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).
Facts May Care About Your Feelings: The Effects of Empirical and Anecdotal Evidence in the Perception of Climate Change
Climate change, communication, perception, emotion, evidence
Although the effects of humanmade climate change become ever more potent, the consensus gap between climate scientists and the public is as wide as ever. It is critical that climate change communication is improved to try and close this gap. There are several strategies that can be implemented, including using anecdotes alongside or instead of empirical evidence to elicit emotions. In this study, 74 members of the public completed a survey. Participants were randomly assigned to one of four conditions which dictated the type of evidence they received: no evidence, empirical evidence, anecdotal evidence, or both empirical and anecdotal evidence. Results suggest that, in general, there was no effect of evidence on participants’ perceptions of climate change. This result held even after controlling for worldview and ideology. These findings have implications for the theory of inserting emotion into climate change communication.
Participants and design There were 74 participants (26 male; 46 female; one non-binary; one preferred not to say). The mean age of the participants was 37.99 (SD = 16.93). Participants were recruited via advertising the study on the researcher’s social media accounts (Facebook and Instagram) using a standardised advertisement (see Appendix A) and through word of mouth. Participants were all members of the general public. The study manipulated two independent variables in a between-participants design: anecdotal evidence (without-anecdotal vs. with-anecdotal) and empirical evidence (without-empirical vs. with empirical), resulting in four conditions. Participants were randomly allocated to one of the four conditions, subject to the constraint of equal cell numbers. This study gained ethical approval from the Faculty of Science and Technology Research Ethics Committee. Participants and design There were 74 participants (26 male; 46 female; one non-binary; one preferred not to say). The mean age of the participants was 37.99 (SD = 16.93). Participants were recruited via advertising the study on the researcher’s social media accounts (Facebook and Instagram) using a standardised advertisement (see Appendix A) and through word of mouth. Participants were all members of the general public. The study manipulated two independent variables in a between-participants design: anecdotal evidence (without-anecdotal vs. with-anecdotal) and empirical evidence (without-empirical vs. with empirical), resulting in four conditions. Participants were randomly allocated to one of the four conditions, subject to the constraint of equal cell numbers. Evidence Passages Empirical Evidence The empirical evidence vignette included a statement explaining that human-induced carbon dioxide emissions and global average temperature have synchronously increased since pre-industrial times, accompanied with graphs demonstrating these upward trends. The vignette also highlighted the scientific consensus that humanmade climate change is occurring and will have adverse consequences. Finally, the vignette explained that these adverse consequences had already begun to materialise. The increase of extreme weather events was highlighted in a graph that showed the tripling of weather-related disasters between 1980 and 2010. Finally, the vignette finished with references for the information it contained (see Appendix B). Anecdotal Evidence The anecdotal evidence vignette contained information about Storms Dudley, Eunice and Franklin which all made landfall in Britain in quick succession in 2022. The storms were a weather-related event that some scientists have linked to climate change (Barrett, 2022); Specifically, the vignette included information about the storms’ destructiveness, such as the cost of the damage they caused, and the number of people killed. The destructiveness of the storms was highlighted with images of damage and flooding in Wells, Otley, and Brentwood, as well as an image from Blackpool demonstrating the height and power of the waves caused by the storms. The vignette included a stock image of a man standing in a flooded living room and a short passage outlining the experience of a fictitious character named Matt Johnson whose family home had been severely flooded as a result of the storms. The vignette concluded with a statement from climate scientist Robert Klein who argued that the impact of the storm was exacerbated by climate change, which generated “super storm” conditions. Finally, there was a reference to an article about the storms and their link to climate change (see Appendix C). Measures Table 1 contains an overview of the measures embedded in the questionnaire. For the full questionnaire, please refer to Appendix D. Disaster Belief The disaster belief measure measured predicted estimates of the frequency of weather-related disasters that will occur in the listed years. Participants were given an approximate frequency for 2019 from the International Disaster Database. The measure consisted of six items: 2030, 2040, 2050, 2060, 2070 and 2080. Participants responded by typing in their estimated number next to the relevant year. Harm Extent The harm extent measure consisted of questions concerning how much harm that participants think climate change will cause themselves, their family, their community, Britain, other countries, and future generations. There were six items, such as ‘How much do you think climate change will harm you?’, and ‘How much do you think climate change will harm people in Britain?’ Responses were rated from (1) ‘not at all’ to (4) ‘a great deal’. Harm Timing The harm timing measure consisted of questions concerning when participants thought climate change will cause harm to themselves, their family, their community, Britain, other countries, and future generations. There were only two items, ‘When do you think climate change will begin to harm Britain?’ and ‘When do you think climate change will begin to harm other countries?’. Responses were rated as (1) ‘Never’, (2) ‘100 years’; (3) ‘50 years’; (4) ‘25 years’; (5) ‘10 years’ and (6) ‘Right now’. CO2 Attributions The CO2 attributions measure measured how much participants think human carbon dioxide emissions contribute to events such as heatwaves, rising sea levels, flooding, and Storms Dudley, Eunice, and Franklin. There were six items, such as ‘CO2 contribution to the observed increase in atmospheric temperature during the last 130 years’, ‘CO2 contribution to the European heat wave in 2022 that killed over 5,000 people’, and ‘CO2 contribution to storms Dudley, Eunice, and Franklin in the UK (2022)’. These responses were gathered using a sliding scale from 0 to 100%. Intention The intention measure consisted of questions asking about participants’ pro-environmental intentions. There were seven items. Examples of items include ‘I will take part in an environmental event (e.g., Earth hour)’, ‘I will give money to a group that aims to protect the environment’, and ‘I will switch to products that are more environmentally friendly’. The response options were simply ‘Yes’ or ‘No’. Mitigation The mitigation measure consisted of questions asking about participants’ support for mitigating policies. There were five items. Example items include, ‘Signing an international treaty that requires Britain to cut its carbon dioxide emissions by 90% by 2050’, ‘Adding a surcharge to electrical bills to establish a fund to help make buildings more energy efficient and to teach British citizens how to reduce energy use’, and ‘Providing tax rebates for people who purchase energy-efficient vehicles or solar panels’. Responses were rated from (1) ‘Strongly Oppose’ to (4) ‘Strongly Support’. CO2 Adjustment The CO2 adjustment measure measures how much participants think Britain should adjust its CO2 emissions over the next 10 years. There was only one item: ‘How much should Britain adjust CO2 emissions during the next 10 years?’. Responses were rated from (1) ‘Not at all’ to (6) ‘Reduce by 50%’. Free-Market Support The free-market support measure consisted of questions asking about participants’ support for the free market. There were five items. Examples items include, ‘An economic system based on free-markets, unrestrained by government interference, automatically works best to meet human needs’ and ‘The preservation of the free-market system is more important than localized environmental concerns’. Two items, ‘Free and unregulated markets pose important threats to sustainable development’ and ‘The free-market system is likely to promote unsustainable consumption’, required reverse coding upon analysis. Table 1 Measures embedded within the questionnaire. The first column contains the name of the measures; the second column contains the instructions on how to respond to items in that measure; and the third column describes how answers to the items were coded. Measure Name Questions Coded Response Disaster belief Please provide an estimate of the frequency of weather-related disasters that will occur in each year (6 items). Participants used the keyboard to type in a number for each year. Harm extent The following items examine your thoughts about the extent of harm that will be caused by climate change (6 items). 4-point scale: (1) ‘Not at all’; (2) ‘A little’; (3) ‘A moderate amount’; (4) ‘A great deal’. Harm timing The following items examine your thoughts about when climate change will begin to cause harm (2 items). 6-point scale: (1) ‘Never’; (2) ‘100 years’; (3) ‘50 years’; (4) ‘25 years’; (5) ‘10 years’; (6) ‘Right now’. CO2 attribution For each of the following questions, please estimate the contribution from human CO2 emissions to cause each event. For example, 0% would mean humans are not at all responsible, whereas 100% would mean that human CO2 emissions are fully responsible Participants used the mouse to place their response on a sliding scale. The sliding scale contained the numbers, ‘0’, ‘10’, ‘20’, ‘30’, ‘40’, ‘50’, ‘60’, ‘70’, ‘80’, ‘90’, and ‘100’. Pro-environmental intentions Please indicate whether or not you will engage in the following actions (7 items). 0 = No 1 = Yes Mitigation How much do you support or oppose the following policies (five items). 4-point scale; (1) ‘Strongly Oppose’; (2) ‘Oppose’; (3) ‘Support’; (4) ‘Strongly Support’. CO2 adjustment How much should Britain adjust CO2 emissions during the next 10 years? 6-point scale; (1) ‘Not at all’; (2) ‘Reduce by 10%’; (3) ‘Reduce by 20%’; (4) ‘Reduce by 30%’; (5) ‘Reduce by 40%’; (6) ‘Reduce by 50%’. Free-market belief Please indicate how much you agree with each statement (5 items). 5-point scale: (1) ‘Strongly Disagree’; (2) ‘Disagree’; (3) ‘Neutral’; (4) ‘Agree’; (5) ‘Strongly Agree’. Demographic questions What is your age? Participants used the keyboard to type in a number. What is your gender? 1 = Male; 2 = Female; 3 = Non-binary; 4 = Other; 5 = Prefer Not to Say Procedure All participants completed a questionnaire assessing their belief in and concern about humanmade climate change and their mitigation beliefs. The questionnaire was administered online using Qualtrics survey software. Participants responded to the questionnaire by using either the mouse to select answers or the keyboard to type in numbers. At the beginning of the questionnaire, all participants received an information sheet about the aim of the study, the lack of risks associated with participating, and how participant information is stored. Participants were asked to indicate their informed consent. For the full participant information sheet and consent form, please refer to Appendix E. After participants gave their consent and continued onto the survey, they were asked their age and gender. They were then presented with evidence according to the condition they were assigned to. There were four conditions: no evidence, empirical evidence, anecdotal evidence, and both empirical and anecdotal evidence. After they had read one or both evidence passages, participants answered the disaster belief measure. Next, they answered the CO2 attribution measure. Then they answered the harm extent measure and the harm timing measure. After that was the intention measure, and then they answered the mitigation measure. In the final part of the questionnaire, they were asked how much Britain should cut its CO2 emissions over ten years, and then questions on their support for the free market. Participants were then asked demographic questions about their age and gender. Finally, the participants were given a debrief sheet (Appendix F).
This study gained ethical approval from the Faculty of Science and Technology Research Ethics Committee. Participants and design There were 74 participants (26 male; 46 female; one non-binary; one preferred not to say). The mean age of the participants was 37.99 (SD = 16.93). Participants were recruited via advertising the study on the researcher’s social media accounts (Facebook and Instagram) using a standardised advertisement (see Appendix A) and through word of mouth. Participants were all members of the general public. The study manipulated two independent variables in a between-participants design: anecdotal evidence (without-anecdotal vs. with-anecdotal) and empirical evidence (without-empirical vs. with empirical), resulting in four conditions. Participants were randomly allocated to one of the four conditions, subject to the constraint of equal cell numbers. Evidence Passages Empirical Evidence The empirical evidence vignette included a statement explaining that human-induced carbon dioxide emissions and global average temperature have synchronously increased since pre-industrial times, accompanied with graphs demonstrating these upward trends. The vignette also highlighted the scientific consensus that humanmade climate change is occurring and will have adverse consequences. Finally, the vignette explained that these adverse consequences had already begun to materialise. The increase of extreme weather events was highlighted in a graph that showed the tripling of weather-related disasters between 1980 and 2010. Finally, the vignette finished with references for the information it contained (see Appendix B). Anecdotal Evidence The anecdotal evidence vignette contained information about Storms Dudley, Eunice and Franklin which all made landfall in Britain in quick succession in 2022. The storms were a weather-related event that some scientists have linked to climate change (Barrett, 2022); Specifically, the vignette included information about the storms’ destructiveness, such as the cost of the damage they caused, and the number of people killed. The destructiveness of the storms was highlighted with images of damage and flooding in Wells, Otley, and Brentwood, as well as an image from Blackpool demonstrating the height and power of the waves caused by the storms. The vignette included a stock image of a man standing in a flooded living room and a short passage outlining the experience of a fictitious character named Matt Johnson whose family home had been severely flooded as a result of the storms. The vignette concluded with a statement from climate scientist Robert Klein who argued that the impact of the storm was exacerbated by climate change, which generated “super storm” conditions. Finally, there was a reference to an article about the storms and their link to climate change (see Appendix C). Measures Table 1 contains an overview of the measures embedded in the questionnaire. For the full questionnaire, please refer to Appendix D. Disaster Belief The disaster belief measure measured predicted estimates of the frequency of weather-related disasters that will occur in the listed years. Participants were given an approximate frequency for 2019 from the International Disaster Database. The measure consisted of six items: 2030, 2040, 2050, 2060, 2070 and 2080. Participants responded by typing in their estimated number next to the relevant year. Harm Extent The harm extent measure consisted of questions concerning how much harm that participants think climate change will cause themselves, their family, their community, Britain, other countries, and future generations. There were six items, such as ‘How much do you think climate change will harm you?’, and ‘How much do you think climate change will harm people in Britain?’ Responses were rated from (1) ‘not at all’ to (4) ‘a great deal’. Harm Timing The harm timing measure consisted of questions concerning when participants thought climate change will cause harm to themselves, their family, their community, Britain, other countries, and future generations. There were only two items, ‘When do you think climate change will begin to harm Britain?’ and ‘When do you think climate change will begin to harm other countries?’. Responses were rated as (1) ‘Never’, (2) ‘100 years’; (3) ‘50 years’; (4) ‘25 years’; (5) ‘10 years’ and (6) ‘Right now’. CO2 Attributions The CO2 attributions measure measured how much participants think human carbon dioxide emissions contribute to events such as heatwaves, rising sea levels, flooding, and Storms Dudley, Eunice, and Franklin. There were six items, such as ‘CO2 contribution to the observed increase in atmospheric temperature during the last 130 years’, ‘CO2 contribution to the European heat wave in 2022 that killed over 5,000 people’, and ‘CO2 contribution to storms Dudley, Eunice, and Franklin in the UK (2022)’. These responses were gathered using a sliding scale from 0 to 100%. Intention The intention measure consisted of questions asking about participants’ pro-environmental intentions. There were seven items. Examples of items include ‘I will take part in an environmental event (e.g., Earth hour)’, ‘I will give money to a group that aims to protect the environment’, and ‘I will switch to products that are more environmentally friendly’. The response options were simply ‘Yes’ or ‘No’. Mitigation The mitigation measure consisted of questions asking about participants’ support for mitigating policies. There were five items. Example items include, ‘Signing an international treaty that requires Britain to cut its carbon dioxide emissions by 90% by 2050’, ‘Adding a surcharge to electrical bills to establish a fund to help make buildings more energy efficient and to teach British citizens how to reduce energy use’, and ‘Providing tax rebates for people who purchase energy-efficient vehicles or solar panels’. Responses were rated from (1) ‘Strongly Oppose’ to (4) ‘Strongly Support’. CO2 Adjustment The CO2 adjustment measure measures how much participants think Britain should adjust its CO2 emissions over the next 10 years. There was only one item: ‘How much should Britain adjust CO2 emissions during the next 10 years?’. Responses were rated from (1) ‘Not at all’ to (6) ‘Reduce by 50%’. Free-Market Support The free-market support measure consisted of questions asking about participants’ support for the free market. There were five items. Examples items include, ‘An economic system based on free-markets, unrestrained by government interference, automatically works best to meet human needs’ and ‘The preservation of the free-market system is more important than localized environmental concerns’. Two items, ‘Free and unregulated markets pose important threats to sustainable development’ and ‘The free-market system is likely to promote unsustainable consumption’, required reverse coding upon analysis. Table 1 Measures embedded within the questionnaire. The first column contains the name of the measures; the second column contains the instructions on how to respond to items in that measure; and the third column describes how answers to the items were coded. Measure Name Questions Coded Response Disaster belief Please provide an estimate of the frequency of weather-related disasters that will occur in each year (6 items). Participants used the keyboard to type in a number for each year. Harm extent The following items examine your thoughts about the extent of harm that will be caused by climate change (6 items). 4-point scale: (1) ‘Not at all’; (2) ‘A little’; (3) ‘A moderate amount’; (4) ‘A great deal’. Harm timing The following items examine your thoughts about when climate change will begin to cause harm (2 items). 6-point scale: (1) ‘Never’; (2) ‘100 years’; (3) ‘50 years’; (4) ‘25 years’; (5) ‘10 years’; (6) ‘Right now’. CO2 attribution For each of the following questions, please estimate the contribution from human CO2 emissions to cause each event. For example, 0% would mean humans are not at all responsible, whereas 100% would mean that human CO2 emissions are fully responsible Participants used the mouse to place their response on a sliding scale. The sliding scale contained the numbers, ‘0’, ‘10’, ‘20’, ‘30’, ‘40’, ‘50’, ‘60’, ‘70’, ‘80’, ‘90’, and ‘100’. Pro-environmental intentions Please indicate whether or not you will engage in the following actions (7 items). 0 = No 1 = Yes Mitigation How much do you support or oppose the following policies (five items). 4-point scale; (1) ‘Strongly Oppose’; (2) ‘Oppose’; (3) ‘Support’; (4) ‘Strongly Support’. CO2 adjustment How much should Britain adjust CO2 emissions during the next 10 years? 6-point scale; (1) ‘Not at all’; (2) ‘Reduce by 10%’; (3) ‘Reduce by 20%’; (4) ‘Reduce by 30%’; (5) ‘Reduce by 40%’; (6) ‘Reduce by 50%’. Free-market belief Please indicate how much you agree with each statement (5 items). 5-point scale: (1) ‘Strongly Disagree’; (2) ‘Disagree’; (3) ‘Neutral’; (4) ‘Agree’; (5) ‘Strongly Agree’. Demographic questions What is your age? Participants used the keyboard to type in a number. What is your gender? 1 = Male; 2 = Female; 3 = Non-binary; 4 = Other; 5 = Prefer Not to Say Procedure All participants completed a questionnaire assessing their belief in and concern about humanmade climate change and their mitigation beliefs. The questionnaire was administered online using Qualtrics survey software. Participants responded to the questionnaire by using either the mouse to select answers or the keyboard to type in numbers. At the beginning of the questionnaire, all participants received an information sheet about the aim of the study, the lack of risks associated with participating, and how participant information is stored. Participants were asked to indicate their informed consent. For the full participant information sheet and consent form, please refer to Appendix E. After participants gave their consent and continued onto the survey, they were asked their age and gender. They were then presented with evidence according to the condition they were assigned to. There were four conditions: no evidence, empirical evidence, anecdotal evidence, and both empirical and anecdotal evidence. After they had read one or both evidence passages, participants answered the disaster belief measure. Next, they answered the CO2 attribution measure. Then they answered the harm extent measure and the harm timing measure. After that was the intention measure, and then they answered the mitigation measure. In the final part of the questionnaire, they were asked how much Britain should cut its CO2 emissions over ten years, and then questions on their support for the free market. Participants were then asked demographic questions about their age and gender. Finally, the participants were given a debrief sheet (Appendix F).
Farmer and Non-Farmer Attitudes towards Alternative Animal Products
farmers, plant-based alternatives, cultured products, COM-B Model, Transtheoretical Model
Farmers’ livelihoods and way of living could be argued to be under threat from the simultaneous rapid rise of plant-based products, development of cultured products, and our growing understanding of the detrimental impact of traditional animal agriculture. Little research has investigated farmers attitudes towards cultured and plant-based products. Furthermore, famers appear to have limited awareness of these animal product alternatives. This study presented 45 omnivorous farmers and 53 omnivorous non-farmers with information about plant-based burgers, cultured burgers, plant-based milk, and cultured milk. Product acceptance and COM-B facilitators and barriers were explored. Farmers were less accepting of all alternative products than non-farmers, suggesting that their vested interest in the continuation of traditional animal agriculture affected their attitudes towards alternative products. Closer inspection of farmer acceptance suggests that personal investment in animal agriculture also led to differences within farmers, with occupational farmers being less accepting of the products than the members of farming families. The findings are interpreted using the Transtheoretical Model to suggest that regarding the adoption of alternative products, occupational farmers appear to be in the rejection stage, whereas members of farming families appear to be in the contemplation stage. As occupational farmers had more negative attitudes towards the alternative products, they appear more likely to consider the alternatives a threat to their livelihood.
Participant Recruitment and Exclusions Participant recruitment followed a pre-registered plan (https://aspredicted.org/blind.php?x=QL3_H96). Between July and August 2022 two groups of participants were recruited: adults with experience of livestock farming (Farmers), and a comparison group of adults without experience of livestock farming (Non-Farmers). Farmers make up a very small percentage (0.2%) of the UK population (DEFA, 2021) so we included current farmers, retired farmers, farm workers, and members of farming families. Fifty-five livestock farmers predominately living in Gloucestershire were recruited using snowball sampling. Farmers that were known to the author were first contacted via telephone, social media, or visited in-person. Interested participants were provided with the URL link to the questionnaire, a brief description of the study, and a request to forward the information to other individuals in the farming community. Individuals without internet access received a paper copy of the questionnaire. Sixty-one non-farmers were recruited through snowball sampling in the same method as for farmers. As farmers are typically older males (DEFRA, 2019), we attempted to match the ages of the non farmers to the farmers and effort was taken to recruit female farmers and members of farming families. Our recruitment plan was to recruit a minimum of 40 participants per group. To qualify for the study, farmers and non-farmers had to be omnivores. A further 23 farmers and 10 non-farmers were recruited using Prolific by pre-screening for those in the ‘Agriculture, Food, and Natural Resources’ employment sector, the description of the study also encouraged participation among those with “experience of working with farmed animals.” A total of 130 participants consented to participate: 55 farmers, 61 non-farmers, and a further fourteen who were excluded as they did not reach the demographics section so could not be classified into a group. Following our preregistered exclusion criteria, 18 participants who reported dietary restrictions were excluded (10 Farmers and 8 Non-Farmers). The final sample consisted of 45 Farmers and 53 Non-Farmers. Design and Procedure A 2x4 mixed design was used, with Group as a between-subjects factor with two levels: Farmer and Non-Farmer, and Product type as a within-subjects factors with four levels: plant-based burgers, cultured beef burgers, plant-based milk, and cultured cow’s milk. Participants completed an online questionnaire on Qualtrics (Qualtrics, 2005) that “drew attention to existing and emerging food innovations and explored beliefs and attitudes towards these products “, see Appendix A. The questionnaire took approximately 15 minutes. Ethical Statement The study was approved by Lancaster University’s Department of Psychological Ethics Committee. Participation was anonymous and Farmers were not asked to disclose the name or location of their farm. All participants gave their informed consent before accessing the questionnaire. On completion of the questionnaire, participants were debriefed, reminded of their right to withdraw their data, and were thanked. Materials The questionnaire comprised of six sections: vignettes, product acceptance, facilitators and barriers to product acceptance, consumer behaviour, demographics, and farming information. Vignettes Participants were presented with a brief description of factory farming, including its prevalence in the UK and the negative consequence on farmed animals and the environment. See Appendix B for full vignette details and references. Factory farming was chosen as it is the main method of farming in the UK (FAIRR, 2016). Participants were then presented with brief descriptions of plant-based products and methods of creating cultured animal products. Product features were compared against traditional animal products, including the sensory qualities, nutritional content, animal involvement, and environmental impact. Using a similar table to Van Loo et al. (2020), participants were presented with a comparison of the relative environmental impact of a plant-based soya burger and a cultured beef burger compared to a factory farmed beef burger
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).
Film language affecting behaviour: A psycholinguistic approach
Films are a popular form of art and entertainment that enable people to enjoy a story through multiple stimuli perception and stimulation of emotions. Plenty are the film elements that impact the audience’s attitude towards the film, yet language style has rarely been taken in consideration for research. This study focused on examining whether there exists a relationship between the audience’s favouritism for films and the linguistic style present in them, predominantly concentrating on emotional factors of language in films. A dataset containing the widest public ratings of films was obtained from the Internet Movie Database platform and paired with respective transcribed film dialogues provided by OpenSubtitles.org. The corpora’s transcripts (n=88,573) were analysed using the Linguistic Inquiry and Word Count software and all the variables produced were then correlated with IMDb’s weighted film ratings. The project found that all types of emotions present in transcripts of film language were significantly, negatively associated with the IMDb rating outcomes, while the effect sizes were small. This finding suggests there might be an inclination for emotions to be felt in other areas of stimuli perception, rather than verbal language, when it comes to films. Additional exploratory analyses showed how other variables correlated with film rating scores and practical application of study findings within the advertising industry were identified.
Dataset The dataset used for the study is purely secondary and consists of transcribed film dialogues (N=88,573) complemented with each film’s respective Internet Movie Database (IMDb) rating, which at the time of collection had a minimum of 100 user ratings per film. IMDb is an online film rating platform where the wider audience must register for an account and is then able to rate and review the films they have watched. Registered IMDb members rate films on a 10-point scale, with 1 indicating “terrible” and 10 indicating “excellent” (Boyd et al., 2020). IMDb’s rating algorithms produce ratings that are weighted by metrics associated with users, rather than average ratings. Although the algorithms are unavailable to the public, IMDb’s rating system has shown consistency across all films because the weighted ratings constantly provide reliability by reducing the possibilities of a small group of users to take advantage of the rating system (IMDb, 2021). IMDb is one of the most popular and authoritative film rating websites, where the total ratings of a film are anonymous and voluntarily provided (Sawers, 2015). The transcribed film dialogues data was provided by OpenSubtitles.org and the corpora was previously organised and used in a study by Boyd et al. (2020); it was generally provided by the authors for the purpose of this project. OpenSubtitles.org is an online website that provides transcribed and translated captions of motion pictures, audio files and various other audio-visual files (OpenSubtitles.org, 2021). The corpora used by Boyd et al. (2020) contains purely English-language film subtitles, corresponding to films originally released in English, or foreign films whose dialogues have been translated to English. Boyd et al. (2020) combined the transcribed film dialogues provided by OpenSubtitles.org with the IMDb ratings, along with other IMDb categories such as film genre, year of release, country of production, et cetera. Almost 90% of the IMDb categories linked to the films’ ratings are irrelevant for the purpose of this project, thus solely the film ratings will be taken in consideration for analysis. Automated Textual Analysis Software (LIWC) To conduct the automated textual analysis, this research project will use the Linguistic Inquiry and Word Count (LIWC) tool; also called “Luke”. LIWC is a textual analysis program that measures the degree to which various dimensions of words are used in a text (Tausczik & Pennebaker, 2010). LIWC program has two central features – the processing component and the dictionaries. The processing feature takes a text file and analyses it word by word, comparing each word with the dictionary files, sorting the word out as, for example, verb or second person pronoun (Boyd, 2017). Once the program finishes running, it produces an output where all the LIWC categories used in the text are listed, as well as the rates and percentages that each category was used in the given text. The dictionaries are at the heart of the LIWC program and they identify the group of words that belong to each category (Pennebaker et al., 2015). When the program was being created, the authors aimed at developing measures to define emotions present in words, cognitive processes, signs of self-reflection, et cetera, and in order to assign a psychological component to words, human judges contributed in developing the categories LIWC possesses today (Boyd, 2017). Across approximately 80 dimensions (see Appendix A), LIWC analyses the text in relation to various parts of speech, thinking styles, social concerns and emotions (Pennebaker et al., 2001). For example, the “positive emotion” category contains words such as “love”, “happy” and “nice”, while the “cognitive processes” category comprises words like “examine”, “think” and “understand”. Over the years, LIWC has been able to uncover psychological patters and personalities purely from textual analysis; Petrie et al. (2008) used LIWC to investigate the Beatles’ lyrics and found out that it was possible to distinguish each songwriter’s unique language style, and also to discover whose Beatle’s style was predominant in collaboratively written songs. Researches have shown LIWC to be one of the most reliable automated textual analysis tools that is able to uncover and predict psychological implications residing in written sources, thus this study will employ this tool to test its hypothesis. Data Preparation and Analysis The initial corpora was subjected to cleaning procedures, where data which did not meet all inclusion criteria was removed from the dataset. The inclusion criteria consisted of film ratings having at least 100 user votes, transcribed dialogues having at least 100 words and corpora variables containing all data values. The cleared dataset (N=85,130) is going to be tested in the LIWC program, where each word within the transcripts will be counted and sorted among the LIWC dictionary categories it belongs to. For the main hypothesis, the program will analyse the dataset for LIWC variables that have been shown to be correlated with positive and negative evaluations in the past. This way, the quantified rates of positive and negative emotion words in each dialogue will be identified. Once the rates have been extracted, a bivariate Pearson’s correlation will be conducted to assess whether there exists a significant relationship between positive and negative emotion words in film dialogues and their IMDb ratings. Additionally, exploratory analyses will be run to search for significant relationships between the dataset variables and the film ratings, again by conducting Pearson’s correlation tests between the ratings and all LIWC variables produced.
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.
Gender identity, attitudes, and bystander intervention
Gender prejudice Feminist identity Feminist theory three partite model of violence.
Identifying as a feminist and demonstrating a commitment to feminist activism has suggested an increased likelihood of engaging in bystander interventions in sexist situations in women university students (Brinkman et al., 2015), and awareness about gender prejudices as a result of undertaking women studies and/or diversity courses seems to relate to an increased involvement in feminist activity (Stake & Hoffmann, 2001). Together with this, confrontational responses to prejudicial attitudes can be perceived as a means for decreasing stereotypic responding (Mallett, Ford & Woodzicka, 2016;; Czopp, & Monteith, 2003). For this research levels of exposure to feminist research and self- identification as feminist were examined to determine its effect on sexism levels, and the ability to identify sexism on given hostile and benevolent sexist scenarios. Likewise, the responses participants have given in the past when witnessing sexism was also recorded, and then analyzed to determine correlations between a confrontational response, exposure to feminism, and the strength of feminist identity participants self-identify with. Gender differences were also analysed. Results revealed that participants with high levels of exposure to feminist had significant lower levels of only benevolent sexism. Further analysis also suggests that those with exposure to feminist theory are significantly more likely to identify sexism in hostile sexist scenarios than are those with no exposure. Exposure to feminist theory also increases the likelihood to have a stronger feminist identity. Significant gender differences were also found. Application of these findings and recommendations for future research is further discussed.
Measurements Vignettes Exercise. The vignettes exercise presented participants with 15 scenarios, of which 5 were hostile sexism scenarios, 5 were benevolent sexism scenarios, and 5 were neutral scenarios. The participants were asked 3 questions after reading each vignette. First, they were asked if the scenario presented involved sexism, which was evaluated with a 5 point Likert scale from “strongly disagree” to “strongly disagree”. Secondly, the participants were asked to rate the seriousness of the event, with a 6 point Likert scale which rated from “not applicable”, “not at all serious” to “very serious”. The third question asked participants to pick the type of phenomena that best described the scenario from 8 different choices, which included “hostile or negative comments about women”, “reproduction of the idea that women are not complete without a significant other”, and “the scenario does not describe a situation that involves sexism”, among others that derived from Glick and Fiske ́s (1996) definitions of sexism. Examples for the vignettes (see Appendix A) were taken from Mallett, Ford, and Woodzicka (2016), McCarty, and Kelly (2015), Durán, Moya, & Megías, (2011), Kato et al. (2011), Expósito, Herrera, Moya, and Glick (2010), and Sibley and Wilson (2004). Experiences of Gender Prejudices Instrument. Past experiences of gender prejudice were measured using Brinkman et al’s (2015) Experience of Gender Prejudices Instrument. Participants were asked to identify the last time they were in a situation in which they witnessed a woman being the target of sexism (see Appendix B). They were asked to pick which scenario best described the type of sexism witnessed from 7 options that included “hostile or negative comments about women” and “reproduction of the idea that women are not complete without a significant other”. They were then asked how they reacted to the situation, and if they intervened what their motivation had been. The participant ́s reactions to the sexism situation were coded as either ́confrontational ́ or ́non-confrontational ́, and as ́not applicable ́ in two occasions. Responses “tried to help the victim”, “ignored the person/people”, “left the situation”, “responded indirectly, but in a way I hoped would end the situation”, “used a nonverbal gesture to express that I was offended (ex. rolled my eyes, gave them a dirty look, etc.)”, “said something to the instigator(s) to express my thoughts/feelings”, and “used a physical response to express my thoughts/feelings (ex. slap the instigator)” were classified as confrontational. Responses “ignored the person/people”, “left the situation”, and “nothing” were coded as non-confrontational. Where participants reported a confrontational response, their motivations to intervene were again sought. Participants were presented with a list of 8 options which included “wanted to do my duty as a man by being chivalrous / wanted to do my duty as a woman by being nice”, “wanted to help a person in distress”, “wanted to stop the sexist behaviour because is wrong”, and “other”. Their motivations were then coded as “feminist goal”, “non-feminist goal”, “neutral” and “other”. The Ambivalent Sexism Inventory (ASI). The Ambivalent Sexism Inventory (ASI; Glick & Fiske, 1996) is a measure of modern sexism in participants. It comprises 22 statements, such as “men are incomplete without women” and “women exaggerate problems they have at work”, which participants evaluate on a 5 point Linkert scale, from “disagree strongly” to “agree strongly” (see Appendix C). The mean of all 22 items was obtained, closer means to 5 equals higher levels of sexism. The ASI also measures two sub-scales, the mean of 11 items was used to generate a hostile sexism score and the mean the other 11 items generated a benevolent sexism score. Demographic Information. Demographic information was collected relating to each participant ́s gender, age, and year in University (see Appendix D). Participants were also asked to quantify the hours of exposure to teaching on gender-related topics during their undergraduate and/or postgraduate studies on the following scale, from 0 hours, to 1-10, 10-20, 20-40, 40-60 or 60(+). Participants were also asked if they self-identified as feminist or not, and the strength of their identification as feminist was measured on a 5 point Likert scale, from “I strongly identify as a feminist” to “I strongly do not identify as a feminist”. The Demographic Information Questionnaire also measured, on a 5 point Likert scale, the degree to which participants identified with feminist goals and the degree to which they agree that the transformation of gender relations is needed in order to achieve gender equality. Design The study adopted a survey design and the variables measured are as follow: Independent and participant variables: Gender, age, feminist identity, strength of feminist identity, feminist goal, sexism and exposure to feminist theory. Dependent variables: Bystander intervention, identification, and evaluation of different forms of sexism, ambivalent sexism scale. Procedures Ethical approval for this study was obtained from the Psychology department research ethics committee at Lancaster University on May 26th 2017. Once ethical approval was gained, the participants’ recruitment stage began. Participants answered an invitation to complete an online survey which was hosted on the Qualtrics platform (2017). First, participants read the Participant Information Sheet (see Appendix E), and then completed the consent form (Appendix F). Then, participants answered the Vignettes exercise, followed by the “Experiences of Gender Prejudice Instrument” (Brinkman et al., 2015), then they were asked to fill “The Ambivalent Sexism Inventory” (Glick & Fiske, 1996), to finish with the Demographic Information Questionnaire. After answering the participants were debriefed (Appendix G) through the same platform. Completion of the survey typically took 20-30 minutes. Results Section: Demographic information Table 1 shows the demographic data relating to the gender of the participants and identification as feminist; the category “rather not say” was excluded from all the analysis of the gender variable owing to nil response. From the total of participants, 56 self-identified as feminist (68.3%) and 26 said they did not self-identify as feminist (31.7%). Chi-square analysis revealed significant gender differences in self-identification as feminist X2(1,81)=4.858, p<.05, significantly more female 77.4% participants reported being feminist than did male 53.6% participants. Effect of exposure to feminist theory, effect of gender, and interactions The purpose of this study was to look the effect of exposure to feminist theory, the effect of gender, and the effect of the interaction between gender and exposure to feminist theory on the sexism levels of the participants, on recognition of sexist scenarios and on their responses to witnessing sexism in their lives. The effect of exposure to feminist theory to the strength of self-identification as feminist was also measured. Effect of exposure to feminist theory, effect of gender, and interactions on sexism levels Participants were asked to quantify in hours their exposure to feminist research/teaching, then their answers were coded as “exposure” and “no exposure” and results were compared. Sexism was measured with the Ambivalent Sexism Inventory (Glick & Fiske, 1996), which provides three measures; the ambivalent (or overall) sexism levels, benevolent sexism levels and the hostile sexism levels. The levels of sexism were calculated for each participant, higher numbers indicating higher levels of sexism.
Grasping Ability in Virtual Reality: Effects of Eating Disorders on Perceptions of Action Capabilities
Action Capability, Eating Disorder, Interoceptive Awareness
Knowledge of one’s body size is vital to be able to accurately judge an object’s size. For example, knowing the length of your arm is crucial to estimating the maximum distance reachable. Accurate perception of action capabilities is the result of a healthy mental body representation at a conscious and implicit level. This ability to use one’s mental body representation in action perception is assumed to be distorted in individuals with eating disorders (ED). However, unlike prior research, this study will be investigating both the effect of body image and schema distortion on action capabilities. Thus, this study will assess whether the ability to update one’s perception of their action capabilities in response to morphological changes is altered in individuals with EDs. The experiment had participants (N = 20) embody small (50% of hand size), normal, and large (150% of hand size) avatar hands (in virtual reality) and then estimate the maximum size of a box graspable. The size of the box, beginning as either large or small across all three conditions, was manipulated to observe haptic perception in participants. We found that individuals with ED showed similar estimates despite embodying different hand sizes alluding to their inability to successfully update their haptic perceptions. Low interoceptive awareness and body image disturbances were the root cause of this perceptional flaw in eating-disordered individuals. Treatment focused on improving the altered IA and implicit distortions in body schema could improve haptic perception in ED individuals.
A priori power analysis was conducted through the G*Power software (Faul et al., 2007) to determine the sample size required to achieve adequate power (N = 30). The required power (1- β) was set at .80 and the significance level (α) was set to .05. Based on Readman et al. (2021), who used the same methodology as this study, we anticipated a large effect size of 0.9. This was deduced as this study obtained a ηp2 of .49 with a sample of N =30. For the frequentist parameters defined, a sample size of N = 3 is required to achieve a power of .80 at an alpha of .05. EDs are also notoriously variable. Given that previous studies using similar methodologies have typically recruited between 20-30 participants (Readman et al., 2020; Lin et al., 2020), we elected to recruit 30 participants (15 per condition). However, this study was only able to recruit 23 participants in total. 22 participants from Lancaster and Lancaster University (seven males, 15 females) aged between 18-30 (Mage = 21.73, SDage = 1.98) participated in this study. Two participants were removed due to being extreme outliers resulting in the present dataset (N = 20; Mage = 21.65, SDage = 2.06). Amongst participants of this study, seven participants disclosed a diagnosis of ED. In accordance with the revised Edinburgh Handedness Inventory (R-EHI) classification system (Milenkovic & Dragovic, 2013), the majority of the participants (N = 19) were right-handed, with only one participant being left-handed. Borderline to high levels of anxiety, as measured through the Hospital Anxiety and Depression Scale (HADS; Stern, 2014), was observed in 16 participants, while seven participants showed similar levels of depression. Eating Disorder Inventory (EDI): Participants with ED were also asked to complete the EDI. It is a self-report questionnaire that can assess the presence and level (depending on the estimate) of AN, BN, and Binge Eating Disorder (BED) (Augestad and Flanders, 2002). It consists of 64 items, with eight subscales measuring dimensions such as drive of thinness, body dissatisfaction, perfectionism, interpersonal distrust, and IA (Garner, Olmstead, & Polivy, 1983; Vinai et al., 2016; Santangelo et al., 2022). Seven participants had ED while the remaining formed the healthy control group.​ Design This study includes variables in a 2 (Between factor: Group – Control vs. ED) x 3 (Within: Hand size – small vs. normal vs. large) factorial design. The dependent variable (DV) is the grasping ability, and the independent values are the groups involved and the hand size conditions. All participants of each group experienced all conditions of the hand size. The order of condition completion was randomised across participants through use of a Latin square method. Such counterbalancing allows for the control of confounding/extraneous variables and diminishes order and sequence effects, improving internal validity (Corriero, 2017). Stimuli and Apparatus Participants were seated an arm’s length away from the front of a standardized table. Unity 3D© Gaming Engine with the Leap motion Plugin was used to create a virtual environment in 3D VR colour. Participants were able to view this environment through an Oculus Rift CV1 Head Mounted Display (HMD). The HMD displayed the stereoscopic environment at 2,160 × 1,200 at 90 Hz split (Binstock, 2015). Head and hand movements were tracked in real-time by the HMD and the Leap motion hand-tracking sensor attached to the HMD. The HMD ensured that the participants’ perspective was updated in real-time. Hand movements were updated in accordance with the virtual hand that was mapped onto the participant’s natural hands. Leap Motion for Unity provided assets such as avatar hands based on actual human hands. The virtual environment was visible to the participants in a first-person perspective adjusted to their height. The VR display is comprised of a model room, with a table located in the middle. Upon this table were either two white dots (Calibration trials) or a white box (Test trails). Questionnaires Revised Edinburgh Handedness Inventory (R-EHI). Participants’ handedness was deduced using the R-EHI. The modified version of the inventory was used as it accounted for and improved the inconsistencies and validity compared to the past questionnaire (Milenkovic & Dragovic, 2013). Participants are estimated on handedness depending on their preferences of either hand for doing activities such as writing, drawing, throwing a ball, etc. Hospital Anxiety and Depression Scale (HADS). The HADS questionnaire was also provided to all participants to assess the presence of borderline or abnormal levels of anxiety and depression in them. It is a quick questionnaire consisting of seven questions each for anxiety and depression, with both being scored separately (Stern, 2014). Procedure Participation in this study took up to an hour of the participant’s time. It was conducted in the Whewell Building of Lancaster University. Participants were recruited partly through opportunity sampling, and advertisements. All participants received £5 for their contribution to this study. All participants were native English speakers, had normal or corrected vision, and had no motor difficulties. Participants provided informed consent through a consent form signed before the onset of the study. They were also provided a debrief sheet and were verbally debriefed at the end of the experiment. The methodology of this study mirrors that of Readman et al. (2021). The experiment was conducted in a virtual environment (VE) through a VR device. The inclusion of VR allows for controlled changes to grasping ability, with responses collected similar to how an individual would act in the real world (Normand et al., 2011). Moreover, the inclusion of VR enabled interactions with the morphologically altered virtual body in real-time, and in a similar physical environment through the immersive system built through the head-mounted displays (HMD) and motion sensors (Gan et al., 2021). Participants completed the R-EHI, EDI, and HADS questionnaires before beginning the experiment. Participants were asked to don the HMD and introduced to the virtual environment through a brief demonstration. They were given approximately 5 minutes to explore the environment, to familiarise themselves with the immersive VR experience and ensure no undue effects occur. Participants completed three experimental conditions: Normal hand size, constricted hand size (50% of their hand size), and extended hand size (150% of their hand size). Each condition consisted of calibration and test trials. Calibration trials. Participants were presented with the virtual table upon which two horizontally spaced dots were located. Using their dominant hand, participants were asked to touch the left-most dot with their left-most digit and then touch the right-most dot with the right-most digit of their dominant hand. This occurred for 30 trials to ensure that the participant has habituated to the virtual hand. Test trials. The participants were instructed to place their hands behind their backs, out of sight. The Leap Motion sensor was then temporarily paused to ensure that the virtual hands are not visible to the participants. On ensuring this position, participants were then presented with a block in the VE, that they had to envision they could grasp with their dominant hand from above. The size of the block was manipulated, making it either larger or smaller, with each alteration causing 1cm changes. The participant was asked to tell the researcher when the block reflects the maximum size that they would be able to grasp. The final size was saved before the participant was presented with another block. Grasping was defined to participants as the ability to place their thumb on one edge of the block and extend their hand over the surface of the block and place one of their fingers on the parallel edge of the block. This grasp was also demonstrated to participants. Participants completed four test trials; in two test trials, the block started small (0.03 cm) and was made larger. In the remaining two trials the block started large (0.20 cm) and was made smaller. This was done to omit the hysteresis effect, which would cause prior visual stimuli to influence later perception (Poltoratski & Tong, 2014). Therefore, four grasp-ability estimates were obtained for each experimental condition. This study received ethical approval from Lancaster University Psychology department. Data Analysis An Analysis of Variance (ANOVA) is a statistical model used to examine differences in means (Rucci & Tweney, 1980). The present dataset contains both between-subjects (group) and within-subjects (hand size) factors. Thus, a mixed ANOVA would allow us to compare these variables and the means of the groups they are cross classified with. This is a two-way analysis as there are two independent variables (group and hand size) but only one DV (grasping ability estimate). Analysis through ANOVA is appropriate for this dataset as the effect of both variables in this study can be studied on the response estimate (Field, 2009). This study aims to establish the effect of group and hand size on grasping ability (GA). Therefore, a mixed ANOVA would help us identify the significant effect of either factor on the GA estimate and examine their interaction effect. Results of the mixed ANOVA analysis would help assess whether individuals with ED do update to changes in morphology. Data Preparation The present dataset combined demographic, physicality, and questionnaires related (EDI, R-EHI, HADS) information and GA estimates across the hand size conditions (small vs normal vs large). GA estimate of each condition was further sub-categorized into whether the box started large or small with four trials each. Averages of these four trials for the small starting box and large starting box for each condition was taken forming the mean grasp-ability estimates (cm).
Hemispheric Lateralisation of Facial Emotion Processing: A Possible Explanation of Atypical Empathetic Responses in Children with Autism Spectrum Disorder
Hemispheric Lateralisation, Emotion Processing, Autism Spectrum Disorder, Empathy, Chimeric Face Task
Existing research suggests that children with autism are endowed with a significant delay in the lateralisation of facial emotion processing (Taylor et al., 2012), and that this delay is associated with some of the social and emotional based deficits that manifest within the disorder. The present study therefore aimed to ascertain the reliability of Taylor et al.’s (2012) findings by determining whether the strength of lateralisation for facial emotion processing differs between children with and without autism, while also determining whether this difference can explain atypical empathetic responses in children with autism. To explore these aims, an online version of the chimeric face task was administered to 11 neurotypical children and 5 children with a diagnosis of autism. The Child Empathy Quotient was completed by parents of all children, and The Autism Quotient – Children’s Version was completed by parents of children with autism. Results indicated that there was no significant difference in the strength of hemispheric lateralisation for facial emotion processing between children with and without autism, and that the strength of lateralisation did not predict a child’s level of empathy, nor did a child’s autism severity. Instead, levels of empathy were best predicted by an individual’s diagnostic status and age. The present study was therefore unable to support the finding of Taylor et al. (2012) or explain empathy deficits in the autistic population. However, the limitations identified in this study help to inform future research on the relationship between the lateralisation of facial emotion processing and empathy.
Participants Participants were recruited from mainstream primary schools, wrap around care settings and specialist educational provisions in the Lancashire area, as well as via social media. A total of 22 parents completed the required questionnaires on behalf of their children, out of which 17 parents arranged a date and time for their child to complete the chimeric face task. One child, who is non-verbal and has received a diagnosis of ASD had difficulty completing the task and selected responses impulsively without looking at, or taking sufficient time to consider, the facial stimuli and the emotion it depicted. For this reason, the chimeric face task was terminated prior to completion and the child’s data was not included in the analysis. The final sample of participants consisted of 16 children aged between 5- and 10-years-old, of which 5 had received a formal diagnosis of ASD (5 boys; Mage = 6.8, SDage = 1.48). One child with ASD had a comorbid diagnosis of hypermobility and sensory processing disorder. All children with ASD were reported to speak English at home, one child was left-hand dominant, and four children were right-hand dominant. The remaining participants were 11 typically developing children (6 girls, 5 boys; Mage = 7.0, SDage = 1.90), who had not been diagnosed with any neurodevelopmental disorders. One of these children was reported to speak Russian at home, however, is fluent in English. All children in the typically developing group were right-hand dominant. Design A two-factor between-subjects experimental design was employed to determine whether the strength of hemispheric lateralisation for facial emotion processing differs between children with and without a diagnosis of ASD. The independent variable for this research question was diagnostic status, a between-subject factor, with two groups; ASD and typically developing. Participants were assigned to one of these groups based on their diagnostic status, which was ascertained by their parent’s responses on the demographic questionnaire. The dependent variable for this research question was the strength of hemispheric lateralisation for facial emotion processing which was measured using the chimeric face task. A three-factor mixed-subjects predictive correlational design was employed to determine whether a child’s diagnostic status, and strength of hemispheric lateralisation for facial emotion processing can predict a child’s level of empathy. The predictor variables for this research question were diagnostic status, a between-subject factor (typically developing or ASD), and the strength of hemispheric lateralisation for facial emotion processing, a within-subject factor. The outcome variable for this design was empathy, a within-subject factor, measured by the Child Empathy Quotient. Measures Demographic Questionnaire Materials. The online demographic questionnaire (see Appendix A) was comprised of eight questions. Three of which required parents of the participants to input a response, these questions were used to determine the child’s age (in years), month of birth, and year of birth. The remaining questions were multiple choice, and therefore, required parents to select an answer out of 2-4 possible answer options. These questions acquired information including the child’s gender (male or female), dominant hand (left, right or don’t know/no preference), the language used in their home environment (English or other) and diagnostic status (formal diagnosis of ASD or no formal diagnosis of ASD). If the child did not speak English at home, then parents were required to input the language predominantly spoken. Parents who confirmed that their child had received a formal diagnosis of ASD were asked to input any comorbid diagnoses their child had received, so that they could be considered in the analysis. Parents who confirmed that their child had not received a diagnosis of ASD were asked if their child had received a diagnosis of any other neurodevelopmental disorders, this question was used for exclusionary purposes. Procedure. Completion of the questionnaire took approximately 2 minutes. Following completion of the questionnaire participants were excluded from the study and unable to proceed to the next stage if they did not meet the age criterion, or if they had not received a diagnosis of ASD but had received a diagnosis of another developmental disorder. The Child Empathy Quotient (Auyeung et al., 2009) Materials. The Child Empathy Quotient (EQ-Child) is a parent report questionnaire composed of 27 items (see Appendix B) used to measure a child’s level of empathy. This questionnaire was developed by Auyeung et al. (2009) using the adapted version of The Adult Empathy Quotient (Baron-Cohen & Wheelwright, 2004), individual items have therefore been modified and made applicable and relevant to children. The items therefore refer to behaviours, responses or difficulties commonly exhibited or experienced by children, e.g., ‘My child shows concern when others are upset’. Parents had to indicate the extent to which they agreed with each item by selecting one of the following options on a four-point Likert scale; ‘definitely agree’, ‘slightly agree’, ‘slightly disagree’, and ‘definitely disagree’. The EQ-Child has previously been completed by parents of neurotypical children, and children with ASD, aged between 4- and 11-years-old. The pilot study conducted by Auyeung et al. (2009) yielded findings indicative of a high-internal consistency and good test-retest reliability, and the patterns of results were consistent with those found in adult research (Baron-Cohen & Wheelwright, 2004). Procedure. All parents were required to complete the EQ-Child, which took approximately 5 minutes. The order the questionnaire items were presented in remained consistent between parents and parents were unable to proceed to the next part of the study before they had provided a response for all 27 items. Scoring. Parental responses on individual questionnaire items were converted into numerical points and summed together to calculate an empathy score for each child. For the following numbered items; 1, 4, 8, 10, 13, 14, 15, 16, 19, 21, 22, 23, 24, and 25, a response of ‘definitely agree’ equalled 2, ‘slightly agree’ equalled 1, and, ‘slightly disagree’ or ‘definitely disagree’ equalled 0. The remaining items were reverse coded. The maximal attainable empathy score was 54, the higher the score, the more empathetic a child is perceived to be by the adult completing the questionnaire. The scoring method applied in this study is consistent with the scoring method used, and detailed, in Auyeung et al. (2009). See Appendix B for the 27 items, and their corresponding item number. The Autism Spectrum Quotient – Children’s Version (Auyeung et al., 2008) Materials. The Autism Spectrum Quotient – Children’s Version (AQ-Child) developed by Auyeung et al. (2008) is a parent report questionnaire composed of 50 items (see Appendix C), used to quantitatively measure autistic traits in children aged between 4- and 11-years-old. The items in the AQ-Child are derived from the Autism Spectrum Quotient – Adult’s Version (Baron-Cohen et al., 2001) and the Autism Spectrum Quotient – Adolescent’s Version (Baron-Cohen et al., 2006), however, they have been revised and adapted to be pertinent to children. The items therefore refer to scenarios and behaviours that children are likely to have experienced or exhibited, e.g., ‘S/he would rather go to a library than a birthday party’. Parents indicated how strongly they agreed with each descriptive statement by selecting one of the following responses on a four-point Likert scale; ‘definitely agree’, ‘slightly agree’, ‘slightly disagree’ and ‘definitely disagree’. Previous studies have administered the AQ-Child to parents of children with ASD, aged between 5- and 11-years-old (Auyeung et al., 2008). Administration of the AQ-Child has been reported to have excellent test-retest reliability and a high alpha and reliability coefficient. Procedure: This questionnaire was only completed by the parents of children with a diagnosis of ASD, all of whom were unable to proceed to the next stage of the study until they had provided an answer for all 50 items. This questionnaire took approximately 5-10 minutes to complete. The order of items remained constant between parents. Scoring. For each child reported to have a diagnosis of ASD, a total AQ score was calculated. Total scores were calculated by converting responses on the four-point Likert scale into numerical scores and summing them together. For the following items 1, 3, 8, 10, 11, 14, 15, 17, 24, 25, 27, 28, 29, 30, 31, 32, 34, 36, 37, 38, 40, 44, 47, 48, 49 and 50, a response of ‘definitely agree’ equalled 0, ‘slightly agree’ equalled 1, ‘slightly disagree’ equalled 2, and ‘definitely disagree’ equalled 3. The remaining items were reverse scored. The higher the overall score, the greater number of autistic traits exhibited and endowed by the child. See Appendix C for the 50 items, and their corresponding item number. The Chimeric Face Task Materials. The chimeric face task is a widely used measure of the lateralisation of facial emotion processing. Chimeric faces are composite visual stimuli that are made by splitting two symmetrically averaged images of a face vertically down the middle and combining them together to depict a different emotional expression in each hemiface. The chimeric faces and the symmetrically averaged images used in this study derive from the work of Michael Burt (Burt & Perrett, 1997; Innes et al., 2016), and are supplied by Parker et al. (2021) via Gorilla Open Materials: https://gorilla.sc/openmaterials/104636. In the practice trail, two symmetrically averaged images of male faces and two chimeric faces were used, these faces depicted the emotions fear and surprise. A further 12 chimeric faces were used in the experimental trial, which depicted all possible combinations of the emotion’s happiness, sadness, anger and disgust. Four symmetrically averaged images of male faces depicting these emotions were also used. See Figure 2 for the stimuli used in the experimental trial. Figure 2. The Facial Stimuli used in the Experimental Trial of the Chimeric Face Task Note. The 16 facial stimuli presented to children during the experimental trial of the chimeric face task, including the four symmetrically averaged faces depicting the emotions happiness, sadness, anger and disgust, and the 14 possible combinations of these four symmetrically averaged faces. Adapted from “A leftward bias however you look at it: Revisiting the emotional chimeric face task as a tool for measuring emotional lateralisation” by B. R. Innes, D. M. Burt, Y. K. Birch, and M. Hausmann, 2016, Laterality: Asymmetries of Body, Brain and Cognition, 21(4-6), p. 649, supplied by “Assessing the reliability of an online behavioural laterality battery: A pre-registered study” by A. J. Parker, Z. V. Woodhead, P. A. Thompson, and D. V. Bishop, 2021, Laterality, 26. The participants used emotional emoticons to indicate the emotion they believed to be depicted by the facial stimuli. In the practice trial, two emoticons were used, which illustrated the emotions fear and surprise. In the experimental trial, a further four emoticons were used, which illustrated the emotions happiness, sadness, disgust and anger. The emoticons used were taken from Oleszkiewicz et al. (2017), as it was found that children aged between 4- and 8-years-old were able to accurately assign emotions to these emoticons. See Figure 3 for the emoticons used in the experimental trial. Figure 3.The Emoticon Stimuli used in the Experimental Trial of the Chimeric Face Task Note. The emoticon stimuli selected by the child participants to indicate which emotion they believed the facial stimuli to be depicting. The emotions depicted by the emoticons, from left to right, are; anger, disgust, happiness and sadness. Adapted from “Children can accurately recognize facial emotions from emoticons” by in A. Oleszkiewicz, T. Frackowiak, A. Sorokowska, and P. Sorokowski, 2017, Computers in Human Behavior, 76, p. 373. Procedure. The procedure used derives from Parker et al. (2021), however, it has been adapted accordingly for its use with children. The chimeric face task was administered remotely via Microsoft Teams, a video collaboration platform. The virtual meeting was only accessible by the participant and the researcher, via a unique uniform resource locator, meeting ID and passcode. The chimeric face task could be completed on a laptop, computer or electronic tablet, and participants were required to share their screen to allow for the delivery of verbal instructions. Children were accompanied by an adult family member who was asked to refrain from engaging in any verbal and non-verbal communication with their child during completion of the task. Prior to administration of instructions, participants completed an estimation of screen size. This involved placing a 8.56cm X 5.39cm card onto the screen and dragging a bar until the size of the card on the screen corresponded with the physical card possessed by the participant. This was to ensure that all instructions and stimuli were presented as the same size to all participants. Instructions were administered visually to the child participants, using visual-graphic symbols, example screens and visual stimuli taken from the study, to ensure that the child’s understanding of the task was not compounded by their language ability. The visual instructions were accompanied by verbal instructions, that omitted the use of vocabulary that would not typically be understood by children aged between 5- and 10-years-old. Following administration of the instructions, participants were familiarised to two symmetrically averaged faces depicting the emotions fear and surprise, and their corresponding emoticons, which would be used in the practice trial. During completion of the practice trial participants were exposed to each symmetrically averaged face and each chimeric face, twice, meaning they were exposed to a total of 8 stimuli. The practice trial was employed to acquaint the child to the procedure used in the experimental trial. Following the practice trial, participants were familiarised to the symmetrically averaged faces that comprised the chimeric faces used in the experimental trial, as well as their corresponding emoticons. These faces, and emoticons, depicted the emotions happiness, sadness, anger and disgust. Participants were verbally informed of the emotion depicted by stimuli and were instructed to click ‘next’ or indicate to their parent when they felt they had familiarised themselves with the stimuli presented. Participants were familiarised to the stimuli to ensure they knew which emotion each face and emoticon represented. The experimental trial was composed of four blocks. In each block the participants were exposed to the four symmetrically averaged faces, and the 14 chimeric faces, twice, meaning they were exposed to 32 stimuli per block, and 128 stimuli in total. Participants were exposed to the symmetrically averaged faces to assess their recognition of the emotion, and to the chimeric faces to determine the strength of their hemispheric lateralisation for facial emotion processing. Before being exposed to the stimuli participants were asked to fixate on a white cross in the middle of the screen for 1000ms to ensure the child was looking directly at the facial stimuli when it appeared. This was important as the facial stimuli was only presented for 400ms. Following the presentation of each facial stimulus the participants had 10400ms to provide a response before automatically advancing to the next screen. All participants were instructed to “decide how the face is feeling and click on/point to/touch the emoji that shows that feeling”. The instruction provided differed depending on whether the child was responding using an electronic mouse, touch screen device, or by pointing and having their parent select the response for them. The latter of which was used for children who did not have access to a touch screen device, and who were not yet able to independently control an electronic mouse. At three intervals during the chimeric face task, children were provided with the opportunity to take a break. During this break children received verbal praise and encouragement, the duration of the break was determined by the child. Administration of the chimeric face task took approximately 20-40 minutes. Scoring. A laterality index was calculated for each child, to determine their strength of lateralisation for facial emotion processing. The laterality index was calculated by calculating the number of times the participant selected the emoticon corresponding with the emotion depicted on the right and left side of the face. The following sum was then computed for each participant 100 X (No. of right hemiface responses – No. of left hemiface responses)/(No. of right hemispace responses + No. of left hemiface responses). Study Procedure Ethical approval was obtained from the Lancaster University Department of Psychology Ethics Committee. Consent was received from all schools who agreed to distribute the study information to parents. Parental consent was obtained on behalf of all child participants, and oral consent was sought from the child participants during the virtual meeting. The study was comprised of two parts, the first of which required parents to complete a series of questionnaires to provide a measure of the child’s demographic information, level of empathy, and autism severity. Parents were first presented with the demographic questionnaire to determine which additional questionnaires they were required to complete. If the parent’s responses on the demographic questionnaire indicated that their child had a diagnosis of ASD, then they were directed to, and required to complete, the EQ-Child and AQ-Child. If the parent’s response denoted that their child did not have a diagnosis of ASD they were only directed to, and required to complete, the EQ-Child. All questionnaires were completed on Gorilla (www.gorilla.sc), a cloud-based software platform for collecting data in the behavioural sciences (Anwyl-Irvine et al., 2020). All participants therefore completed the questionnaires remotely, on a personal electronic device. The questionnaires were compatible with a range of technological equipment, including a laptop, computer, electronic tablet and mobile phone. Following successful completion of the required questionnaires, parents received an email arranging a convenient date and time for their child to complete the second part of the study, which required their child to complete the chimeric face task. The data collected during completion of the chimeric face task was linked to the parental questionnaire responses via a unique participant ID code, which was allocated to parents following confirmation of participation. Following completion of the chimeric face task, a debrief sheet and certificate was sent to the parent’s email address.