\r\n\tEach questionnaire met Cronbach alpha level or internal consistency where the criterion is at .70 or above (Nunnally & Bernstein, 1994), apart from Brief Resilience which showed (Cronbach´s alpha = 0.39), even though will not be excluded.\r\nProcedure \r\n\tThe methodology was pre-registered before data collection (see Appendix 1). After a review and approval from Lancaster University´s Psychology Department´s Research Ethics committee, the study commenced. Hundred and fifty-four participants were collected and answered an internet survey on Qualtrics (2018) but were reduced to a hundred and forty-nine. Participants were immediately informed of the purpose of the study without revealing the research hypothesis to prevent social desirability or to avoid demand characteristics. Participants were also enlightened that their data will be anonymised and treated as confidential and only used to understand who has taken part in the study. In the following, participants were given an explanation of possible risks in two measures, and for ethical issues, participants were told in advance that they would be asked about whether they have experienced any traumatic or difficult life events. For example in LEC-17 questions like “sexual assault (rape, attempted rape, made to perform any type of sexual act through force or threat of harm” among other questions in relation to recalling of events that were related to traumatic experience and could cause some inconveniences. Second, PSS-14 with a question such as “in the last month, how often have you been angered because of things that happened that were outside of your control?” could cause some inconveniences also in association to antecedent stress or stress that the participant perceived at the moment. \r\n\tParticipants were made aware that participating in the study is entirely voluntarily and informed about the rights to withdraw at any time during the study without being penalised or being in debt to the Lancaster University by any means. Participants were also informed about the benefit of participating in the survey by contributing to a better understanding of academic achievement and how different events can affect the academic process (See Appendix 2). Therefore, after participants agree to participate in the study, the demographics were obtained such as which university participants study at, if participants responded to at Lancaster University, they were asked for permission of acquiring their average grade with dichotomous yes and no. Then records of age, nationality, student status (Undergraduate 1,2,3 year, Master, PhD, Other or Not a student), and what major they are studying (See Appendix 4). The participants were approached at the university campus regardless of locations and responded to six measurements with 87 items on an Ipad owned by the principal investigator(See Appendix 5,6,7,8,9,10). \r\n\tIn the debrief part of the research, participants were informed about the purpose of the study and the study hypothesis along with short details of the literature behind this review. Additionally, contact information such as the principal investigator or supervisor if any questions were provoked afterwards about the research itself or anything related to the process of the study. If participants wish to discuss with someone outside of the study, information about the head of the Psychology department was also tangible. \r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"1939"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1940"},["text","data/SPSS.sav"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"1941"},["text","Olafsson2018"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"1942"},["text","Ellie Ball"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"1943"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"1944"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1945"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1946"},["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":"1947"},["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":"1948"},["text","Dr Neil McLatchie"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"1949"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"1950"},["text","Developmental Psychology"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"1951"},["text","149 participants"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"1952"},["text","Correlation\r\nLinear regression"]]]]]]]],["item",{"itemId":"85","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"43"},["src","https://www.johnntowse.com/LUSTRE/files/original/fd8beba4d36cf77f159a4790ff0ed220.pdf"],["authentication","b212f6caefe48528fc1d7661f8ab8278"]],["file",{"fileId":"87"},["src","https://www.johnntowse.com/LUSTRE/files/original/fe8a70579aa21f555d3941edb7ad0146.csv"],["authentication","2816070da63c5db57305fb3aedcf7cae"]],["file",{"fileId":"88"},["src","https://www.johnntowse.com/LUSTRE/files/original/fecb178b57c68a834ab4ddb2bf3da9af.pdf"],["authentication","835d6a6191486c38d5fddc010858179a"]]],["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":"1953"},["text","Influence of an autobiographical memory recollection on moral decision making.\r\n"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"1954"},["text","Sandra Andrasiunaite\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":"1955"},["text","2018"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1956"},["text","Research shows that emotional states are involved in moral reasoning and may affect\r\npeople’s decision-making processes (Achar, So, Agrawal, & Duhachek, 2016).\r\nHowever, in recent research emotional states were shown to be easily influenced by\r\nsuch factors as the language type. It was found that a stimulus presented in the native\r\nlanguage was perceived more emotionally when compared to stimuli presented in the\r\nsecond language (Pavlenko, 2005). This difference in emotionality was called the\r\nlanguage effect (Puntoni, S., Langhe, & Van Osselaer, 2009). The relationship\r\nbetween used language (native vs. second) and emotionality level is important as it\r\nmay provide potential applications in promoting beneficial decision making and\r\nconsequent behaviour. Many advertising campaigns already target emotions (i.e.\r\nempathy, guilt, regret) in order to persuade people to act by their request (Lee,\r\nAndrade, Palmer, 2013). Thus the focus of this research was to analyse the\r\nrelationship between emotional language processing (native vs. second language)\r\ntargeting guilt, empathy levels and how they influence the consequent behaviour (i.e.\r\nhelping). A multicultural sample of 126 bilingual adults, who all speak English, as a\r\nsecond language, completed an online questionnaire, assessing self-reported guilt,\r\npro-social behaviour inclination, empathy and pro-social behaviour. Results showed\r\nthat no significant differences were found between two language groups, indicating\r\nthe lack of language effect in the present sample. Also, the results showed that high\r\nlevels of self-reported guilt were significantly and positively associated with high\r\nlevels of pro-social inclination and pro-social behaviour. Empathy was shown to have\r\nthe same association – high levels of empathy being associated with high levels of\r\npro-social inclination and pro-social behaviour. Lastly, further analysis found selfreported guilt as a predictor of pro-social behaviour and pro-social behaviour\r\ninclination. Overall, this study contradicted the previous research on the language\r\neffect, but at the same time, it supported the relationship between guilt and pro-social behaviour. Based on current findings and consideration of potential limitations, future\r\nresearch could examine the emotional language processing and its’ influence on\r\nbehaviour by targeting specific two languages and presenting text adverts as an\r\nemotional stimulus in order to control more variables and to increase applicability."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1957"},["text","The language effect\r\nemotional decision making\r\n guilt\r\nempathy\r\n pro-social behaviour"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"1958"},["text","Participants\r\nParticipants of this study were adults, who spoke English as a second language (N=\r\n126, 58 males, 68 females) and ranged in age from 18 to 46. Originally there were\r\n138 participants, but 12 were excluded from further analysis due to being the native\r\nspeakers of the English language and therefore not fitting the core requirement –\r\nspeaking English as a second language. Also 10 participants wrote the memory in\r\nEnglish instead of their native language, so they were diverted to the second language\r\ncondition before proceeding with the analysis. The whole sample of participants was\r\nvery diverse, which consisted of 25 different nationalities and 24 different native\r\nlanguages (see Appendix D), the top four languages being - Lithuanian (40), Spanish\r\n(14), German (13) and Polish (13). All participants signed an online consent form and\r\nanswered questions about their nationality, native language, country of residence, and\r\nEnglish language proficiency before proceeding with the questionnaire.\r\nMaterials\r\nSelf-reported guilt\r\nSelf-reported guilt was measured by asking participants to first – recall and describe a\r\nmemory in either their native or second language (i.e. English) and then to evaluate\r\nhow bad they feel about their recalled actions, how guilty they feel about those\r\nactions and how much they regret them (Nelissen, 2012). All of the three questions\r\ntesting self-reported guilt were assessed by 6-point forced choice Likert scale from 1\r\n(‘Very much’) to 6 (‘Not at all’). Before the start of analyses, the scale was reverse\r\nscored from 1 (‘Not at all’) to 6 (‘Very much’) to ensure consistency with other\r\nmeasures.\r\nPro-social behaviour\r\nThe pro-social behaviour was measured by asking participants, how many additional\r\nquestions they would be willing to answer after completing the survey. Participants\r\nwere informed that they are almost done with the survey. However, it was stated, that\r\nit would be a great help to the researchers if participants could answer some\r\nadditional questions from a different survey. Participants were provided with a choice\r\nto answer from zero to 10 questions, after completing the original survey.\r\nConsequently, willingness to answer the higher number of questions was perceived as\r\nan indication of higher pro-social behaviour.\r\nPro-social behaviour inclinations\r\nPro-social behaviour inclination was measured using a set of five moral dilemmas\r\nfrom the research done by Zhang, Chen, Jiang, Xu, Wang, and Zhao (2017). This measure tested how much a person is inclined to display helping behaviour. The\r\nanswers to these moral dilemmas were assessed by a forced choice Likert scale from\r\n1 (‘Strongly disagree’) to 6 (‘Strongly agree’), which was changed from the original\r\n7-point Likert scale to ensure consistency with the measures of the present study.\r\nAlso, some moral dilemmas were adapted by changing mentioned currency from yens\r\nto pounds in order to make dilemmas more relatable for mostly UK based\r\nparticipants. A sample of the item measuring pro-social behaviour inclination is:\r\n‘Your school’s foundation is raising money for children from poor areas. The money\r\nwill be used to buy textbooks and writing materials for the children. You have 100\r\npounds to spare. Are you willing to donate the money to the student?’\r\nEmpathy\r\nEmpathy was assessed by using The Short 3 Factor Version of Empathy Quotient\r\n(Muncer & Ling, 2006). The empathy measure consisted of 15 items, with a choice of\r\nanswers assessed by a forced choice 6 point - Likert scale from 1 (‘Strongly\r\ndisagree’) to 6 (‘Strongly agree’). The original measure was provided with a 4 point\r\nLikert scale (1-strongly disagree, 2- disagree, 3- agree, 4- strongly agree), but it was\r\nchanged for the current research into 6 points Likert scale in order to ensure\r\nconsistency with other measures and provide a wider range of answers. Seven items\r\n(6, 7, 8, 9, 12, 13, 14) of this empathy measure were reverse scored before the start of\r\nanalysis to ensure its’ reliability and validity. A sample of the item measuring\r\nempathy is: ‘I am quick to spot when someone in a group is feeling awkward or\r\nuncomfortable.’\r\nProcedure\r\nThis study received the ethical approval from the Psychology Department Research\r\nEthics Committee of Lancaster University.\r\nThe hypotheses, method and analyses of the current study were preregistered before\r\nthe collection of participants has started. The whole information about the study will\r\nbe available on the Open Science Framework page.\r\nParticipants were recruited using social media platforms like Facebook and Instagram\r\nand in person, inviting people to complete the survey online. The survey was\r\ndistributed using an anonymous link, which directed to a Qualtrics page of the survey.\r\nParticipants were presented with an information sheet and the consent form and only\r\nafter signing it, they were allowed to proceed with the questionnaire. At first,\r\nparticipants were asked to provide some general information about themselves such as\r\nage, gender, nationality, English language proficiency and country of residence.\r\nParticipants were then randomly allocated to an experimental condition (native\r\nlanguage, second language). Then they were requested to recall a memory, when they\r\ncaused someone harm and felt bad about it. They were asked to recall and describe\r\nthis memory either in English or in their native language at random. Participants in\r\nthe native language condition were asked to recall the memory in their native\r\nlanguage. Participants in the second language condition were asked to recall the\r\nmemory in English. After providing the memory, participants were asked to evaluate\r\nhow bad, guilty and regretful they feel about their recalled actions. Afterwards, they\r\ncompleted the measure of pro-social behavior, by indicating how many additional\r\nquestions they would be willing to answer after the current survey ends. The last part\r\nof the survey consisted of five moral dilemmas assessing pro-social behaviour inclination (see Appendix A) and the measure of empathy (see Appendix B). Overall,\r\nthe survey took approximately 15 minutes to complete. At the end of the survey,\r\nparticipants were presented with a debrief sheet, explaining the aims and the\r\nimportance of this research (see Appendix C).\r\n "]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"1959"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1960"},["text","Data"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"1961"},["text","Andrasiunaite2018\r\n"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"1962"},["text","Ellie Ball"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"1963"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"1964"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1965"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1966"},["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":"1967"},["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":"1968"},["text","Dr Neil McLatchie\r\n"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"1969"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"1970"},["text","Social Psychology"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"1971"},["text","126 Participants"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"1972"},["text","Correlations\r\nt-test\r\nANOVA\r\nmultiple regression"]]]]]]]],["item",{"itemId":"86","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"44"},["src","https://www.johnntowse.com/LUSTRE/files/original/7ce02be67f9a2fd035ce8a9537a1b05a.doc"],["authentication","712e09db491c09bbaea294160206917b"]]],["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":"1973"},["text","Figurative language comprehension and links to autistic traits "]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"1974"},["text","Anamarija Veic"]]]],["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":"1975"},["text","2018"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1976"},["text","Figurative language is used quite frequently in both speech and writing, as to express our creative and abstract thoughts. Traditionally, it was thought that metaphors are ornamental in nature, as well as they are used rarely compared to literal language. However, today’s research suggests that people use metaphors in everyday communication. Moreover, people seem to pay more attention to sentences which are emotionally evocative, rather than neutral ones. In addition, it has been extensively reported that socio-communicative skills might be related to the successful comprehension. Special populations, such as autistic individuals, often struggle with both figurative language comprehension and acknowledging properly other people’s emotions. However, no prior research has explored both different types of sentences and their content (emotional or neutral). Sixty-two participants took an online questionnaire measuring their comprehension abilities and the Autism-Spectrum Quotient (AQ) test, in order to measure their socio-communicative skills. Significant results were found for both the type of sentences, and the content. No significant effect of socio-communicative skills affecting comprehension was found. The results are discussed in terms of their theoretical and clinical importance."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1977"},["text","figurative language\r\ncomprehension\r\n emotions\r\nautism"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"1978"},["text","Participants\r\n\tSixty-two typically developed participants (M=31, F=31) between the ages of 18 and 62 (M= 24, SD=9.32) were got involved in the study. The majority of sample were students at Lancaster University (N=51). Participants were recruited in Lancaster (United Kingdom) via SONA or email. Twenty-nine participants were paid £5 (five British pounds) for taking part in the study. The remaining participants were not re-imbursed for their time. Only the adults (minimum age of 18) who were British English native speakers could have taken part in this study. Participants were not aware of a true aim of the study. Participants were simply told that the project is about figurative language comprehension, as to avoid any possible bias. At the end of their participation, they were informed about the details and the aims of the study.  The study has been approved by the ethics committee.\r\nApparatus and materials\r\n The participants were asked to complete an online questionnaire developed with the Qualtrics survey software. Upon recruitment, participants were sent a Qualtrics link to the survey. All participants were exposed to the same stimuli but each of them got a different randomised order. Approximately ten minutes were sufficient for participants to take part in the study. Participants could start answering the questionnaire and then finish it at another point of time if needed, as their answers were automatically saved for seven days after they opened the questionnaire on their browser. No more than 10 sentences were shown per page, as to avoid fatigue. \r\nBoth literal sentences and novel metaphors used as stimuli in this project were originally structured by Cardillo, Schmidt, Kranjec, and Chatterjee (2012). Their aim was to construct a design of matched metaphoric and literal sentences as to test the role of novelty and different metaphor types involved in metaphor comprehension. The authors managed to control the next ten dimensions: dimensions: length, frequency, concreteness, familiarity, naturalness, imageability, figurativeness, interpretability, valence, and valence judgment reaction time. What makes these sentences even more different than previous work is the fact that the same word was used in both literal and novel metaphors. As such, literal sentences and novel metaphors were further analysed and selected in a laboratory by Francesca (my supervisor) Citron’s students. The students selected the stimuli based on existing value of valence and imageability, so that sentences from different condition would differ in emotional valence, but not in the imageability. Conventional metaphors were structured by the same students, as well. Students created simple sentences which contained similar structure as the existing ones. Yet, it was not possible to use the same word as from literal sentences and novel metaphors, so conventional metaphors were a bit more diverged. The content of sentences was controlled in a way that half of the sentences were positive, and another half of them was neutral, so that their level of imageability would have been similar to novel metaphors and literal sentences. \r\nFinally, for the current research, the conventional metaphors were edited as to make them shorter to be more alike to both literal sentences and novel metaphors. The length was calculated and analysed statistically, for both the content and the types of sentences. There was no significant difference neither between the number of words nor the number of letters, both regarding the content and the types of sentences, p>.05. It is important to note that the current study did not replicate what Cardillo, Schmidt, Kranjec, and Chatterjee (2012) already explored since their main interest was to investigate neural processes underlying metaphor meaning. \r\nThe questionnaire consisted of 120 short questions such as ‘To which extent do you understand this sentence?’ containing one type of a metaphor expression (e.g. ‘The woman dove into the pool.’). Participants were required to rate the ease of the comprehension on a scale from one (‘It does not make any sense at all.’) to five (‘It makes perfect sense.’). The questionnaire included 20 sentences of each of the following groups, which are presented in the Table 1.\r\nThe Autism-Spectrum Quotient (AQ) \r\nThe AQ test was used at the end of the questionnaire. It is a self-report measure of autistic traits and presents a valuable instrument for rapid quantifying where any given individual is situated on the continuum from autism to normality (Ruzich et al., 2015).  The test was constructed by Baron-Cohen, Wheelwright, Skinner, Martin, and Clubley (2001) since no prior instrument at that time could have measured such factor. It can be administered to adults of at least average intelligence with autism or to nonclinical controls but can also be administered to clinical control groups (e.g., individuals with depression) (Ruzich et al., 2015). The AQ consists of 50 questions assessing five different areas: social skill, attention switching, attention to detail, communication, and imagination. Thus, participants’ scores could range between 0 and 50. Approximately half the items were worded to produce a “disagree” response, and half an “agree” response. This was to avoid a response bias either way. Following this, items were randomized with respect to both the expected response from a high-scorer, and with respect to their domain (Baron-Cohen, Wheelwright, Skinner, Martin, & Clubley, 2001). \r\nDesign and procedure \r\nThe dependent variable was the ease of figurative language understanding. The within-participants independent variables were type of a sentence (conventional, novel, and literal) and content (positive or neutral). Conventional metaphors represent expressions commonly used in everyday setting, whereas novel metaphors were made up for this occasion. The between-participants independent variable was the degree of autistic-like traits (either high or low). To obtain this latter variable, participants were divided into two groups based on their AQ scores. The median score was used to split them. Participants were instructed to rate their understanding of metaphors in 120 sentences. There were 20 sentences of each type × content (e.g., conventional positive) (see Appendix A).  Thus, six different mean scores were calculated for each participant (conventional positive, conventional neutral, literal positive, literal neutral, novel positive, novel neutral).The Likert scale consisted of five points (1-‘It doesn’t make any sense at all’, 2-‘It doesn’t make much sense’, 3- ‘It makes some sense’, 4- ‘It makes sense’, 5-‘It makes perfect sense’). The following coding rules were applied to calculate the AQ score: “definitely agree” or “slightly agree” responses scored 1 point on items number 1, 2, 4, 5, 6, 7, 9, 12, 13, 16, 18, 19, 20, 21, 22, 23, 26, 33, 35, 39, 41, 42, 43, 45, 46. “Definitely disagree” or “slightly disagree” responses scored 1 point on items number 3, 8, 10, 11, 14, 15, 17, 24, 25, 27, 28, 29, 30, 31, 32, 34, 36, 37, 38, 40, 44, 47, 48, 49, 50 (see Appendix B). Subsequently, the AQ scores were divided in two groups based on the median score (Med = 19.5). Any results above the median threshold were categorised as high, and those below were categorised as low. Half of the sample (N = 31) scored high, while the other half (N= 31) achieved a low score. Results were analysed using a 3x2x2 mixed analysis of variance (ANOVA).\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"1979"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1980"},["text","Data/SPSS.sav"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"1981"},["text","Veic2018"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"1982"},["text","Ellie Ball"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"1983"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"1984"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1985"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1986"},["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":"1987"},["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":"1988"},["text","Francesca Citron"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"1989"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"1990"},["text","Clinical Psychology\r\nCognitive Psychology\r\nPsycholinguistics"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"1991"},["text","62 participants (31 males and 31 females)"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"1992"},["text","Mixed ANOVA"]]]]]]]],["item",{"itemId":"87","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"48"},["src","https://www.johnntowse.com/LUSTRE/files/original/45545dfd8470a68ec670a3f57154c126.doc"],["authentication","40410c80ef34bc41f0b1784cd5ffca00"]]],["collection",{"collectionId":"4"},["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":"183"},["text","Focus group"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"184"},["text","Primarily qualitative analysis based on forming focus groups to collect opinions and attitudes on a topic of interest"]]]]]]]],["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":"1993"},["text","Exploring Guilt Appeals "]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"1994"},["text","Mridhula Ravi"]]]],["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":"1995"},["text","2015"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1996"},["text","Guilt appeals are commonly used in charity advertising as a means of persuading a consumer to donate. This qualitative study uses an Indian sample to understand if there exists any differences in how they are perceived by individuals in a society that is not guilt based. Participants were exposed to 5 advertising campaigns in a focus group interview. The research also seeks to understand other factors that persuade a consumer to donate. It was found that guilt was only a supplementary factor in persuasion and factors of personal relevance and focus of action played a larger role in persuading with the sample used in this research. Guilt was effective in changing the attitude and beliefs of a consumer, but it was the factors of personal relevance and ease and convenience that were influential in changing donation intention into charitable behaviour. However, the small sample is also a limitation in generalising the responses to an entire culture.  "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1997"},["text","None"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"1998"},["text","The purpose of this research was to understand the effectiveness of charity advertisements using guilt appeals in an Indian sample. Content analysis was then used to find patterns and themes in the responses of the participants. \r\n\r\nResearch Design\r\n\r\nFocus Group Interviews\r\n\r\nSince the research aimed to create a narrative of the participants opinions and views, focus groups were employed. Focus groups also enable for understanding and exploring a topic in depth and understanding the nuances of the thoughts and opinions of the participants and thus understand how they respond to guilt appeals.\r\n\r\nInterviewer\r\n\r\nThe primary researcher was used as the interviewer on the basis of being well versed with the material and thus the quality of establishing rapport and guiding the focus group discussion. \r\n\r\nDiscussion Guide\r\n\r\nThe primary aim of this research was to understand the perception of guilt appeals in charity adverts and the factors used in the adverts that contribute to donation intention. A discussion guide was formulated in line with the aim of the research and to provide a structure to the direction of the interview. Some of the questions included: ‘How do you feel when you look at this advertisement’, ‘The advertisements intend to use guilt. Do you think that was effective’ and ‘Did you feel guilty when you were exposed to the advertisements?’  (See Appendix A). However the questions were not asked in order and were chosen based on the responses chosen by the participants.  \r\n\r\nParticipants\r\n\r\nA focus group with 7 participants was organised. All the participants were Indian by nationality and graduate students of Lancaster University. Of the 7 participants. There were 5 males and 2 females. The only criteria for choosing the sample was that they had to have lived in India for at least 10 years or identify as an Indian national The age of the participants ranged from 20 to 25 years old. There was no difference by gender and gender was not considered as a variable in this research. \r\n\r\nMaterials\r\n\r\nFive advertisements were used in this research to understand guilt appeals. \r\n\r\nThe advertisements chosen for this study were for causes ranging from child labour, poverty and housing for the poor. To bring some diversity into the advertisements, both online and billboard poster advertisements were used. The people in the advertisements also belonged to different race and age groups to understand if these factors played a role in the effectiveness of the advertisements to both groups. The last advertisement (Shelter) also alluded to shame and I was interested in understanding how this added variable would influence the participants evaluation. \r\n\r\nThe advertisements were chosen from the internet and have been used as part of ad campaigns. The basis for choosing the advertisements was the framework used by Huhmann and Brotherton (1997): \r\n•\tThe presence of comparison between the well-being of the consumer and the other\r\n•\tPlacement of responsibility in the consumer\r\n•\tA call to action to the consumer which will aid the cause, failing which the affected group’s misfortune will prolong \r\n•\tExistence of violation of personal moral standards of the consumer\r\nThe five advertisements below were used in the research can be found in Appendix A, B, C, D and E. \r\n\r\n\r\nProcedure\r\n\r\nParticipants were recruited for the interviews through messages on Social Networking Sites such as Facebook and WhatsApp. A remuneration of 7 pounds was promised for participation and the interview was conducted in the library of Lancaster University. Participants then signed consent forms and were shown the adverts. \r\n\r\nThe advertisements were shown consecutively, with participants providing their opinion on each advertisement before proceeding to the next. Questions were then asked regarding the advertisements and discussed. Finally, participants were debriefed about the nature of the research and paid. \r\n\r\nEthical Standards\r\n\r\nThe research conformed to the Market Research Society’s guidelines. Participation was voluntary and participants were asked to sign consent forms prior the interview. Participants were made aware that their voice would be recorded prior to the start of the interviews. However, for the purpose of anonymity, their names were not used in the study. The participants were also provided with the choice to opt out of the interviews at any given point should they wish to.  \r\n\r\nResults Section:\r\n\r\nThis research sought to understand the effectiveness of guilt appeal adverts in Indians and to understand their perceptions of the advertisements and campaigns. The factors in guilt appeals that contribute to a successful advert was also studied. The following results section has been organised in order of the five adverts shown in the interviews to participants and the responses are accounted. Some common themes found in the responses are also discussed following the responses. \r\n\r\nResponses to the first advert by People in Need (Appendix A) ranged from a participant feeling that the advert was a “sarcastic attempt” and trying to “make a parody of the poor living situation” of the model and his surroundings to claiming that “They are trying to sell the aftershave” “They are trying to show that the product is efficient and works well”. A participant also said that the advert was trying to “enter larger markets” and thus make the product more approachable. Most participants except two misinterpreted the advert into viewing it as an advert for the aftershave and not as a charity advertisement. Even after explanation for the advert was provided, the participants maintained that they felt no sense of guilt. \r\n\r\nOnly one participant understood the mechanism of the guilt appeal used in the advertisement, identifying the underlying message of disparity the advertisement was trying to highlight, saying that the advert showed that “You are spending so much on yourself, (but) with a very little amount, you can help improve the lives of others and make an impact for those people” and said that the advert was simply asking the consumer to care about others. Participants also mentioned that the sparse and bare background “shows poverty and amplifies the situation of the person”. \r\n\r\nHowever, the themes the participants identified related to the efficiency of the product as the opinion was that the product worked well because it could be used by different people and the brand’s intention to show people across different nationalities and income levels. Participants were also provided the background of the campaign and a participant then said that she felt a deeper sense of guilt with this knowledge as she was not using her purchasing power to help others and instead for her own self. The impact of the advert on the participants was also varied with one claiming it had no impact and having a great impact on another. \r\n\r\nWhen presented with the second advert by Unicef against child labour (Appendix B), participants pointed out that the advert targeted Nike, saying that “It mocks Nike by making a direct comparison” and also that “Use of Nike makes it easy to understand to target the industry as a whole”.  A participant also claimed that the obvious dig at Nike left him unable to focus on the intention of the advert that many brands are contributing to child labour because “All I am seeing is Nike and child labour”. Participants who had knowledge about the background about the advert said that they were able to understand the advert better since they could understand why the advert used Nike. The boy in the picture seemed to evoke some emotion, as participants said that the advertisement was basically the fight by “A small boy against a big corporation” and that he is “Helpless and poor” because he cannot fight the situation. They also maintained that the advert sends the message of “restriction and no freedom” as well as “children forced to do it” and children who need money being misused”. The participants also claimed that while they did feel bad for the child, their attention is drawn more towards Nike than cause of child labour. The participants also felt that the campaign should use more brands as the advertisement sends the message of targeting only Nike and not the overall problem with a participant even saying that “Maybe it would have been better not to mention Nike at all”\r\n\r\nWith regard to the third advert by Feed SA (Appendix C), participants felt that the “language is strong”, “message is crisp and clear” and that it was “powerful because it shows an African child”. Conversation centred around the race of the child with participants saying that the advertisement would not have been as effective had the child not been Black and that “I would not have taken the advert seriously if it was an Asian kid”. The participants also said that had the advert emphasised on the race of the child and not the cause, they would have felt offended.  Participants however said that they would donate if they saw this advert because the ad, which was stuck on shopping trolleys explicitly shows he process thereby making the job easier for the consumers. The participants said that the advert is effective in “making people aware of the ease of helping people” as it targets the ease of donation. The advert was seen as “direct, easy, fast, convenient”. \r\n\r\nOn showing the fourth advert by Shelter (Appendix D), participants said that they would most likely not pause to read the entire advert due to it being word heavy. “That’s a big ad” said a participant, continuing that the advert “could have funnelled it down”. However, other participants disagreed saying that one could just read the highlighted text and understand the ad and that it does not demand too much attention. Some participants claimed that despite the size of the advertisement, the process of helping the cause was unclear and ambiguous. Others said that the advert would be effective should they want to donate because the problem is clearly highlighted, and the crux is conveyed with details of what they can do to help and the opinions on the effectiveness of the advert seemed divided. There appeared to be consensus with regard to the child in the picture as participants said that “emotion is instant when you see the girl” and the child would make them pause and read the advert. \r\n\r\nFor the last advert by Amnesty (Appendix E), participants said that the advert makes a strong and powerful statement, immediately catching one’s eyes but felt directionless. A participant said that the advert “hits the emotions but I do not know what to do about it”. Another participant commented that their eyes were immediately drawn towards the word “deserve”. The advert, while impactful, was stated to be vague because it does not inform the viewer what they might be able to do except go on a website, which the participants said was forgettable. A participant said that “Other ads are more about the action; this ad asks for interest and energy” and that one would not bother to do so unless they had time or was personally invested in the cause. Discussion of race again came to the forefront as participants said that the advert resonated more with them given the ethnic unambiguity of the child in that the child could have belonged to an Indian or even Latino background just as easily as American and that “crying face, torn clothes, messy hair make an impact to which race is second”. Not clearly defining the child’s ethnicity was seen as a clever marketing strategy but participants said that they had difficulty relating to a cause from a developed nation. A participant also said that “I would rather pick an Indian child and help that child” in response to helping a cause in America.  \r\n\r\nParticipants were then told that all the adverts worked by using guilt appeals and were asked if they did feel guilty when they viewed the adverts. Some participants identified the Shelter and Amnesty advertisements to evoke emotion in them, whereas others maintained that\r\nwhile they did feel bad and also sad when they viewed the adverts, they could not identify their emotions specifically to say that it was guilt and a couple also admitted that the adverts did not evoke much feelings of guilt.  \r\n\r\n \t“Unless I feel strongly about a cause, I would not donate to the cause regardless of how much the ad tries to guilt me or how powerful an ad is” maintained a participant who said that he would donate to the advert for poverty not only because the advert caught his attention, but also because he was more sensitive towards poverty, having grown up in a poor household. Another participant was of the opinion that he was more likely to donate to causes with adverts with a call for action. Participants also viewed adverts as a “reminder” or “trigger” to take action and that they were most likely to participate in a cause that is the easiest or most convenient to them. A different view was provided by another participant who said that unless he was personally invested to a cause, he would not feel guilt towards an advert for other causes due to the neutral perspective he maintained. Thus, there would be no response in any form towards the advert. \r\n\r\nA participant was also of the view that she would rather help other developing nations than a developed nation. She maintained that because she had seen so much poverty on the streets of India and that because of frequent donations to beggars, the child poverty advert did not evoke any guilt. Another participant revealed that his support only for causes that provided individuals with skills, regardless of the guilt the advert evoked, saying that “I will participate if I think the ad could solve the problem.”\r\n\r\nThe participants were also asked if pictures or words had a greater impact on them and while the consensus was that pictures evoked more emotion, having only pictures could be detrimental and lead to not understanding the purpose of the advert and the greater risk of misinterpretation.\r\n\r\nParticipants were finally asked if them being Indian or their culture had an effect on how they viewed the adverts. Growing up in a country with lots of poverty seemed to have had a great impact on the participants who said that they were more likely to help children in poverty. Religion also played a role for a participant who practised Islam who was of the opinion that he would have donated to any of the causes in the adverts had he seen them in the month of Ramzan. \r\n\r\nThere were several themes that were identified through the analysis of the responses from the interviews. Firstly, while the adverts did elicit negative emotions in participants that persuaded donation intention and to undertake advocated behaviour, that emotion was not immediately identified as guilt by the participants. The general responses to the adverts were that they made one feel “bad” or that they were “hard hitting” and “powerful”. Verbal enunciation of guilty feelings was difficult and indirect. Additionally, while some advertisements did elicit feelings of guilt, the factors that persuaded an individual to support were different from those discussed below.  \r\n\r\n“Unless I feel strongly about a cause, I would not donate to the cause regardless of how much the ad tries to guilt me or how powerful an ad is”\r\n\r\nAn important factor that persuaded charitable behaviour was the personal relevance of the cause for the individual. Personal relevance is largely influenced by life experiences of an individual. Prior knowledge and circumstances had a significant impact on the perception of adverts. The Unicef campaign appealing against child poverty through Nike had a greater impact on individuals who were aware of the case against Nike in reinforcing their perception of the brand than it did on those who were unaware. In such cases where a brand is targeted, the inclusion of facts and background might have resulted in an increase of interest. \r\n\r\nIndividuals who did not have an opinion on a particular cause or had a neutral perspective did experience negative emotions upon exposure to an advertisement, however, the strength of the emotions were not enough for them to consider acting on them. \r\n\r\nReligion also seemed to play a role in charity behaviour. Religions practises such as ‘zakat’ in Islam which requires one to donate a small share of their wealth to the poor and needy with the belief that such donation frees one from excessive greed and desires influenced those who practised the religion to donate during the time of Ramzan. \r\n\r\n\r\n“An advertisement to me is only a reminder”\r\n\r\nThe role of an advertisement was seen as a trigger or a reminder of the cause an individual supports and did not create a new belief or attitude towards a cause. Rather, they seemed to reinforce prevailing ideas and strengthened them. For instance, a participant felt more strongly about the Unicef child labour advertisement because he was informed about the cause and aware of the controversy Nike found itself embroiled it. The advert remined the participant about the cause and his interest in the advert was more a product of personal research than because of the guilt appeal used. However, advertisements time and again seem to be very persuasive in shaping attitudes as well as changing behaviour and it is to be further researched if the opinions in this research are because of the advertisements used or due to individual differences in beliefs of participants. \r\n\r\n“I would rather support an African child than an American child”\r\n\r\nThe willingness to help a cause also depended on the country the cause was addressed towards. There was a greater hesitancy and reluctance in supporting a cause from a “developed” country such America in comparison to developing countries or countries that had the same or lower level of economic growth as India. However, this seemed to be a key factor only when the country the advertisement originated from was explicitly stated. The Shelter advert was an advertising campaign from the United Kingdom, however, it was very persuasive and one of the most effective advertisements according to the participants. The advertisement made no mention of any location. There is a strong commitment in Indians to help extended family and friends or members of the same community, owing to the collectivistic nature of the society (Cantegreil, Chanana, & Kattumuri, 2013) and this is reflected in the responses from participants. This is an important factor to account for with an Indian population, where consumers might be reluctant to support causes from another state of India that is not their own. \r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"1999"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2000"},["text","None"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2001"},["text","Ravi2015"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2002"},["text","Rebecca James"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2003"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2004"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2005"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2006"},["text","None"]]]],["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":"2007"},["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":"2008"},["text","Leslie Hallam"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2009"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2010"},["text","None"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2011"},["text","7 participants"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2012"},["text","None"]]]]]]]],["item",{"itemId":"88","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"49"},["src","https://www.johnntowse.com/LUSTRE/files/original/f5a8c7f2b9110b1f583b9bf21cf2c204.doc"],["authentication","8a28b328858001d9d2bb429dcc9e7bb8"]]],["collection",{"collectionId":"4"},["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":"183"},["text","Focus group"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"184"},["text","Primarily qualitative analysis based on forming focus groups to collect opinions and attitudes on a topic of interest"]]]]]]]],["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":"2013"},["text","Sexualised Advertising through Instagram: An exploration into the effects this has on female appearance satisfaction"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2014"},["text","Chrystal Champion"]]]],["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":"2015"},["text","2018"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2016"},["text","This study explored the beliefs and opinions held by females aged 20-23 years on Instagram. It aimed to uncover possible effects that exposure to sexualised content and beauty standards could have on young female’s appearance satisfaction. Previous literature has addressed extensively how social comparisons and internalisation of beauty ideals can negatively affect females, increasing body dissatisfaction. This research aimed to expand these findings, exploring how body and facial attractiveness seen online can affect appearance satisfaction as a whole. Previous studies have determined that internalisation and social comparison are prevalent in women that compare themselves to others on Instagram. These theories along with objectification and cultivation theory are utilized to comprehend female’s perceptions of beauty and how it could be implicating them to act in a sexualised way online. The study consisted of two focus groups, each lasting approximately one hour. A convenience sample was used recruiting university students. A semi-structured interview schedule was utilised to allow for rich data to be produced. The data was categorised by using thematic analysis strategies of coding, mapping and deducing themes. The research conclusion found that women did report decreased appearance satisfaction when viewing ‘beautiful’ girls on Instagram, social comparisons was identified as more salient with peers, yet they did also report comparing themselves with reality television stars. Findings also reported that internalisation of beauty ideals was strong, they remark television and the social media for ‘normalising’ beauty standards. Lastly, participants were found to self-objectify themselves in a sexual manner more for Instagram than other social media sites. "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2017"},["text","None"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2018"},["text","This study explores the possible effects social networking site Instagram has on young females, in relation to their appearance satisfaction. Overall, it aims to add to existing literature within this field and other domains such as sociology and women’s studies, whilst also extending previous literature, as this research looks beyond body satisfaction and addresses appearance satisfaction completely. It also provides scope into understanding Instagram and the magnitude of its effects on the user, as the majority of previous literature focuses on Facebook. \r\n\r\n3.1 Research Design\r\nTwo focus groups were conducted, each lasting approximately one hour. The focus group was held in a small lecture theatre at Lancaster University in the Management School (Lecture Theatre 12). A phenomenological approach was applied as the research aims to explore a group of participant’s experiences and aims to further make sense of these experiences (Creswell, 2013). Application of focus groups was applied as it allowed for a semi-structured narrative of findings. The participants were able to express their thoughts, feelings and opinions in relation to this topic of research. A semi-structured interview type was applied as it allows for more flexibility, allows for more rapport building and these aspects can lead to richer data which enters more novel spheres (Smith & Osborn, 2003).\r\n\r\n3.2 Sampling \r\nThe overall sample consisted of 13 female students studying at Lancaster University between the ages of 20-23 years. This age was used as research has suggested that young females within these age brackets tend to be heavy Instagram users. These participants were recruited through convenience sampling, no specific recruitment criteria concerning use of social media was applied, in order to allow this variable to fall out naturally in the sample.  \r\n\r\n3.3 Research Procedures \r\n3.3.1 Materials \r\nThe participants were given an information sheet and a consent sheet at the beginning of the focus groups. These detailed the purpose of the study, outlined the potential risks/benefits, and provided the participants with information regarding their anonymity and confidentiality as well as making them aware of their right to withdraw. During the focus group participants were asked to discuss images which included advertisements of brands and celebrities and well as images showcasing cosmetic enhancements (See appendix E). The focus groups were recorded using a MacBook Pro, the recordings were stored in a file on the laptop, which was password protected. \r\n\r\n3.3.2 Interview Schedule \r\nA discussion guide was created for the focus groups which outlined a schedule for conversation and was used to informally guide the discussion. Guides are used to be suggestive, not prescriptive (Smith and Osborn, 2003). The discussion guide contained open-ended questions which were used to detect Instagram usage, opinions, beliefs and perceptions. However, it must be noted that some additional questions were asked during the focus group, coherent with its semi-structured nature to gather richer data where applicable. Lastly, the discussion guide was created to address the research aim.  \r\n\r\n3.3.3 Ethical Considerations\r\nThe research design adhered to Lancaster’s Universities ethics committee which is in line with the British Psychological Society’s Code of Ethics and Conduct (BPS, 2009). Each participant gave informed consent, they were informed of the confidentiality agreement, which was to anonymise their identity when using the data by given each of the individuals a pseudonym (Forrester, 2010). Participants were ascribed a pseudonym from the letters A-L to protect their identities. They were informed of their right to withdraw and were given a debrief sheet at the end of the focus groups. Data recorded was discussed only between the researcher and the supervisor.     \r\n\r\n3.3.4 Data Analysis Procedure \r\nData analysis from the research findings are used in a way which helps to manifest the respondent’s discussion, to examine possible beliefs or constructs as portrayed by the participants (Smith and Osborn, 2003). This aims to understand the complexity of the content, rather than depicting general frequency. The transcript is used to interpret meanings beyond the literal meaning, including context and deducing themes from the data. Thematic analysis was used to analyse the transcribed data. This method was utilised due to its flexible nature, which helps to produce rich descriptions and accounts of the topic being studied (Braun & Clarke, 2006). The research followed the 6-stage account as outlined by Braun and Clarke (2006). Stage one of their model involves familiarity of content, which is done by re-reading the transcripts. Stage two involves identifying key features and giving them a relating initial code. Thirdly, themes are deduced from the features by combining relevant codes, some create sub-themes and others are able to be subordinate themes. Fourthly, the themes are broken down and refined into separate themes, in the fifth stage these themes are used to create a thematic map. Lastly, each theme is written up and analysed to the fullest extent. \r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2019"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2020"},["text","Text/.docx"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2021"},["text","Champion2018"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2022"},["text","Rebecca James"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2023"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2024"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2025"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2026"},["text","Text"]]]],["element",{"elementId":"38"},["name","Coverage"],["description","The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant"],["elementTextContainer",["elementText",{"elementTextId":"2027"},["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":"2028"},["text","Leslie Hallam"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2029"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2030"},["text","Social, Marketing"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2031"},["text","13 female students "]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2032"},["text","Qualitative (Thematic Analysis), Qualitative "]]]]]]]],["item",{"itemId":"89","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":"2033"},["text","Does the use of prompts in shared reading facilitate the quantity and quality of language in Down Syndrome children?"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2034"},["text","Laura J. Durrans"]]]],["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":"2035"},["text","2017"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2036"},["text","Children with Down syndrome typically present with specific linguistic and communicative difficulties. The present study aims to explore how dialogic prompted reading facilitates better quality and quantity of language production in pre-school aged Down syndrome children. Research has demonstrated how reading interventions enhance typically developing children’s linguistic qualities, yet few studies have investigated the beneficial effects of dialogic prompted reading among Down syndrome children. Eight Down syndrome and 8 typically developing children completed two shared reading tasks with their mothers. One task involved reading a book containing a series of prompted questions, the other book contained no prompts. As predicted, prompted reading resulted in the development of more complex syntax, better vocabulary production and facilitated better responses accuracy to literal and inferential concepts, in Down syndrome children. In addition, the inclusion of prompts also increased parental scaffolding techniques for both diagnostic groups. The results from this study indicate that dialogic prompted reading does improve Down syndrome children’s qualitative and quantitative linguistic abilities and promotes better communication with parents during shared reading tasks. These findings highlight the educational significance of prompted dialogic reading as a highly beneficial intervention for developing an array of linguistic qualities in children with Down syndrome."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2037"},["text","Down syndrome, linguistic abilities, dialogic reading, prompted reading."]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2038"},["text","Participants\r\nA total of 16 children and their mothers took part in this study. Eight children with Down syndrome (DS: 4 female, 4 male, age range = 4.58 years to 6.75 years, Mage = 5.3 years) and 8 typically developing children (TD: 2 female, 6 male, age range = 3.9 years to 6.66 years, Mage = 5.1 years). This is a secondary data analysis study and all participants were previously recruited by the principle investigator and supervisor, Kate Cain. Video recordings of all child-parent reading dyads were made and were transcribed into written from. The Departmental Ethics Committee approved this study prior to the author receiving any video or transcribed data.\r\nStimuli \r\nIn this study, mothers were given two books to read with their children, ‘Mooncake’ and ‘Skyfire’ (Asch, 2014; 2014). Parents were asked to read both books as they normally would read at home with their child. One version of each book contained a series of 12 prompts which were inserted at specific points and parents where asked read them aloud as they went through the book (based on Van Kleek et al, 2006). Between both books there were a total of 24 prompts. For each book, prompts were evenly split between 4 sub-categories: picture labelling prompts “What is that? (pointing to Bear)”, vocabulary prompts “What does ‘hollow’ mean?”, inference prompts “ Why did Bear fall asleep?”, and general knowledge prompts “What else could Bear have used to stick the spoon to the arrow?”. The aim of the prompts was to encourage communication and scaffolding interactions between mothers and children when reading together. These books where specifically selected for multiple reasons: first, they have been successfully used in previous studies investigating linguistic impairments in pre-school aged children with language difficulties (Van Kleek et al 1997; 2006; Hammet, Van Kleek & Huberty, 2003). Second, the classic story-line of each book provides opportunities for children to follow a written and pictorial narrative, enhancing their visual perception skills, as well as being age suitable and cognitively stimulating for DS and TD children (Gibson 1996; Engevik et al 2016).\r\nProcedure and Design\r\nParent/child reading dyads were separated into groups based on diagnosis, where DS children and their mothers formed the experimental group, and TD children and their mothers formed the control group. There were two conditions; typical ‘unprompted’ reading and prompted reading. All participants took part in all conditions. In the unprompted reading condition, parents were given one of the books, selected at random (i.e ‘mooncake’) and asked to read with their child as they would normally read at home. In the prompted reading condition, parents were given the other book (i.e ‘skyefire’) and asked to read with their child as they normally would at home, but to additionally ask the twelve prompts that were inserted into the book. Within each condition, the order in which each child/parent dyad read each book was counterbalanced, as well as the order of books being presented between diagnostic groups was counterbalanced.\r\n         The experimental sessions were conducted either in a university lab or at the participants home, and was a record session. The researcher did not take part in reading sessions, and was there for recording purposes only. Each reading session was audio and video recorded, which was later transcribed in to written format using Microsoft Excel. The specific areas of language where coded for using the Excel written transcript and then inputted into SPSS for statistical analysis.\r\n\r\n\r\nCoding Categories\r\nChild and parent speech were coded for under the following categories: children’s production of language (length and syntax), children’s production of specific vocabulary types (nouns, verbs, adjectives, adverbs, affirmatives and fillers), parents use of questions (literal and inferential questioning styles), children’s language abilities in response to questions (literal and inferential), accuracy of children’s response to questions (literal and inferential), parental scaffolding techniques and children linguistic abilities in response to scaffolding techniques. This was done so the direct effects of prompted reading on a variety children’s language abilities could be primarily investigated, as well as assessing the effect prompted reading has on parental scaffolding techniques. \r\nLength and Syntax: total number of utterances, total number of words and mean length of utterances produced by children The total number of utterances produced by DS and TD children was coded for using a simple counting strategy, from the written transcripts in Microsoft Excel. Each sentence spoken by both groups of children, including singular words which posed as a sentence, were tallied to create the total number of utterances, between reading conditions. The total number of words was calculated by totalling every word in each utterance across both reading conditions, and the mean length of utterance was calculated by dividing by the total number of words by the total number of utterances each child spoke. Inaudible speech and vocalisations were not included in the coding, neither where onomatopoeic noises children made, such as ‘Zzzzz’ when pretending to be a bee, as they are representations of sound not speech. Onomatopoeic speech, for example ‘splash’ or ‘bang’ was included in the coding process as they are representations of speech. Additionally, speech where children were reading sections of the book alongside their mothers was excluded from the coding process, for the sole reason that reading alongside a parent does not represent language ability but reflects their reading ability. Each child had a score for the total number of utterances, total number of words and mean length of utterances produced for prompted and unprompted reading conditions, which were then inputted into statistical software SPSS. These factors represent the quantity element of language.\r\nVocabulary Production: nouns, verbs, adjectives, adverbs, affirmatives and fillers Children’s vocabulary production was coded under six sub-categories: nouns, verbs, adjectives, adverbs, affirmatives and fillers. These specific categories were chosen as previous research investigating vocabulary within DS has demonstrated that children present difficulties producing complex vocabulary categories, therefore two tiers of vocabulary were created: ‘basic’ vocabulary (nouns and verbs) and ‘complex’ vocabulary (adjectives and adverbs), to assess the effect of prompted reading on a large selection of vocabulary categories, rather than focusing on one particular type of vocabulary. These specific vocabulary categories are also applicable to the age range of children used in the study. Affirmatives (‘yes’, ‘no’ and ‘don’t know’) were coded for to investigate whether prompted reading affected the use of simplistic answers, specifically whether prompted reading decreased affirmative answers. Questions asked by children, like ‘what?’ and ‘why?’ were also included in the affirmative category, as they reflect an aspect of speech where a child is requesting for more information to further engage with the parent. Child questioning was rare and therefore did not require a category of its own. ‘Fillers’, additional words that make up a sentence, were also totalled. This was to investigate whether prompted reading facilitated more structured sentences, and therefore increased the number of fillers children produced. This was of particular interest for the DS group, as children with DS present difficulties in sentence structure. The total amount of vocabulary produced (inc. affirmatives and fillers) would therefore be equal to the total number of words produced.\r\nLiteral and Inferential Parental Questioning and Language Production Children’s ability to respond to literal and inferential questioning during shared reading sessions was coded for by adapting a four-level coding system previously used in studies investigating literal and inferential language in pre-school aged children (Van Kleek et al, 2003; Tompkins et al, 2013; Engevik et al, 2016). Previous coding schemes were designed to assess children’s literal and inferential speech across four linguistic domains, where the first two levels (Level 1 and Level 2) resemble children’s literal language, and the second two levels (Level 3 and Level 4) represent children’s inferential language (Blank, Rose & Berlin, 1978).\r\n          For the present study, children’s linguistic responses to literal and inferential questioning was only assessed under a 2 level system, where Level 1 represented speech in response to literal questioning, and Level 2 represented speech in response to inferential questioning. This adaptation was done to take into account DS children’s linguistic abilities, as a four-level coding system would have been too advanced for the particular task. Since DS children’s understanding of cognitive concepts and inferential questioning is limited, their linguistic responses to such questions would also be limited, therefore a two-level coding system was more acceptable.\r\n          For each set of 12 prompted questions used, 50% represented literal concepts (Level 1) and 50% represented inferential concepts (Level 2). Level 1 coded for children’s responses to labelling prompts (“What is that?”- pointing at Bear) and vocabulary prompts (“What does ‘hollow’ mean?”). Level 2 coded for children’s responses to inference prompts (“Why did Bear fall asleep?”) and general knowledge prompts (“What else could Bear have used to stick the spoon to the arrow?”). Parental prompts where also coded and separated between literal and inferential levels. The number of textual prompts and parental prompts where coded using a binary counting strategy, as well as the level of each question (literal or inferential) recorded. For each prompt, children’s responses where coded based their correct or incorrect response and vocabulary production (nouns, verbs, adjectives, adverbs and affirmatives) so each child had a score of response and vocabulary production for literal and inferential questioning, between prompted and unprompted reading conditions. (An example of the coding system can be seen in Appendix A).This particular coding method was designed to assess the extent to which textual and parental literal and inferential prompts enhanced children’s linguistic qualities, and pin point whether a specific type of questioning facilitated more correct responses and production of more vocabulary. \r\nScaffolding Techniques and Language Production Parents ability to successfully utilise scaffolding techniques between reading conditions was assessed, through designing a coding system that recorded each time parents took a break from reading the text to direct questions, these were labelled as ‘turn-taking sections’. The total number of turn-taking sections was coded, as well as the total number of questions parents asked per section and whether each question was literal or inferential. This was done to assess whether prompted reading encouraged parents to take more breaks from reading the text to ask their child questions, whether each time parents took breaks they asked more literal or inferential questions to engage their child. In addition to this, whether parental scaffolding enhanced children’s linguistic abilities were also assessed. This was done by coding the total number of words children produced per section, which would show whether parental scaffolding techniques enhanced children linguistic contribution. (An example of the coding system can be seen in Appendix B). \r\nAccuracy The accuracy of children’s responses, in relation to literal and inferential questioning, was coded by using a three-level coding system, used by previous studies investigating accuracy of children language during shared reading (Engevik et al, 2016). Previously, children’s accuracy of response was coded for along a linguistic continuum, where ‘fully adequate’ represented accurate verbal responses, ‘partially adequate’ reflected verbal communication which is ‘on the right track’ but not necessarily accurate, and ‘inadequate’ which represented any response that was irrelevant (Sorsby & Martlew, 1991; Engevik et al, 2016). Previous studies investigating accuracy of speech in DS children have adapted the coding system to merge ‘fully’ and ‘partially’ accurate categories together, to take into account the linguistic and cognitive difficulties DS children face (based on Engevik et al, 2016). However, the present study uses a slightly adapted version of the original coding system, where children’s ‘fully’, ‘partially’ and ‘not’ accuracy of responses were coded, yet only children’s ‘fully’ accurate responses will be used in the final analysis. This was done so children’s fully accurate responses to literal and inferential parental questioning could be assessed. ‘Partially’ and ‘not’ accurate responses were not assessed in this particular study as the sole interest is children’s ‘fully’ accurate response. The reason as to why ‘fully’ and ‘partially’ categories weren’t merged for the present study was to gain a more realistic understanding of children’s fully accurate responses, and merging categories would not provide this. (An example of the coding system can be seen in Appendix C).\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2039"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2040"},["text","Data/SPSS.sav"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2041"},["text","Durrans2017"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2042"},["text","Rebecca James"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2043"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2044"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2045"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2046"},["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":"2047"},["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":"2048"},["text","Kate Cain"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2049"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2050"},["text","None"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2051"},["text","8 children with Down syndrome and 8 typically developing children"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2052"},["text","None"]]]]]]]],["item",{"itemId":"90","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"47"},["src","https://www.johnntowse.com/LUSTRE/files/original/b1774444318c8b53bba03e2c298cbc26.pdf"],["authentication","88f0277eccd48de43dbb1ad44ed9cb74"]]],["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":"2053"},["text","An investigation into automatic imitation: Comparing live and video setups, the effect\r\nof prior training and the influence on affective empathy"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2054"},["text","Evangelos Baltatzis\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":"2055"},["text","2017"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2056"},["text","If decreased Automatic Imitation(AI) improves empathetic abilities, then selfother distinction processes are probably the mediating factor between imitation and\r\nempathy. But if increased AI improves empathy, then probably imitation is at the core\r\nof the socio-cognitive functions. Until now, it was shown that decreased AI improved\r\nvisual perspective taking, corticospinal empathy and self-reported empathy. Also, the\r\nstudies until now focus on video AI stimuli. But to understand whether AI has a more\r\ndirect relation to mimicry, I developed also live paradigm. My research questions\r\nwere firstly, what effect will imitation training and inhibition training have on AI.\r\nSecondly, whether live stimuli AI will have the same effects on AI testing (inhibition\r\nversus imitation) and arousal empathy testing. Thirdly, whether the effects are\r\ntransferable on arousal empathy. As expected, there was a significant decrease of AI\r\nin the video inhibition condition in comparison to the video imitation condition.\r\nUnexpectedly, a significant, but weak increase in arousal empathy was observed in\r\nthe video imitation condition and not in the video inhibition group. The difference in\r\nAI and arousal empathy between the life imitation group and the life inhibition group \r\nwere not significant. The results give a new perspective on the topic of AI. If the\r\nresults can be reproduced by more studies, then probably imitation is more important\r\nthan self-other distinction processes or maybe arousal empathy is different from other\r\nforms of empathy. Finally, the insignificant results in the life imitation versus life\r\ninhibition training indicate that there are maybe confounding factors in live AI\r\nresearch or that the video AI designs are more artificial than it is assumed. "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2057"},["text","automatic imitation, empathy, imitation training, inhibition\r\ntraining, mirror neuron system, self-other distinction"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2058"},["text","Participants\r\nSixty(N=60) participants were recruited in a two-by-two factorial design, and\r\ndivided equally among two between-subject factors. The first factor is Stimulus,\r\nwhereby AI will be measured in response hand actions performed by an experimenter\r\nsat across a table from the participant (Live) or to the actor’s pre-recorded hand-action\r\nstimuli presented on a monitor. The second factor is Training, whereby participants\r\nwill undertake a brief period of imitating the actions of the live or videoed handaction stimuli (IMI) or performing the opposite actions (IMI-IN).\r\nThe participants were recruited from students of the University of Lancaster.\r\nRandom selection could not be used, because of practical and logistical difficulties.\r\nHence, most of the participants were Masters students and some were PhD students.\r\nThe participants were either friends and acquaintances or they had the motivation to \r\nwin a 10 pounds amazon voucher. In many cases they had the motivation to\r\nparticipate in my study, because they also wanted me to participate in their study.\r\nFirstly, we conducted the experiments with the video paradigm (15 participants in the\r\nimitation training condition and 15 participants in the inhibition training condition)\r\nand then we conducted the experiments of the live paradigm (15 participants in the\r\nimitation training condition and 15 participants in the inhibition training condition).\r\nWe use random assignment for the recruitment in the training condition, thusly, every\r\nparticipant was randomly assigned in either the imitation training or in the inhibition\r\ntraining condition. For instance, we did not conduct first 15 experiments in the\r\nimitation training condition and then 15 experiments in the inhibition training\r\ncondition, but every participant was in a different training condition. Nevertheless,\r\none possible limitation may be that we did not do the same for the stimulus condition,\r\nas we conducted first the experiments of the video condition and then the experiments\r\nof the real condition.\r\nMaterials\r\nThe experiment was conducted on the personal laptop of the researcher. No\r\nspecific room was needed for the experiment to have more flexibility with the data\r\ncollection. The software Mathlab and the program Cogent were used to code and\r\nmake the script. In order to measure affective empathy, we used the Multi-faceted\r\nempathy test (MET). It consisted of 40 images, but it was split in two METS to\r\ninclude also a pre-test approach. For imitation training and for inhibition training we\r\nused three images of the hand of the researcher. In one image, the hand of the\r\nparticipant was in the neutral position. In the second image, the index finger was\r\nlifted and in the third image the middle finger was lifted.\r\nDesign and Procedure\r\nFirst, we conducted the experiments of the video paradigm (30 participants)\r\nand then we conducted the experiments of the live paradigm. The experimental\r\nprocedure was divided into four phases: First, participants will do the MET\r\n(Multifaceted empathy test). The first Met had 22 images. The MET tests affective\r\nempathy. Participants must choose from a scale from 1 until 4 how strong is their\r\naffective arousal when they see the image. The MET took approximately 5-10\r\nminutes, depending on the participants.\r\nAfter the first MET, participants did either imitation training or imitation\r\ninhibition training. The default position for the participants in this task was to press\r\ntwo buttons all the time with their right-hand index and middle finger. In the video\r\ncondition, they pressed button A and button Z -with their right-hand index and middle\r\nfinger, and in the live paradigm they pressed the left and right arrow button -with their\r\nright-hand index and middle finger respectively. In imitation testing, they had to lift\r\ntheir index finger when they saw a lifted index finger (video or live) and to lift their\r\nmiddle finger when they saw a lifted middle finger (video or live). Both actions\r\nshould be done as quickly as possible. In the inhibition training the participants did\r\nthe opposite actions of the observed movements. Thus, when they saw a lifted index\r\nfinger, they lifted their middle finger as quickly as possible. When they saw a lifted\r\nmiddle finger, then they lifted their index finger, again, as quickly as possible. The\r\ntraining phase consisted of two tasks and a small break. Every task had a duration of 6\r\nminutes approximately.\r\nAfter the training, there was the testing phase. Here we tested the effects of\r\ntraining on Automatic Imitation. The training phase consisted of two 6 minutes tasks \r\nwith a break between the two tasks. In the first task, the participants had to lift only\r\ntheir index finger as quickly as possible, irrespective of the lifted finger they saw\r\n(either in video or in the live condition). In the second testing task, they had to lift\r\ntheir middle finger as quickly as possible, again irrespective of the lifted fingers that\r\nthey saw.\r\nAutomatic imitation is measured as the difference in their latency to lift the\r\npre-defined finger when the observed action is the same in relation to when the\r\nobserved action is the opposite finger movement. For instance, when the participant\r\nlifts his index finger, we measure the reaction time of his movement, when he sees a\r\nlifted index finger and when he sees a lifted middle finger. Automatic imitation is the\r\ndifference of those two reaction times. This testing phase lasted 10 minutes,\r\ncomprising 100 trials divided among two blocks. After the lifting of the finger, the\r\nparticipants pressed the button again (default position). Thusly, the reaction times\r\nwere measured by how fast the participant would lift his finger.\r\nTo ensure that the training and the testing really focused on Automatic\r\nImitation and to exclude the spatial compatibility confounds, the participants were\r\nperpendicular to the stimuli (in both the video and the live condition). Sadly, we could\r\nnot have the same perpendicular angle for both conditions, but the difference of the\r\ndegrees was very small. In the video condition, the angle was approximately 45\r\ndegrees (the fingers of the participants were at the buttons A and Z and the stimuli\r\nwere on the laptop screen) and on the live condition, the stimuli were approximately\r\n90 degrees perpendicular (the fingers of the participants were on the right and left\r\narrow and the real stimulus of the experimenter was at the buttons “tab” and “shift”).\r\nIn the final phase, the participants did a second MET test. It was exactly like\r\nthe first, only with different images. The order of the MET tests was changed with\r\nevery participant. In other words, one participant did first the MET.1 and in the end\r\nthe MET.2, while the other participants did first MET.1 and in the end, they did the\r\nMET.2. Both MET tests different parts of the same MET test, but we splitted the test\r\narbitrarily in the middle to have also a pretest empathy base. I changed the order of\r\nthe MET tests with every participant to exclude the factor that some pictures of the\r\nTest are less difficult than the others. Thus, if we find a large and statistical significant\r\ndifference in the final MET between the imitation and the inhibition training group,\r\nthen we can say that in both training conditions we changed equally the order of the\r\nMET tests, so the observed change in empathy performance does not have to do with\r\nsome images being easier or more difficult than the others.\r\nIn the IMI condition, the participants were required to lift their index finger\r\nwhen they see the stimulus hand (live or videoed) perform an index-finger action, or\r\nlift their middle finger when they observe a middle-finger action; in the IMI-IN\r\ncondition they will do the opposite - they will lift their index finger when they\r\nobserve a middle-finger action or lift their middle finger when they see an indexfinger action.\r\nIn the second phase, the participants performed AI testing, during which they\r\nwill be required to make a pre-defined finger-lifting movement (index- or middlefinger lifting action) as soon as the stimulus hand (live or videoed) moves, regardless\r\nof whether the observed movement is an index- or middle-finger lifting action. In the\r\nthird phase, participants will perform the Multi-Faceted Empathy Test, during which\r\nthey will be presented with 30 images of individuals expressing emotions and asked \r\nto judge which emotion is being expressed. The accuracy of their responses will be\r\nrecorded. This final phase takes 10 minutes.\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2059"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2060"},["text","Data/SPSS.sav"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2061"},["text","Baltatzis2017"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2062"},["text","Rebecca James"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2063"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2064"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2065"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2066"},["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":"2067"},["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":"2068"},["text","Dr. Daniel Shaw\r\n"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2069"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2070"},["text","Social psychology"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2071"},["text","60 participants"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2072"},["text","ANOVA, t-test"]]]]]]]],["item",{"itemId":"91","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"62"},["src","https://www.johnntowse.com/LUSTRE/files/original/7eed95df1e1229784ef63083b60f8deb.pdf"],["authentication","70d164182dcb5bfc8ee05947ce40bf6c"]],["file",{"fileId":"63"},["src","https://www.johnntowse.com/LUSTRE/files/original/e2e9d770f78082d0f0184070a591e2a3.csv"],["authentication","d5fa6ce9d4a5dbb2d06c5e8be2067fc7"]]],["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":"2073"},["text","Testing the Heat Hypothesis: The Relationship between Temperature and Violent Crime Rates"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2074"},["text","Georgia Fifer\r\n\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":"2075"},["text","2015"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2076"},["text","This paper explored the relationship between temperature and behaviour. In particular the effect heat has on violent crimes. The heat hypothesis states that increased ambient temperatures can cause increased aggressive motives and behaviours. The current study was longitudinal and archival. Data was collated from four different countries: U.S., Japan, Jamaica and Finland over a period of 40 years. Data was collected from reliable online sources for: Temperature in degrees Celsius (℃), rainfall in millimetres (mm), intentional homicide rates, assault rates, rape rates and burglary rates. Rainfall and burglary were control variables. Analyses revealed a significant and positive relationship between temperature and intentional homicide, assault and rape rates. Temperature and burglary were not significantly related. Such results provide support for the heat hypothesis. The relationship between heat and violent crime should be investigated further; as the effects of global warming increase, so may violent crime rates worldwide."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2077"},["text","None"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2078"},["text","Data\r\nIn accord with Anderson et al’s., (1997) methods, data of the following crimes were collected: intentional homicide, assault, rape and burglary within a specified 40 years. \r\nThis crime data was sampled from the following countries databases: U.S., Japan, Jamaica and Finland. The inclusion criteria were to include the countries which had the most available data on crime. There were no data exclusions as the current study was retrospective, meaning all data had already been collected.\r\nThe 40 years analysed within each country differed depending on data availability. Crime rates were collected in the U.S. between the years 1960 and 2000. Crime rates were collected in Japan between the years 1975 and 2015. Crime rates were collected in Jamaica between the years 1970 and 2010. Crime rates were collected in Finland between the years 1976 and 2016. Therefore there would have been 160 full observations of intentional homicide, assault, rape and robbery. However, due to limited data available there were gaps in the data. For the U.S., 40 full observations of intentional homicide, assault, rape and robbery were obtained. For Japan, 23 full observations were obtained and 17 partial. For Jamaica, 11 full observations were obtained and 29 partial. For Finland, 22 full observations were obtained and 18 partial. \r\n The crime data was police reported and per 100,000 of the population, as smaller figures were easier to manage. Crime data was collected from the following reliable online resources: Bourne et al., (2015), Burns (2013), (Knoema, 2011), (Nation Master, 2003), (Statista, n.d.), (Uniform Crime Reporting, 1930), (United Nations World Surveys, 2006), (UNODC Statistics, 1997). Websites were considered reliable if they were established official government data repositories. \r\nTemperature (℃) and rainfall (mm) data were also collected. This data was obtained from an online climate data portal (Climate Change Knowledge Portal, n.d.). Rainfall was included as a control variable to ensure that any significant effect was a consequence of increased temperatures, rather than reduced rainfall as a consequence of increased temperatures. If rainfall was not controlled for, it would be impossible to decipher whether the observed effect was caused by increased temperature or reduced rainfall. \r\nApparatus  \r\nMicrosoft excel and the Statistical Package for the Social Sciences (SPSS) were used for data analyses.\r\nAnalytical approach\r\nThis study was a longitudinal archival study which analysed existing data. The dependent variable (DV) was crime rates per 100,000 people, collated from reliable online data sources. The independent variables (IV) were: temperature and rainfall. The question asked was whether crime rates can be predicted by temperature and rainfall. The control variables were burglary and rainfall. Burglary was a control dependent variable, as it was expected that temperature would affect violent crime and not non-violent crime such as burglary. Rainfall was a control independent variable, so that rainfall could be controlled for and this made it possible to detect whether temperature alone had an effect on crimes. \r\nThe data collected required certain properties: the source had to be reliable, crimes had to be police reported and crime rates needed to be reported per 100,000 of the population. Pre-existing data available online was collected and sorted into an excel spreadsheet. Each variable had a column on the spreadsheet: country, year, intentional homicide, assault, rape, burglary, temperature and rainfall. The country variable was categorical. Countries were coded: 1 for the U.S., 2 for Japan, 3 for Jamaica and 4 for Finland. The remaining variables were continuous. There were 160 observations, 40 years per country. Some observations included data on all four crimes; some were partially completed due to limited data. \r\nFirstly scatter graphs were plotted with crime against temperature for each country. This revealed the general direction of the relationships between the temperature and crimes. The main analysis was a linear mixed-effects model, where temperature and rainfall were fixed effects and country and year were random effects. \r\nThis analysis was chosen because of the structure of data. For this study there were multiple samples of crime rate data over 40 different years for each country, and multiple samples of crime rate data for the four different countries for each year. Magezi (2015) described how linear mixed-effects models can include such multiple, nested groups and accommodates for missing data. This was useful because the current study was a longitudinal archival study and consequently had missing data. Analyses were conducted using SPSS. An alpha level of .05 was used for each linear mixed-effects model. \r\n+1 lag model analyses for each crime were also implemented, to account for a possible delay of the effect caused by exposure to temperature. To achieve this, the DV columns were shifted down one row using SPSS. It was necessary to check that all values still aligned with the correct country. \r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2079"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2080"},["text","Data/Excel.xslx"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2081"},["text","Fifer2015"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2082"},["text","Rebecca James"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2083"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2084"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2085"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2086"},["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":"2087"},["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":"2088"},["text","Dermot Lynott\r\n\r\n"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2089"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2090"},["text","Social "]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2091"},["text","4 countries"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2092"},["text","Linear mixed effects modelling, longitudinal, archival, heat hypothesis"]]]]]]]],["item",{"itemId":"92","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"50"},["src","https://www.johnntowse.com/LUSTRE/files/original/0a917b3a4543cc825a215484c9f5c190.doc"],["authentication","d7092d017f2f3fc1794f6eaba833fe15"]],["file",{"fileId":"67"},["src","https://www.johnntowse.com/LUSTRE/files/original/d71088a5eb10e3040d607a8ababacc5b.csv"],["authentication","0456eba4e9e8a8f945fa0524fbe53023"]],["file",{"fileId":"68"},["src","https://www.johnntowse.com/LUSTRE/files/original/eba407ee8cee0963a503a35dc278d0e6.csv"],["authentication","4ec9cb51a3c16e51553c3b37b89178c2"]]],["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":"2093"},["text","The Effect of Ambient Temperature on Cognitive Processing"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2094"},["text","Nicola Cook"]]]],["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":"2095"},["text","2018"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2096"},["text","Over recent decades, climate change has caused the world to get warmer and this trend is set to continue into the future. Relationships between increased temperature and changes in human behaviour, such as increased aggression, have been identified and it is therefore important to consider the impact it may have on other aspects of behaviour. At present, there are limited amounts of research on the effect of temperature on cognitive performance. Within the framework of dual-process theories of cognition and using a Cognitive Reflection Task (CRT) and a Syllogisms Task, the current report researches whether increased ambient temperature (artificially manipulated in a temperature lab) encourages the use of System 1 (i.e. fast, unconscious) processing as opposed to System 2 (i.e. slow, deliberate) processing. The paper asks whether increased temperature leads to more heuristic answers on the CRT and more belief bias on the Syllogisms task. We observed no effect of temperature on performance on the CRT or the Syllogisms task. Similarly, we observed no effect of ambient temperature on belief bias or confidence in answers to the Syllogisms task. However, an effect of ambient temperature was found on how many heuristic responses were given to the CRT, with those in the cold condition giving more heuristic answers than those in the hot condition. We conclude that these findings do not provide support for increased temperature impairing certain aspects of cognitive performance, but also explore unexpected results and discuss potential reasons for these"]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2097"},["text","Ambient temperature\r\nCognitive reflection\r\n Syllogistic reasoning\r\n Logistic mixed effects modelling."]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2098"},["text","Participants\r\n65 individuals participated in this research study. Three were excluded for not meeting the pre-decided eligibility criteria of being a native English speaker aged between 18 and 65. This left 62 participants, 19 male and 43 female (Mage = 25.29 SDage = 8.83). Prior to the study, 1.61% had attained a PhD, 9.68% a Master’s degree, 40.32% a Bachelor’s degree, 33.87% A-Levels, 3.23% GSCEs, 9.68% a Certificate or Diploma and 1.61% had no qualifications. All participants completed the whole study, and none indicated awareness of the true aims of the study, thus, following pre-agreed exclusion criteria all participants were retained for analysis.\r\nMaterials\r\nCognitive Reflection Task. To test participants’ cognitive reflection, a form of the CRT (Frederick, 2005) was utilised. The CRT consists of a series of problem solving questions, with four multiple choice answers. For example, the question, ‘A bat and a ball cost £1.10 in total. The bat costs £1.00 more than the ball. How much does the ball cost?’ is presented alongside the following four options; ‘10p’, ‘5p’, ‘15p’ and ‘90p’. In this case the gut instinct is usually to respond with ‘10p’ however this is incorrect, and the correct response is, ‘5p’. \r\nFrederick’s (2005) original version of the task only consisted of three items and has since been criticised for being too short; about 44% of participants who are given the task have previously seen the questions and this leads to the inflation of their scores on subsequent testing sessions (Stieger & Reips, 2016). Consequently, both Primi, Morsanyi, Chiesi, Donati and Hamilton (2016) and Travers, Rolison and Feeney (2016) have since developed longer versions of the tasks; Primi et al.’s (2016) consisted of 6 items, whilst Travers, Rolison and Feeney’s (2016) consisted of 8. The present study combined items from both papers, taking 6 critical items from Primi et al. (2016) and 4 items, used as fillers, (adapted) from Travers, Rolison and Feeney (2016). The filler questions are included to reduce the chance of participants identifying the aims of the study. These questions differ from the critical questions in that the most obvious answer is the correct one. See Table A1 for a full list of the items used in the CRT.\r\nSyllogisms Task. In order to test participants’ syllogistic reasoning 10 Syllogisms were presented to the participant. Six critical Syllogisms (where the answer was invalid) were taken from Morley, Evans and Handley (2004) and used in the present study. Half of these Syllogisms had believable conclusions, whilst half had unbelievable ones. The believable Syllogisms, concluded with a statement that was believable in the real world (e.g. ‘Some addictive things are not cigarettes’), but remained invalid given the two premises, whilst the unbelievable ones concluded with a statement that was both unbelievable in the real world (e.g. ‘Some millionaires are not rich people’), and illogical given the two premises. The task also consisted of four filler Syllogisms. Again, half of the filler items had believable conclusions and half had unbelievable conclusions, however all of the conclusions were valid. See Table A2 for a full list of the items used in the Syllogisms task.\r\nProcedure\r\nParticipants were either recruited through the University’s recruitment portal (SONA), or through individual volunteer sampling. Each testing session was pre-designated as either a hot or cold session and each session consisted of multiple testing slots which were advertised to participants. Participants were unaware of this temperature manipulation and blindly signed up to a testing slot under the pretence of completing a study which investigated behaviour in decision making tasks. As varying numbers of participants signed up to each session, the researchers updated the pre-designated condition of each session accordingly, to ensure there were the same number of participants, 31, within each condition overall.\r\nThe study was conducted in a temperature control lab at Lancaster University. This room contains a temperature control panel, which was used to set the ambient temperature of the room to either 16˚C in the cold condition, or 28˚C in the hot condition. A KTJ TA318 Thermometer (with precision of 0.1˚C) was used to record the exact temperature at which each participant completed the study. In the cold condition, the temperature ranged from 15.5˚C to 16.9˚C (M = 16.14) and in the hot condition the temperature ranged from 27.8˚C to 29.8˚C (M = 28.56). \r\nThe room consisted of five workstations, separated by partitions, meaning it was possible to test up to five participants at once. Each participant completed the study independently at one of the workstations, which contained a computer monitor, keyboard and mouse, stood on an individual sized table. When participants arrived at the study, they were seated at an adjustable chair facing the computer, within easy reach of the keyboard and mouse. If participants commented on the temperature of the room, the researcher responded with short statements of agreement, such as ‘yes, it is isn’t it’, but did not elaborate further to ensure that researcher influence was kept to a minimum. \r\nEach participant was given time to read the information sheet and provide consent (both digitally presented). Participants then entered demographic information such as their age, nationality and education level. Following this, the main section of the study began, and participants completed both the CRT and the Syllogisms task along with two other short tasks administered on behalf of a separate researcher. These two other tasks were not part of this research study. As part of the Syllogisms task, participants were asked to rate how confident they were in their response to each item, on a sliding scale from 0 (completely unconfident) to 100 (extremely confident). The order in which all four tasks were presented was randomised and counterbalanced across participants to negate any potential order effects. Additionally, the order of items within a task was also randomised for the same reason. Participants were given 5 minutes to complete the CRT, as this is consistent with previous administrations of a CRT (e.g. Primi, et al., 2016) and 30 seconds to complete each of the items on the Syllogisms task. These time limits were utilised to encourage participants to keep focus and to mimic the kind of time pressure associated with examinations.\r\nAfter these tasks, participants were asked 3 debriefing questions (see Appendix B) to assess whether they had identified the aims of the study. Answers to these questions were reviewed independently by two members of the research team and if participants demonstrated a link between temperature and cognitive performance their data would have been removed from the analysis, as their results may have been influenced by their awareness. Both assessors agreed that there was no cause to remove any participant on this basis.\r\nFinally, participants provided information about how comfortable they felt in the lab, on a 6-point scale, and then also how hot or cold they feel on average, on a sliding scale from -50 (extremely cold) to +50 (extremely hot). This second measure was taken to account for individual differences, as many people generally feel warmer or colder for reasons such as illness or medical condition, and this may influence how hot or cold they felt in the lab.\r\nAt the end of the study participants were offered the chance to enter a prize draw to win one of twelve £10 Amazon vouchers. This rumination method was chosen above the option of paying every participant, to mimic the uncertainty of reward which is common in many settings such as examinations. \r\nPre-registration\r\nThis project was verified and registered on the Open Science Framework on the 21st May 2018 (https://osf.io/p6879/). The present study deviated from the initial plans in the followings ways. Firstly, the initial plan to recruit 120 participants proved unachievable within the time constraints and therefore 62 participants were tested. Secondly, logistic mixed effects models were used for most analyses instead of linear mixed effects models. This was a consequence of reformatting the data to be able to take into account the random effect of items on each task, resulting in the dependent variable being binary. Thirdly, the random effect of items and participants were not always included. This was because models with and without these factors were compared and random factors were only included if they helped the model to better fit the variation in the data. Finally, the initial plan was to investigate the effect of mood as an exploratory factor. The data on mood was collected, however further investigation was not possible due to project constraints.\r\nAnalyses Strategy\r\nThe aim of this paper was to determine whether increased temperature impairs cognitive performance as measured by a CRT and Syllogisms task. To facilitate assessment of results, the data was analysed using R (R Core Team, 2017). The numerical variables used as predictors in analysis were then scaled using the ‘scale’ function from the ‘standardization’ package (Eager, 2017). To conduct the desired analysis, the data was transformed from wide to long format using the ‘gather’ function from the ‘tidyr’ package (Wickham & Henry, 2018). \r\nTo assess whether the data collected supported the hypotheses and therefore the extent to which temperature condition predicted test performance, several logistic mixed effects (LME) models were computed, using the ‘glmer’ function from the ‘lme4’ package (Bates, Maechler, Bolker & Walker, 2015). This was the most appropriate method of analysis to use as both the dependent and key independent variables were binary and it allowed the random effects of participants’ individual differences, as well as the random effect of items within each task, to be taken into account, which is necessary in a repeated measures design. The models contained the fixed effects of condition (Hot vs. Cold), baseline temperature and comfort level and the interaction effects of condition with comfort level and with baseline temperature. They also included the random effects of participants and/or items, depending on which random factors (if any) were found to aid the model to fit the variation in data best. To evaluate whether the inclusion of the random effects was required in each model, comparisons were made between the Akaike Information Criterion (AIC) of the final model and identical models with (a) the random effects removed, (b) only the random effect of items, and (c) only the random effect of participants, see Table C1. \r\nWhen reporting logistic models, we give estimated coefficients (ß), standard errors (SE), z-values (z) and p-values (p) of predicting variables. We also report the conditional R2 value (R2_c) for each model; a ratio which gives the variance explained by the fixed and random effects as a proportion of the total variance explained by the fixed effects, random effects and residuals. This is calculated using the ‘r.squaredGLMM’ function of the ‘MuMIn’ package (Barton, 2018). Where significant effects are found, estimated log odds are transformed into odds ratios by exponentiating the coefficients, to aid the interpretation of the effect.\r\nCognitive Reflection Task. To investigate whether there was a difference in performance on the CRT between individuals in the hot condition and individuals in the cold condition, the data was coded such that a correct answer was given the value of ‘1’ whilst incorrect answers were given the value of ‘0’. To address whether there was a difference in the number of heuristic responses given on the CRT, the data was recoded (‘1’ = Heuristic response, ‘0’ = Other response). \r\nSyllogisms Task. To investigate whether there was a difference in performance on the Syllogisms task between individuals in the hot condition and individuals in the cold condition, the data was coded such that a correct answer (‘Invalid’) to a critical item was given the value of ‘1’ whilst incorrect answers (‘Valid’) were given the value of ‘0’. In order to investigate whether participants in the hot condition showed more belief bias than those in the cold condition, we extracted the three invalid believable Syllogisms and the two valid unbelievable Syllogisms. The data was recoded such that when a ‘valid’ answer was given to an invalid but believable syllogism or when an ’invalid’ answer was given to a valid but unbelievable syllogism, responses were given a value of ‘1’, to signify belief bias. Other responses were given a value of ‘0’. To analyse the ratings of confidence in participants’ answers to the Syllogisms task a linear mixed effects models was used, as the dependent variable was continuous. \r\nExploratory Analysis. Data collection was conducted during the summer months, partly whilst Britain was experiencing a period of unusually hot weather. It is therefore possible that participants may not have been fully affected by the temperature manipulation. For example, those in the cold condition may have still suffered the negative effects of heat as a result of spending time prior to the study, outside in the heat. To address this, actual environmental temperature at a local weather station, for the times of participation were taken from ‘WeatherOnline.co.uk’ and added to the data set. The LME models included the outside temperature along with condition and the interaction between outside temperature and temperature condition as the fixed factors, and the random effects of items and participants.\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2099"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2100"},["text","data/Excel.csv"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2101"},["text","Cook2018"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2102"},["text","Ellie Ball"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2103"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2104"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2105"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2106"},["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":"2107"},["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":"2108"},["text","Dr. Dermot Lynott"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2109"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2110"},["text","Cognitive Psychology"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2111"},["text","62 Participants (19 male and 43 female)"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2112"},["text","Pearson's Correlation"]]]]]]]],["item",{"itemId":"93","public":"1","featured":"0"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2113"},["text","Perception of sounds sequences: predictions for behavioural measurements generated with a computational model of auditory cortex "]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"2114"},["text","Zsofia Belteki"]]]],["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":"2115"},["text","2015"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2116"},["text","Behavioural and neuroscientific research into sound perception shows that our auditory system is able to represent the temporal structure of sounds over a wide range of time windows – a process labelled as temporal binding. Recent computational modelling work suggests that synaptic depression in auditory cortex, responsible for adaptation of neural responses to repeated stimuli, is also the memory mechanism which allows for temporal structure of sounds to be represented. This project aimed to generate behavioural predictions of this explanation of temporal binding. Simulations examined how the cortex is able to discriminate between sound sequences differing from each other in terms of the timing, amplitude, and frequency of the sequence elements. Along with the temporal length of the sequences, the lifetime of neural adaptation was manipulated. The results predict that the thresholds for discriminating sound sequences should be tuned to a given sequence duration. These findings are discussed in light of the previous research on how the dynamics and anatomical structures within the auditory cortex may facilitate neural adaptation.  "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2117"},["text","Cartesian state space difference calculations"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2118"},["text","The current project investigated the processing of sound sequences by applying a computational model of the auditory cortex described in more detail in the study by May and Tiitinen (2013). The coding of the experiment, including stimulus design and experimental design, along with data analysis all took place in MATLAB. \r\n\r\nModel structure and dynamics \r\n\r\nStructure. The model is made up of 14 brain areas, with 13 cortical areas that include three core, eight belt and two parabelt areas of the auditory cortex, and one sub-cortical area simulating the thalamus. Each area is made up of 16 computational units representing cortical columns, with each column comprising one excitatory (pyramidal) and one inhibitory population of neurons. Altogether, this meant that there are 224 columns within the model. There are three levels of structural connections, namely interaction within columns, interaction between columns and interactions between the different cortical areas. \r\nStructural connections are expressed through connection matrices that describe synaptic connections between the excitatory populations (Wee), from inhibitory to excitatory populations (Wei), and from excitatory to inhibitory populations (Wie). Intra-column connections are assumed to be the strongest, with the synaptic weight for the within-column excitatory feedback (i.e., the diagonal values of Wee ) being set to 6, and the within-column weight values of Wei and Wie (inter-neuron connections targeting excitatory and inhibitory cells respectively) being set to 3.5. \r\nThe excitatory population of each column made lateral connections to the excitatory populations of neighboring columns within the area. These connections extended to a distance of two columns on either side. Similarly, the excitatory population connected to neighboring inhibitory populations across a distance of five columns, with these connections accounting for lateral inhibition (see Figure 1). In both cases, there was a Gaussian drop off of the weight strength. Also, there was a stochastic element to the weights, with a 10% random jitter added to them. These procedures represent modifications in relation to the original model of May & Tiitinen (2013) and are described in Hajizadeh, Matysiak, May, König (in preparation).  \r\nConnections made by the inhibitory population were assumed to be local, and so targeted only the excitatory population in the same column (see Figure 1). Inter-area connections were modelled from anatomical research in primates (Kaas and Hackett, 2000) and were contained entirely in Wee. The tonotopically organized afferent input Iaff targeted the thalamus, where each column functioned as a frequency channel to spectrally organize the input. The thalamus was connected to the three core areas. These were interconnected with the eight belt areas, and the eight belt areas were subsequently interconnected with two parabelt areas. The model had a serial structure, with no direct connections between the core and the parabelt (see Figure 2). Core and belt connections only occurred between neighboring areas, resulting in multiple core-belt-parabelt streams that had roughly a rostral and caudal subdivision (De la Moethe, Blumell, Kajikawa & Hackett, 2006). Connections between the areas were topographic, with each inter-area sub-division of Wee being characterized by most connections occurring near the diagonal, with a Gaussian drop-off in weight strength (as explained in Hajizadeh et al., in preparation).\r\nDynamics. The dynamical unit of the model was the cortical microcolumn, which was made up of a population of excitatory and inhibitory cells, characterized by a single state variable u and v, respectively, expressing the mean activity of the population. For each excitatory population, its mean firing rate g depended on the state variable u through a non-linear monotonically increasing function g(u) = tanh (2/3) (u - ) for u > , g(u) = 0 otherwise, where  = 0.1 was a threshold constant. The mean firing rate of the inhibitory population was similarly determined as g(v). Collecting the states of the excitatory and inhibitory cell populations into vectors u =  [u1….uN] and v = [v1…vN], the dynamic equation of the neural interactions were where m = 30ms is the membrane time constant and Iaff describes the afferent input targeting the thalamus.\r\n\r\nAdaptation. The underlying mechanism for neural adaptation operating on the time scale of seconds is short-term synaptic depression (Wehr & Zador, 2005). To simulate this, all excitatory connections in cortex (i.e., the elements ij of Wee and Wie) were modulated by a time dependent depression term aij(t), where i and j are the index of the post- and presynaptic population, respectively. This term depended on the pre-synaptic spiking rate through the equation.\r\nHere, on = 100ms is the onset time constant and rec is the time constant for the adaptation recovery from depression and thus expresses the lifetime of adaptation. In the current experiments, rec was varied in the 800-2000ms range in seven steps of 200ms. This range reflects electrophysiological findings whereby the adaptation of the N1m response (the MEG equivalent of the N1) can be encapsulated in a time constant that varies across participants in the range of 1-4 seconds (Lu, Williamson & Kaufman, 1992).\r\nStimuli and Procedures\r\nStimuli sets comprised sequences of three consecutively presented tones (50ms duration, 5ms linear onset & offset ramps), with the sequence being characterized by its total duration, measured as the onset from first tone to onset of third tone.  For each measurement, two sequences of the same duration were presented to the model. While the third tone in each sequence was always the same (amplitude = 1; input via thalamic frequency channel 7, middle of tonotopic map), the two sequences differed in terms of the first two tones, that is, in terms of the stimulation history of the final tone (see Figure 3). Simulations were carried out in three experiments where the difference across the sequences was either in the timing, amplitude, or frequency of the first tones.  In each experiment, all other aspects of the sequences were kept constant. This eliminated any counter-effects, with distinctions between sequences depending solely on the manipulation made (independent variable). In each experiment, the total duration of the sequence was varied in the range of 500-4000ms in steps of 200ms, creating a total of 18 different sequence durations. As explained above, the lifetime of adaptation was also varied (from 800-2000ms) to simulate a population of participants. For a diagram of the Stimuli sets, see Figure 3. \r\n\r\nExperiment 1: variations in timing. This looked at the model’s ability to discriminate temporal patterns represented by two sequences of three identical tones (amplitude = 1; frequency channel 7). These sequences were identical, except for the presentation time of the middle tone. In the first sequence, the SOI of the middle tone was jittered away from regular presentation by an amount representing 5% of the total duration of the sequence away (see Figure 3). The second sequence was a reversed version of the first. \r\n\r\nExperiment 2: variations in amplitude. Here, the two sequences varied in terms of the amplitude of the first two tones. In the first sequence, the amplitude of the first and second tone was 1.05 and 0.95, respectively. In the second sequence, these values were reversed. The final third tone had a fixed amplitude of 1. The three tones were presented at regular intervals, and their frequency was 7 on the tonotopic map of the thalamus. \r\nExperiment 3: variations in frequency. Here, the frequency history preceding the third tone was varied. In the first sequence, the first tone had a frequency of 6 and the second tone had frequency 8. Reversed frequencies were used in the second sequence. The three tones were presented at regular SOIs. \r\n\r\nAnalysis\r\n\r\nThe third tone was kept constant both within the two-sequence stimuli sets and across the experiments to ensure that the variations in the response to this final tone reflected changes in the stimulation history only. Thus, the ability of the model to discriminate between the temporal structure of two sequences could be analyzed by examining the activity elicited by the third tone of each sequence.\r\nAs such, the firing rates of the excitatory populations in the cortical areas were treated as coding the previous stimulation history. The response to the third tone was quantified by averaging the firing rate of each excitatory population in a 200-ms time window following the onset of the third tone (see Figure 3). This resulted in a 208-dimensional vector, that is, a point in 208-dimensional state space where each axis represents the activity of one cortical column. The difference in the responses to two sequences was then quantified as the Cartesian distance (using the norm.m function in MATLAB) between the two respective points in state space. This distance measure, denoted by Dstate, was taken to represent the ability of cortex to discriminate between tone sequences. \r\nFor each experiment, the analysis determined how Dstate changed as a function of the total duration of the sequence. Also, this dependence of Dstate on duration was examined in the case of different adaptation lifetimes\r\n\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2119"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2120"},["text","Data/MATLAB"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2121"},["text","Belteki2015"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2122"},["text","Ellie Ball"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2123"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2124"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2125"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2126"},["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":"2127"},["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":"2128"},["text","Perception of sounds sequences: predictions for behavioural measurements generated with a computational model of auditory cortex "]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"2129"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2130"},["text","Modelling (Computational)"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2131"},["text","Unknown"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2132"},["text","Cartesian distance"]]]]]]]]]