The Decoy Effect on Choosing Branded and Non-Branded Alcohol-related Products
The decoy effect describes a phenomenon that the introduction of a third choice, usually an asymmetrically dominated one, would change the distribution of people’s preferences for the original two options. Monk et al. (2016) found a basic decoy effect on alcohol purchasing decisions. Extending this, the current study examined the impact of the decoy effect on alcohol-related purchasing decisions and whether the addition of brand names would further impact this. A total of 106 participants were asked to make decisions amongst four types of branded and unbranded drinks by completing an online questionnaire. They also completed the AUDIT, assessing problem drinking patterns, and a measure of trait effortful control. Results showed that the decoy appeared to affect alcoholic relative to non-alcoholic drinks, and affected branded products more than non-branded products. The results suggest that the decoy effect might affect alcohol-related purchasing decisions differently to non-alcoholic purchasing decisions, which might have managerial implications for marketers and health implications for hazardous alcohol consumptions.
All the stimuli were pictures of bottles presented with text descriptions including the number of bottles and the total prices. Participants viewed a total of 80 deals, with 40 alcoholic products and 40 non-alcoholic products. Half of the products were branded and half unbranded. With regards to branded stimuli, pictures of bottles similar to those presented in supermarkets were shown (see Figure 2), whilst unbranded ones used similar unbranded bottles in terms of colour and shape. This allowed the products to correspond with both the diversity of goods in real supermarket but also to avoid unnecessary brand association (e.g. red glass bottles always remind consumers of Coca-Cola; Underwood, 2003). In the control condition, participants were shown products with two options, one with less bottles but cheaper, and the other with a greater quantity of bottles but more expensive. As such, option 1 represented the competitor option, which was cost-effective, and option 2 represented the target option, which was moderately cost- effective. The order of cost-effective and moderate-cost effective products was randomised throughout the experiment. In comparison, the experimental conditions also included a decoy option, which presented a product that was the least cost-effective. Although the decoy option itself was unlikely to be selected, it was expected to result in a different distribution of selections from the output of the control group. The sequences of the choice A (cost-effective), B (moderate cost-effective), and the C (decoy) were set randomly. Alcohol Use Disorders Identification Test (AUDIT). This questionnaire was made up of 10-items concerning personal drinking habits, drinking frequency and amount (Saunders et al., 1993). On a scale of one to over 30, articipants responsed to the questions such as “How many units of alcohol do you drink on a typical day when you are drinking?” and a total AUDIT score was computed. The scores of each question were accumulated and coded. The output of the AUDIT test showed great reliability of this study, M = 15.09, SD = 4.60, Cronbach’s α = .79. It should be noted that although the figure for the AUDIT test was way above eight which was the hazardous cut-off, indicating a possible harmful alcohol use (Babor et al., 2001), this was in line with student’s drinking cultures in UK. Adult Temperament Questionnaire (ATQ). This questionnaire assessed self-reported effortful control (c.f., Evans & Rothbart, 2007) and comprised of 34-items, such as “When interrupted or distracted, I usually can easily shift my attention back to whatever I was doing before”. Participants were asked to answer the questions by selecting a 7-point Likert Scale (1 = extremely untrue, 7 = extremely true). Their responses were recorded and coded. A small amount of missing data (caused by unexpected errors on the web) was replaced by the mean of the sample on that specific item. The result of the ATQ test revealed internal consistency as well, M = 146.34, SD = 22.82, Cronbach’s α = .85. Design and Procedure This study conducted a 4 Stimuli (Beer, Cider, Orange Juice and Water) x 2 Brading (Branded vs unbranded) x 2 Selection (Cost-effectiveness vs. Moderate Cost-effectiveness) within-subjects research design, to examine the possible shifts of selections with the addition of the decoy. Participants were instructed to look at online supermarket choice sets and asked to make a choice out of two (control condition) of three product options (the experimental condition, with the decoy product added). At the beginning, they were asked to imagine that they were in a real supermarket, and they were told that their selections would be dependent on their own preferences. No other information was provided either in oral or on the screen in order to prevent demand characteristics. The main questionnaire had 80 questions, consisting of 80 trials of stimuli (i.e., 20 trials for beer, water, orange juice, and cider). Also 40 groups of bottles were branded and the other 40 were non-branded. The main questionnaire comprised four web pages, with 20 questions in each page and took approximately 30 minutes to complete. Participants were allowed to take short breaks when they finished one page of questions. There was no time limit for each of the questions as the pressure caused by time constraints has been found to affect one’s decision-making process (Dhar & Nowlis, 1999). Subsequently, participants completed a self-report measure of hazardous drinking behaviour (AUDIT) and the effortful control scale (ATQ). These questionnaires were completed at the end of the experiment to make sure the alcohol-related behaviours were not primed (Monk et al., 2016). At the end of the experiment, participants completed a manipulation check to ensure that they were able to accurately distinguish the cost-effectiveness and the quantity of the products set and that they fully understood the requirements of this study. They were then asked to report if they had consumed alcohol on the day of testing, as alcohol consumption has been shown to affect decision-making and may therefore affect the findings of the experiment (Steele & Josephs, 1990). Therefore, participants who had consumed alcohol before participating in the test were excluded when analysing the decoy effect (n = 8). Finally, participants were fully debriefed after they had finished the whole experiment, and were informed about the true aims and hypotheses of the study.
The Development of an Attentional Bias toward Body Size Stimuli: Performance on a Novel Stroop Task
Distorted perceptions of body size have been identified and well-documented in eating disordered (ED) and eating-restricted populations, however, less is known about the development of this distortion. Research has employed Stroop food- and body-word tasks to investigate attentional biases towards semantically-related words and found a significant Stroop effect to such stimuli in ED, and sub-clinical, cohorts. The Size Congruity Effect (SiCE) has confirmed the perception of inanimate object size, however such an effect has not yet been studied in regards to body size specifically. This study recruited a novel Stroop size task to measure the perception of conceptual body size versus physical object size in four developmental age groups (Child, Adolescent, Young Adult and Adult). The Body Satisfaction Questionnaire (BSQ-34) was also taken as a measure of body dissatisfaction in participants over the age of 18. Findings indicate that a significant attentional bias towards body size is present across all age groups, but is most prevalent in adolescent and young adult participants. These findings imply that cognitive interference towards body size stimuli is not only present in the typical population, but is also present in children from aged 7. Body dissatisfaction, measured using the BSQ-34, did not have a significant effect on Stroop interference scores, suggesting that dissatisfaction with one’s own body does not implicate perception of others body size. The findings contribute to the fields understanding of body size misperception throughout typical development, the results also infer that body size perception is special, and not processed in the same way as inanimate size.
Participants Eighty-eight participants (N = 88) were recruited to participate in this research. The participants (35 males, 53 females) were aged between 7 and 59 years (Mage = 23.38, SDage = 14.34). Participants were divided into one of four groups, dependent on their chronological age. Child group. Child participants (N = 24, 8 male and 16 female), aged between 7 and 11 years (Mage = 10.04, SDage = 1.23), were recruited from St Boniface RC Primary School, Salford. A minimum participation age of 7 years was enforced for this experiment as previous research has not identified a consistent Stroop effect with younger children (Comalli et al., 1962). Parental consent was obtained prior to the research and participant assent was obtained on the day of testing. Five participants required glasses to correct their eyesight and were permitted to wear these throughout the testing period. Five participants reported having a specific learning difficulty (SLD); three participants had dyslexia, one participant had dyspraxia, one participant had attention deficit disorder (ADD) and one participant had attention deficit hyperactivity disorder (ADHD). One participant was on the autism spectrum (ASD). All participants with additional needs were performing well in mainstream school and were therefore considered able to participate in this research. Twelve participants had white British or white Irish ethnicity. Three participants had white European ethnicity. Three participants had black African ethnicity. Three participants had mixed or multiple ethnicities. One participant had Chinese Asian ethnicity. One participant had Irish traveller ethnicity. Two participants spoke English as a second language, however both were fluent English speakers. Each child received a reward sticker for their participation. Adolescent group. Adolescent participants (N = 22, 9 males, 13 females), aged between 13 and 16 years (Mage = 14.73, SDage = 1.12), were recruited through opportunity sampling. Social media posts were used to advertise the study, as well as word of mouth. All participants were recruited from Greater Manchester. Parental consent was obtained prior to testing and participant assent was obtained on the day of testing. One participant was colour blind. Six participants required glasses to correct their eyesight and were permitted to wear these throughout the testing period. Four participants reported having a SLD; two participants had dyslexia, one participant had dyslexia and dyscalculia and one participant had dyslexia and ADHD. All participants with SLD’s were performing well in mainstream school and were therefore considered able to participate in the research. Eighteen participants had white British or white Irish ethnicity. Two participants had black African ethnicity. One participant had mixed or multiple ethnicities. One participant had British and Chinese ethnicity. Young Adult group. Young Adult participants (N = 22, 7 male and 15 female), aged between 22 and 33 years (Mage = 25.86, SDage = 2.34), were recruited through opportunity sampling. The researcher utilised social media, approached classmates in Lancaster Univeristy’s Psychology Department and workplace colleagues to participate in the research. All participants were recruited from the North West of England. Each participant provided their informed consent prior to the research. Six participants required glasses to correct their eyesight and were permitted to wear these throughout the testing period. Two participants reported having a SLD; one participant had dyslexia and one participant had ADD. Both participants reported after testing that they were able to complete the task with no additional difficulty as a result of their SLD. Fifteen participants had white British ethnicity. Five participants had white European ethnicity. One participant had white American ethnicity. One participant had mixed or multiple ethnicities. Three participants spoke English as a second language, however both were fluent English speakers. Adult group. Adult participants (N = 20, 11 male and 9 female), aged between 37 and 59 years (Mage = 45.75, SDage = 8.27), were recruited through opportunity sampling. Social media posts were used to advertise the study, as well as word of mouth. All participants were recruited from Greater Manchester. Each participant provided their informed consent prior to the research. Ten participants required glasses to correct their eyesight and were permitted to wear these throughout the testing period. One participant had dyslexia. This participant reported after testing that they were able to complete the task with no additional difficulty as a result of their SLD. Fourteen participants had white British ethnicity. Three participants had white European ethnicity. Two participants had black Caribbean ethnicity. One participant had mixed or multiple ethnicities. Three participants were removed from the data sample due to a high number of errors. The responses from 85 participants were subsequently included in the data analyses. This study received ethical approval from Lancaster University’s ethics committee on 1st May 2018. Materials Task. The novel Stroop task was created using Psychopy, an open source Python –based programme used to run psychological experiments (Peirce, 2007, 2009). In the task participants were presented with computer-generated images of female bodies. Each body was individually presented on the screen and remained there until the participant made their screen size selection. One hundred and eight images were presented in total; 54 in the congruent trial and the same 54 in the incongruent trial. Eighteen unique images were presented three times, each time the screen size of the image was varied in order to ensure all 18 images were presented in all 3 screen sizes. The 18 images consisted of three model types (See Figure 1) which were used to represent the polarities of body size (3 small body sizes, 3 large body sizes; see Figure 2). Figure 2. An image to show the body ‘models’ used in the experiment. Row 1 Left – Right: Model 1, Model 2, Model 3, Model 4. Row 2 Left – Right: Model 5, Model 6, Model 7, Model 8. The first testing phase of the Stroop task consisted of the individual presentation of 54 stimuli, these stimuli were presented with congruent screen and body sizes; all stimuli presented with a small screen size (10 x 4cm, 11 x 4.4cm, 12 x 4.8cm) contained a small body size, all stimuli presented with a large screen size (21 x 8.4cm, 22 x 8.8cm, 23 x 9.2cm) also contained a large body size. The second testing phase of the Stroop task consisted of the individual presentation of the same 54 stimuli as the first phase. These stimuli were presented with incongruent screen and body sizes; all stimuli presented with small screen size contained large body size, all stimuli presented with large screen size contained a small body size. See Appendix A for screenshots of the Stroop task, demonstrating the congruent and incongruent presentation of the stimuli as described here. The order of stimulus presentation was pseudo-randomised within Psychopy, so that each individual image was presented only once per participant. Randomising the order of stimulus presentation assured that participants were not subjected to order effects (Shaughnessy, Zechmeister, & Zechmeister, 2006). Participants were instructed to determine the screen size of each stimuli and respond as quickly and accurately as possible using the keyboard keys indicated to them in the instruction phase. The relevant keyboard keys (A and L) were indicated with white stickers on the external keyboard. Key allocations (e.g. A = Small, L = Big) were also visible on screen throughout the task, see Appendix A for screenshots of the task. Participant response times were recorded within Psychopy and exported to Microsoft Excel. The task was presented on a Toshiba Satellite Pro laptop computer with a 15.6-inch HD non-reflective display with a 16:9 ratio and LED backlighting. Body stimuli. Eighteen images of computer generated semi-nude female bodies, ranging in body size and physical appearance, were used in the current study. These were created and donated to the researcher by Dr Martin Tovee, body size perception researcher, for the purpose of the current experiment. The bodies ranged in size from ‘emaciated’ to ‘overweight’, the variations in body size were visually distinguishable (see Figure 1), Eight ‘models’ were created, each with variations in physical appearance including hair colour and style, skin tone, facial features and eye colour (see Figure 2). All bodies were presented in a forward facing 0o pose, in order to eliminate visual preference or difficulties in comparing stimuli. Image size was manipulated as a factor of the experiment; to reflect ‘small’ screen size all images were presented at 10 x 4cm, 11 x 4.4cm and 12 x 4.8cm. To reflect ‘big’ screen size all images were presented at 21 x 8.4cm, 22 x 8.8cm and 23 x 9.2cm. These sizes were chosen as they created incremental differences in screen size that were visually distinguishable, as can be seen in Appendix B. Figure 2. An image to show the body size increments in the stimuli provided by Dr. Tovee. Model 3 is used to illustrate the size increments. Row 1 Left – Right: Size 1, Size 2, Size 3, Size 4, Size 5. Row 2 Left – Right: Size 6, Size 7, Size 8, Size 9, Size 10. For the purpose of the current experiment, sizes 1, 3, 4, 7, 8 and 10 were used as body size stimuli as these bodies had the largest size variation when visually scrutinised. Questionnaires. All participants were required to complete a demographic questionnaire, see Appendix C. The parent/guardian of a participant under the age of 16 was required to complete this questionnaire on behalf of the participant. This questionnaire was used to ascertain factors which may affect a participants ability to successfully complete the Stroop task. Participants over the age of 18 years were also required to complete the Body Shape Questionnaire (BSQ-34; Cooper, Taylor, Cooper & Fairburn, 1987). The BSQ-34 is a 34-item scale which measures participants feelings toward their own weight and body shape (Taylor, 1987). For example; ‘Have you been afraid that you might become fat (or fatter)?’ and ‘Has seeing your reflection (e.g. in a mirror or shop window) made you feel bad about your shape?’. Each item of this scale is scored on a six-point Likert scale, ranging from 1 (never) to 6 (always). BSQ-34 scores are totalled using Likert scale points; a score less than 80 indicates no concern with shape, a score between 80 and 110 points indicates a mild concern with shape, a score between 111 and 140 indicates moderate concern with shape and a score of 140 and above indicates a marked concern with shape (Cooper et al., 1987). The BSQ-34 was originally intended for use with female participants; the authors have since approved changes to items 9, 12 and 25 for use with male participants, this version was provided for male participants in the current experiment. The BSQ-34 was not considered suitable for participants under the age of 18 due to the explicit mention of clinically salient stimuli. The BSQ-34, as well as participants consent forms and demographic questionnaires, were provided to participants on Adobe Fill & Sign using an Apple Ipad and touchscreen pen. All participants indicated daily or weekly use of a touchscreen and/or computer. Design Variables. The dependent variable in this study was task response time, recorded by Psychopy in milliseconds. Mean response times (MeanRT) were calculated for the congruent and incongruent trials, per participant. An interference score (incongruent MeanRT minus congruent MeanRT) was also calculated for each participant. The dependent variables of MeanRT and Interference Score were both used in the current data analyses. The independent variables in the study were; AgeGroup and Congruency. AgeGroup. This was a between subjects factor. Participants were placed into one of four age groups, based solely on their chronological age. Congruency. This was a within subjects factor. All eighty-eight participants completed the same novel Stroop task, containing both congruent and incongruent trials. The order of trial presentation were randomised for each participant. Procedure Three months prior to testing, the parents/guardians of children in years five and six of St Boniface RC Primary School, Salford were contacted and given the opportunity for their child to participate in this study. The children of parents/guardians who returned the consent form and completed questionnaire were able to participate. The research was also advertised, via social media and word of mouth, to potential participants. The parents/guardians of participants under the age of 16 years, and participants over 16 years, were provided with an information letter, consent form and demographic questionnaire (See Appendices C, D and E).. Those who responded with a complete consent form and questionnaire participated in the research. Participants were individually invited to complete the procedure in a small quiet room. All participants were seated at a desk in front of the testing laptop and an external keyboard, see Figure 3 for the testing set-up. Participant consent, and child assent, was ascertained once the participants were seated. All participants were encouraged to ask any questions they had and child participants were reminded that they could return to their class at any time, without providing a reason. Once the preliminary period was completed participants were then asked to complete the computerised Stroop task. The task was visible on the screen prior to each participant entering the room. Participants were aided through the initial instruction screens of the task and encouraged to stop and ask questions at this stage. The researcher read all instructions to participants under the age of 16, and to any participant who requested that the instructions be read to them. The task then contained two practice trials, in order to ensure that participants understood their role in the task. All participants were able to complete the two test trials without difficulty and were therefore permitted to complete the rest of the task. The researcher left the room and waited nearby for all participants over the age of 16 years, the researcher remained in the testing room for younger participants. Participants were informed that they should only take a break when they reached an instruction screen as their times were being recorded on all testing screens. Participants were asked to alert the researcher once they had completed all stages of the computer task and reached the end screen. Child participants were given an envelope containing a parental debrief and escorted back to their classroom. Young adult and adult participants were asked to complete the BSQ-34 (Cooper et al., 1987) using Abobe Fill & Sign on an Apple Ipad. The BSQ-34 was provided after the task as Davison and Wright (2002) reported that this method reduced demand characteristics in a similar study. Upon completion of the testing period all participants were thanked for their time and provided with a debrief sheet as well as help and information pertaining to eating disorder or body anxiety concerns. Child participants were rewarded with a sticker for completing the task. Please see Appendix F for the participant debrief. Each participants response times were recorded in an Excel document which was then encrypted and saved to the researchers password protected laptop. All data was also stored on an encrypted external hard-drive, this copy of the data will be securely destroyed upon completion of the data analyses. Figure 3. A photograph to show the testing set-up used in the current study. Note, participants were encouraged to adjust their seat height to remain at a ninety-degree angle to the screen. The testing set-up was replicated for all eighty-eight participants to ensure continuity.
The Effect of Ambient Temperature on Cognitive Processing
Ambient temperature Cognitive reflection Syllogistic reasoning Logistic mixed effects modelling.
Over recent decades, climate change has caused the world to get warmer and this trend is set to continue into the future. Relationships between increased temperature and changes in human behaviour, such as increased aggression, have been identified and it is therefore important to consider the impact it may have on other aspects of behaviour. At present, there are limited amounts of research on the effect of temperature on cognitive performance. Within the framework of dual-process theories of cognition and using a Cognitive Reflection Task (CRT) and a Syllogisms Task, the current report researches whether increased ambient temperature (artificially manipulated in a temperature lab) encourages the use of System 1 (i.e. fast, unconscious) processing as opposed to System 2 (i.e. slow, deliberate) processing. The paper asks whether increased temperature leads to more heuristic answers on the CRT and more belief bias on the Syllogisms task. We observed no effect of temperature on performance on the CRT or the Syllogisms task. Similarly, we observed no effect of ambient temperature on belief bias or confidence in answers to the Syllogisms task. However, an effect of ambient temperature was found on how many heuristic responses were given to the CRT, with those in the cold condition giving more heuristic answers than those in the hot condition. We conclude that these findings do not provide support for increased temperature impairing certain aspects of cognitive performance, but also explore unexpected results and discuss potential reasons for these
Participants 65 individuals participated in this research study. Three were excluded for not meeting the pre-decided eligibility criteria of being a native English speaker aged between 18 and 65. This left 62 participants, 19 male and 43 female (Mage = 25.29 SDage = 8.83). Prior to the study, 1.61% had attained a PhD, 9.68% a Master’s degree, 40.32% a Bachelor’s degree, 33.87% A-Levels, 3.23% GSCEs, 9.68% a Certificate or Diploma and 1.61% had no qualifications. All participants completed the whole study, and none indicated awareness of the true aims of the study, thus, following pre-agreed exclusion criteria all participants were retained for analysis. Materials Cognitive Reflection Task. To test participants’ cognitive reflection, a form of the CRT (Frederick, 2005) was utilised. The CRT consists of a series of problem solving questions, with four multiple choice answers. For example, the question, ‘A bat and a ball cost £1.10 in total. The bat costs £1.00 more than the ball. How much does the ball cost?’ is presented alongside the following four options; ‘10p’, ‘5p’, ‘15p’ and ‘90p’. In this case the gut instinct is usually to respond with ‘10p’ however this is incorrect, and the correct response is, ‘5p’. Frederick’s (2005) original version of the task only consisted of three items and has since been criticised for being too short; about 44% of participants who are given the task have previously seen the questions and this leads to the inflation of their scores on subsequent testing sessions (Stieger & Reips, 2016). Consequently, both Primi, Morsanyi, Chiesi, Donati and Hamilton (2016) and Travers, Rolison and Feeney (2016) have since developed longer versions of the tasks; Primi et al.’s (2016) consisted of 6 items, whilst Travers, Rolison and Feeney’s (2016) consisted of 8. The present study combined items from both papers, taking 6 critical items from Primi et al. (2016) and 4 items, used as fillers, (adapted) from Travers, Rolison and Feeney (2016). The filler questions are included to reduce the chance of participants identifying the aims of the study. These questions differ from the critical questions in that the most obvious answer is the correct one. See Table A1 for a full list of the items used in the CRT. Syllogisms Task. In order to test participants’ syllogistic reasoning 10 Syllogisms were presented to the participant. Six critical Syllogisms (where the answer was invalid) were taken from Morley, Evans and Handley (2004) and used in the present study. Half of these Syllogisms had believable conclusions, whilst half had unbelievable ones. The believable Syllogisms, concluded with a statement that was believable in the real world (e.g. ‘Some addictive things are not cigarettes’), but remained invalid given the two premises, whilst the unbelievable ones concluded with a statement that was both unbelievable in the real world (e.g. ‘Some millionaires are not rich people’), and illogical given the two premises. The task also consisted of four filler Syllogisms. Again, half of the filler items had believable conclusions and half had unbelievable conclusions, however all of the conclusions were valid. See Table A2 for a full list of the items used in the Syllogisms task. Procedure Participants were either recruited through the University’s recruitment portal (SONA), or through individual volunteer sampling. Each testing session was pre-designated as either a hot or cold session and each session consisted of multiple testing slots which were advertised to participants. Participants were unaware of this temperature manipulation and blindly signed up to a testing slot under the pretence of completing a study which investigated behaviour in decision making tasks. As varying numbers of participants signed up to each session, the researchers updated the pre-designated condition of each session accordingly, to ensure there were the same number of participants, 31, within each condition overall. The study was conducted in a temperature control lab at Lancaster University. This room contains a temperature control panel, which was used to set the ambient temperature of the room to either 16˚C in the cold condition, or 28˚C in the hot condition. A KTJ TA318 Thermometer (with precision of 0.1˚C) was used to record the exact temperature at which each participant completed the study. In the cold condition, the temperature ranged from 15.5˚C to 16.9˚C (M = 16.14) and in the hot condition the temperature ranged from 27.8˚C to 29.8˚C (M = 28.56). The room consisted of five workstations, separated by partitions, meaning it was possible to test up to five participants at once. Each participant completed the study independently at one of the workstations, which contained a computer monitor, keyboard and mouse, stood on an individual sized table. When participants arrived at the study, they were seated at an adjustable chair facing the computer, within easy reach of the keyboard and mouse. If participants commented on the temperature of the room, the researcher responded with short statements of agreement, such as ‘yes, it is isn’t it’, but did not elaborate further to ensure that researcher influence was kept to a minimum. Each participant was given time to read the information sheet and provide consent (both digitally presented). Participants then entered demographic information such as their age, nationality and education level. Following this, the main section of the study began, and participants completed both the CRT and the Syllogisms task along with two other short tasks administered on behalf of a separate researcher. These two other tasks were not part of this research study. As part of the Syllogisms task, participants were asked to rate how confident they were in their response to each item, on a sliding scale from 0 (completely unconfident) to 100 (extremely confident). The order in which all four tasks were presented was randomised and counterbalanced across participants to negate any potential order effects. Additionally, the order of items within a task was also randomised for the same reason. Participants were given 5 minutes to complete the CRT, as this is consistent with previous administrations of a CRT (e.g. Primi, et al., 2016) and 30 seconds to complete each of the items on the Syllogisms task. These time limits were utilised to encourage participants to keep focus and to mimic the kind of time pressure associated with examinations. After these tasks, participants were asked 3 debriefing questions (see Appendix B) to assess whether they had identified the aims of the study. Answers to these questions were reviewed independently by two members of the research team and if participants demonstrated a link between temperature and cognitive performance their data would have been removed from the analysis, as their results may have been influenced by their awareness. Both assessors agreed that there was no cause to remove any participant on this basis. Finally, participants provided information about how comfortable they felt in the lab, on a 6-point scale, and then also how hot or cold they feel on average, on a sliding scale from -50 (extremely cold) to +50 (extremely hot). This second measure was taken to account for individual differences, as many people generally feel warmer or colder for reasons such as illness or medical condition, and this may influence how hot or cold they felt in the lab. At the end of the study participants were offered the chance to enter a prize draw to win one of twelve £10 Amazon vouchers. This rumination method was chosen above the option of paying every participant, to mimic the uncertainty of reward which is common in many settings such as examinations. Pre-registration This project was verified and registered on the Open Science Framework on the 21st May 2018 (https://osf.io/p6879/). The present study deviated from the initial plans in the followings ways. Firstly, the initial plan to recruit 120 participants proved unachievable within the time constraints and therefore 62 participants were tested. Secondly, logistic mixed effects models were used for most analyses instead of linear mixed effects models. This was a consequence of reformatting the data to be able to take into account the random effect of items on each task, resulting in the dependent variable being binary. Thirdly, the random effect of items and participants were not always included. This was because models with and without these factors were compared and random factors were only included if they helped the model to better fit the variation in the data. Finally, the initial plan was to investigate the effect of mood as an exploratory factor. The data on mood was collected, however further investigation was not possible due to project constraints. Analyses Strategy The aim of this paper was to determine whether increased temperature impairs cognitive performance as measured by a CRT and Syllogisms task. To facilitate assessment of results, the data was analysed using R (R Core Team, 2017). The numerical variables used as predictors in analysis were then scaled using the ‘scale’ function from the ‘standardization’ package (Eager, 2017). To conduct the desired analysis, the data was transformed from wide to long format using the ‘gather’ function from the ‘tidyr’ package (Wickham & Henry, 2018). To assess whether the data collected supported the hypotheses and therefore the extent to which temperature condition predicted test performance, several logistic mixed effects (LME) models were computed, using the ‘glmer’ function from the ‘lme4’ package (Bates, Maechler, Bolker & Walker, 2015). This was the most appropriate method of analysis to use as both the dependent and key independent variables were binary and it allowed the random effects of participants’ individual differences, as well as the random effect of items within each task, to be taken into account, which is necessary in a repeated measures design. The models contained the fixed effects of condition (Hot vs. Cold), baseline temperature and comfort level and the interaction effects of condition with comfort level and with baseline temperature. They also included the random effects of participants and/or items, depending on which random factors (if any) were found to aid the model to fit the variation in data best. To evaluate whether the inclusion of the random effects was required in each model, comparisons were made between the Akaike Information Criterion (AIC) of the final model and identical models with (a) the random effects removed, (b) only the random effect of items, and (c) only the random effect of participants, see Table C1. When reporting logistic models, we give estimated coefficients (ß), standard errors (SE), z-values (z) and p-values (p) of predicting variables. We also report the conditional R2 value (R2_c) for each model; a ratio which gives the variance explained by the fixed and random effects as a proportion of the total variance explained by the fixed effects, random effects and residuals. This is calculated using the ‘r.squaredGLMM’ function of the ‘MuMIn’ package (Barton, 2018). Where significant effects are found, estimated log odds are transformed into odds ratios by exponentiating the coefficients, to aid the interpretation of the effect. Cognitive Reflection Task. To investigate whether there was a difference in performance on the CRT between individuals in the hot condition and individuals in the cold condition, the data was coded such that a correct answer was given the value of ‘1’ whilst incorrect answers were given the value of ‘0’. To address whether there was a difference in the number of heuristic responses given on the CRT, the data was recoded (‘1’ = Heuristic response, ‘0’ = Other response). Syllogisms Task. To investigate whether there was a difference in performance on the Syllogisms task between individuals in the hot condition and individuals in the cold condition, the data was coded such that a correct answer (‘Invalid’) to a critical item was given the value of ‘1’ whilst incorrect answers (‘Valid’) were given the value of ‘0’. In order to investigate whether participants in the hot condition showed more belief bias than those in the cold condition, we extracted the three invalid believable Syllogisms and the two valid unbelievable Syllogisms. The data was recoded such that when a ‘valid’ answer was given to an invalid but believable syllogism or when an ’invalid’ answer was given to a valid but unbelievable syllogism, responses were given a value of ‘1’, to signify belief bias. Other responses were given a value of ‘0’. To analyse the ratings of confidence in participants’ answers to the Syllogisms task a linear mixed effects models was used, as the dependent variable was continuous. Exploratory Analysis. Data collection was conducted during the summer months, partly whilst Britain was experiencing a period of unusually hot weather. It is therefore possible that participants may not have been fully affected by the temperature manipulation. For example, those in the cold condition may have still suffered the negative effects of heat as a result of spending time prior to the study, outside in the heat. To address this, actual environmental temperature at a local weather station, for the times of participation were taken from ‘WeatherOnline.co.uk’ and added to the data set. The LME models included the outside temperature along with condition and the interaction between outside temperature and temperature condition as the fixed factors, and the random effects of items and participants.
The effect of different question types during shared book reading on children’s narrative comprehension
This study investigated the effect of different question types on narrative comprehension in young children. Forty one five year olds participated in this study. One group (N=14) received three sessions of shared storybook reading in which they practised answering questions about literal information in the story, during the course of the storybook reading. A second group (N=13) practiced answering questions about information that had to be inferred. A third group of controls (N=14), did not receive any intervention. All groups completed two comprehension assessments before and after the intervention: one was a measure of general listening comprehension, the other included measures of both literal and inferential comprehension. Children’s engagement during the storybook reading was also assessed. Contrary to predictions, neither intervention benefitted post-test comprehension significantly. In addition engagement levels did not change over the course of the study. However, a consistent pattern was found for each comprehension measure: the group who received practice with answering inferential questions made the greatest gains. Implications for early literacy experiences are discussed.
Design The study was an intervention design with three phases: a pre-test, training phase and post-test. There were three groups: two experimental groups who participated in all phases and a control group who only completed the pre and post tests. The design is shown in Table One. In the pre and post test sessions, participants completed a general measure of listening comprehension (adapted from the Neale Analysis of Reading Ability II, Neale, 1997) and a bespoke measure of listening comprehension with questions to tap literal and inferential comprehension. Participants were assigned to groups on the basis of their scores in the pre-test so that the three groups (two intervention and one control) did not differ in their performance on these measures (see Table Five). Children in the intervention conditions listened to three stories in separate sessions and either received practice at answering literal or inferential questions throughout the stories. In the post test all children were again assessed on alternate forms of the same measures used in the pre-test. Table 1. Intervention design used. Group Pre Test 1 Training 2 3 Post test Control General + Bespoke Listening Comprehension. x x x General + Bespoke Listening Comprehension. Literal General + Bespoke Listening Comprehension. Literal Literal Literal General + Bespoke Listening Comprehension. Inferential General + Bespoke Listening Comprehension. Inferential Inferential Inferential General + Bespoke Listening Comprehension. Materials: Pre and Post test. General Measure of Listening Comprehension. The following stories taken from the Neale Analysis of Reading Ability (NARA, Neale, 1997) were read to each participant in either the pre or post test: Toys, Tree house, Lost and Found, Road Safety. Toys or Lost and Found were used as practice tasks at the beginning of the pre/post test to help develop rapport. The stories were chosen so that the level of difficulty was consistent pre and post test. Comprehension questions that went with each story were asked at the end of the story to obtain the general measure of listening comprehension score. Table Two shows an example of a story and some of the questions given. Table 2. Example of general listening comprehension story used. General Comprehension Example Sample of Questions asked My friend and I made a tree house. We like to hide in it. We climb up the rope and pull it up after us. Then no-one knows where we are. We play space-ships. At tea time we slide down fast and we are always first for tea. What would you say was the best name for that story? Who built the tree house? How did the children always manage to be first for tea? Bespoke Measure of Listening Comprehension. The stories used in this study were a series of books about a dog named ‘Harry’ written by Gene Zion. These stories were chosen as they were first published between 1956 and 1965 and so were suitable for this age group but the children were not likely to be familiar with them. The pictures from the stories were scanned then printed on A4 sheets and laminated to make a set of wordless picture books. The original text was retained for each story, however, small sections of some of the stories were omitted to try and keep each story the same length. Two different types of questions were used in the bespoke measure of listening comprehension: literal and inferential questions. In the pre and post tests each child received eight literal questions and eight inferential questions after each story reading. The literal questions required the participants to recall facts from the text. The inferential questions tapped children’s ability to make inferences about information that was not stated explicitly in the text. These questions were designed to address: causality (why an event happened), emotions (how a character was feeling) and future events (what might happen next in the story). The Inferential questions in the pre and post test, however, consisted of four emotion and four causality questions as prediction questions could not be used at the end of the story. Table Three gives examples of literal and inferential questions used. Table 3. Examples of literal and inferential questions used. Extract Question 1. Harry was a white dog with black spots who liked everything except having a bath. So one day when he heard the water running in the tub he took the scrubbing brush and buried it in the back garden. Literal: What did Harry bury in the back garden? Forced choice: the scrubbing brush/a sponge. Causal Inferential: Why do you think Harry buried the scrubbing brush in the back garden? Forced choice: Because the family told him to/Because he did not want a bath. 2. That night Harry slept in the dog house – again. Literal Question: Where was Harry made to sleep again? In the Kitchen/in the dog house. Emotion Inference Question: How do you think Harry felt about sleeping in the dog house? Forced choice: happy/sad. 3. (After a sequence of events that lead to Harry being covered in seaweed and thinking the hot dog man was calling his name.) Harry still thought the man was calling his name. He barked and jumped with joy. He jumped so much that suddenly… Literal Question: (before - he jumped so much…) What was the hot dog man really shouting? Hurry/Harry Prediction Inferential question*: What do you think happened next? Forced choice: Everyone ran away/ the seaweed fell off him. *Please note. These were only used during the intervention sessions. Materials: Intervention Three of the stories were used for the intervention sessions. Scripts were produced that incorporated the questions for the intervention sessions during the stories. In the inferential intervention group there were four of each question type: causal, emotion and prediction. The inferential and literal questions were always placed at the same point in the story. Procedure Phase One: Pre-test. Children in all groups completed the general listening comprehension measure and the bespoke measure of literal and inferential comprehension. Each child was tested individually in a quiet space away from the classroom. The pre-test session was audio and video recorded. The video recorder was set in front of the participant to capture their direction of eye gaze. The experimenter explained the task to the child and obtained verbal consent. In the pre-test the experimenter asked the child if they had heard any stories about Harry the dog while showing them the front cover. One child reported recognising the story, but could not remember any details. General Listening Comprehension Measure. Each participant was read two stories, the first acted as a practice task to help develop rapport. Immediately after each story the children were asked the comprehension questions for that story. If a child could not answer a question then the experimenter offered the correct response and moved onto the next question. If the child gave the incorrect answer then the experimenter did not highlight that this was incorrect but simply moved onto the next question. The decision to respond to answers in this way was based on the pilot of the procedure. This age group seemed to become easily disengaged if they supplied no answer on a number of occasions or incorrect answers and it was felt that this way of responding helped to maintain their confidence and interest in the task. Responses were scored as correct or incorrect. Acceptable answers were provided in the NARA manual. Bespoke Listening Comprehension Measure. After the assessment of general listening comprehension each child completed the bespoke listening comprehension task. The experimenter read out the story whilst the child followed the pictures in a wordless picture book version. At the end of the story sixteen questions were asked: 8 literal and 8 inferential, of which four were causal and four were emotion related. If the child could not answer a question or gave the wrong answer then s/he was offered a forced choice of two possible answers (examples in Table Three). One option was the correct target answer and one was incorrect. The forced choices were included in the pre/post test as they were also used during the intervention; however, answers based on a forced choice were not included in the analysis. In the pre and post-test if the child chose the correct response then the experimenter agreed with the child and moved onto the next question. If the child selected the incorrect option, the experimenter also continued with the next question. The decision was taken not to correct the child at this stage as if the child was still getting the answer incorrect despite assistance then giving them the correct answer may change the representation they had created of the story and also have an effect on their confidence as mentioned earlier. The forced choices were alternated so that the correct answer occurred equally in first and second positions across items. When scoring the responses if the child gave the correct answer unaided (i.e. without the forced choice option) then they were given one point. All other responses were scored zero. Phase two: Intervention (Intervention groups only). The intervention sessions took place the week after the selection phase, on three consecutive days. On each day, each child in the intervention groups was tested individually in a quiet space away from the classroom and the session was audio-recorded. Different stories were used in each session. As the stories were read to the participant they were asked questions (either literal or inferential depending on group assignment) about the story content. Children in the control group were not read to by the experimenter during this phase. Literal Questions Intervention Group. Children in this condition were read one story in each of the three intervention sessions and asked twelve questions that assessed their understanding of explicit details in the story, e.g., ‘What did the lady next door sing louder than?’ The questions were positioned throughout the text and related directly to information that had just been given in the story. If the children gave no response or an incorrect response they were offered the forced choice. If a child still gave an incorrect answer after being given the forced choices then the experimenter corrected them and offered the correct answer. This was to try and ensure that the children were building accurate representations as they listened to the stories. Inferential Questions Intervention Group. The same stories and question-response technique were used as outlined in the literal questions condition. Questions were also placed at the same position in the text, however, children in this condition were asked twelve inferential questions throughout each story that required them to think beyond the facts present in the text. In each story there were four causal inferential questions, e.g., ‘Why were Harry’s ears hurting?’ four prediction questions, e.g., ‘What do you think Harry did next?’ and four questions assessing understanding of the emotions of the characters. e.g., ‘How do you think Harry felt when the old lady told him to go away?’ Phase three: Post-test. This session took place between five and seven days after the final intervention session and followed the same format as the pre-test. Children in all three groups completed the general listening comprehension story and the bespoke listening comprehension story with literal and inferential questions asked at the end of the story. Measure of Engagement. The video recordings from the pre and post-test were analysed for the children’s level of engagement. This was only based on the child’s behaviour during the reading of the bespoke listening comprehension story. The coding scheme used for this analysis is shown in Table Four. A second rater scored 20% of the pre-test videos. There was 100% agreement between raters. Table 4. Coding scheme used to analyse level of engagement while listening to the bespoke story. Code Description of Behaviour 1 Limited Engagement. The child appears off-task and makes a large number of unrelated comments or is distracted and looking away for a large part of the story reading. 2 Engaged- Quiet. The child looks at the pictures and listens well throughout the story but does not make any independent comments. 3 Engaged – Interactive. The child looks at the pictures and listens well throughout the story. They also make independent comments relating the events in the story to their lives/elaborate on the text/ ask questions about the text. Group Assignment. Scores on the pre-test measures were used to assign the children to groups to ensure an equal range of scores in each. One-way Analysis of Variance was carried out on the general comprehension scores, literal and inferential scores. All F<1.0 and all p>0.1. In addition, where possible, an equal number of boys and girls were assigned to each group. Table Five shows the ages, number of boys and girls and pre-test scores for each group. Table 5. Distribution of gender, age and pre-test scores across groups. Variable Control Literal Inferential Gender Male Female 8 6 7 7 7 6 Age (years; months) 5;5 5;5 5;4 General Comprehension (proportion) 0.43 0.46 0.46 Bespoke Literal (max=8) 3.79 3.79 4.15 Bespoke Inferential (max=8) 5.0 4.50 4.77
The Effect of Positive and Negative Emotional States on the Price Sensitivity to Green Fast-Moving Consumer Goods in the UK
Psychology, behaviour, mood, pricing, green marketing, advertising
Consumers are growing increasingly aware about the environmental consequences of their daily purchases, creating a potentially lucrative space for agile brands to leverage sustainable or green fast-moving consumer good (FMCG) production and increase revenue and profit. However, a fuller exploitation of this growth is impeded by the high costs of offering greener FMCG’s, which are passed onto consumers via higher prices, leading to a preference for cheaper, non-green FMCG’s due to price sensitivity. The purpose of this study was to investigate the power of positive and negative emotional states in reducing this price sensitivity and thus, increasing green FMCG buying behaviour. To induce the two emotional states, conventionally happy and sad video stimuli were utilised, followed by a fictional product selection between green and non-green FMCG’s. The research involved two phases. Phase 1 applied a qualitative method in the form of two focus groups (total n = 10) to test and enhance the general research procedure, while gathering additional insights regarding the overall study subject. Phase 2 integrated the refined procedure into a quantitative questionnaire, which involved a sample for each emotional state and a third sample as a control (total n = 300). The results demonstrated that neither positive nor negative emotional states had an overall significant influence on FMCG product selection. The discussion of the results includes insights from Phase 1 and provides recommendations for brands. The study limitations and future research directions are also presented. The research was conducted for and funded by Astroten – a behavioural science consultancy in London.
Methods Overall Design In accordance with the research questions and hypotheses, the methodology tested the effect of positive and negative emotional states, which were induced by two online videos. Each video contained copyright-free footage, one depicting humorous scenes (positive state), and the other depicting sadness (negative state). The impact of the videos’ mood-inducement was primarily measured by the outcomes of a fictional product selection in which participants chose between a more expensive green FMCG and a less expensive non-green FMCG. Specific Design The project comprised two data collection and analysis phases. Phase 1 was a pilot qualitative study in which the overall design described above was discussed/tested and a series of additional questions regarding the relationship between green and non-green FMCG’s, emotional state (mood), and price were asked. Hence, the utility of Phase 1 was two-fold. First, it obtained richer insights afforded by the inherent advantage of qualitative research over quantitative research, through an in-depth exploration of participants’ perspectives around their decision-making regarding more expensive green FMCG’s. Second, this same advantage also yielded direct feedback from the participants on the general procedure so that it could be refined for Phase 2 – an online quantitative questionnaire. The questionnaire’s purpose was to achieve a stronger empirical basis for the effects of positive and negative emotional states. Phase 1: Pilot Qualitative Study The qualitative approach for Phase 1 consisted of focus groups. This method was selected because focus groups could facilitate the dynamic development of ideas between participants in contrast to individual in-depth interviews. In the latter, certain thoughts and perspectives could have failed to emerge, and to introduce these thoughts and perspectives, the researcher would risk posing leading questions, affecting data validity. In addition, given the study timeframe, focus groups were deemed to be more feasible in terms of data collection and analysis. Two focus groups (FG1 – approximately 70 minutes; FG2 – approximately 90 minutes) were conducted, each comprising 5 participants, split approximately by gender. The participants were post-graduate students from Lancaster University and were selected via opportunity sampling by posting the study details in a WhatsApp group chat for residents of the university’s Graduate College accommodations. Participants were each paid £15, and refreshments (snacks and beverages) were provided. Regarding the mood-inducing stimuli for Phase 1, the positive emotional state stimulus was a video containing clips of monkeys performing comic or happy actions (e.g., reading a newspaper or jumping around) (see Figure 1). The video was sourced from the Nature ALL (2020) channel on YouTube and was copyright-free (https://youtu.be/YQ4xwK7_rUY). The video also included a copyright-free comedic soundtrack, which effectively accompanied the content of the video. The duration of the video was edited down to one minute to ensure sufficient emotional impact, while preventing excessive exposure, which could have led to boredom and, logically, impacted the desired emotional state.
The Effect of Repetitive Headers on Acute Vestibular, Neural, Cognitive and Auditory Function in Football Players
Repetitive Sub-concussion, Football Heading, Neurocognitive Performance
The potential long-term consequences of repetitive sub-concussive head impacts, particularly from heading in football, have raised concerns about their association with neurodegenerative diseases in ex-professional football players. Recent research suggests that the accumulative nature of heading in football may lead to subtle brain changes, ultimately contributing to Chronic Traumatic Encephalopathy. This study aimed to investigate the immediate short-term effects of repeated headers in football on brain function. Seventeen football players completed a total of five high-force linear headers, one header every 2-minutes, imitating corner clearance headers, positioned 32 meters away from a ball launching machine. Four neurophysiological assessments were reported pre- and post-heading exercise: 1) vestibular evaluation for balance and sway changes, 2) neural assessment for resting brain activity changes, 3) cognitive tests measuring memory, attention and reaction time, 4) auditory assessment to assess any auditory processing changes. Paired-samples t-tests and Wilcoxon’s signed rank tests found no significant changes in pre-to-post heading exercise scores in any measurements. These findings warrant further investigation to determine whether the measures used were sensitive enough to detect subtle sub-concussive changes. Or, whether findings indicate a safe maximum number, specific to this type of header, has been established and this frequency does not pose any additional risks to footballers’ brain function. This study contributes to the ongoing research surrounding player safety in football and the immediate short-term effects of repetitive sub-concussive head impacts.
Method Participants A power analysis for Analysis of Variance was conducted to determine the sample size needed for this study with an 80% power level, which identified a minimum of 40 participants to achieve a medium effect size of f=0.25, α=.001. This study did not collect a full sample and therefore is underpowered, as there are only a total of 17 participants (mean age=20.35). Participants were either academy players from Burnley Football Club or Lancaster University’s football team and were required to be male aged between 18 and 30- years with no history of concussion within the last month. This ensured variability between participants was minimal and excluding individuals with a recent history of concussion will mitigate potential confounding effects and isolate acute sub-concussive effects of heading, meaning this study will better attribute any observed effects to the specific act of heading rather than to prior injuries. Prior to volunteering, participants gave full consent and completed a modified version of the Physical Activity Readiness Questionnaire (PAR-Q), which is designed to measure participants readiness to participate in exercise or physical activity. See Appendix A for questionnaire. The purpose of the PAR-Q was to identify any potential underlying health concerns that may become an issue when participating. Additionally, participants completed a demographic questionnaire which was used to collect information about characteristics of the sample and highlighted whether participants had recently been concussed. See Appendix B for questionnaire. If any health concerns emerged during the completion of either questionnaire, participants were unable to continue with participation. Materials Participants were tested using a test battery comprised from four elements detailed below. PROTXX. Vestibular sway was measured using a wearable inertial measurement unit (IMU), called PROTXX. IMU is an electronic device designed to measures and report an individual’s orientation, velocity and gravitational forces (Powell et al., 2022). The IMU includes an accelerometer with three axis, X, Y and Z. The X-axis measures front-back acceleration, Y- axis measures vertical acceleration, and Z-axis measures left-right acceleration. For each of the three axes (x, y and z), during each 60 second test, data is recorded at a sampling rate of 100Hz and generates a total of 12,000 samples. Samples are filtered, meaning PROTXX eliminates gravitational bias and drift by using a high pass filter with a .04Hz cut-off frequency. An overall average is taken for each axis to compute one score for each of the four measures, 1) eyes open, 2) eyes closed 3) a ratio of the first two scores and 4) average power. It is also thought that the average power, calculated by adding the eyes closed and eyes open scores together, and divided by 2, can support a more objective way to clinically diagnose concussion, rather than the single tests alone (Ralston et al., 2020). EEG Acquisition and Pre-Processing Neural function was measured using EEG, Enobio 8 5G wireless device (Neuroelectrics, Cambridge, MA, USA). Participants wore a Neoprene headband to collect data from the frontal part of the head only, as this is where participants will later be instructed to header the ball. The Neoprene headband offers predefined positions for seven channels (F7, AF8. Fp1, Fpz, Fp2, AF8. F8) used to record EEG data and is based on the 10-10 international system (Jurcak et al., 2007). Figure 1 is a schematic of electrode location sites on the forehead. Participants wore an ear clip on their right ear with reference DRL/CMS electrodes. EEG data was initially visualised at a sampling rate of 500Hz and the line noise filter at 50Hz. Sticktrode pre-gelled self-adhesive electrodes were used and placed under the gaps of the Neoprene headband.The Necbox, is the core of the Enobio system, and is wirelessly connected to a laptop using NIC software (Neuroelectrics, Barcelona, Spain). Before any analysis, recorded EEG signals were coded and pre-processed in EEGLAB, a MATLAB toolbox (See Appendix C for EEGLAB Script) (Mathworks, Natick, MA, USA) (Delorme & Makeig, 2004). This is to ensure that data is in a suitable format and quality for analysis is reliable. Signals were downsampled to 256Hz, re-referenced to the average of all channels, and two types of filtering were applied to EEG data, high-pass (0.1Hz) and low-pass (40Hz) filtering. Independent Component Analysis was then applied to the pre-processed EEG data using a threshold of 0.8. This step was added to identify and remove any eye blinks, heart and muscle artifacts with 80% certainty (Chang et al., 2020). Components that have a score between 0.8 and 1 for artifacts are flagged for potential rejection and removed from EEG data. Neural activity pre-and post-heading exercise were analysed using power spectral density analysis (PSD). PSD analysis is a method used to analyse frequency components present in a signal. To conduct a PSD analysis, this study used the code spectopo() function within EEGLAB. The average power of EEG frequency bands was calculated for each of the seven electrodes used in this study. The frequency bands were separated in the following way: theta (4-8Hz), alpha (8-12Hz), beta (12-30Hz) and gamma (30-40Hz) (Harris & Myers, 2023; Munia et al., 2017). ImPACT Quick Test ImPACT Quick Test measures different areas of cognitive function using five subtests that contribute to three overall composite scores used within this study’s analysis: Motor Speed, Memory, and Attention Tracker. The five subtests used to measure the participants cognitive abilities are: 1. Symbol Match – Reaction Time Subtest. The first subtest was a symbol match test which measured reaction time. Participants had to match a series of shapes with a specific number and the average time taken to complete all trials was recorded. (Figure 2a) 2. Symbol Match – Memory Subtest. This symbol match test also measured memory and asked participants to recall the number-symbol pairs and remember which symbol was matched up with which number. The resulting score is the percentage of correctly recalled number-symbol pairs across the trials. (Figure 2b) 3. Three Letter Memory – Speed Subtest. The participant is initially given three consonants. Participants are then given a computer-randomised 5x5 number grid and asked to count backwards from 25. The result is how long it takes the participant to count backwards from 25 to 1. This subtest provides a measure of speed, but also serves as an interference task for the next subtest. (Figure 2c) 4. Three Letter Memory – Memory Subtest. This subtest measures the participants memory and recall. It provided a measure of memory and tested how well the participants could recall the three consonants after completing the computer-randomised 5x5 number grid interference task. (Figure 2d) 5. Attention Tracker – Reaction Time and Attention Subtest. This subtest is comprised of three separate tasks and involves a circle that moves in the shape of a square, figure 8 and a sporadic/random pattern across the screen. The participant is asked to tap the circle when it changes from red to green at various points during its movement. This subtest provides results for reaction time and how fast the participant can react to the colour change and how well the participant can keep their attention sustained on the moving circle. (Figure 2e) Digits in Noise Test (DiN) The final testing measure used within this study was an online DiN test to measure participant’s auditory function. The DiN task is written in Javascript and hosted as a web- application on a Google Cloud Platform. Participants remained seated for this measure and listened to a British female voice who said three digits in a random order that are embedded into speech-shaped background noise (Smits et al., 2004). Stimuli was presented diotically in a quiet environment through supplied wired overhead SteelSeries 5Hv2 headphones. Signal- to-noise ratio (SNR) is a measure used to quantify strength of a desired signal relative to background noise level. A flexible approach called an adaptive 1-up, 1-down psychophysical method was employed. When a participant recalled the three digits correctly, SNR decreased, and when participants recalled the digits incorrectly, SNR increased. The DiN test began with a SNR of 0dB. As the test progressed, the changes in difficulty, known as step sizes, decreased from 5 to 2 dB after 3 reversals. Then after 3 more reversals, step sizes reduced even more to 0.5dB. A reversal refers to a change in direction, therefore the difficulty level is adjusted in the opposite direction. The test concluded after a total of 10 reversals and the final five SNR were recorded and an average was created, to calculate the participant’s speech in noise threshold. This threshold represents the level of background noise at which participants correctly identify the digits spoken to them. Football Heading Within this study, participants received headers by a ball launching machine (Ball Launcher Pro Trainer, Ball Launcher). Participants completed five high-force linear headers at 35 yards from the ball launching machine at a ball speed of 50mph, the speed of the ball is regarded as below the average corner kick for collegiate-level players, which helps reduce the likelihood of injury and discomfort to players (Elbin et al., 2015; Tierney et al., 2021). This exercise is designed to mimic heading during football matches, specifically a clearance header from a corner (Figure 3). This ball launcher allowed for each of the headers to be consistent when measuring the effects of heading in football. The football used in this study was size 5, inflated to the FA standards of 8.6-15.6 PSI (The Football Association, 2023). Procedure A chronological schematic representation of the experimental procedure has been provided below (Figure 4). Players at Burnley Football Club were contacted via their club’s representative and Lancaster University players were emailed directly. Upon arrival, participants were informed that the study will take around one hour to complete and asked to read the participant information sheet to ensure they fully understood the requirements before completing the consent, PAR-Q and demographic form. Participants height and weight was taken on the day, meaning that the demographic questionnaire will be filled in accurately. These forms were screened by the researcher(s) to ensure eligibility. Once completed, participants were first tested using PROTXX sensor. Participants were asked whether they experience any skin irritation or sensitivities due to prolonged adhesive contact, for example when using plasters. If there were no known adhesive-related reactions, PROTXX sensor was attached to the right mastoid using a disposable medical adhesive patch (figure 5). However, if participants did have adhesive-related reactions, PROTXX sensor was placed into a headband, and positioned in the same location (figure 6). Participants were instructed to stand still, in an upright relaxed position with feet hips width apart and arms by their side whilst maintaining a straight, fixed gaze, three meters away from a specific target. Participants were instructed not to talk, chew gum, turn their head, fidget or move while the test is in progress. A smartphone app (protxxclinic; Version 1.0 build 13), connects to PROTXX via Bluetooth to run the tests and collect data. Participants completed two 60 second trials; eyes open and eyes closed. The app is used to start the test and participants are made aware of an audible countdown. One researcher stood by the participant to ensure no apprehension of falling during the eyes closed trial. The app sounded a tone signifying the test was 10-seconds away from finishing. Participants were instructed not to move until tests are completed and researchers had informed them, they can relax. If any anomalous participant movement was observed during the testing, said test data was excluded from analysis. The second testing measure completed was EEG. Participants were seated for this measure and prior to setting up EEG, they were asked to wipe their foreheads with an alcohol wipe to reduce the impedance. Participants wore a Neoprene headband across their forehead with seven pre-gelled adhesive electrodes placed on bare skin located at each channel site and the reference channels were linked to their right ear (figure 7). Electrode placement was completed, then connected via Bluetooth to a desktop app. The researcher(s) instructed participants to blink rapidly several times to create distinct electrical patterns on EEG recordings. This procedure is known as artifact-inducing task and is used to verify the quality of EEG readings (Grosselin et al., 2019). Participants were asked to sit in a comfortable position with eyes closed and 5-minutes of resting state EEG activity was recorded. A quiet environment was used, with minimal foot traffic, to reduce background noise and lessened potential of any auditory artifacts. The third testing measure completed was ImPACT Quick Test. Participants remained seated for this measure and completed the assessment tool on an iPad in a quiet environment to remove distractions. The iPad was placed on a table in front of the participant who was instructed not to hold the iPad in their hands (Figure 8). The test was taken in one sitting and took participants between 5-7 minutes to complete. The final testing measure participants completed was DiN. This measure required participants to remain seated in the quiet environment and wear provided overhead- headphones, that were plugged into the iPad (Figure 9). Before the test began, some music played through the headphones and participants were asked to find a volume level that was comfortable for them and were instructed to not change once selected. Participants were informed that this measure will vary in difficulty, and to guess the digits if they were unable to identify them. There was an opportunity to have a practice trial at this measure, so participants were familiar with the task and response procedure before the measure began. Participants would input three digits that they heard or guessed on the iPad’s keypad displayed. Again, this test was to be completed in one sitting and took no more than 3- minutes to complete. After all baseline assessments were complete, participants moved on to the heading exercise, which was conducted in an indoor open space. The primary objective of this exercise was to execute five consecutive linear high-force headers within a timeframe of 10- minutes, giving participants 2-minutes rest between each header. Before commencing the heading exercise, participants received a briefing to prepare them. They were informed about their designated position, situated 35 yards away from the ball launching machine, replicating the distance of a typical corner kick in real-game scenarios. The ball would be launched at a velocity of 50mph from a ball launching machine, ensuring consistency. To optimise their heading technique, participants were encouraged to aim for frontal contact and direct the ball back in a linear trajectory towards the ball launching machine and were allowed to take a single step and execute a jump into the header (to replicate real-life situations). Additionally, a secondary researcher positioned further back from the participant was responsible for retrieving any missed headers, thereby sparing participants unnecessary energy expenditure. To familiarise participants with the dynamics and to help maximise their performance during this heading task, participants were acclimatised to the ball’s trajectory, observing several ball launches from the side-line and standing in their designed position before initiating any heading attempts. This also ensured that participants were comfortable with the ball speed. Participants immediately completed the test battery again to obtain their post-heading scores, which were compared to evaluate the effect of headers on various test battery components. To close the study, participants were given a debrief sheet, and given a further opportunity to ask questions or raise concerns. Statistical Analysis Data pre- and post-heading were evaluated using paired-samples t-tests. The specific data used to input into the analyses was the independent variable, the point at which participants completed the test battery, pre-post heading exercise. The dependent variables consisted of data collected from the different measures: PROTXX; using individual eyes open and closed condition sway power scores, in addition to ratio and average power of these conditions, EEG; PSD for the four frequency bands, (alpha, beta, theta and gamma) were averaged across each seven electrodes for each participant, ImPACT; overall composite scores for each cognitive domain (motor speed, memory and attention) and DIN; SNR thresholds. The paired-samples t-test is specifically designed to compare the means or averages of two related groups. These analyses test for immediate short-term effects that may occur after RSHI. Data was tested for normality using Shapiro-Wilks’ test (Shapiro & Wilk, 1965). This step is crucial to verify whether the data meets parametric assumption of a normal distribution before proceeding with further analyses. Analyses were performed using statistical software R Studio. See Appendix D for R Studio Script.
Niko Liu ,Anusha Sandeep, David Racovita
Excel.csv("Linear Heading Study Data.xlsx") r_file.R("Dissertation_Masters.R")
The Effect of Sleep on the Processing of Emotional False Memories
People often think they remember events and information that in fact never happened. In previous studies using the Deese-Roediger-McDermott (DRM) paradigm, participants viewed lists of semantically related words, and during testing were more likely to accept as seen words that were related to the lists but were actually unseen, indicating a false memory. Research suggests that sleep promotes this effect, as does the use of negatively valenced stimuli, although the effect of emotion is disputed. The current study investigated what effect emotion, in particular valence, has on false memory formation, and whether sleep promotes emotional false memories. Fifty participants were tested on their recognition performance using an emotional and neutral DRM paradigm after a 12-hour period of sleep or wake. As predicted, we found an increase in false recognition of negatively valenced lure words, as well as an overall effect of emotion, with emotional words leading to increased false recognition compared to neutral. We failed to replicate any sleep effect on performance accuracy of neutral or emotional memory, although the response time data indicates some effect of sleep on emotional memory performance. The quality of participants’ sleep and design of the current study are explored as possible explanations for this lack of a sleep effect. This study therefore indicates that emotion plays a significant role in the formation of false memories independent of sleep.
Negative and positive DRM word-lists and critical lures were taken from Brainerd, Holliday, Reyna, Yang, and Toglia (2010) who controlled for other properties that are thought to affect false memory formation, including concreteness, meaning and frequency of words (Roediger, Watson, McDermott, & Gallo, 2001). Neutral DRM lists and critical lures were taken from Stadler, Roediger, and McDermott (1999). Two separate lists were formed, one with negative and neutral words, and the other with positive and neutral words (see Appendix A for word-lists). Participants in both the positive and negative condition viewed the same five lists of neutral words, as well as ten negative or positive word-lists. Mean valence and arousal scores for word-lists and critical lures were taken from the Affective Norms for English Words (ANEW) (Bradley & Lang, 1999). Independent samples t-tests showed that positive words had significantly higher ratings of valence than negative t(11.41) = 7.42, p < .001, and neutral words, t(13) = 7.43, p < .001. Negative words had significantly lower ratings of valence than neutral words, t(13) = 2.31, p = .038. Furthermore, negative and positive word-lists did not significantly differ in terms of arousal, t(12.92) = 0.52, p = .613, however neutral words had significantly lower ratings of arousal than positive, t(13) = 2.67, p = .019, and negative words, t(13) = 4.87, p < .001. It was also important that word-lists were controlled in terms of frequency and BAS. Frequency scores were taken from the MRC Psycholinguistic Database (Coltheart, 1981). Independent samples t-tests showed no significant difference in frequency ratings between negative and positive word-lists, t(18) = 0.18, p = .816, positive and neutral word-lists, t(13) = .35, p = .735, and negative and neutral word-lists, t(13) = 0.50, p = .624. BAS ratings were taken from the University of South Florida Free Association Norms (Nelson, McEvoy & Schreiber, 1998). There was no significant difference in ratings of negative and positive words, t(18) = 4.92, p = .629, positive and neutral words, t(13) = 0.32, p = .757, and negative and neutral words, t(13) = 0.89, p = .391. (See Appendix B for mean ratings). For critical lures, independent samples t-tests showed that positive lure words had higher ratings of valence than negative lures, t(15.11) = 11.20, p < .001, and neutral lures, t(11) = 4.24, p = .001. Negative lures had significantly lower ratings of valence than neutral lures, t(11) = 3.62, p = .004. There was no reliable difference between ratings of arousal for negative and positive lures, t(18) = 0.22, p = .828, positive and neutral lures, t(11) = 1.08, p = .305, and negative and neutral lures, t(11) = 1.62, p = .134. There was no reliable difference between frequency ratings of negative and positive lures, t(18) = 1.14, p = .268, positive and neutral lures, t(13) = 0.55, p = .593, and negative and neutral lures, t(13) = 1.11, p = .287. (See Appendix B for mean ratings). During testing, participants viewed 60 words in total; two previously seen from each DRM list (total of 30), the critical lure associated with each list (total of 15), and an unrelated word for each list (total of 15). Unrelated words were taken from lure words of unused DRM lists, as well as from Kousta, Vinson, and Vigliocco (2009), who developed emotional and neutral word-lists using the ANEW database. Unrelated words were matched to DRM word-lists in terms of valence, resulting in five unrelated neutral words, ten unrelated negative words and ten unrelated positive words. All words were presented in Courier new bold, black font, lower case and in 18-point. Participants in the sleep condition were required to wear an actigraph sleep monitor to more accurately measure their time spent asleep and the number of awakenings. All participants were given a questionnaire before each session to collect data on sleep habits, caffeine and alcohol intake (see Appendix C), and those in the wake condition were instructed not to nap throughout the day. Procedure Participants were randomly allocated to either the wake or sleep group, with those in the wake group trained on word-lists at 9am and tested on the same day at 9pm. Those in the sleep group took part in the training session at 9pm, and were tested the following day at 9am. Participants were randomly allocated to the negative or positive stimuli condition. During the training session, participants were first asked to fill out a questionnaire to assess sleep habits and caffeine and alcohol intake. Participants were then required to sit approximately 60cm from the computer screen, and were presented with 15 lists of 12 words presented one word at a time in the centre of the screen. They were first presented with a fixation point for 500ms before the words from one list were presented for 1500ms each. After each list participants were presented with three maths problems to solve for 1000ms each as a distractor task, in order to prevent participants from rehearsing words they had seen. Maths problems were presented in a random order for each participant, and each problem was only presented once throughout the task. After the three maths problems were presented, the fixation cross reappeared and participants were given another list to remember. The order of word-lists was randomised, and the order in which each word in a list was presented was also randomised. Participants were then asked to return 12 hours later after a period of daytime wakefulness or overnight sleep. During the second session, participants first viewed a fixation cross for 500ms, and then the test words were presented to participants one at a time in the centre of the screen for 120ms. Participants were required to identify whether they thought they had seen the word in the previous session or not. They did this through the press of a key on the keypad, with a press of zero corresponding to an old word (previously seen), and one corresponding to a new word (previously unseen). The numbers zero and one on the keypad were labelled ‘old’ and ‘new’ respectively, to aid participants. Participants were not given a response deadline. Participants then saw the fixation point again 500ms after giving their response, before another word appeared on the screen. All words were presented in random order.
The Effect of Systematic Variance in Action Capabilities on Grasp Ability Perception.
Embodied perception Grasp ability Affordance perception Virtual Reality
The ecological approach to visual perception asserts that individuals perceive environments relative to the possibility of action within their environment. Hence, to successfully interact with one’s environment, individuals must be able to accurately perceive the extent over which actions can be performed, widely referred to as action boundaries. Furthermore, as the world in which we inhabit is continually changing and subsequently placing various constraints upon ones action boundaries, it is necessary for individuals to be able to update their perceived action boundaries to accommodate for such variance. While research has displayed that individuals can update their perceptions to accommodate for variance, what is unclear in these circumstances is which action boundary does the perceptual system calibrate to. This study investigated this by analysing the effect of systematic variance on perceived grasp ability in virtual reality. Participants provided estimates of grasp ability following motor experience grasping with either a small, normal, large or a varied size hand. In the variance condition, participants experienced the small hand 25% of the time, the normal hand 25% of the time, and the large hand 50% of the time. The results indicated that participants’ perception of grasp ability reflected the artificial manipulation such that grasp ability was largest in the large hand condition. In addition, regarding the variable condition participants took all visual information into consideration however erred on the side of caution. However, it may be that factors such as age and personality influenced the results.
Open Science Framework (OSF) This study has been pre-registered with the OSF; See https://osf.io/zkjdt/ for the main OSF project page. The following study deviated from the pre-registration in that data collection occurred for 12 days longer than initially intended as participant uptake was not as high as initially assumed it would be. Participants 30 Lancaster University Students (5 males and 25 females) aged between 18-26 (Mage = 21.07, SDage = 1.17), naïve to the purpose of this study, participated. All participants were recruited via opportunity sampling, utilising the Lancaster University Sona research participation system, advertisements and the researcher’s social network, and were paid £5 for their participation. Of these participants 29 were right-handed, and one was mixed-handed. The one mixed-handed participant elected to complete the study with their right hand, therefore, the following conclusions and data should be treated as all right-handed participants. In addition, all participants had normal or corrected-to-normal vision and had no known medical history of visual atypicalties, beyond being long or short-sighted, motoric or rheumatologic difficulties. All participants provided informed consent. Lancaster University Research Ethics Committee granted ethical approval for this study. Stimuli and apparatus A virtual environment was developed in Unity 3D© Gaming Engine with the Leap Motion plugin. The 3D VR colour display comprised a 3D model of a room in which a table was located in the centre. Upon this table were either two grey dots (in the calibration trials; See Panel A of Figure 2) or a grey block (block size manipulation trials; See Panel B Figure 2). The participant’s viewed the VR from a first-person perspective reflecting their natural eye-height. The environment was presented to participants through an Oculus Rift CV1 HMD, which displayed the stereoscopic reality at 2160×1200 at 90Hz split over both displays (Binstock, 2015). The movement of the head was tracked by the head mounted display (HMD) and updated in real-time as the participant looked around the environment. Furthermore, the location of the hand was tracked in real-time, using the Leap Motion hand-tracking sensor mounted on to the Oculus Rift CV1 HMD, and was mapped onto the virtual hand thereby causing the virtual hand to move in correspondence with the natural hand. Procedure Each participant was required to attend one testing session, which lasted approximately 30 minutes in duration. Prior to the commencement of the study, full information regarding the requirements of the study was provided by means of a written information sheet. This information sheet was supplemented with a verbal explanation and an opportunity to ask questions. Once full understanding of the study requirements was established, participants provided informed consent and were reminded of their right to withdraw. Following the attainment of consent, participants were required to complete a simple demographic questionnaire notably detailing the participant’s age, sex, hand dominance, and the presence of ocular atypicalities and motoric or rheumatologic difficulties. Critically, at this time the grasp that the participants are required to visualise employing during the perceptual task was defined and demonstrated. This grasp was defined 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. Following this participants were required to don the oculus rift HMD with attached Leap Motion Sensor and complete four experimental conditions, the order of completion was randomly counterbalanced across participants. The four experimental conditions were the constricted grasp condition, the normal grasp condition, the extended grasp condition and the systematically varied grasp condition. In the constricted grasp condition participants gained motor experience with a virtual hand that was 50% of the size of their actual hand, therefore constricting the grasp to 50% of the normal grasp ability. In the normal grasp condition participants gained motor experience with a virtual hand reflecting the true size of their actual hand, therefore grasp ability was 100% of their normal grasp ability. In the extended grasp condition participants gained motor experience with a hand that was 150 % of the size of their actual hand thereby extending their grasp ability 50% beyond normal grasp ability. Whilst in the systematically varied grasp ability condition the participants experienced the constricted hand size 25% of the time, the normal hand size 25% of the time and the extended hand size 50% of the time. Each experiential condition consisted of two phases: the calibration phase and the block size manipulation phase. The calibration phase consisted of 30 trials in which participants viewed the virtual display comprising of a table upon which two grey dots, one to the left and one to the right, were located (See Panel A Figure 2). The inclusion of a calibration phase occurred to provide the participants with the necessary amount of synchronous visual motor information to subsequently induce the illusion that the virtual hand is the participant’s hand (Kilteni et al., 2012). The engagement of this illusion is critical because if the participants do not employ this illusion, the subsequent results will not accurately reflect the study manipulations. In addition, the calibration phase provided participants with visual and motor experience regarding the action boundary associated with the virtual hand. Completion of the calibration phase required participants to touch the leftmost dot with the leftmost digit of their dominant hand and the rightmost dot with the rightmost digit again of their dominant hand. Participants were informed that it was ok if they could not reach the dot so long as they performed the action. After the participants had performed the action touching both dots, the two dots disappeared and reappeared in a different location on the table. The location of the dots and the distance between the dots was randomly varied across all 30 trials. However, the distance away from the participants that the dots appeared was maintained throughout as dictated by the Z coordinate in the study script. On completion of the calibration phase participants were instructed to place both their hands on their lap, this occurred so that the hand was out of range of the Leap Motion Sensor and hence the virtual hand was not visible in the virtual reality. At this time the virtual reality display was altered so that that the participant viewed the display of the table upon which there was a white block located (See Panel B Figure 2). Once the new display was presented the researcher placed the participant’s hand, they had just completed the calibration phase with on the right and left arrow keys of a standardised QWERTY keyboard. Participants were then instructed to imagine that they were going to grasp the block, employing the previously demonstrated grasp, and manipulate the size of the block to reflect the maximum size they believe they would be able to grasp with their dominant hand using the right and left keys. Each button press altered the size of the block by 1cm. Once the participant was happy that the block reflected the maximum size they could grasp with their dominant hand the researcher saved the final size and presented another block. This phase consisted of eight trials, in four of which the block started small at 3cm and the remaining four the block started large at 20cm. This occurred in order to control for the potential influence previous perception has on later judgements, a phenomenon commonly known as hysteresis (Poltoratski & Tong, 2014) On completion of both the calibration and block size manipulation phases for each four conditions participants were given a short verbal debrief regarding the true aims and theoretical underpinning of the study and an opportunity to ask any questions. To supplement this verbal debrief participants were also provided with a written debrief again documenting the aims and theory of the study and contact details for the lead researcher. The subsequent raw data obtained included eight maximum grasp block size estimates, four relating to the block that started at 3cm and four relating to the block that started at 20cm, for each experimental condition; small hand size, normal hand size, large hand size and variable hand size. Therefore 32 estimates were obtained from each participant.
The effects of ambient temperature on aggressive cognitions
Ambient, temperature, aggression Linear mixed effects modelling, regression, correlation
The world is getting warmer and it is of interest to researchers to explore how changes in temperature experience affect human behaviour. The heat hypothesis suggests that an increase in heat is associated with an increase in antisocial behaviour (e.g. violence, aggression). However social embodiment studies have also demonstrated hotter temperatures to be associated with less antisocial behaviour (e.g. greater gift giving). This study investigated whether higher ambient temperatures are associated with more or less antisocial responding using a controlled laboratory approach. Participants were placed into either a cold room or a hot room whilst they completed two tasks that implicitly measured the accessibility of aggressive cognitions. Using a combination of linear mixed effects analyses and regression analyses, the results demonstrated that there was no significant difference between the two temperature conditions concerning the accessibility of aggressive cognitions in a lexical decision go/no-go task and a word fragment completion task. Consequently the heat hypothesis and theories based upon a social embodiment framework were not supported in this case. Possible alternative explanations and limitations of the study are discussed regarding the inconsistent results to that proposed by particular theoretical frameworks and illustrated in previous research. Directions for future research are suggested in light of the present findings.
Participants In total, 65 participants took part in this study. Unfortunately the preregistered sample size figure of 120 participants was unable to be reached due to recruitment limitations. Participants were recruited via Lancaster University’s SONA system, via adverts, were friends of the researcher or were recruited on an opportunistic basis around the Lancaster University campus. As a reward for participating, participants were entered into a prize draw to win one of 12 £10 Amazon vouchers. Participants were excluded if they met any of several a priori agreed upon rules for exclusion: (a) non-native English speaker, or (b) made a connection in the debrief section between the room temperature and aggression measurements. Three participants were excluded from the analyses on this basis. Therefore 62 participants data remained in the analyses. Demographic information was obtained using questions on the Qualtrics survey (Qualtrics, Provo, UT). The mean age of participants was 25.29 years (SD = 8.83; 43 female, 19 male). It was preregistered that participants must be between 18 and 55 years of age however due to the prospect of increasing the sample size, the age range was increased to 18 to 60 years of age. Participants were randomly assigned to the cold condition (n = 31) or the hot condition (n = 31). Materials Lexical decision go/no-go task. A lexical decision go/no-go task was used to gauge the accessibility of aggressive cognitions. The standard lexical decision task (LDT) is an indirect measure of semantic activation of specific constructs (e.g. aggression) and is an excellent method to assess the activation of such semantic networks (Marsh & Landau, 1995; see Parrott, Zeichner & Evces, 2005). Advantageously, as the task does not require conscious expression, it is not easily affected by demand characteristics (see Greitemeyer & Osswald, 2011). The LDT task was used in conjunction with a go/no-go response whereby participants are instructed to respond as quickly as possible to a word (alike to the LDT) but to withhold any response if the presented stimulus is a nonword. The lexical decision go/no-go task has been demonstrated to be an excellent alternative to the standard LDT but also measures performance in a similar manner (Perea, Rosa & Gomez, 2002). Essentially, network activation is measured by the response latency with which participants respond to particular stimulus words, with faster reaction times (RTs) demonstrating more accessibility of the target construct (i.e. aggression) (Forster & Davis, 1984; Johnson & Hasher, 1987; Schacter, 1987; Morton, 1970). Specifically, faster RTs to aggressive words by participants in the hot condition, compared to the cold condition, would suggest that the construct of aggression is more accessible in hotter conditions. The lexical decision go/no-go task included the presentation of one hundred letter strings; 25 of which were aggressive-related words (e.g., gun), 25 of which were nonaggressive words (e.g., leaf) and 50 of which were nonword letter strings (e.g., breaff). The aggressive-related words were taken from Anderson, Carnagey & Eubanks (2003) and Johnson (2012). The non-aggressive items were extracted from Anderson et al. (2003) or chosen by the experimenter. Three independent raters who were blind to the study aims assessed the nonaggressive and aggressive words to determine if they were appropriately determined as nonaggressive or aggressive respectively. Fleiss Kappa demonstrated perfect agreement between the three individuals judgments, κ = 1, p < .0001, indicating that the raters agreed that all items coded as aggressive or nonaggressive were appropriately coded as such. Nonword letter strings took the form of pseudowords to prevent the possibility of participants classifying the words by a simple surface analysis of substrings. To illustrate this, a letter string consisting of “xx” can be quickly and easily recognised as a nonword without in-depth processing because no valid English words contain “xx” (see Bösche, 2010). Furthermore, research has demonstrated that more frequent words (e.g. Perea et al., 2002) and shorter words are responded to quicker (e.g. Spieler & Balota, 2000). Given this, the word frequency of each real word (i.e., aggressive-related words and nonaggressive words) was obtained using the SUBLECT database (Van Heuven, Mandera, Keuleers, & Brysbaert, 2014) and the word type categories were matched on word length. According to Welch's t-test, there was no significant difference between the aggressive related words and nonaggressive words in terms of word frequency, (t (40) = 1.64, p = .12), and word length, (t (48) = 0, p = 1). Together this reduces the effect that word length and frequency might have on response latencies. In the lexical decision go/no-go task, participants were instructed to respond by pressing the ‘spacebar’ key on the keyboard when presented with a valid English word (i.e. go response) however to withhold any response if presented with a nonword (i.e. no-go response). The experimental trials consisted of 50 real word letter strings and 50 nonword letter string trials. The onset of each trial was marked by a plus sign (+), which acted as a fixation point for the participant. After a 1000ms latency, the fixation point was replaced by a letter string. This stimulus item disappeared after a latency of 3000ms and was followed by the next fixation point and then the next letter string was presented automatically in the same aforementioned fashion. The presentation and randomization of letter strings, and the recording of response latencies were controlled by JavaScript code running on Qualtrics. Word Fragment Completion (WFC) Task. To measure the activation of aggressive thoughts participants also completed a WFC task consisting of 50 word fragments (adapted from Anderson et al., 2003). Using Qualtrics, participants filled the blanks with letters to form a valid English word within a five-minute timeframe. Of the 50 word fragments, 25 could be completed to form either a nonaggressive word or aggressive word (e.g., “ki__” could be completed with “kill” or “kite”). The other 25 word fragments could be completed with only nonaggressive words. Only the word fragments with possible aggressive-completions were used in the analyses. The remaining 25 fragments were used as a decoy to ensure that participants would not guess that aggression was being measured. If a word could not be completed, participants were required to leave the answer box blank. This task is a valid measure of aggressive cognitions (Anderson et al., 2003). The outcome variable of aggressive cognitions was calculated by dividing the number of word fragments that were completed as aggressive words by the total number of word-fragment completions that could be completed as aggressive. Fragments were presented in a randomized fashion for each participant controlled by Qualtrics. Baseline Temperature Comfort. A measure of baseline temperature comfort level was also included in the Qualtrics survey, which measured how cold or hot the participant generally feels. A rating scale of -50 to +50 measured this, where a higher score indicates a feeling of generally hotter. Many aspects can affect an individual’s thermal perception and comfort ranging from physical to cultural aspects (Laskari, et al., 2017; see for e.g. Djamila, 2017). For example, body temperature deviations can have their roots in physiology such as age (Castle, Norman, Yeh, Miller & Yoshikawa, 1991). These factors vary across individuals, raising the possibility that individuals have baseline temperatures or comfort levels that differ systematically from the average population (Obermeyer, Samra, & Mullainathan, 2017). In other words, the same temperature that is normal for one person might be cold for another. Given this, variations in an individuals subjective measure of baseline temperature comfort will be explored to see whether this moderates temperature effects on aggressive cognitions. Outside Temperature. A measure of outside temperature was not originally planned and its inclusion was not preregistered. However data from the local weather station was used to calculate outside temperature during each testing session. Overall, the mean outside temperature was 18.6°C (SD = 2.91) and ranged from 12.6 to 22.9°. Procedure and Design Participants were welcomed into either the cold or hot room depending on their random allocation. The room temperature reading before each testing session began was recorded, which demonstrated that the range of temperatures for all sessions was at 15.5-16.9°C (M = 16.14, SD = 0.39) and 27.8–29.8°C (M = 28.56, SD = 0.60) for the cold and hot condition respectively. The heat-controlled room consisted of five workplaces equipped with conventional PCs allowing for simultaneous data collection from five participants at one time. Participants were separated from each other by partitions between the workstations. Whilst at a workstation, participants received the study information and gave their consent to participate. They then completed four decision making tasks using the Qualtrics survey software, two of which measured the accessibility of aggressive thoughts (i.e. lexical decision go/no-go task and WFC task) and two of which measured cognitive ability (as part of another students MSc project). All instructions concerning the tasks were given via the computer. The four tasks were presented in a randomised order between participants by Qualtrics to reduce order effects (e.g. participants may be tired for tasks at the end) and carryover effects (e.g. earlier tasks may influence behaviour on subsequent tasks) (see Shaughnessy, Zechmeister & Zechmeister, 2006).
The effects of code switching in the level of persuasiveness of advertising and marketing messages on bilingual consumers.
Bilingualism Code-switching Language Manipulation Advertising Communication Language Comprehension/Cognition
Bilingualism and advertising are two concepts which are not commonly related, but based on recent statistics they definitely should be. Recent numbers show that more than 50% of the world’s population is bilingual (Grosjean, 2010). However, there has been minimal research concerning bilingual consumers and how bilinguals may differently encounter advertising messages, based on their ability to speak two languages. The research that has been done, is primarily based on code switching; the practice of switching between languages during speech. It is a very common practice between bilinguals, which they use to better communicate and better express themselves during a conversation in a specific social context. This study will attempt to analyse the effects of language manipulation upon bilingual individuals, by implementing the concept of advertising and more specifically bilingual advertising. participants will firstly encounter a manipulation of attitude towards language, before encountering a set of advertising slogans of certain products, in a code-switched format. They will then have to rate the products, based on the persuasiveness of the advertising slogans.
Firstly, a manipulation of attitude towards the language took place. Participants were presented with a random mock article, either in Greek or English. Participants were then presented with four audio recordings of advertising messages/slogans of four different products. Slogans were either all in Greek or English and they were presented in the same code-switching direction; from primary to Secondary or from Secondary to primary. A single word was chosen from each slogan and was code-switched to the opposite language appropriately. Participants were then asked to evaluate the featured products based on the advertising message they heard. Evaluations were obtained through a series of six questions, asking the participant to rate the featured product on a Likert type scale, varying from one to six. These included: “poor/high quality”, “level of appeal”, “odds of recommending the product to others”, “odds of buying the product”, “mediocre/exceptional” and “bad/good”.