Can better linguistic fluency improve the memorability and credibility of a sentence?
Linguistic Fluency, Alliteration, Advertising,Memory,Credibility
Processing fluency is often defined as how easy information is to comprehend based on a range of characteristics. One form of processing fluency is linguistic fluency, which refers to how easy a sentence is to interpret, regardless of the information within it. Some research suggests that disfluency can increase the recall of material, but this is contested. Previous studies have also shown that the linguistic fluency of a sentence can be improved with literary devices, such as rhyme, and that this can result in better perceptions of credibility. Research has yet to investigate how alliteration, as an example of linguistic fluency, could improve perceptions of credibility and the memorability of a sentence. This research investigated this by operationalising lists of alliterating and non-alliterating aphorisms, alongside measures of self-reported credibility and memorability, in a between-subjects study. Results of two independent t-tests provided two significant results, suggesting that better linguistic fluency improves the credibility and memorability of a sentence. Implications for researchers, the legal system and advertising are discussed.
Materials The preliminary five aphorisms were provided by Astroten with five further aphorisms being added to increase the power of the study. Aphorisms that were selected came from various literary examples, such as quotes from English Literature (Williams, 2011). Alternatively, some aphorisms were created using the definition “a short clever saying that is intended to express a general truth” (Cambridge Dictionary, 2022). The most common alliterating aphorisms, such as “All roads lead to Rome”, were purposefully avoided so that the effect of familiarity had a reduced effect on the memorability self-report. When creating the non-alliterating aphorisms, alliterating words were exchanged for non-alliterating words using a thesaurus so that the change in alliterative properties did not affect the overall meaning. The alliterating and non-alliterating aphorisms were kept divided into two different lists and were counterbalanced in a random order for each participant (Appendix C). Participants were asked to rate the credibility of the aphorisms based on a Likert scale of 1-9, in parallel with the scale used by McGlone and Tofighbakhsh (1999). Participants were asked to complete two games of Sudoku as a filler task (Appendix D). The grids were designed so that participants would begin with the easier version and move on to a more challenging version to ensure that the task occupied the full amount of time. Instructions were provided so that those who were unfamiliar with the game were still able to attempt the task. 18 Additionally, participants were given a piece of paper with 10 individual sections to write down as many of the aphorisms as they could remember at the end of the study. They were also provided with a pen, and time was kept using a watch. Design This study used a between-subjects design. This was chosen because there was a strong chance that order effects would impact the results of the memory test in a repeated measures design, due to the similarity between the alliterating and non-alliterating aphorisms. Choosing to mix the aphorisms could have resulted in demand characteristics affecting the results as the disparity between them would have been obvious to the participant. This is something that Oppenheimer and Frank (2008) were also keen to avoid. A quantitative data collection approach was taken because it was judged as the most appropriate way to measure memory, as well as facilitating comparison with other studies that have employed similar methods (McGlone & Tofighbakhsh, 1999; Kara-Yakoubian et al 2022). Participants were either part of the alliterating or non-alliterating aphorisms condition. Procedure Ethical approval for this study was given by the supervisor of this research, in line with Lancaster University Psychology Department protocols (Appendix E). When participants were approached to take part in the study they were first asked to read an information sheet (Appendix F) followed by a consent form, completion of which evidenced their informed consent to take part. Participation began in a quiet room within the university library. It was ensured that they could spare 20 minutes to take part and that they had turned off their phones before the study began. They began the study by rating each aphorism in 19 their list on a scale of 1-9 based on how credible they thought the aphorism was. The instructions were read to them, but they also had the opportunity to read them if they were unsure (Appendix G). They were then given three minutes to memorise as many of the aphorisms as possible. Following this, participants spent 10 minutes completing the Sudoku, with instructions again read to them and provided on the sheet. Once the 10 minutes were complete the participants were asked to spend five minutes trying to recall as many of the aphorisms from their list as possible by writing them down (Appendix H). They were given one point for every aphorism they could remember correctly. No points were given if the participants could only remember parts of the aphorism. As short-term memory is often described as being 7+/-2 (Miller 1956), memorisation of the entire list would likely have been impossible. Therefore, a prompt was added by reading the participant the first word from each of their aphorisms after three minutes. This aligns more closely with advertising research, which frequently measures prompted recall (Romaniuk, 2006; Charlesworth et al, 2022). On completion, participants were thanked for their participation in the research and given their £5 payment. They were also provided with a debrief sheet (Appendix I) that provided details of resources related to the study and the contact details of the researcher and supervisor.
Inner Speech and Its Role in Purchasing Decision-Making Process: Analysis of Within-Subjects Experiment and Questionnaires
Inner speech, memory, decision-making, purchasing behaviour.
Inner speech is a cognitive function related to language processes. Based on its functions reflecting information processing and memorising, it may link to the purchasing process, which includes searching and evaluating product information. Inner speech may also help people think and imagine using the product in the future during their purchasing process. This study discussed and investigated the role of inner speech in the purchasing process and how it might affect the decision-making time. This study also mentioned how inner speech may be identified and suppressed. Participants’ data was collected through experiments and several questionnaires. The findings indicated that inner speech might help people in Information Search and Alternative evaluation and affect decision time. The findings also suggested what people may consider and how they use inner speech. By uncovering the potential relationship between the purchasing process and inner speech, this research provided valuable information for marketing and psychology research fields. It gave companies some suggestions for practical use, reflecting how people may use inner speech during the purchasing process.
This study was approved by ethics committees at Lancaster University. There were no ethical issues for researchers managing the personal information. The participants’ information remained anonymous and were assigned subject ID (P01, P02, P03…, P30 in Experiment 1 and PCT01, PCT02, PCT03…, PCT30 in Experiment 2). All data were stored anonymously with no identifiable information. Participants were given the Participant Information Sheet (PIS) before participating in the experiments. On the day of testing, they asked any questions they might have, then consented to attend the experiment in person or via online platforms like Microsoft Teams, Zoom, or Google Meet to ensure that the suppression was active when needed. The experiment took approximately 30 minutes, including answering all questionnaires. The experiment was held in the participant’s home or a place where no one spoke so that the participant would not be disturbed by any chance. Experiment 1 Participants G*power suggested 52 participants within groups using t-tests and multiple mixed linear regression models, with a .4 effect size and .05 (5%) a-error probability in 80% power (1-b error of probability) (Brysbaert, 2019). Thirty participants were recruited in this experiment with no record or history of neurophysiological disorders, such as dyslexia or aphasia, to ensure that no conditions influence the result and affect the participant to complete the tasks in the experiment. The recruitment process included in-person invitations around campus and social media messages to reach diverse participants. Although only 30 participants were recruited in this experiment, the results of the t-tests suggest that the effect size (see Experiment 1 result section) may be enough for testing the hypothesis. Design This study was an experimental within-subjects design. Participants simulated purchase experience in the suppression task and the control task without interference assigned to them. The independent variables were self-rating agreements on information search and alternative evaluation and participants’ average decision time in the suppression and control tasks. The dependent variables were inner speech frequency in five dimensions measured by the Inner Speech Frequency Questionnaire (VISQ). Quantitative data were analysed using R to conduct t-tests, GLMM and CLMM. Secondly, qualitative data were collected through questionnaires and categorised into different variables to identify why participants made the decisions and their inner speech content during the purchasing process. Overall, the experiment aims to investigate how people use inner speech during purchasing and whether Articulate Suppression task and task without interference influenced decision time and agreement score on information search and alternative evaluation. Materials Stimuli Participants viewed six product sets (stimuli), which information was copied from the official website. To prevent participants from focusing on the effect of the products’ brands and prices (Albari & Safitri, 2020), the products in each set were the same brand with similar or the same price, unisex, and recognisable, although these products might not exist or remain the latest information on the market. Two-item Statement Questions (see Appendix B) Participants rated the two statements on a seven-point Likert score from strongly disagree to strongly agree (Maity & Dass, 2014) to identify the Information Search and Alternative evaluation agreement level between tasks. Then, participants were asked: “Which product did you choose? Why?” after each purchasing decision. Variety of Inner Speech Frequency Questionnaire (VISQ, see Appendix C) The Inner Speech Frequency Questionnaire (Alderson-Day et al., 2018) included twenty questions asking participants to generally rate their inner speech frequency after the mock e-commerce purchasing tasks with a 7-point Likert scale ranging from "Never" to "All the time". Questions 7 and 15 were reversely coded; the value should be reversely calculated when doing analysis. Experiment 1 Qualitative Questions (ExpQ1, see Appendix D) After participants finished all the tasks (six decisions), they were asked to answer three questions at the end of the experiment. These questions gathered qualitative data about the participants’ experiences during the mock e-commerce purchasing tasks and what they had in mind. Procedure Figure 2 illustrates the diagram of Experiment 1. Participants were invited and consented to join the research to do Suppression and Control (without interference) tasks. Each task contained three product sets; participants were asked to imagine and choose a product for themselves or a friend according to the provided information on the mock e-commerce channel (Maity & Dass, 2014). The screen of the researcher or participants presented the information, including the price and details of the product set. Since these two tasks are counterbalanced and randomly ordered, participants repeated the decision-making process three times in the control task and the other three in the suppression task. After each decision, participants answered the two-statement questionnaire and explained which products they chose and why they chose them. According to different tasks, they started with the control task by themselves. However, they were asked to practise counting out loud from 1 to 4 following 160 bpm metronome sounds until the researcher ensured they remained suppressed before starting the suppression task. Then, they answered VISQ, which measured their inner speech frequency and qualitative questionnaires (ExpQ1) to understand how they used inner speech when viewing the products in the last part of the study. Analysis R was used to analyse the quantitative data to identify the task differences via t-tests and the relationship between variables in two tasks via Generalised Linear Mixed Effect Models (GLMM) and Cumulative Link Mixed Model (CLMM). When conducting the GLMM with family gamma, the quantitative data will follow the standard procedure of data trimming and keep the trimmed data within 5% or 2.5 standard deviations (Berger & Kiefer, 2021). The qualitative coding scheme (See Appendix F) was created to identify what participants considered and what they said to themselves using inner speech during the experiment. The coding process involved re-reading the data to identify and assign relevant contexts to the appropriate categories. For example, if participants mention that they have used the product before, the value of the variable “Memory” increases by one unit. These variables were then calculated to identify what factors influenced participants’ purchasing decision-making more. Following the same coding scheme, what kind of inner speech was used when viewing the products could also be found. For example, people may ask themselves questions or repeat the product in mind. In summary, Quantitative and qualitative data were analysed to report the results for different purposes and test the hypothesis in this research. Figure 2 The Diagram of Experiment 1 Procedure Note: Participants were required to do suppression and control tasks, the order was randomised and counterbalanced. The products presented during the tasks were also randomised. Experiment Optimising The task without interference in Experiment 1 may not be a reasonable control task since it might include the secretary task effect, as participants were asked to do both tasks and be influenced after they did the suppression task when they were doing the control task. As a secretary task, the finger-tapping task, which has been used in inner speech experiments, could be the better control task in Experiment 2 (Emerson & Miyake, 2003; Wallace et al., 2009). Although Finger-tapping might influence working memory’s function and influence people to memorise (Armson et al., 2019; Kane & Engle, 2000; Moscovitch, 1994; Rose et al., 2009), Rogalsky et al. (2008) also mentioned that the performance of people’s understanding of complex sentences might decrease but not as much as suppression occur. Therefore, doing the second experiment was motivated to replicate the results with a better control condition involving Finger-tapping. Experiment 2 Participants Based on the findings of Experiment 1, another 30 participants were recruited with the duplicate requirements as the first experiment. The recruitment requirement and process were the same as in the previous experiment. Design The independent variables were similar to Experiment 1, while the only difference was that the control task here had been changed into the Finger-tapping task. The goal of the whole design is to replicate the results of Experiment 1 to investigate the role of inner speech in the purchasing process. Materials Experiment 2 applied the same materials used in Experiment 1. The only difference was the qualitative questions after tasks. In Experiment 1, participants answered “Experiment 1 Qualitative Questions” at the end of the experiment. However, to better understand the difference between tasks, they were asked to answer a similar questionnaire (see below) after each task to discover the inner speech used in the two tasks. Experiment 2 Qualitative Questions (ExpQ2, see Appendix E) Participants were asked to answer three questions about their experiences during the mock e-commerce purchasing tasks and what they had in mind for the Suppression and Finger-tapping tasks separately. Procedure The procedure was the same as the first experiment, except for adjusting the control task and the order of the qualitative questionnaire (ExpQ2). Figure 3 illustrates that participants were invited to the experiment using the same stimuli, similar questionnaires, and the same method of presenting stimuli (participants joined in person or via online platforms) with Suppression and Finger-tapping tasks. Participants were asked to practice counting 1,2,3,4 out loud or tapping their index, middle, ring, and little fingers in order (see which task came first) following metronome beats at 160 bpm before the researchers decided to move on. They were asked to view the product set by imagining choosing one for a friend or themselves three times in each task. Participants answered two statements and answered what product was chosen and why after each decision they made. Then, they were asked to answer three Qualitative questions (Appendix E) after each task. They repeated another task in the same process afterwards with a 2-minute break between tasks. After they finished the Finger-tapping and Suppression tasks, they answered VISQ questions at the end of the experiment. Analysis R was also used to analyse the quantitative data for the same purposes and followed the same data-trimming procedure if needed. The same coding scheme was followed to generate the result that could replicate and optimise the clarity of the Experiment 1 results. Overall, the second experiment is to generate the same or more evident results as Experiment 1 and to find more valuable information for the different inner speech used between tasks. In conclusion, these two experiments and the analysis might give this research a deeper understanding of inner speech and its role and provide more precise information on how inner speech may related to the purchasing process. Figure 3 The Diagram of Experiment 2 Procedure Note: Participants were required to do suppression and control tasks, the order was randomised and counterbalanced. The products presented during the tasks were also randomised.
inner speech, purchasing behaviour, memory, decision-making.
Methods Section: This study was approved by ethics committees at Lancaster University. There were no ethical issues for researchers managing the personal information. The participants’ information remained anonymous and were assigned subject ID (P01, P02, P03…, P30 in Experiment 1 and PCT01, PCT02, PCT03…, PCT30 in Experiment 2). All data were stored anonymously with no identifiable information. Participants were given the Participant Information Sheet (PIS) before participating in the experiments. On the day of testing, they asked any questions they might have, then consented to attend the experiment in person or via online platforms like Microsoft Teams, Zoom, or Google Meet to ensure that the suppression was active when needed. The experiment took approximately 30 minutes, including answering all questionnaires. The experiment was held in the participant’s home or a place where no one spoke so that the participant would not be disturbed by any chance. Experiment 1 Participants G*power suggested 52 participants within groups using t-tests and multiple mixed linear regression models, with a .4 effect size and .05 (5%) a-error probability in 80% power (1-b error of probability) (Brysbaert, 2019). Thirty participants were recruited in this experiment with no record or history of neurophysiological disorders, such as dyslexia or aphasia, to ensure that no conditions influence the result and affect the participant to complete the tasks in the experiment. The recruitment process included in-person invitations around campus and social media messages to reach diverse participants. Although only 30 participants were recruited in this experiment, the results of the t-tests suggest that the effect size (see Experiment 1 result section) may be enough for testing the hypothesis. Design This study was an experimental within-subjects design. Participants simulated purchase experience in the suppression task and the control task without interference assigned to them. The independent variables were self-rating agreements on information search and alternative evaluation and participants’ average decision time in the suppression and control tasks. The dependent variables were inner speech frequency in five dimensions measured by the Inner Speech Frequency Questionnaire (VISQ). Quantitative data were analysed using R to conduct t-tests, GLMM and CLMM. Secondly, qualitative data were collected through questionnaires and categorised into different variables to identify why participants made the decisions and their inner speech content during the purchasing process. Overall, the experiment aims to investigate how people use inner speech during purchasing and whether Articulate Suppression task and task without interference influenced decision time and agreement score on information search and alternative evaluation. Materials Stimuli Participants viewed six product sets (stimuli), which information was copied from the official website. To prevent participants from focusing on the effect of the products’ brands and prices (Albari & Safitri, 2020), the products in each set were the same brand with similar or the same price, unisex, and recognisable, although these products might not exist or remain the latest information on the market. Two-item Statement Questions (see Appendix B) Participants rated the two statements on a seven-point Likert score from strongly disagree to strongly agree (Maity & Dass, 2014) to identify the Information Search and Alternative evaluation agreement level between tasks. Then, participants were asked: “Which product did you choose? Why?” after each purchasing decision. Variety of Inner Speech Frequency Questionnaire (VISQ, see Appendix C) The Inner Speech Frequency Questionnaire (Alderson-Day et al., 2018) included twenty questions asking participants to generally rate their inner speech frequency after the mock e-commerce purchasing tasks with a 7-point Likert scale ranging from "Never" to "All the time". Questions 7 and 15 were reversely coded; the value should be reversely calculated when doing analysis. Experiment 1 Qualitative Questions (ExpQ1, see Appendix D) After participants finished all the tasks (six decisions), they were asked to answer three questions at the end of the experiment. These questions gathered qualitative data about the participants’ experiences during the mock e-commerce purchasing tasks and what they had in mind. Procedure Figure 2 illustrates the diagram of Experiment 1. Participants were invited and consented to join the research to do Suppression and Control (without interference) tasks. Each task contained three product sets; participants were asked to imagine and choose a product for themselves or a friend according to the provided information on the mock e-commerce channel (Maity & Dass, 2014). The screen of the researcher or participants presented the information, including the price and details of the product set. Since these two tasks are counterbalanced and randomly ordered, participants repeated the decision-making process three times in the control task and the other three in the suppression task. After each decision, participants answered the two-statement questionnaire and explained which products they chose and why they chose them. According to different tasks, they started with the control task by themselves. However, they were asked to practise counting out loud from 1 to 4 following 160 bpm metronome sounds until the researcher ensured they remained suppressed before starting the suppression task. Then, they answered VISQ, which measured their inner speech frequency and qualitative questionnaires (ExpQ1) to understand how they used inner speech when viewing the products in the last part of the study. Analysis R was used to analyse the quantitative data to identify the task differences via t-tests and the relationship between variables in two tasks via Generalised Linear Mixed Effect Models (GLMM) and Cumulative Link Mixed Model (CLMM). When conducting the GLMM with family gamma, the quantitative data will follow the standard procedure of data trimming and keep the trimmed data within 5% or 2.5 standard deviations (Berger & Kiefer, 2021). The qualitative coding scheme (See Appendix F) was created to identify what participants considered and what they said to themselves using inner speech during the experiment. The coding process involved re-reading the data to identify and assign relevant contexts to the appropriate categories. For example, if participants mention that they have used the product before, the value of the variable “Memory” increases by one unit. These variables were then calculated to identify what factors influenced participants’ purchasing decision-making more. Following the same coding scheme, what kind of inner speech was used when viewing the products could also be found. For example, people may ask themselves questions or repeat the product in mind. In summary, Quantitative and qualitative data were analysed to report the results for different purposes and test the hypothesis in this research. Experiment Optimising The task without interference in Experiment 1 may not be a reasonable control task since it might include the secretary task effect, as participants were asked to do both tasks and be influenced after they did the suppression task when they were doing the control task. As a secretary task, the finger-tapping task, which has been used in inner speech experiments, could be the better control task in Experiment 2 (Emerson & Miyake, 2003; Wallace et al., 2009). Although Finger-tapping might influence working memory’s function and influence people to memorise (Armson et al., 2019; Kane & Engle, 2000; Moscovitch, 1994; Rose et al., 2009), Rogalsky et al. (2008) also mentioned that the performance of people’s understanding of complex sentences might decrease but not as much as suppression occur. Therefore, doing the second experiment was motivated to replicate the results with a better control condition involving Finger-tapping. Experiment 2 Participants Based on the findings of Experiment 1, another 30 participants were recruited with the duplicate requirements as the first experiment. The recruitment requirement and process were the same as in the previous experiment. Design The independent variables were similar to Experiment 1, while the only difference was that the control task here had been changed into the Finger-tapping task. The goal of the whole design is to replicate the results of Experiment 1 to investigate the role of inner speech in the purchasing process. Materials Experiment 2 applied the same materials used in Experiment 1. The only difference was the qualitative questions after tasks. In Experiment 1, participants answered “Experiment 1 Qualitative Questions” at the end of the experiment. However, to better understand the difference between tasks, they were asked to answer a similar questionnaire (see below) after each task to discover the inner speech used in the two tasks. Experiment 2 Qualitative Questions (ExpQ2, see Appendix E) Participants were asked to answer three questions about their experiences during the mock e-commerce purchasing tasks and what they had in mind for the Suppression and Finger-tapping tasks separately. Procedure The procedure was the same as the first experiment, except for adjusting the control task and the order of the qualitative questionnaire (ExpQ2). Figure 3 illustrates that participants were invited to the experiment using the same stimuli, similar questionnaires, and the same method of presenting stimuli (participants joined in person or via online platforms) with Suppression and Finger-tapping tasks. Participants were asked to practice counting 1,2,3,4 out loud or tapping their index, middle, ring, and little fingers in order (see which task came first) following metronome beats at 160 bpm before the researchers decided to move on. They were asked to view the product set by imagining choosing one for a friend or themselves three times in each task. Participants answered two statements and answered what product was chosen and why after each decision they made. Then, they were asked to answer three Qualitative questions (Appendix E) after each task. They repeated another task in the same process afterwards with a 2-minute break between tasks. After they finished the Finger-tapping and Suppression tasks, they answered VISQ questions at the end of the experiment. Analysis R was also used to analyse the quantitative data for the same purposes and followed the same data-trimming procedure if needed. The same coding scheme was followed to generate the result that could replicate and optimise the clarity of the Experiment 1 results. Overall, the second experiment is to generate the same or more evident results as Experiment 1 and to find more valuable information for the different inner speech used between tasks. In conclusion, these two experiments and the analysis might give this research a deeper understanding of inner speech and its role and provide more precise information on how inner speech may related to the purchasing process.
Pitch-Brightness Correspondence in Four-month-old Infants
Adults, children, and infants as young as 10-months have been shown to appreciate a correspondence between auditory pitch and visual brightness, with most participants associating high-pitch with brighter stimuli and low-pitch with darker stimuli. Research across ages is vital for understanding more about the developmental trajectory of crossmodal correspondences. The present study used preferential looking to examine the sensitivity of 4-month-old infants to the pitch-brightness correspondence. Following Mondloch and Maurer (2004), infants were presented with a display of two balls bouncing simultaneously. One ball had a dark surface-brightness, whilst the other had a brighter surface. A single, high or low-pitch sound accompanied the bounce of both balls onto the surface. The research examined whether infants looked differentially to the ball which adults would generally classify as matching. Infants did not look significantly longer to the ball with the congruent pitch-brightness matching. Infants did however look preferentially towards the black ball across trials. It is proposed that this could be the result of the brightness-weight correspondence, whereby darker objects are thought of as heavier than brighter objects. It is therefore possible that infants look longer towards the black ball as it is the heavier ball which should produce the sound, regardless of pitch.
Animations were displayed on a 49cm x 39cm screen, surrounded by black card and screens to block-out excess light and other distractions. Initially, infants were seated (legs stretched forwards) on their caregiver’s lap for the experiment. In this position infants tended to lean forwards, looking towards the floor, meaning that the amount of codeable looking-time was very limited; this procedure was therefore abandoned after four infants had been tested and these infants were excluded from the sample. To increase looking towards the display new approaches were taken. Nine infants were seated 80cm from the screen in a supportive, from-birth highchair. Fourteen infants were seated in an alternative position on the caregiver/researcher’s lap. Infants were now held in a relatively upright position to reduce the likelihood that infants would look towards the floor or their feet. How infants were seated was decided by considering: infants’ head-support, familiarity with high-chair, and infant reactions. It was not thought that being in the high-chair or on the lap would significantly affect looking behaviour. All animations involved variants of balls bouncing on a horizontal surface. All balls had a diameter of 4cm and were identical to one another aside from their surface brightness. The brightness of balls was measured in candela per square meter (cd/m²) using a lux-meter. A higher cd/m² reading equates to a higher degree of luminosity/brightness. The balls appeared to bounce on a medium brightness (39.52cd/m²), green surface, which had a 49cm diameter. The background of displays was a diffused cloud image which was also medium brightness (57.06cd/m²). The image was blurred slightly to reduce contrast and make the background less visually interesting. It was important that the surface and background had a medium brightness and were not distracting, so as not to alter the effect of ball brightness. Previously, white dots on a black background have been used to portray depth; alternatively this experiment used the clouds and converging-line surface to depict 3-Dimensions. In the familiarization phase there was one ball of standard-brightness (53.86cd/m²) with a diameter of 4cm. This ball moved up and down along a 25cm vertical axis, stopping for 0.05s at the bottom and 0.1s at the top. The up-down motion of the ball gave the impression that it was bouncing on the surface. The bounce was accompanied by a sound of standard-pitch (782Hz) which lasted for 0.25s. The familiarization trial was presented to indicate to infants that a single ball produces a single noise when it hits a surface. This was important for the test trials as we did not want infants to perceive that the balls in unity were producing the sound. The standard-brightness and standard-pitch of this ball could also be used as reference-points for the brightness and pitch in test trials. The test animations consisted of three balls, each with a diameter of 4cm. The standard-brightness ball (53.86cd/m²) from the familiarization phase remained stationary at the centre of the surface as a reference point. Alongside the standard ball there were two test balls. Both balls differed only in terms of their surface-brightness. One of the balls had a duller, black surface-brightness (6.3cd/m²) and the other had a brighter, white surface-brightness (144.25cd/m²). Two, independent, vertical trajectories of 25cm formed the path of movement for each ball. Similar to the standard animation, the balls bounced on the surface in synchrony, to either side of the stationary ball (see Figure 1); stopping for 0.05s at the bottom and 0.1s at the top. As the balls hit the surface, a higher-pitch (2096Hz) or a lower-pitch (228Hz) sound was produced which lasted for 0.25s. Figure 1. These figures are screenshots of the animations seen by infants. The two shots display how the two balls moved in synchrony along vertical trajectories. The pitch of a sound can affect its perceived loudness. Controlling for sound loudness was crucial because of the correspondence between loudness and brightness (Marks, 1989). To ensure that loudness was not responsible for the effect, the perceived loudness of sounds were equalized. dBA (A-weighted decibels) is a measure of relative intensity perceived by the human ear, weighted for frequency (Plack, 2013). To ensure that perceived loudness did not vary, it was important that sound dBA was approximately the same. A sound-level meter (placed where the infant would sit) was used to measure the dBA of each sound. When sounds were created in Audacity, they were produced with equivalent amplitude. However when the sounds were played, the medium-pitch (782Hz) sound produced a higher 77.2dBA , compared to 72dBA and 71.3dBA for the high (2096Hz) and low-pitch (228Hz) sounds respectively. This meant that the medium-pitch sound would be perceived louder. To compensate for this, a 6dB gain was added to the high and low-pitch sounds. Therefore the relative loudness of the sounds had a much smaller range of values: 76dBA (high-pitch), 76.6dBA (low-pitch), and 77.2dBA (medium-pitch). Although the dB of two sounds needed to be increased, the frequencies of all sounds are within the normal hearing range of 20Hz to 20kHz (Plack, 2013). To confirm that these tones sounded psychologically equivalent, four adults listened to the sounds and were asked ‘Does any tone sound louder than any other tone?’ All participants reported that sounds had equivalent volumes. Design The dependent variables in this study were looking-time and number of fixations to the white and black balls. These variables were measured to examine whether infants look preferentially to congruent/incongruent pitch-brightness displays to determine whether they appreciate the pitch-brightness correspondence. To examine this, a 4 (trial) x 2 (pitch: low vs. high) x 2 (brightness: black vs. white) x 4 (condition) mixed ANOVA design was used with 3 within factors (trial, pitch, brightness) and 1 between factor (condition). There were four distinct trials that were all seen twice by each infant, producing eight test trials. In one trial the black ball was on the left of the screen and a high-pitch sound was heard. In another high-pitch trial, the black ball was on the right. In one trial the black ball was on the left and a low-pitch sound was heard. In another low-pitch trial, the black ball was on the right. It was important that infants saw an equal number of trials with each ball on each side as this ensured that preference for looking towards one side did not affect the results. Each infant was randomly allocated to one of four conditions. All conditions contained the same displays, the conditions varied only in terms of order. Procedure The parent and infant were greeted by the experimenter, told the aims of the study and given the opportunity to ask any questions. Parents were instructed not to point towards the screen to avoid influencing looking. Informed consent was then obtained from all parents. Once the introduction was complete, the infant was seated and the study began. Firstly, infants were shown the standard animation which consisted of a single, standard-brightness ball bouncing with a standard-pitch tone. This display lasted for a maximum duration of 120s, however the trial ended once 20s of looking towards the screen had been accumulated. This time was pre-defined to ensure that all infants saw the initial display for the same duration. Once the accumulated looking-time was reached, an attention getter (auditory and visual rattle) was presented to re-direct the infants’ attention towards the screen. The test trials begun when the observer used a computer key-press to indicate that the infants attention had been retrieved. The two balls of the test trials were accompanied by a high or low-pitch sound upon bounce. Each display was presented for a maximum duration of 60s, however the trial ended if the infant looked away from the screen for 2s or longer. After each test trial, an attention getter was presented until the infant looked again. The next test trial was presented when the observer indicated that the infant regained attention. Eight test trials were presented meaning the test trials lasted a maximum of 8 minutes. Looking-times were coded live using the updated version of Habit2000 software (Cohen, Atkinson & Chaput, 2000). Each session was recorded on camera so that a proportion of infant data could be re-coded by a second observer. This allowed measurement of inter-rater reliability. Once the infant had completed the experiment, the parent was thanked for their time and given a book for their infant. They were also given a debrief and reminded of their right to withdraw their infant’s data.
Extending the Cortical Hyperexcitability Index
Perceptual Aberrations, Cortical Hyperexcitability, Migraine, Aura, Tinnitus, Auditory Perception, Visual Perception, Hallucinations
Anomalous perceptual experiences are associated with underlying excitation of neural activity in the cerebral cortex, known as cortical hyperexcitability (Wilkins, 1995). This can be measured behaviourally by the pattern glare test, where migraineurs consistently show greater susceptibility to anomalous visual percepts in response to grating patterns than control participants (for review see Evans & Stevenson, 2008). Based on these findings, Fong, Takahashi and Braithwaite (2019) developed a screening measure of visual cortical hyperexcitability, the Cortical Hyperexcitability Index (CHi-II), through exploratory factor analysis. This project aims to create auditory-based items for the CHi-II. We know cortical hyperexcitability in the auditory cortex is also associated with a number of auditory symptoms in migraine such as heightened auditory sensitivity and a range of anomalous auditory percepts, ranging from tinnitus-like tones to multiple conversing voices (Vingen, Pareja & Støren et al., 1998; Miller, Grosberg, Crystal & Robbins, 2015). As such we created seven auditory items through adaptation of related questionnaire items and generating unique items based on phenomenology of patient descriptions; these refer to experiences of hearing voices or unexplained sounds under various circumstances, as well as sensitivity to noise. Exploratory Factor Analysis will be conducted on the CHi-II alongside auditory items to test which factor each item best loads onto, as well as using Cronbach's Alpha to assess internal validity. Results are discussed in terms of the debate on global versus localised effects of patterns of hyperexcitability, as well as implications for our understanding of multisensory anomalous perceptual experiences.
Method Participants Forty-five participants age 18-24 (M = 19.24) took part either for research credits or without incentive. Of these, thirty-seven (82%) were female and thirty-seven (82%) were right-handed. Prior to the main questionnaire, a pre-screening survey asked participants to declare any history of neurosurgeries (8.22%), neurological conditions (2.22%), psychological conditions (17.78%), ocular conditions (15.56%), epilepsy (0%), migraine (24.44%), or tinnitus (15.56%). Auditory Item Creation As with the original CHi-II, items were based on previous questionnaires measuring anomalous perceptual experiences (Sierra & Berrios, 2000; Bell, Halligan & Ellis, 2006) alongside patient reports of auditory experiences in migraine (Miller, Grosberg, Crystal & Robbins, 2015; Vreeburg, Leijten, Sommer & Sommer, 2016). These items were split into two categories: voice-hearing, and noise-hearing. We distinguished between hearing a single voice in item one ‘Do you ever hear a single voice talking aloud in your head without a clear source?’, or multiple voices in item two ‘Do you ever hear 2 or more unexplained voices talking with each other?’, as these are delineated in patient reports (Miller et al., 2015; Vreebrug et al., 2016). We also distinguish between hearing instructing voices in item three ‘Do you ever hear voices telling you what to do?’, and hearing voices which comment on thoughts and actions in item four ‘Do you ever hear voices telling you what to do, or commenting on what you are thinking or doing?’, as suggested by the CAPS and CDS (Sierra & Berrios, 2000; Bell et al., 2006). The first noise item asked participants about the occurrence of anomalous sounds in item five ‘Do you ever notice sounds, such as ringing / buzzing , which other people around you cannot hear?’ as recommended by CAPS and CDS (Sierra & Berrios, 2000; Bell et al., 2006). The final noise items referred to volume of sounds in item six ‘Do you ever become annoyed or agitated by sounds that are too loud or uncomfortable for you?’, and distraction caused by sounds in item seven ‘Do you ever become distracted when surrounded by lots of noise?’ as these are common auditory complaints of migraine sufferers (Miller, Grosberg, Crystal & Robbins, 2015; Vreeburg, Leijten, Sommer & Sommer, 2016). As with the original CHi-II, participants respond to items in terms of their frequency on a zero (‘Never’) to six (‘All the time’) Likert scale, and their intensity on a zero (‘Not at all’) to six (‘Extremely intense’) Likert scale. Scores from these two scales are added to create a total score for each item. Informed consent was obtained from all participants. Analysis Total scores were collected from both the original CHi-II questionnaire (Braithwaite, Marchant & Takahashi et al., 2015; Fong, Takahashi & Braithwaite, 2019) and these additional auditory items to complete an EFA. Parallel analysis was also applied to statistically verify the loadings of the new items onto the underlying factor structure (Horn, 1965; Hayton, Allen & Scarpello, 2004). Cronbach’s alpha was used to test the internal consistency of each factor.
Braithwaite, Marchant, Takahashi, Dewe & Watson (2015) Fong, Takahashi & Braithwaite (2019)
Exporing the Effect of Visual Complexity on Recall
#visualcomplexity #recall #free-recall #cued-recall #advertisements #simple #complex
This study was conducted to explore the effect of visual complexity on an individuals` recall of product brands and their attributes in either simple or complex adverts . Within the field of visual complexity, there has been contradiction as to whether complexity helps or hinders recall, this study aims to resolve this question. A survey was conducted to measure their free and cued recall for adverts that varied in their visual complexity. The complex advertisements were defined as having three objects included whilst the simple advertisements had only one object included. This was decided to align with the industry standard for defining visual complexity as set by Attneave (1954), Snodgrass & Vanderwart (1980) and Chikhman et al., (2012). A percentage scoring system was used to compare overall memory performance. The data showed that those in the simple condition performed better compared to those in the complex condition. However, this was not the case for every individual. The results found the effects of complexity to be marginally significant (p < 0.09); however, the study had limited power, and a replication with a larger population could provide a more complete picture of the influence of the independent variable. Whilst this study does not provide a definitive conclusion towards the effect of visual complexity, it does explore and provide an insight into the effects of complexity on recall of product attributes in advertisements.
PARTICIPANTS The larger the number of participants in a study, the better-protected results will be from extraneous variables. For this reason, the participants were collected through random snowball sampling (Emerson, 2015). Each condition had 22 participants, a minimum age of 16 being the only participation condition. The participants were randomly allocated to each one of the four experimental conditions, providing 88 total participants (N= 88). There were no gender requirements for participation (Females (N = 47), Males (N = 31), Other (N = 4)). The majority of participants were born in the U.K. (N = 46) or Poland (N = 35). The majority are currently residing in England (N = 57) or Poland (N = 21), but responses were still collected from further afield, such as France and the U.S.A. (N = 10). The majority of participants fell into the two youngest age categories, 16 to 18-year-olds (N = 22) and 22 to 27-year-olds (N = 37). General demographic information provided insight into the advertisement exposure in participants' generic routines. The majority of participants were native English speakers (N = 49). The majority of participants use streaming services (N = 76), of which just under half of the respondents said their service had adverts (N = 38). Participants also use ad blockers (N = 49). Just over a quarter of participants use cable T.V. (N = 27). When asked whether they pay for premium applications, the majority said ‘never’ (N = 60), occasionally (N = 16), sometimes (N = 9), usually (N = 2), whilst only one participant always pays for premium applications (N = 1). MATERIALS Firstly, two product categories were chosen, bottled water and soap bars, four brands were then selected per category (see table 1). There were 16 advertisements in total, eight for the simple and complex conditions, respectively. (APPENDIX A) The editing software Gimp was used to design the advertisements to enable the selected products to be presented in the controlled advert setting. This 'controlled setting' ensured that the backgrounds were consistent across the adverts, e.g., they all used the same blue background. Additionally, no text or fonts were added, and the objects included had the same position as their counterparts. There were two experimental groups wherein participants were presented the advertisements. Within those two groups participants would view one of the product categories e.g., the water products. To account for confounding variables advertisements were counterbalanced, randomizing their order of appearance. Participants only saw one product category (e.g., soap or water) and one variation of the advert e.g., if they saw the simple A1 Aveeno advert, they were not be presented with the complex B1 Aveeno advert. If participants saw the complex B5 Buxton advert, they were not presented with the simple B1 Buxton version. If participants saw the soap adverts, they did not see the water and vice versa. The web-based software Qualtrics was used to create the surveys (APPENDIX B) and a generalized report of the results. After extracting the data, SPSS was used to dummy code and manipulate the data to measure the effect of visual complexity on recall. DESIGN This experiment used a between-group design wherein participants were allocated either the simple or complex condition to examine which level of complexity had the larger effect (Turkeltaub et al., 2011). The type of complexity, simple or complex, is the independent variable of the experiment. The dependent variable is the effect this has on participants' recall (Atinc et al., 2011). In this project, simple advertisements are defined by having only one object included in the background, whereas complex advertisements are defined by having three objects. Participants were first asked questions pertaining to free recall of product attributes before then being presented with the cued recall questions. This was to allow a distinction between non prompted (free) and prompted (cued) responses, enabling me to mark each survey and allocate a combined percentage recall score to each participant. To control for confounding variables, the surveys were counterbalanced. Participants were shown the adverts randomly within each experimental group so that I could isolate the sequence effects that participants are exposed to. However, I could not control for extraneous variables such as the time of day participants completed the survey, their emotional state, or their level of intelligence. Additionally, situational factors such as the location they were in, e.g., whether the room they were in was too loud, too hot, too cold, could not be accounted for. To prevent participants from rehearsing the material, distraction tasks were provided before requesting question responses (APPENDIX C). These were designed to be cognitively engaging by requiring participants to read sections of text and 'fill in' the missing words and select the 'odd word out' in a listing task. When completing these tasks, participants would not necessarily be aware that they were not an essential part of the study and thus, in processing their responses, would have to pause. For example, 'which word does not belong with the others?' had the response options of ‘Dog’, ‘Cat’, ‘Donkey’, and ‘Dragon’. There are actually two responses that could be deemed correct; however, participants are told to select one. The correct responses were ‘Cat’ as it is the only word beginning with the letter 'C' and ‘Dragon’ as it is the only creature with wings. Participants could not advance to the next section if there were any responses left blank. All of the advertisements had the same consistent blue background, no fonts were used, and all objects had the same positioning between the simple and complex conditions. For example, A2 and B2 Dove both had the blue ribbon object included in the same position. All simple advertisements had one object; all complex advertisements had three objects to allow a comparison of the effect of complexity on consumers' explicit recall. PROCEDURE Participants were found and randomly allocated to one of the experimental groups. They were first presented with the participant information sheet (APPENDIX D) in which general information about the experiment was explained without revealing that it was the level of complexity being measured. Participants were also required to complete the consent form. (APPENDIX E) Thus ensuring the participant is aware that their data will be collected anonymously and that they have the right to withdraw at any time should they please. Participants then viewed four advertisements for 30 seconds per advert. They were not able to advance to the next image until the timer ended . The counterbalancing of questionnaires meant that the adverts were viewed in random orders. The distraction task then engaged participants for a few minutes as they could not advance until the distraction tasks were complete. Participants were then asked the free recall questions in which they are expected to list the brands they can remember and list the product attributes for said brands. The soap category had 26 points available for free recall, and the water category had 15 points available. This is due to more attributes generally being included on the packaging of the soap comparatively to a generic product like water. Ergo, a more comprehensive list of features was able to be asked. Once the participant had submitted the free recall section, they moved onto the cued recall questions. This section provided prompts in the questions, for example, ‘name the products, if any, that were moisturizing?’ participants may not have been able to recall this attribute freely. Therefore, these questions had to be presented separately so as not to influence each other. Furthermore, the free recall had to be asked first for the same reason of not influencing responses. If participants had filled the cued responses first, this would invalidate any free recall questions which may have followed. The soap and water categories respectively had 16 points available for the cued recall questions. Once the survey was completed, participants were shown the debrief sheet (APPENDIX F) in which the aim of the study was fully explained, and they were provided with details should they have any questions about their role and wish to discuss it further.
Persuasion within Advertising: Metaphorical Expressions vs. Literal Expressions
Metaphor literal persuasion advertising marketing figurative language emotion
The present research built upon research conducted by Citron and Goldberg (2014) on figurative language, emotion, and the brain. This study examined the three different data sets: sentences, stories and sentences with taste metaphors collected by Citron and Goldberg (2014). It examined three different data sets: sentences, stories and sentences with taste metaphors. Metaphorical and literal sentences, stories and taste metaphors were rated on emotional valence, imageability, emotional arousal, metaphoricity and similarity in meaning. Familiarity was rated within sentences and taste metaphors and understandability and naturalness were rated within stories. This study explored relationships among variables, relationships between metaphors and literal counterparts, relationships between each data set and lastly, relationships between each data set when split by type: metaphor and literal. Findings from this investigation provide evidence for marketers, of the benefits of using metaphors within advertising to increase persuasion and consumer buying behaviour. A company who wants to portray imagination, develop images within a consumer’s mind and evoke emotional arousal should use metaphorical sentences within their advertisements. Additionally, the more arousing a sentence the more imaginable, therefore, marketers should specifically employ emotionally arousing material to further engage a consumer. This study can add to literature on figurative language and persuasion. Also, provide evidence for marketers who want to increase their sales and further persuade consumers with an effective approach
All metaphorical sentences and stories were created in German with words that would obtain a metaphorical interpretation. Then each word was replaced with its literal counterpart, which created: one hundred and twenty non-taste related sentences, sixty metaphorical “The bride was very moved by her wedding” and sixty literal “The bride was very happy about her wedding”. Sixty-four stories, thirty-two metaphorical “Lisa was sitting in her physics class and was still digesting the stuff from the lesson before when her teacher announced a task to bite your teeth out on.” and thirty-two literal “Lisa was sitting in her physics class and was still having problems with the stuff from the lesson before when her teacher announced a really difficult task.” Finally, seventy-four taste metaphors, thirty-seven metaphorical “She received a sweet compliment” and thirty-seven literal “She received a nice compliment”. Specific instructions were created by Francesca Citron for each variable to be rated (See Appendix A). Sentences, stories and taste metaphors were rated on emotional valence, imageability, emotional arousal, metaphoricity and similarity in meaning. Emotional Valence refers to how positive or negative the stimulus is which was rated on a scale from -3 (very negative) to + 3 (very positive) through 0 (neutral). All other variables were measured on a scale of 1 to 7. Imageability is the ability to evoke a mental picture rated: 1 “not imaginable at all” and 7 “very imaginable”. Emotional arousal describes to what extent the stimulus is emotionally stimulating rated: 1 “not intense at all” and 7 “very intense”. Metaphoricity describes the figurativeness of the stimulus rated: 1 “literal” and 7 “very metaphorical”. Lastly, similarity in meaning which refers to how similar the meaning of both metaphorical and literal counterparts are with regard to contents. For instance, the metaphorical sentence “He praised her to the skies” compared to the literal sentence “He praised her fulsomely”. These have the same meaning, thus the meaning similarity between metaphorical and literal sentence is high. This was rated 1 “not similar at all” and 7 “very similar/equal in meaning”. Familiarity was rated within sentences and taste metaphors, which describes how familiar the stimulus is rated: 1 “not familiar at all” and 7 “very familiar”. Additionally, taste relatedness was measured for taste metaphors which refers to the extent a sentence is associated with degustation. It was rated as 1 “not taste-related at all” and 7 “very taste-related”. Lastly, understandability and naturalness were rated within stories. Understandability is about the easiness of grasping what the content means rated: 1 “very difficult to understand” and 7 “very easy to understand”. Naturalness is how normal and daily a story or its parts are rated: 1 “not natural at all” and 7 “very natural”. To evaluate complexity, several measurable parameters were created. For each parameter one “complexity point” was given, therefore, creating one overall complexity score. For all data sets all 9 characteristics were the same: subordinate clauses, relative clauses, passive forms, compound nouns, appearing persons, adverbs and adverbial phrases, conjunctive forms, analytically-formed tenses/infinitive constructions and marked/deviating structure of sentence. For sentences and taste metaphors alone the number of words was also a characteristic and within stories the number of metaphors. (See Appendix B). Procedure Participants were each provided with a consent form to sign if they agreed to partake in the study. Once completed, participants were provided with a URL via E-mail to access the questionnaire. General instructions were shown first, followed by the specific instructions for the first variable to be rated. The words were then presented, each one at the centre of the page immediately followed by the 7-point scale. When all words had been rated for one variable, instructions for the next variable rating appeared. The order of variables were random for each participant. This procedure was the same for all sentences, stories and taste metaphors. Data Analysis All the means and standard deviations were calculated and used for the analyses for all sentences, stories and taste metaphors. Independent sample t-tests were then used to look at the differences between metaphors and literal counterparts of each variable within the three data sets. When there was a specific hypothesis a one tailed t-test was implemented however, when there was no hypothesis a two tailed t-test was applied. Next, the variable emotional valenced squared was computed to represent the quadratic relationship between all other variables and then used within the following data analyses. Firstly, a multiple regression was then used to analyse any quadratic or linear relationships between emotional valence and other variables within each data set. In each regression, features of no interest were partialled out by entering them as predictors in the first step; then valence and valence squared entered in the second step. Additionally, partial correlations were conducted within each data set to look at linear relationships between pairs of variables within metaphors and literal counterparts by controlling for other variables. Lastly two types of analyses of variances were conducted, firstly, one-way between subjects ANOVAs to look at the difference between datasets: sentences, stories and taste and their impact on emotional arousal, imageability, emotional valence and metaphoricity. Then one-way between subjects ANOVAs to look at the differences between datasets when split by type, metaphors and literal counterparts and their impact upon variables.
The rating data had been gathered already by Francesca Citron during her research in Berlin and ethical approval had been obtained at that time. The present study has been approved by the Department’s Research Ethics committee at Lancaster University.
Do foetuses have the ability to retrieve and retain information presented by both the mother-to-be and partner?
language, foetus, mother-to-be, partner, retention
The complex phenomenon of language development is a vital criterion for communication and for the strengthening of the attachment bond between caregiver and baby (Chew & Ng, 2021). The period in which humans begin to process speech is difficult to define; previous research has identified that foetuses that have the capacity to retain linguistic information presented to them over six weeks by their mother-to-be show a preference for this information postnatally (DeCasper and Spence, 1986). However, the language environment of the foetus also likely incorporates that of the secondary carer role and very little research has investigated the role of the partner in influencing language retention. This study aims to investigate the extent to which foetuses have the ability to retrieve and retain linguistic input presented to them by both their mother-to-be and their partner. A within-measures design with two participant pairs who were recruited via opportunistic sampling through Lancaster University’s Babylab was conducted. Participants were asked to record themselves reading “The Cat in the Hat” and play both of the recordings to the foetus every day for two weeks. During these sessions, the mother-to-be was required to count the frequency of kicks and the movement intensity per session. The findings concluded that foetuses can retrieve and retain language that is presented over a two-week period at only 32 weeks’ gestation. Foetal kicking decreased significantly as exposure to recordings increased. This provides evidence of online processing of linguistics at 32 weeks’ gestation, implying that the full six-week exposure, as previous research indicated, is not necessary thus providing evidence of an innate processing of language. Although there is scope of environmental influence on this. No significant impact of parent recording on foetal ability to process language was found. This suggests that humans have an innate ability to process linguistic information which is despite levels of exposure to voice. However, this conclusion is based on a null hypothesis in an underpowered study; it would be very beneficial for further research to use a larger sample size to increase statistical power and be more representative of the general public.
Methods: Ethics Statement: Ethical approval was granted by Lancaster University Psychology Department on the 12th of April 2021 before any data collection was completed. Participants were provided with information for review and asked to complete an informed consent form online before participating within this experiment and were given the option to withdraw at any point of the study. Participants: Three mothers-to-be and their partners were recruited via opportunistic sampling through Lancaster University BabyLab social media (http://wp.lancs.ac.uk/babylab/) and word of mouth in exchange for a £5 book voucher from Waterstones. In order to take part in this research mothers-to-be must live with a partner and also have a foetal gestation age of between 32-34 weeks. If any participants were bilingual, they were asked to record the story in English to ensure reliability. Materials and Measures: Due to current restrictions because of COVID-19, this experiment took place online. Participants were sent an email containing a link to a Qualtrics survey. Qualtrics is a software that allows participants to access surveys and questionnaires on all digital devices at any point of time to help aid easy distribution. Qualtrics Survey: To complete this survey, participants were required to have access to a mobile device or computer. The Survey contained the information sheet, consent form, instructions, and demographic questions. The questionnaire consisted of questions asking the mother-to-be to rate the intensity of movements and state the frequency of kicking per session (see Appendix A). The intensity of kicks were recorded using a scale bar where mothers-to-be could rate the intensity of the kicking per session (0-100). Recording “The Cat in the Hat”: Participants were given a copy of an extract from “The Cat in the Hat” and both the mother- to-be and their Partner were asked to record themselves reading the story aloud using a device that they were then able to play the recording on every day for two weeks. This was estimated to take between five and ten minutes depending on reading speed per participant. To control the decibel of their recordings, parents were advised to download the “Decibel X” app which can monitor sound level in order to keep it at the recommended 90db (Luu, T, 2011). Also, to help mothers track their foetal kicks, they were also advised to download the NHS “kicks count” app which helped mothers-to-be accurately count the frequency of kicks per story session. At the end of the survey and after completion of the study, participants were given a debrief sheet which contained the aims of the research study and any contact information they might need for further questions. Design: This research study used a within-measures design as all participants took part in all sections of the experiment. The independent variables in the study were the parent reading the story which has two levels; the mother-to-be or their partner. The second independent variable related to the time point from day one until the end of the two weeks. The dependent variables were the frequency and intensity of foetal kicking during the exposure to both the mother-to- be and their partners recording of “The Cat in the Hat”. This was measured by the mother-to- be. Procedure: Once they had consented, the mother to be and partner were given an extract from the story “The Cat in the Hat” via the Qualtrics survey and were asked to record themselves individually reading the story on a device that they were able to play back on several occasions. Once the story had been recorded by both the mother-to-be and their partner, they were asked to play the story to the foetus every day for two weeks. The order of presentation was counterbalanced. While the study was being recorded, the mother was required to monitor the intensity and frequency of kicks that occurred for the duration of the auditory exposure. The mother-to- be was told to do this for both the duration of exposure to the recordings every day and then upload the outcomes for each session using the original Qualtrics survey link. Analysis: Rstudio is a professional software that allows for programming statistical analysis, production of graphs and tables that were used to analyse that data collected. Linear mixed effects model was conducted for analysis.
Inner Speech and Grit: Do Positive Inner Speech and Evaluative Inner Speech Lead to Grit Behaviour
Inner speech, grit, articulatory suppression
Grit, defined as perseverance and passion for long-term goals, is a reliable predictor of success metrics, surpassing even IQ. While the exploration of grit has been conducted extensively, studies on the mechanisms of grit are still lacking. Inner speech, the silent production of words in one’s mind, plays a pivotal role in managing thoughts. This includes cognitive reframing, which is essential for enhancing perseverance. Theoretically, inner speech can predict grit. This study, employing a survey and experimental design, aims to investigate whether positive inner speech and evaluative inner speech can predict grit behaviour. The data for this study (n=56) were collected in two ways: (1) using the grit scale and inner speech VISQ-R via a Qualtrics survey, and (2) using participants’ task retention decisions and a qualitative classification approach. The data were analysed using R Studio. The survey data were analysed via a linear model, while the qualitative data were analysed using a generalised linear mixed-effects model. The survey results showed that only evaluative inner speech can positively predict grit. However, there were imbalanced results regarding the participants’ task retention decisions. Collectively, these findings underscore that grit can be predicted by evaluative inner speech. This prompts further research to explore its multifaceted role in shaping grit across various domains.
This study applied a mixed-method and correlational research design that aims to examine whether evaluative inner speech and positive inner speech lead to grit behaviour. The data for this study were collected using two methods: (1) questionnaires through a Qualtrics survey, and (2) an experimental task where the participants were asked to complete two sets of puzzles under different conditions (baseline and with articulatory suppression) and provide their retrospective experience after each puzzle task. Participants’ task retention decisions (decision to quit) were also recorded in the study. Three different analyses were applied in the research. For the first analysis, the positive inner speech and evaluative inner speech scores from VISQ-R acted as the predictors, and grit from the Short Grit Scale as the outcome. For the second analysis, the participant’s grit score acted as the predictor, and the participant’s task retention decision acted as the outcome. Lastly, the third analyses the types of inner speech based on the participant’s retrospective experience (positive inner speech and evaluative inner speech) acted as the predictors, and the participant’s decision to quit or not to quit was the output. In this study, the participants were students from Lancaster University, ranging from undergraduate degree students to master’s degree students and doctorate students. Participants were recruited using social networks, direct emails, and posters around the campus and/or on social media. The session took approximately 30 minutes for the data collection process, including the briefing, and each participant was reimbursed with five GBP for participating. Ethical approval for this study was submitted and approved by the ethics committees at Lancaster University. The number of participants involved in the study was 56 people in total. This number was determined by using G power. The test family was set at the t-test because this research will use a comparison between the control approach (baseline) and the experimental approach (with articulatory suppression). The effect size f2 was set at 0.15, while the α-error probability was set to 0.05 (5%) and the power 1−β error of probability at 0.8 (80%), with the number of predictors set at five. In total, 56 participants took part in the study, where the number of male and female participants was 23 (41%) and 33 (59%), respectively, and the number of native English participants in the study was 15 (27%), while non-native speakers were 41(73%). Demographic Information: The demographic information collected pertained to each participant’s attributes. This included sex (male, female, non-binary/third gender, and prefer not to say) and English native background (yes or no). Although the study has no biases towards the participant’s native language, the word used in the study ‘aluminium’, a word that is suggested by Gathercole and Baddeley (2014) for the research, may or may not influence the fluidity of pronunciation, making the articulatory suppression more challenging for non-native speakers. Varieties of Inner Speech Questionnaires Revised (VISQ-R): The VISQ-R was developed to link the everyday phenomenology of inner speech, including any psychopathological traits and inner dialogue (Alderson-Day et al., 2018). There are two versions of the Varieties of Inner Speech Questionnaire, where the original one consisted of 18 items and the revised version VISQ-R consisted of 26 items (see Appendix D) that took approximately 5-8 minutes to be completed via a Qualtrics survey. In this study, VISQ-R has been presented as internal experience questions as a dummy to the real name. This is to eliminate any possible biases by the respondents. Responses from VISQ-R can be subdivided into five dimensions and into seven scales (Not like me at all – Very much like me) for scoring: dialogical, evaluative, condensation, other people, and positive. A higher score in dialogical indicates that the person often uses inner speech to exchange ideas with oneself and vice-versa. A higher evaluative score means that the person often uses inner speech to evaluate their thoughts, actions, and decisions. For condensation, a higher score indicates that a person talks to themselves in a concise or short words manner to encapsulate complex thoughts or ideas. Meanwhile, a higher ‘other people’ score indicates that a person often imagines other people’s voices or opinions when engaging in inner speech. Lastly, a high positive score indicates that the person often uses inner speech to encourage oneself in a supportive and comforting manner. Subscale totals for each dimension were acquired by adding the scores for each subscale and dividing it by the total number of items answered across the respective subscale. The Varieties of Inner Speech Questionnaire has been supported for its reliability and validity in measuring inner speech. Racy et al. (2022) have studied the reliability of VISQ-R and compared it to six other instruments relating to inner speech. VISQ-R has moderate to strong concurrent validity with other instruments with self-evaluation showing a strong correlation with other measures. The internal consistencies and reliabilities were excellent (Cronbach’s α > .80) for each of the dimensions with only a positive dimension that is slightly lower with moderate to high test-retest reliability (>.60) (Alderson-Day et al., 2018). Short Grit Scale (Grit-S): The questionnaire of Grit-S was developed by Angela Duckworth to measure the trait level of perseverance and passion for long-term goals (Duckworth & Quinn, 2009). The Grit-S consisted of eight items of questions (See Appendix D) with four fewer items in comparison to the original version, retaining the factor structure and improving on the psychometric properties. The questionnaire needs an approximation of 3- 5 minutes to be completed in the Qualtrics survey. Similar to VISQ-R, the Grit-S questionnaire has been presented as a personality instead of a grit scale to avoid any possible biases. There are two dimensions included in the Grit-S for scoring: Consistency of Interest, where a higher scale subscale score indicates that the individual is able to maintain their interest for and focus on their long-term goal, and Perseverance of Effort, where a higher subscale score represents sustained effort towards a long-term goal despite the presence of setbacks (Van Doren et al., 2019). The subscale for the dimension of Consistency of Interest is acquired by adding the scores for all the subscale items (item-1, item-3, item-5, and item-6), while for Perseverance of Effort (item-2, item-4, item-7, and item-8). There are a few items that have been coded inversely and have been recoded before running the analysis. Several research studies have confirmed the validity and reliability of the Short-Grit Scale Instrument. Eskreis-Winkler et al. (2014) conducted a study involving predicting retention in the military where the grit instrument was used to measure the grit level of cadets. The instrument has been proven to be reliable as grittier soldiers were more likely to complete the Army Special Operation Forces (ARSOF), likely to get a job, and likely to stay married. In a more recent study by Priyohadi et al. (2019), the Grit-S again proved its validity and consistency. The internal consistencies between items in a dimension were moderate to high (>.60) for both persistence of effort and consistency of interest and have high consistencies between studies. Active Task: The jigsaw puzzle was used as the active task for this research. Two jigsaw puzzles from Livewire Puzzles were predetermined by the website as expert-level with 70 puzzle pieces (10 X 7) with an 8-minute time limitation. The puzzle can be accessed through the games.puzzle.ca website. The puzzles have been created by Arkadium, a company that is well-recognised in making online games. New puzzles have been uploaded daily, but to avoid any possible advantage or disadvantage, the puzzles used are from the 22nd of June 2023 and 21st of June 2023. Marks will also be provided at the end of each puzzle. There are two ways of measuring participants’ performance: (1) Quitting - participants were allowed to quit the task at any time during the 8-minute time limit by telling the researcher present that they want to stop, and (2) Puzzle performance - marks will be given at the end of the puzzle (marks will be given even if participants quit halfway) by the source website. The marks will be calculated based on the number of puzzles fixed correctly and then divided by the total number of unfixed puzzles and will be multiplied by the amount of time left in the puzzle. The maximum score of the puzzle is 5,000 and the minimum score is zero. All calculations will be automatically measured by the source website. The puzzle from Livewire Puzzle has also been used by other studies that focus on measuring grit using an active task. Kalia et al. (2019), similar to this study, used puzzles from Livewire Puzzle as an active task to measure perseverance in participants. Instead of using a jigsaw puzzle, Kalia opted to use sudoku to measure the role of grit and cognitive flexibility 2.4 Procedure The research took place in one-on-one sessions at the Lancaster University library. Data collection sessions were administered in the following order: demographic information, the first puzzle task, the difficulty level question, the subjective inner speech question, the second puzzle task, the second puzzle difficulty level question, and finally, the second subjective inner speech question. Each participant undertook the puzzle task in both control (baseline) and experimental conditions (with articulatory suppression). The sequence of which puzzle task they had to complete first was decided based on the participant’s subject ID assigned by the researcher. Participants with odd Subject ID numbers were assigned the control puzzle task first, while participants with even Subject ID numbers were assigned the experimental puzzle task first. Before starting the experimental puzzle task, the researcher spent a few minutes helping the participants practice performing the articulatory suppression by saying the word ‘aluminium’ repeatedly at 90 BPM using an online metronome. Throughout the experimental task, if the participants mispronounced the word too obviously or consistently missed or skipped a beat, the researcher aided them by correcting their pronunciation or assisting them to meet the 90 BPM until they matched the rhythm again. During data collection, the researcher offered participants an opportunity for a break between puzzles if they began to get tired to prevent their answers from being expedited. The participants were also allowed to ask any questions while they were completing the questionnaire to clarify their understanding of the items presented. At the end of each data collection session, the researcher thanked the participants for their participation and answered any questions that they had. The researcher also explained that participants would be emailed a participant debrief sheet and could request a summary of the study’s findings once data analyses had been completed. For participants who were eligible for reimbursement of travel expenses, they were asked to fill out a participant payment form as a receipt of confirmation that they had been paid. Three different models of analysis were carried out in the study. To measure the first prediction, a linear model was used by entering the positive inner speech and evaluative inner speech scores from the VISQ as the predictors and the grit score from the short grit scale as the output. For the second prediction, a linear model was used with the outcome set at the participant’s decision to quit or not to quit and the predictor set as the interaction between different experimental conditions and grit. To measure the third prediction, a generalised linear mixed-effect model was explored by entering the interaction of different experimental conditions and dimensions of inner speech (evaluative inner speech and positive inner speech) recorded from the participant’s retrospective experience as the predictor and participant’s decision to quit the task as the outcome. In this model, a random effect of differences between the conditions (baseline and with articulatory suppression) in slope and participants in the intercept were also included.