["itemContainer",{"xmlns:xsi":"http://www.w3.org/2001/XMLSchema-instance","xsi:schemaLocation":"http://omeka.org/schemas/omeka-xml/v5 http://omeka.org/schemas/omeka-xml/v5/omeka-xml-5-0.xsd","uri":"https://johnntowse.com/LUSTRE/items?output=omeka-json&page=9&sort_field=Dublin+Core%2CTitle","accessDate":"2026-05-23T06:10:08+00:00"},["miscellaneousContainer",["pagination",["pageNumber","9"],["perPage","10"],["totalResults","148"]]],["item",{"itemId":"193","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"215"},["src","https://johnntowse.com/LUSTRE/files/original/2d733bde1c35f66edba319392e339771.pdf"],["authentication","bcd96b51fb4c89cefd082eb9845b288a"]]],["itemType",{"itemTypeId":"14"},["name","Dataset"],["description","Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing."]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3852"},["text","Investigating infant expectation on object search tasks"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"3853"},["text"," Leah Murphy"]]]],["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":"3854"},["text","2023"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3855"},["text","The current study aims to distinguish between Piaget’s (1954) theory of object understanding, highlighting the role of object permanence on A not B task performance, and Diamond’s (1985) theory highlighting the role of motor demands and lack of ability to inhibit habitual behaviours during the task. These two theories differ in their predictions for the expectations of the infants taking part, with Piaget (1954) predicting that infants’ lack of object permanence causes poor performance on the task and Diamond (1985) predicting that infants understand the movement of objects and a lack of inhibition of habitual behaviours cause error in performance. We tested 15 nine-month-old infants on a looking version of the A not B task. The use of impossible and possible outcomes was also incorporated on B trials, with the object being revealed from either the correct or incorrect location (e.g., see Ahmed & Ruffman, 1998). Infant first look direction, accumulated looking time during trials and the number of social looks initiated post-outcome, were used as measures. We found significant evidence of the ‘AB’ error during trials, with a significantly increased number of incorrect first looks on B trials. There was also a descriptive pattern showing surprise at object location reveals with increased number of social looks during B compared to A trials, though this was not significant. Accumulated looking analysis showed that infants looked longer on A than B trials, suggesting that infants expected the object to be in location B on B trials, demonstrating infants’ ability to understand objects and supporting Diamond’s (1985) theory. However, implications for a small sample size and presence of individual differences on interpretation of looking time data are discussed. Implications in theory and future research are suggested and overall, results provide support for the application of Piaget’s (1954) theory and suggest that infants have limited object understanding based on their displayed expectations during testing."]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"3856"},["text","3.1. Participants\r\nIn this study, 15 participants took part, aged 8 months and 12 days to 9 months and 27 days old (M = 9 months and 3 days, SD= 11.3 days). Six further infants were excluded from data analysis as they became too fussy to complete the study. Participants were recruited from the Lancaster Baby lab database, along with the Lancaster Baby lab Facebook page and were also recruited via word of mouth from guardians taking part in the \r\nstudy. \r\n3.2. Materials\r\nThe video stimuli were created using Canva software (Canva.com, 2023) and was uploaded onto ‘Habit 2’ software (see Oakes et al., 2019) to display the stimuli during testing and to measure the accumulated looking time of the infant participants. The stimuli involved a novel object obtained from the NOUN database (Horst & Hout, 2016). A camera was used to record the social looks exchanged between the infant and guardian, as well \r\nas the direction of the infants’ first looks during testing. \r\n3.3. Design\r\nThis study had a within-subjects design, with all participants being exposed to the same experimental conditions and the same stimuli. To counterbalance for location effects, half of the participants witnessed A trials being hidden in the box on the left, whilst the other half witnessed the object being hidden in the box on the right during A trials. The presentation of the accurate and inaccurate B trials was further counterbalanced across participants, as half of the participants viewed the inaccurate B trials first, and the other half viewed the accurate B trials first.\r\n3.4. Ethical approval\r\nEthical approval for this study was granted by the departmental ethics committee (DEC) at Lancaster University. Guardians were recruited via their preferred contact method and were sent the participant information sheet to read before agreeing to take part in the study. A date and time of testing was arranged at the Babylab building at Lancaster University, via telephone or email. Upon arrival, guardians were presented with the consent form to sign and initial all points before being allowed to take part. They were also given the opportunity to ask any questions about the study and were informed that they could withdraw at any time. \r\nAfter the study, the guardian received a five-pound contribution to travel costs, along with a free children’s book for the infant, as a reward for taking part in the study. The guardian also received a debrief sheet to read and to take home, providing them with all contact information of the lead researcher, if they wished to ask any questions or to withdraw from the study. \r\n3.5. Procedure\r\nThe testing took place in a private room within the Whewell building at Lancaster University. The infant and guardian were sat in front of a computer screen with the infant sat in a highchair positioned directly in front of the screen, and the guardian sat in a chair to the side, slightly behind the infant (to allow researchers to see clearly when the infant initiated a social look). The experimenter sat behind a divider at a computer, out of sight of the infant and guardian. A social engagement video of the experimenter saying, “Let’s hide the blap, can you find the blap?” was presented to the infants at the start of the experiment and between each trial, to insert social communication and guide the attention of the infant to the screen before the stimuli were presented. The infant then watched a series of video stimuli in which a novel object appeared on the screen and moved into one of two boxes, both boxes were then covered (the object was hidden), and a there was a delay period of five seconds (see figure 1). After the delay period, both boxes were revealed, and the location of the toy was visible to the infant. Any movement of the object was accompanied by a sound to guide the attention of the infant to the object, but this sound was not present when the object was revealed to avoid any leading factors when measuring infant expectation. Instead, the occluders made a simple “whoosh” sound when they were removed, to ensure the infant was paying attention. After five identical A trials, the object was then hidden in the second location and the process was repeated consisting of six B trials. However, during the B trials, the object was hidden in the second location, but was either revealed to be in the correct (accurate) or incorrect (inaccurate) location (see figure 2). This variation in outcome was presented alternately to the infant, with the object being revealed from the incorrect location for three out of the six B trials. The study lasted for approximately 10 minutes per participant.\r\n3.6. Behavioural coding\r\nInfant looking time was coded online as trial lengths were infant controlled. Each trial ended when the infant looked away for four seconds. As this controlled the trial length, this was not double coded as this inherently will lead to a high agreement level. For the coding of infant first look and number of social looks, the videos recorded of the participants were saved and uploaded onto Microsoft OneDrive to be offline coded. First look was defined as the direction that the infant first looked towards once the occluder was removed and the object was revealed. On trials where the infant was not looking as the occluder was removed, the first look was defined as the direction in which they looked once their gaze returned to the screen. The first look direction was coded as correct and incorrect. The number of social looks initiated by the infant per trial was also measured during coding, defined by the infant turning towards the guardian during each trial after an outcome was revealed. Twenty percent of the videos were dual coded and there were no discrepancies between researchers during the dual coding process for first looks (r = 1, p<0.01) or social looking (r= 1, p<0.01)."]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3857"},["text",".xslx"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3858"},["text","Shiyu Pang\r\nYuewen Qin"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3859"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3863"},["text","dataset"]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3864"},["text","Chi-squared, Correlation, Factor analysis, Linear mixed effects modelling"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"3866"},["text","Murphy(2023)"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"3867"},["text","open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"3868"},["text","none"]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"3860"},["text"," Kirsty Dunn"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"3861"},["text","In this study, 15 participants took part, aged 8 months and 12 days to 9 months and 27 days old (M = 9 months and 3 days, SD= 11.3 days). Six further infants were excluded from data analysis as they became too fussy to complete the study."]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"3862"},["text","Chi-squared, Correlation, Factor analysis, Linear mixed effects modelling"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"3870"},["text","Cognitive - developmental, Developmental"]]]]]]]],["item",{"itemId":"201","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"228"},["src","https://johnntowse.com/LUSTRE/files/original/ea2c0c6f1d9da3c754aeca4f45c6e344.pdf"],["authentication","bcd96b51fb4c89cefd082eb9845b288a"]]],["collection",{"collectionId":"9"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. 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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":"4007"},["text","Investigating infant expectation on object search tasks.  "]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"4008"},["text","Leah Murphy"]]]],["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":"4009"},["text","2023"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"4010"},["text","The current study aims to distinguish between Piaget’s (1954) theory of object understanding, highlighting the \r\nrole of object permanence on A not B task performance, and Diamond’s (1985) theory highlighting the role of \r\nmotor demands and lack of ability to inhibit habitual behaviours during the task. These two theories differ in \r\ntheir predictions for the expectations of the infants taking part, with Piaget (1954) predicting that infants’ lack \r\nof object permanence causes poor performance on the task and Diamond (1985) predicting that infants \r\nunderstand the movement of objects and a lack of inhibition of habitual behaviours cause error in performance. \r\nWe tested 15 nine-month-old infants on a looking version of the A not B task. The use of impossible and possible \r\noutcomes was also incorporated on B trials, with the object being revealed from either the correct or incorrect \r\nlocation (e.g., see Ahmed & Ruffman, 1998). Infant first look direction, accumulated looking time during trials \r\nand the number of social looks initiated post-outcome, were used as measures. We found significant evidence \r\nof  the ‘AB’ error during trials, with an significantly increased number of incorrect first looks on B trials. There \r\nwas also a descriptive pattern showing surprise at object location reveals with increased number of social looks \r\nduring B compared to A trials, though this was not significant. Accumulated looking analysis showed that infants \r\nlooked longer on A than B trials, suggesting that infants expected the object to be in location B on B trials, \r\ndemonstrating infants’ ability to understand objects and supporting Diamond’s (1985) theory. However, \r\nimplications for a small sample size and presence of individual differences on interpretation of looking time data \r\nare discussed. Implications in theory and future research are suggested and overall, results provide support for \r\nthe application of Piaget’s (1954) theory and suggest that infants have limited object understanding based on \r\ntheir displayed expectations during testing."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"4011"},["text","Infant, behaviours, theory"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"4012"},["text","3.1. Participants \r\nIn this study, 15 participants took part, aged 8 months and 12 days to 9 months and 27 days old (M = 9 \r\nmonths and 3 days, SD= 11.3 days). Six further infants were excluded from data analysis as they became too \r\nfussy to complete the study. Participants were recruited from the Lancaster Baby lab database, along with the \r\nLancaster Baby lab Facebook page and were also recruited via word of mouth from guardians taking part in the \r\nstudy.  \r\n3.2. Materials \r\nThe video stimuli were created using Canva software (Canva.com, 2023) and was uploaded onto ‘Habit \r\n2’ software (see Oakes et al., 2019) to display the stimuli during testing and to measure the accumulated looking \r\ntime of the infant participants. The stimuli involved a novel object obtained from the NOUN database (Horst & \r\nHout, 2016). A camera was used to record the social looks exchanged between the infant and guardian, as well \r\nas the direction of the infants’ first looks during testing.  \r\n3.3. Design \r\nThis study had a within-subjects design, with all participants being exposed to the same experimental \r\nconditions and the same stimuli. To counterbalance for location effects, half of the participants witnessed A \r\ntrials being hidden in the box on the left, whilst the other half witnessed the object being hidden in the box on \r\nthe right during A trials. The presentation of the accurate and inaccurate B trials was further counterbalanced \r\nacross participants, as half of the participants viewed the inaccurate B trials first, and the other half viewed the \r\naccurate B trials first. \r\n3.4. Ethical approval \r\nEthical approval for this study was granted by the departmental ethics committee (DEC) at Lancaster \r\nUniversity. Guardians were recruited via their preferred contact method and were sent the participant \r\ninformation sheet to read before agreeing to take part in the study. A date and time of testing was arranged at \r\nthe Babylab building at Lancaster University, via telephone or email. Upon arrival, guardians were presented \r\nwith the consent form to sign and initial all points before being allowed to take part. They were also given the \r\nopportunity to ask any questions  about the study and were informed that they could withdraw at any time. \r\nAfter the study, the guardian received a five-pound contribution to travel costs, along with a free children’s book \r\nfor the infant, as a reward for taking part in the study. The guardian also received a debrief sheet to read and to \r\ntake home, providing them with all contact information of the lead researcher, if they wished to ask any \r\nquestions or to withdraw from the study.  \r\n3.5. Procedure \r\nThe testing took place in a private room within the Whewell building at Lancaster University. The infant \r\nand guardian were sat in front of a computer screen with the infant sat in a highchair positioned directly in front \r\nof the screen, and the guardian sat in a chair to the side, slightly behind the infant (to allow researchers to see \r\nclearly when the infant initiated a social look). The experimenter sat behind a divider at a computer, out of sight \r\nof the infant and guardian. A social engagement video of the experimenter saying, “Let’s hide the blap, can you \r\nfind the blap?” was presented to the infants at the start of the experiment and between each trial, to insert \r\nsocial communication and guide the attention of the infant to the screen before the stimuli were presented. The \r\ninfant then watched a series of video stimuli in which a novel object appeared on the screen and moved into \r\none of two boxes, both boxes were then covered (the object was hidden), and a there was a delay period of five \r\nseconds (see figure 1). After the delay period, both boxes were revealed, and the location of the toy was visible \r\nto the infant. Any movement of the object was accompanied by a sound to guide the attention of the infant to \r\nthe object, but this sound was not present when the object was revealed to avoid any leading factors when \r\nmeasuring infant expectation. Instead, the occluders made a simple “whoosh” sound when they were removed, \r\nto ensure the infant was paying attention. After five identical A trials, the object was then hidden in the second \r\nlocation and the process was repeated consisting of six B trials. However, during the B trials, the object was \r\nhidden in the second location, but was either revealed to be in the correct (accurate) or incorrect (inaccurate) \r\nlocation (see figure 2). This variation in outcome was presented alternately to the infant, with the object being \r\nrevealed from the incorrect location for three out of the six B trials. The study lasted for approximately 10 \r\nminutes per participant.  \r\nFigure 1 \r\nExample of A not B task stimuli presentation during A trials or accurate B trials.  \r\nFigure 2 \r\nExample of A not B task stimuli presentation during inaccurate B trials.  \r\n3.6. Behavioural coding \r\nInfant looking time was coded online as trial lengths were infant controlled. Each trial ended when the \r\ninfant looked away for four seconds. As this controlled the trial length, this was not double coded as this \r\ninherently will lead to a high agreement level. For the coding of infant first look and number of social looks, the \r\nvideos recorded of the participants were saved and uploaded onto Microsoft OneDrive to be offline coded. First \r\nlook was defined as the direction that the infant first looked towards once the occluder was removed and the \r\nobject was revealed. On trials where the infant was not looking as the occluder was removed, the first look was \r\ndefined as the direction in which they looked once their gaze returned to the screen. The first look direction was \r\ncoded as correct and incorrect. The number of social looks initiated by the infant per trial was also measured \r\nduring coding, defined by the infant turning towards the guardian during each trial after an outcome was \r\nrevealed. Twenty percent of the videos were dual coded and there were no discrepancies between researchers \r\nduring the dual coding process for first looks (r = 1, p<0.01) or social looking (r= 1, p<0.01)."]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"4013"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"4014"},["text","Text/Word.doc"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"4015"},["text","Murphy2023"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"4016"},["text","Alicja Kowalska"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"4017"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"4018"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"4019"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"4020"},["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":"4021"},["text","LA1 4YW"]]]]]],["elementSet",{"elementSetId":"4"},["name","LUSTRE"],["description","Adds LUSTRE specific project information"],["elementContainer",["element",{"elementId":"52"},["name","Supervisor"],["description","Name of the project supervisor"],["elementTextContainer",["elementText",{"elementTextId":"4022"},["text","Kirsty Dunn"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"4023"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"4024"},["text","Developmental"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"4025"},["text","15 participants"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"4026"},["text","Correlation"]]]]]]]],["item",{"itemId":"79","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"35"},["src","https://johnntowse.com/LUSTRE/files/original/8f2f87e573c831b72cee2c8b8ba543dc.pdf"],["authentication","f34ccfe7021afea913451a930716e424"]],["file",{"fileId":"36"},["src","https://johnntowse.com/LUSTRE/files/original/9fc3d7b08fbf5aba53f3d3f32bc10296.pdf"],["authentication","1697756e4beef9e38469b4104adb6c7b"]],["file",{"fileId":"37"},["src","https://johnntowse.com/LUSTRE/files/original/6e8fe4b7fd6c4b29c575e3b1249198eb.pdf"],["authentication","f1ee4628271e3179323d196a01d03e3c"]],["file",{"fileId":"77"},["src","https://johnntowse.com/LUSTRE/files/original/4c4162827312b2c2d00e7c64b9587ebd.csv"],["authentication","ed6519051947a6e4b43340598a2c7bf9"]],["file",{"fileId":"78"},["src","https://johnntowse.com/LUSTRE/files/original/fe12af25b11cfb5f017a248c53c613e3.csv"],["authentication","aadf65e48136716fdfc5f72bb3921dbe"]]],["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":"1834"},["text","Investigating the Effects of Challenging Behaviour on the Sibling Relationship: Influenced by Behaviour Topography and Shaped by Attributions of Controllability?"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"1835"},["text","Lauren Laverick-Brown"]]]],["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":"1836"},["text","2018"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1837"},["text","Challenging behaviour (CB) displayed by individuals with an intellectual disability (ID) is consistently identified as a stressor on the relationship that they have with their typically developing (TD) sibling. Given the potentially damaging effects of CB on the quality of the sibling relationship and the wellbeing of the TD sibling, understanding the cognitions that underpin TD siblings’ emotional and behavioural responses to CB is essential to direct sibling-targeted psychoeducational interventions. This study considered whether siblings’ responses to CB vary according to behavioural topography. Further, the study considered whether any effects detected were shaped by attributions made by TD individuals regarding the controllability of their siblings’ CB. Thirty-eight siblings of individuals with ID, and 36 participants with a nondisabled sibling, completed a web-based questionnaire measuring participants’ positive and negative affect towards their sibling, the nature of their sibling’s CB, and controllability perceptions regarding their sibling’s CB. The results of this study reiterate that CB is a stressor on the sibling relationship, with externally directed CB (i.e. aggression, destruction) eliciting greater negative affect in siblings compared to internally directed behaviours (i.e. self-injury). However, it could not be concluded with an appropriate level of significance (i.e. p<.05) that this was due to participants perceiving their siblings as more in control of their externally directed behaviours. These findings may have resulted from the diverse nature of the participant group. Further research is required to examine specific differences in the emotional impact of each type of challenging behaviour (and then subsequently, whether any differences detected arise due to contrasting perceptions of behaviour controllability)."]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"1838"},["text","Participants\r\nSeventy-four TD individuals who had a sibling completed this study. Participants were allocated to one of two conditions according to whether they had a sibling with an ID, or did not (i.e. their sibling was TD). There were 38 participants who had a sibling with ID (82% female, Mage=27.32, SD=9.65) and 36 participants with a TD sibling (92% female, Mage=28.61, SD=10.81); ranging between 13 to 60 years old. Siblings diagnoses are reported in Table 1. \r\nTable 1: Diagnoses of participants' siblings\r\n\r\n\r\nParticipants were recruited on a voluntary basis through social media advertisements posted by the researcher and by disability organisations (who also sent emails to their followers), and through word of mouth. The researcher developed a digital research flyer summarising study’s purpose and procedure, distributed as described above. To incentivise participation, participants had the option to enter themselves in a prize draw for a £20 Amazon voucher upon completion of the study. \r\nA minimum participation age was determined after inputting the text of each questionnaire included in the study into Coh-Metrix (Version 3.0; Graesser, McNamara, Louwerse & Cai, 2004): a web-based software tool assessing the cohesion and coherence of a text. Coh Metrix provides an index of readability by generating the reading age of a piece of text, and the reading age determined of the questionnaires was “grade six”; indicating that 10/11-year-olds should have the ability to comprehend and respond to questions. Thus, it was decided that the questionnaires were suitable for TD individuals aged 12 or above.\r\nConsent was gained from all those over 16 years of age, and parental consent for and assent from those aged 12-15 years of age (see “Ethical Considerations” below for further information).\r\nDesign\r\nThe study was of a correlational design, investigating the relationship between the following continuous variables: the quality of the sibling relationship, CB displayed by the sibling with ID, attributions of controllability made by participants in respect to their sibling’s behaviour, and participants’ general relational abilities. \r\nAs part of further analysis, the intention was to examine whether there were effects of having a brother/sister with a disability, gender, and birth order (i.e. whether participants were older/younger than their sibling) (all between-subjects factors) on the sibling relationship. \r\nMaterials\r\nDuring this study, four self-report questionnaires were administered to all participants: the Positive and Negative Affect Scale (PANAS) (Watson, Clark & Tellegen, 1988) (Appendix A), the Behavioral Problems Inventory (Short Form) (BPI-S) (Rojahn, Matson, Lott, Esbensen, & Smalls, 2001) (Appendix B), the Controllability Beliefs Scale (CBS) (Dagnan, Grant & McDonnell, 2004) (Appendix C), and Social Competence and Close Friendship subscales taken from the Harter Self-Perception Profile for Adolescents (Harter, 2012) (Appendix D). The development and presentation of the questionnaires was done using online Qualtrics software (Qualtrics, Provo, UT). \r\nThe Harter Self-Perception Profile for Adolescents (Harter, 2012) is a multidimensional measure of how young people evaluate their scholastic, social, athletic, and job competencies, as well as physical appearance, romantic appeal, behavioural conduct, and close friendship. However, for the purposes of this study, only the subscales regarding social competence and close friendship were included to detect an individual’s general ability in forming and maintaining relationships with others, which might be a confounding influence on detecting the quality of the sibling relationship. Furthermore, the phrasing of the questionnaire was deemed suitable for both adult and adolescent participants.\r\nThe questions are presented as two clauses (e.g. \"Some people know how to make others like them, but…”, and “Some individuals do not know how to make others like them”). Participants are able to select whether each clause is “really true for me” or “less true for me”, though are required to make the one selection out of four options across both clauses that is most self-descriptive. These responses are coded into a 4-point scale, with “1” representing poorer social/friendship abilities, and some items are negatively coded. Sufficient levels of validity and reliability of the Profile have been reported within a range of population groups (e.g. Donnellan, Trzesniewski & Robins, 2015; Rose, Hands, & Larkin, 2012).\r\nA modified version of the PANAS (Watson et al. 1988) was used to assess participants’ feelings towards their brother/sister with a disability, which were then used to infer the quality of the sibling relationship i.e. greater positive affect would indicate a positive and fulfilling sibling relationship, whilst greater negative affect would indicate poor sibling relationship quality. The PANAS is a self-report questionnaire that consists of two separate scales containing emotion-based items that encapsulate positive and negative affect. Participants were asked to think about their sibling and whether they had felt each emotion towards them, rating this on a 5-point scale to specify how often they feel that emotion, ranging from 1 (very slightly or not at all) to 5 (extremely often). Higher total scores on each scale indicated greater positive/negative affect. “Total negative affect” and “total positive affect” scores were obtained for each participant; whereby higher scores pertain to greater affect.\r\nThe PANAS has been widely utilised to measure variation in affect, and previous research investigating its psychometric properties concludes it to have high reliability and validity across many populations (e.g. Merz, Malcarne, Roesch, Ko, Emerson, et al., 2013; Bakhshipour & Dezhkam, 2006). In this study, certain items of the PANAS were adapted to ensure that they were recognisable to younger participants; for example, “hostile” and “strong” were changed to “angry” and “happy”, respectively. The items “jittery”, “active” and “determined” were excluded as the researcher did not view them as relevant to the sibling relationship. Nevertheless, statistical analysis revealed that internal consistency remained, with the positive and negative affect scales showing high reliability in the current sample, Cronbach’s αnegative=.87; Cronbach’s αpositive=.93.\r\nThe BPI-S (Rojahn et al. 2001) is a psychometrically sound behaviour rating instrument (Rojahn, Rowe, Sharber, Hastings, Matson, et al., 2012; Mascitelli, Rojahn Nicolaides, Moore, Hastings et al., 2015) constituting a series of items referencing examples of CB. When completing the BPI-S, respondents consider whether a specific individual (in this study, participants’ sibling) engages in a behaviour, and then rate its frequency on a 1-to-6-point scale; corresponding to responses ranging from “never” to “daily”. The original BPI-S also contains a severity-rating subscale; however, this was excluded from the study, as rating the severity of behaviour was deemed to be too complicated for younger participants to judge. \r\nThe BPI-S contains questions relating to three types of problem behaviours: self-injurious, stereotypic, and aggressive/destructive behaviours. For the purposes of this study, the behavioural items of the BPI-S were grouped and scored according to whether they constituted IDB (i.e. self-injury) or EDBs (i.e. aggression and destruction). Items referencing stereotyped behaviour were excluded, as it was not possible to neatly categorise them into IDB or EDB. As an addition to the questions of the BPI-S, an opportunity for “free text” was included immediately after, whereby participants could describe any behaviours of concern that were not specified by the questionnaire and rate their frequency. Total scores for the BPI-S were obtained, as well as separate total scores for IDB and EDB frequency, whereby higher scores represent a greater number of incidences of CBs.\r\nLastly, the CBS (Dagnan et al., 2004) is a 15-item measure designed to capture participants’ perceptions regarding an individual’s (in this case, their siblings’) control over their CB. Responses are scored on a 1-to 5-point scale, corresponding to ‘disagree strongly’, ‘disagree slightly’, ‘unsure’, ‘agree slightly’ and ‘agree strongly’. Ten items are worded such that agreement reflects participants attributing high control over behaviour (e.g. ‘They are trying to wind me up’). In contrast, five items are phrased whereby agreement indicates participants attributing low control over behaviour (e.g. ‘They don’t mean to upset people’); thus, these items are reversed scored. A “total CBS” score was calculated for each participant, with higher scores pertaining to perceptions of greater control over behaviour. Moreover, Dagnan et al. (2004) report good internal reliability, with a Cronbach's alpha of 0.89.\r\nDemographic information relating to participants’ age, gender, birth order (i.e. were they older/younger than their sibling) and the diagnosis of their disabled sibling (if their brother/sister was disabled) was collected prior to participants completing the questionnaires.  \r\nProcedure\r\nAfter receiving expressions of interest from prospective participants and confirming they had a sibling (with or without an ID), the researcher issued a participant information sheet detailing the nature and aims of the study. Both groups of siblings followed the same study procedure but received participant information sheets that were relevant to their role in the study. The researcher also provided a weblink to the online consent form hosted by Qualtrics. Once participants completed the consent form, they answered demographic questions and generated a participant code to ensure anonymity of responses. Participants were informed prior to the study commencing that they could withdraw at any time, either by closing the webpage or by contacting the researcher and asking to be removed from the dataset.\r\nInitially, participants responded to items of the Close Friendship and Social Competence subscales of the Harter Self Perception Profile. Following completion of these questions, participants then completed the PANAS, BPI-S and CBS (in that order). Upon finishing the CBS, participants who had a sibling with ID proceeded to a debrief form that outlined the study in detail and provided contact information for support organisations (if needed following discussion of their encounters with CB). Control participants received a debrief form detailing their role in determining the baseline/typical sibling relationship.\r\nThe procedure differed slightly for participants aged under 16 years old. With one exception, who contacted the researcher directly (but ultimately could not participate due to lack of parental consent), this group expressed their desire to participate through their parents contacting the researcher. In response, the researcher sent a consent form for a parent/guardian to complete, giving their permission for their child to participate in the study. Two participant information sheets were also provided; one for parents and another simplified version of the adult participant information sheet for individuals under 16 years old. Once the researcher had received the completed consent form, the weblink to the study was emailed. It was stressed to parents that, though they may wish to support their child in understanding the questions of the study, they should refrain from guiding their child’s answers.\r\nAfter clicking the weblink, younger participants completed an assent form and were informed about the participation withdrawal procedures, if required. The presentation of the questionnaires was the same as for those aged 16 years old and above. However, the debrief form was simplified in its language and content to ensure it was accessible to younger participants. Contact information for organisations who could support this group of participants specifically was also provided. Additionally, younger participants with a non-disabled sibling received a simplified version of the adult participant debrief form relevant to their role in the study. After reading the debrief sheet, all participants were given the opportunity to enter into a prize draw for a £20 Amazon voucher. The study lasted roughly 15-20 minutes. \r\nAll participant information sheets, consent forms and debrief sheets are listed in Appendices E – S. \r\n\r\n\r\nEthical Considerations\r\nThis study was reviewed and approved by the Psychology Department Research Ethics Committee at Lancaster University.\r\nThe topic of this study revolved around participants’ experiences of CB, which could involve reflection upon sensitive experiences (including those of violence and destructive behaviour) that elicit negative psychological reactions (such emotional upset, worry, stress, and shame). Furthermore, the minimum age specified for participants is 12 years old, so some participants recruited would be minors (i.e. a vulnerable participant group).\r\nIn case the discussion of CB experiences elicited negative psychological reactions in participants, contact information for sources of wellbeing support was given as part of the study debrief for both young and adult participants (e.g., talking to a trusted family member or a teacher; information and contact details for free services such as Childline, the Samaritans, The CB Foundation etc.). Offering access to support services was particularly important to younger participants, who may not feel able to speak to their parents about any issues they have.\r\nFurthermore, consent was required from all participants over the age of 16. If a participant indicated being under the age of 16, consent was sought from a parent/guardian, whilst assent was obtained from all 12-to-15-year-old participants. Consent and assent were monitored throughout the study. All participants were given sufficient opportunity to understand the nature, aims and expected outcomes of research participation. Complex technical information was suitably adapted so that participants aged under 16 years old could give consent to the extent that their capabilities allowed. \r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"1839"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1840"},["text","Data/SPSS.sav"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"1841"},["text","LaverickBrown2018"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"1842"},["text","Rebecca James"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"1843"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"1844"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1845"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1846"},["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":"1847"},["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":"1848"},["text","Chris Walton"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"1849"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"1850"},["text","Clinical"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"1851"},["text","Seventy-four typically developing individuals"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"1852"},["text","None"]]]]]]]],["item",{"itemId":"63","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"53"},["src","https://johnntowse.com/LUSTRE/files/original/6706f99fb62f6749b7c0d33bae37059f.pdf"],["authentication","38f45aae780ada036b447d77607c2a80"]]],["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":"1552"},["text","Investigating the effects of dimensionality and referent variability on word learning in autism and typical development.\r\n"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"1553"},["text","Fiona Smith\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":"1554"},["text","2015"]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1555"},["text","Dimensionality, referent variability, word learning."]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2142"},["text","The ability to learn words from pictures could give children another forum to develop\r\ntheir lexical understanding and vocabulary. This is particularly important for children\r\nwith developmental disorders such as Autism. This research investigated how word\r\nlearning processes (referent selection, retention and generalisation) in autism and\r\ntypical development are influenced by learning from pictures and objects, including\r\nsingle and multiple exemplars of symbols. The participants in this study were 16\r\ntypically developing children, M age=3.68, the TD group was composed of 7 males\r\n(43.75%) and 8 females (56.25%). And 16 children diagnosed with ASD, M\r\nage=9.37, 8 males (50%) and 8 females (50%). Participants looked at pictorial and\r\nobject referents. This was to differentiate whether there was a preference in word\r\nacquisition and retention, depending on the structure of the stimuli. It was expected\r\nthat word referent selection, retention and generalisation would be more accurate in\r\nthe object condition compared to the picture condition, as participants would not be\r\nrelying of picture-word-associations. Participants also examined words paired with\r\neither single or multiple exemplars of referents, to determine whether multiple \r\nexemplars of shaped matched referents would promote shape-based generalisation\r\nin the ASD group, which has been shown to be impaired (Hartley and Allen, 2014).\r\nIt was expected that retention would be superior when learning directly from objects\r\nin both the ASD and TD groups, which was found in this research. We also\r\nanticipated that labelling from multiple exemplars, rather than single exemplars,\r\nmay scaffold more consistent shape-based generalisation. We found that referent\r\nselection was more accurate in both groups in the multiple exemplar condition\r\ncompared to the single exemplar condition. The implications of this research are\r\nthat we can further understanding of how symbols or objects benefit word learning,\r\nretention and generalisation in ASD or TD children. And whether there are any\r\ncognitive differences in the ASD and TD groups when it comes to word learning\r\nprocesses. "]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"2143"},["text","Participants\r\nThe participants in this study were 16 minimally verbal children with ASD (M age =\r\n10.42 years, SD = 3.29) and 16 typically developing children (M age = 3.64, SD =\r\n1.64).\r\nChildren with ASD were recruited from the specialist schools Dee Banks School in\r\nChester, and Hinderton School in Ellesmere Port. Typically developing children were\r\nrecruited via opportunity sampling, via the social media platform Facebook through\r\nadvertisement. \r\nAll the children with ASD received their diagnosis from a qualified clinical or\r\neducational psychologist. This was obtained using standardised instruments (i.e.\r\nAutism Diagnostic Observation Scale and Autism Diagnostic Interview—Revised;\r\n(Lord, Rutter & Le Couteur, 1994, Lord, Rutter, DiLavore & Risi, 2002) and expert\r\njudgment. Clinical diagnosis was confirmed for children with autism using the\r\nChildhood Autism Rating Scale (CARS; Schopler, Van Bourgondien, Wellman &\r\nLove, 2010), which was completed by a class teacher (Raw Score M score = 37.26,\r\nRaw Score range = 27 – 53.5). The ASD were tested for non-verbal vocabulary using\r\nthe British Picture Vocabulary Scale (BPVS; Dunn, Dunn, Whetton, & Burley, 1997),\r\nwhich was conducted by the experimenter. Mean receptive vocabulary of children\r\nwith autism was years 2.84 (range = 6 years – 2 years 4 months).\r\nSome of the children diagnosed with ASD who participated in this study were current\r\nPECS-users with impaired expressive language skills. Most of the children with ASD\r\nwho participated in this study were functionally non-verbal (no spoken words),\r\nalthough, some produced speech of 1–2 words in length (however, much of this was\r\necholalia) and one child could speak some short phrases over three words in length.\r\nTherefore, the sample was linguistically representative of children with ASD who\r\nreceive and may benefit from picture-based communication interventions. Participants\r\nhad 1–6 years’ experience of using PECS.\r\nWhen recruiting the children diagnosed with ASD, the experimenter emailed\r\nspecialist schools, explaining the study and whether the school would be interested in\r\nparticipating. When recruiting the TD children, advertisements were put on social \r\nmedia platforms such as Facebook (see Appendix A). The information poster\r\ninstructed the parents to contact the experimenter via email if they were interested in\r\ntheir child participating.\r\nThe study was approved by the Lancaster University Ethics Committee and informed\r\nconsent was obtained from parents before children were included in the study.\r\nSee Appendix B for completed and approved Lancaster University Ethics Committee\r\nform\r\nMaterials\r\nFor the warm up test trials in all tests the participants were shown three familiar\r\nobjects (for example; dog, bus, chair), these were small laminated pictorial symbols.\r\nIn the picture, single and multiple exemplar conditions the participants were shown 12\r\nlaminated pictorial symbols, 6 familiar and 4 novel. The participants saw each novel\r\nsymbol once and the novel symbol twice. Participants saw the same named novel\r\nsymbols in the retention test trial, in this trial the named novel objects were shown to\r\neach participant twice. In the generalisation test trial, the participants saw shape\r\nmatches (same object or picture, for example both would be paperclips) to the named\r\nnovel objects from the referent selection test trial and retention test trial, however they\r\nwere different colour variations (for example a red and blue paperclip). In the object\r\ncondition participants followed the same test layout and number of referents as the\r\nother conditions, the difference being that the stimuli were actual objects compared to \r\npictorial symbols. The words for the familiar stimuli were gathered using the CDI\r\ndatabase (Fenson, Dale, Reznick, Bates, Thal, Pethick, Stiles, 1994) and appropriately\r\naged matched to the non-verbal age range of the ASD children and the chronological\r\nage of the TD children (See Appendix C). The words for the novel stimuli were\r\npicked from the NOUN database (Horst & Hout, 2016), these were picked to all be\r\ntwo syllables long and words to have different phonological sounds per set. In the\r\npicture condition were, Gloop, Virdex, Akar and Teebu. For the novel words for the\r\nobject condition were, Fiffin, Tranzer, Brisp and Pentants. For the single exemplar\r\ncondition the novel word were, Tulver, Kaki, Jefa and Blicket. For the multiple\r\nexemplar condition the novel word were, Zepper, Toma, Modi and Chatten (see\r\nAppendix D)\r\nObjects were obtained through the equipment assistant at Lancaster University and\r\npurchased through amazon. Appendix E is an example warm up selection trial which\r\na participant saw, and the response form completed by the experimenter. Appendix F\r\nis an example of a referents selection trial, which participant saw, and the response\r\nform completed by the experimenter. Appendix G is an example of a retention test\r\ntrial a participant will have seen, and the response form completed by the\r\nexperimenter. Appendix H is an example of the generalisation test trial which a\r\nparticipant saw, and the response form completed by the experimenter. All test trials\r\nwere pseudorandomised per participant per condition and trial. Therefore, while all\r\nthe participants will have seen the same number of familiar and novel objects or\r\npictures. And each picture or object will have had the same name per shape matched\r\nobject they will have been in a different order. Therefore, a different response form\r\nwas required per participant, for the change in referent location and set order. \r\nProcedure\r\nPrior to the children participating the parents received, the information sheet (see\r\nAppendix I), and the consent form (see Appendix J). On the last day of experiments\r\nthe experimenter brought the debrief forms (see Appendix K).\r\nParticipants were test individually, in their schools for the children with ASD or in\r\ntheir own homes for the TD children, and were always accompanied by a familiar\r\nadult, teaching assistant or parent. The participants were seated at a table opposite the\r\nexperimenter; the materials were placed within reaching distance of the participants.\r\nChildren were reinforced throughout the session; correct performance was only\r\nreinforced during the warm up trial. The first test examined the picture condition vs\r\nthe object condition, the second test examined single vs multiple exemplars. The tasks\r\nwere between participants, as they were examining the results of the TD group\r\ncompared to the ASD group, however for the analysis some within participants\r\nanalysis was carried out to determine accuracy between test conditions (e.g. picture vs\r\nobject). Each task always consisted of a warm up stage, referent selection trial,\r\ndistracter familiarisation trial, retention test trial and generalisation test trial. The test\r\ntrials were based on that done by Horst and Samuelson in 2008, with the extension of\r\nthe generalisation trial which was not included in the Horst and Samuelson (2008)\r\nstudy.\r\nPicture Condition vs Object Condition Tests\r\nWarm Up Stage\r\nParticipants were shown three sets of three familiar objects, in the object condition, in\r\nthe picture condition participants were shown three familiar pictures. Participants\r\nwere asked to identify each in turn, the warm up objects or pictures were\r\npseudorandomised per participant, changing the order and location per participant per\r\ncondition. The pictures or objects were removed and reordered after each set, and the\r\nparticipants response recorded.\r\nReferent Selection Trial\r\nParticipants were shown four sets of stimuli (pictures for the picture condition and\r\nobjects for the object condition) the sets of stimuli were different per condition, each\r\nconsisting of two familiar items and one novel item, each set was shown four times,\r\nthe novel referent was shown twice and the two familiar referents once. The order and\r\nlocation of the sets was pseudorandomised for each participant, the location of the\r\nnovel object was never in the same location twice consecutively, and a novel or\r\nfamiliar object or picture was never requested more than twice consecutively. Sets\r\nwere not presented twice in a row.\r\nDistractor Familiarisation\r\nTo control for novelty or familiarity preferences in the subsequent test trials, children\r\nwere shown all the novel objects that used in generalisation test trials. The new novel\r\nobjects were a different colour variation of a previously seen novel object, which was\r\nnamed in the referent selection trial. Novel objects or pictures were shown against a\r\npreviously named novel objects or pictures, which was not a shape or colour match to\r\nthe new novel object. Objects or pictures were shown so one previous named novel \r\nobject was shown against a new novel object or picture. The objects were not shape or\r\ncolour matched, the objects or pictures were placed in front of the participant, they\r\nwere not asked to identify them just to “look”.\r\nRetention Test Trial\r\nRetention trials will assess children’s memory of the newly-learned word-referent\r\npairings. Participants were shown four sets; each set was shown twice with the target\r\nobject requested twice. The sets were made up of three named novel objects, names\r\nwere picked from the NOUN database (Horst & Houst, 2016), each made up of two\r\nsyllables, objects or pictures were picked on the basis that participants items that\r\nwould be novel to them, for instance gym or plumbing equipment. Objects and\r\npictures which were not shape or colour matches to each other and were shown in the\r\nreferent selection test trial. The order and location of each object or picture per set\r\nwas pseudorandomised per participant per trial. The location of the novel object was\r\nnever in the same location twice consecutively, and a novel or familiar object or\r\npicture was never requested more than twice consecutively. Sets were not presented\r\ntwice in a row.\r\nGeneralisation Test Trial\r\nGeneralisation trials will assess children’s extension of labels to new items.\r\nParticipants were shown four sets; each consisting of three objects or pictures, each\r\nset was shown twice with the target object being requested twice. The objects or\r\npictures in the sets were shape matches to the objects or pictures shown in the referent\r\nselection, and retention trials, but different colour variations. All the shape matched \r\nobjects or pictures were also colour matched to a non-shape matched object from the\r\nprevious conditions. The order and location of each object or picture per set was\r\npseudorandomised per participant per trial. The location of the novel object was never\r\nin the same location twice consecutively, and a novel or familiar object or picture was\r\nnever requested more than twice consecutively. Sets were not presented twice in a\r\nrow.\r\nSingle vs Multiple Exemplars Tests\r\nWarm Up Trial\r\nParticipants were shown three sets of three familiar pictures in both the single and\r\nmultiple exemplar conditions. Participants were asked to identify each in turn, the\r\npictures were pseudorandomised per participant, changing the order and location per\r\nparticipant per condition. The pictures were removed and reordered after each set, and\r\nthe participants response recorded.\r\nReferent selection Trial\r\nParticipants were shown four sets of stimuli, the sets of stimuli were different per\r\ncondition, each consisting of two familiar items and one novel item, each set was\r\nshown four times, the novel referent was shown twice and the two familiar referents\r\nonce. In the multiple exemplar trial, two differently-coloured versions of each\r\nunfamiliar object were named (one per novel trial for each set). The order of the sets\r\nwas pseudorandomised for each participant. The order and location of each object or\r\npicture per set was pseudorandomised per participant per trial. The location of the\r\nnovel object was never in the same location twice consecutively, and a novel or \r\nfamiliar object or picture was never requested more than twice consecutively. Sets\r\nwere not presented twice in a row. The order and location of the sets was\r\npseudorandomised for each participant, the location of the novel object was never in\r\nthe same location twice consecutively, and a novel or familiar object or picture was\r\nnever requested more than twice consecutively. Sets were not presented twice in a\r\nrow.\r\nDistractor Familiarisation\r\nTo control for novelty or familiarity preferences in the subsequent test trials, children\r\nwere shown all the novel pictures that used in generalisation test trials. The new novel\r\npictures were a different colour variation of a previously seen novel picture referent,\r\nwhich was named in the referent selection trial. Novel pictures were shown against a\r\npreviously named novel pictures, which was not a shape or colour match to the new\r\nnovel picture. Pictures were shown so one previous named novel referent was shown\r\nagainst a new novel picture. The referents were not shape or colour matched, the\r\npictures were placed in front of the participant, they were not asked to identify them\r\njust to “look”.\r\nRetention Test Trial\r\nRetention trials will assess children’s memory of the newly-learned word-referent\r\npairings. Participants were shown four sets; each set was shown twice with the target\r\nreferent requested twice. The sets were made up of three named novel objects, names\r\nwere picked from the NOUN database (Horst & Houst, 2016), each made up of two\r\nsyllables, pictures were picked on the basis that participants items that would be novel\r\nto them, for instance gym or plumbing equipment. Pictures which were not shape or \r\ncolour matches to each other and were shown in the referent selection test trial. The\r\norder and location of each picture per set was pseudorandomised per participant per\r\ntrial. The location of the novel object was never in the same location twice\r\nconsecutively, and a novel or familiar object or picture was never requested more than\r\ntwice consecutively. Sets were not presented twice in a row.\r\nGeneralisation Test Trial\r\nGeneralisation trials will assess children’s extension of labels to new items.\r\nParticipants were shown four sets; each consisting of three pictures, each set was\r\nshown twice with the target object being requested twice. The pictures in the set were\r\nshape matches to the picture shown in the referent selection, and retention trials, but\r\ndifferent colour variations. All the shape matched pictures were also colour matched\r\nto a non-shape matched object from the previous conditions. The order and location\r\nof each picture per set was pseudorandomised per participant per trial. The location of\r\nthe novel object was never in the same location twice consecutively, and a novel or\r\nfamiliar picture was never requested more than twice consecutively. Sets were not\r\npresented twice in a row. In the multiple exemplar condition the generalisation test\r\ntrial introduced the shape matched referent in a third colour that was coloured\r\nmatched to a referent of a different shape matched seen in the referent selection or\r\nretention test trial. "]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"2144"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2145"},["text","Data/SPSS.sav"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"2146"},["text","Smith2015"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"2147"},["text","Rebecca James"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"2148"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"2149"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2150"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"2151"},["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":"2152"},["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":"1556"},["text","Calum Hartley\r\n"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"1557"},["text","MSC"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"2153"},["text","Cognitive, Developmental Psychology"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"2154"},["text","16 minimally verbal children with ASD and 16 typically developing children "]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"2155"},["text","ANOVA, Correlation, quantitative, t-test"]]]]]]]],["item",{"itemId":"202","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"229"},["src","https://johnntowse.com/LUSTRE/files/original/2fc9eb768f4d00d92b5e73627b2912cf.docx"],["authentication","2c3e89d0f82f7c2b4dd77fac20aa220e"]],["file",{"fileId":"230"},["src","https://johnntowse.com/LUSTRE/files/original/199d736584372c0beff6cff855b5aae8.xlsx"],["authentication","0fba9d41dead25b6239c2151286388d8"]],["file",{"fileId":"231"},["src","https://johnntowse.com/LUSTRE/files/original/aa42a4e75948741e54f7972ce17998eb.xlsx"],["authentication","75c7c9e87ba5477883053a77a5350982"]]],["collection",{"collectionId":"5"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"185"},["text","Questionnaire-based study"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"186"},["text","An analysis of self-report data from the administration of questionnaires(s)"]]]]]]]],["itemType",{"itemTypeId":"14"},["name","Dataset"],["description","Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing."]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"4028"},["text","Is selfie-related behaviour motivated by sexual orientation and gender conformity"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"4029"},["text","Wen Li"]]]],["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":"4030"},["text","2022-2023"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"4031"},["text","In the digital age, selfie culture has become an integral part of social media platforms. This globally widespread phenomenon created a distinctive form of self-expression, allowing selfie- makers to convey their identities, shape online personas, and build connections with others. Selfies are more than photos presented but also refer to a series of backstage to finally lead to creation and sharing. As research into selfies, gender differences in selfie-related behaviours have enabled further comprehension of selfies in terms of self-expression. Social Role Theory (SRT) explained the existence of gender differences in selfie culture that gender role norms and social expectations shape individuals' identity and behaviours. This study explored the concept of gender conformity among heterosexuals and non-heterosexuals and the impact on selfie-related behaviours. A total of 120 participants, categorized into heterosexual men, heterosexual women, non-heterosexual men, and non-heterosexual women, engaged in an online questionnaire, and contributed a total of 150 selfies. Data analysis involved one-way variance (ANOVA) to test the differences between the four groups, and multiple regression analysis to assess the influence of gender, the Traditional Masculinity-Femininity (TMF) scale and sexual attraction to me score. The results revealed no differences across the four groups in terms of the nine domains of selfie motives, as well as preoccupation. However, retention of moments and entertainment as the most prominent motives for selfies. For selfie behaviours, time spent on taking, editing, and selecting selfies, as well as taking amount and edit frequency differed significantly among the four groups. Specifically, both heterosexual women and non-heterosexual women tended to allocate more time on taking, editing, and selecting selfies for posting. Meanwhile, heterosexual women and non-heterosexual men displayed a higher trend for taking a greater number of selfies and editing selfies more frequently. These findings support the current studies indicating that women engage in selfie-related behaviours more actively than men, but more deeply that sexual orientation, especially the sexual attraction to men, also encourage some of selfie-related behaviours. While the results provide evidence for SRT as gender roles shape behaviours through socialisation, but also draw criticisms as TMF scale failed to predict the impacts on selfie-related behaviours and sexual orientation can break the traditional gender role expectations. Future research should keep exploring these relationships, offering deeper insights into gender conformity and gender non- conformity in the realm of self-presentation across diverse identity roles, thereby contributing to a more inclusive and diverse self-image narrative."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"4032"},["text","Selfie, Self-expression, Gender conformity, Sexual orientation"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"4033"},["text","Participants\r\nThis study recruited 120 normal adults as participants through a Qualtrics online questionnaire voluntarily and anonymously, of which 67 completed the questionnaire, including 22 men, 42 women and 3 self-identified as non-binary gender. However, since only binary gender was considered for the analysis of gender conformity, the three non-binary gender responses were removed. Additionally, in terms of sexual orientation, there were 48 heterosexuals, 6 homosexuals, 8 bisexuals and 2 others. The participants were divided into four sample groups, that is, 19 heterosexual men, 29 heterosexual women, three non-heterosexual men and 13 non-heterosexual women.\r\nMaterials\r\nSexual orientation and gender conformity were the two domains of prediction, and selfie- related behaviours were regarded as the outcomes. Sexual orientation was measured by self-rated sexual attraction to men and women, while gender conformity was measured by self-ascribed the Traditional masculinity/femininity (TMF) scale. As for selfie-related behaviour, it involves several aspects of selfie taking, editing, and posting. In addition, selfie motives and attributes of uploaded selfies were also be taken into account.\r\nSexual attraction score\r\nSexual orientation was self-identified by participants themselves as heterosexual, homosexual, bisexual, and others. The participants were asked to self-rated two statements about their sexual attraction to men and women. The latter, with some adjustment to Lippa's (2002) methodology, included two questions: \"I am sexually attracted to men\" and \"I am sexually attracted to women\". In both cases, participants were asked to self-rated on a scale of 0-10, where a higher score indicated greater sexual attraction to men or women. This measure transformed sexual orientation from a categorical variable to a continuous variable for further analyses of differences and relationships. In particular, the separate assessment of sexual attraction to men and sexual attraction to women could help to better detect whether sexual attraction to men is more influential in selfie-related behaviours.\r\nTraditional Masculinity-Femininity scale\r\nGender conformity was measured as a continuous variable by using the Traditional Masculinity-Femininity (TMF) scale from Kachel et al. (2016). This scale comprises of six questions which are self-rated on a scale of 1-7, with 1 represented very feminine and 7 represented very masculine. Example items include \"I consider myself as...\", \"Ideally, I would like to be...\" regarded their preferred gender role. The remaining four questions concerned identified gender roles in terms of interests, attitudes and beliefs, behaviours, and appearance from a traditional perspective, being asked respectively as \"Traditionally, my... would be considered as...\". Then, the mean score of these six items would eventually be used as the individual’s masculinity/femininity score.\r\nKachel et al.(2016) pointed out that the TMF scale had been proven to be a reliable one- dimensional construct tool to assess masculinity because it correlates well with another gender- related instrument, the Bem Sex Role Inventory (BSRI) and successfully distinguishes between groups, such as females vs. males, lesbians/gays vs. heterosexual females and males,that are expected to be different (See Figure 2).\r\nFigure 2\r\nMediation of the relation between BSRI and sexual orientation by the TMF (Kachel et al., 2016). Mean TMF scores separately for gender and sexual orientation (Kachel et al., 2016).\r\n   \r\nSelfie Coding\r\nParticipants were asked to upload 1-3 selfies that they would post on social media. All selfies were coded based on four aspects. First, participants were asked to whether their uploaded selfies had been edited or retouched. Then, the experimenter coded the number of people in the selfie (alone or in a group), the angle of the selfie (upward, horizontal, or downward), and the amount of body shown (face only, upper body, body without face, or whole body with face).\r\nMeanwhile, a total of 150 portrait pictures were collected from the participants, although 17 of them looked like taken by others rather than selfies.\r\nSelfie-related Behaviours\r\nSelfie-related behaviours and motivations measures were taken from Bij de Vaate et al. (2018). For motivations, 33 items were used to reflect nine domains of motives, and each item was an agreement extent scale (1 = totally disagree to 5 = totally agree). The nine domains of motives included \"Retention of moments\" (e.g., \"I make selfies to memorise a moment\"), \"Entertainment\" (e.g., \"Making selfies is enjoyable\"), \"Expressive information sharing\" (e.g., \"I tell others something about myself by using selfies\"), \"Social interaction\" (e.g., \"I make selfies to keep in touch with friends and family\"), \"Social use\" (e.g., \"I make selfies to show who I am and what I do\"), \"Habitual passing of time\" (e.g., \"Making selfies is a habit\"), \"Relaxation\" (e.g., \"Making selfies enables me to relax\"), \"Imaginary audience\" (e.g., \"I post selfies with a specific audience in mind\"), and \"Social pressure and identity\" (e.g., \"I make selfies because everybody does it\"). Preoccupation (e.g., \"I often share selfies\") implied the degree to take part in selfie behaviours, was measured with six items by an agreement extent scale (1 = totally disagree to 5 = totally agree). See Appendix A for specific questions of items in the questionnaire.\r\nSelfie-taking behaviour was measured by taking frequency, time spent and amount in the last three months, each of them was designed as an ordinal variable depending on an increasing degree. For instance, frequency referred to how often taking selfies, time spent referred to how long it taken within a selfie session, whereas amount referred to how many photos taken within a selfie session. Selfie-editing behaviour only accounted for two aspects, editing frequency and time spent, and selfie-posting behaviour used to select spend time instead of posting spend time.\r\nAdditionally, four items were designed to collect feedback on related concerns and feelings about selfies with a Likert scale that ranged from 0 (totally unconcerned) to 10 (totally concerned), including the attractiveness of their online image, the attention and comments of others on their selfies post on the social platform, the comparison with other people's selfies. Finally, 3 questions were designed to reflect participants’ satisfaction degree on their appearance in real life, before retouching and after retouching by the same 11-point Likert scale (0 = extremely uncomfortable to 10 extremely comfortable).\r\nProcedure\r\nThis study had been reviewed and approved by a member of the Psychology department from the Lancaster University Board of Ethics. At the beginning of the survey, participants were provided with a participant information sheet, informing them that the study is about selfie- related behaviours in terms of sexual orientation and gender conformity. Anonymity and confidentiality were ensured because of sensitive information such as selfies and sexual orientation. After the confirmation of the consent, all participants complete the same questionnaire which is conducted on Qualtrics (www.qualtrics.com).\r\nThe survey questionnaire (See Appendix A) was designed to collect information through six key sections. In the first section, some demographic information was asked, such as age,\r\nrelationship status, gender identity, sexual orientation, and sexual attraction. Then, it was a six- item self-ascribed Traditional Masculinity/Femininity (TMF) scale. For the third section, participants were expected to upload three different selfies that would be posted on social media and state whether these selfies have been retouched. This section was optional and if a selfie were uploaded, a specific selfie consent would be required to confirm. The last three sections involved a series of questions on selfie-motives and preoccupation, selfie-related behaviours and feelings. At the end of the survey, participants were given a debrief sheet upon completion and were allowed the chance to ask any questions after the survey was undertaken. Meanwhile, information consent would be confirmed to get the final approval about all responses before submitting the questionnaire.\r\nAnalysis \r\nPre-Tests\r\nFirstly, two pre-tests were conducted by one-way analyses of variance (ANOVA) to analyse differences in Traditional Masculinity/Femininity (TMF) score and sexual attraction to men score for each of the four sample groups, with corresponding post-hoc multiple comparison tests, to examine expected differences in TMF scale and sexual attraction to men score by the four sample groups.\r\nMain Tests\r\nSubsequently, selfie motives in nine domains, and preoccupation were examined for each of their differences across the four sample groups by ANOVAs with corresponding post-hoc multiple comparison tests.\r\nIn the context of selfie behaviours, we tested three relevant stages: selfie-taking, editing and posting. For each of these behaviours, we conducted ANOVAs with corresponding post-hoc\r\nmultiple comparison tests to assess differences across the four sample groups, and Multiple Linear Regression analyses to investigate the influences by self-identified gender, TMF score\r\nand sexual attraction to men score. In particular, we delved into three aspects of taking selfies, involving frequency, time spent, and amount. Similarly, we analysed two aspects of selfie editing, frequency and time spent, as well as three aspects of selfie posting , which included frequency, time spent on selection, and amount.\r\nIn addition, in order to examine whether selfie content itself was affected by gender conformity and sexual orientation, a total of 150 uploaded selfies were coded according to four attributes: editing usage, selfie format, the shown part in the selfie, and the taking angle. Each of the attributes was firstly tested by a chi-square test to examine the association between attribute and the four sample groups because both were categorical variables. Furthermore, we conducted two separate ANOVAs, each followed by post-hoc multiple comparison tests. One used the TMF scores and the other used sexual attraction to men scores, with each of the four attribute of these selfies as independent variables to test for differences. In these analyses, the TMF scores and sexual attraction to men scores, as interval data, were regarded as dependent variables.\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"4034"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"4035"},["text",".xlsx"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"4036"},["text","Li2023"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"4037"},["text","Mshary Al Jaber"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"4038"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"4039"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"4040"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"4041"},["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":"4042"},["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":"4043"},["text","Jaime Benjamin"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"4044"},["text","Developmental"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"4045"},["text","120"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"4046"},["text","ANOVA, Chi-sqaured, Regression"]]]]]]],["tagContainer",["tag",{"tagId":"5"},["name","gender coformity"]],["tag",{"tagId":"7"},["name","self -xpression"]],["tag",{"tagId":"8"},["name","Selfie"]],["tag",{"tagId":"6"},["name","sexual orientation"]]]],["item",{"itemId":"154","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"172"},["src","https://johnntowse.com/LUSTRE/files/original/3ddc0d86634b8437530ec3352beb2ebc.pdf"],["authentication","1ad80421bc21a8ecbaac8b6704bb657f"]]],["collection",{"collectionId":"2"},["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":"179"},["text","Eye tracking "]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"180"},["text","Understanding psychological processes though eye tracking"]]]]]]]],["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":"3165"},["text","Levodopa and antisaccade performance in Parkinson’s disease: the influence of intrinsic dopaminergic functioning, dopamine agonists and chronic anti-parkinsonian medication "]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"3166"},["text","Amy Austin"]]]],["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":"3167"},["text","14th September 2022"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3168"},["text","The antisaccade (AS) task is a validated eye-tracking paradigm primarily used to assess response inhibition. Although several studies have established AS error rate and latency to be increased in Parkinson’s disease (PD), the evidence regarding the effect of existing anti-parkinsonian medication (e.g., levodopa) on these parameters is contradictory. According to the dopamine overdose hypothesis (DOH), the effect of levodopa on AS performance should be dependent upon the intrinsic dopaminergic functioning of the individual. The current study is the first study to use spontaneous eye blink rate (SEBR), a proxy measure for dopamine activity, to investigate the influence of intrinsic dopaminergic functioning on AS performance following levodopa consumption. The influence of additional PD related factors was also examined. SEBR and AS performance was assessed in eleven healthy controls (HC) and nine participants with PD. SEBR and AS performance was assessed twice in participants with PD, once 30 minutes prior to, and once one hour after, the consumption of levodopa. Pre-levodopa consumption SEBR was a significant positive predictor of AS error rate post, but not pre, levodopa consumption. Total years consuming anti-parkinsonian medications was positively predictive of AS error rate both pre and post levodopa consumption. The regular consumption of dopamine agonists was found to significantly predict fewer AS errors following the consumption of levodopa. The current results support the DOH; higher intrinsic dopaminergic functioning was associated with increased AS errors following the artificial stimulation of dopamine via by levodopa. Therefore, artificial dopaminergic stimulation of an intrinsically sufficiently functioning dopaminergic system appears to produce an overstimulation/overdose effect whereby consequential detrimental effects on AS performance/response inhibition are observed. The current findings go some way in explaining the inconsistencies within the literature. "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3169"},["text","Keywords: Parkinson’s disease, dopamine overdose hypothesis, spontaneous eye blink rate, levodopa, dopamine agonists, antisaccade "]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"3170"},["text","Twenty-one participants, 10 individuals with mild-moderate idiopathic PD (Mage = 67.10, SDage = 8.63) and 11 healthy control older adults of comparable age (HC; Mage = 66.82, SDage = 9.09) were recruited to the study. The mean age of recruited HC and PD individuals did not differ significantly, t (18.95) = - 0.07, p = .943). Participants were recruited via established research databases and via the social network of the researcher. As the current study focused on PD, participants with a diagnosis of any neurological conditions (beyond PD) were excluded. Additionally, as depression and anxiety influence an individual’s saccadic performance profile and SEBR (Jazbec et al., 2005; Mackintosh et al., 1983), individuals who obtained a clinically moderate depression or anxiety score, as measured by the Hospital Anxiety and Depression scale (HADS), were excluded. Similarly, mild cognitive impairment (MCI) and dementia are associated with increased AS error rate and AS latency (Opwonya et al., 2022), and increased SEBR (D’Antonio et al., 2021). As such, those who presented a cognitive profile indicative of MCI/dementia (score < 82 on the Addenbrookes Cognitive Exam-III, ACE-III; Hsieh et al., 2013) were excluded from the current study. Finally, as experimental stimuli in the current study were coloured red and green, individuals with red-green colour vision deficiency, detected via the Ishihara test (Ishihara, 1917) were also excluded. \r\nOn these grounds of exclusion, one individual with PD was excluded from the current study due to obtaining an ACE-III score indicative of MCI. Subsequently, nine individuals with mild-moderate idiopathic PD (Mage = 65.89, SDage = 8.21) and eleven HC individuals (Mage = 66.82, SDage = 9.09) participated in the study. All participants had normal or corrected to normal vision. \r\nAll participants with PD were classified as Hohen and Yahr stage II or below (Hoehn & Yahr, 1998), indicating they were physically independent and capable of completing all study tasks. At the time of testing, all PD participants were receiving anti-parkinsonian medication (see table 2 for PD sample anti-parkinsonian medication summary). All PD participants were tested under their normal medication regime, that is, participants attended the study 30 minutes prior to the consumption of their next, normally scheduled, dosage of levodopa-based medication. Accordingly, measures were obtained both pre (30 minutes prior) and post (1 hour after) levodopa consumption, permitting the respective investigations of pre and post levodopa consumption SEBR, motor symptom severity, AS performance and PS performance. \r\nAn online calculator computed the levodopa equivalent daily dosages (LEDD) for each participant with PD. LEDD indicates the equivalent amount of levodopa an individual receives from all anti-parkinsonian medications across a 24-hour window (Julien et al., 2021). The online calculator can be accessed via: https://www.parkinsonsmeasurement.org/toolBox/levodopaEquivalentDose.htm \r\nMaterials and measures \r\nOnline questionnaire \r\nA questionnaire comprised of a demographics and health screening survey, the Edinburgh handedness inventory (EHI), the HADS, and a PD and associated medication \r\nsurvey was developed and distributed via Qualtrics (Qualtrics, 2013). The questionnaire required 15 minutes to complete. \r\nDemographics and health screening survey. Participants were asked to disclose key demographic and health information (e.g., age, sex, whether they had normal or corrected to normal vision). Participants were also asked to disclose any history of visual impairments, neurological conditions (beyond PD), psychiatric illness, or rheumatic illness. \r\nThe EHI (Oldfield, 1971). The EHI is a highly reliable (r = .97, p < .001; Oldfield, 1971) and internally consistent (a = 0.88; Oldfield, 1971) self-report measure of an individual’s hand dominance (Edlin et al., 2015). Participants are requested to indicate their typical hand preference, via five-point Likert scales ranging from ‘always left’- ‘always right’, when completing a range of daily activities (e.g., writing). A final score of ≥ 50 indicates right hand dominance, < 50 to > −50 indicates ambidexterity, and ≤−50 indicates left hand dominance. As hand dominance typically corresponds to ocular dominance (McManus et al., 1999), the EHI was used to infer the dominant eye of each participant in the current study. Monocular eye tacking was then conducted on the dominant eye (Ehinger et al., 2019). \r\nThe HADS (Zigmond & Snaith, 1983). The HADS is a short self-assessment questionnaire validated to detect anxiety and depression within the general population, inclusive of the elderly (Bjelland et al., 2002). Respondents are required to indicate, via four- point Likert scales, how 14 items relate to their recent feelings. Responses range from ‘0’ (the item has little relevance to recent feelings), to ‘4’ (the item is significantly representative of recent feelings). Likert responses are summed separately for anxiety and depression relevant items. Scores of seven or less indicate no notable presence of anxiety and depression. Scores ranging between eight and 10 indicate mild levels, between 11 and 14 indicate moderate levels, and between 15 and 21 indicate severe levels. \r\nPD and associated medication survey. Individuals with PD were asked to disclose further health information regarding the number of years since their PD diagnosis, which anti-parkinsonian medications they were currently receiving, the daily dosages of these medications and the total number of years they had been consuming anti-parkinsonian medications. \r\nACE-III (Hsieh et al., 2013) \r\nThe ACE-III is a well validated (Hseih et al., 2013), highly reliable and internally consistent (ICC = 0.92, a = 0.87 respectively; Takenoshita et al., 2019) cognitive assessment used to screen for the presence of MCI and dementia syndromes (Hsieh et al., 2013). To provide a global neuropsychological evaluation, participants are asked to complete tasks assumed to relate to five principal cognitive functions, namely: memory, language, attention, visuospatial skills, and verbal fluency (Hodges & Larner, 2017). Scores ascertained from each of the five domains are summed and the individual receives an overall score relative to the maximum possible score of 100. Higher scores indicate better cognitive functioning. A score below 82 is indicative of cognitive impairment. \r\nIshihara colour deficiency test (Ishihara, 1917) \r\nThe Ishihara colour deficiency test is a 38-item assessment of red-green colour perception. Typical red-green colour vision is marked by the ability to correctly decipher a number or pattern embedded within 38 red/green circular images. The test requires three minutes to complete. \r\nMDS-UPDRS (Goetz et al., 2008) \r\nBoth motor and non-motor PD symptoms were evaluated using the MDS-UPDRS. The MDS-UPDRS is comprised of four distinct subscales. Subscale I focuses on non-motor symptoms associated with PD (e.g., cognitive impairment, dopamine dysregulation syndrome), whereas subscales II – IV focus on the motor symptoms associated with PD. Subscales I, II and IV require participants to retrospectively respond with answers reflecting their average symptoms/experiences over the previous week. Whereas subscale III directly assesses current functioning via a motor exam. The motor examination requires participants to perform a series of motor tasks (e.g., finger tapping, walking, arising from a chair) under the observation of the examiner. The examiner rates the severity of motor impairment displayed during each motor task performed. All subscales of the MDS-UPDRS are scored according to four-point-Likert scales whereby ‘0’ indicates no impairment and ‘4’ indicates the most severe impairment. Hoehn and Yahr (Hoehn & Yahr, 1998) stages were calculated based upon the MDS-UPDRS assessment. The accumulative score of subscales I, II, III and IV provide an overall MDS-UPDRS score indicative of PD severity. A maximum score of 199 is reflective of the most severe disability the result of PD (Holden et al., 2018). The MDS-UPDRS requires approximately 30 minutes to complete. \r\nSEBR \r\nSEBR was assessed by recording participant’s eye movements whilst sitting at rest. The recording device was located approximately 55cm directly in front of the participant. Participants were not informed that they were completing an assessment of their blink rate, nor were they engaged into conversation with the examiner as both informing participants that their blink rate is being assessed and conversing increase SEBR (Doughty, 2001). Participants eye movements were recorded for two-and-a-half minutes however, only the last one minute of each recording was coded for SEBR (one minute is sufficiently long enough to obtain a representative blink rate, Deuschl & Goddemeier, 1998). A blink was identified (and coded accordingly) as full eye lid closure which was the result of bilateral movement of the eyelids (Kimber & Thompson, 2000). SEBR was scored as the number of blinks per minute. PD participant pre-levodopa consumption SEBR was considered their baseline SEBR, reflective of intrinsic dopaminergic functioning (Kimber & Thompson, 2000).
\r\nEye tracking tasks \r\nApparatus \r\nA desktop mounted eye tracker (Eyelink Desktop 1000), operating in monocular mode, with a sampling rate of 500 Hz was used to record eye movements of the participant’s dominant eye. An adjustable chin rest with attached forehead rest was utilized to minimise head movements. The eye tracking camera was located at the base of the stimuli presenting computer monitor. Participants sat approximately 55cm away from the eye tracking camera and computer monitor. A 4-point calibration, whereby participants are asked to fixate upon a red circle as it moves from the top, bottom, right and left side of the computer screen, was used prior to the commencement of all eye tracking tasks. Frequent calibration improves the accuracy of eye-tracking data (Pi & Shi, 2019). All eye tracking tasks were developed and operated using experiment builder software version 1.10.1630. Habitual eye glass wearers were not required to remove their eyeglasses during eye tracking tasks. Eye tracking tasks required approximately 10 minutes to complete.
\r\nProsaccade task \r\nParticipants completed four practice trials and 16 experimental gap trials. To centre a participant’s gaze at the start of each trial, a white fixation stimulus was presented for 1000 milliseconds (ms) in the centre of a back computer screen. A red lateralised target was then displayed randomly either to the right or the left of the central fixation for 1200ms at 4 ° eccentricity. The PS task operated according to the gap paradigm. Accordingly, to create a temporal gap between fixation and target stimuli, a black interval screen was presented for 200ms between the extinguishing of the white fixation stimulus and the presentation of the red target stimulus. For the PS task, participants were instructed to shift their visual focus towards the location of the red target as quickly and as accurately as possible. \r\nAntisaccade task \r\nParticipants completed four practice trials followed by 24 experimental gap trials. Participants were presented with a white central fixation stimulus on a black computer screen for 1000ms. Following a 200ms black interval screen, a green lateralised target stimulus was presented at random to either the left or right of the central fixation. The green target was displayed for 2000ms at 4 ° eccentricity. Participants were instructed to shift their visual focus to the opposite direction of where the green target stimulus appeared. An example of a successful trial would be as follows, if the green target stimulus was presented left-lateralised, participants should direct their gaze to the right side of the computer screen. \r\nProcedure \r\nThe present study was reviewed and approved by Lancaster University’s ethics committee. All participants provided informed consent prior to participating. \r\nParticipants were tested on one day and testing sessions took no longer than two hours. Individuals with PD completed SEBR assessments, MDS-UPDRS III motor examinations and all eye tracking tasks twice, once 30 minutes prior to consuming their usually scheduled dosage of levodopa medication, and once again one hour following the consumption of their levodopa medication. Prior research indicates that one hour is sufficient for levodopa to be metabolized and produce therapeutic effects (Lu et al., 2019). This method of testing the effect of anti-parkinsonian medications is widely used within the literature and no detrimental effects of this method have been reported (Cools et al., 2003). Similarly, re- test on the PS and AS tasks does not significantly influence performance (Larrison-Faucher et al., 2004). HC participants completed all study tasks once. \r\nAll participants completed the online questionnaire 48 hours prior to attending testing sessions. Upon arriving to testing, all participants completed an assessment of SEBR followed by the PS and the AS tasks. HC participants then completed the ACE-III and the Ishihara test. HC participation in the study was then complete. PD participants continued with further testing. Specifically, PD participants then completed the MDS-UPDRS subscale III motor examination. PD participants then consumed their usual dose of levodopa medication at their usual time. During the one-hour levodopa metabolization period, participants with PD completed subscales I, II and IV of the MDS-UPDRS, the ACE-III and the Ishihara test. \r\nOnce one hour had elapsed, individuals with PD then re-completed an assessment of SEBR, the PS and the AS task, and were also re-assessed via the MDS-UPDRS subscale III motor examination. Thus, motor symptom severity (MDS-UPDRSIII), SEBR and eye- tracking data were obtained from both pre (baseline) and post levodopa consumption medication states. \r\nData processing \r\nRaw data were extracted via EyeLink using DataViewer Software Version 3.2 and processed offline using the bespoke software SaccadeMachine (Mardanbegi et al., 2019). SaccadeMachine removes noise and spikes within the data; frames with a velocity signal greater than 1500 deg/s or with an acceleration signal greater than 100,000deg2/sec are filtered out. Fixations and saccadic events were detected via the EyeLink Parser. Trials were excluded where participants failed to direct their gaze to the central fixation stimulus. To ensure saccadic data were reflective of responses to target presentation, a temporal window of 80-700ms from the initial onset of the target stimulus was used (i.e., anticipatory saccades produced prior to 80ms, and excessively delayed saccades produced after 700ms were excluded). The following variables were extracted from the processed data: PS latency (the time taken between the onset of the target stimulus and the first correct fixation), PS error rate (the number of times the participant failed to generate a reflexive saccade to fixate upon the target stimulus), AS latency (the time taken between the onset of the target stimulus and the first correct fixation in the opposite direction to the target stimulus), AS error rate (the number of times a participant erroneously performed a reflexive PS towards the novel target stimulus instead of looking away). "]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"3171"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3172"},["text","Data/R.csv"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"3173"},["text","Austin 2022"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3174"},["text","Rachel Jordan\r\nSian Reid"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"3175"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"3176"},["text","N/A"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3177"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3178"},["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":"3179"},["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":"3403"},["text","Dr Megan Readman"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"3404"},["text","Msc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"3405"},["text","Neuro-clinical psychology"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"3406"},["text","20 (9 individuals with mild-moderate Parkinson's disease, 11 healthy control individuals of similar age)"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"3407"},["text","Regression, T-Test"]]]]]]]],["item",{"itemId":"148","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"146","order":"2"},["src","https://johnntowse.com/LUSTRE/files/original/055f608897628d54c7f2a243de72eb63.txt"],["authentication","849ed4bf5f0ebe3ec34bccd7856d6c63"]],["file",{"fileId":"147","order":"3"},["src","https://johnntowse.com/LUSTRE/files/original/0caf76688d0fd87a937daad8cef0af66.txt"],["authentication","913353fac700af17d02d4381a7540773"]],["file",{"fileId":"148","order":"4"},["src","https://johnntowse.com/LUSTRE/files/original/3385513f4c4cf01a4bbf9e074f9fcf10.csv"],["authentication","16a611e6b866f8552c70c6cb4c5f698a"]],["file",{"fileId":"143","order":"5"},["src","https://johnntowse.com/LUSTRE/files/original/8c74bde845d079abadf048bba0316db4.doc"],["authentication","c06cb4848dbba3e5b81d80f0518d47b5"]],["file",{"fileId":"149"},["src","https://johnntowse.com/LUSTRE/files/original/0dfdf4ec4a7cc89c6cc485920a130a43.doc"],["authentication","ebc62a1e24e476b869cb3c367f917845"]]],["collection",{"collectionId":"2"},["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":"179"},["text","Eye tracking "]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"180"},["text","Understanding psychological processes though eye tracking"]]]]]]]],["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":"3062"},["text","Lights, Camera, Action: Investigating Advertisement Susceptibility in Films Amongst Individuals with Parkinson’s Disease and Controls. "]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"3063"},["text","Elena Ball"]]]],["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":"3064"},["text","07.09.2022"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3065"},["text","Product placement is the merging of entertainment with advertising, and its presence in our daily lives is increasing. Despite this, there is an inherent lack of consideration of its influence amongst vulnerable populations such as individuals with Parkinson’s disease (PD). Research suggests that individuals with PD have reduced inhibitory control (IC) which may drive impulsive behaviours. A concernment, therefore, is the influence that product placement may have on the purchase behaviour of individuals with PD alongside a possible propensity to partake in risky and impulsive behaviours. Thus, this study aimed to examine whether reduced IC increases the likelihood that an individual with PD will be susceptible to product placement. The study adopted an experimental approach, recruiting 20 healthy younger controls, 20 healthy older controls, and 13 individuals with mild to moderate PD to participate in watching two films containing product placement; one featuring Coca Cola and the other an Audi. A pre and post product placement questionnaire was used to measure change in purchase behaviour before and after exposure to product placement, and an antisaccade eye tracking task and a Stroop task was used to measure IC. An ANOVA indicated that IC was significantly impaired in individuals with PD compared to healthy controls.  Despite this, linear mixed effects modelling suggested that IC may not be a factor that increases the likelihood that an individual will be more susceptible to product placement. Implications of these findings are discussed relative to other clinically vulnerable populations with similar cognitive impairment symptomology, and the consequent need for future research to continue to explore product placement susceptibility amongst vulnerable populations. \r\n\r\n"]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3066"},["text","Parkinson’s Disease, Inhibitory Control, Product Placement Susceptibility \r\n\r\n"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"3067"},["text","Method\r\nParticipants\r\nA voluntary sample of 54 participants were recruited, 20 healthy younger controls (YC) (16 females and four males, (Mage= 22.70, SDage= 2.42)), 20 healthy older controls of comparable age to those with Parkinson’s (OC) (females and males, (Mage= 66.85, SDage= 8.53)), and 15 adults with mild-moderate idiopathic PD (females and males, (Mage= 65.00, SDage= 7.84)). As this research area is entirely novel this sample size was modelled on comparable population studies that have explored IC (Meyer et al., 2020; Paz-Alonso et al., 2020).  YC were defined as young adults aged between 18 to 26 years old with no neurological or cognitive conditions (Stroud et al., 2015). OC were defined as adults aged between 50 to 85 years old with no neurological or cognitive conditions (Zhang et al., 2020). The participants with PD had been diagnosed with mild-moderate idiopathic PD, characterised by mild-moderate impairments of motor and cognitive functioning (DeMaagd & Philip, 2015). \r\nThe exclusion criteria for both the healthy controls and individuals with PD were those who had a diagnosis of any additional neurological or cognitive conditions other than PD. Moreover, given that visual impairments may affect the visual experience of product placement, all participants were screened for red-green colour blindness using the Ishihara test. The standardised cut off for normal vision is 15 (Rodriguez-Carmona & Barbur, 2017), therefore, participants who score 14 or less were excluded as this is indicative of the presence of red-green colour blindness. \r\nAll participants had normal or corrected-to-normal vision. The Addenbrooke’s Cognitive Examination-III (ACE) was used to screen for the presence of cognitive impairment (Bruno & Vignaga, 2019). Participants’ data was only included in analysis if participants achieved a score within the normal range (≥ 82 out of 100). Following this exclusion criteria, one PD participant’s data was removed. Research has shown saccadic eye movements to be influenced by cognitive dysfunction (Hutton, 2008; MacAskill et al., 2012), thus cognitive impairments need to be screened for as this study is measuring saccadic eye movements as a measure of IC. Subsequently, following exclusion criteria, 53 participants’ data was included within analysis.  \r\nPD participants were selected who were at a Hoehn and Yahr Stage three or less (see Table 1 for background characteristics for participants attached in the files below). The Hoehn and Yahr is used to give a summary of the laterality and severity of PD symptomology (Readman et al., 2021b). Five participants presented unilateral symptoms only (stage one), seven participants presented bilateral symptoms with no impairment of balance (stage two) and one participant presented bilateral symptoms with some postural instability but were not physically dependent (stage three). PD symptomology was assessed using the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) (Evers et al., 2019). All PD participants were tested under their usual medication regimes and were in a typical functioning ‘ON’ phase. Eight participants were taking a dopamine agonist (e.g., Ropinirole), eight participants were taking a combination drug (e.g., Madopar), six participants were taking a monoamine oxidase inhibitor (e.g., Rasagiline), and two participants were taking a Catechol-O-Methyl Transferase (e.g., Entacapone). \r\nYC were recruited through the researcher’s social network. Whereas both OC and individuals with PD were recruited established research interest databases (OC C4AR database; PD MRR PD interest database (FST2005)).  \r\nMaterials\r\nHealth and Demographic Questionnaire\r\n\tThe health and demographic questionnaire (HADQ) was developed and distributed using Qualtrics (Qualtrics, 2022), an online software that aids the process of building, distributing, and analysing surveys (Carpenter et al., 2019). The HADQ was comprised of four distinct subsections pertaining to both the participants general demographics, and more specific health related measures.\r\n\tDemographic Questions. For participant group allocation, participants were asked for their age, sex, and whether they held a diagnosis of PD. Information about participants’ age also afforded the opportunity for exploration into the possible effect of age as well as PD on product placement susceptibility.  \r\nThe Hospital Anxiety and Depression Scale (HADS). The HADS is a 14 item (7 items pertaining to anxiety and 7 items pertaining to depression) self-report assessment of anxiety and depression suitable for both psychiatric and non-psychiatric populations (Stern, 2014). All items are rated on a 4-point severity scale with a total score of 11 or more being indicative of probable anxiety and depression respectively (Caci et al., 2003; Edelstein et al., 2010). Literature has found HADS to be high in construct validity and very good internal consistency was observed when measuring anxiety (Cronbach’s α = .83) and depression (Cronbach’s α = .82) (Bjelland et al., 2002; Johnston et al., 2000; Mondolo et al., 2006). \r\n\tEdinburgh Handedness Inventory. The Edinburgh Handedness Inventory is a 10-item self-report questionnaire in which participants are asked to indicate a preference for which hand they would use when completing a range of daily activities (e.g., brushing teeth) (Robinson, 2013). Through this a handedness score ranging from 100 (strong right) to -100 (strong left) deduced.  Excellent internal consistency was observed in the 10-item Edinburgh Handedness Inventory (Cronbach’s α = .94) (Fazio et al., 2013). Previous literature suggests that handedness and eye-dominance are correlated because of hemispheric specialisation (McManus,1999; Willems et al., 2010), therefore establishing participants’ handedness was indicative of their dominant eye when measuring IC through saccadic eye movements. \r\nPD Diagnosis questions. Participants with PD were asked to provide specifics relating to their diagnosis, including years since diagnosis, years since presumed onset, and what medication, and its dosage, they are prescribed. These items were necessary to investigate whether PD severity and medication type influence product placement susceptibility.\r\nScreening Assessments\r\n\tCognitive Impairments. The Addenbrooke’s Cognitive Examination-III (ACE) is a cognitive assessment that screens for the probable presence of cognitive impairments (Noone, 2015). The ACE is comprised of 24 items that analyse attention, memory, fluency, language, and visuospatial processing (Bruno & Vignaga, 2019). Very good internal consistency was observed in the ACE (Cronbach’s α = .88) (Kan et al., 2019) and validity (Matias-Guiu et al., 2017; Takenoshita et al., 2019). \r\nVisual Impairments. The Ishihara test is a reliable (Birch, 1997) 17 item assessment for red-green colour blindness that requires participants to read aloud a set of numbers on Ishihara plates that are made up of coloured dots (Marey et al., 2015). \r\nPD Symptomology. MDS-UPDRS is a tool to measure the progression of PD symptomology (Evers et al., 2019). MDS-UPDRS is comprised of a series of tasks that assesses PD symptomology within the last week, in the domains of mentation, behaviour and mood, activities of daily life, motor abilities, and complications of therapy (Holden et al., 2018). Very good internal consistency was observed in the MDS-UPDRS (Cronbach’s α = .90) (Abdolahi et al., 2013) and valid assessment of PD symptomology severity (Goetz et al., 2008; Metman et al., 2004). \r\nMeasures of Inhibitory Control \r\n\tEye Tracking Tasks. The prosaccade and antisaccade tasks were created using Experiment Builder Software Version 1.10.1630 and the data was extracted and analysed using Data Viewer Software. Eye movements were recorded via the EyeLink Desktop 1000 at 500 Hz. Whilst recording eye movements, participants were asked to place their chin on a chin rest to reduce their head movements. Participants sat approximately 55cm away from the computer monitor (monitor run at 60Hz). \r\nFirstly, participants were asked to complete the 4-point calibration task to improve eye tracking accuracy (Pi & Shi, 2019). In this task participants were asked to follow a red target around the screen as it moved up, down, left, and right. Next, participants completed the prosaccade eye tracking task. To centralise participants’ gaze, participants were instructed to look at a white fixation target displayed on a computer screen for 1000ms. Participants were then instructed to look towards a red lateralised target that appeared on screen for 1200ms at a 4o visual angle either to the left or to the right of where the white central dot had been located, as quickly and as accurately as possible (Readman et al., 2021a). The eye tracking equipment measured participants’ saccades and latencies (how long it took for participants to fixate on the red target). A total of 16 gap trials were presented with a blank interval screen displayed for 200ms between the extinguishment of the white fixation target and the initial appearance of the red target, which resulted in a temporal gap in stimuli presentation. The prosaccade task was incorporated to ensure that alternations in participants antisaccade task performance were not due to impaired prosaccades and rather are indicative of alterations in IC. \r\nFor the antisaccade task, participants were first asked to look at a central white fixation dot for 1000ms to centralise their gaze. Participants were then asked to direct their gaze and attention focus to the opposite side of the screen to where a green lateralised target was presented for 2000ms at a 4o visual angle either to the left or to the right of where the white central dot had been located, as quickly and accurately as possible (Derakshan et al., 2009). See figure 1 above for a visual display of an antisaccade task. The eye tracking equipment measured participants’ saccades, latencies (how long it took participants to fixate their gaze to the opposite direction to the green target), and error rates (how many time participants incorrectly looked at the green target). A total of 16 gap trials were presented with a blank interval screen displayed for 200ms between the extinguishment of the white fixation target and the initial appearance of the red target, which resulted in a temporal gap in stimuli presentation. \r\n\tStroop Test. The Stroop test was conducted using PsyToolkit’s free online demonstration (PsyToolkit, 2022). Unlike in the original Stroop test whereby participants had to say the ink colour aloud (Stroop, 1935), using PsyToolkit’s online Stroop test allowed for a more accurate measurement of participant’s reaction time (ms) through pressing the key corresponding to the ink colour (Brenner & Smeets, 2018). Participants completed the Stroop test on a HP ProBook 470 G5 17.3” laptop (HP, 2022), and were sat approximately 30cm away from the laptop. Presenting the Stroop test on this laptop enabled participants to view the test on a large screen, thus improving the accessibility of the test. The colour words presented to participants were ‘red’, ‘green’, ‘yellow’, and ‘blue’.\r\n\tParticipants were instructed to press the key corresponding to the initial letter of the ink colour of the printed word presented on screen as quickly and accurately as possible. For example, the correct answer for RED would be if the participant pressed the key ‘B’ for blue. A total of 40 gap trials were presented. For each trial, a colour word was presented on screen for 2000ms. The colour word was either congruent (the colour word and the meaning are the same, e.g., GREEN) or incongruent (the colour word and the meaning is different, e.g., GREEN). There was a 100ms gap in presentation of the word in which a white cross was presented on a black interval screen. Participants’ congruent and incongruent reaction times (ms), correct Stroop score (correctly identified ink colour out of 40), and Stroop effect (incongruent reaction time (ms) minus congruent reaction time (ms)) were recorded.\r\nThe ease at which the Stroop test can be conducted in a non-laboratory environment and the simplicity at which the colour words can be translated into other languages, increases its accessibility and universality as a measure of IC (Gass et al., 2013). This assessment would, however, be an invalid measure of IC for individuals affected by colour blindness or dyslexia, limiting the populations the Stroop task can assess (Scarpina & Tagini, 2017). \r\nProduct Placement Film Clips\r\nThe incorporation of film clips containing product placement was guided by the prominent use of film clips within previous research that had investigated product placement susceptibility (Kamleitner & Jyote, 2013; Yang & Roskos-Ewoldsen, 2007). Jurassic World featuring Coca Cola and Avengers Endgame featuring Audi were chosen as they were popular films that contained product placement that both younger and older adults would recognise (Malaj, 2022), minimising the effects of familiarity. Furthermore, these two film clips were chosen as they contained product placement of products of different monetary value products. Thus, controlling for the potential effects of monetary value on product placement susceptibility (McDermott et al., 2006). \r\n\tBoth film clips were downloaded from Youtube and trimmed to last approximately one minute each to lessen the study length because of the propensity for individuals with PD to tire because of the symptomology they present with (see Appendix A for the screen shots of the two film clips). The two film clips were shown on a HP ProBook 470 G5 17.3” laptop because the large screen enhanced participants’ visual experience of product placement (HP, 2022).\r\nMeasure of Purchase Intention\r\n\tSeparate pre and post product questionnaires for each clip were made using Qualtrics (Qualtrics, 2022). To measure purchase behaviour, participants were asked how strong their preference was to buy those drink/car brands on a Likert scale of one to seven (from one = “Extremely unlikely” to seven = “Extremely likely”). Literature has found 7-point Likert scales to be a more reliable scale because it allows for more accurate and differentiated responses than smaller scales like 5-point Likert scales (Cicchetti et al., 1985; Finstad, 2010). The use of a 7-point Likert scale therefore gained a more sensitive and accurate measurement of product placement susceptibility. Both the pre and post product placement questionnaires asked participants the same questions therefore enabling us to measure if there was a change in participants’ responses prior to and after exposure to product placement (Matthes et al., 2007).\r\nDesign\r\n\tThe study used a 3 between (Participant Status: Healthy Young Controls vs. Healthy Older Controls vs. Individuals with Parkinson’s Disease) x 2 within (Product Placement Category: Drink vs. Car) mixed-subjects design.\r\nProcedure\r\nAs this study recruited a vulnerable population, the information sheet was sent to participants via email 48 hours prior to the in-person study. This afforded participants the time to ask questions or express any concerns about the study before then being sent the consent form 24 hours prior to commencing the in-person study. Once participants had read and completed the digital consent form, participants were sent the digital HADQ. The HADQ took participants approximately 10 minutes.  \r\n\tPrior to the main study, participants were screened for cognitive impairment, using the ACE, and visual impairment, using the Ishihara test. At this time the severity of Parkinson’s symptomology was assessed using the MDS-UPDRS where appropriate.\r\n\tOn completion of all pre-study screening, participants were asked to firstly complete a prosaccade eye tracking task and then an antisaccade eye tracking task which took approximately 10 minutes. \r\n\tParticipants were then asked to complete a pre product placement questionnaire and then watch a short film clip. After watching the film clip, participants were asked to complete a post product placement questionnaire. Finally, participants were asked to complete the Stroop test which took approximately five minutes to provide a further measure of IC and to act as a buffer in time. \r\n\tThis process was repeated for a second product category condition. The order of condition completion was randomly counterbalanced across participants to increase internal validity by minimising the potential for order effects (Corriero, 2017). The in-person study lasted approximately an hour for healthy controls and an hour and 30 minutes for PD. At the end of the study, participants were read and given a copy of the debrief sheet, thanked for their participation and time, and given £10 as a contribution towards travel expenses. All raw data was stored on the Lancaster University OneDrive, on a password-protected computer.\r\nData Analysis\r\n\tThe raw data from the prosaccade and antisaccade tasks were extracted using the EyeLink DataViewer Software (Version 3.2) and processed using the bespoke software SaccadeMachine (Mardanbegi et al., 2019). Noise in the dataset was removed by filtering out frames with a velocity signal greater than 1,500 deg/s or with an acceleration signal greater than 100,000 deg2/s. The EyeLink Parser was used to detect fixations and saccadic events. Saccades were extracted alongside multiple temporal and spatial variables. Trials were excluded in cases when the participant did not direct their gaze to the central fixation target. The onset of target display was a temporal window of 80-700ms, thus anticipatory saccades made prior to 80ms and excessively delayed saccades made after 700ms were removed.\r\n\tTo improve data analysis reproducibility, statistical analyses were conducted using RStudio (version 2022.09.0) (Quick, 2010). To prepare the Stroop test data for analysis, participants’ Stroop scores (correctly identified ink colour out of 40), congruent and incongruent trial reaction times (ms), and Stroop effect (incongruent trials reaction time (ms) minus the congruent trials reaction time (ms)) were downloaded from Psytoolkit into an Excel file. IC was operationalised as the Stroop effect (Kane & Engle, 2003). \r\n\tTo investigate the susceptibility to product placement, a difference in purchasing behaviour score was calculated for each product. To do so, the pre product placement ratings of the likelihood of purchasing each brand were subtracted from the post product placement ratings of the likelihood of purchasing each brand. A positive difference was indicative of participants being more likely to buy the featured product after exposure to product placement, a negative difference suggested that participants were less likely to buy the featured product, and a difference of zero indicated no change in purchase behaviour. \r\n\tFirst to confirm the assumption that is impaired in individuals with PD compared to healthy controls, three separate between-factor ANOVAs were performed to compare the main effect of group (YC, OC, and PD) on antisaccade latency, antisaccade error rate, and Stroop effect (See Appendix B for R code). A between-factor ANOVA was chosen because it compares three or more categorical groups to establish whether there is a significant difference on a dependent measure (Henson, 2015). As ANOVA results only identify a difference between groups, post hoc Tukey HSD tests for multiple comparisons were conducted to determine where the differences lie between groups (Abdi & Williams, 2010). \r\n\tTo investigate whether IC influences product placement susceptibility, a linear mixed effects modelling (LMM) was fitted. The LMM fitted incorporated difference in purchase behaviour scores (differencescore) as the outcome, and group (PD v Healthy older control v Healthy younger control) and measures of IC (antisaccade latency, antisaccade error rate, and Stroop) as the fixed effects. Given that IC is part of an individual’s executive function (Crawford et al., 2002), ACE score (as a measurement of the participants overall cognitive function; Noone, 2015) was also fitted as a fixed effect. As LMM allows for the analysis of fixed effects of independent variables, whilst also considering unexplained differences corresponding to random effects like participant variation (Baayen et al., 2008).  Random effects of both participants and product (Car or Drink) on intercepts were added (See Appendix C for R code). The LMM was fitted using the Satterthwaite adjustment method in lme4 package (Bates et al., 2014) in R (version 2022.09.0) (Quick, 2010). \r\nEthics\r\n\tThis study received ethical approval from the Psychology Department Research at Lancaster University on the 22/06/2022 and complied to The British Psychological Society’s guidelines (2014).\r\n\r\n\r\n\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"3068"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3069"},["text","Data/R.csv"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"3070"},["text","Ball2022"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3071"},["text","Elena Ball"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"3072"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"3073"},["text","N/A"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3074"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3075"},["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":"3076"},["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":"3077"},["text","Dr Megan Readman"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"3078"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"3079"},["text","Psychology of Advertising"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"3080"},["text","53 Participants. 20 healthy younger controls, 20 healthy older controls, 13 individuals with mild-moderate Parkinson's disease"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"3081"},["text","ANOVA\r\nLinear Mixed Effects Modelling"]]]]]]]],["item",{"itemId":"192","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"212"},["src","https://johnntowse.com/LUSTRE/files/original/7d6c9cf5fdd98d716c94e889c243c0c0.pdf"],["authentication","fa4b33e4b92ee93a65616bbab7185e5c"]],["file",{"fileId":"213"},["src","https://johnntowse.com/LUSTRE/files/original/f11ffa6a464eee8a38144f043e6d8a06.pdf"],["authentication","9e37ad79ac89170b5ec0237b8d9230f6"]],["file",{"fileId":"214"},["src","https://johnntowse.com/LUSTRE/files/original/8093b4f91fa9d0452695e80ef3ecf6eb.pdf"],["authentication","671adccd1d64ac672834905ab18a0ce2"]]],["collection",{"collectionId":"3"},["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":"181"},["text","EEG"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"182"},["text","Electroencephalography (EEG) is a method for monitoring electrical activity in the brain. It uses electrodes placed on or below the scalp to record activity with coarse spatial but high temporal resolution"]]]]]]]],["itemType",{"itemTypeId":"14"},["name","Dataset"],["description","Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing."]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3832"},["text","N1 Adaptation: Exploring the Neuronal Basis of the Interaction Between Auditory Sensory Memory and Attention"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"3833"},["text","Gengjie Jack Ho"]]]],["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":"3834"},["text","2023"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3835"},["text","The aim was to explore whether voluntarily focusing on repetitive auditory stimuli influences the lifetime of N1 adaptation, which indexes the lifetime of auditory sensory memory. Twenty-six neurotypical participants with self-reported normal hearing were recruited from Lancaster University. Electroencephalogram (EEG) recording took place in a sound-attenuated laboratory. A two-by-two factorial design was employed, where one factor manipulated the presence or absence of attention, whereas the other factor manipulated the stimulus-onset interval (SOI), which primarily served to calculate the lifetime of adaptation. Three different amplitude measurement methods were used to calculate the N1 amplitude, therefore three sets of statistical analyses were performed for each investigation. For the preliminary investigation, two-way ANOVAs were conducted to evaluate the impact of attentional focus (presence or absence) and SOI (short or long) on the amplitude of N1. For the primary investigation, paired-samples t-tests were conducted to evaluate whether the presence or absence of attention influences the N1 adaptation lifetime. The preliminary results indicated no significant difference in N1 amplitude between the presence and absence of attentional focus. There was also no significant difference in the SOI, except for one of the amplitude measurement methods, which showed greater N1 amplitudes in the Long SOI condition. The primary results indicated that whether attention was present or not showed no significant effect on the adaptation lifetime across all three amplitude measurement methods. However, the study suffered from low statistical power and possible issues with the methodological design due to the combined use of visual and auditory modalities to manipulate attentional focus. Therefore, it is inappropriate to draw conclusions from the findings of this study. Methodological improvements and theoretical implications were discussed."]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3836"},["text","neuropsychology, attention, auditory sensory memory, N1 adaptation, sensory processing, neural responses"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"3837"},["text","Methods Section:\r\nParticipants\r\nTwenty-six neurotypical participants with self-reported normal hearing (9 males, 16 females, 1 prefer not to say), all of whom were students from Lancaster University, were recruited using opportunity sampling via advertising on social media platforms and SONA. The age range of the participants spanned from 18 to 34 years (M = 22.85, SD = 2.55). Sixteen participants were excluded due to excessive electric noise, resulting in a remaining pool of 10 participants. All participants provided written consent and volunteered to participate in the experiment. The study received ethical approval from Lancaster University’s Department of Psychology.\r\nStimuli\r\nThe experiment employed the oddball paradigm to elicit auditory responses. The standards were presented at a constant rate of 210 repetitions per condition, while the deviants appeared unpredictably at a 5% probability (10 deviants per condition). The sequence of standards and deviants remained consistent across all conditions. The standards were presented as a 500-Hz pure tone, while the deviants were a 503-Hz pure tone. The duration of each tone was 100 milliseconds, with 10 milliseconds of linear onset and offset ramps. All tones were presented at a consistent and comfortable volume level (28% volume on Windows 10). The auditory stimuli were programmed and delivered using MATLAB.\r\nDesign\r\nThe study followed a two-by-two factorial design (see Figure 1). It included two attention conditions: Active and Passive. In the Active condition, participants were presented with a stream of standards and deviants while focusing on a fixation cross. Their objective was to count the occurrences of deviants. In the Passive condition, participants viewed a nature documentary displayed on a smartphone screen. Their objective was to count the number of animal species featured in the documentary while ignoring the stream of auditory stimuli playing simultaneously in the background. Both the fixation cross and the smartphone screen were positioned one metre in front of the participants. Additionally, there were two SOI conditions: Short SOI (1.7 seconds) and Long SOI (3.4 seconds). The oddball paradigm was integrated into a stimulus block design - with two types of stimulus blocks, each having a specific SOI. Note that the order of the conditions was randomized among participants.\r\nThe purpose of the design was to manipulate attention towards repetitive auditory stimuli and calculate adaptation lifetime. The counting tasks in the Active and Passive conditions manipulated attentional focus. In the Active condition, the count-the-deviants task aimed to maintain participants’ attention on the repetitive auditory stimuli. In the Passive condition, the count-the-animal-species task aimed to divert participants’ attention away from the repetitive auditory stimuli using visual stimuli in the form of a nature documentary. Additionally, the counting tasks served as a quality control measure, excluding participants whose answer substantially differed from the correct answer. Conversely, the inclusion of both short and long SOI measured adaptation lifetime using the amplitude ratio (explained below in Data Analysis).\r\n Figure 1. A visual representation of the study’s two-by-two factorial design, encompassing four distinct conditions: Active with Short SOI (1.7s), Passive with Short SOI (1.7s), Active with Long SOI (3.4s), and Passive with Long SOI (3.4s).\r\nProcedure\r\nEEG was used as the method of data collection. The Enobio NIC2 suite recorded EEG data, using three dry electrodes (Fpz, Cz, and Fz) to capture neuroelectrical activity in the auditory cortex (Neuroelectrics, n.d.). Data recording was conducted in a sound-attenuated laboratory. The entire experiment lasted approximately 60 minutes, which included a 20-minute preparation period.\r\nBefore the experiment, participants were sent an information sheet online and completed a consent form upon arrival. They were then fitted with an electrode cap and headphones, and instructed to avoid excessive movement during recording to minimise muscle artifacts. When recording was ongoing, participants were verbally given instructions at the start of each condition, and they were asked about their answers to the counting tasks after each condition. Short breaks were allowed when transitioning between conditions. After the experiment, participants were inquired about their age and gender, and received a verbal and written debrief regarding the true purpose of the study.\r\nData Analysis\r\nWe conducted a priori power analyses using G*Power 3.1. to determine the required sample size for testing the two hypotheses (Faul et al., 2007). For the preliminary investigation, results indicated that the required sample size to achieve 80% power for detecting a medium effect, at a significance criterion of α = .05 was N = 36 for a two-way ANOVA. For the primary investigation, results indicated that the required sample size to achieve 80% power for detecting a medium effect, at a significance criterion of α = .05 was N = 34 for a paired-sample t-test. Our recruitment target of 36 participants was based on the larger of the two required sample sizes.\r\nIn data preprocessing, we discarded the first few trials from each condition to minimise initial variability in orienting and habituation effects, and excluded any unidentifiable N1 responses.\r\nMeasuring the N1 amplitude is essential for estimating adaptation lifetime and conducting the planned data analysis. There are three methods available - N1, N1-P2, and mean voltage displacement. Notably, baseline correction was performed as a standard initial procedure, addressing a baseline that extended over 100 milliseconds within this experiment. The first method identifies and measures the N1 amplitude as the point of maximum negativity (Marton et al., 2018). The second method measures the peak-to-peak amplitude difference between N1 and P2, as it captures the relationship between the two and avoids the problem of a noisy baseline by not depending on the pre-stimulus baseline (Al-Abduljawad et al., 2008; Scaife et al., 2006). The third method estimates the mean voltage displacement (absolute amplitude value) over a specific time frame, particularly useful when the N1 component is difficult to identify, or the stimulus onset is ambiguous (Hoehne et al., 2020; Komssi et al., 2004). All three methods were employed to conduct a more comprehensive data analysis, given that consistent findings across different methods increase the reliability of results and inconsistencies can guide further investigation.\r\nIn the traditional approach for estimating adaptation lifetime, one uses multiple stimulus blocks, each featuring varying SOIs ranging from 0.5 to 10 seconds. The ERP is derived separately for each stimulus block, and notably, the peak N1 amplitude is plotted as a monotonically increasing function of SOI. This relationship between the N1 amplitude and the SOI can be described as an exponentially saturating function, represented by the model equation A(1-e-(t-to)/τ), where A (amplitude), τ (time constant), and to (time origin) represent fitting parameters (Lü et al., 1992). Graphically, one fits the exponentially saturating curve to the measured N1 amplitudes. Here, the fitting parameter τ characterizes the steepness of the curve in seconds. τ signifies the SOI at which the amplitude curve reaches 66% of its way towards the saturation limit, indicating the lifetime of adaptation. However, this method is time-consuming and difficult for participants, insofar as boredom-induced mind wandering may confound the effects of attentional focus (Eastwood et al., 2012; Meier et al., 2023).\r\nAn alternative approach of amplitude ratio only used two stimulus blocks with contrasting SOIs. By graphically plotting the amplitude ratio of a short SOI against a long SOI over a range of τ values (measured in seconds), it shows that the ratio is a monotonically increasing function of τ. Although this ratio-to-τ relationship is not strictly linear, it can be used to estimate the adaptation lifetime rather than the conventional time constant, given that the ratio increases as τ increases. In practical terms, both SOI conditions produced a clear difference in amplitude. The short SOI of 1.7 seconds ensures a distinct ERP with an observable N1 component (if the SOI is less than 300 milliseconds, it would render the N1 response too minute and difficult to observe), while the long SOI of 3.4 seconds brings the N1 amplitude closer to its saturation limit. By shortening the experiment duration, this ‘dimensionless’ measure addressed the limitations of the traditional approach without significantly compromising estimation accuracy.\r\nTwo-way ANOVAs were conducted to assess how the N1 amplitude is influenced by attentional focus (presence or absence) on repetitive auditory stimuli and SOIs (short or long).\r\nPaired samples t-tests were conducted to assess if the presence or absence of attentional focus on repetitive auditory stimuli significantly affects adaptation lifetime (calculated via amplitude ratio).\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"3838"},["text","Lancaster University "]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3839"},["text","Data/SPSS.sav"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"3840"},["text","Ho2023"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"3841"},["text","Sharon Boyd"]]]],["element",{"elementId":"47"},["name","Rights"],["description","Information about rights held in and over the resource"],["elementTextContainer",["elementText",{"elementTextId":"3842"},["text","Open"]]]],["element",{"elementId":"46"},["name","Relation"],["description","A related resource"],["elementTextContainer",["elementText",{"elementTextId":"3843"},["text","None"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3844"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"3845"},["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":"3846"},["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":"3847"},["text","Patrick May"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"3848"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"3849"},["text","Neuropsychology"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"3850"},["text","Participants: 26\r\nExcluded Participants: 16\r\nFinal Sample: 10 Participants"]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"3851"},["text","ANOVA, t-test"]]]]]]]],["item",{"itemId":"47","public":"1","featured":"0"},["collection",{"collectionId":"5"},["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"185"},["text","Questionnaire-based study"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"186"},["text","An analysis of self-report data from the administration of questionnaires(s)"]]]]]]]],["elementSetContainer",["elementSet",{"elementSetId":"1"},["name","Dublin Core"],["description","The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/."],["elementContainer",["element",{"elementId":"50"},["name","Title"],["description","A name given to the resource"],["elementTextContainer",["elementText",{"elementTextId":"1340"},["text","National Identity of chinese overseas student"]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"1341"},["text","Yisu Hu"]]]],["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":"1342"},["text","2013"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1343"},["text","Since 21st century, with the development of global and China’s economy, an increasing number of Chinese students preferred study abroad. Chinese oversea students are very special group. They were influenced by the traditional Chinese culture and education. They also accept Western education and thought. This research aims to investigate whether the study-abroad experience will affect Chinese oversea students’ national identity. 35 Chinese students who are studying in UK and 35 Chinese students who are studying in China completed the questionnaire which assessed national identity. All questionnaires sent to the participants by email. According to the results of this study, Chinese students who are studying in UK did not show significant differences in national identity by compared with the Chinese students who are studying in China. Results of current study also indicated that Chinese students’ ethnocentrism scores were marginally higher than Chinese oversea students."]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"1344"},["text","The national identity was assessed using the National Identity Scale. The National Identity Scale has five factors: membership, private, public, Identity and comparison. On a 7-point Liker Scale, participants reported their agreement (1 = strongly disagree, 7 = strongly agree) with items. \r\n\r\nEthnocentrism was measured with the Revised Ethnocentrism Scale, on a 5-point Liker scale, participants indicated their agreement (1 = strongly disagree, 5 = strongly agree) with statements.\r\n"]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"1345"},["text","Lancaster University"]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"1346"},["text","Xu2013"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"1347"},["text","Eleni Sevastopoulou"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1348"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1349"},["text","Data"]]]]]],["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":"1350"},["text","Tamara Rakic"]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"1351"},["text","MSc"]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"1352"},["text","Two groups of participants took part in this research. One group is the students who studying in the United Kingdom, they are from the Mainland of China, were studying in a one year taught Master’s course and had no previous experience of learning in any western countries. 50 Chinese oversea students who are studying in UK were invited to take part in this research, and 40 of these students done the questionnaire, 5 of the 40 questionnaires are uncompleted. Finally, a total of 35 questionnaires were valid. Another group is the Chinese students who studying in China, they are also from the Mainland of China, were studying in taught Master’s course, and they had no experience of learning in any other countries. 42 Chinese students who are studying in China were invited to take part in this research, all of them done the questionnaire, but 7 of the questionnaires were uncompleted, at last, 35 valid questionnaires were used in this research."]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"1353"},["text","independent-samples t-tests "]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"1387"},["text","Social Psychology"]]]]]]]],["item",{"itemId":"68","public":"1","featured":"0"},["fileContainer",["file",{"fileId":"21"},["src","https://johnntowse.com/LUSTRE/files/original/6e55fa69336c955afd8161d2c2f4951f.doc"],["authentication","4f750621696649cd87b16387c2a59e72"]]],["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":"1620"},["text","Neural response to infant-directed speech: gamma band oscillatory activity in 4-month-old infants "]]]],["element",{"elementId":"39"},["name","Creator"],["description","An entity primarily responsible for making the resource"],["elementTextContainer",["elementText",{"elementTextId":"1621"},["text","Marina Ciampolini"]]]],["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":"1622"},["text","2019"]]]],["element",{"elementId":"41"},["name","Description"],["description","An account of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1623"},["text","Infant-directed speech is an ostensive signal preferred by infants over adult-directed speech. We studied infants’ neural response to auditory stimuli by measuring gamma band oscillatory activity over the frontal area of the brain in response to ostensive infant-directed speech and non-ostensive adult-directed speech. Two groups of 4-month-old infants were presented with the same auditory stimuli, but the two groups differed in terms of visual stimuli (inverted vs. upright faces), being our study a part of a broader research project. We investigated only the auditory portion of the trial. We found that, in the inverted face group, the activation to the ostensive infant-directed speech was significantly enhanced while, in the upright group, this outcome was not found. These findings support the use of gamma band oscillations in assessing the basis of social communication and establish infants’ early specialization in understanding communicative signals directed to them. "]]]],["element",{"elementId":"49"},["name","Subject"],["description","The topic of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1624"},["text","Infant-directed speech; neural response; EEG; gamma oscillation"]]]],["element",{"elementId":"48"},["name","Source"],["description","A related resource from which the described resource is derived"],["elementTextContainer",["elementText",{"elementTextId":"1625"},["text","Experimental Design \r\nWe used data that had already been collected for a broader study, designed for the observation of the influence of auditory stimuli on face processing. In the main experiment, a total of 36 four-months-old infants was divided into two groups that differed on the visual stimulus presented at the end of each trial. Immediately after an auditory stimulus in IDS or ADS, the first group was presented with inverted faces, while the second group was exposed to upright faces. Participants in both groups were thus exposed to the same auditory stimuli, just before being presented to the visual stimuli, that were different depending on the group. In this research we focused only on the auditory portion of the trial, where participants were exposed to IDS or ADS (Fig. 1).  \r\n \r\n \r\nFigure 1. Representation of the complete trial presented to infants. In every trial, 18 infants were presented with upright faces, while the other 18 were presented with inverted faces. However, each infant was exposed to auditory stimuli in ADS or IDS, regardless of the visual stimulus. The green rectangle shows the portion of the trial analysed in this dissertation. \r\nParticipants \r\nInfants were recruited from the Lancaster Babylab database. All were free of any known neurological, ocular or auditory abnormality and met the screening criteria of normal birth, born full term (gestational age >37 weeks), in the normal weight range (>2500g) and with an Apgar score of at least 8 at five minutes after the birth.  \r\nIn our study we focused on infants’ neural response to the auditory stimuli (Fig. 1). However, the distinction between the two groups was preserved in order to observe possible differences between them. The group exposed to inverted faces included 18 infants (5 females, age range 117 to 161 days, M= 135.61 days). Thirteen additional infants were excluded owing to an insufficient number of artifact free segments (n=10), sleep (n=1), and technical issues during the experiment (n=2). The group presented with upright faces included 18 infants (5 females, age range 115 to 171 days, M= 145.22 days). 17 additional infants were excluded because of an insufficient number of artifact free segments (n=14) and technical issues during the experiment (n=3). In the final datasets (N=36) were included infants that provided artifact-free EEG recording in at least 10 trials within each experimental condition.   \r\nStimuli \r\nThe auditory stimulus was the word “Hello” pronounced by a female voice using two different intonations: either IDS or ADS. The two words were recorded and edited with Audacity (v. 1.2.5) and Praat (v. 5.1) by setting a digitalization at 32-bit resolution and a sampling rate at 48 kHz. Both words were 850 ms long. The IDS stimulus had an average volume intensity of 61.86 dB, while the ADS stimulus had an average volume intensity of 61.50 dB.  \r\nApparatus \r\nInfants’ behaviour was video recorded for the entire duration of the test by a remote-control video camera placed behind the monitor. A pair of computer speakers situated behind the monitor were used for the presentation of the auditory stimuli. The infants’ EEG was recorded at a sampling rate of 500 Hz using a 124-channel Hydrocel Geodesic Sensor Nets (Electrical Geodesic Inc., Eugene, OR, USA). \r\nProcedure \r\nInfants sat on their parent’s lap at a distance of 70 cm from a computer monitor. Each trial started with a dynamic fixation grabber at the centre of the monitor, for the duration of 2150 ms. Then the attention grabber stopped moving and the auditory stimulus (in IDS or ADS) was released by loudspeakers positioned behind the monitor and lasting 850 ms. The attention grabber remained still for an interval randomly varying between 200 and 400 ms. Then the grabber disappeared and the visual stimulus was presented for 1000 ms. A blank screen as an inter-trial interval between 1000 and 1200 ms was inserted between successive trials. Auditory stimulus in IDS or ADS were presented in a random order with the following constraint: no more than three successive trials of the same kind in a row. The trials were presented as long as the infants were willing to look at them. When they became fussy, the experimenters played a dynamic spiral together with an attractive sound. The session ended when the infant could no longer be attracted to the screen.  \r\nEEG measurement and data analysis \r\nThe electrical potential was band-pass filtered between 0.3-100 Hz. The filtered EEG was then segmented into epochs including 600 ms before stimulus onset and 1400 ms following the stimulus onset for each trial. EEG epochs containing artifacts caused by body and eye movement were automatically eliminated, whenever the average amplitude of a 80 ms gliding window exceeded 55 µV at horizontal Electrooculogram (EOG) channels or 150 µV at any other channel. In addition to automatic rejection, each individual epoch was visually inspected for further epoch selection. When <10% of the channels contained artifacts, the contaminated channels were replaced by mean of spline interpolation, while segments in which >10% of the channels included artifacts were rejected. Infants exposed to upright faces contributed on average 17.5 artifact free trials to the IDS condition (range: 8 to 36) and 18.34 trials to the ADS condition (range: 9 to 39). Infants exposed to inverted faces contributed on average 20.89 artifact free trials to the IDS condition (range: 8 to 38) and 20.78 trials to the ADS condition (range: 10 to 39).  \r\nIn the artifact free segments induced gamma-band oscillations were uncovered through time-frequency analysis. These segments were imported into Matlab® and re-referenced to average reference through the free toolbox EEGLAB (v. 9.0.5.6b). The custom-made scripts collection WTools (available at request) was used to compute complex Morlet wavelets for the frequencies 10-90 Hz with 1 Hz resolution. A continuous wavelets transformation of single trials of EEG in each channel was performed, on 2000 ms long segments (600 ms pre-stimulus onset and 1400 ms after stimulus onset). The transformed segments were averaged for each condition separately. To remove the distortion in the time-frequency decomposition caused by convolution with the wavelets, 400 ms at each edge of the epochs were chopped, leaving a segment from -200 to 1000 ms around the auditory event. The average amplitude of the 200 ms pre-stimulus window was used as the baseline and was subtracted from the whole segment at each frequency. \r\nBased on prior findings (Parise & Csibra, 2013), we selected the scalp location over the forehead (the average of channels 3, 9, 10, 15, 16, 18, 22, 23, corresponding to Fp2, Fpz, Fp1, respectively, Figure 2), a time window from 200 ms to 600 ms, and 25 to 45 Hz frequency window.  \r\nIn order to verify that there were no significant differences between the accepted segment for each participant, a t-test between the average of accepted segments for each condition (speech) was performed and the same procedure was repeated for each group (face orientation). The mean amplitude was assessed by a repeated measure ANOVA with Speech (IDS x ADS) as a within subject factor, and Group as a between subject factor (upright x inverted). Paired-Sample t-tests were used for post hoc comparisons between the induced gamma-band oscillatory activity in response to IDS and to ADS. One-sample t-tests against 0 were used to assess whether the analysed gamma-band oscillatory activity differed significantly from the baseline.  \r\n \r\nFigure 2. Sensor layout for the Electrical Geodesics Inc. (EGI) 124-channel hydrocel sensor net, showing the locations of the electrodes under study (circled in green), averaged for measurement of the oscillatory activation.  "]]]],["element",{"elementId":"45"},["name","Publisher"],["description","An entity responsible for making the resource available"],["elementTextContainer",["elementText",{"elementTextId":"1626"},["text","Lancaster University"]]]],["element",{"elementId":"42"},["name","Format"],["description","The file format, physical medium, or dimensions of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1627"},["text","Excel files; Matlab files; SPSS files. "]]]],["element",{"elementId":"43"},["name","Identifier"],["description","An unambiguous reference to the resource within a given context"],["elementTextContainer",["elementText",{"elementTextId":"1628"},["text","Ciampolini2019"]]]],["element",{"elementId":"37"},["name","Contributor"],["description","An entity responsible for making contributions to the resource"],["elementTextContainer",["elementText",{"elementTextId":"1629"},["text","John Towse"]]]],["element",{"elementId":"44"},["name","Language"],["description","A language of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1630"},["text","English"]]]],["element",{"elementId":"51"},["name","Type"],["description","The nature or genre of the resource"],["elementTextContainer",["elementText",{"elementTextId":"1631"},["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":"1632"},["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":"1633"},["text","Eugenio Parise "]]]],["element",{"elementId":"53"},["name","Project Level"],["description","Project levels should be entered as UG or MSC"],["elementTextContainer",["elementText",{"elementTextId":"1634"},["text","MSc"]]]],["element",{"elementId":"54"},["name","Topic"],["description","Should contain the sub-category of Psychology the project falls under"],["elementTextContainer",["elementText",{"elementTextId":"1635"},["text","Cognitive; developmental "]]]],["element",{"elementId":"56"},["name","Sample Size"],["description"],["elementTextContainer",["elementText",{"elementTextId":"1636"},["text","36 infants "]]]],["element",{"elementId":"55"},["name","Statistical Analysis Type"],["description","The type of statistical analysis used in the project"],["elementTextContainer",["elementText",{"elementTextId":"1637"},["text","Anova; t-tests "]]]]]]]]]