Training Transfer Between False-belief, Card Sorting and Counterfactual Reasoning in Children with ASD.
ASD, Training study Domain general Theory of Mind Counterfactual reasoning Executive Functions
Previous training studies for typically developed (TD) children and children with Autism Spectrum Disorder (ASD) show that theory of mind and executive functions are two interrelated domains, and that training in one task could lead to improvement on the other. This training study aimed to examine the developmental relationship between three domains (Theory of Mind (ToM), Executive Functions (EF) and Counterfactual Reasoning (CR)) in children with ASD. A group of 30 children diagnosed with ASD were randomly allocated to one of three training groups, each group received training in one of the three domains stated. After training, the entire sample was tested to measure for improvements. Results indicate that ToM training leads to improvement on the EF and CR tasks, while EF training did not lead to ToM improvement and CR training did not lead to EF improvement. Findings are discussed and a novel cognitive model is proposed to account for the observed outcomes.
Following the design of Kloo and Perner (2003), first children were pretested. The pretest involved measures of verbal and nonverbal ability, two false-belief tasks followed by a card sorting task and two counter-factual reasoning tasks. The pretest was scored to create a baseline for the participants' abilities in each of the areas assigned to the training groups. Children were then randomly assigned to one of three experimental training groups. Each group was given two sessions of training (approximately 1 week apart) on one of the three areas; false belief, counterfactual reasoning or DCCS. A posttest was given a week after the second training session, it was similar to the pretest in design but different materials were used. The posttest was given to the children to measure any improvements in performance after training and examine any crossover effects between the different training groups. Finally, the children were given a follow-up test (approximately 6 weeks after the posttest) to investigate if the effects of training are lasting. All of the sessions took place in a quiet room in the child's school. Procedure and Materials Pretest and posttest. Both sessions that preceded and followed the training sessions involved tasks measuring performance in false belief, counter-factual reasoning and card sorting. False-belief. One of two traditional unexpected transfer tasks was administered on the pretest based on Wimmer and Perner (1983), modeled after Baron-Cohen et al.’s Sally-Anne task (1985). A scene was enacted to the child using wooden toy figures and a kitchen model in which an item is unexpectedly transferred during the protagonist's absence. The stories where altered slightly to be more fitting to the knowledge of a Bahraini child by changing character names and making other alternations where appropriate. However, the main consciences of the stories remained very similar to the original stories. After the story is told, the character returns to the scene and the child is then asked a false-belief test question such as 'where do you think Ahmed will look for his teddy bear now?' followed by two control questions (memory and reality). One of the two stories was administered in the pre-test and the other in the post-test. The false-belief pretest and posttest also included an unexpected content task, another task modeled by Wimmer and Perner (1983) as a measure of false-belief. In this task the child was presented with a closed familiar container (such as a Band-Aid box) and then the child was asked to guess the content of the box. The item in the box was then revealed to the child (a coin, for example). Next the item was placed in the closed box again and the child was asked 'what did you think was in the box before I opened it?' The correct answer should be Band-Aids, but most children with ASD find difficulty in suppressing the reality of what they know to be in the box so the answer they give is ‘a coin’. The child was then asked about another person’s state of mind 'what will (name another child) think is inside the box?’ Finally, the child was asked a memory control question 'what is really in the box?' Card Sorting. Following the false-belief task, the child was presented with a dimensional change card sorting task (DCCS; Frye et al., 1995). One set of cards (5cm x 10cm) was used as well as two target cards (a blue house and an orange car) to be placed on two sorting boxes (12cm x 16cm). The card set had 12 testing cards (6 orange houses and 6 blue cars). The task involved two phases, in the pre-switch phase the participant was asked to sort the cards according to shape. After completing six trails successfully, the examiner explained to the child that now the rules of the game will change and the child was asked to sort the cards according to colour rather than shape in the post-switch phase. Counterfactual Reasoning. Lastly, the pretest and posttest sessions included two counterfactual thinking tasks based on Beck et al. (2011). One of the tasks in each session was enacted using wooden figures and materials such as doll sized bed, cabin, teddy bears or pets. The second task was presented using a picture story consisting of three panels illustrating the events of the story. In these stories, both enacted and illustrated, a series of events lead to a specific end state. For example, the character picks flowers from the garden and places them in a vase on the table. Then the child is asked 'if Zainab had not picked the flowers where would they be’? Two control questions (memory and reality) followed. Similarly to the false-belief task, some alterations where made to the stories where appropriate to accommodate the child's environment and imagination. The use of two different methods of delivery for the counter-factuality task was introduced to create more variation in the understanding of counterfactual reasoning and to distinguish this task from the false-belief task. Training Following the pretest, the participants were assigned to three experimental groups each receiving two training sessions in one of the three areas; false-belief, counterfactual reasoning and DCCS. The aim of the training is to provide the children with explanations and feedback based on performance. False-belief training group. In each of the training sessions, the false belief group received two of four Ernie-says-something-wrong tasks (renamed to Ali-says-something-wrong) (Hale & Tager-Flusberg, 2003), one unexpected transfer task different from the tasks administered during the pre and post-test sessions, and finally one unexpected content task. Ali-says-something-wrong. As in the original Kloo and Perner (2003), the task was presented with the aid of three puppets. In each of the stories Ali carried an action towards one of the puppets but then stated that he did it to another puppet. In each training session the child received two of the four original stories followed by a question about the content of Ali's statement and about the conflicting reality. The other two stories where then administered in the following session. Unexpected transfer. The training sessions also included one story about an item being unexpectedly transferred in the protagonist's absence following Baron-cohen et al. (1985). The stories was enacted using wooden dolls and doll house furniture. This training task aimed to teach children about the main aspects of an unexpected transfer and to gradually guide them towards considering the character's false belief (Kloo and Perner, 2003). Unexpected content. This task is presented using a different box and content for each test and training session. Examples of the materials used are a smarties tube, a pringles box, a crayons card box. The training of this task aimed to help the child understand his own false-belief as well as others’ state of mind. DCCS training group. The card sorting group was given training in two DCCS tasks in each of the training sessions. Both tasks involved sorting according to colour and number, and the switch was always from colour to number. The two tasks administered were the three dimension switch and the transfer sorting task. Three dimension switch. In this card sorting task, the participant was presented with two target cards (one yellow house and two green houses) placed on a sorting box. The test cards were similar to the target cards on one dimension; either colour or number (two yellow houses, one green house). The child had to sort by colour, then number, then by colour again and finally by number one last time. Two sets of cards were used, one for each training session. The experimenter helped the child identify each dimension after each switch was made and the rules of the game were covered again. Each switch involved six trials. Transfer sorting task. Here, the target cards remained the same as the previous task (one yellow house and two green houses) but a new test card that is only similar to the target cards on one dimension (two yellow cars) was introduced. The test cards was supposed to be sorted according to the dimension stated by the experimenter, starting with colour then switching to number. Counterfactual reasoning training group. Counter-factual reasoning tasks and false-belief tasks are interchangeable in some studies by asking questions testing both skills following a single story. However, in this study, the training groups had to receive different stories, followed by questions that only tap on counterfactual thinking in order to distinguish it from false-belief training. The purpose of this divide in training is to ensure that each experimental group receives training that does not overlap with the other groups' as the study aims to ultimately measure the crossover effects. The CR group received two tasks in each training session. Like the pretest and posttest, one of the tasks was enacted using figures and the other was presented as a picture story. The stories are based on Beck et al. (2011) and Guajardo and Turley-Ames (2004). Figure stories. Following Guajardo and Turley-Ames' (2004) counterfactual thinking tasks, the children were shown a story, presented using wooden dolls, in which an event occurs (usually as a consequence of an action taken by the protagonist) and the child was asked to generate alternative scenarios that would have prevented the occurrence of that event. For example, the character is drawing a picture using pencil colours when the colour breaks and a result he cannot finish his drawing. The question following this story is 'what could the character have done so that he would have drawn the rest of the picture?' and the child is to give as many responses as he/she can generate. Other scenarios include avoiding breaking a glass, keeping their clothes clean, taking a nap leading them to miss their favorite show, and someone eating the character's last chocolate bar. In the training sessions, the examiner walks the child through the logic of having different actions leading to alternative endings. Picture stories. The second task in the counter-factual training involved a single picture story based on Beck et al (2011). The images were digitally drawen using Adobe Illustrator and the stories showed a sequence of three square panels. However, the question format following the stories differed from the task given using figures. In the picture stories task, the child is presented with a simple story of consequential events followed by a question about where someone or something would have been if a certain event had not occurred. For example, one of the stories showed a cat napping on top of a car, the cat then spies a bird flying by and chases the bird all the way to the traffic light. The question associated with this story is 'if the cat had not spied the bird, where would the cat be?' Similar illustrations include a man receiving a call to meet a friend, a girl picking flowers, a drawing flying out of an open window and a man who gets sand on his shoes. The training aims to allow the child some insight on how an occurrence could alter the course of events resulting in certain outcomes, and thus if the occurrence had not taken place we would be presented with a counterfactual state. Follow-up test. The follow up test was added to the experiment to measure whether children with ASD maintained any effects gained from the training past the posttest. Therefore, this test was similar to the pretest and posttest in design; it included a false belief task, a card sorting task and two counter-factuality tasks. However, the materials and stories used were all different from those used previously in the tests and training. The follow-up test took place 6 weeks after the post-test session.
Levodopa and antisaccade performance in Parkinson’s disease: the influence of intrinsic dopaminergic functioning, dopamine agonists and chronic anti-parkinsonian medication
Keywords: Parkinson’s disease, dopamine overdose hypothesis, spontaneous eye blink rate, levodopa, dopamine agonists, antisaccade
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.
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. On 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. All 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. An 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 Materials and measures Online questionnaire A questionnaire comprised of a demographics and health screening survey, the Edinburgh handedness inventory (EHI), the HADS, and a PD and associated medication survey was developed and distributed via Qualtrics (Qualtrics, 2013). The questionnaire required 15 minutes to complete. Demographics 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. The 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). The 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. PD 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. ACE-III (Hsieh et al., 2013) The 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. Ishihara colour deficiency test (Ishihara, 1917) The 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. MDS-UPDRS (Goetz et al., 2008) Both 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. SEBR SEBR 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). Eye tracking tasks Apparatus A 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. Prosaccade task Participants 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. Antisaccade task Participants 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. Procedure The present study was reviewed and approved by Lancaster University’s ethics committee. All participants provided informed consent prior to participating. Participants 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. All 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. Once 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. Data processing Raw 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).
Four-Dimensional Ultrasound Analysis of Fetal Independent Oculomotor Control
Four-dimensional Ultrasound Imaging Fetal Visual Development Third Trimester Light Stimuli Independent Oculomotor Control
This dissertation seeks to enhance the present understanding of elicited fetal independent ocular-motor control during late gestation. Independent ocular-motor control refers to the ability to more the eyes independently from the head when fixating on a visual stimulus. Whilst there is a wealth of information regarding fetal visual development and responsiveness to light stimulation, there is a paucity of research investigating elicited fetal visuo-motor abilities. Therefore, the current research aims to utilsise four-dimensional ultrasound imaging to view fetal responsiveness when exposed to a custom-made light source. To assess fetal independent ocular movement, light was presented through the maternal abdomen (N=54) towards the peripheral of the fetal head to elicit directed purposeful eye and head movements. Ultrasound scans were recorded and later coded for frequency of eye and head movements at each stage of light exposure (before, during and after light). The primary experimental hypothesis suggested that the fetus would exhibit independent ocular-motor control when exposed to a light stimulus and that, the fetus would produce behavioural responses more often during light stimulation, than in the absence of light stimulation. Analysis of results indicated that the fetus was able to make independent, directed ocular movements towards stimuli during late gestation. Eye movements were more frequent during and after light exposure, in comparison to before light exposure. Head movements were more common during light exposure; however, head movements were more commonly performed by the fetuses than eye movements overall. The results suggest that the fetal visual system maybe more advanced than previously thought and may provide clinical implications, as independent ocular movement may be utilised as a neurological diagnostic tool
Experimental Design The study employed a repeated-measures, within-subjects design, in which one sample of participants were exposed to a light stimulus and assessed for behavioural responses before, during and after light exposure. The independent variable manipulated light stimuli presentation time (before stimulation, during stimulation and after stimulation). The dependent variable measured the frequency of behavioural responses (head movements and eye movements) elicited at each stage of light exposure. The participants were counterbalanced in regards to the presentation of two forms of light exposure (constant beam and intermittent beam, described below) to avoid the introduction of confounding variables and reduce the possibility of order effects. Three extraneous variables were identified however; this included maternal abdominal thickness, fetal positioning and external room illumination. Maternal abdominal thickness was controlled for by first assessing maternal thickness before the experimental procedure and then altering the light strength dependant on this factor. Therefore, if the thickness was greater, a stronger light strength would be used to ensure light reached the fetal retina in accordance to Del Giudice’s (2011) model of light penetration. There were three different light strengths employed within this study, as will be discussed below. Furthermore, fetal positioning was considered an extraneous variable as the location of light exposure on the maternal abdomen was dependant on the fetus’s position within the womb. To ensure light was presented to the same location for each participant, an initial examination was conducted to determine the orientation of the fetus. Then, the light source was positioned towards the peripheral of the fetus head. Conducting this initial examination increased research validity as each fetus experienced the light similarly and was able to perform horizontal eye and head movements. Lastly, external room illumination was an important factor to consider, as if the room was not dark, it was possible the light stimulus would not have had an experimental effect. Room illumination was controlled for by conducting the experimental procedure only in complete darkness to ensure no other light could reach the fetus and influence fetal responsiveness. Materials Light Stimulus. The light stimuli employed within the current study was a customised, ethically approved light source which emitted light at 650nm. The light stimulus was specially constructed to ensure extraneous variables, such as light strength and maternal thickness, could be controlled for. The stimulus was assembled using a custom-made semiconductor laser torch. The torch was created with a triangular shape at the end, which included three dots, each distanced 15mm apart. Three dots were used to provide a smaller light guide, as this has been described to provide better fetal response rate (Dunn et al, 2015). Utilising Del Giudice’s (2010) model of light penetration, the light source was adjustable to ensure 0.1-1% of light reached the fetus and was within the range of the fetal visual system. In addition, red spectrum lumen levels were used, as this wavelength penetrates tissue most successfully when compared to other colour spectrums (Dunn et al., 2015). An advantage of employing red spectrum wavelengths means lower levels of light can be presented, without reducing the amount of light reaching the fetal retina. An important component of the light stimulus was the ability to alter light strength depending on maternal abdominal thickness. More specifically, the light was calibrated at output optical powers of 0.5mW, 1mW or 5mW for thickness (t) below 1.5cm, between 1.5cm and 3cm and above 3cm. To control for variations in light stimulation in regards to maternal thickness, and to ensure a constant level of light was experienced by every fetus, dependent optical powers were delivered. Ultrasound Machinery. Observations of eye and head movements were recorded during experimental ultrasound scans, located at either Cumbria University Medical Imaging Unit or Blackpool Victoria Hospital. At Cumbria University Medical Imaging Unit, a GE Healthcare Voluson iBT07 4D live ultrasound scanner and 4D probe, model RAB4-8-RS was used. Also, at Blackpool Victoria Hospital using a GE Healthcare Voluson E8 Expert BT13 advanced 4D HD live ultrasound scanner and 4D probe, model RM66. The ultrasound recordings were streamed onto a laptop during the scans and then saved on to an external hard drive, which contained no previous data. The external hard drive was used for coding of eye and head movements offline, at a private location on Lancaster University campus. Procedure On arrival at one of the two medical clinics, either located at Blackpool Victoria Hospital or Cumbria University Medical Imaging Unit, the participant was greeted by a researcher and taken into a room containing an ultrasound imaging machine. The participant was introduced to the sonographer and then asked to remove all items of clothing covering the abdomen and to lie down on a medical bed. When the participant voiced their comfort, the sonographer proceeded in applying a lubricating jelly to the area of examination on the abdomen. The lubricating jelly was used to ensure smooth movement of the probe against the skin during the ultrasound scan. The sonographer then placed the probe onto the abdomen and began the first 2D ultrasound scan to assess the maternal tissue thickness (in millimetres) and to determine the fetal head position. These assessments were undertaken to inform the experimenter of where the light stimulus should be presented and the strength of the light needed, in order to reach the fetal retina. Tissue thickness was measured from maternal skin to uterine wall and ranged between 1cm and 5cm thick. Del Guidice’s (2010) model of light penetration was employed to determine the strength of light needed. During the ultrasound assessment and experimental procedure, the 3D and 4D scans were broadcasted simultaneously to both the ultrasound machine and a laptop which recorded the scans onto an external hard drive. Once it was concluded, there were no fetal abnormalities and the light strength and fetal orientation had been established, the participant was asked to remain motionless to preserve image acuity and light source position. The lights in the room were then switched off, and the experimental study began. The custom-made light source was presented to the participant’s abdomen, showing a three dotted red light in two stages of light exposure. The times in which the light source was turned on and off, as well as the minutes measured, were noted and recorded by the experimenter on a data collection sheet and were controlled using a digital stop watch. The two stages of light exposure were randomised between participants to counterbalance the sample and reduce order effects. When the experimenter was ready to switch on the light source and begin testing, they would signal the sonographer so that both the 4D scan recording, the light source, and stopwatch were all started at the same time. In the first stage of light exposure, light was presented to the fetus in a constant stationary beam for 3 minutes, presented to the periphery to the side of the fetus. There was then a break period between the two stages of light exposure, to allow the participant, sonographer, and researchers to readjust their positions. The second stage of light exposure consisted of 10 intermittent beams of light, in which timing between each light beam was again controlled by an experimenter using a digital stopwatch. This stage of light was created according to the procedure of Johnson and Morton (1991), in which a light stimulus was slowly presented to the fetus along the arc of a protractor. The light was presented at a rate of around five degrees per second when the fetal head was positioned on the protractor mid-line at zero degrees. Therefore, the present study decided the second form of light would be presented to the side of the fetal head and then moved away from the head position horizontally across the abdomen for approximately five seconds, at a rate of 1 centimetre per second. After the assigned five seconds, the light source was temporarily switched off and the 4D scan turned to a 2D scan for around 20 seconds, following which the 5 second light exposure would then begin again. As aforementioned, this stage was repeated 10 times over a 3 minute period. On completion of both stages of light exposure, the experiment was finished, and the participants were thanked for their cooperation. Each scan recording ranged from between 8 to 22 minutes, corresponding to safety standards (Harr, 2011). All recordings were saved onto a specific file on an external drive and stored in a filing cabinet in the Lancaster University Psychology Department. The hard drive was kept separate from the light presentation times and mothers personal details, which were stored elsewhere in the department to retain maximum confidentiality and security. Data Coding Data was gathered from the participants by recording and coding 4D ultrasound real-time videos for fetal movements in response to a light stimulus. Consequently, a specific coding process needed to be established to certify all researchers were coding matching responses and ensuring research validity. The ultrasound recordings were coded using an external hard-drive and Mac computer. During a research team meeting, the experimenters agreed on four specific behavioural responses that would be coded for, before stimuli, during stimuli, and after stimuli. Coding for before stimuli was conducted for only the first three minutes before the first light exposure stage began, meaning if light stimulation began at eight minutes on the ultrasound recording, only five minutes onward would be coded for potential ‘before stimuli’ movement. The short break between the two light exposure stages was coded as after stimuli, despite additional stimulation being presented after a short interval. A timed approach was decided as the fetus had previously been exposed to light, therefore, possible continued fetal activation could influence behavioural response. Initially, the researchers observed several scans to better understand the procedure and to examine the characteristics of the data, in which four behaviours were clearly demonstrated. These four behaviours were used as the categories for coding movement. The first response was named ‘head movement, with eye movement’; the second response was ‘head movement, eyes move first’; the third response was ‘head movement, cannot depict eye movement' and the fourth response was ‘independent eye movement’. An excel spreadsheet was used to code the frequency of behavioural responses in three columns, before, during and after stimuli. Within these columns were a further four columns with each of the four possible behavioural responses. When a movement was observed, the participant number and time was noted in a row and a number one was placed in the corresponding behavioural column located on the same row. To reduce subjectivity during coding it was agreed that eye movements were to be coded when the probe was stationary and the light stimulus (displayed as a white dot on the 2D image scan) moved in any direction over the abdomen. Head movements were coded only when the centre position of the head moved clearly either right or left and up or down. This is important as the fetus often made small movements or moved their limbs, which may cover and/or reposition the head. Such movements could be confused with a singular head movement; therefore, only centre position movements were included in the coding data sheet. In addition, other non-fetal movements the researchers needed to be aware of included movement of the probe, as the probe was occasionally moved to gain greater image acuity. To identify this, the researchers agreed that the surrounding environment in utero must remain motionless as the head moves, such as the line representing the edge of the maternal uterus wall. Similarly, this rule was implemented when the mother breathed, as the fetus can appear to move, potentially causing further coding confusion. Thus, fetal head movements were only included in the data set if the external image was unmoving. Data Reduction Data clearing was conducted in an effort to increase internal research validity. Participant data was not submitted for behavioural coding if the fetal position could not be established or clearly seen during the ultrasound procedure. Visual acuity was particularly important during the experiment to determine where the light stimulus would be presented, therefore, if the fetal position was not clear, the light could not be accurately exposed to the peripheral of the fetus. Additionally, 12 individuals were later excluded from data analysis, as when coding for behavioural responses, the fetus was inactive and showed no movements. Inactivity meant a lack of any fetal actions available during behavioural coding, considered a sleep state in the fetal behavioural literature, therefore, the data was not included in the overall analysis.
Figurative language comprehension and links to autistic traits
figurative language comprehension emotions autism
Figurative language is used quite frequently in both speech and writing, as to express our creative and abstract thoughts. Traditionally, it was thought that metaphors are ornamental in nature, as well as they are used rarely compared to literal language. However, today’s research suggests that people use metaphors in everyday communication. Moreover, people seem to pay more attention to sentences which are emotionally evocative, rather than neutral ones. In addition, it has been extensively reported that socio-communicative skills might be related to the successful comprehension. Special populations, such as autistic individuals, often struggle with both figurative language comprehension and acknowledging properly other people’s emotions. However, no prior research has explored both different types of sentences and their content (emotional or neutral). Sixty-two participants took an online questionnaire measuring their comprehension abilities and the Autism-Spectrum Quotient (AQ) test, in order to measure their socio-communicative skills. Significant results were found for both the type of sentences, and the content. No significant effect of socio-communicative skills affecting comprehension was found. The results are discussed in terms of their theoretical and clinical importance.
Participants Sixty-two typically developed participants (M=31, F=31) between the ages of 18 and 62 (M= 24, SD=9.32) were got involved in the study. The majority of sample were students at Lancaster University (N=51). Participants were recruited in Lancaster (United Kingdom) via SONA or email. Twenty-nine participants were paid £5 (five British pounds) for taking part in the study. The remaining participants were not re-imbursed for their time. Only the adults (minimum age of 18) who were British English native speakers could have taken part in this study. Participants were not aware of a true aim of the study. Participants were simply told that the project is about figurative language comprehension, as to avoid any possible bias. At the end of their participation, they were informed about the details and the aims of the study. The study has been approved by the ethics committee. Apparatus and materials The participants were asked to complete an online questionnaire developed with the Qualtrics survey software. Upon recruitment, participants were sent a Qualtrics link to the survey. All participants were exposed to the same stimuli but each of them got a different randomised order. Approximately ten minutes were sufficient for participants to take part in the study. Participants could start answering the questionnaire and then finish it at another point of time if needed, as their answers were automatically saved for seven days after they opened the questionnaire on their browser. No more than 10 sentences were shown per page, as to avoid fatigue. Both literal sentences and novel metaphors used as stimuli in this project were originally structured by Cardillo, Schmidt, Kranjec, and Chatterjee (2012). Their aim was to construct a design of matched metaphoric and literal sentences as to test the role of novelty and different metaphor types involved in metaphor comprehension. The authors managed to control the next ten dimensions: dimensions: length, frequency, concreteness, familiarity, naturalness, imageability, figurativeness, interpretability, valence, and valence judgment reaction time. What makes these sentences even more different than previous work is the fact that the same word was used in both literal and novel metaphors. As such, literal sentences and novel metaphors were further analysed and selected in a laboratory by Francesca (my supervisor) Citron’s students. The students selected the stimuli based on existing value of valence and imageability, so that sentences from different condition would differ in emotional valence, but not in the imageability. Conventional metaphors were structured by the same students, as well. Students created simple sentences which contained similar structure as the existing ones. Yet, it was not possible to use the same word as from literal sentences and novel metaphors, so conventional metaphors were a bit more diverged. The content of sentences was controlled in a way that half of the sentences were positive, and another half of them was neutral, so that their level of imageability would have been similar to novel metaphors and literal sentences. Finally, for the current research, the conventional metaphors were edited as to make them shorter to be more alike to both literal sentences and novel metaphors. The length was calculated and analysed statistically, for both the content and the types of sentences. There was no significant difference neither between the number of words nor the number of letters, both regarding the content and the types of sentences, p>.05. It is important to note that the current study did not replicate what Cardillo, Schmidt, Kranjec, and Chatterjee (2012) already explored since their main interest was to investigate neural processes underlying metaphor meaning. The questionnaire consisted of 120 short questions such as ‘To which extent do you understand this sentence?’ containing one type of a metaphor expression (e.g. ‘The woman dove into the pool.’). Participants were required to rate the ease of the comprehension on a scale from one (‘It does not make any sense at all.’) to five (‘It makes perfect sense.’). The questionnaire included 20 sentences of each of the following groups, which are presented in the Table 1. The Autism-Spectrum Quotient (AQ) The AQ test was used at the end of the questionnaire. It is a self-report measure of autistic traits and presents a valuable instrument for rapid quantifying where any given individual is situated on the continuum from autism to normality (Ruzich et al., 2015). The test was constructed by Baron-Cohen, Wheelwright, Skinner, Martin, and Clubley (2001) since no prior instrument at that time could have measured such factor. It can be administered to adults of at least average intelligence with autism or to nonclinical controls but can also be administered to clinical control groups (e.g., individuals with depression) (Ruzich et al., 2015). The AQ consists of 50 questions assessing five different areas: social skill, attention switching, attention to detail, communication, and imagination. Thus, participants’ scores could range between 0 and 50. Approximately half the items were worded to produce a “disagree” response, and half an “agree” response. This was to avoid a response bias either way. Following this, items were randomized with respect to both the expected response from a high-scorer, and with respect to their domain (Baron-Cohen, Wheelwright, Skinner, Martin, & Clubley, 2001). Design and procedure The dependent variable was the ease of figurative language understanding. The within-participants independent variables were type of a sentence (conventional, novel, and literal) and content (positive or neutral). Conventional metaphors represent expressions commonly used in everyday setting, whereas novel metaphors were made up for this occasion. The between-participants independent variable was the degree of autistic-like traits (either high or low). To obtain this latter variable, participants were divided into two groups based on their AQ scores. The median score was used to split them. Participants were instructed to rate their understanding of metaphors in 120 sentences. There were 20 sentences of each type × content (e.g., conventional positive) (see Appendix A). Thus, six different mean scores were calculated for each participant (conventional positive, conventional neutral, literal positive, literal neutral, novel positive, novel neutral).The Likert scale consisted of five points (1-‘It doesn’t make any sense at all’, 2-‘It doesn’t make much sense’, 3- ‘It makes some sense’, 4- ‘It makes sense’, 5-‘It makes perfect sense’). The following coding rules were applied to calculate the AQ score: “definitely agree” or “slightly agree” responses scored 1 point on items number 1, 2, 4, 5, 6, 7, 9, 12, 13, 16, 18, 19, 20, 21, 22, 23, 26, 33, 35, 39, 41, 42, 43, 45, 46. “Definitely disagree” or “slightly disagree” responses scored 1 point on items number 3, 8, 10, 11, 14, 15, 17, 24, 25, 27, 28, 29, 30, 31, 32, 34, 36, 37, 38, 40, 44, 47, 48, 49, 50 (see Appendix B). Subsequently, the AQ scores were divided in two groups based on the median score (Med = 19.5). Any results above the median threshold were categorised as high, and those below were categorised as low. Half of the sample (N = 31) scored high, while the other half (N= 31) achieved a low score. Results were analysed using a 3x2x2 mixed analysis of variance (ANOVA).
The roles of reading motivation and reading strategies in secondary school students’ reading comprehension
reading comprehension; reading inference; reading motivation; expository and narrative texts; secondary school
The aim of the study was to investigate comprehension and inference ability in relation to text genre, reading strategies, intrinsic and extrinsic reading motivation, and gender in mainstream secondary school UK students. Data were collected from a sample of 27 participants; retained data of 9 secondary school students (5 males, 4 females) data were used for the study analysis. These responses were used to inform a simulated dataset for the analysis. The participants completed an online study, which measured their intrinsic and extrinsic reading motivation The Motivation for Reading Questionnaire (MRQ; Wang & Guthrie, 2004), comprehension and inference ability of narrative and expository texts (Currie et al., 2021), and reading strategies (Denton, Wolters, et al., 2015). Due to sample size limitations the decision was made to simulate individual datasets for reading strategies, intrinsic reading motivation, extrinsic reading motivation, narrative texts, and expository texts by gender, following the simulation methods proposed by Muldoon (2019). The results of the study revealed that female participants scored lower on reading strategies and demonstrated poorer performance for narrative and expository texts. There was no gender difference found for reading motivation. These findings will be discussed in relation to our understanding of gender differences in inferential reading comprehension, reading motivation and practical implications for the classroom.
Participants The intention was to collect original data from UK Year 7, 8, 9, and 10 mainstream secondary school students. This was through schools and word of mouth. Unfortunately, schools who were approached were not able distribute the study information in time for data collection before the summer break. In total 27 students started the study and completed data was collected from 9 (5 males, 4 females; M age = 13.83 years, SD = 2.45). These data were used to inform a simulated dataset to test the study predictions.
Materials Reading Motivation To assess students’ reading motivation 7 out of 8 domains from “The Motivation for Reading Questionnaire” (MRQ): A Revised Version (Wang & Guthrie, 2004) were used (grades domain from extrinsic scale was removed). The forty-one-question scale measured extrinsic and intrinsic motivation. Intrinsic motivation consisted of three domains: curiosity (7 items), involvement (7 items), and preference for challenge (5 items). Seven scales (curiosity, involvement, challenge, recognition, social and competition) reported good internal consistency (Cronbach’s alpha ˃ .70; Wang and Guthrie, 2004). An example of intrinsic motivation item: “I enjoy a long, involved story or fiction book”. Extrinsic motivation measured the following four domains: recognition (5 items), social (7 items), competition (6 items), and compliance (4 items). An example of extrinsic motivation item: “I like having my friends sometimes tell me I am a good reader”. Each statement had four possible answers, which were assigned values from 0 to 3 (very different from me = 0, a little different from me = 1, a little like me = 2, a lot like me = 3), and participants were asked to select the most appropriate for them. Scoring for negative item 40 was reversed before assigning the values. Text Genre Participants were asked to read 12 narrative, and 12 expository texts. Narrative texts focussed on human characteristics and activities, based on interactions with different social groups, as families, friends, peers at schools and youth clubs. Expository texts, were science-based, underpinned by chemistry, physics, biology, and geology. Each text consisted of 7 sentences, with 2 critical sentences that required an inference in order to integrate their meanings. The distance between two critical sentences was varied – either adjacent or separated by up to 3 sentences of filler text to minimise the detection of any pattern by readers, which might result in a focus on just the critical sentences, rather than reading the text as a whole. Each text was followed by one question, requiring choosing one answer from yes/no options (correct answer was allocated a value = 1; incorrect answer = 0), which assessed participant’s inference ability and comprehension. Participants completed two practice items, one expository and one narrative text, before starting the test. Reading Strategies Reading strategy knowledge was assessed with items from the Contextualized Reading Strategy Survey (CReSS; Denton et al., 2015). In this, participants read situation-based reading scenarios and rate how frequently they use different reading strategies in those situations. The three selected scenarios assessed reader’s construction integration abilities (Kintsch, 1988). An example of a scenario used for the study “As a homework assignment for your English class, you have been asked to read a story from your textbook. Tomorrow your teacher will give you a quiz about the story. Which of these things do you do to help you understand a story while you are reading or after reading?”. The following strategies were displayed for students to choose from “I try to make mental pictures of the information in the story while I read. While I am reading, I think about how the parts of the story go together. I think about what the characters are doing in the story and why they are acting as they are. I predict what I think will happen next. I think about how this story is like other stories I have read”. Each strategy had four response options, with values assigned from 0 to 3 (I almost never do this = 0; I sometimes do this = 1; I usually do this = 2; I almost always do this = 3) for participants to choose the one, which they use the most.
Procedure The study was hosted on Qualtrics platform. First, the parents/ guardians accessed the study via a link, then they provided their consent. The child saw the next screen, where they read the information about the study and provided their assent. Participants were asked to complete the task at home in their own time, outside of their school commitment time. Participants were asked to provide information about their gender, age - month and year only. Task order was: (1) reading strategies, (2) narrative texts with yes/no questions about the texts, (3) expository texts with yes/no questions about the texts, and (4) intrinsic and extrinsic reading questionnaire. For the reading strategies questionnaire, participants were asked to read 3 scenarios, as described above. They read each scenario and then indicated on a 4-point Likert scale how frequently they used each strategy. To assess inference making, participants read 12 short narrative texts, and also 12 short expository texts. Each text was shown on 1 screen with the inference-tapping question on a separate screen. They pressed a button next to YES or NO to provide their answer. The final task required participants to complete a reading motivation questionnaire. They read 19 statements for intrinsic and 22 statements for extrinsic reading motivation, and then indicated on the 4-point Likert scale how likely of them it was, as described above. The whole procedure took approximately 30 minutes. Collected data was stored in password-protected file, on password-protected Master student’s Lancaster University’s Office 360, accessed through password-protected laptop.
Ethical Considerations The research was approved by the University Department Ethics Committee, and conducted in line with the Lancaster University ethics guidelines: https://www.lancaster.ac.uk/sci-tech/research/ethics/, and the BPS Code of Ethics and Conduct (2018). Measures were taken to maintain the participants’ anonymity: identifiable information as participant’s name, school name, participant’s full date of birth were not collected; with references to data collection in England. To investigate the study purposes of age and gender related differences, participant’s month and year of birth were obtained, and the student’s gender as reported by participant were collected.
Does Noise Affect How Children Learn Grammar in the Classroom?
In a classroom environment noise can be a significant impediment, obstructing and distorting essential information being taught. Extensive prior research consistently indicates that noise has a detrimental impact on learning, those who learn in noise retain and comprehend far less information than their counterparts who learn in quiet. To date there are no studies that investigate the effect of noise on learning grammar specifically -the primary aim of the current study is the address this research gap. This paper details our recruitment of 16 children aged 7– 12 through the Babylab database at Lancaster university. This study employed a between participants design, where children completed a three-part audio evaluation, engaged in an artificial grammar paradigm, and a undertook a working memory task. The artificial grammar paradigm was employed as our primary assessment tool, participants were exposed to the grammar either in noise or in quiet. Results were analysed using a multiple regression with total grammar score as the dependent variable and age, gender, condition, and working memory as the independent variables. In contrast the prior research, our results revealed that the effect of the independent variables on the dependent variable was statistically nonsignificant, proving our null hypotheses to be true. These findings suggest that background noise does not affect how children learn grammar in the classroom challenging the existing understanding that noise negatively impacts learning.
Participants 16 children aged 7-12 years old participated in this study, unfortunately due to technical issues 5 participants’ data were excluded leaving 11 children’s data to be included in the analysis (M=8.64, SD=1.63, female=7, male=4). Children were recruited through the Lancaster University Babylab database and by flyers posted on social media and local community. A requirement of the current study was that children be English speaking monolinguals, this is because an abundance of research has indicated that those who can speak two or more languages are at a far greater advantage when it comes to new language acquisition (Antoniou et al., 2015). Therefore, in order to control the likelihood of extraneous variables such as this we ensured all participants were English speaking monolinguals only. Furthermore, children were also required to have normal vision or corrected to normal vision. To rule out hearing loss all children had to pass an otoscope inspection, a tympanometry test, and a pure tone hearing screening at 20dB in the standard frequencies (250Hz-8kHZ). The current study employed a between participant design whereby subjects were allocated to a condition based on their age and gender -age was categorised into 7-9 and 10-12- in order to ensure that there were as equal an amount of males and females in each condition over all ages. It is crucial for the validity of the study that children are only exposed to the artificial grammar paradigm once or data will be rendered unreliable as they will have an unfair advantage over the other participants. Ethics for the current study have been obtained from the Departmental Ethics Committee (DEC), Psychology Department at Lancaster University. Materials This study was conducted within a double walled soundproof chamber at Lancaster University’s PELiCAN lab where the participant sat at a desk with a monitor placed in front of them. A secondary researcher was present in the lab for health and safety purposes. Consent and assent forms, a background questionnaire on the child’s hearing, audio evaluation results, and task data were all recorded on REDCap (Harris et al., 2009; Harris et al., 2019): a GDPR compliant application for data capture. Travel compensation was provided: £5 within 40 minutes and £10 for over 40 minutes. Furthermore, children received a certificate and book of their choosing from the PELiCAN lab. The audio evaluation This study was comprised of three sections: an audio evaluation whereby an otoscope examination, tympanometry test, and audiogram using Affinity Suite were conducted. During the audiogram participants wore headphones and had a handheld button that they pressed when they heard the pure tone sounds. The Artificial Grammar Paradigm After passing the hearing evaluation the children completed an artificial grammar paradigm previously used by Torkildsen et al. (2013) consisting of two grammatical forms: aX and Yb. The paradigm was presented in the form of an alien game whereby the children helped an alien learn a new language. We presented the paradigm in this format in order to increase engagement; children are motivated by the colourful and curious nature of a game (Blumberg et al., 2019) and therefore we are far more likely to obtain more data (less drop outs due to fatigue and boredom). This task was created in PsychoPy and hosted by Pavlovia. The background noise In order to imitate the background noise of a classroom speech shaped noise (SSN) (e.g. Leibold et al., 2013) was emitted through a speaker on the back wall of the booth behind the child. The background noise speaker was 180 degrees on the azimuth, and the target speaker was 0 degrees on the azimuth. Background stimuli was calibrated so that for the quiet condition the stimulus was emitted at 35dB and for the noisy condition it was played at 65dB. The n-back Test of Working Memory Lastly, we conducted the 1-back test of working memory (Owen et al., 2005) which was also created on PsychoPy and hosted by Pavlovia Procedure Prior to the commencement of the study guardians gave informed consent (See Appendix C), if the child was 11 or older they gave informed assent in addition to this (See Appendix D). Guardians were then asked to complete a short background questionnaire pertaining to their child’s hearing (See Appendix H). Whilst they completed these forms the researcher began the study inside the booth; using Affinity suite it was ensured that the microphone inside the booth was turned on in order for the guardian to be able to hear what was going on inside the booth by using the headphones places outside the booth. As aforementioned, the audio evaluation consisted of three tests, these were administered in the booth by the researcher and took up to 15 minutes. Firstly, an ear inspection was conducted using an otoscope, participants were required to have clear ears free of perforations and/or any infection. Secondly, a tympanometry test was conducted whereby participants must have passed with type A (normal) results. Lastly a pure tone hearing screening was conducted at 20dB in the standard frequencies (250Hz-8kHZ). The researcher left the booth for the audiogram in order to run the program on the desktop outside the booth while the child remained inside the booth. The task consisted of 11 blocks comprised of 4 exposure items and 2 test items, before the test portion children were exposed to 4 examples of what is expected of them, they had to get these right in order for the software to move onto the test phase. If children did not get these right the researcher explained and promoted them to pick the correct answer. Children were required to press ‘x’ on the keyboard for right and ‘n’ on the keyboard for wrong, answers were saved and recorded automatically on Pavlovia. The software was run by the researcher from outside the booth and was mirrored onto the desktop inside the booth. Lastly, we conducted the 1-back test of working memory (Owen et al., 2005), where children were exposed to a number of animal sounds and were required to record weather the stimuli was a new sound or one they had heard before, ‘x’ represented repeated sound and ‘n’ represented a new sound, participants had to ensure they made a button press after each noise. Once all tasks were completed the researcher collected the child from inside the booth and a short verbal and written debrief was given to the child and guardian. Guardians were given and signed for their travel compensation, and children received a certificate from the PELiCAN lab and were able to choose a book of their liking. Participants were walked back to their car or bus to bring a close to the visit. Analysis In order to answer our research questions we will carry out a multiple linear regression using IBM SPSS Statistics (version 28). We will be employing a between participants design where we will examine the effect of background noise (noisy and quiet) on total grammar score. Our additional independent variables will be working memory, gender and age. If we find a statistically significant result with regard to grammar score then we will be conducting a post hoc test on grammar score breaking them down into aX and Yb in order to determine the difference between the two types of grammar.
In a classroom environment noise can be a significant impediment, obstructing and distorting essential information being taught. Extensive prior research consistently indicates that noise has a detrimental impact on learning, those who learn in noise retain and comprehend far less information than their counterparts who learn in quiet. To date there are no studies that investigate the effect of noise on learning grammar specifically -the primary aim of the current study is the address this research gap. This paper details our recruitment of 16 children aged 7– 12 through the Babylab database at Lancaster university. This study employed a between participants design, where children completed a three-part audio evaluation, engaged in an artificial grammar paradigm, and a undertook a working memory task. The artificial grammar paradigm was employed as our primary assessment tool, participants were exposed to the grammar either in noise or in quiet. Results were analysed using a multiple regression with total grammar score as the dependent variable and age, gender, condition, and working memory as the independent variables. In contrast the prior research, our results revealed that the effect of the independent variables on the dependent variable was statistically nonsignificant, proving our null hypotheses to be true. These findings suggest that background noise does not affect how children learn grammar in the classroom challenging the existing understanding that noise negatively impacts learning. Analysis In order to answer our research questions we will carry out a multiple linear regression using IBM SPSS Statistics (version 28). We will be employing a between participants design where we will examine the effect of background noise (noisy and quiet) on total grammar score. Our additional independent variables will be working memory, gender and age. If we find a statistically significant result with regard to grammar score then we will be conducting a post hoc test on grammar score breaking them down into aX and Yb in order to determine the difference between the two types of grammar.
Participants 16 children aged 7-12 years old participated in this study, unfortunately due to technical issues 5 participants’ data were excluded leaving 11 children’s data to be included in the analysis (M=8.64, SD=1.63, female=7, male=4). Children were recruited through the Lancaster University Babylab database and by flyers posted on social media and local community. A requirement of the current study was that children be English speaking monolinguals, this is because an abundance of research has indicated that those who can speak two or more languages are at a far greater advantage when it comes to new language acquisition (Antoniou et al., 2015). Therefore, in order to control the likelihood of extraneous variables such as this we ensured all participants were English speaking monolinguals only. Furthermore, children were also required to have normal vision or corrected to normal vision. To rule out hearing loss all children had to pass an otoscope inspection, a tympanometry test, and a pure tone hearing screening at 20dB in the standard frequencies (250Hz-8kHZ). The current study employed a between participant design whereby subjects were allocated to a condition based on their age and gender -age was categorised into 7-9 and 10-12 in order to ensure that there were as equal an amount of males and females in each condition over all ages. It is crucial for the validity of the study that children are only exposed to the artificial grammar paradigm once or data will be rendered unreliable as they will have an unfair advantage over the other participants. Ethics for the current study have been obtained from the Departmental Ethics Committee (DEC), Psychology Department at Lancaster University. Materials This study was conducted within a double walled soundproof chamber at Lancaster University’s PELiCAN lab where the participant sat at a desk with a monitor placed in front of them. A secondary researcher was present in the lab for health and safety purposes. Consent and assent forms, a background questionnaire on the child’s hearing, audio evaluation results, and task data were all recorded on REDCap (Harris et al., 2009; Harris et al., 2019): a GDPR compliant application for data capture. Travel compensation was provided: £5 within 40 minutes and £10 for over 40 minutes. Furthermore, children received a certificate and book of their choosing from the PELiCAN lab. The audio evaluation This study was comprised of three sections: an audio evaluation whereby an otoscope examination, tympanometry test, and audiogram using Affinity Suite were conducted. During the audiogram participants wore headphones and had a handheld button that they pressed when they heard the pure tone sounds. The Artificial Grammar Paradigm After passing the hearing evaluation the children completed an artificial grammar paradigm previously used by Torkildsen et al. (2013) consisting of two grammatical forms: aX and Yb. The paradigm was presented in the form of an alien game whereby the children helped an alien learn a new language. We presented the paradigm in this format in order to increase engagement; children are motivated by the colourful and curious nature of a game (Blumberg et al., 2019) and therefore we are far more likely to obtain more data (less drop outs due to fatigue and boredom). This task was created in PsychoPy and hosted by Pavlovia. The background noise In order to imitate the background noise of a classroom speech shaped noise (SSN) (e.g. Leibold et al., 2013) was emitted through a speaker on the back wall of the booth behind the child. The background noise speaker was 180 degrees on the azimuth, and the target speaker was 0 degrees on the azimuth. Background stimuli was calibrated so that for the quiet condition the stimulus was emitted at 35dB and for the noisy condition it was played at 65dB. The n-back Test of Working Memory Lastly, we conducted the 1-back test of working memory (Owen et al., 2005) which was also created on PsychoPy and hosted by Pavlovia Procedure Prior to the commencement of the study guardians gave informed consent (See Appendix C), if the child was 11 or older they gave informed assent in addition to this (See Appendix D). Guardians were then asked to complete a short background questionnaire pertaining to their child’s hearing (See Appendix H). Whilst they completed these forms the researcher began the study inside the booth; using Affinity suite it was ensured that the microphone inside the booth was turned on in order for the guardian to be able to hear what was going on inside the booth by using the headphones places outside the booth. As aforementioned, the audio evaluation consisted of three tests, these were administered in the booth by the researcher and took up to 15 minutes. Firstly, an ear inspection was conducted using an otoscope, participants were required to have clear ears free of perforations and/or any infection. Secondly, a tympanometry test was conducted whereby participants must have passed with type A (normal) results. Lastly a pure tone hearing screening was conducted at 20dB in the standard frequencies (250Hz-8kHZ). The researcher left the booth for the audiogram in order to run the program on the desktop outside the booth while the child remained inside the booth. The task consisted of 11 blocks comprised of 4 exposure items and 2 test items, before the test portion children were exposed to 4 examples of what is expected of them, they had to get these right in order for the software to move onto the test phase. If children did not get these right the researcher explained and promoted them to pick the correct answer. Children were required to press ‘x’ on the keyboard for right and ‘n’ on the keyboard for wrong, answers were saved and recorded automatically on Pavlovia. The software was run by the researcher from outside the booth and was mirrored onto the desktop inside the booth. Lastly, we conducted the 1-back test of working memory (Owen et al., 2005), where children were exposed to a number of animal sounds and were required to record weather the stimuli was a new sound or one they had heard before, ‘x’ represented repeated sound and ‘n’ represented a new sound, participants had to ensure they made a button press after each noise. Once all tasks were completed the researcher collected the child from inside the booth and a short verbal and written debrief was given to the child and guardian. Guardians were given and signed for their travel compensation, and children received a certificate from the PELiCAN lab and were able to choose a book of their liking. Participants were walked back to their car or bus to bring a close to the visit.
Academic Resilience: Adversity and traumatic experience in an educational context at university
academic resilience traumatic experience resilience nontraumatic experience stress self-esteem self-efficacy academic performance
Resilience is a process whereby individuals bounce back or beat the odds despite the significant threat that can jeopardise their development. Academic resilience pertains to student´s success after educational adversity and their coping behaviour in challenging circumstances. Recently academic resilience became a validated psychological construct, and the present study uses this Academic Resilience Scale (ARS) to measure students response to academic adversity in a university sample with three analysis. The primary analysis: estimated the Life Event Checklist (LEC) or traumatic experienced and academic resilience which is unresearched. The findings indicated that students´ who have experienced a traumatic life event(s) and stressful situations are showing slightly more academic resilience than those who have not experienced a traumatic life event and stressful situations. A second analysis: academic resilience in a relationship with the life event, brief resilience, self-esteem, self-efficacy, perceived stress, and academic performance. Both self-efficacy and brief resilience predicted academic resilience. Third analysis: same parameters from the second analysis was utilised but now in a relationship with traumatic experienced and displayed that traumatic students had a more tendency for brief resilience, self-efficacy, self-esteem but perceived more stress than nontraumatic student´s. These results show that the academic resilience could be used as an intervention in the educational environment to enhance student´s coping behaviour and facilitate them to adjust more effectively in challenging circumstances.
Participants The sample was based on an internet survey of 154 Lancaster University students from 29 different nationalities who enrolled either as an undergraduate at first year (n = 47), second year (n = 49), third year (n = 30), Master student (n = 19) or PhD student (n = 3). Subsequently, five participants were excluded because of not being a student. The final sample contained 149 participants between the ages of 18 and 52 years old (M = 21.21; SD = 3.66). Majority of participants ethnicity was 51.6% British, 10.5% Chinese, 3.3% Indian, 2,6% South Korean and 2.6% Cypriot and other nationalities were in the minority. The principal investigator was not able to obtain gender because of a technical problem. Materials Academic Resilience Scale-30 (ARS-30) ARS-30 (Cassidy, 2016), measures academic resilience and is developed to estimate university students. Participants answer 30 statements of an imaginative vignette where a comment or feedback from a tutor about a low grade on an assessment that was presented. Participants imagine themselves being in that position and their response is confined to a statement: „You have received your mark for a recent assignment, and it is a ‘fail.’ The marks for two other recent assignments were also poorer than you would want as you are aiming to get as good a degree as you can because you have clear career goals in mind and don’t want to disappoint your family. The feedback from the tutor for the assignment is quite critical, including reference to ‘lack of understanding’ and ‘poor writing and expression,’ but it also includes ways that the work could be improved. Similar comments were made by the tutors who marked your other two assignments.“ Responses were on a 5-point Likert scale 1 (very likely) to 5 (very unlikely). Items include, “ I would not accept the tutors´ feedback”; “I would just give up”; and” I would blame the tutor.” Following the guidelines provided by Cassidy (2016), 9 of the items were reverse-coded (e.g., “I would not accept tutors´ feedback”). The author of the scale report high internal consistency (Cronbach´s alpha = 0.90). The ARS-30 has a theoretical range of 30-150, with higher scores indicating greater academic resilience (Cassidy, 2016). The internal consistency of ARS-30 in the current study was (Cronbach's alpha = 0.85). Life Event Checklist-17 (LEC-17) LEC-17 (Blake, Weathers, Nagy, Kaloupek, Charney, & Keane, 1995) is a measure of traumatic experiences and stressful situations which range from single stressful life experience to aggregates across multiple incidents. Participants respond to 17 items on 5-point nominal scale 1 (happened to me) 2 (witnessed it) 3 (learned about it) 4 (not sure) and 5 (does not apply). Example of questions, “Natural disaster (for example, flood, hurricane, tornado, earthquake)”; “Assault with a weapon (for example, being shot, stabbed, threatened with a knife, gun, bomb)”; “Sudden, unexpected death of someone close to you.” The measurement is usually used in a clinical setting to assess PTSD (Gray, Litz, Hsu, & Lombardo, 2004). In the present study, the measurement is merely utilised to examine if participants have experienced traumatic and stressful situations. Other than that, internal consistency of recent studies (Bae, Kim, Koh, Kim, & Park, 2008) is (Cronbach alpha = 0.66), LEC-17 also shows external reliability from r = .44 to r = .55, suggesting significant correlation with other measures that assess traumatic experiences and stressful situations in supporting of the scale´s construct validity (Gray, Litz, Hsu, & Lombardo, 2004). The internal consistency of LEC-17 in the current study was (Cronbach´s alpha = .90). Subsequently, the life event variable was divided into two variables (1 = Traumatic and 2 = Nontraumatic). Previous studies assigned participants who scored 1 (happened to me) as only traumatic individuals and 0 was assigned if any other responses option was endorsed and recorded as nontraumatic individuals (Gray et al., 2004). In the current study, participants who responded to 1 (happened to me) and 2 (witnessed) were combined as traumatic based on the effect of witnessing a traumatic event; it can not be ruled out how intense and excessive this experiences might be (American Psychiatric Associations, 2013). On the other hand, participants who based their responses on 3 (learned about it), 4 (not sure) and 5 (does not apply) was registered as nontraumatic. Brief Resilience Scale-6 (BRS-6) The resilience of participants was assessed with the BRS-6 and participants responded to 6 items on a 5-point Likert scale ranging from 1 (Strongly disagree) to 5 (Strongly agree), on items such as “I tend to bounce back quickly after hard times”; “It does not take me long to recover from a stressful event”, and “I tend to take a long time to get over set-backs in my life.” Three items were reverse-coded (e.g., “I have a hard time making it through stressful events”) to follow the structure of prior studies. The internal consistency of (Cronbach alpha 0.80-0.91). A higher score indicating greater resilience (Smith, Dalen, Wiggins, Tooley, Christopher & Benard, 2008). The internal consistency of BRS-6 in the current study was (Cronbach´s alpha = 0.39). Rosenberg Self-Esteem-10 (RSE-10) Self-esteem was measured with RSE-10 (1965) by evaluating both positive and negative feeling about the self. Participants answer ten items on 4-point Likert scale 1 (Strongly agree) to 4 (Strongly disagree). Example of items are, “On the whole, I am satisfied with myself”; “I feel I do not have much to be proud of”; “I take a positive attitude toward myself.” Five items were reverse-coded (e.g., “At times I think I am no good at all”). Reported (Cronbach's alpha = 0.84-0.86) (Tinakon & Nahathai, 2012). A higher score indicates greater self-esteem. The internal consistency of RSE-10 in the current study was (Cronbach´s alpha = 0.87). Student Self-Efficacy-10 (SSE-10) Self-efficacy was assessed with SSE-10 which is an estimation of the student´s belief in their capabilities to carry out, organise and perform a task successfully. The previous study by (Rowbotham & Schmitz, 2013) used a different way to measure with a four-point response format 1 (Not at all true) to 4 (Exactly true). Participants in the current research respond to 10 items on 4-point Likert scale 1 (Strongly agree) to 4 (Strongly disagree). Item example, “ I am convinced that I am able to successfully learn all relevant subject content even if it is difficult”; When I try really hard, I am able to learn even the most difficult content”; “I know that I can stay motivated to participate in the course.” Reported (Cronbach´s alpha = 0.84), and external r = .70 reliability and implying that students self-efficacy correlates significantly with similar measures of self-efficacy showing construct validity (Martin & Marsh, 2006; Cassidy, 2016). Scores ranged from 10-40 with higher scores representing higher student self-efficacy (Rowbotham & Schmitz, 2013). The internal consistency of SSE-10 in the current study was (Cronbach´s alpha = 0.85). Perceived Stress Scale-14 (PSS-14) Perceived stress was evaluated with PSS-14 which is a measure of stress quite general and consequently relatively free of content specific to any sub-population group. Participants respond to 14 items on 5- point Likert scale 0 (Never) to 4 (Very often). Related items are, “In the last month, how often have you been upset because of something that happened unexpectedly?”; In the last month, how often have you felt nervous and “stressed”?”; In the last month, how often have you felt that you were on top of things?”. Following the guidelines provided by Cohen, Kamarck & Mermelstein (1983), seven items were reverse-coded (e.g. “In the last month, how often have you felt confident about your ability to handle your personal problems”). Internal consistency of previous studies is between (Cronbach´s alpha = 0.70) (Lee, 2012) and (Cronbach´s alpha = 0.82) (Andreou, et al., 2011). A higher score indicates greater stress. The internal consistency of PSS-14 in the current study was (Cronbach´s alpha = 0.82). Academic Performance Academic performance derives from average grade from each participant, undergraduates at first year provided merely two marks at the second year and master students provided only part 1 mark. Both undergraduates at a second and third year offered part 1 mark and part 2 mark. These average grades were combined and used as a measure of their academic performance. Not all participants gave permission for obtaining their average grades, but hundred and three participants approved this inquiry. The undergraduate at first year with part 1 mark was (M = 62.6; SD = 10.0) and part 2 mark was (M = 71.9; SD = 2.33). The undergraduate at second year with part 1 mark with two participants was (M = 63.0; SD = 8.56 and part 2 mark (M = 63.5; SD = 9.42). The undergraduate at third year with part 1 mark was (M = 62.6; SD = 6.41) and part 2 mark (M = 63.7; SD = 7.05). Masters mark with merely part 1 mark (M = 68.7; SD = 5.41). The combination of these marks are measured as Academic Performance (See Table 1.). Cronbach alpha threshold Each questionnaire met Cronbach alpha level or internal consistency where the criterion is at .70 or above (Nunnally & Bernstein, 1994), apart from Brief Resilience which showed (Cronbach´s alpha = 0.39), even though will not be excluded. Procedure The methodology was pre-registered before data collection (see Appendix 1). After a review and approval from Lancaster University´s Psychology Department´s Research Ethics committee, the study commenced. Hundred and fifty-four participants were collected and answered an internet survey on Qualtrics (2018) but were reduced to a hundred and forty-nine. Participants were immediately informed of the purpose of the study without revealing the research hypothesis to prevent social desirability or to avoid demand characteristics. Participants were also enlightened that their data will be anonymised and treated as confidential and only used to understand who has taken part in the study. In the following, participants were given an explanation of possible risks in two measures, and for ethical issues, participants were told in advance that they would be asked about whether they have experienced any traumatic or difficult life events. For example in LEC-17 questions like “sexual assault (rape, attempted rape, made to perform any type of sexual act through force or threat of harm” among other questions in relation to recalling of events that were related to traumatic experience and could cause some inconveniences. Second, PSS-14 with a question such as “in the last month, how often have you been angered because of things that happened that were outside of your control?” could cause some inconveniences also in association to antecedent stress or stress that the participant perceived at the moment. Participants were made aware that participating in the study is entirely voluntarily and informed about the rights to withdraw at any time during the study without being penalised or being in debt to the Lancaster University by any means. Participants were also informed about the benefit of participating in the survey by contributing to a better understanding of academic achievement and how different events can affect the academic process (See Appendix 2). Therefore, after participants agree to participate in the study, the demographics were obtained such as which university participants study at, if participants responded to at Lancaster University, they were asked for permission of acquiring their average grade with dichotomous yes and no. Then records of age, nationality, student status (Undergraduate 1,2,3 year, Master, PhD, Other or Not a student), and what major they are studying (See Appendix 4). The participants were approached at the university campus regardless of locations and responded to six measurements with 87 items on an Ipad owned by the principal investigator(See Appendix 5,6,7,8,9,10). In the debrief part of the research, participants were informed about the purpose of the study and the study hypothesis along with short details of the literature behind this review. Additionally, contact information such as the principal investigator or supervisor if any questions were provoked afterwards about the research itself or anything related to the process of the study. If participants wish to discuss with someone outside of the study, information about the head of the Psychology department was also tangible.
Seeing helps our hearing: How the visual system plays a role in speech perception
Difficult listening conditions can result in a decrease in our ability to successfully discriminate speech. In these conditions, the visual system assists with speech perception through lipreading. Stimulus onset asynchrony (SOA) is used to investigate the interaction between the two senses in speech perception. Due to widely stimulus dependent effects, the exact timings for how far one stream can be asynchronized against the other drastically differs from account to account. Previous research has not considered viseme categories to ensure that selected speech phonemes are visually distinct. This study aims to create and validate a set of audiovisual stimuli that considers these variables for examining speech-in-noise, and to determine the SOA integration period for these stimuli. 27 online participants would be presented with either audio-only stimuli of a speaker speaking or audiovisual stimuli that also contained visuals of the speaker’s lip and mouth area as the speech were spoken. The speech was either clear or in-noise, and either displayed no stimulus onset asynchrony (SOA) or had SOA introduced at one of five different levels (200ms, 216.6ms, 233.3ms, 250ms, 266.6ms). Results indicate that, whilst the effect of visual information assisting with speech-in-noise is apparent, it is weaker of an effect than previous literature. Whilst response times imply that 250ms marks the integration window period for our stimuli, no significant accuracy changes corroborate this finding. In all, the study was successful in creating a more valid set of stimuli for testing. As power sufficiency was not met, more testing would be required to firmly cement the findings.
connection, allowing for a direct, uninterrupted video feed at 1920x1080 resolution and 60 frames per second. The camera was mounted onto a stable tripod to reduce movement of the camera as much as possible during recording. DroidCam X software was used to aid the streaming of the video in real-time with little compression and loss whilst still retaining a 1080p@60fps quality level. OBS software was used for recording as it allowed the audio from the external microphone and the video from the camera to be encoded together in real-time as a single MKV file. This was beneficial, as it removed potential human error that can occur when manually stitching audio files and video files together. Therefore, we can be certain that there were no asynchronous anomalies between the audio and video streams during encoding. Another benefit of OBS software is that it reports how many frames of video are dropped when recording and encoding an MKV file, which was important to ensure that the home desktop was encoding the video in its entirely akin to a lab-calibrated desktop. No frames were reported to be dropped for all speech tokens recorded. All stimuli were recorded as MKV files initially to avoid lossy compression in the recording. A software-based x264 bit CPU encoding method was used for the recording, due to a lack of internal GPU encoding method (such as Nvenc encoding) on the home system. After the initial recording, the speech tokens were edited in length and converted to mp4 files at a resolution of 1280 x 720p and a frame rate of 60 frames per second. As the study would be completed on participant’s laptops or desktop systems and using their internet connection, we cannot ensure that all participants are using a device with a 1920 x 1080p resolution screen. By reducing the resolution of files to 720p, all potential participant resolution sizes can be accommodated whilst ensuring all participants view the files at the same resolution. For audio-only conditions, the video of the lips was overlayed with a plain black PNG image file. This kept the audio-only stimuli in video format rather than export the file as an mp3. Regarding the inability to control the internet connection speeds of each participant, the experiment was set to download all stimuli as browser cache before it began, ensuring that there were no latency differences. Audacity software (Audacity Team, 2021) was then used to rip the audio from the MKV files to be edited as WAV files in Praat software (Boersma & Weenink, 2021) for the creation of speech-shaped noise. First, a sentence using English words – ‘His plan meant taking a big risk’ - was recorded to provide a base for the speech-shaped noise. White noise was then produced using Praat’s white noise generator. The noise was brought down to an intensity tier, then an amplitude tier. This was then multiplied with the sentence above to create speech-shaped noise. Praat was then used to combine the speech-shaped noise with the speech-in-noise conditions at a speech to noise ratio of minus 16dB. This was done using a Praat script developed by McCloy (2021). Finally, Audacity was used again to ramp up the start and ramp down the ends of all audio files for every condition. The audio was then stitched back onto the MP4 files. For the conditions where the onset of the stimuli was asynchronous, Lightworks was again used to displace the audio ahead of the onset of the speech token using exact frames of the video footage (12, 13, 14, 15, and 16 frames per second) which corresponded with the stimulus onset asynchrony levels of the relevant conditions. The result was 42 stimuli in MP4 format, representing three speech tokens (Ba, Fa, and Ka) for each of the 14 conditions presented to the participant. These were uploaded to a GitHub repository to be accessed by Pavlovia during the experiment. Procedure Participants were first given a participant code and a link to the online Qualtrics consent and screening forms via email. A copy of the participant information sheet was displayed at the start of the Qualtrics questionnaire to remind participants of the study to ensure informed consent was given. Participants were also reminded at this stage to ensure that they were in a quiet room with no background noise, as well as to load the experiment on either Microsoft Edge, Google Chrome, or Mozilla Firefox internet browsers on a laptop or desktop computer. They were explicitly told not to open the experiment on any other browser, such as Safari, nor on a mobile or tablet device as these were incompatible. Once consent had been given and the participant had met the screening criteria based on their answers, they were automatically redirected to the experiment on Pavlovia. If a participant did not meet the criteria for the study, they were redirected to a message informing them of their ineligibility and they were prevented from proceeding to the rest of the experiment. To begin the experiment, participants were once again reminded of browser and device limitations and told to use headphones in a quiet room. If a participant was using an incompatible device or browser to load the experiment, they were instructed to close the experiment and re-open it on the correct device or browser before beginning. A volume check began, in which a constant A tone played, and participants were asked to adjust the volume of their device as necessary for a comfortable auditory experience and to ensure that the audio was playing correctly at a sufficient volume level. In a typical lab setting, a set volume would be decided for all participants. However, as the study was completed online on the participant’s own devices, settling for the participant’s preferred hearing volume was preferable instead. Once complete, the spacebar would be pressed, and the tone stopped. Participants were then given a brief explanation of the task to complete. They were informed that a video would play either showing no visual information or visual information of lips moving. Meanwhile, speech would be played. Participants were told to listen carefully to the speech sound spoken, and after hearing the sound to press one of three buttons on their keyboards that corresponded with the three available speech tokens. They were reminded before and after each trial to press 'z' on their keyboard if they heard "Ba", 'x' for "Fa", or 'c' for "Ka”. Participants were told to answer as quickly as possible. If they were unsure, they were told to make a guess. To begin, participants were given 6 practise trials to attempt the task before data was collected. This was using the clear, 0ms, audiovisual condition stimuli, with 2 trials for each of the 3 speech tokens (Ba, Fa, and Ka). A white crosshair would be displayed on the screen for 1000ms before the trial began to bring attention to the centre of the screen where the video trials would be displayed. Stimuli were shown for 2500ms, then the response screen would display. On this screen, the participants were reminded of the buttons to press for each of the three speech sounds. Only the three buttons could be pressed and pressing the buttons whilst the stimuli were still playing was not possible. The first key pressed after the stimuli were played was recorded and then would take the participant to a relay screen, where they would be informed to press the spacebar to continue. Upon pressing the spacebar, the white crosshair would return, and the next trial began. After completing the practice, the participant was reminded of the task details once more before the experiment began for real. A total of 546 trials (not including the practise trials) were completed. The order of the trials and conditions was completely random to counterbalance any potential order bias. Every 42 trials, a broken screen would appear. This screen told the participant to take a short break before continuing with a press of the spacebar. If the participant did not wish to take a break, they were permitted to continue with a spacebar press immediately. There was a total of 12 breaks in the experiment. After each break, participants were asked a basic mathematics question, for example: ‘What is 3 +2?’. Participants could only proceed to the next chunk of trials if they responded with the correct answer. This was put in place to ensure that participants were continuing to pay attention to the experiment. Upon reaching the end of the final trial, participants were shown an ending screen where they were informed that the experiment had ended. Participants were also informed to email the primary researcher for debriefing information. Upon completing the study, participants could close the browser tab or window down and all data would remain recorded on the Pavlovia system. If a participant closed the browser tab or window during the experiment, partial data would be recorded up to the last trial that they responded to. If this was by mistake, participants could open the experiment again and restart. However, progress would not be saved, and the participant would have to start the experiment again from scratch. Using the same participant code would not overwrite the participant’s previous data, and instead created a new participant dataset. Full datasets were used over the partial dataset in this case, unless no full dataset was recorded for a participant. Analysis Descriptive statistics were first gathered from each condition for both the accuracy ratings and the reaction times. The assumptions of linear and generalised linear mixed-effects models were tested, including residual plots to check for linearity, quantile-quantile plots for normality, assessing the levels of multicollinearity between stimuli type, speech type, and stimulus onset asynchrony levels using variance inflation factors, and ensuring the assumption of homoscedasticity is met. Using both lmerTest (Kuznetsova et al., 2020) and lme4 packages, a combination of both linear mixed-effects regression model (LMER) analyses for the response time scores and generalized linear mixed-effects regression model (GLMER) analyses for the accuracy scores were conducted. LMERs were chosen instead of repeated measures generalised linear models like ANOVA tests because it considers random effects that may be present across all 546 trials on a participant-by-participant basis. As accuracy is inherently bound – due to either being accurate or inaccurate only – it can be argued to be categorical. Therefore, GLMERs were used for accurate analyses to ensure that assumptions of categorical dependent variables in mixed-effects models are met. For the LMER analyses, there were two models. Model 1 used response times as the dependent variable, modelled with stimuli type and speech type as fixed effects. The interactive effect between stimuli type and speech type was also included in the model. Model 2 used response times as the dependent variable, modelled with speech type and stimulus onset asynchrony timings as fixed effects. The interactive effect between speech type and stimulus onset asynchrony timings was also included in the model. The GLMER analyses also had two models. Model 1 used accuracy as the dependent variable, modelled with stimuli type and speech type as fixed effects, including the interactive effects between the two fixed effects. Model 2 used accuracy as the dependent variable, modelled with speech type and stimulus onset asynchrony timings as fixed effects. Again, interactive effects were included. For all four analyses, the speech sound token used (Ba, Fa, or Ka), participant age, and the participant ID were all included as random effects in the respective models.
Factors Related to Burnout in Arab Social and Community Development Workers
The nature of social and community development work leaves the workers at the risk of experiencing burnout and emotional difficulties. The aim of this study was to explore the relationships between burnout and empathy, emotional dissonance, self-compassion and type of work (voluntary, paid) amongst social and community development workers. We hypothesised that high levels of empathy, high levels of self-compassion, low levels of emotional dissonance and fewer hours of paid work would be significant predictors of low levels of burnout. The sample consisted of 315 participants from Syria, Egypt, Lebanon, Jordan and Tunisia. Participants completed an online survey that includes the following measures: Maslach Burnout Inventory, Interpersonal Reactivity Index, Self-compassion Scale, and Emotional Dissonance Subscale from Frankfurt Emotion Work Scale. Correlation and regression analyses were performed to examine the relationships between the variables. The findings showed that empathy was not significantly correlated to burnout, however a positive correlation was observed between personal accomplishment and perspective taking. Self-compassion was strongly and negatively correlated with burnout. Emotional dissonance was negatively correlated with burnout, and it was the strongest predictor of burnout amongst the studied variables. Paid work hours were positively related to emotional exhaustion, depersonalisation and personal accomplishment while voluntary work hours were not related to any of burnout components. The present study indicates novel findings, and contributes to the literature by highlighting the key role of personal emotional regulation in predicting burnout amongst social and community development workers.
Participants completed an online Qualtrics-based survey which includes the following four measures: Burnout. The scores of burnout were assessed by the Maslach Burnout Inventory Human Services Survey (MBI-HSS). The MBI-HSS is a 22-item self-reported measure that comprises three subscales: Emotional Exhaustion (9 items), Depersonalisation (5 items) and Personal Accomplishment (8 items). Emotional Exhaustion (EE) refers to the feeling of being drained emotionally and physically. Depersonalisation (DP) stands for the negative inordinately attitude towards job-related aspects. Personal Accomplishment (PA) refers to the feelings of efficiency, productivity and competence achievements in the job. (Maslach et al., 2001; Maslach, & Jackson, 1996). All answers are rated on a seven-point scale that ranges from 0 “never” to 6 “every day”. Subscales produce separate scores that are calculated as the following: for EE and DP scores the high scores represent high levels of burnout. For PA the high scores represent low levels of burnout (Maslach & Jackson, 1981). Empathy. The scores of empathy were assessed by Interpersonal Reactivity Index (IRI) scale. The IRI is a multidimensional scale that has 28 items rated on a 5-point Likert scale that ranges from 1 “Does not describe me well” to 5 “Describes me very well”. The measure comprised of four 7-item sub-scales. Only three subscales were used for the study. These subscales are Perspective Taking (PT) which represents the ability to conceive the psychological perspective of others. Empathic Concern (EC) measures the feelings of warmth and compassion and towards others. Personal Distress (PD) looks into "self-oriented" feelings of stress and apprehension as a reaction to the miserable conditions of others (Davis, 1980). Previous studies have reported high levels of validity and reliability of the scale (Davis, 1983; 1994; Fernández, Dufey, & Kramp, 2011). Emotional dissonance. The scores of emotional dissonance were measured using the subscale of the Frankfurt Emotion Work Scale. This scale has been extensively validated, and it is a five-item Likert scale ranging from 1 (never) to 5 (always). A sample item is: “How often in your job do you have to display emotions that do not agree with your true feelings?” (Zapf, Vogt, Seifert, Mertini, & Isic, 1999). The Cronbach alpha for the scale was .848 (Kundu, S., & Gaba, 2017). Self-compassion. The scores of self-compassion were measured using the Self-Compassion Scale (SCS)which consisted of 26 items rated on a 5-point Likert scale ranging from “Almost never” (1) to “Almost always” (5). The scale asks the participants on how often do they behave in the stated manner. An example statement is “I’m disapproving and judgmental about my own flaws and inadequacies”. The scale has six subscales: Self-Kindness, Self-Judgment, Common Humanity, Isolation, Mindfulness and Over-identified scales. The instrument has high inter-correlations between each of the six subscales, and it has an excellent internal consistency reliability and a good test-retest reliability. The coefficient alpha of the scale was .92 (Neff, 2003a). To ensure the maximum validity of the responses, a safety question was added to each questionnaire to ensure that the respondent is paying attention and not providing random answers. A sample item “Some people might provide random answers for this survey, which effects the research results very negatively. Just to make sure that you are not answering randomly, please select the answer number 1 (Never). Thank you”. For the purpose of the study, both Arabic and English versions were used in all the measures. The original language of the instruments was English. For the MBI-HSS the Arabic version was adopted from Hamaideh, (2011) who translated the entire instrument into Arabic and reported high internal consistency, the Cronbach’s alpha coefficient was .84 for the total scale, .91 for EE, .84 for DP and .88 for PA. For the current study, the internal consistency was .86. Emotional dissonance, IRI and self-compassion scales were translated into Arabic by a professional English/Arabic translator. Additionally, a backward translation was done by another professional English/Arabic translator, and the two versions were compared by the researcher. All the translated measures were accurate and correspondent with the original English scales. The translated forms reported high internal consistency which was calculated by the Cronbach’s alpha coefficient. The internal consistency was .86 for self-compassion, .76 for IRI and .70 for emotional dissonance. Design The study was comprised of one online Qualtrics-based survey that was sent to all the participants. Based on the study hypotheses the independent variable is burnout, and the dependent variables are self-compassion, empathy, emotional dissonance and type of work. Procedure Ethical approval for the study was acquired from the ethics committee at Lancaster University. Participants were initially told that the study was designed to investigate what pressures do workers in social and community development field face, and how do they feel about their work, themselves, people they work with and others in general. The actual aim was hidden initially to ensure maximum genuine and unbiased answers. Information sheets included the study objectives, description of the measures and how much time each one takes, the confidentiality of the data, participation eligibility, the voluntary participation, and the researcher contact information. Consent forms were displayed on the online survey before the initiation of the measures. Additionally, debriefing forms were given to the participants following the completion of the survey. Debriefing forms stated the actual purpose of the study as well as the study design. The survey was completed within 20-30 minutes approximately. Analysis Pearson’s Correlation and regression analysis were conducted to examine the study’s hypotheses. Regression analysis was chosen according to the nature of the variables which were continuous variables. Additionally, the number of paid and voluntary work hours were included as covariates, since dividing the participants into two groups (volunteers and workers) was not possible because most of the participants were doing both voluntary and paid work at the same time. All statistical analyses were conducted using IBM SPSS Statistics software (Version 23).