A Scoping Review of the Effects of Benzodiazepines on Emotions in Young People
Benzodiazpines, Young people, Children, Adolscents, Emotion/s, Emotional dsyregualtion, Non-prescription misuse.
Background: Benzodiazepines are primarily used to manage anxiety and agitation. While it is understood how benzodiazepines work physiologically it is not fully understood how these physiological changes cause the emotional changes. As this relationship is not fully understood, it maybe that benzodiazepines also affect emotions in ways not currently known, such as being a factor in emotional dysregulation. Objective: To conduct a scoping review into the effects of benzodiazepines on young people. To map the of the effects benzodiazepines have on emotions in young people and identify any links between benzodiazepines and emotional dysregulation. Design: A scoping review was conducted. PRISMA protocols were followed but other sources such as Cochrane and Joanna Briggs Institute were consulted to develop a framework. Results: This review’s findings suggests that benzodiazepines do reduce anxiety and agitation. However, the research concerning children and adolescents is limited, and suggests benzodiazepines maybe less effective than in adults. There are many adverse effects but despite this prescription use remains relatively high. Non-prescription misuse in adolescents is evident and globally prevalent. Only one direct link was found to emotional dysregulation, but other possible links were also found. Conclusions: More research into the areas of the efficacy of benzodiazepines in children and adolescents and the risks associated with paradoxical and adverse effects is needed. Possible links between emotional dysregulation and benzodiazepines misuse were made and research is needed to understand if this relationship exists and the effects. Any improvement in understanding this relationship will enable targeted interventions to be developed.
The search was conducted using the following databases: Web of Science, PubMed, CINAHL, Psych Info, Medline and Embase. Searches were dependent on the functionality of the different databases such as different key terms, different abilities to expand search terms and different limiters or age groups, these are all shown in the search terms document in the OSF repository. All searches were limited to English language. No further sources were used to supplement the search.
An Exploratory Analysis of Cortical Hyperexcitability, Anxious Tendencies, and Sleep
Cortical hyperexcitability, Anxiety, Problematic Sleep
Cortical hyperexcitability reflects abnormal or aberrant neural processes and has been associated with visual distortions, discomfort, and hallucinations. Abnormal visual behaviors have previously been found to exist within non-clinical populations. The present study explored the previously implied relationship between anxiety, sleep patterns, and cortical hyperexcitability. Three inventories were used to gather data; the General Anxiety Disorder inventory (GAD-7; Löwe et al., 2008) measured anxiety, the Pittsburgh Sleep Quality Index (PSQI: Buysse, Reynolds, Monk, Berman, & Kupfer, 1989) measured problematic sleep behaviors, and the Cortical Hyperexcitability index version two (CHi-II; Braithwaite, Marchant, Takahashi, Dewe, & Watson, 2015; Fong, Takahashi, & Braithwaite, 2019) measured cortical hyperexcitability, which is composed of three separate dimensions, or ‘factors’. In order to analyse the three factors, this study utilised three separate multiple regression models (n = 97), and a correlation analysis was used to analyse the relationship between anxiety symptoms and problematic sleep behaviors. Some significant results were found in support of the relationship between anxiety and cortical hyperexcitability. No significant results were found for the relationship between sleep and cortical hyperexcitability. A significant correlation analysis found that there is a significant positive relationship between anxiety and sleep. Collectively, these findings provide additional external validation for the CHi-II as an indirect proxy measure for symptoms of cortical hyperexcitability.
Participants Due to the ongoing pandemic, 34 participants were gathered from Lancaster University student-based Facebook groups. This was an attempt to gather students in a similar manner to common recruitment without the use of in-person interaction. In addition to the gathered 34, 63 additional participants were used from previously collected data, gathered in-person also from Lancaster University students. Overall, 97 participants were gathered for this study. The mean age of participants was 21 (age range 18-33 years), of which 65 (67%) were female. Informed consent was obtained from all participants. Materials Due to the remote nature of the study, each of the surveys used was a digital variant made on Qualtrics. The Cortical Hyperexcitability II (CHi-II) is one of the first verified measures of cortical hyperexcitability. The CHi-II consists of 30 items and takes 20 to 25 minutes to complete. Each item focuses on a specific experience followed by two 7-point Likert scales, to measure participant’s frequency and intensity of each experience (Fong et al., 2019). The CHi-II can be broken down into three separate factors. Factor one, “Heightened Visual Sensitivity and Discomfort”, which consists of 11 items. Factor two, “Aura-Like Visual Hallucinatory Experiences”, which consists of nine items. Factor three, “Distorted Visual Perception,” which consists of six items (see Fong et al., 2019). For each of the three factors, intensity and frequency scores were added for a global score of each factor, for each participant. These global factor scores were then divided by the number of items in each factor, respectively, to provide an average for each participant for each factor. There are four items that are not part of any factor. Although these items were recorded in data collection, they are not used in this analysis. The General Anxiety Disorder assessment (GAD-7) measures anxious tendencies and has been established as conceptually valid and reliable in measuring anxiety in non-clinical populations (Löwe et al., 2008). The GAD7 consists of seven items with a 4-point Likert scale of frequency for responses. All items will be scored (never – 0, almost always – 3) and be added together to form a global anxiety score. A higher score indicates a greater level of anxiety. Total scoring will have a range of 0-21, with set cut offs for mild (5-10), moderate (10-15), and severe anxiety (15+). This inventory should only take about 5 to 10 minutes to complete. The Pittsburgh Sleep Quality Index (PSQI) is a measure of sleep quality and sleep disturbances over the past month, and has demonstrated good psychometric properties with various populations, including non-clinical subjects (Buysse et al., 1989; Grandner et al., 2006; Mollayeva et al., 2015). The PSQI has been found to have high internal validity, high test-retest consistency, and is one of the most direct methods of measuring sleep quality (Mollayeva et al., 2015). The PSQI consists of 19 items measuring: subjective sleep quality, sleep latency, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. All 19 items are scored and added to form a conclusory global score (range 0 to 21), a higher score indicating an increased presence of sleep disturbances (Buysse et al., 1989). This inventory should only take about 10 to 15 minutes. Overall, these three surveys should take 35 to 50 minutes to complete. Once each score is coded from the digital surveys, researchers used R Studio to find various predicted relationships or significance between scores. Each participant was given an anonymous participant ID, and a randomised order to complete the three surveys, in order to avoid order effects. Procedure Participants were contacted through email, where they were given participant IDs, in order to anonymise their results, and the order in which they were to complete the three surveys. One link was sent to each participant which contained separate links for each survey. The main link also contained a participant information form, which informed participants about what the study consisted of and what was expected of them, and a consent form. Participants were advised to complete the surveys in an isolated area, free from distractions, and all in one sitting. After the three main surveys were completed the participants received a debrief form. Analysis To uncover significant positive relationships between the two variables, sleep and anxiety, and cortical excitability, three separate multiple regression models were conducted. Three regression models were conducted separately by the “visreg,” “tidyverse,” “pwr,” and “gvlma” packages installed under the R statistical program (version 3.6.1, R Development Core Team, 2019; see Champely, 2020; Breheny & Burchett, 2017; Pena & Slate, 2019; Wickham et al., 2019). For the multiple regressions, the independent variables, or ‘predictor variables’, used for each were the universal sleep (PSQI) and anxiety (GAD-7) scores. For the dependent variables, each of the three factors of the CHi-II were used, respectively. In addition, a correlation analysis was used to determine if there was a significant relationship between the GAD-7 and PSQI scores in order to validate the use of this particular sample. Particularly, this relationship should be significant as found by previous studies, a non-significant result would show that this particular sample is problematic. Finally, to ensure no major deviations occurred between the two separately-collected groups of participants, descriptive statistics of both groups were gathered and a T-test analysis of all variables were conducted.
Hemispheric Lateralisation of Facial Emotion Processing: A Possible Explanation of Atypical Empathetic Responses in Children with Autism Spectrum Disorder
Hemispheric Lateralisation, Emotion Processing, Autism Spectrum Disorder, Empathy, Chimeric Face Task
Existing research suggests that children with autism are endowed with a significant delay in the lateralisation of facial emotion processing (Taylor et al., 2012), and that this delay is associated with some of the social and emotional based deficits that manifest within the disorder. The present study therefore aimed to ascertain the reliability of Taylor et al.’s (2012) findings by determining whether the strength of lateralisation for facial emotion processing differs between children with and without autism, while also determining whether this difference can explain atypical empathetic responses in children with autism. To explore these aims, an online version of the chimeric face task was administered to 11 neurotypical children and 5 children with a diagnosis of autism. The Child Empathy Quotient was completed by parents of all children, and The Autism Quotient – Children’s Version was completed by parents of children with autism. Results indicated that there was no significant difference in the strength of hemispheric lateralisation for facial emotion processing between children with and without autism, and that the strength of lateralisation did not predict a child’s level of empathy, nor did a child’s autism severity. Instead, levels of empathy were best predicted by an individual’s diagnostic status and age. The present study was therefore unable to support the finding of Taylor et al. (2012) or explain empathy deficits in the autistic population. However, the limitations identified in this study help to inform future research on the relationship between the lateralisation of facial emotion processing and empathy.
Participants Participants were recruited from mainstream primary schools, wrap around care settings and specialist educational provisions in the Lancashire area, as well as via social media. A total of 22 parents completed the required questionnaires on behalf of their children, out of which 17 parents arranged a date and time for their child to complete the chimeric face task. One child, who is non-verbal and has received a diagnosis of ASD had difficulty completing the task and selected responses impulsively without looking at, or taking sufficient time to consider, the facial stimuli and the emotion it depicted. For this reason, the chimeric face task was terminated prior to completion and the child’s data was not included in the analysis. The final sample of participants consisted of 16 children aged between 5- and 10-years-old, of which 5 had received a formal diagnosis of ASD (5 boys; Mage = 6.8, SDage = 1.48). One child with ASD had a comorbid diagnosis of hypermobility and sensory processing disorder. All children with ASD were reported to speak English at home, one child was left-hand dominant, and four children were right-hand dominant. The remaining participants were 11 typically developing children (6 girls, 5 boys; Mage = 7.0, SDage = 1.90), who had not been diagnosed with any neurodevelopmental disorders. One of these children was reported to speak Russian at home, however, is fluent in English. All children in the typically developing group were right-hand dominant. Design A two-factor between-subjects experimental design was employed to determine whether the strength of hemispheric lateralisation for facial emotion processing differs between children with and without a diagnosis of ASD. The independent variable for this research question was diagnostic status, a between-subject factor, with two groups; ASD and typically developing. Participants were assigned to one of these groups based on their diagnostic status, which was ascertained by their parent’s responses on the demographic questionnaire. The dependent variable for this research question was the strength of hemispheric lateralisation for facial emotion processing which was measured using the chimeric face task. A three-factor mixed-subjects predictive correlational design was employed to determine whether a child’s diagnostic status, and strength of hemispheric lateralisation for facial emotion processing can predict a child’s level of empathy. The predictor variables for this research question were diagnostic status, a between-subject factor (typically developing or ASD), and the strength of hemispheric lateralisation for facial emotion processing, a within-subject factor. The outcome variable for this design was empathy, a within-subject factor, measured by the Child Empathy Quotient. Measures Demographic Questionnaire Materials. The online demographic questionnaire (see Appendix A) was comprised of eight questions. Three of which required parents of the participants to input a response, these questions were used to determine the child’s age (in years), month of birth, and year of birth. The remaining questions were multiple choice, and therefore, required parents to select an answer out of 2-4 possible answer options. These questions acquired information including the child’s gender (male or female), dominant hand (left, right or don’t know/no preference), the language used in their home environment (English or other) and diagnostic status (formal diagnosis of ASD or no formal diagnosis of ASD). If the child did not speak English at home, then parents were required to input the language predominantly spoken. Parents who confirmed that their child had received a formal diagnosis of ASD were asked to input any comorbid diagnoses their child had received, so that they could be considered in the analysis. Parents who confirmed that their child had not received a diagnosis of ASD were asked if their child had received a diagnosis of any other neurodevelopmental disorders, this question was used for exclusionary purposes. Procedure. Completion of the questionnaire took approximately 2 minutes. Following completion of the questionnaire participants were excluded from the study and unable to proceed to the next stage if they did not meet the age criterion, or if they had not received a diagnosis of ASD but had received a diagnosis of another developmental disorder. The Child Empathy Quotient (Auyeung et al., 2009) Materials. The Child Empathy Quotient (EQ-Child) is a parent report questionnaire composed of 27 items (see Appendix B) used to measure a child’s level of empathy. This questionnaire was developed by Auyeung et al. (2009) using the adapted version of The Adult Empathy Quotient (Baron-Cohen & Wheelwright, 2004), individual items have therefore been modified and made applicable and relevant to children. The items therefore refer to behaviours, responses or difficulties commonly exhibited or experienced by children, e.g., ‘My child shows concern when others are upset’. Parents had to indicate the extent to which they agreed with each item by selecting one of the following options on a four-point Likert scale; ‘definitely agree’, ‘slightly agree’, ‘slightly disagree’, and ‘definitely disagree’. The EQ-Child has previously been completed by parents of neurotypical children, and children with ASD, aged between 4- and 11-years-old. The pilot study conducted by Auyeung et al. (2009) yielded findings indicative of a high-internal consistency and good test-retest reliability, and the patterns of results were consistent with those found in adult research (Baron-Cohen & Wheelwright, 2004). Procedure. All parents were required to complete the EQ-Child, which took approximately 5 minutes. The order the questionnaire items were presented in remained consistent between parents and parents were unable to proceed to the next part of the study before they had provided a response for all 27 items. Scoring. Parental responses on individual questionnaire items were converted into numerical points and summed together to calculate an empathy score for each child. For the following numbered items; 1, 4, 8, 10, 13, 14, 15, 16, 19, 21, 22, 23, 24, and 25, a response of ‘definitely agree’ equalled 2, ‘slightly agree’ equalled 1, and, ‘slightly disagree’ or ‘definitely disagree’ equalled 0. The remaining items were reverse coded. The maximal attainable empathy score was 54, the higher the score, the more empathetic a child is perceived to be by the adult completing the questionnaire. The scoring method applied in this study is consistent with the scoring method used, and detailed, in Auyeung et al. (2009). See Appendix B for the 27 items, and their corresponding item number. The Autism Spectrum Quotient – Children’s Version (Auyeung et al., 2008) Materials. The Autism Spectrum Quotient – Children’s Version (AQ-Child) developed by Auyeung et al. (2008) is a parent report questionnaire composed of 50 items (see Appendix C), used to quantitatively measure autistic traits in children aged between 4- and 11-years-old. The items in the AQ-Child are derived from the Autism Spectrum Quotient – Adult’s Version (Baron-Cohen et al., 2001) and the Autism Spectrum Quotient – Adolescent’s Version (Baron-Cohen et al., 2006), however, they have been revised and adapted to be pertinent to children. The items therefore refer to scenarios and behaviours that children are likely to have experienced or exhibited, e.g., ‘S/he would rather go to a library than a birthday party’. Parents indicated how strongly they agreed with each descriptive statement by selecting one of the following responses on a four-point Likert scale; ‘definitely agree’, ‘slightly agree’, ‘slightly disagree’ and ‘definitely disagree’. Previous studies have administered the AQ-Child to parents of children with ASD, aged between 5- and 11-years-old (Auyeung et al., 2008). Administration of the AQ-Child has been reported to have excellent test-retest reliability and a high alpha and reliability coefficient. Procedure: This questionnaire was only completed by the parents of children with a diagnosis of ASD, all of whom were unable to proceed to the next stage of the study until they had provided an answer for all 50 items. This questionnaire took approximately 5-10 minutes to complete. The order of items remained constant between parents. Scoring. For each child reported to have a diagnosis of ASD, a total AQ score was calculated. Total scores were calculated by converting responses on the four-point Likert scale into numerical scores and summing them together. For the following items 1, 3, 8, 10, 11, 14, 15, 17, 24, 25, 27, 28, 29, 30, 31, 32, 34, 36, 37, 38, 40, 44, 47, 48, 49 and 50, a response of ‘definitely agree’ equalled 0, ‘slightly agree’ equalled 1, ‘slightly disagree’ equalled 2, and ‘definitely disagree’ equalled 3. The remaining items were reverse scored. The higher the overall score, the greater number of autistic traits exhibited and endowed by the child. See Appendix C for the 50 items, and their corresponding item number. The Chimeric Face Task Materials. The chimeric face task is a widely used measure of the lateralisation of facial emotion processing. Chimeric faces are composite visual stimuli that are made by splitting two symmetrically averaged images of a face vertically down the middle and combining them together to depict a different emotional expression in each hemiface. The chimeric faces and the symmetrically averaged images used in this study derive from the work of Michael Burt (Burt & Perrett, 1997; Innes et al., 2016), and are supplied by Parker et al. (2021) via Gorilla Open Materials: https://gorilla.sc/openmaterials/104636. In the practice trail, two symmetrically averaged images of male faces and two chimeric faces were used, these faces depicted the emotions fear and surprise. A further 12 chimeric faces were used in the experimental trial, which depicted all possible combinations of the emotion’s happiness, sadness, anger and disgust. Four symmetrically averaged images of male faces depicting these emotions were also used. See Figure 2 for the stimuli used in the experimental trial. Figure 2. The Facial Stimuli used in the Experimental Trial of the Chimeric Face Task Note. The 16 facial stimuli presented to children during the experimental trial of the chimeric face task, including the four symmetrically averaged faces depicting the emotions happiness, sadness, anger and disgust, and the 14 possible combinations of these four symmetrically averaged faces. Adapted from “A leftward bias however you look at it: Revisiting the emotional chimeric face task as a tool for measuring emotional lateralisation” by B. R. Innes, D. M. Burt, Y. K. Birch, and M. Hausmann, 2016, Laterality: Asymmetries of Body, Brain and Cognition, 21(4-6), p. 649, supplied by “Assessing the reliability of an online behavioural laterality battery: A pre-registered study” by A. J. Parker, Z. V. Woodhead, P. A. Thompson, and D. V. Bishop, 2021, Laterality, 26. The participants used emotional emoticons to indicate the emotion they believed to be depicted by the facial stimuli. In the practice trial, two emoticons were used, which illustrated the emotions fear and surprise. In the experimental trial, a further four emoticons were used, which illustrated the emotions happiness, sadness, disgust and anger. The emoticons used were taken from Oleszkiewicz et al. (2017), as it was found that children aged between 4- and 8-years-old were able to accurately assign emotions to these emoticons. See Figure 3 for the emoticons used in the experimental trial. Figure 3.The Emoticon Stimuli used in the Experimental Trial of the Chimeric Face Task Note. The emoticon stimuli selected by the child participants to indicate which emotion they believed the facial stimuli to be depicting. The emotions depicted by the emoticons, from left to right, are; anger, disgust, happiness and sadness. Adapted from “Children can accurately recognize facial emotions from emoticons” by in A. Oleszkiewicz, T. Frackowiak, A. Sorokowska, and P. Sorokowski, 2017, Computers in Human Behavior, 76, p. 373. Procedure. The procedure used derives from Parker et al. (2021), however, it has been adapted accordingly for its use with children. The chimeric face task was administered remotely via Microsoft Teams, a video collaboration platform. The virtual meeting was only accessible by the participant and the researcher, via a unique uniform resource locator, meeting ID and passcode. The chimeric face task could be completed on a laptop, computer or electronic tablet, and participants were required to share their screen to allow for the delivery of verbal instructions. Children were accompanied by an adult family member who was asked to refrain from engaging in any verbal and non-verbal communication with their child during completion of the task. Prior to administration of instructions, participants completed an estimation of screen size. This involved placing a 8.56cm X 5.39cm card onto the screen and dragging a bar until the size of the card on the screen corresponded with the physical card possessed by the participant. This was to ensure that all instructions and stimuli were presented as the same size to all participants. Instructions were administered visually to the child participants, using visual-graphic symbols, example screens and visual stimuli taken from the study, to ensure that the child’s understanding of the task was not compounded by their language ability. The visual instructions were accompanied by verbal instructions, that omitted the use of vocabulary that would not typically be understood by children aged between 5- and 10-years-old. Following administration of the instructions, participants were familiarised to two symmetrically averaged faces depicting the emotions fear and surprise, and their corresponding emoticons, which would be used in the practice trial. During completion of the practice trial participants were exposed to each symmetrically averaged face and each chimeric face, twice, meaning they were exposed to a total of 8 stimuli. The practice trial was employed to acquaint the child to the procedure used in the experimental trial. Following the practice trial, participants were familiarised to the symmetrically averaged faces that comprised the chimeric faces used in the experimental trial, as well as their corresponding emoticons. These faces, and emoticons, depicted the emotions happiness, sadness, anger and disgust. Participants were verbally informed of the emotion depicted by stimuli and were instructed to click ‘next’ or indicate to their parent when they felt they had familiarised themselves with the stimuli presented. Participants were familiarised to the stimuli to ensure they knew which emotion each face and emoticon represented. The experimental trial was composed of four blocks. In each block the participants were exposed to the four symmetrically averaged faces, and the 14 chimeric faces, twice, meaning they were exposed to 32 stimuli per block, and 128 stimuli in total. Participants were exposed to the symmetrically averaged faces to assess their recognition of the emotion, and to the chimeric faces to determine the strength of their hemispheric lateralisation for facial emotion processing. Before being exposed to the stimuli participants were asked to fixate on a white cross in the middle of the screen for 1000ms to ensure the child was looking directly at the facial stimuli when it appeared. This was important as the facial stimuli was only presented for 400ms. Following the presentation of each facial stimulus the participants had 10400ms to provide a response before automatically advancing to the next screen. All participants were instructed to “decide how the face is feeling and click on/point to/touch the emoji that shows that feeling”. The instruction provided differed depending on whether the child was responding using an electronic mouse, touch screen device, or by pointing and having their parent select the response for them. The latter of which was used for children who did not have access to a touch screen device, and who were not yet able to independently control an electronic mouse. At three intervals during the chimeric face task, children were provided with the opportunity to take a break. During this break children received verbal praise and encouragement, the duration of the break was determined by the child. Administration of the chimeric face task took approximately 20-40 minutes. Scoring. A laterality index was calculated for each child, to determine their strength of lateralisation for facial emotion processing. The laterality index was calculated by calculating the number of times the participant selected the emoticon corresponding with the emotion depicted on the right and left side of the face. The following sum was then computed for each participant 100 X (No. of right hemiface responses – No. of left hemiface responses)/(No. of right hemispace responses + No. of left hemiface responses). Study Procedure Ethical approval was obtained from the Lancaster University Department of Psychology Ethics Committee. Consent was received from all schools who agreed to distribute the study information to parents. Parental consent was obtained on behalf of all child participants, and oral consent was sought from the child participants during the virtual meeting. The study was comprised of two parts, the first of which required parents to complete a series of questionnaires to provide a measure of the child’s demographic information, level of empathy, and autism severity. Parents were first presented with the demographic questionnaire to determine which additional questionnaires they were required to complete. If the parent’s responses on the demographic questionnaire indicated that their child had a diagnosis of ASD, then they were directed to, and required to complete, the EQ-Child and AQ-Child. If the parent’s response denoted that their child did not have a diagnosis of ASD they were only directed to, and required to complete, the EQ-Child. All questionnaires were completed on Gorilla (www.gorilla.sc), a cloud-based software platform for collecting data in the behavioural sciences (Anwyl-Irvine et al., 2020). All participants therefore completed the questionnaires remotely, on a personal electronic device. The questionnaires were compatible with a range of technological equipment, including a laptop, computer, electronic tablet and mobile phone. Following successful completion of the required questionnaires, parents received an email arranging a convenient date and time for their child to complete the second part of the study, which required their child to complete the chimeric face task. The data collected during completion of the chimeric face task was linked to the parental questionnaire responses via a unique participant ID code, which was allocated to parents following confirmation of participation. Following completion of the chimeric face task, a debrief sheet and certificate was sent to the parent’s email address.
Does implicit mentalising involve the representation of others’ mental state content?
implicit mentalising, co-representation, joint action, domain specificity
Implicit mentalising involves the automatic awareness of the perspectives of those around oneself. Its development is crucial to successful social functioning and joint action. However, the domain specificity of implicit mentalising is debated. The individual/joint Simon task is often used to demonstrate implicit mentalising in the form of a Joint Simon Effect (JSE), in which a spatial compatibility effect is elicited more strongly in a joint versus an individual condition. Some have proposed that the JSE stems from the automatic action co-representation of a social partner’s frame-of-reference, which creates a spatial overlap between stimulus-response location in the joint (but not individual) condition. However, others have argued that any sufficiently salient entity (not necessarily a social partner) can induce the JSE. To provide a fresh perspective, the present study attempted to investigate the content of co-representation (n = 65). We employed a novel variant of the individual/joint Simon task where typical geometric stimuli were replaced with a unique set of animal silhouettes. Half of the set were each surreptitiously assigned to either the participant themselves or their partner. Critically, to examine the content of co-representation, participants were presented with a surprise image recognition task afterwards. Image memory accuracy was analysed to identify any partner-driven effects exclusive to the joint condition. However, the current experiment failed to replicate the key JSE in the Simon task, as only a cross-condition spatial compatibility effect was found. This severely limited our ability to interpret the results of the recognition memory task and its implications on the contents of co-representation. Potential design-related reasons for these inconclusive results were discussed. Possible methodological remedies for future studies were suggested.
Pre-test: Selection of Suitable Stimuli Participants Twenty-five undergraduate students at Lancaster University were recruited via SONA systems (a University-managed research participation system) and gave informed consent to participate in an online pre-test that aided in the selection of suitable experimental stimuli for the main experiment. Ethical considerations were reviewed and approved by a member of the University Psychology department. Stimuli and Materials Pavlovia, the online counterpart to the experiment building software package PsychoPy (version 2022.2.0; Peirce et al., 2019), was used to remotely run the stimuli selection pre-test. One hundred images of common black-and-white animal silhouettes were initially selected and downloaded from PhyloPic (Palomo-Munoz, n.d.), an online database of taxonomic organism images, freely reusable under a Creative Commons Attribution 3.0 Unported license . All images were resized and standardised to fit within an 854 x 480-pixel rectangle. Design and Procedure An online pre-test was conducted to identify the recognisability of possible animal stimuli and to select the most recognisable set of 32 animal silhouettes to use in the main experiment. Recognisability was an important consideration because participants would only briefly glimpse at the animals; therefore, the ability to recognise the silhouettes quickly and subconsciously was paramount. The 100 chosen animal silhouettes (as outlined in the Stimuli and Materials section) were randomised and sequentially presented. Each image was displayed for 1000ms to match the duration of stimuli exposure in the final experimental design. The participant then rated each animal’s recognisability on a 7-point Likert scale (1 = Extremely Unrecognisable to 7 = Extremely Recognisable). Additionally, they were asked to guess each animal’s name by typing it in a text box, and to provide a confidence rating corresponding to each naming attempt (again, on a 7-point Likert scale, from 1 = Extremely Unconfident to 7 = Extremely Confident). To choose which 32 animals were included, the recognisability scores for each animal were summed, averaged, and sorted in descending order. Duplicate animal species were excluded by removing all but the highest-scoring animal of the same species. Because the 32nd place was tied between two animals which achieved the same recognisability scores, the animal with the highest name-guessing confidence rating was selected. Main Experiment Participants Sixty-five participants who have not previously participated in the pre-test gave informed consent to participate in the main experiment (M¬age = 23.93 years, SDage = 8.06; 49 females), 51 of whom were students/staff/members of the public at Lancaster University recruited via SONA systems or through opportunistic recruitment around the University campus (e.g., on University Open Days). The remaining 14 participants were A-level students around Lancashire, recruited as part of a Psychology taster event at the University. All participants had normal or corrected-to-normal vision and had normal colour vision. Past studies of the JSE obtained medium-to-large effect sizes (e.g., Shafaei et al., 2020; Stenzel et al., 2014). An a priori power analysis was performed using G*Power (Version 3.1.9.6; Faul et al., 2009) to estimate the participant sample size required to detect a similar interaction. Due to the novel adaptation made to the Simon task (thus possibly attenuating the strength of previously found effects) and the additional memory/recognition task, a conservative-leaning effect size estimate was used. With power set to 0.8 and effect size f set to 0.2, the projected sample size needed to detect a medium-small effect size, repeated measures, within-between interaction was approximately 52. Stimuli and Materials The online survey software Qualtrics (Qualtrics, 2022) was used to provide participants in the main experiment with information and consent forms, plus obtain demographic information and (for participants in the joint condition) interpersonal relationship scores (see Appendix A for a list of the presented questions). The Simon and Recognition Tasks were run using the PsychoPy on three iMac desktop computers with screen sizes of 60 cm by 34 cm and screen resolutions of 5120 x 2880 @ 60 Hz. Responses to the Simon task were recorded using custom pushbuttons (see Appendix B for images) assembled and provided by Departmental technicians. The 32 animals chosen via the pre-test to be used in the main experiment (Simon/Recognition task) were recoloured to be entirely in either blue (hexadecimal colour code: #00FFFF) or orange (#FFA500). Varying by trial, the animals were displayed either 1440 pixels on the left or the right from the centre of the screen (for an example, see Figure 1). Figure 1 Example of Stimuli Used in Simon Task Note. Diagram (a) contains a screenshot of the Simon Task in which the orange stimulus appeared on left, whilst diagram (b) depicts a blue stimulus appearing on the right. Design and Procedure Simon Task. For the Simon task, a 2 x 2 mixed design was employed, with Compatibility (compatible vs. incompatible) as a within-subject variable and Condition (individual vs. joint) as a between-subject variable. Participants were first individually directed to computers running Qualtrics to read and sign information and consent forms, and to provide demographic information. Afterwards, participants were guided to sit at a third computer, where they sat approximately 60 cm (diagonally, approximately 45° from the centre of the screen) away from the computer either on the left or right side, with a custom pushbutton set directly in front of them. They were instructed to use their dominant hand on the pushbutton. In the joint condition, each pair of participants sat side-by-side, approximately 75 cm beside their partner. In the individual condition, an empty chair was placed in an equivalent location next to the participant. In both conditions, participants were individually assigned a colour (either blue or orange) to pay attention to. Participants were instructed to “catch” the animals by pressing their pushbutton when an animal silhouette of their assigned colour appeared on the computer screen . Participants were not otherwise instructed to pay specific attention to any of the animal species, nor the location (left/right) that it appears in; the focus was solely on the animals’ colour. Crucially, participants were unaware of the recognition task which came afterwards. Sixteen out of the 32 animal silhouettes selected during the pre-test were chosen to be displayed to them during the Simon task. The 16 animals were further divided in half and matched to each of the two colours, such that each participant was assigned eight animals in their respective colours. The remaining unchosen 16 animals were used as foils in the Recognition Task. Participant sitting location (left/right), stimuli colour (blue/orange), and animals presented (as stimuli in the Simon task/ as foils in the Recognition task) were counterbalanced between participants. Additionally, stimuli presentation position (left/right, and by extension, compatibility/incompatibility) was pseudorandomised on a within-subject, per-block basis. After reading brief instructions, participants completed a practice section. When participants achieved eight more cumulative correct trials than incorrect/time-out trials, they were allowed to proceed to the main experiment. This consisted of eight experimental blocks, where each block contained 16 trials (which corresponded to the 16 chosen animals), totalling 128 trials. Half of the trials in each block (i.e., 8) were spatially compatible, while the remaining half were incompatible. Furthermore, each block contained the same number of (in)compatible trials for each participant (i.e., four of each compatible/incompatible trials per participant). Trials in which the coloured stimulus and its correct corresponding response pushbutton were spatially congruent were coded as compatible, whilst spatially incongruent trials were coded as incompatible trials. A mandatory 10-second break was included at the half-way point of the experiment (i.e., after block four, 64 trials). Each trial began with a fixation cross in the centre of the screen for 250 ms. Following this, colour stimuli (circles in the practice trials, animal silhouettes in the main experiment) appeared on either the left or right of the screen for 1000 ms. A 250 ms intertrial interval (blank screen) was implemented. If a participant correctly pressed their pushbutton when stimuli of their assigned colour appeared, they were met with the feedback “well done”. Incorrect responses (i.e., when a participant pressed their pushbutton when a stimulus not of their assigned colour appeared) or timeouts (i.e., failing to respond within 1000 ms) were met with the feedback “incorrect, sorry” or “timeout exceeded” respectively. In addition to recording accuracy (correct/incorrect responses), each trial’s reaction time (time elapsed between stimulus display and pushbutton response) was also recorded and coded as response variables. Regardless of participants’ response time, each stimulus appeared for the full 1000 ms, and feedback was only provided after a full second has elapsed. This deviated from the design of previously used Simon tasks—in some studies, each trial (and thus stimuli presentation) immediately terminated upon any type of response (e.g., Dudarev et al., 2021); in other studies, each stimulus was only displayed for a fraction of a second (e.g., 150 ms; Dittrich et al., 2012), after which was a response window during which the stimulus was not displayed at all. The design choice of fixing the stimuli presentation duration to 1000 ms irrespective of participant response was to ensure that each animal colour/species were displayed for an equal duration of time. This was important so as not to bias the incidental memory of participants towards trials wherein one participant was slower to respond (and would have therefore kept the stimulus on screen for longer, disproportionally encouraging encoding). Surprise Recognition Task. For the recognition task, a 2 x 2 mixed design was employed, with Colour Assignment (self-assigned vs. other-assigned) as a within-subject variable and Condition (individual vs. joint) as a between-subject variable. Colour Assignment refers to whether the animal was previously assigned to, and presented in the Simon task as, the participant’s personal colour (i.e., self-assigned) or their partner’s colour (in individual condition’s case, this simply refers to the not-self-assigned colour, i.e., other-assigned). After completing the Simon task, participants were each guided back to their individual computers which they had initially used to give consent and demographic information, so as to minimize bias from familiarity effects on memory. Using a PsychoPy programme, participants were shown 32 black-and-white animal silhouettes one-by-one and were asked two questions: (1) “Do you recall seeing this animal in the task before?”, with binary “yes” or “no” response options; and (2) “How confident are you in your answer above?”, with a 7-point Likert scale between 1 = Extremely Unconfident to 7 = Extremely Confident as response options. For both questions, participants used a mouse to click on their desired response. Participants were additionally instructed that it did not matter what colour the animals appeared as during the previous (Simon) task—so long as they remember having seen the silhouette at all, they were asked to select “yes”. There was no time limit on this task. Thirty-two animal silhouettes were presented, of which 16 were seen in the Simon task, while the remaining 16 yet-to-be-seen animal images were added in as foils in this recognition task. The participants’ responses to the two aforementioned questions were recorded as key response variables. Check Questions and Interpersonal Closeness Ratings. At the end of the study, participants were asked several check questions which, depending on their answers, would lead to further questions. For example, they were asked about whether they had any suspicions of what the study was testing, or whether they paid specific attention to, and/or memorised the animal species shown in the Simon task on purpose (see Appendix A for a full list of questions and associated branching paths). The latter questions served to identify whether participants had intentionally memorised the animals, which may undermine the usefulness of the data collected in the object recognition task. Additionally, participants in the joint condition were also asked to individually rate their feelings of interpersonal closeness with their task partner with two questions. The first was a text-based question which asks how well the participant knows their partner (Shafaei et al., 2020), with four possible responses between “I have never seen him/her before: s/he is a stranger to me.”, and “I know him/her very well and I have a familial/friendly/spousal relationship with him/her.” The next was question contained the Inclusion of the Other in the Self (IOS) scale (Aron et al., 1992), which consisted of pictographic representations of the degree of interpersonal relationships. Specifically, as can be seen in Figure 2, the scale contained six diagrams, each of which consisted of two Venn diagram-esque labelled circles which represented the “self” (i.e., the participant) and the “other” (i.e., the participant’s partner) respectively. The six diagrams depicted the circles at varying levels of overlap, as a proxy measure of increasing interconnectedness. Participants were asked to rate which diagram best described the relationship with their partner during the study. In following the steps of Shafaei et al. (2020), the first text-based question was included, and was used as a confirmatory measure for the IOS scale, the latter of which was the primary measure for interpersonal closeness. Figure 2 Inclusion of Other in the Self (IOS) scale
Malcolm Wong Aubrey Covill Elisha Moreton
An exploration of the psychological mechanism and effectiveness behind the co-creation process in advertising, based on the ‘Co-create by Sharp’ method.
Keywords: Co-creation, advertising, psychology, behaviour
Scholars have referred to co-creation as the interaction between firms and stakeholders to create value. Co-creation for product innovation and campaign delivery is a growing trend in today’s competitive market due to a demand for consumer-centric communication and product development strategies. Even when traditional research techniques are relevant for evaluating brand messaging, they are considered backwards looking. Traditional research techniques (e.g., interviews, questionnaires, focus groups) rely on companies’ terms rather than the customer’s domain, limiting stakeholders to only react to market offers instead of cooperating to build them. The application of co-creation techniques does not replace reactive research but is the new next step to building brand and campaign strategies. The Sharp Agency developed ‘Co-create by Sharp’, a co-creation methodology that aims to build campaign and brand strategies with a higher value of insight than other approaches. According to The Sharp Agency, their unique approach to co-creating ideas with stakeholders has demonstrated effectiveness in their clients’ performance (i.e., 400% of revenue increase, 33% growth speed, and 19% spending increase). However, the method lacks information that supports its efficacy, more specifically, an exploration of the perceptions of people involved in their co-creation methodology (i.e., co-creation participants, Sharp team members, and Sharp’s commissioning clients). This report aims to identify the presence of plausible psychological theories that could support the ‘Co-create by Sharp’ methodology. Accordingly, this study intends to explore the dynamics, perceived effectiveness, and limitations of the ‘Co-create by Sharp’ methodology through a series of individual interviews with the people involved in the process. The researcher worked as an intern in the Sharp Agency, and a qualitative experimental design was used to investigate the research objective. Three types of interviews were conducted to understand the ‘Co-create by Sharp’ process from its main perspectives: Co-creation participants, Sharp team members, and Sharp’s commissioning clients. Findings indicated that the ‘Co-create by Sharp’ method is supported by a specific psychological mechanism explained by Self-Determination and Implicit Self-esteem theories. Based on these theories, interviewees’ perceptions of co-creation suggest that the ‘Co-create by Sharp’ methodology generates participant engagement in brand co-creation. According to the literature reviewed, participant engagement increases the level of insight in co-creation outcomes. As a result, this report has determined that the ‘Co-create by Sharp’ methodology produces a chain of benefits that begins with psychological benefits and brand-self connection, resulting in higher campaign delivery effectiveness. In conclusion, the ‘Co-create by Sharp’ methodology appears to be supported by a psychological mechanism that motivates participants to co-create in developing campaign strategies and brand building. Moreover, co-creating with stakeholders as a next step to gathering data with market research techniques could increase customer value in campaign delivery.
The researcher worked as an intern in the Sharp Agency to better understand the company’s way of work and the ‘Co-create by Sharp’ method. The internship allowed the researcher to be involved in various steps of the co-creation method: 1) Attend co-create sessions and observe participant behaviour (see Appendix K and Appendix L). 2) Develop post-co-create decks of information, including sessions’ outputs. 3) Participate in strategic brainstorming sessions. 4) Collate evidence of the final results of messaging and visuals for campaign delivery. A qualitative experimental design was used to investigate the research objectives and provide answers to research questions. Three types of interviews were conducted with different participant profiles, including co-creation participants, Sharp team members and Sharp clients. Interview sessions lasted between twenty and thirty minutes, using a pre-determined discussion guide for each interview and received ethical approval. Interviews were designed to gather insights about co-creation perceptions from every person involved in the process. A qualitative design allowed interviewees to express freely their co-creation experience with The Sharp Agency. Considering the research aimed to explore people’s attitudes, it would not have been appropriate to use a quantitative method. Instead, a qualitative design allowed for gathering a spectrum of people’s observations and feedback. Sampling Representative sampling was used to obtain results that reflect each participant’s profile perspective. Interviewing involved five participants from the latest co-creation sessions moderated by Sharp, seven Sharp team members with roles involved in different stages of the co-creation process (including founders of the ‘Co-create by Sharp’ method), and three company commissioning clients that represent market leader companies (i.e., Medical Protection Service, Barbour ABI, and Lonza). Considering that Medical Protection Service (MPS) and Lonza are part of the healthcare industry and Barbour ABI provides data and intelligence to the construction industry, these companies manage technical language and require higher accuracy of message delivery. (Ekiyor & Altan, 2021; Mokhtariani et al., 2017). This project received ethical approval under the auspices of the Lancaster University Psychology Department (see Appendix M). Participants gave informed consent using a consent form sent and signed via e-mail (see Appendix B). Participants were additionally provided with a debrief sheet, including contact details, should they have further questions (see Appendix C). Materials Interviews were regulated using three discussion guides (see Appendix E, Appendix F, and Appendix G). These were devised based on the objectives of the investigation set collectively with Sharp. Each discussion guide responded to a specific question based on participants’ profiles (co-creation participants, Sharp team members, and commissioning clients. Participants were encouraged to elaborate on their answers as much as possible. When conducted virtually, interviews were recorded using the current version of Microsoft Teams, and in person, interviews were recorded using Apple’s Voice Memo app. Research Procedure Participants were introduced to the researcher by The Sharp Agency and invited to participate in a scheduled interview via Microsoft Teams or in Sharp’s headquarters in the case of Sharp team member participants. The interviewer followed a discussion guide that began with questions that allowed participants to introduce themselves and warm up to the conversation. It concluded with questions that aimed to obtain the most robust responses. For further analysis purposes, interviews were transcribed using the Otter.ai software.
Neural response to infant-directed speech: gamma band oscillatory activity in 4-month-old infants
Infant-directed speech; neural response; EEG; gamma oscillation
Infant-directed speech is an ostensive signal preferred by infants over adult-directed speech. We studied infants’ neural response to auditory stimuli by measuring gamma band oscillatory activity over the frontal area of the brain in response to ostensive infant-directed speech and non-ostensive adult-directed speech. Two groups of 4-month-old infants were presented with the same auditory stimuli, but the two groups differed in terms of visual stimuli (inverted vs. upright faces), being our study a part of a broader research project. We investigated only the auditory portion of the trial. We found that, in the inverted face group, the activation to the ostensive infant-directed speech was significantly enhanced while, in the upright group, this outcome was not found. These findings support the use of gamma band oscillations in assessing the basis of social communication and establish infants’ early specialization in understanding communicative signals directed to them.
Experimental Design We used data that had already been collected for a broader study, designed for the observation of the influence of auditory stimuli on face processing. In the main experiment, a total of 36 four-months-old infants was divided into two groups that differed on the visual stimulus presented at the end of each trial. Immediately after an auditory stimulus in IDS or ADS, the first group was presented with inverted faces, while the second group was exposed to upright faces. Participants in both groups were thus exposed to the same auditory stimuli, just before being presented to the visual stimuli, that were different depending on the group. In this research we focused only on the auditory portion of the trial, where participants were exposed to IDS or ADS (Fig. 1). Figure 1. Representation of the complete trial presented to infants. In every trial, 18 infants were presented with upright faces, while the other 18 were presented with inverted faces. However, each infant was exposed to auditory stimuli in ADS or IDS, regardless of the visual stimulus. The green rectangle shows the portion of the trial analysed in this dissertation. Participants Infants were recruited from the Lancaster Babylab database. All were free of any known neurological, ocular or auditory abnormality and met the screening criteria of normal birth, born full term (gestational age >37 weeks), in the normal weight range (>2500g) and with an Apgar score of at least 8 at five minutes after the birth. In our study we focused on infants’ neural response to the auditory stimuli (Fig. 1). However, the distinction between the two groups was preserved in order to observe possible differences between them. The group exposed to inverted faces included 18 infants (5 females, age range 117 to 161 days, M= 135.61 days). Thirteen additional infants were excluded owing to an insufficient number of artifact free segments (n=10), sleep (n=1), and technical issues during the experiment (n=2). The group presented with upright faces included 18 infants (5 females, age range 115 to 171 days, M= 145.22 days). 17 additional infants were excluded because of an insufficient number of artifact free segments (n=14) and technical issues during the experiment (n=3). In the final datasets (N=36) were included infants that provided artifact-free EEG recording in at least 10 trials within each experimental condition. Stimuli The auditory stimulus was the word “Hello” pronounced by a female voice using two different intonations: either IDS or ADS. The two words were recorded and edited with Audacity (v. 1.2.5) and Praat (v. 5.1) by setting a digitalization at 32-bit resolution and a sampling rate at 48 kHz. Both words were 850 ms long. The IDS stimulus had an average volume intensity of 61.86 dB, while the ADS stimulus had an average volume intensity of 61.50 dB. Apparatus Infants’ behaviour was video recorded for the entire duration of the test by a remote-control video camera placed behind the monitor. A pair of computer speakers situated behind the monitor were used for the presentation of the auditory stimuli. The infants’ EEG was recorded at a sampling rate of 500 Hz using a 124-channel Hydrocel Geodesic Sensor Nets (Electrical Geodesic Inc., Eugene, OR, USA). Procedure Infants sat on their parent’s lap at a distance of 70 cm from a computer monitor. Each trial started with a dynamic fixation grabber at the centre of the monitor, for the duration of 2150 ms. Then the attention grabber stopped moving and the auditory stimulus (in IDS or ADS) was released by loudspeakers positioned behind the monitor and lasting 850 ms. The attention grabber remained still for an interval randomly varying between 200 and 400 ms. Then the grabber disappeared and the visual stimulus was presented for 1000 ms. A blank screen as an inter-trial interval between 1000 and 1200 ms was inserted between successive trials. Auditory stimulus in IDS or ADS were presented in a random order with the following constraint: no more than three successive trials of the same kind in a row. The trials were presented as long as the infants were willing to look at them. When they became fussy, the experimenters played a dynamic spiral together with an attractive sound. The session ended when the infant could no longer be attracted to the screen. EEG measurement and data analysis The electrical potential was band-pass filtered between 0.3-100 Hz. The filtered EEG was then segmented into epochs including 600 ms before stimulus onset and 1400 ms following the stimulus onset for each trial. EEG epochs containing artifacts caused by body and eye movement were automatically eliminated, whenever the average amplitude of a 80 ms gliding window exceeded 55 µV at horizontal Electrooculogram (EOG) channels or 150 µV at any other channel. In addition to automatic rejection, each individual epoch was visually inspected for further epoch selection. When <10% of the channels contained artifacts, the contaminated channels were replaced by mean of spline interpolation, while segments in which >10% of the channels included artifacts were rejected. Infants exposed to upright faces contributed on average 17.5 artifact free trials to the IDS condition (range: 8 to 36) and 18.34 trials to the ADS condition (range: 9 to 39). Infants exposed to inverted faces contributed on average 20.89 artifact free trials to the IDS condition (range: 8 to 38) and 20.78 trials to the ADS condition (range: 10 to 39). In the artifact free segments induced gamma-band oscillations were uncovered through time-frequency analysis. These segments were imported into Matlab® and re-referenced to average reference through the free toolbox EEGLAB (v. 9.0.5.6b). The custom-made scripts collection WTools (available at request) was used to compute complex Morlet wavelets for the frequencies 10-90 Hz with 1 Hz resolution. A continuous wavelets transformation of single trials of EEG in each channel was performed, on 2000 ms long segments (600 ms pre-stimulus onset and 1400 ms after stimulus onset). The transformed segments were averaged for each condition separately. To remove the distortion in the time-frequency decomposition caused by convolution with the wavelets, 400 ms at each edge of the epochs were chopped, leaving a segment from -200 to 1000 ms around the auditory event. The average amplitude of the 200 ms pre-stimulus window was used as the baseline and was subtracted from the whole segment at each frequency. Based on prior findings (Parise & Csibra, 2013), we selected the scalp location over the forehead (the average of channels 3, 9, 10, 15, 16, 18, 22, 23, corresponding to Fp2, Fpz, Fp1, respectively, Figure 2), a time window from 200 ms to 600 ms, and 25 to 45 Hz frequency window. In order to verify that there were no significant differences between the accepted segment for each participant, a t-test between the average of accepted segments for each condition (speech) was performed and the same procedure was repeated for each group (face orientation). The mean amplitude was assessed by a repeated measure ANOVA with Speech (IDS x ADS) as a within subject factor, and Group as a between subject factor (upright x inverted). Paired-Sample t-tests were used for post hoc comparisons between the induced gamma-band oscillatory activity in response to IDS and to ADS. One-sample t-tests against 0 were used to assess whether the analysed gamma-band oscillatory activity differed significantly from the baseline. Figure 2. Sensor layout for the Electrical Geodesics Inc. (EGI) 124-channel hydrocel sensor net, showing the locations of the electrodes under study (circled in green), averaged for measurement of the oscillatory activation.
Examining the Effect of Anxiety on the Development of False Memory
memory, generalized anxiety disorder, confidence-accuracy calibration
Up till the late 70s, people believed their memory worked in similar to a video-recorder, accurately collecting and storing every information seen and heard. This belief was brought to question after researchers started thorough investigation on memory, and found that in actuality memory is highly impressionable and prone to numerous errors such as the formation of false memories. There now appears to have been found many causes for the formation of false memories. However, limited to no research exists on the effect of generalized anxiety disorder (GAD) on formation of false memories. The present study aimed to investigate the effect of GAD on the development of false memories by using the misinformation effect paradigm. Confidence-accuracy calibration (CAC) was assessed as a secondary analysis. Participants (N = 100) were recruited through online means and took part in a 15-45-minute-long experiment involving neutral stimuli. The experiment consisted of a video of an event and were subsequently asked to read a text description with misinformation after partaking in filler tasks. Afterwards their memory of the original event was tested. Results demonstrate that GAD and false memory are not significantly associated. CAC analysis revealed that participants were relatively aware of when their memory had been distorted by providing low confidence ratings to more inaccurate items and higher confidence ratings to accurately recalled answers. Additionally, false memories created due to misinformation was significantly observed, though GAD did have any influence over this. To conclude, GAD does not contribute to the formation of false memories.
A total of 100 participants were recruited and provided with an online link through social media sites, ages ranging from 18-50. Out of the recruited participants, 66 identified as females, 31 as males, two as non-binary and, one preferred not to say. The link begins with the consent sheet, and once the participants click to agree, they were then redirected to the start of the experiment. Participant’s anxiety was tested by administering a standardized and validated tool, the Generalized Anxiety Disorder Questionnaire (GAD-7) (Spitzer et al., 2006), (see Appendix B). GAD7 has seven rating scale questions, and the participant’s anxiety was calculated by assigning scores of zero (not at all), one (several days), two (more than half the days), and three (nearly every day). Samples questions include “worrying too much about different things?” and “becoming easily annoyed or irritable?”. For scores ten and above, GAD-7 has a specificity of 82% and sensitivity of 89% (Kroenke et al., 2007). Cut-off points for the scores are a score of five for mild anxiety, ten for moderate anxiety, and 15 for severe anxiety. For the present study, participants who scored nine and below were grouped under “low” anxiety, and participants who scored ten and above were grouped under “high” anxiety. The stimulus set developed by Okado and Start (2005) were used for this study. Two neutral stimuli were obtained, and each stimulus consisted of 50 coloured digital images. These were compiled into a short video, with each image displayed for 300ms, and the whole video lasting 150s. Out of the 50 slides, 12 of them were critical, meaning these slides consisted of an item that would later be altered in the text description of the event, hence providing the misinformation. The two stimuli are summarized below. Stimulus One is about a female named Rachel who was doing her work at home, then feels hungry and checks her refrigerator for food, sees that there is not much at hand, and so goes grocery shopping. She was seen viewing different aisles for grocery and sees a friend in there as well. She then pays the bill and takes the elevator back home and stores the food away. (See Appendix C for the critical images) Stimulus Two is about a male student named Nicholas who was just seen leaving his classroom to go sit on a bench in the hallway, studying between classes and runs into three friends: a male (Henry) who displays his new shirt, another male (Frank) who wanted to know when an exam was scheduled, and a female (Stephanie) whose conversation was interrupted by a phone call. (See Appendix F for the critical images) Text descriptions derived from Okado and Stark’s (2005) stimulus set were used for the present study. For both Stimulus One and Stimulus Two, 12 critical details from the original event were altered in the text description, with every other detail remaining true to the original event. To give an example of a critical detail, in stimulus One’s original event a woman was seen picking up two bananas, whereas in the text description it was written, “She started with the healthy items and picked up five bananas.” (See Appendix D and G). Recognition test involving three choice options derived from Okado and Stark (2005) were used for the present study. The test was composed of 18 detailed questions concerning the video presented at the beginning (the original event phase). Out of the 18 questions, 12 were critical questions (i.e., regarding the events that were changed in the text description), and six were control questions (i.e., regarding events that were consistent throughout the video and text description). After each question participants reported their confidence in their response on a scale of 0-100, where zero indicated not at all confident and 100 indicated extremely confident. A sample critical question was, “In the fruits section, how many bananas did Rachel pick up?” Participants were required to choose one answer out of the three: (1) one banana (filler option), (2) two bananas (as seen from the original event’s video), and (3) five bananas (altered detail presented in the text description). Control questions were also akin to critical questions, e.g., “Where does Rachel put her shopping bags in the kitchen?” For answers: (1) on the counter (as seen from the original event’s video), (2) on the floor (filler option), (3) on the table (filler option). (See Appendix E and H). The current research was designed as a 2x2x2 mixed factorial study. All participants had to complete all aspects of the experiment; henceforth, the memory accuracy for control and critical items were within-subject factors. The levels of anxiety (high and low) and stimulus (one and two), were between-subject factors. Participants were tested individually online and were informed they are partaking in a study concerning memory and mood. The experiment was created online in Qualtrics, and upon viewing, participants are first required to consent. The consent sheet had also explained that the study is completely voluntary and participants can withdraw at any point. Subsequently, participants were to either watch stimulus One or Two (the two videos were set to view randomly), and a timer was set to ensure no skipping was allowed. Immediately afterwards, participants had to fill in few demographic questions pertaining to their age, education, and employment (see Appendix A). Afterwards, they were required to complete the GAD-7. These two questionnaires served as a filler task to ensure sufficient time to allow some memory decay between watching the video of the event and reading the text description of the event. Next, participants read the altered text descriptions of the original event shown in the video. Participants were unaware of the changes brought and were told to read the text descriptions which had described the events from the original video. Akin to the video, a two-minute timer was set to ensure participants do not skip the text descriptions. Thereupon, participants were diverted to a game of sudoku, where they would spend at least five minutes playing it. They were instructed that we were interested in knowing how individuals play games and so were not aware of the true nature of the game, which was to serve as a second filler task. Lastly, participants completed the recognition memory test, where they had to choose the correct answer out of the three response options and to indicate their confidence for each answer to assess the C-A relationship. CAC layout is relatively simple by computing the accuracy for each level of confidence. When perfect calibration occurs, it is a straight line with the decisions being made at each level of confidence are all correct. Once completed, participants were thanked for their time spent on the experiment and presented with the debrief sheet explaining the true nature of the study The debrief sheet was provided with international and local numbers for people from different continents should they need to seek immediate assistance. Participants spent around an estimate of 15-45 minutes to complete the experiment.