The Effects of Different Sleep Stages on Language Learning Tasks in Young Adults
Language learning, novel generalisation, REM, sleep, sleep spindle density, sleep stages, speech segmentation, SWS
In order to learn a language, one must practice multiple tasks, including speech segmentation and generalisation. Segmenting speech allows for the identification of words and learning the meaning as well as syntactic role of those words within phrases and sentences. Novel generalisation requires generalising over the structure of a new language not yet experienced. Frost and Monaghan (2016) showed that participants were able to use the same statistical information at the same time to complete both language tasks. They suggest that segmentation and grammatical generalisation are dependent on similar statistical processing mechanisms. The role of sleep for learning to segment and generalise language is still unclear. Sleep affects memory consolidation, which is necessary for learning a novel language. This refers to the amount of sleep individuals get within their sleep cycle, yet it is unknown whether the duration of separate sleep stages has an effect. The declarative/procedural (DP) model by Ullman (2004) on learning provides distinctions in DP memory that associate with slow-wave sleep (SWS) and rapid-eye movement (REM) sleep respectively. SWS has a role in declarative memory processes, including memory for words and grammar. Rapid-eye movement (REM) sleep has a role in procedural memory processes, involving motor skills and coordination. Sleep spindle density should also be considered, as spindles are involved in offline information processing and information transfer. It was found that increased SWS and stage 2 spindle density have a positive effect on speech segmentation compared to generalisation.
Participants The original experiment was completed by 54 participants, 8 males and 46 females, with an age range of 18-24-years-old (mean age = 18.52). All participants reported being native-English speakers, with no history of auditory, speech or language disorders known. All participants either received university course credit or £20 for completing the experiment. Observations may be excluded for the first linear mixed-effects model. Exclusions may come from participants in the sleep group who did not sleep during the permitted time. This is because the first analysis aims to compare sleep vs. wake. The same participants’ data will be kept for the other linear mixed-effects models which aims to compare duration of sleep stages. This research received ethical approval by Dr Padraic Monaghan and Lancaster University’s Psychology Department on 22/04/2021. Design This study had a between-participants design with two conditions: sleep vs. wake between training and testing, and test type. There were two test types of speech segmentation and novel generalisation. Participants were randomly allocated to the sleep or wake conditions, and split evenly, meaning 27 participants slept and 27 remained awake. This study had access to PSG data for 18 of the participants in the sleep group. All participants received both test types. All participants were provided with an information sheet and gave written consent before the study commenced. Materials Stimuli Using the Festival speech synthesiser (Taylor et al., 1998), speech stimuli were created that were based on similar stimuli used by Peña et al. (2002). This artificial training language contained monosyllabic items, of which there were nine (pu, ki, be, du, ta, ga, li, ra, fo), used to form three different non-adjacent pairings with three possible X items in-between (A1X1–3C1, A2X1–3C2, and A3X1–3C3) (Frost & Monaghan, 2016). Using Peña et al.’s (2002) study, A and C items contained plosive phonemes (pu, ki, be, du, ta, go) and X items contained continuants (li, ra, fo). All AXC item strings had a duration of approximately 700ms. Any preferences – for dependencies not due to the statistical structure of the sequences – were controlled for by generating eight versions of the language. Each version had randomly assigned syllables to A and C items, and the same X items were used in all versions. These versions of the language were counterbalanced across both task types. When testing for novel generalisation, three additional syllables were used with continuant phonemes (ve, zo, thi) (Frost & Monaghan, 2016). Research on the similarities in phonological properties of non-adjacent dependent syllables has shown that these similarities show support for acquisition of such nonadjacencies (Newport & Aslin, 2004). Nonetheless, other research has found that they are not essential for language learning to occur (Onnis et al., 2004). Words in the same grammatical category tend to be coherent regarding phonological properties (Monaghan et al., 2007), so regardless of learning, this property of the artificial language used within this study is consistent with natural language, which allows for real-life implications. Training The speech stimuli were formed into a 10.5-minute-long continuous speech stream by stringing together the AXC words within the language. It was ensured that no Ai_Ci dependencies were repeated immediately after each other. The speech stream included 5s fades for the onset and offset of speech, which ensured that such a feature of speech could not be used as a language structure cue (Frost & Monaghan, 2016). Testing Segmentation: part-words were trisyllabic items that were heard in the training speech stream but overlapped word boundaries. As such, part-words comprised of either the last syllable of one word and the first two syllables of the next (CiAjX), or the last two syllables of one word and the first syllable of the next (XCiAj). For all nine AXC items, both part-word types were created. 18 test pairs were constructed which participants listened to, by matching each part-word with its corresponding word (for example, the A1X2C1 item was paired with the X2C1A2 part-word) (Frost & Monaghan, 2016). Novel generalisation: nine forced choice tests included a rule-word which contained one of three novel syllables (ve, zo, thi) (AiNCi), where N is the novel syllable and a novel part-word. For each Ai_Ci dependency, each novel rule-word appeared once. Part-words were made of two syllables that were heard in the training task, in their respective positions, with the same novel syllable as in the rule-word sequence (Frost & Monaghan, 2016). This novel syllable could appear in any position (first NCiAj, second XNAi, or third CiAjN) and each novel syllable occurred once in each of these positions. Rule-word and part-word novelty presence controlled for the effect of the novel syllable, yet the novel generalisation task still tested for generalisation of the non-adjacent structure of items within speech (Frost & Monaghan, 2016). Randomisation of test-pairs in all conditions was ensured across all participants, including the position of the correct response in each test-pair, to reduce response bias. When listening to the test-pairs, items in each pair were separated by a 1s pause. All participants completed The Stanford Sleepiness Scale (SSS) (Hoddes et al., 1972). This was in order to note participant sleepiness before the period of sleep or wake. The SSS consists of one item on a scale of seven statements, within which participants were required to select one statement that best described their perceived level of sleepiness (Shahid et al., 2011) (see Appendix A). Participant responses in the testing task were excluded if 90% of responses were always “1” or “2”, or if responses alternated between “1” and “2”. Procedure The whole procedure lasted for a three-hour period. For the training task, all participants listened to the continuous stream of speech and were instructed to pay attention to the language and think of possible words it contains. After the training task was complete, participants were split into two groups for the sleep vs. wake condition. Half of the participants, the sleep group, were given an hour and 45 minutes to sleep. These participants slept at Lancaster University Psychology Department’s sleep lab, and their sleep was monitored using polysomnography (PSG). PSG and an Embla N7000 system can record the amount of time spent in each sleep stage, and sleep spindle density, with EEG sites: O1, O2, C3, C4, F3, and F4 referenced against M1 and M2. The other half of participants remained awake for the same duration, watching a non-verbal, emotionally neutral video with neutral music. The testing task was then given to all participants after the same amount of time, 15 minutes after the break period. All participants were then required to complete the testing forced choice tasks. Within each trial, participants listened to a test-pair of items and were instructed to select which item best matched the training language. A response of “1” for the first item or “2” for the second item on a computer keyboard was recorded. All participants listened to the speech using closed-cup headphones in a quiet room (Frost & Monaghan, 2016). To test speech segmentation, participants completed a forced choice task on preference for word/part-word comparisons. To test novel generalisation, participants completed a similar forced choice task for rule-word/part-word preference. Data analysis Analysis included mixed-effects models to allow for random participant and item variability. As all participants responded to both task types, therefore multiple items, the likelihood of correlations in responses from the same participant and to the same item increases. Generalised linear mixed-effects allow for a more flexible approach compared to ANOVA, that can handle missing data better, without significantly losing statistical power. Participant and item variation, the effects of sleep/wake, test type, and sleep stage duration were all considered. The interactions between sleep/wake and test type, and sleep stage duration and test type, were also considered in separate models.
Secondary data analysis. Data were originally collected for the paper below, but they were not analysed by the authors. Frost, R. L. A., & Monaghan, P. (2016). Simultaneous segmentation and generalisation of non-adjacent dependencies from continuous speech. Cognition, 147, 70- 74
Data/Excel.csv Data/Excel.xlsx Analysis/r_file.R
The Effects of Posture on Body Part Width Representations
Body perception, affordances, somatosensation, visual perception
Despite the ubiquity of our bodily experiences, our representations of our body’s size are not geometrically accurate. For example, when estimating the length of body parts using the hand as a metric, consistent patterns of distortions across body parts are observed. Given the presence of these distortions, some have proposed that representations of length and width emerge directly, or indirectly, from the organisation of somatotopic maps in somatosensory cortex, rather than from their actual relative dimensions. However, whilst length representations are well researched with respect to this notion, less is known about representations of body part width across the body. Moreover, it is unclear from previous research whether body part width representations may be confounded by participants’ posture. Specifically, individuals have shown an enhanced tendency to overestimate body part width when seated upon a chair, suggesting that the chair may become incorporated into the body representation. Consequently, the aim of the current investigation was to further elucidate how width is represented across body parts and whether posture moderates these representations. Participants estimated how many hands widths made up the width of the back, shoulders, hips, torso, thigh, and head in one of three conditions: standing (n = 37), seated upon a chair (n = 33), or seated upon a backless stool (n = 39). Whilst estimates did differ across body parts, no effect of posture was observed. Moreover, the patterns of distortions observed differed from those seen in previous investigations. Results therefore indicate that body part width representations are neither accurate nor fixed, rather, they show distortions which vary across individuals and contexts. It is proposed that inter-individual heterogeneity in width representations may result from humans possessing alternative perceptual mechanisms for judging aperture passability. Therefore, maintaining fixed width representations is unnecessary, and hence too energetically costly to maintain.
Method Participants Ethical approval for this study was obtained from Lancaster University Psychology Department on 31st May 2023. As this study aimed to investigate body part width representations in healthy populations, only participants aged 18-55 years without any physical, or mental impairment were included in the study. However, as previous research (Readman et al., 2021) using the same paradigm for length estimates has shown no influence of anxiety or depression on body part estimates, participants with diagnoses of these conditions were not excluded. Participants were excluded if they had any current or historic diagnosis of cognitive impairment, as this can affect instruction comprehension (Han et al., 2011), or visual impairment, to ensure difficulties in seeing the body parts did not confound findings. Furthermore, given the associations between other psychiatric impairments (e.g., Priebe & Röhricht, 2001), neurological impairments (e.g., Blanke et al., 2004), or eating disorders (Mölbert et al., 2017) with distorted body perceptions, individuals with a current or historic diagnosis of a condition falling within any of these categories were excluded. A total of 123 (61 females) participants ranging from 18 to 68 years (M = 28.80 years, SD = 10.79) were recruited via opportunity sampling for this study. Participant recruitment was ended before the required N = 150 due to time constraints. All participants were entered into a draw to win one of two £25 vouchers as an expression of goodwill. A total of 15 participants were excluded for failing to meet the inclusion criteria, leaving a final sample of N = 108 (50 females). Participants were aged 18 to 55 years (M = 27.98 years, SD = 9.56); the majority of participants were right-handed (n = 99) and over half the participants had normal vision (52.78%), with the remaining participants having corrected-to-normal vision. Reasons for exclusion included a current or historic psychiatric impairment (n = 2) or eating disorder (n = 4), falling outside the study age restrictions (n = 3), visual impairment (n = 2), being pregnant (n = 1), failing to provide demographic information needed to determine eligibility (n = 2), and a self-reported misunderstanding of task instructions (n = 1). Design This study constituted a 3x6 mixed design with condition (standing, chair, or stool) as the between-subjects variable and body part (torso, hips, shoulders, back, thigh, or head) as the within-subjects variable. The dependent variable was participants’ accuracy ratios for each body part (actual size/ estimated size) where an accuracy ratio of over 1.0 indicated overestimation, and under 1.0 indicated underestimation of body part width. Materials and Procedure After providing their consent, participants completed a self-report demographic and clinical questionnaire administered via Qualtrics (Qualtrics, Provo, UT) which asked about participants’ age, biological sex, preferred hand, and details regarding their neurological, cognitive, and psychiatric history. Following this, participants were randomised to one of the three conditions (Standing, Chair, or Stool). In each condition, participants were asked to estimate how many hand widths of their dominant hand made up the width of six different body parts: the torso, shoulders, hips, back, head, and thigh. Participants were instructed to be as accurate as possible, using fractions where necessary. They were asked to refrain from touching the body part with their hand, or basing estimates off estimates for previous body parts if the two body parts were proportionally related. The researcher defined each body part verbally and pointed to their endpoints on their own body prior to the participant making their estimate. Participants in the standing condition performed all estimates whilst stood upright, without leaning on any surfaces. In the chair condition, participants were seated upon a standard desk chair with a high back and no arm rests. In the stool condition, participants were seated upon a fixed height bar stool with no back. The condition completed by participants was counterbalanced, and the order of body parts estimated was randomised. After making their estimates, the researcher used a soft tape measure to measure the actual width of the cued body parts before debriefing participants. The study took around 10 minutes to complete. Analysis Prior to conducting the analysis, outliers were removed using the median absolute deviation (MAD) approach. This procedure involves removing participants whose accuracy ratios deviated more than three absolute deviations from the median for a given body part. The MAD approach was chosen as it is more robust than traditional methods of outlier detection based upon standard deviations from the mean (Jones, 2019; Leys et al., 2013). To calculate the dependent variable of accuracy ratios, first, participants’ hand estimates for each body part were converted to centimetres by multiplying their estimate in hands by their measured hand width. After this, estimates for each body part were divided by the actual width of the body part to produce an accuracy ratio. To test the study hypotheses, data was analysed using a 3x6 mixed ANOVA using the rstatix package available from RStudio (Version 4.2.1). Body Part was entered as the within-subjects variable, and Condition as the between-subjects variable. The assumption of normality was checked using the Shapiro-Wilks test, and the sphericity assumption via Mauchly’s test. Partial eta-squared was used as a measure of effect size. Though frequently used in analysis, frequentist statistics are not without limitations. It is typically assumed that a p-value of <.05 is evidence for the alternative hypothesis, however this value only represents the probability of obtaining results as extreme as those observed, if the null is true (Wagenmakers et al., 2018). Therefore, data which is unusual under the null hypothesis is not automatically any less unusual under the experimental hypothesis (Wagenmakers et al., 2017). Moreover, a non-significant finding in frequentist analyses cannot be taken as evidence in favour of the null hypothesis (Kruschke & Liddell, 2018). In this regard, Bayesian statistics have several advantages over frequentist statistics including the ability to incorporate prior knowledge, quantify the degree of uncertainty surrounding the existence of an effect, and the ability to quantify the strength of evidence in favour of the null, or alternative hypotheses (see Wagenmaker et al., 2018 for a discussion). Consequently, to provide further support for conclusions drawn using frequentist analyses, a Bayesian Mixed ANOVA was conducted using the anovaBF function from the BayesFactor available in RStudio (Version 4.2.1). Default priors were used given that these reflect average effect sizes observed across all psychological experiments, and hence are likely to be more reliable than priors drawn from a single, potentially methodologically flawed, study (Rouder et al., 2012). Where a significant main effect of Body Part or Condition was observed, Holm-Bonferroni adjusted frequentist, and Bayes Factor, pairwise t-test comparisons were conducted to determine the pattern of differences underlying these effects. In addition, to determine whether body part width estimates differed significantly from 1.0 (i.e., an unbiased estimate), Holm-Bonferroni adjusted frequentist, and Bayes Factor, one-sample t-tests were conducted for each body part. To judge the strength of evidence provided by the Bayes Factor analyses, Kass and Raftery (1993) criteria was used. By this criteria, Anecdotal evidence is regarded as inconclusive. Percentage error (a measure of certainty in the estimate) was reported alongside Bayes Factors, where <20% is regarded as an acceptable level of uncertainty (Van Doorn et al., 2021).
The Effects of Schema-typical and Atypical Contexts on Memory for Brand Names of Products
Distinctiveness effects Schema Memory Product recall Product recognition Brand recall Brand recognition Product-brand binding
The memory for an advertisement can be affected by the way it is constructed. In general, the more distinctiveness, the better memory performance. Traditionally, it has been assumed that the whole memory episode will be better remembered if it is featured by any odd element(s) because it is more attention-demanding and creates stronger memory traces. However, recent evidence suggests that the distinctiveness effect might not spread to everything; it might only affect those distinctive elements without necessarily affecting their linkages with other elements. Accordingly, regarding the advertisements, the memory for each element can be diverse. We manipulated the distinctiveness effect by composing products with schema-typical contexts (undistinctive condition) and schema-atypical contexts (distinctive condition). Participants observed 20 advertisements; 10 were schema-typical and another 10 were schema-atypical. They then completed recall and recognition tests which allowed us to explore how far the distinctiveness effect could extend. We found that only product recall and recognition in the schema-atypical condition were robustly enhanced, other variables were not significantly affected. These findings went against the traditional view and conform with the recent research. We discussed that, in the schema-atypical condition, the products and their contexts made each other distinctive, hence, they were better remembered. In contrast, the brand names and product-brand bindings were schema-neutral, thus, they did not receive more attention and not better remembered. The results were further interpreted to form some practical implications that improve advertising effectiveness.
The stimuli were 40 newly constructed print advertisements (in digital format). Print advertisements were employed because they allow the better experimental control (Keller, 1987). A half of these advertisements belonged to toiletries category (i.e. shampoo. sunscreen, and toothpaste), whereas another half belonged to foods category (i.e. pizza, sandwiches, and fried chicken). For each category, there were 10 types of products. For each product, there were two versions of its advertisement; schema-typical and schema-atypical (but only one of which was viewed by each participant). The schema-typical advertisements referred to the ones in which the product was bound with an expected context (i.e. a toothpaste appearing a bathroom scene), while the schema-atypical advertisements referred to the ones in which the product was bound with an unexpected context (i.e. a toothpaste appearing in a bedroom scene). In terms of the stimuli construction, there were three key elements for all advertisements, the first of which was the product, the second was the background or the scene illustration which was considered as the context of that advertisement, and the last element was the brand name. The first two elements were to form advertising pictures, and all together with the third one were to form complete advertisements. The researchers purchased stock images from Shutterstock website (https://www.shutterstock.com). The images purchased (product shots, backgrounds, and decorative elements) were then retouched and composted into the print advertising pictures using Adobe Photoshop (Adobe Photoshop CC 2015). All the advertising pictures were controlled not to include any text so that the only copy presented in each advertisement was its brand name. In respect of brand names, we invented new brand names for all 20 products. Each brand name was controlled to be easily pronounceable. They were names of between one to three syllables i.e. Hans, Raven, and Moana. The brand names, texts in Candara 48-point type, were placed on top of every advertising picture. Figure 1 shows examples of stimuli. Table 1 shows the List of products, brand names, their schema-typical contexts, and their schema-atypical contexts. The illustrations of all 40 advertisements can be found in Appendix A. Figure 1. Examples of stimuli Table 1 List of products, brand names, their schema-typical contexts, and their schema-atypical contexts Product Brand name Schema-typical context Schema-atypical context Toiletries Category 1 Soap Flounder Bathroom Garden 2 Shower gel Naveen Bathroom In the bus 3 Deodorant Megara Bathroom Library 4 Perfume Attina Bedroom Street 5 Sunscreen Moana Beach Kitchen 6 Shaving cream Hans Bathroom Office 7 Toothpaste Pongo Bathroom Bedroom 8 Talcum powder Fauna Bathroom Beach 9 Shampoo Rolfe Salon Forest 10 Lipstick Armoire Office Cooking table Food Category 11 Sandwich Duchess Kitchen On the stairs 12 Fried chicken O’Malley Kitchen Yoga room 13 Yogurt Rialey Kitchen In the bus 14 Energy bar Gaston Sport field Bedroom 15 Pizza Linguini Restaurant Bathroom 16 Pasta Tony Kitchen On the bed 17 Soup Perdita Kitchen Gym 18 Raw burger Gus Kitchen Study room 19 Ice-cream Bo Bo Street Library 20 Fresh fruit Raven Garden Bathroom In addition, there was an effort to provide the variability of context for both schema-typical and schema-atypical advertisements. To illustrate, for the schema-typical advertisements, regarding the advertisements of toiletries category, from the total of 10 products, six of them were bound with a bathroom scene as their schema-typical context, while another four products were bound with other different schema-typical contexts (i.e. a beach scene for sunscreen). Similarly, for foods category, six products were bound with a kitchen scene as their schema-typical context, while another four products were bound with other different schema-typical contexts (i.e. a restaurant scene for pizza). Furthermore, for the schema-atypical advertisements, all 20 products had their own different schema-atypical contexts. For example, a forest scene was for shampoo, while a Yoga room was for fried chicken. Consequently, despite the effort to make the context of schema-typical advertisements more varied, there was probably more variability for the schema-atypical ones. Moreover, regarding the judgement of schema typical or atypical context, it was initially set up based on researchers’ perspective. Then, a pilot study was conducted on five participants where they were asked to judge whether the contexts were schema-typical or atypical for a particular product. All five participants judged each context to be typical and atypical as judged by the researchers, for all products listed. Furthermore, we constructed some additional materials to be used in the recognition test which were 20 foils of similar product images and 20 foils of similar brand names. As for the foil product images, we purchased another set of stock images (product shots and decorative elements) to be retouched and composted into another 20 product images as icons in isolation. Each foil was designed after one of the target product images, for example, we constructed the foil image of a toothpaste tube to be paired with the target image of a toothpaste tube. These two images were controlled to look similar in terms of product type and size, but different regarding the product design (packaging and colour scheme). As for the foil brand names, we further invented 20 similar brand names, 10 for toiletries category and another 10 for foods category. All foil brand names were controlled to have the same characteristics as the target brand names; names of between one to three syllables which were easily pronounceable. Design and data analysis strategy The overall design and the variables. A repeated measures design was employed in this study. The within-subjects independent variable was the advertising context which consisted of two levels; schema-typical and schema-atypical. There were six dependent variables examined in separate analyses. The first three variables were from the recall test including the percentage of correctly recalled products (product recall), the percentage of correctly recalled brand names (brand name recall), and the percentage of correctly recalled product-brand bindings (product-brand binding recall). The first two variables were simply calculated from the number of correct answers divided by the total number of advertisements of each level. These variables were to answer whether the performance of products and brand names recall would be better if the advertising contexts were different from their typical schemas. For the third variable, the product-brand bindings recall, it was calculated based on the number of correctly recalled sets (which were counted when the products were written together with their matching brand names) divided by the number of correctly recalled products. Hence, this third variable was to explore that when people recall the products, how much would they extend their memory to the brand names. Likewise, the other three dependent variables were from the recognition test including the percentage of correctly recognized products (product recognition), the percentage of correctly recognized brand names (brand name recognition), and the percentage of correctly recognized product-brand bindings (product-brand binding recognition). Similarly, the fourth and fifth variables were calculated by dividing the correct answers by the total number of advertisements of each level. These variables were to answer whether the performance of products and brand names recognition would be better if the advertising contexts were different from their typical schemas. Also, for the sixth variable, the product-brand bindings recognition, it was calculated based on the number of correctly recognized sets (which were counted when participants picked the right choices of product images and their matching brand names concurrently) divided by the number of correctly recognized products. Hence, this last variable was to explore that when people recognize the products, how much would they extend their memory to the brand names. Presentation phase. In terms of experimental design, firstly, 20 advertisements were presented to participants. For counterbalancing purpose, 32 participants were equally divided into four groups (eight participants in each). Each group was bound with a different set of advertisements. Each set consisted of 20 advertisements, 10 from toiletries category and another 10 from foods category. From 10 toiletries advertisements, half of them were the schema-typical advertisements and another half were schema-atypical. From five schema-typical advertisements, three of them had a bathroom as their context, and another two had other typical contexts. The arrangement mentioned above was also applied to the foods category advertisements; three schema-typical advertisements were bound with a kitchen scene, another two schema-typical advertisements were bound with other schema-typical contexts, and five different schema-atypical advertisements. Appendix B shows four different sets of stimulus. However, the actual orders of advertisements presented to participants were not the same as shown in the Appendix B, as all 20 advertisements in each set were then randomly mixed. Hence, the positions of advertisements were different in each set to minimize the order effect. Additionally, all the advertisements were presented on a laptop screen (13-inch MacBook Air) and each of them was shown for 10 seconds, using a timed PowerPoint display. After the presentation of stimuli, there was a distractor task for two minutes. Immediately after the two-minute interval, participants were administered a free recall test followed by a recognition test. In addition, to achieve the most appropriate study design, prior to the establishment of the final experiment procedure, we ran a small pilot study to determine a suitable memory interval (the duration of the distractor task). We had two participants (two females, mean age = 25 years) do the pilot study which 10-minute interval was employed, and we found that it led to a ceiling effect for product recognition but a floor effect for brand name recall and recognition. Therefore, we decided to cut down this interval to only two minutes. Test phase. For the free recall test, participants were asked to write down every product and brand name which they could remember in the answer sheet. Figure 2 shows the presented slide for the recall test. For the recognition test, we separated it into two subsections; the toiletries subsection and the foods subsection. In each subsection, there were 10 questions referring to all 10 products in that category. Thus, there were the total of 20 main questions in this recognition test. The questions were also presented on the same laptop screen (13-inch MacBook Air). The toiletries-category questions were presented first, followed by the foods-category questions. Figure 2. The PowerPoint slide used in the recall test In respect of recognition test construction, for each question, there were two sub-questions; product question and brand name question. For each product question, there were two choices (A and B) which included the target image of product and the foil of similar product. The right answers were randomly varied between A and B throughout the test. Besides, for each brand name question, there were 20 choices (1 to 20) which include 10 target brand names and 10 foils of similar brand names. For each category, the right answers were different for every brand name question and randomly varied between odd (1, 3, 5, etc.) and even (2, 4, 6, etc.) choices throughout the test. Figure 3 shows examples of recognition-test questions. All the questions can be found in the Appendix C. Figure 3. Examples of PowerPoint slides used in the recognition test
The effects of screen exposure on developmental skills among children at two and three years of age.
Previous research into the topic of children’s development has tended to take place in Western nations (Kuta, 2017; Martinot, 2021). One aspect of development is language development, and one aspect of research on that matter is the use of electronic devices, with the potential for consequent effects on children’s language abilities. This paper reviews and builds upon the scope of the available research, with its disparate findings, by offering research from the context of Kuwait, a non-western nation where parents tend to be in favour of their children having access to new technologies regardless of their age (Dashti & Yateem, 2018). The increasing number of children being exposed to electronic devices of various descriptions raises concerns regarding the possible adverse effects of screen exposure on their development, particularly through displacement of educationally enriching activities, which provides the motivation here (Haughton, Aiken & Cheevers 2015). Based on a review of the existing literature, the present research starts from the hypothesis that language development will be negatively correlated with media exposure. Valid data relating to 96 children of 24 to 36 months of age were collected using two questionnaires, one relating to the child’s knowledge of Arabic words on various topics (voices of animals, names of animals, vehicles, toys, food and drink, etc.) and the other quantifying the child’s daily screen time. Ordinary least squares analysis was performed using SPSS, version 26. While a statistically significant positive moderate correlation between language expression score and age was found – an increase in age was associated with an increase in language expression or the number of words understood and expressed – no significant effect of screen time on language expression was found after adjusting for age. This indicates, therefore, the value of employing non-western populations in research into cognitive development, and suggests the need for further research in order to attain generalisable findings.
The parents of a total of 100 participant children) took part in a questionnaire survey. The reports of 4 parents were excluded because their child’s age exceeded 36 months and the inclusion criteria for the study were set at 24 to 36 months. Participants were selected by means of opportunity sampling. An announcement was sent via WhatsApp to those of my contacts who had children of an age appropriate for inclusion in the study. Parents were recruited by sending a link to the survey through WhatsApp. Family and friends were then asked to deliver the WhatsApp number to those who they knew who had children within the set age range. Parents read information about the study and their informed consent to participate in the questionnaire survey was obtained via Qualtrics. The Lancaster University Psychology Department gave ethical approval for the present study. Procedure The data for the present work were gathered by means of an online questionnaire via Qualtrics between 7 June 2021 and 22 June 2021. During this time, participants submitted answers to two questionnaires: a) the Arabic CDI, which measures Arabic words arranged according to groups (for example voices of animals, names of animals, vehicles, toys, food and drink, etc.) to measure the child’s knowledge of the Arabic language (Abdel Wahab, 2020) and b) a questionnaire related to the number of hours the child spent in front of the screen , and their opinion of the appropriate amount of screen time which children can spend at their screens, as well as their control over their children’s viewing of the screens, and whether or not they are allowed to watch while sleeping and eating. The survey instruments were designed to measure the extent to which screen viewing is related to the language development of Kuwaiti children aged between two and three years. Materials CDI: The Arabic CDI language scale developed by Abdel Wahab (2020) is a questionnaire comprising a set of categories containing checklists for identifying variety and number of words. In front of each word there are three options (‘knows it’, ‘knows it and says it’, ‘does not know it’) and parents are asked to respond to each item according to their children’s knowledge of these words. The Arabic CDI questionnaire contains 100 words divided into the following categories: voices of animals, names of animals, transport, toys, food and drink, clothes, parts of body, home furniture, little things inside the house, things and places outside the home, people, games and daily routine, actions, time-related words, adjectives, pronouns, question words, prepositions, and number formulas. Media exposure questionnaire: Following the language questionnaire, parents completed a second survey measuring their children’s screen viewing, stating how many hours per day they spent watching a screen. Parents were asked to report frequency of screen use by choosing among the following six options: None, 0 to 1 hour, 1 to 2 hours, 3 to 4 hours, 5 to 6 hours, and > 6 hours. Participating parents were then asked to state what length of time they would consider it appropriate for their children to watch a screen, with the same set of responses available to them. There was then an item asking the parents whether they were making any efforts to reduce their children’s screen time, such as setting specific days or times for viewing or preventing them from viewing their screens while eating or in the bedroom, for example.
The impact of retribution on perception of transgressor by others
Retribution, Transgression, Guilt, Vignette
Emotions play a key role in within society, behaviour and human life with moral emotions such as guilt, regret and shame being able to influence individuals’ judgments and actions. For example, a person who experiences guilt will want to fix their wrongdoing that has caused this. There are times where these efforts to repair ones transgression, can lead an individual to self-punish in order to repair bonds with others and reduce negative consequences of the situation. The present study experimentally investigated the effect of self-punishment intensity on perceptions of a transgressor. Participants were randomly assigned to one of three conditions of self-punishment intensity (low, correct and high). Vignettes were manipulated for each condition and presented for participants to read for them to answer questions on their judgments of the transgressor (perceptions of guilt, shame, regret, moral character, and trustworthiness, their willingness to forgive the transgressor, how likely they thought they would reoffend in the future) and rated this on a Likert scale of 0-5. Participants allocated to low self-punishment had more negative perceptions towards the transgressor overall when compared to correct self-punishment. However, this was not found beyond this as no differences were seen for those within the high self-punishment condition
Participants. Participants were recruited through the use of LU Sona system as well as opportunity sampling through use of social media and network platforms accessible. A total of 174 responses were collected via Qualtrics, of those 158 have been successfully completed through to the end whilst 16 have only been started and answered few questions at most. Therefore, the decision has been made to exclude any incomplete attempts. This resulted in a final sample of 158 of which 54 are in the high punishment condition, 52 in low punishment condition and 52 in correct punishment. Design. This is a one-factor study with 3 levels (self-punishment: Low punishment, correct punishment, and high punishment) between-subjects design. Qualtrics randomly allocated participants to one of the three conditions. Materials. A short hypothetical vignette was used to describe an event between two individuals; ‘Simon’ the transgressor and his friend, who he steals money from. With each of the punishment conditions, the vignette introduced the scenario with the same starting sentences to create the scene of someone performing a transgression against their friend with feelings of self-directed negative affect presented by the transgressor: Simon is out with his friends when he noticed that a member of his group has left their wallet unattended. Simon helps himself to the £40 that was in the wallet. His friend eventually realises that the money has been stolen and seems distressed. The next day, Simon feels bad for his actions and confesses to his friend that he took the money. The final sentence of the vignettes was manipulated for each of the three conditions. The sentence stated the amount of money returned to Simon’s friend, which was either less than originally taken (low punishment, £20), same amount (correct punishment, £40) or more than originally taken (high punishment, £60). He gives his friend all the money he has in his wallet, which came to £20 (or £40, or £60). Hypothetical vignettes have been a popular method to explore social actions within research allowing actions to be explored in context to specific situations, people’s judgments, reactions and perceptions of the scenario being described and/or the individual people within the vignette. It allows this all to be clarified in the form of data collection and provides a less personal, and therefore less threatening way of exploring sensitive issues and topics in society (Barter & Renold, 1999; Hughs, 1998; Schoenberg & Ravdal, 2000). Vignettes are a valuable technique for exploring perceptions of situations and have been utilised previously in research on guilt and perceptions of a transgressor post-transgression (McLatchie, 2019; Manstead & Semin, 1981; Dijk, de Jong & Peters, 2009) and so have been utilised in this research of intensity of self-punishment post-transgression. Empirical research has shown that emotions and perceptions of guilt specifically focuses attention on the behaviour and action that has occurred which has in turn elicited these feelings (Tangney & Dearing, 2002). This is why the vignette in the present study was written with a particular emphasis on presenting the transgressor to be feeling remorse/guilt after failing to adhere to a social standard, being explicitly stated through acceptance of responsibility. This was done through stating that Simon ‘felt bad for his actions’, intentionally presenting to participants that, regardless of the punishment, Simon did know his behaviour was wrong. It can also be seen in this study through the motivations and efforts to recompensate the wrongdoing through his self-punishment and returning of a quantity of money. Absence of this could imply to participants a lack of emotional response, this could have impacted judgments on Simon regardless of the presence of punishment or not. As stated previously, other emotions can be used synonymously within conversation when referring to guilt, such as self-conscious emotions like regret and shame; it was important to ensure that guilt was specifically being portrayed. McLatchie (2019) ensured this in his study investigating punishment types (no punishment, self-punishment, and other punishment). McLatchie used a vignette that described interpersonal violations as these are primarily associated with guilt than the other emotions. This is because it includes other individuals and not merely directed at the self where the common emotion that would most likely be triggered would be shame instead. Due to this, the present study also used a vignette that described an interpersonal violation of moral and social standards with the last sentence manipulated to present three self-punishment conditions based on varying intensities. These terms are popularly used interchangeably within conversation due to multiple similarities between them (Shen, 2018; Bhushan, Basu & Dutta; 2020; Stearns & Parrott, 2012), Participants were then asked a series of questions which gathered information on the participants judgments of Simon. Participants were asked to rate the extent of the perceived guilt, shame, and regret of the transgressor as a third-party observer which keeps in line with current research which provides evidence for a strong internal consistency of these measures (McLatchie, 2019). It is also consistent with previous research where the same elements were combined to calculate an overall guilt score. This emphasised the importance of these emotional responses and behaviours that an individual may present when judging overall guilt being experienced by the perpetrator. How much the participant thinks Simon (the transgressor) deserves to be forgiven was also measured. This was done with an adapted version of Zhu et al.’s (2017) way of measuring this and has proved to be effective in prior research related to guilt and self-punishment (McLatchie, 2019). The final questions were – how likely the participants thought Simon would reoffend, and to what extent they thought the punishment performed was sufficient for the transgression committed. All answers were presented and rated on a Likert scale with the question above. Procedure. Participants were invited to partake in a study aiming to evaluate a ‘social action’. Qualtrics was used to provide the survey to participants where they were asked to read through the vignette prior to moving through the questions and answers which measured their responses. As each question appeared, the vignette remaining at the top of the screen for reference throughout. Answers were presented on a 6-point Likert scale ranging from 0 (“Not at all”) to 5 (“Completely”) which they were required to choose their response through a rating. Once participants completed this survey, a final section asked participants to provide demographic information with a full debrief. Demographic information included basic information such as the participants age and gender. Additional questions were included in order to gain an insight into the participants experience with situations such as the one described in the vignette and their personal experiences with guilt allowing any influences of the participants character to be seen when analysing results. These include being asked if they have ever had an experience as the protagonist (Simon in this case), someone who has been stolen from, and if they are prone to feelings of guilt.
The Impact of Sleep Patterns on Emotion Regulation in Taiwanese Adolescents
sleep patterns, circadian types, morningness-eveningness, on/off-peak time, emotion regulation, cognitive control, adolescents
Emotion regulation has been shown in a number of studies to be related to sleep, which often suggested that good sleep quality leads to better emotion regulation. However, research which has empirically documented the link between individuals’ specific sleep patterns/circadian types and emotion regulation among adolescents is scant. Therefore, the aim of this study attempts to explore whether there is an interaction between circadian types and the corresponding peak time on emotion regulation. Participants were 204 boys and 148 girls, who were from 13 to 16 years of age. The present study involved three questionnaires and two modified emotional Stroop tasks, including Facial-Emotional Stroop task and Lexical-Emotional Stroop task, as the assessment of emotion regulation. The analysis of the questionnaires and experiments was conducted through a series of multivariate ANOVA analyses in order to indicate whether there is a main effect of two independent variables or interactions on two emotion regulation. The results showed three main findings. Firstly, ‘morning people’ committed more error on facial tasks than ‘evening people’. Secondly, participants who attended the tasks in the afternoon had faster reaction times on Lexical task than who were tested in the morning. Thirdly, the interaction between circadian types and the corresponding peak time only showed in the evening group. To sum up, this study might be of importance in explaining the relationship between sleep patterns and emotion regulation in adolescents. Nevertheless, further studies for adolescents in investigating circadian types in relation to emotion regulation are needed.
Materials Each participant was asked to complete three online questionnaires about sleep and mood as well as two experimental tasks about emotion regulation. Three questionnaires had been translated into a Chinese version and inspected by a native Chinese-speaking professor in the Department of Psychology at Lancaster University. Sleep Measures. Circadian Types Questionnaire. Participants were given a Morningness-Eveningness Questionnaire (MEQ) (Horne & Östberg, 1976) to assess when their biological clock can achieve peak alertness, which indicates the better timing for people to behave more efficiently in their work and cognitive, behavioural and emotional functioning (see Appendix A). Three groups were be categorized based on the MEQ score: score > 58 for the morning type, 42 < score < 58 for the Intermediate type and score < 42 for the evening type. Sleep Quality Questionnaire. To assess whether participants have sleep dysfunction, participants were also asked to fill out the Pittsburgh Sleep Quality Index (PSQI) (Buysse, Reynolds, Monk, Berman & Kupfer, 1989), which elicited information concerning their sleep quality (see Appendix B). The higher score the participants gain, the poorer sleep quality they have. This score can be used to examine whether people's sleep quality can influence their emotion regulation ability. Mood Measurements. Emotional Problems Questionnaire. Participants needed to fill out the Depression Anxiety Stress Scale-21 (DASS-21) (Antony, Bieling, Cox, Enns & Swinson, 1998), which is a self-reported measure to record their mood during over one recent week (see Appendix C). There were three dimensions of negative mood in this questionnaire, including depression, anxiety and stress. Each dimension had an independent score, with a higher score indicating more emotional problems. In this study, three sub-scores were added together to produce a composite measure of emotional difficulties. Emotion Regulation. In addition to the questionnaires, participants were requested to complete two modified “Emotional Stroop Tasks”, including the Lexical-Emotional Stroop Task and the Facial-Emotional Stroop Task, as the assessment of their cognitive control in response to emotional stimuli (Isaac, Vrijsen, Eling, van Oostrom, Speckens & Becker, 2012). Lexical-Emotional Stroop Task. The experiment stimuli consisted of three kinds of emotional words, namely positive, negative and neutral words, each of which had five presentative words (see Table 1), and each word was printed in four colours (blue, green, red and yellow). In order to assess the emotion regulation ability, participants were asked to classify the colour by pressing a different button as fast as they can. For example, when participants see a blue or green word they have to press “Q”, whereas when they see a red or yellow word they have to press “P”. Before presenting the stimulus, a fixpoint lasted 200 ms and was followed by the presented stimulus, which lasted 2000ms to make sure that participants had enough time to react. All emotional-colour words were randomly presented during this task. After participants press the key, feedback showed whether the response was correct, which lasted 500 ms (see Figure 1). Before the 30 real trials, there was a clear instruction about this task and then each participant had six trials for practise to ensure that they indeed understood how to operate this task. All stimuli were translated into Chinese and appeared in font DFKai_SB and in font size 96. The projected stimuli came out on the computer screen and colour words appeared against a black background. Facial-Emotional Stroop Task. A total number of stimulus was 160 emotional faces which were composed of 10 different identities (5 males and 5 females) x 4 emotions (happy, neutral, angry and sad) x 4 Stroop colours (blue, green, red and yellow) (see Figure 2). Emotional faces were selected from Taiwan Corpora of Chinese emotions and relevant psychophysiological data (Chen, Zhou & Zeng, 2013). It could reduce the cultural difference effectively when Taiwanese participants took the Facial-Emotional Stroop task. As the same as the execution in the Lexical-Emotional Stroop task, participants were also requested to do colour classification by pressing different buttons as fast as they can. For instance, when participants see a blue or green facial expression, they have to press “A”, whereas when they see a red or yellow emotional face they have to press “L”. Before stimulus appeared, a fixpoint showed and lasted 200 ms, which was then followed by the presented stimulus, which lasted 2000ms, to ensure that participants had enough time to respond the stimuli. The Stroop trials consisted of 30 real trials and were randomized per participant. Participants had six extra trials to practice as well before the real trials. Within the trials, participants saw feedback to tell them whether the response was correct for the last trial, which lasted 500 ms (see Figure 3). All facial stimuli were cropped, free from hair or other external accessories that could prevent any distractions during the task. The projected stimuli showed on the computer screen and the coloured facial expression appeared against a black background. Both Lexical and Facial stimulus presentation and response collection were programmed by using PsyToolkit on the website (Stoet, 2010) (see Appendix D and E) and run on Windows computers. Table 1 Stimuli from the Lexical-Emotional Stroop Task Positive Neutral Negative 快樂 (Happy) 被愛 (Beloved) 滿足 (Satisfaction) 自豪 (Pride) 舒服 (Comfort) 無聊 (Boredom) 平靜 (Calmness) 驚訝 (Surprise) 疑惑 (Confusion) 害羞 (Shyness) 生氣 (Anger) 焦慮 (Anxiety) 厭惡 (Disgust) 恐懼 (Fear) 悲傷 (Sadness) Figure 1. The diagram of Lexical-Emotional Stroop Task. In this example, the stimulus is a word of Blue Happy. Figure 2. Sample happy male stimuli used from the Facial-Emotional Stroop Task. Figure 3. The diagram of Facial-Emotional Stroop Task. In this example, the stimulus is a male’s face of Blue Happy. Procedure This study was approved by the director of the Counselling Department in Mingder High school and combined with the counselling curriculum. All students’ parents were provided with the information sheets (see Appendix F) about this study and an opt-out consent form (see Appendix G) one week prior to it. Only parents who did not want their child to participate in this study needed to sign and return the opt-out consent form. However, no opt-out consent form was returned. Participants were tested in a computer lab, with the researcher and their counselling teacher present. In order to balance the number of classes with the time of test, half of the classes per grade were tested in the morning (8 a.m. to 9 a.m. or 9 a.m. to 10 a.m.), and the others were tested in the afternoon (2 p.m. to 3 p.m. or 3 p.m. to 4 p.m.) (see Table 2). The duration of participation lasted around 45 minutes. Before the beginning of the study, the research topic and aims were presented on each computer screen. Participants were provided an opportunity to ask questions, and then the researcher asked whether anyone was not willing to attend this study. None of the participants were blind as to the aim of this study. Then, participants were given the links to the experiments and questionnaires; they needed to key the links onto the browser and start the study. In order to effectively use their time, participants were requested firstly to complete two Emotional Stroop tasks. Following the experiments, participants were instructed to fill out three questionnaires.
The Impact of Spatial Locations Involving Schema Representations on False Memories
Schema, false memory, source monitoring, distinctiveness heuristic, object-location binding.
While numerous studies have investigated the effects of schema on false memories, few have looked at how schematic framework involving spatial locations have influenced levels of true and false memories in different age groups. For this study, two separate analyses were conducted; both analyses required participants to study four environment scenes, which contained schema- consistent objects that were placed in either schema-expected or schema-unexpected locations and schema- irrelevant objects. After each scene, a distractor task was presented, followed by the test scene. In the first analysis, false memory rates were examined by adding objects, which were not present during study, into test scenes; in the second analysis, false memory rates were assessed by shifting schema-consistent objects from a schema-expected to a schema-unexpected location or vice versa between study and test scene. In both analyses, target objects that remained in the same location for both study and test scenes assessed for true memories. Three different age groups were studied; younger children aged seven and eight, older children aged nine and ten, and adults who were university students. Results revealed that overall, adults were more schema-bound, and had significantly higher levels of true memories as well as significantly lower levels of false memories compared to younger and older children. Furthermore, schema-inconsistent objects attracted lower levels of false memories across all age groups. However, objects that shifted from a schema-unexpected to a schema-expected location yielded high false memories for object-location pairing. This study is of particular significance to the field of forensic psychology.
The experiment was programmed using a computer software called Psyscript and was run on a Mac laptop. Four different environments were used during the experiment, which were a kitchen, a living room, an office and a bathroom. For the practice run, a separate image, which was a seminar room, was used. All the photographs used were standardized across all four environments, with each photograph being 1300 x 864 pixels, to ensure that the quality and clarity of each photograph was the same. To every environment image, three different versions were prepared for the study scene, ensuring that all six of the schema-relevant target objects had the opportunity to appear in a schema-unexpected location, a schema-expected location, or not being present at all. Moreover, to every version, two test scenes were prepared, to create a variation between which of the target objects that were initially placed in schema-relevant or schema-irrelevant locations during study phase would be shifted during the test scene. Figure 1a is an example of a bathroom scene during study phase and Figure 1b is an example of the test scene for that version. The program had been set to ensure that the sequence of the four different environment images would be pseudo-randomized for counterbalancing purposes, in which all the scenes were presented once, whereas the versions and test scenes selected were randomized. Moreover, the target objects that were circled during the test scenes were also pseudo-randomized, in which each object would only be circled once. For the practice run, both the study scene and the test scene were presented in a hardcopy form, which was laminated. Two separate slips of paper were prepared, one being “Was this object anywhere in this picture before?” for the participants allocated to the Presence condition, and “Was this object in this place before?” for the participants allocated to the Location condition. The paper slips containing the questions were left on the table for participants to refer to. Figure 1a The above image depicts version 1 of the bathroom scene. The two target objects in schema-expected locations are the shampoo and toothpaste, whilst the two target objects in the schema-unexpected locations are the mirror and toilet brush, and the schema-irrelevant objects are the file, glove, toy. Figure 1b The above image depicts Test 1 of Version 1 of the bathroom scene. The mirror has now been shifted from a schema-unexpected location to a schema-expected location whilst the toothpaste remains in the same position. The shampoo has now been shifted to a schema-unexpected location. The toilet paper and weighing scale, which was previously not present during the study scene is now present in the schema-expected and schema-unexpected location respectively, with the toilet paper being circled for the participant to respond to. The schema-irrelevant objects that were added were the jacket, pencil case and handbag. Design: This study consists of two analyses; to address the two research questions. First regarding whether location affects true and false memories, and second, to see what shifts in location do to memory for the original object memory (condition 1) and object-location pairing (condition 2). The first analysis investigates the true and false memories involving objects that were present and not present at study, whilst the second analysis investigates the true and false memories toward objects that were present at study and were later shifted during the test scene. Hence, a mixed ANOVA design was used to address the first of these questions. The within-subject independent variables include the study (present, not present), and the schema appropriateness of the object location (schema-expected, schema-unexpected, irrelevant). The between- subjects factors include the conditions (presence, location) and age groups (younger children, older children, adults). The “yes” responses for the objects that were present in both scenes but not shifted and objects that were not present during the study scenes but were present in the test scene were analyzed. For objects that were shifted during the study and test scenes, the within-subjects factor was schema (schema-expected, schema-unexpected), and the shifting of objects (shift, no shift). The between-subjects factors include the conditions (Presence, Location) and age groups (younger children, older children and adults). The dependent variable was the accuracy of responses given, to compare the difference between objects that shifted and objects that did not shift. Procedure: The experiment consisted of a study phase, a distracter task and a test phase, which took an estimated 10 minutes to complete and was conducted in an unoccupied learning classroom, in the Burnley Primary School, whereby participants were individually tested. Each participant was required to undergo a practice run before the actual experiment took place, to ensure that the participant had understood what he or she had to do. In the practice run, the laminated image of the seminar room was presented alongside the paper slip with either the Presence question or the Location question, depending on which condition the participant had been assigned to. The participants were given 12 seconds to study the image. After 12 seconds, the participant was presented with another image with several target objects circled, in which the objects would be pointed to one by one by the researcher. The participant would then be prompted to verbally respond if they had either seen that object anywhere before during the study scene or if that object had been in that location before during the study scene. For both conditions, the participants were instructed to press either the “Y” or “N” key on the keyboard in response to whether they had seen the circled object anywhere in the picture before during the study phase (Presence condition), or if they had seen the circled object in that particular location before were it the Location condition. Once the participants acknowledged that they had understood, they were presented with the actual experiment. Each participant was required to study four different environments, in which one of three versions would be selected for every environment. Each study scene would last for 12 seconds for the participant to study, and then a distracter task would immediately appear. The distracter task, which lasted for 30 seconds, required the participant to hit any key on the keyboard whenever a specified animal (eg: giraffe, frog, hippopotamus) appeared. A green tick would appear every time the participant successfully presses a key before the specified animal disappears. Once 30 seconds was up, the distracter task would end, and one of two of the test scenes for that environment would appear. A total of twelve objects would be circled sequentially, with the next object only being circled 0.5s after the participant had given a response. Depending on which condition the participant was in, once every object had been circled, the participant would be required to respond to the question “was this object anywhere in this picture before?” (Presence condition), or “was this object in this place before?’ (Location condition). If the participant, who was in the ‘presence’ condition, deemed that the object was somewhere in the picture before, he or she would respond by pressing the “Y” for Yes on the keyboard; if it was deemed to not be in the picture before, the participant would then press the “N” for No on the keyboard. The same thing was conducted for the Location condition. Once the participant had responded to all 12 objects, a different environment scene would appear and the participant would be required to repeat the process until all four scenes had been shown.
The Paradox of Choice in fictitious COVID-19 vaccination scenario: the role of the number of options and the amount of information in decision-making.
Previous research evidence showed that when people face abundance of choices or too much information, they tend to experience the paradox of choice. This study investigates the role of the number of options and amount of information in decision-making, respectively, the paradox of choice in the fictitious COVID-19 vaccination scenario. Participants (N = 128) were randomly allocated to one of four experimental conditions. The conditions differed in the number of options (high – six options; low – two options) and the information (high – six pieces of information per option; low – two pieces of information per option). As a result, the four experimental conditions were: low options, low information; low options, high information; high options, low information; high options, high information. Participants were asked to choose one of the vaccines from a list presented separately from the experimental stimuli. The reaction time of choosing a vaccine was measured. Participants were asked to evaluate how satisfied they were with their choice, how confident they were about their choice and their anticipated regret. Participants were also asked to write the reason why they chose a particular option. The study did not find a significant effect of the number of options and the amount of information on the decision-making. Participants identified five main themes why they chose a particular option: features of the vaccine, scientific evidence, information, lawfulness, and personal preference. The study revealed positive relationships between choice satisfaction, confidence, and anticipated regret.
Participants The participants’ pool was collected from the general public. In total, 191 participants took part in the study. However, 62 participants were excluded due to missing values. Another participant was further excluded because of stating being 0 years of age. Thus, the data of 128 participants (36 males, 90 females, 1 non-binary/third gender, and 1 prefer not to say) were used for the analysis. The participants were in the age group between 18 and 51 years of age (M = 23.1, SD = 6.02). Based on power analysis when effect size f = .25 (medium effect), p = .05, power (1 – β error probability) = .80, and the number of groups = 4, it was indicated that the sample size of 128 participants is necessary to ensure the study results have high statistical power. In terms of age, one participant was stated to be 22,5 years old. For the analysis, this was taken as 22 years of age. The participants were invited to the research via Facebook post, Instagram story, and direct messaging friends and family circles. From the overall sample, 103 participants (29 males, 72 females, 1 non-binary/third gender, 1 prefer not to say) also filled an additional qualitative question investigating the reasoning behind the participants’ choice. As drawn from the overall sample, the age of participants responding to the qualitative question ranged from 18 to 47 years of age (M = 22, SD = 5.76). Design Participants were presented with information about fictitious COVID-19 vaccines. The current study applied a 2x2 between-subject design. Participants were randomly split according to the number of options (high – six options; low – two options) and the amount of information they received (high – six pieces of information per option; low – two pieces of information per option). Consequently, the four experimental conditions were: a) Low options, low information b) Low options, high information c) High options, low information d) High options, high information The six vaccines in the high options scenario represented the first six COVID-19 vaccines used in the world in more than two countries (Forbes, 2021). Two vaccines in the low option scenario were chosen as it is the smallest number of options participants can compare and choose from. The amount of information then copied the design of the number of options. The number of options and the amount of information was then counterbalanced, enabling testing the effect of the number of options versus the amount of information and their interaction on decision-making. Materials As mentioned above, the data was collected using an online questionnaire. Participants were randomly allocated to one of the experimental conditions using the Qualtrics.com question randomiser function. Thus, there was no control of the researcher regarding the experimental condition allocation. The experimental stimuli consisted of pictures containing the information about vaccines varying in the number of information and the number of vaccines, as can be seen in Figure 1 to Figure 4. The information about each vaccine in the experimental stimuli was inspired by the real-world COVID-19 vaccines in use. For collecting the information, official sources were reviewed, news articles and videos, and other websites. Although the information was modified, it does not directly correspond with any real-world vaccine. The sources also do not directly match with real-world sources of information. All people, social media accounts, and websites are fictitious. The information was counterbalanced, so each of the fictitious vaccines has a similar amount of information from official sources (CDC, NHS, WHO, Government) and unofficial sources (made up websites and social media profiles). Further, to ensure there is no dominant option, the number of people in fictitious vaccine trials was similar. Likewise, the efficiency levels were kept similar across the options, and positive and negative information was also balanced. Figure 1 Experimental stimulus – Low information, low options Note. This picture represents the low information, low options experimental condition presenting two pieces of information and two vaccines options. Figure 2 Experimental stimulus – Low information, low options Note. In this picture, the low option high information experimental condition can be seen. Two options of vaccines and six pieces of information for each vaccine were presented in this condition. Figure 3 Experimental stimulus – Low information, high options Note. This figure illustrates the high options and low information experimental condition. In this experimental condition, six vaccines and two pieces of information for each vaccine were presented. Figure 4 Experimental stimulus – High information, high options Note. The high options, high information condition stimulus was split into two pictures to assure that the font of the text is sufficiently large for the participants to read the information. Six options of vaccines and six pieces of information to each vaccine were presented in this condition. After viewing the stimuli, participants were asked to select one vaccine from the list on a separate page. The lists of vaccines varied depending on the experimental conditions—the number and type of vaccines corresponded with the experimental stimulus. The page with vaccines options was timed to measure how long participants spend deciding between the vaccines. The time was measured from when the page came up until submitting the page. For the open-ended question about the rationale behind the choice, a larger text box was provided so the participants could type in a short paragraph about why they decided on that vaccine. 5-point Likert scales were used to measure satisfaction (unsatisfied to satisfied), confidence (unconfident to confident), and regret (regret to not regret at all). Procedure In the beginning, participants were informed about the nature of the experimental task; however, they were not told that the study measures the paradox of choice. Participants could continue the study after completing a consent form. Then, participants were informed that they would view lists of information about fictitious COVID-19 vaccines. They were recommended to take notes to maximise their attention to the information. Then participants proceeded to one of the experimental conditions and were asked to read through the information presented. Then they continued to another page and were asked to choose one of the vaccines from the list based on the information from the previous page. The questionnaire continued with the open-ended question. The following page contained the evaluation of the choice satisfaction, confidence, and regret. Participants were disclosed that the paradox of choice was measured in the debriefing, followed by its definition and links to the actual COVID-19 vaccines information. The participants were given the option to withdraw by closing the browser window without saving their data if they no longer wished to participate in the study. The experimental design was reviewed and approved by the Lancaster University Department of Psychology ethical committee. Data analysis methods This study investigates the effect of the number of options and the amount of information on the paradox of choice across the four experimental conditions. The dependent variables measured were the reaction time, satisfaction levels, choice confidence, and anticipated regret measured using a 5-point Likert scale. The data gathered consists of independent observations as everyone went through one experimental condition at the time. Convenient sampling was used to collect data as the participants were mainly the researcher’s family, friends, and acquaintances. However, the participants come from different countries, age categories and educational backgrounds; thus, it can be assumed that the observations are independent of each other. The effect of two factors (information, options) with two levels (low and high) on dependent variables are observed. Hence, a 2x2 analysis of variance (ANOVA) was chosen as an appropriate analysis for testing the research hypotheses. The relationships between choice satisfaction, confidence, and anticipated regret were also investigated. The data were checked for the assumption of linearity. The data on satisfaction seems to be positively skewed similarly to the data on confidence and regret. However, the data appear not to be linear nor homoscedastic. Therefore, Spearman’s correlation was chosen as an adequate analysis for this type of data. The short responses to the qualitative question “Why did you decide on that option?” was analysed using template analysis (King & Brooks, 2017). Template analysis is a flexible type of thematic analysis that can be used to analyse written responses to an open-ended question on a questionnaire (Brooks et al., 2015; King & Brooks, 2017). The question about the participants’ rationale behind their choice used in the current study was open-ended. Participants were asked to give a short written answer. Because the data result from an open-ended question and the flexibility of template analysis, template analysis was chosen to analyse the quantitative data. The final template is presented below in Figure 5 in the results section. In the beginning, all data was put together in one document. Next, the participants’ answers were coded line by line. Then the line coding was used to identify themes. The second level of themes was generated from the first level themes. Because the answers consist of short sentences with a maximum of short paragraphs, two levels of themes were used in the analysis. The template was developed from the two levels of codes. The template checked whether it fits all the recorded answers ensuring the template accuracy. Then the template was reviewed and concluded, referring to the sixth research question.
The Relationship Between Perspective-taking, Lie Detection and Self-construal Among Taiwanese
“Theory of Mind” (ToM) refers to an ability, which allows us to understand what other people may believe, think, know, feel. Also, ToM is considered to play an essential role in social interaction. Evidence suggests that improved ability to understand others’ mental states through training can also improve our ability to generate lies and understand what kind of situations people may lie. In addition, previous studies point that there are differences in lie-telling and perspective-taking between individualistic and collectivist cultures. Therefore, the current study aimed to investigate whether there is a relationship between the perspective-taking, lie detection and self-construal (individualism and collectivism). Data were collected from 40 typically developed adults in Taiwan (M = 23.98, SD = 2.99). Each participant was asked to complete three computer-based tasks, namely a perspective-taking task; a lie detection task, and a questionnaire of Auckland Individualism and Collectivism scale (AICS). The result showed that there is no relationship between the ability of perspective-taking and lie detection. Also, the people scored higher individualism will show better performance on pointing out truths, but worse on detecting lies. It might relate to the “truth bias”, which means that people will typically assume or believe others are telling truths rather than lies, especially distinguishing on individualists. However, because cultural effects such as language differences and self-construal might affect individuals’ performances on instances of ToM use, the current study suggests that people might need to use different cues to detect lies in a truth-versus-lie judgment between different cultures.
Participants Data were collected from 40 typically developing adults from an opportunity sample in Taiwan. The entire group was composed of 20 males and 20 females between the ages of 18 and 30 (M = 23.98, SD = 2.99). All participants stated that they were Taiwanese, speaking Chinese/Taiwanese Mandarin as their first language, with normal vision or vision which had been corrected to normal. All of the participants had not been diagnosed with any neurological or developmental disorders. The data of participant No.40 was excluded from analyses because the participant only responded with the same positive answer to each question in the lie detection task. The original minimum required sample size was 44, which was determined a priori by using G*Power software. This number was calculated based on assuming a medium effect size of 0.4 and a reasonable power of 0.8. However, 40 was considered as a more suitable sample size, as the experiment consisted of two orders for the perspective-taking task, four sub-sets of the lie detection task and a questionnaire. In order to counterbalance stimuli presentation, the target sample was set to 40, as it is a multiple of eight (two times four times one); it is also the closest number to 44. All participants had been given the consent form and the information sheet to understand the contents of the project before the tests began. Furthermore, this project was approved by the ethics process from the Department of Psychology at Lancaster University. Design and Procedure Each participant was asked to complete three computer-based tasks, namely, the perspective taking task, the lie detection task, and a questionnaire of the Auckland Individualism and Collectivism Scale (AICS). All of the tasks were translated or designed in the participants’ first language, in this case, Chinese/Taiwanese Mandarin. All of the tasks were presented on a laptop and participants responded by using the computer mouse. The full session took around an hour in total. Perspective-taking Task The original perspective-taking task was called the “director task”, which can be traced back to the studies from Keysar et al. (2000) and Apperly et al. (2010). The present study employed a similar version of the director task which was presented in the study from Wang et al. (2016). In the instruction of the perspective-taking task, participants were given a demonstration of how to use a computer mouse to select and move the object. Later, the experimenter explained to participants that the speaker/director was standing behind the shelf and would not be able to see the objects in the blocked slots. It was impossible for the speaker/director to ask participants to move the object which was in the blocked slot (see Figure 1). Participants were asked to consider the speaker/director’s perspective and respond as quickly and accurately as possible. Participants had a chance to practice (6 trials) and ask questions before the start of the task. The task was divided into four blocks, and participants were allowed to take breaks between each block. There were a total 128 trials in the task, 16 of which corresponded to the experimental trials; the other 16 corresponded to the control trials and the rest were fillers. The fillers were regarded as a baseline measure for the non-perspective taking aspect of the task, such as understanding and identifying the speaker/director’s instructions. In 16 of the experimental trials, there were differences between the speaker/director’s description and the participants’ point of view. In contrast, the control trials provided a close match in terms of visual and audio stimuli, but the control trials did not impose the demand to perspective-taking. For example, as can be seen in the right-hand picture in Figure 1, if the speaker/director ask participants to move the “bigger” balloon to take the speaker/director’s perspective, participants should move the yellow balloon rather than the pink one, which was the bigger balloon from the participants’ own perspective. By the end of the task, only the number of egocentric errors committed on experimental trials were counted; the errors reflect failure to account for the director’s perspective. Figure 1. Left: An example of the control trials. Right: An example of the experimental trials. Lie Detection Task Participants were asked to watch 16 videos (each video lasting around 15~45 seconds). The videos were recorded by four volunteer models from Lancaster University. All models were Taiwanese and spoke Chinese/Taiwanese Mandarin as their first language. Each model recorded 16 videos in total which comprised four stories. Each story contained to two truths and two lies, from a first person and a third person perspective for each story (there are four versions of each story). For the story contents, there were several elements that storytellers were required to include in their stories (see Appendix A). In addition, the storytellers were given two designated elements to lie about in the lie stories. There was a total of 64 videos. The videos were evenly and pseudo-randomly divided into four lists. For example, participants never watched two videos of the same storylines containing lies and told from a same perspective by different storytellers in one list. Therefore, each list contained 16 unique videos. Participants watched videos from one of the lists, and at the end of each video, they were asked to identify whether they thought that the storytellers were telling a truth or a lie. To make sure the participants would concentrate on watching videos rather than just guess the answers, participants were asked a question about an aspect of each video. The questions were used as inclusion criteria, whereby only correct responses of the aspects were included in the data analysis. Auckland Individualism and Collectivism Scale (AICS) The third test used was the Auckland Individualism and Collectivism scale (AICS), which was developed by Shulruf, Hattie and Dixon (2007) and was used to measure individuals’ self-construal, namely, individualism and collectivism. The questionnaire consists of 30 questions (see Appendix B and C), which includes three dimensions of individualism and two dimensions of collectivism. For individualism, the scale consists of 12 items and is divided into three dimensions, namely, responsibility, uniqueness, and competitiveness. For collectivism, the scale consists of 8 items, and two dimensions are referred to: advice and harmony. Each of the dimensions was composed of four items. The questionnaire was presented in an online form, and participants were asked to complete it after they had finished the lie detection task. The response to each question was scored using a six-point likert scale from 0 (Never) to 5 (Always). The maximum score in the individualism trial was 60, and the maximum score in the collectivism trial was 40. A higher score on each of the trials indicated that an individual was more inclined to individualism or collectivism. The AICS questionnaire has been shown to work in different cultures such as the United Kingdom, China, Romania and Italy (Bradford et al., 2018; Ewerlin, 2013). This means that this questionnaire can be used as a feasible measure in both individualistic and collectivistic cultures. Previous studies have mentioned that an individual can simultaneously show tendencies towards both individualism and collectivism; in other words, an individual may be able to achieve a high or low score on both subscales (Bradford et al., 2018; Shulruf et al., 2011). With this in mind, the analysis of the current study did not divide participants into two groups for individualism and collectivism. Instead, this study used the AICS questionnaire to obtain participants’ scores in individualism and collectivism, and to observe the relationship between individuals' self-construal and their ability to detect lies.