The Effects of Different Sleep Stages on Language Learning Tasks in Young Adults
Language learning, novel generalisation, REM, sleep, sleep spindle density, sleep stages, speech segmentation, SWS
In order to learn a language, one must practice multiple tasks, including speech segmentation and generalisation. Segmenting speech allows for the identification of words and learning the meaning as well as syntactic role of those words within phrases and sentences. Novel generalisation requires generalising over the structure of a new language not yet experienced. Frost and Monaghan (2016) showed that participants were able to use the same statistical information at the same time to complete both language tasks. They suggest that segmentation and grammatical generalisation are dependent on similar statistical processing mechanisms. The role of sleep for learning to segment and generalise language is still unclear. Sleep affects memory consolidation, which is necessary for learning a novel language. This refers to the amount of sleep individuals get within their sleep cycle, yet it is unknown whether the duration of separate sleep stages has an effect. The declarative/procedural (DP) model by Ullman (2004) on learning provides distinctions in DP memory that associate with slow-wave sleep (SWS) and rapid-eye movement (REM) sleep respectively. SWS has a role in declarative memory processes, including memory for words and grammar. Rapid-eye movement (REM) sleep has a role in procedural memory processes, involving motor skills and coordination. Sleep spindle density should also be considered, as spindles are involved in offline information processing and information transfer. It was found that increased SWS and stage 2 spindle density have a positive effect on speech segmentation compared to generalisation.
Participants The original experiment was completed by 54 participants, 8 males and 46 females, with an age range of 18-24-years-old (mean age = 18.52). All participants reported being native-English speakers, with no history of auditory, speech or language disorders known. All participants either received university course credit or £20 for completing the experiment. Observations may be excluded for the first linear mixed-effects model. Exclusions may come from participants in the sleep group who did not sleep during the permitted time. This is because the first analysis aims to compare sleep vs. wake. The same participants’ data will be kept for the other linear mixed-effects models which aims to compare duration of sleep stages. This research received ethical approval by Dr Padraic Monaghan and Lancaster University’s Psychology Department on 22/04/2021. Design This study had a between-participants design with two conditions: sleep vs. wake between training and testing, and test type. There were two test types of speech segmentation and novel generalisation. Participants were randomly allocated to the sleep or wake conditions, and split evenly, meaning 27 participants slept and 27 remained awake. This study had access to PSG data for 18 of the participants in the sleep group. All participants received both test types. All participants were provided with an information sheet and gave written consent before the study commenced. Materials Stimuli Using the Festival speech synthesiser (Taylor et al., 1998), speech stimuli were created that were based on similar stimuli used by Peña et al. (2002). This artificial training language contained monosyllabic items, of which there were nine (pu, ki, be, du, ta, ga, li, ra, fo), used to form three different non-adjacent pairings with three possible X items in-between (A1X1–3C1, A2X1–3C2, and A3X1–3C3) (Frost & Monaghan, 2016). Using Peña et al.’s (2002) study, A and C items contained plosive phonemes (pu, ki, be, du, ta, go) and X items contained continuants (li, ra, fo). All AXC item strings had a duration of approximately 700ms. Any preferences – for dependencies not due to the statistical structure of the sequences – were controlled for by generating eight versions of the language. Each version had randomly assigned syllables to A and C items, and the same X items were used in all versions. These versions of the language were counterbalanced across both task types. When testing for novel generalisation, three additional syllables were used with continuant phonemes (ve, zo, thi) (Frost & Monaghan, 2016). Research on the similarities in phonological properties of non-adjacent dependent syllables has shown that these similarities show support for acquisition of such nonadjacencies (Newport & Aslin, 2004). Nonetheless, other research has found that they are not essential for language learning to occur (Onnis et al., 2004). Words in the same grammatical category tend to be coherent regarding phonological properties (Monaghan et al., 2007), so regardless of learning, this property of the artificial language used within this study is consistent with natural language, which allows for real-life implications. Training The speech stimuli were formed into a 10.5-minute-long continuous speech stream by stringing together the AXC words within the language. It was ensured that no Ai_Ci dependencies were repeated immediately after each other. The speech stream included 5s fades for the onset and offset of speech, which ensured that such a feature of speech could not be used as a language structure cue (Frost & Monaghan, 2016). Testing Segmentation: part-words were trisyllabic items that were heard in the training speech stream but overlapped word boundaries. As such, part-words comprised of either the last syllable of one word and the first two syllables of the next (CiAjX), or the last two syllables of one word and the first syllable of the next (XCiAj). For all nine AXC items, both part-word types were created. 18 test pairs were constructed which participants listened to, by matching each part-word with its corresponding word (for example, the A1X2C1 item was paired with the X2C1A2 part-word) (Frost & Monaghan, 2016). Novel generalisation: nine forced choice tests included a rule-word which contained one of three novel syllables (ve, zo, thi) (AiNCi), where N is the novel syllable and a novel part-word. For each Ai_Ci dependency, each novel rule-word appeared once. Part-words were made of two syllables that were heard in the training task, in their respective positions, with the same novel syllable as in the rule-word sequence (Frost & Monaghan, 2016). This novel syllable could appear in any position (first NCiAj, second XNAi, or third CiAjN) and each novel syllable occurred once in each of these positions. Rule-word and part-word novelty presence controlled for the effect of the novel syllable, yet the novel generalisation task still tested for generalisation of the non-adjacent structure of items within speech (Frost & Monaghan, 2016). Randomisation of test-pairs in all conditions was ensured across all participants, including the position of the correct response in each test-pair, to reduce response bias. When listening to the test-pairs, items in each pair were separated by a 1s pause. All participants completed The Stanford Sleepiness Scale (SSS) (Hoddes et al., 1972). This was in order to note participant sleepiness before the period of sleep or wake. The SSS consists of one item on a scale of seven statements, within which participants were required to select one statement that best described their perceived level of sleepiness (Shahid et al., 2011) (see Appendix A). Participant responses in the testing task were excluded if 90% of responses were always “1” or “2”, or if responses alternated between “1” and “2”. Procedure The whole procedure lasted for a three-hour period. For the training task, all participants listened to the continuous stream of speech and were instructed to pay attention to the language and think of possible words it contains. After the training task was complete, participants were split into two groups for the sleep vs. wake condition. Half of the participants, the sleep group, were given an hour and 45 minutes to sleep. These participants slept at Lancaster University Psychology Department’s sleep lab, and their sleep was monitored using polysomnography (PSG). PSG and an Embla N7000 system can record the amount of time spent in each sleep stage, and sleep spindle density, with EEG sites: O1, O2, C3, C4, F3, and F4 referenced against M1 and M2. The other half of participants remained awake for the same duration, watching a non-verbal, emotionally neutral video with neutral music. The testing task was then given to all participants after the same amount of time, 15 minutes after the break period. All participants were then required to complete the testing forced choice tasks. Within each trial, participants listened to a test-pair of items and were instructed to select which item best matched the training language. A response of “1” for the first item or “2” for the second item on a computer keyboard was recorded. All participants listened to the speech using closed-cup headphones in a quiet room (Frost & Monaghan, 2016). To test speech segmentation, participants completed a forced choice task on preference for word/part-word comparisons. To test novel generalisation, participants completed a similar forced choice task for rule-word/part-word preference. Data analysis Analysis included mixed-effects models to allow for random participant and item variability. As all participants responded to both task types, therefore multiple items, the likelihood of correlations in responses from the same participant and to the same item increases. Generalised linear mixed-effects allow for a more flexible approach compared to ANOVA, that can handle missing data better, without significantly losing statistical power. Participant and item variation, the effects of sleep/wake, test type, and sleep stage duration were all considered. The interactions between sleep/wake and test type, and sleep stage duration and test type, were also considered in separate models.
Secondary data analysis. Data were originally collected for the paper below, but they were not analysed by the authors. Frost, R. L. A., & Monaghan, P. (2016). Simultaneous segmentation and generalisation of non-adjacent dependencies from continuous speech. Cognition, 147, 70- 74
Data/Excel.csv Data/Excel.xlsx Analysis/r_file.R
Implicit Hand Representations in Typical Ageing and in Parkinson's Disease
Having an internal representation of one’s own body is important for many interactions with the environment, and in making decisions about what actions we are capable of performing. However, even in healthy adults, these representations are known to be distorted. In the hand specifically, individuals are likely to underestimate the length of all fingers, but overestimate the distance between each adjacent pair of knuckles. Both healthy ageing and Parkinson’s Disease (PD) include apsects which are known to further distort body representations, including, but not limited to, diminished tactile sensitivity and impaired action capabilities. This study was designed to investigate the accuracy of hand representations in typical ageing and in PD. Fourteen participants with mild to moderate PD, 17 healthy age-matched controls and 20 younger controls made estimates about the location of hand landmarks when the hand was hidden from view. Estimations were compared with actual hand size. Older controls and individuals with PD both demonstrated more accurate representations of thumb length, and of distance between the index and middle knuckles than younger controls, with older controls also showing differences in their perception of distance between thumb and index knuckles. However, no differences were found between the PD group and older controls, suggesting that the formation of body representations is an ability which is preserved in PD. Possible explanations for, and implications of these results are discussed.
Participants To determine the number of participants necessary, a priori power analysis was conducted in G*Power (Faul et al., 2009), using α= 0.05, β= .08 and effect size = 0.32. This effect size was calculated from Longo (2014), which employed a similar methodology. The analysis determined that 10 participants in each condition were required to yield sufficient power. Previous studies using this methodology have included sample sizes ranging from 12-22 participants (Longo & Haggard, 2010, 2012; Peviani & Bottani, 2020). The intended sample size, therefore, was 20 participants per condition. Due to the time constraints of the study, this number was not reached for all conditions, but all conditions included more than the 10 participants needed as suggested by the priori analysis. 20 younger controls were tested (15 female). Their ages ranged from 19 to 30 (M = 22.40 yrs, SD = 2.21 yrs). 17 were right-handed, and 3 were left-handed, with handedness ranging from -89.5 to 100 (M = 64.52, SD = 61.84) on the Edinburgh Handedness Inventory (EHI; Oldfield, 1971). 17 healthy older controls were tested (11 female). Their ages ranged from 52 to 79 (M = 66.12 yrs, SD = 9.16 yrs). 14 were right-handed, and 3 were left-handed, with handedness scores ranging from -100 to 100 (M = 65.29, SD = 77.31). 14 individuals with PD were tested (4 female). Their ages ranged from 54 to 78 (M = 65.93 yrs, SD = 8.43 yrs). All PD participants were right-handed, with handedness scores ranging from 33.5 to 100 (M = 88.31, SD = 21.20). There was no significant difference between the ages of the participants in the typically ageing and the PD condition, t(29) = 0.06, p = .95. For the PD participants, the most recent onset of PD was 3 years ago, with the longest diagnosis of 20 years (M = 7.75 yrs, SD = 4.81 yrs). All presented with a Hoehn and Yahr Stage of 3 or below. This indicated that all participants were physically independent. All participants had been prescribed antiparkinsonian medication, and they were all tested under their normal medication regime. Younger controls were recruited through use of social media and personal connections of the researcher. PD participants were recruited through a Parkinson’s Research Interest Database which was developed by the researcher’s supervisor (Dr Megan Readman), and by contacting a local branch of Parkinson’s UK. Older controls were primarily friends and family of PD participants. Materials 24 hours before testing, participants were asked to submit demographic information in a questionnaire created using the design software Qualtrics (Qualtrics, Provo, UT). Participants’ hand movements were recorded by an Xbox Kinect camera, mounted on the ceiling directly above the hand. The camera had a resolution of 640x480 pixels, and a frame rate of 30 captures per second. The recording was made using the Kinect Studio application. Within the frame of the recording, a 30cm ruler was placed, to allow for conversion of pixels to centimetres during analysis. During the experiment, the board used to hide the participants’ hands from view was a piece of black cardboard, approximately 85x60cm. The board was 2mm thick and completely opaque. The board was positioned approximately 10cm above the hand, and was supported in this position by 5 cylindrical weights (one under each corner of the board, and one placed centrally). At each side of the board was a small mark of duct tape. This was to indicate where the participants should point between each trial. A mark was placed on each side of the board, as the handedness of the participant determined which hand they used during testing, and therefore determined which side of the board was easier to point to. Participants were asked to point using a red straw, approximately 10cm long. All participants completed the EHI (Oldfield, 1971). This includes a list of tasks (for example, writing or striking a match), for which the participant must indicate which hand they prefer to use. The response options include a strong or slight preference for the right or left hand, or no preference. A score of 100 indicates pure right-handedness, while a score of 100 indicates pure left-handedness. Participants in all conditions were screened for cognitive impairments using the Addenbrookes Cognitive Examination (ACE-III; Hodges & Larner, 2017). This assessment included 19 tasks which examine cognitive function on 5 separate domains; attention (e.g. ‘count down from 100 in 7’s’), memory (e.g. ‘remember this name and address’), fluency (e.g. ‘name as many animals as you can in one minute’), language (e.g. ‘write two full sentences’) and visuospatial reasoning (e.g. ‘draw a clock which reads 10 past 5). Typically, a score of less than 87 out of 100 would be considered abnormal, however, as some aspects of the ACE-III require participants to perform motor tasks, it is accepted that the best cut-off score to identify cognitive impairment in Parkinson’s is 80 points (Kaszás et al., 2012). Using this assessment as an exclusion criterion, only 1 PD participant’s data was removed from further analysis. There was no significant difference in the ACE-III scores of the remaining participants between the three conditions, F(2, 48) = 2.10, p = .13. Participants in the PD condition were also assessed using the Movement Disorder Society- Unified Parkinson’s Disease Rating Scale (MDS-UPDRS; Goetz et al., 2008), to determine the severity of PD symptoms at the time of testing. The UPDRS assesses both the motor and the non-motor symptoms of PD. The non-motor assessment involves questions about the individual’s experience of symptoms during the past week, for example how well they are sleeping, and if they are experiencing tremors regularly. A motor assessment is also conducted, with the participants performing tasks such as opening and closing their hand as quickly as possible, and walking from one side of the room to the other. The researcher was also required to make judgements about the severity of typical PD symptoms such as tremors and rigidity present throughout the examination. All questions and tasks are scored on a scale of 0 to 4, with 0 indicating no impairment, and 4 indicating severe impairment. This assessment has previously been validated and determined to be a reliable indicator of the severity of PD symptoms at the time of testing (Gallagher et al., 2012; Martinez-Martin et al., 2013). Testing occurred in the action and perception lab in the Whewell building at Lancaster University. This study received ethical approval from the Ethics Department of Lancaster University. Procedure Participants were emailed an information sheet 24 hours in advance to inform them of the requirements of the study. This email also directed them to a Qualtrics survey, where they were asked to submit their demographic information (age and sex). Here, they also completed the EHI, and were asked to confirm that they had normal or corrected-to-normal vision. On the day of testing, participants were first screened for cognitive impairment using the ACE-III. At this point PD participants also completed the full MDS-UPDRS. After the recording had started, participants were asked to place their dominant hand (as determined by the EHI) on the table in front of them. They were asked to move their chair so that their hand was aligned with the middle of their body. The participants were instructed to not move their hand throughout the experiment, before an occluding board was placed so that the participants could no longer see their hand. They were asked verbally to confirm that this was the case. Participants were given a straw to use as a baton with which to point. They were then directed to use the straw to point on the board, directly above where they believed specific locations of the hand to be. 10 different locations were used: the tips of each finger, and the knuckle where each finger meets the palm of the hand. Small duct tape marks were placed on the knuckles of each finger. This was done both to ensure that the participants were clear about which knuckles were intended, and also so that location of the knuckle would be clearer on the recording. The location for each trial was read aloud by the experimenter. Between each trial, participants were asked to move the straw to point at a duct tape mark on the side of the board. This was to ensure that all estimations were made where participants believed their hand to be, instead of them using alternative methods such as measuring where they believe one location to be based on the previous location. One block of testing consisted of 10 trials (one trial for each hand landmark). For the younger control condition, participants were directed to each landmark 10 times, meaning that data were obtained over 10 blocks. However, testing of the first PD participant determined that asking participants in this condition to complete all 10 blocks was not a viable option. Individuals with PD suffer from motor fatigue ability (Fabbrini et al., 2013) and multiple repetitive tasks led to an increased severity of PD symptoms such as tremors. For these reasons, all subsequent participants only completed 5 blocks of 10 trials each. This ensured we still had 5 estimations for each landmark, without causing distress to participants. Two different random orders were created for the presentation of the locations, and these were randomly assigned to participants. After testing, the occluding board was removed so that the recording could be used to ensure that the hand had not significantly moved throughout the testing period, before the recording was ended. Data Analysis To determine both the actual and estimated locations of the hands, the recordings were replayed using the Kinect Studio software. For each trial, the footage was paused when the participant had the straw pointed at the estimated location. The cursor was then moved to this point, and the x and y coordinates of the cursor was manually inputted into a spreadsheet. The same method was used to determine the actual position of each hand while the occluding board was not in place. The beginning and end of each recording was examined to confirm that the hand had not moved between the start and the end of the experiment. It was often the case that although the hand had not moved in any significant way, there was a couple of pixels difference in the position of a few landmarks. For this reason, the x and y coordinates of the hand position was recorded both before the board was placed, and after it was removed, and the average of these locations was used. For analysis, we were interested in the overestimation of the length of each finger and of the distance between each pair of adjacent knuckles. To calculate the length of each finger, the difference between the x coordinates of the tip and knuckle of the finger was calculated, and the same was done for the y coordinates. Pythagoras’s theorem was then employed to determine the distance, leading to the following formula: The same formula was adapted to determine the distance between each pair of knuckles. These distances were calculated for each block of 10 trials, and then the average was taken for each participant, before being compared to the actual measurements to calculate the percentage overestimation of each distance. For the detection of outliers, all estimations were plotted using RStudio. Code was adapted from Helbing (2020) to plot an ellipse for each hand location per participant, which encompassed at least 80% of all data points. Estimations outside these ellipses were treated as outliers and removed from further analysis. Setting the inclusion of data points to 80% meant that even for older participants, who only performed 5 trials per location, it was still possible for outliers to be seen outside of the ellipse. RStudio did not have the capacity to plot 10 separate ellipses at once, therefore 2 separate plots had to be made per participant. Before analysis, hand maps were also created using RStudio. Although these plots were not used for analysis, they helped to visualise the data. All hand maps can be found in the Appendices.
What person attributes influence the comprehension of written health information? A scoping review and critical appraisal
health literacy, comprehension, person attributes, health outcomes.
Increasingly, individuals are required to be actively involved in their healthcare. To do so successfully, individuals need to possess the skills and resources to be able to access, understand, and apply health information. Health communication guidance proposes that health information is not understood due to the mismatch between adults average literacy skills and the literacy skills required to comprehend health information. To tackle this, the use of plain language, such as shortening sentences and removing jargon, is promoted. Policies, however, do not commonly consider the impact of person attributes, such as age, education, and gender, on the comprehension of health information. To understand the nature and scope of current research, and whether person attributes do have an impact, a scoping review was conducted. The search strategy yielded 5,459 articles which were then screened, resulting in a final sample of 99 studies. Quantitative analyses and a critical appraisal revealed three main findings: (1) the research is heterogenous and evolving; (2) person attributes are not commonly used in analyses; and (3) when person attributes are included, the effects on comprehension vary. The findings and implications of this review have the potential to influence how future research is conducted, and crucially inform policies about the importance of person attributes on the comprehension of health information.
Stage 1: Identify the Research Question The current research is an updated scoping review, building upon earlier work by Davies et al. (in preparation), which seeks to answer: What person attributes affect or can be predicted to affect the response of individuals to written health information? Table 2 Form Developer: Rebecca A. James Search strategy methods Strategy Method Bibliographic Searched the following: Cumulative Index to Nursing and Allied Health Literature (CINAHL); PsycINFO; PubMed; and Web of Science (WoS). Journal Obtained all sources from the following journals between 2018-11-08 and 2023-05-05: Patient Education and Counselling; Health Communication; and Journal of Health Communication. Author Obtained sources from the following authors between the dates 2018-11-08 and 2023-05-05: TC Davis; Dan Morrow; Chiung-Ju Liu; Michael Paasche-Orlow; Lisa Soederberg Miller; Rima Rudd; and Michael Wolf. Reference Once the full text of the bibliographic, journal, and author searches were complete, the reference lists of the included items were examined to locate new and possibly relevant articles. Stage 2: Identifying Relevant Studies Sources were identified using four methods: (1) bibliographic search; (2) journal search; (3) author search; and (4) reference search. Grey literature was not searched due to concerns with the quality of the literature and possible time constraints. Excluding the reference search, all articles were published between 8th November 2018 to 5th May 2023. Details of each of the search methods are outlined in Table 2. Stage 3: Study Selection Once articles were imported to Rayyan, a free online software application for conducting reviews (Ouzzani et al., 2016), duplicate articles were identified and removed. Then articles went through a title and abstract screening whereby articles which did not include the following were excluded: (1) a measure of understanding, comprehension, or readability; (2) a quantitative outcome; (3) populations who are typically developed; (4) presentation of health information; (5) present original data (excluding reviews); and (6) presented in English or English was a first language. The exclusion criteria (Table 3) enabled the final sample of studies to be focussed and relevant to the review. Included articles were then read in full and the same exclusion criteria was applied. Articles which passed the full-text screening were then examined to identify relevant studies from the reference lists, and these references then underwent the same screening process outlined above. Following best practice recommendations (Levac et al., 2010), study selection was conducted by myself and TM (a MSc student) to reduce the chance of bias. Further, regular training and meetings took place (with TM and supervisor RD) to become familiar with the process and to discuss and resolve conflicting decisions between researchers. Table 3 Exclusion criteria for study selection Exclusion Criteria Reasoning Not a measure(-s) of understanding, comprehension, or readability, metacomprehension, or recall Articles which do not measure understanding, either directly, or indirectly, and do not measure readability of texts, are not relevant to the current review. Not quantitative outcomes Quantitative data is needed to understand average associations between the variation of person attributes and comprehension responses. Not typical development (excluding participants presenting cognitive or language impairments) Need to first understand how responses to health information varies within a typical population. Future research should be more inclusive to see how response varies in the whole population. No presentation of health information. The present review is concerned with comprehension and response to written health information. Not original data (rather than reviews). Although reviews themselves are not targets for review, they will be identified as potentially informative. Not English or second language speakers of English. There is limited information regarding how comprehension responses to text may be different or similar in different language, further, text properties may differ. Stage 4: Data Charting Articles were classified as being either an experimental, readability, or review article and as this paper focusses on research investigating the effects of person attributes, only experimental articles are analysed and reported. TM analysed and reported readability studies. Data extraction was completed so that information about the nature and characteristics of the study could be recorded. Data extraction was achieved by entering information (Table 4) into an online Qualtrics form which was developed and used by Davies et al. (in preparation) in their scoping review, which allowed for systematic extraction of information regarding the characteristics, methods, and findings of each study. To ensure that data extraction was reliable, a sample of studies were charted in parallel by myself and TM and were checked by RD for consistency. Table 4 Characteristics that will be extracted from experimental studies for data charting. Form Developer: Rebecca A. James the article title the article DOI, if available the article authors the article year of publication the location of data collection (location may be inferred by author affiliation, or reported in article text concerning the regional or national source of health texts, or the locality of participant recruitment) information about the composition of the participant sample (e.g., healthy adults, patients, etc.) the number of participants individual differences measures, if reported (e.g., gender, age, etc.) text type (the type of the health information text sampled, e.g., website, medicine information, etc.) text topic (the topic of the health texts sampled) text sample size (the number of texts sampled) if the study involved the manipulation of text properties, information on what linguistic or other features were manipulated, or what intervention was implemented (e.g., variation in organization or structure, in the inclusion of pictures, in readability, format, or other) what test of comprehension was conducted (e.g., verbal or written summary, true/false question, open-ended questions, multiple-choice questions, cloze, recall, etc.) what outcome measure was analysed (accuracy, or other) Stage 5: Collating, summarising and reporting the results Data charting resulted in the creation of a database of detailed information about the nature and scope of each article. To effectively make sense of such information, the original database of information was organised using thematic labels (Table 5). For example, the thematic label leaflet would be applied to articles which referenced handouts of medical information as pamphlets, leaflets, and brochures. This process enabled greater ease and clarity to conduct quantitative analyses and to provide a textual commentary of the findings. Quantitative analyses include frequencies and distributions of study characteristics observed in the sample, in addition to evidencing what direction of effect person attributes had on responses to health information. Directionality of the results, as opposed to reporting significance is deemed appropriate as the reporting of significance in reviews is misleading (McKenzie & Brennan, 2019). Following the synthesis and quantitative analyses, a critical appraisal of the evidence was conducted. Although this stage is optional for scoping reviews (Tricco et al., 2018; Levac et al., 2010), it was considered necessary to provide a sense-making of the conclusions we can reach given the synthesis of evidence. The appraisal followed guidance from the Synthesis Without Meta-Narrative (SWiM) guidance (Campbell et al., 2020) and Realist And Meta-narrative Evidence Syntheses: Evolving Standards (RAMESES) publication standards (Wong et al., 2013). Such guidance provides a framework Form Developer: Rebecca A. James for the critical appraisal to comprehensively answer the research question, and discuss the traditions, trends, and value of research. Unlike other reviews such as systematic reviews, formal assessment tools such as the Cochrane Risk of Bias tools will not be used as this review does not focus on examining randomised control trials and the research is too heterogenous to appropriately apply such tools (Levac et al., 2010). Table 5 Thematic labels for experimental studies location text type (e.g., consent form, decision aid) topic or health area (e.g., arthritis, cancer) intervention (e.g., counselling, drug) [study] design (e.g., illustration type, text readability) [study] implementation (e.g., different data visualizations, different organisation) outcome (e.g., comprehension, knowledge) [outcome] measure (e.g., multiple choice question, self-rated) individual differences (e.g., age, gender)
In part, in collaboration with TM. Supervised by Dr. Rob Davies
Can We Reduce Childhood Obesity in the Community? A qualitative Perspective that Discusses the Barriers and Strategies to Childhood Obesity within Miles Platting and Newton Heath.
Childhood Obesity. Poverty. Education. Barriers. Strategies. Recommendations.
Childhood obesity (CO), which can have long-term negative health issues, has increased dramatically over the last thirty years. Given this, NHS Manchester has commissioned this study, with a particular focus on the Manchester boroughs of Miles Platting and Newton Heath, due to the high rates of CO in those areas, to explore the relevant dynamics involved, understand the barriers to healthier eating/lifestyles and derive strategies to combat CO. A semi-structured interview style was utilised, with healthcare professionals. Within these interviews, the healthcare professionals commented on their experiences of CO within their job roles and what they believe to be the barriers for parents to be for CO. Their thoughts based on parents' experience with CO were formed due to working with parents and discussing these barriers with them. It was found that a child's home life massively impacts the likelihood of a child's obesity, with parental education, motivations and poverty playing significant roles, along with a parent’s lack of skills, knowledge, money, and time. Based on these factors, strategies are discussed that have been successful or unsuccessful previously, as well as ideas for future strategies. Based on these findings, it is suggested that collaboration between the different services offered within the Manchester area offers scope for improvement, while strategies to help reduce CO need to focus on a ‘show and tell’ aspect whereby individuals receive immediate support, such as having access to healthy food, while gaining the practical skills to help them create a sustainable change, such as learning how to cook or budget. These strategies are discussed about the general community and specific goals for NHS Manchester to increase the likelihood of healthier lifestyles being adopted.
Sample Nine people participated in the current study. Each of these participants were healthcare professionals over the age of 18. The term ‘healthcare professionals’ was a broad term for anyone in a professional capacity who dealt with CO in their job role. The initial participants were recruited from the contacts of the NHS Manchester Local Care Organisation, and then a snowball sample from these initial participants. The job roles presented in this sample included a business manager for a school, a school meal supervisor, a GP nurse, a bursary manager, and an array of service workers for the local community in different services, such as the Healthy Weight Team in Manchester. Each participant worked within Manchester, specifically Miles Platting and Newton Heath. Design and Materials Ethics Data collected in this qualitative study was reviewed and approved by the Faculty of Science and Technology Ethics Committee at Lancaster University (see Appendix A). All the participants were provided with information about this study and knew their ethical rights, such as the right to withdraw, confidentiality, and data protection. Procedure The initial participants were introduced to the researcher via email by a Manchester Local Care Communication member. Once this introduction had taken place, communication about the research and the arrangement of the interviews were discussed between the researcher and the participant through email. After completing their interview, these participants introduced the researcher to their other contacts through email (snowball sample). Email was the primary contact method for each participant and the recruitment process. Each interview was an online semi-structured interview, lasting between 30-60 minutes. The online software used was Microsoft Teams, which facilitated the discussion, recorded it and created a transcript. Due to the limitations of the software, the audio and visual information of the Microsoft Teams Meeting would be recorded. Therefore, the participants were informed of this limitation before the recording and asked if they would like to turn their cameras off. While the interview was ongoing, a discussion guide and prompts for further elaboration on their answers were used. Footnote The initial methodology planned to include interviews with parents who had children at a primary school age. However, the logistics, timing and lack of engagement made this impossible, meaning no parents were included in the sample. Due to this, a parental perspective from the viewpoint of healthcare professionals was asked in the interviews. The viewpoint was informative due to these healthcare professionals' interactions with the parents, which provided insight into parents' thoughts about CO. However, this is from a secondary source, so an element of accuracy needed to be considered.
The Specificity of Inhibitory Impairments in Autism and Their Relation to ADHD-type Symptoms
Findings on inhibitory control in autism have been inconsistent. It is proposed that this may be partly task-related, with different ‘inhibition’ tasks tapping different classes of inhibitory ability. Thus, children with autism (CWA) (N = 31) and typically developing controls (TDC) (N = 28) matched for verbal and non-verbal mental age completed three tasks of inhibitory control, each representing different inhibition subcomponents: a Go/No-Go task (delay inhibition), the Dog-Pig Stroop task (conflict inhibition), and a Flanker task (resistance to distractor inhibition). Behavioural ratings of inattention and hyperactivity/impulsivity were also obtained for each child to consider a possible source of heterogeneity in inhibitory ability. It was predicted that the conflict task would be more problematic for CWA, and that higher ADHD-symptom ratings would predict poorer performance. On the Go/No-Go task, CWA showed superior inhibitory function to controls – making fewer false alarm errors and better task sensitivity. On the Dog-Pig Stroop, CWA showed impaired performance compared to controls – making more accuracy and speed related inhibitory errors. On the Flanker task, CWA showed equivalent inhibitory performance to TD children. Inhibitory impairments were predicted by high ratings of inattention in CWA, but only on the Dog-Pig Stroop. It is argued that CWA are perhaps impaired on tasks of conflict, but not delay or resistance to distractor inhibition. This may reflect the additional working memory demands of these tasks, and suggests that inhibitory difficulty is not a core executive deficit in autism. Symptoms of inattention may be an important predictor of inhibitory heterogeneity amongst CWA.
Sessions were completed in a well-lit and quiet room, free of distractions. Participants were tested individually, and completed the three inhibitory control tasks (Go/No-Go task; Dog-Pig Stroop task; Flanker task) and two standardised measures (RCPM; BPVS) in counterbalanced order. Experimental session lasted approximately 40-60 minutes. All three inhibition tasks were written using Psyscript, and run on a computer using an OS X 10.6 operating system. Go/No-Go Task Task Design.On each trial, a shape (O, ∆, ⧠, or ◊) would appear centrally on the computer screen. The shapes were simple black line-drawings, subtending approximately 5° vertically and horizontally. Prior to the task, children were instructed to respond to three of the shapes by pressing a large external “star” button (i.e. “Go” stimuli), but to resist responding to a fourth shape (i.e. the “No-Go” stimulus). The shape designated as the “No-Go” stimulus was counterbalanced between participants. To generate a prepotent response, 75% of trials were “Go” trials requiring a button press, and 25% of trials were “No-Go” trials where the response should be withheld. The maximum inter-stimulus interval (ISI) (i.e. from stimulus onset to stimulus onset) was 2500ms. At the start of each trial, a fixation cross would appear at the centre of the screen for 200ms. This was then replaced by the stimulus, which remained on-screen for 200ms. After the stimulus offset, participants had a further 1000ms to respond, at which point the trial automatically terminated. Stimulus presentation was followed by a 1100ms pause before the next trial commenced. An error tone (“bleep”) was played immediately if the child made an omission error (i.e. failed to respond on a “Go” trial), or a false alarm (i.e. pressed the star button on a “No-Go” trial). A positive feedback-noise (“ping”) was played if the participant made a correct response. Procedure. Before starting the task, each child completed a warm up session to familiarize with the “Go” and “No-Go” stimuli. Training was terminated only when the child could correctly identify the required response for each shape. Children then completed a short practice block of eight trials containing all four stimuli presented in a fixed, but superficially random order. Then followed 144 experimental trials split into three 48-trial blocks, each separated by a short break. Stimulus presentation was randomised throughout each half block to avoid clustering of “No-Go” trials. The task (including training) lasted approximately ten minutes. Four measures of task performance were obtained: 1. Number of false alarms (or commission errors): “No-Go” trials on which the button was pressed. This is the main measure of inhibitory control, with false alarms representing failure to inhibit the prepotent button-press response. 2. Number of hits: “Go” trials on which the child responded. This is not a main measure of inhibitory control performance, but indicates how reliably participants detect targets when present and suggest the strength of the prepotent response generated. Hit-rates are also used for calculations of task sensitivity (see below). 3. Task Sensitivity: Estimates of participants’ task sensitivity can be calculated using signal detection theory (A0) and probability estimates of False Alarms and Hits. This permits differentiation between participants who make fewer false alarms, but also fewer hits (poor task sensitivity), and those who make fewer false alarms despite a good hit rate (good task sensitivity). This is important because a low false alarm rate could be due to a generally low response rate (for both “Go” and “No Go” stimuli). Task sensitivity (A0) is a nonparametric measure which ranges from 0.5 (chance performance) to 1 (perfect sensitivity), and is calculated as follows (Grier, 1971): A = 0.5 (H-FA) (1+H-FA) / [4H (1-FA)] Where, H = probability (Hits), FA = probability (False Alarms). 4. Hit Trial Reaction Time (RT): Although not a measure of inhibitory control per se, this might indicate between-group differences in processing speed and/or task-strategy. Dog-Pig Stroop Task. Task Design. The stimuli used in this task were two simple line drawings of a dog and a pig (see Appendix 4). Stimuli were presented centrally on the computer screen, subtending approximately 6° vertically and 9° horizontally. Two experimental conditions, each containing 32 trials were administered. In the control (baseline) condition, children were simply instructed to say “dog” when they see the dog-image, and “pig” when they see a pig as quickly possible. In the Stroop (i.e. inhibition) condition, children were instructed to say "dog" to pig images, and "pig" to dog-images, as quickly and accurately as possible. Children’s responses were recorded by an assistant during the task, and also audiotaped so that manuscripts could be subsequently checked by the experimenter. If a child made a mistake on a trial and then corrected themselves, their initial response was recorded. To estimate response latency on each trial, the experimenter would press a large external button as soon as the child made their initial response. Although this measure of reaction time is relatively crude, many of the children taking part would not have been testable with throat microphones which measure voice-onset. These technologies are highly sensitive to all sounds including subtle body movements, lip-smacks and vocalizations, reducing their reliability for use with participants who might have difficulty minimizing task-irrelevant movement or vocalizations. It is also notable that the additional error in reaction-time estimates induced by this method would be constant across groups. On each trial, the stimulus remained centrally on-screen until a response had been registered (i.e. the response button had been pressed). If no response had been registered after 3000ms had elapsed, the trial automatically terminated, and the message “Too Slow” was presented for 500ms. Stimulus presentation was followed by a 2000ms pause (inter-trial interval) before the next trial commenced. The maximum ISI was thus 5500ms. Procedure. All children completed the control condition first to provide a measure of baseline picture naming speed and accuracy[2]. After the control condition had been completed, children were presented with training slides to familiarise them with the Stroop naming procedure. After successfully completing the four practice trials, children would commence the 32-trial Stroop condition block. The task (including training) lasted approximately 7 minutes. Flanker Task Task Design. For this computer task, children were presented with two large arrow-shaped buttons – one pointing left and one pointing right. There were three experimental conditions: baseline, congruent, and incongruent. Children were asked to respond by pressing the arrow-button pointing the same way as the white target arrow, which was positioned centrally, subtending approximately 4° vertically and 6° horizontally. On baseline trials, the white target arrow was presented on its own. On congruent trials, the white target arrow was flanked by four red ‘distractor’ arrows pointing the same way as the target (e.g. ààààà). On incongruent trials, the white target arrow was flanked by four red ‘distractor’ arrows facing in the opposite direction to the target arrow (e.g. ßßàßß). It is thus only on incongruent trials that the distractors must be actively inhibited/suppressed for correct target identification. The maximum ISI was 2900ms. A fixation cross would appear centrally on-screen for 200ms. This was then replaced by the stimulus (neutral, congruent or incongruent), which remained on-screen until a button-press had been registered. If no response had been registered after 1200ms had elapsed, the trial automatically terminated. An error-tone (“bleep”) was played if the participant pressed the wrong arrow-button . If the child failed to respond before the trial terminated, an error-tone was played and a “Too-Slow” message was briefly displayed. When the child responded correctly, a positive feedback-noise was given (a “ping”). There was a 1100ms pause (inter-trial interval) between trials. Procedure. Each child first completed a series of familiarisation trials. This was followed by three blocks of 30 trials separated by a short break (90 trials in total). Each block contained ten baseline, ten congruent and ten distractor trials, which were distributed randomly. Error-rates and mean reaction times (RT) for neutral, congruent and incongruent trials were recorded. [1] Although a cut-off of 30-points is typically used with younger children, a slightly lower cut-off score is thought to be more accurate for use with older children/adolescents (Mesibov et al., 1989). This is due to the inclusion of one or two items on which older children with autism tend not to score highly (e.g. imitation). [2]Condition-order was fixed because a pilot study showed that if children completed the experimental (i.e. Stroop) condition first they had difficulty forgetting the ‘opposite’ rule in order to name the pictures normally for the control condition. This was shown by elevated error-rates and poorer naming speeds. Therefore, in order to obtain a realistic measure of ‘automatic’ (i.e. control-condition) picture naming speed and accuracy, and a stronger prepotent response, it was decided appropriate to fix the order of condition presentation (Control, then Stroop). Although this may lead to practice effects, this effect is constant across groups.
Typeface and taste: The bittersweet effect of typeface on the perception of taste
This article aims to explore how the visual features of typeface on a product’s packaging, are capable of altering one’s taste experience with the product within through cross-sensory correspondences. A total of ninety-two participants from a selection of university graduates were selected to take part in one of three studies rating yogurts, typefaces and the interaction between the two. While visual features of the typeface like thickness and heaviness did not directly affect the rating of a products perceived thickness and weight, the typefaces were able to trigger different experiences of bitterness. When presented on the yogurt container, the more angular, thin typeface Palatino Italic caused the yogurt to be rated as significantly more bitter than the rounder, thicker font Cooper Black. Secondary tests found that the two typefaces rated alone, without the yogurt, did not possess the same significant differences in bitterness. However, they were rated as significantly different on the other scales measured, thus raising the question of exactly how the fonts were capable of manipulating participant’s taste experience. The study addresses this question and looks further into how typefaces perceptual qualities change once the letters presenting it are capitalised.
Rating Chart A rating chart (found in Appendix 4) was designed to allow participants to select the most neutral yogurt by ordering them in terms of the adjectives rated in the main study. These were thick to thin, heavy to light, dull to sharp, sweet to bitter and slow to quick. The chart contained a three point scale with related variables anchored at each end. Participants were then able to fill in which yogurt (A, B or C) they believed possessed the extremities of each variable pair (i.e. the thickest and the thinnest) leaving the most neutral yogurt being rated as somewhere between the two. Products As natural yogurt appeared to be the plainest yogurt in terms of flavour, colour and texture, three natural yogurts were selected for the pre-test. The first yogurt ‘A’ was the cheapest home-brand yogurt from Morrisons. Yogurt B was slightly more expensive (Yeo Natural), and the third (yogurt C) was the most expensive plain natural yogurt available (Onken). All yogurts were purchased from Morrisons Supermarket and cost between £1.00 and £2.00. Packaging Because all three products contained packaging with commercial labels which used a combination of various typefaces, colours and shapes, the yogurt had to be removed from the containers. The yogurts were then placed in three identical bowls and set on a table. A piece of paper in front of each informed the participant which was yogurt A, B and C. Procedure In turn participants were brought into an empty room and asked to sit at a desk in front of the three yogurts. They were presented with an information sheet, consent form and the rating sheet (Appendix 1, 2 and 4) and asked to sample each yogurt as many times as they felt necessary to rate which of the three was the least extreme in regards to the variables rated. They were each given a plastic spoon to test the yogurt and asked not to touch the bowl in case its weight affected their perception of the product. They then used the pen provided to rate which yogurt (A,B or C) possessed the least extreme qualities. Once the twenty participants had completed the test they were given the opportunity to ask any questions and presented with the debrief sheet in Appendix 3. Their results were then correlated and ‘Yogurt A’ was clearly found to be the most neutral yogurt of the three in terms of the variables rated. Main Study Participants Between June 2014 and July 2014 forty-eight students and recent graduates (Male= 36, Female= 12) aged between eighteen and fifty-four years old (M= 23.25, SD=4.86) from Lancaster University were recruited as part of a volunteer sample to take part in this study. They were informed of the study through a monthly newsletter emailed to their University email address by a University Administrator. The students came from a variety of academic years and subject areas. All participants confirmed that they had no deficits regarding their ability to smell or taste, nor any allergy to dairy. Materials Rating Chart The rating chart was designed to allow participants to quantify their perception of the product. Each quality was presented on a scale with one extreme anchored horizontally to the other (See Appendix 5). So for the adjective pair thick-thin participants would state if the product was ‘Very Thick, Quite Thick, Slightly Thick, Neither Thick nor Thin, Slightly Thin, Quite Thin or Very Thin’. This produced a seven-point scale for each variable rated. Several qualities that had previously been identified as sharing cross-modular correspondences linked to shape, and influencing aspects of flavour were implanted within the rating chart. In addition to being held by one or several modalities, they were a sample of adjectives both able and unable to be conveyed directly by visual qualities of the typeface to the yogurt (for example a thick font may lead to the yogurt being rated as thick but a typeface is unable to directly convey bitterness through its visual features). The adjectives rated were thick-thin, heavy-light, sharp-dull, bitter-sweet, quick-slow. The order by which these variables were rated was swapped between participants in order to reduce order effects. It was predicted that the adjectives thick, heavy, dull, sweet and slow would be aligned, while thin, light, sharp, bitter and fast would share conative meaning. Products Following the preliminary test yogurt A (Morrison’s own Natural Yogurt) was selected as the most neutral yogurt in terms of the variables rated and yogurt tested. In effect the yogurt was most frequently rated as neither the thickest, nor thinnest yogurt of the three tested, as so on across the variables rated. As a result yogurt A was chosen for the study. Regardless of the label on the pot, the contents within were always yogurt A, leading to participants rating the same yogurt twice without their knowledge. Packaging There were four parts to the packaging: the typeface used; the brand name in which the typeface was printed; the label displaying the brand name; and the pot containing the yogurt. Each element of the packaging aimed to trigger as few cross-sensory perceptions as possible, with the exception of the typeface being tested. After a great deal of consideration, the two typefaces chosen were Cooper Black and Palatino Italic. Walker et al had noted that these typefaces possessed a variety of qualities capable of triggering cross-modular correspondences strong enough to induce a congruency effect between word meaning and typeface characteristic (Lewis and Walker, 1989). As a result they seemed the most likely typefaces to induce cross-modular correspondences relating to taste. Additionally they were particularly representative of typefaces as a whole possessing characteristics such as italics, roman and bold. Visually Cooper Black is much thicker and rounder than Palatino Italic. Palatino Italic also appears to convey speed and sharpness, pointing forward at an angle. Existing brand names and real words could not be used to display the typeface due to the potential confounding connotations they may carry. Additionally if both typefaces were presented in the same brand name participants would be more likely to realise that both yogurts were indeed the same. Therefore two non-words had to be selected as product brand names. Sound symbolism is known to have an effect on the perceptions activated by a word, in particular Klink noted that brand names containing front vowels were associated with more angular brand marks than back vowels (Klink, 2003). To avoid this effect confounding the ratings, a combination of front and back vowels were present in each brand name. Moreover, because the positioning of back and front vowels has been highlighted as a factor influencing perception, the order of the front and back vowels were changed between the two non-words. This process was inspired by a similar method by Klink and Wu, where brand names were built using vowels and letters conveying different meanings (Klink and Wu, 2013). The two non-words generated from this procedure were ‘Bemdom’ (front/closed vowel ‘bem’, back/open vowel ‘dom’) and ‘Nordin’ (back/open vowel ‘nor’, front/closed vowel ‘din’). As seen in Figure 1, these names were printed in black on white rectangular sticker paper creating the label. Printed in font size 14, their first letters were capitalised to appear more like a product name. Four versions of the label were created: one with the curved typeface (Cooper Black) stating Bemdom; one with the curved typeface stating Nordin; one with the angular typeface (Palatino Italic) stating Bemdom and one with the angular typeface presenting Nordin. Figure 1: Examples of the four yogurt pots presented to participants. Presented first is Bemdom in Palatino Italic, followed by Nordin the same type, Nordin in Cooper Black and Bemdom in Cooper Black. The labels were attached to the circular lids of ninety-six clear 60ml plastic sample pots displayed in Figure 2. In an attempt to counter-balance the effect of a circular shaped lid on the rating of the yogurt, the sticker containing the brand name was cut into the more angular shape of a rectangle. The pot was also clear allowing visibility of the white yogurt contained within it, rather than being coloured packaging that may have its own connotations. Figure 2: The pots used to present participants with the yogurt and the typeface. With the type of spoon used to consume yogurt being found to affect one’s perception of yogurt, all participants consumed the yogurt with the same type of white plastic spoon displayed in Figure 3 (Piqueras-Fiszman and Spence, 2011). As the testing pot was already plastic and the yogurt white, a plastic white spoon seemed the best option for reducing the number of new extraneous variables introduced into the study. Figure 3: The plastic spoon used for sampling the yogurt. Research Design The study involved a 2 (type of typeface) x 2 (non-word used) x2 (order in which the font was presented) design. It was conducted using a repeated measures design with each participant rating each typeface and non-word although in different combinations. The order of both the typeface and non-word used was counterbalanced throughout the study leading to the creation of four participant groups. Procedure Participants were randomly split into four conditions; two of whom rated ‘Bemdom’ in Cooper Black and ‘Nordin’ in Palatino Italic but in contrasting orders, and two of whom rated ‘Bemdom’ in Palatino Italic and ‘Nordin’ in Cooper Black, again in contrasting orders. All groups received exactly the same experimental procedure and exactly the same yogurt in each pot. The only differences were the order each typeface and non-word were presented, and which non-word was allocated which type. Participants were not informed that the samples of yogurts were identical, and were encouraged to believe they were two different yogurts through use of different brand names. Once the participant was seated they were randomly assigned to a research group, then asked to read the participant information sheet (Appendix 1) and complete the consent form shown in Appendix 2. Once they had had the opportunity to ask any questions that came to mind, two boxes were placed on the table in front of the participant. Each had ‘Nordin’ or ‘Bemdom’ printed on it in either Cooper Black or Palatino Italic depending on the group they were assigned to. In order to provide a contrast effect highlighting the package’s typeface, the two pots of yogurt were taken from larger boxes sharing their name and label, which were present on the table throughout the study. This again aimed to reduce participant’s likelihood of identifying the yogurts as the same. The participant was then presented with a yogurt pot from one of the boxes and asked to write the product’s name on the rating sheet (Appendix 5) ensuring that they had paid some attention to the name and in doing so, the typeface. To ensure that the weight of the yogurt didn’t confound participant’s perception of the product, the pot of yogurt was placed in a tube securing it in place on the table while the participant sampled it. Participants were given a plastic spoon to consume it with and still water was provided for the participants to cleanse their mouth with between tastings. The participant was welcome to eat as much or as little of the produce as required to rate it on the several variables. Once they had finished rating the first yogurt it was removed from the tube and replaced by the second. The original pot was left on the table in order to allow contrast between the names and more importantly typeface. When the rating was complete participants were given the debrief sheet (Appendix 3) and the opportunity to ask any questions before being thanked for their time. Ethics An ethics review rated the study as low risk to participants. As the main risk was that of an allergy to the yogurt, all participants were asked twice if they were allergic to dairy products- once through the consent form and once verbally. Informed consent was collected from all participants. Participants were also asked if they were happy to participate in the experiment and told they had the right to withdraw at any point without facing any negative consequences. The participants were debriefed after, being informed of the reasoning behind the study. All interviews followed the BPA code of conduct. While a small amount of deception was used to imply that the two pots of yogurt were different, participants were never explicitly lied to. During debriefing, not one participant stated that they had had a problem with the small lack of full disclosure.
Farmer and Non-Farmer Attitudes towards Alternative Animal Products
farmers, plant-based alternatives, cultured products, COM-B Model, Transtheoretical Model
Farmers’ livelihoods and way of living could be argued to be under threat from the simultaneous rapid rise of plant-based products, development of cultured products, and our growing understanding of the detrimental impact of traditional animal agriculture. Little research has investigated farmers attitudes towards cultured and plant-based products. Furthermore, famers appear to have limited awareness of these animal product alternatives. This study presented 45 omnivorous farmers and 53 omnivorous non-farmers with information about plant-based burgers, cultured burgers, plant-based milk, and cultured milk. Product acceptance and COM-B facilitators and barriers were explored. Farmers were less accepting of all alternative products than non-farmers, suggesting that their vested interest in the continuation of traditional animal agriculture affected their attitudes towards alternative products. Closer inspection of farmer acceptance suggests that personal investment in animal agriculture also led to differences within farmers, with occupational farmers being less accepting of the products than the members of farming families. The findings are interpreted using the Transtheoretical Model to suggest that regarding the adoption of alternative products, occupational farmers appear to be in the rejection stage, whereas members of farming families appear to be in the contemplation stage. As occupational farmers had more negative attitudes towards the alternative products, they appear more likely to consider the alternatives a threat to their livelihood.
Participant Recruitment and Exclusions Participant recruitment followed a pre-registered plan (https://aspredicted.org/blind.php?x=QL3_H96). Between July and August 2022 two groups of participants were recruited: adults with experience of livestock farming (Farmers), and a comparison group of adults without experience of livestock farming (Non-Farmers). Farmers make up a very small percentage (0.2%) of the UK population (DEFA, 2021) so we included current farmers, retired farmers, farm workers, and members of farming families. Fifty-five livestock farmers predominately living in Gloucestershire were recruited using snowball sampling. Farmers that were known to the author were first contacted via telephone, social media, or visited in-person. Interested participants were provided with the URL link to the questionnaire, a brief description of the study, and a request to forward the information to other individuals in the farming community. Individuals without internet access received a paper copy of the questionnaire. Sixty-one non-farmers were recruited through snowball sampling in the same method as for farmers. As farmers are typically older males (DEFRA, 2019), we attempted to match the ages of the non farmers to the farmers and effort was taken to recruit female farmers and members of farming families. Our recruitment plan was to recruit a minimum of 40 participants per group. To qualify for the study, farmers and non-farmers had to be omnivores. A further 23 farmers and 10 non-farmers were recruited using Prolific by pre-screening for those in the ‘Agriculture, Food, and Natural Resources’ employment sector, the description of the study also encouraged participation among those with “experience of working with farmed animals.” A total of 130 participants consented to participate: 55 farmers, 61 non-farmers, and a further fourteen who were excluded as they did not reach the demographics section so could not be classified into a group. Following our preregistered exclusion criteria, 18 participants who reported dietary restrictions were excluded (10 Farmers and 8 Non-Farmers). The final sample consisted of 45 Farmers and 53 Non-Farmers. Design and Procedure A 2x4 mixed design was used, with Group as a between-subjects factor with two levels: Farmer and Non-Farmer, and Product type as a within-subjects factors with four levels: plant-based burgers, cultured beef burgers, plant-based milk, and cultured cow’s milk. Participants completed an online questionnaire on Qualtrics (Qualtrics, 2005) that “drew attention to existing and emerging food innovations and explored beliefs and attitudes towards these products “, see Appendix A. The questionnaire took approximately 15 minutes. Ethical Statement The study was approved by Lancaster University’s Department of Psychological Ethics Committee. Participation was anonymous and Farmers were not asked to disclose the name or location of their farm. All participants gave their informed consent before accessing the questionnaire. On completion of the questionnaire, participants were debriefed, reminded of their right to withdraw their data, and were thanked. Materials The questionnaire comprised of six sections: vignettes, product acceptance, facilitators and barriers to product acceptance, consumer behaviour, demographics, and farming information. Vignettes Participants were presented with a brief description of factory farming, including its prevalence in the UK and the negative consequence on farmed animals and the environment. See Appendix B for full vignette details and references. Factory farming was chosen as it is the main method of farming in the UK (FAIRR, 2016). Participants were then presented with brief descriptions of plant-based products and methods of creating cultured animal products. Product features were compared against traditional animal products, including the sensory qualities, nutritional content, animal involvement, and environmental impact. Using a similar table to Van Loo et al. (2020), participants were presented with a comparison of the relative environmental impact of a plant-based soya burger and a cultured beef burger compared to a factory farmed beef burger
The Effect of Sleep on the Processing of Emotional False Memories
People often think they remember events and information that in fact never happened. In previous studies using the Deese-Roediger-McDermott (DRM) paradigm, participants viewed lists of semantically related words, and during testing were more likely to accept as seen words that were related to the lists but were actually unseen, indicating a false memory. Research suggests that sleep promotes this effect, as does the use of negatively valenced stimuli, although the effect of emotion is disputed. The current study investigated what effect emotion, in particular valence, has on false memory formation, and whether sleep promotes emotional false memories. Fifty participants were tested on their recognition performance using an emotional and neutral DRM paradigm after a 12-hour period of sleep or wake. As predicted, we found an increase in false recognition of negatively valenced lure words, as well as an overall effect of emotion, with emotional words leading to increased false recognition compared to neutral. We failed to replicate any sleep effect on performance accuracy of neutral or emotional memory, although the response time data indicates some effect of sleep on emotional memory performance. The quality of participants’ sleep and design of the current study are explored as possible explanations for this lack of a sleep effect. This study therefore indicates that emotion plays a significant role in the formation of false memories independent of sleep.
Negative and positive DRM word-lists and critical lures were taken from Brainerd, Holliday, Reyna, Yang, and Toglia (2010) who controlled for other properties that are thought to affect false memory formation, including concreteness, meaning and frequency of words (Roediger, Watson, McDermott, & Gallo, 2001). Neutral DRM lists and critical lures were taken from Stadler, Roediger, and McDermott (1999). Two separate lists were formed, one with negative and neutral words, and the other with positive and neutral words (see Appendix A for word-lists). Participants in both the positive and negative condition viewed the same five lists of neutral words, as well as ten negative or positive word-lists. Mean valence and arousal scores for word-lists and critical lures were taken from the Affective Norms for English Words (ANEW) (Bradley & Lang, 1999). Independent samples t-tests showed that positive words had significantly higher ratings of valence than negative t(11.41) = 7.42, p < .001, and neutral words, t(13) = 7.43, p < .001. Negative words had significantly lower ratings of valence than neutral words, t(13) = 2.31, p = .038. Furthermore, negative and positive word-lists did not significantly differ in terms of arousal, t(12.92) = 0.52, p = .613, however neutral words had significantly lower ratings of arousal than positive, t(13) = 2.67, p = .019, and negative words, t(13) = 4.87, p < .001. It was also important that word-lists were controlled in terms of frequency and BAS. Frequency scores were taken from the MRC Psycholinguistic Database (Coltheart, 1981). Independent samples t-tests showed no significant difference in frequency ratings between negative and positive word-lists, t(18) = 0.18, p = .816, positive and neutral word-lists, t(13) = .35, p = .735, and negative and neutral word-lists, t(13) = 0.50, p = .624. BAS ratings were taken from the University of South Florida Free Association Norms (Nelson, McEvoy & Schreiber, 1998). There was no significant difference in ratings of negative and positive words, t(18) = 4.92, p = .629, positive and neutral words, t(13) = 0.32, p = .757, and negative and neutral words, t(13) = 0.89, p = .391. (See Appendix B for mean ratings). For critical lures, independent samples t-tests showed that positive lure words had higher ratings of valence than negative lures, t(15.11) = 11.20, p < .001, and neutral lures, t(11) = 4.24, p = .001. Negative lures had significantly lower ratings of valence than neutral lures, t(11) = 3.62, p = .004. There was no reliable difference between ratings of arousal for negative and positive lures, t(18) = 0.22, p = .828, positive and neutral lures, t(11) = 1.08, p = .305, and negative and neutral lures, t(11) = 1.62, p = .134. There was no reliable difference between frequency ratings of negative and positive lures, t(18) = 1.14, p = .268, positive and neutral lures, t(13) = 0.55, p = .593, and negative and neutral lures, t(13) = 1.11, p = .287. (See Appendix B for mean ratings). During testing, participants viewed 60 words in total; two previously seen from each DRM list (total of 30), the critical lure associated with each list (total of 15), and an unrelated word for each list (total of 15). Unrelated words were taken from lure words of unused DRM lists, as well as from Kousta, Vinson, and Vigliocco (2009), who developed emotional and neutral word-lists using the ANEW database. Unrelated words were matched to DRM word-lists in terms of valence, resulting in five unrelated neutral words, ten unrelated negative words and ten unrelated positive words. All words were presented in Courier new bold, black font, lower case and in 18-point. Participants in the sleep condition were required to wear an actigraph sleep monitor to more accurately measure their time spent asleep and the number of awakenings. All participants were given a questionnaire before each session to collect data on sleep habits, caffeine and alcohol intake (see Appendix C), and those in the wake condition were instructed not to nap throughout the day. Procedure Participants were randomly allocated to either the wake or sleep group, with those in the wake group trained on word-lists at 9am and tested on the same day at 9pm. Those in the sleep group took part in the training session at 9pm, and were tested the following day at 9am. Participants were randomly allocated to the negative or positive stimuli condition. During the training session, participants were first asked to fill out a questionnaire to assess sleep habits and caffeine and alcohol intake. Participants were then required to sit approximately 60cm from the computer screen, and were presented with 15 lists of 12 words presented one word at a time in the centre of the screen. They were first presented with a fixation point for 500ms before the words from one list were presented for 1500ms each. After each list participants were presented with three maths problems to solve for 1000ms each as a distractor task, in order to prevent participants from rehearsing words they had seen. Maths problems were presented in a random order for each participant, and each problem was only presented once throughout the task. After the three maths problems were presented, the fixation cross reappeared and participants were given another list to remember. The order of word-lists was randomised, and the order in which each word in a list was presented was also randomised. Participants were then asked to return 12 hours later after a period of daytime wakefulness or overnight sleep. During the second session, participants first viewed a fixation cross for 500ms, and then the test words were presented to participants one at a time in the centre of the screen for 120ms. Participants were required to identify whether they thought they had seen the word in the previous session or not. They did this through the press of a key on the keypad, with a press of zero corresponding to an old word (previously seen), and one corresponding to a new word (previously unseen). The numbers zero and one on the keypad were labelled ‘old’ and ‘new’ respectively, to aid participants. Participants were not given a response deadline. Participants then saw the fixation point again 500ms after giving their response, before another word appeared on the screen. All words were presented in random order.
Sexualised Advertising through Instagram: An exploration into the effects this has on female appearance satisfaction
This study explored the beliefs and opinions held by females aged 20-23 years on Instagram. It aimed to uncover possible effects that exposure to sexualised content and beauty standards could have on young female’s appearance satisfaction. Previous literature has addressed extensively how social comparisons and internalisation of beauty ideals can negatively affect females, increasing body dissatisfaction. This research aimed to expand these findings, exploring how body and facial attractiveness seen online can affect appearance satisfaction as a whole. Previous studies have determined that internalisation and social comparison are prevalent in women that compare themselves to others on Instagram. These theories along with objectification and cultivation theory are utilized to comprehend female’s perceptions of beauty and how it could be implicating them to act in a sexualised way online. The study consisted of two focus groups, each lasting approximately one hour. A convenience sample was used recruiting university students. A semi-structured interview schedule was utilised to allow for rich data to be produced. The data was categorised by using thematic analysis strategies of coding, mapping and deducing themes. The research conclusion found that women did report decreased appearance satisfaction when viewing ‘beautiful’ girls on Instagram, social comparisons was identified as more salient with peers, yet they did also report comparing themselves with reality television stars. Findings also reported that internalisation of beauty ideals was strong, they remark television and the social media for ‘normalising’ beauty standards. Lastly, participants were found to self-objectify themselves in a sexual manner more for Instagram than other social media sites.
This study explores the possible effects social networking site Instagram has on young females, in relation to their appearance satisfaction. Overall, it aims to add to existing literature within this field and other domains such as sociology and women’s studies, whilst also extending previous literature, as this research looks beyond body satisfaction and addresses appearance satisfaction completely. It also provides scope into understanding Instagram and the magnitude of its effects on the user, as the majority of previous literature focuses on Facebook. 3.1 Research Design Two focus groups were conducted, each lasting approximately one hour. The focus group was held in a small lecture theatre at Lancaster University in the Management School (Lecture Theatre 12). A phenomenological approach was applied as the research aims to explore a group of participant’s experiences and aims to further make sense of these experiences (Creswell, 2013). Application of focus groups was applied as it allowed for a semi-structured narrative of findings. The participants were able to express their thoughts, feelings and opinions in relation to this topic of research. A semi-structured interview type was applied as it allows for more flexibility, allows for more rapport building and these aspects can lead to richer data which enters more novel spheres (Smith & Osborn, 2003). 3.2 Sampling The overall sample consisted of 13 female students studying at Lancaster University between the ages of 20-23 years. This age was used as research has suggested that young females within these age brackets tend to be heavy Instagram users. These participants were recruited through convenience sampling, no specific recruitment criteria concerning use of social media was applied, in order to allow this variable to fall out naturally in the sample. 3.3 Research Procedures 3.3.1 Materials The participants were given an information sheet and a consent sheet at the beginning of the focus groups. These detailed the purpose of the study, outlined the potential risks/benefits, and provided the participants with information regarding their anonymity and confidentiality as well as making them aware of their right to withdraw. During the focus group participants were asked to discuss images which included advertisements of brands and celebrities and well as images showcasing cosmetic enhancements (See appendix E). The focus groups were recorded using a MacBook Pro, the recordings were stored in a file on the laptop, which was password protected. 3.3.2 Interview Schedule A discussion guide was created for the focus groups which outlined a schedule for conversation and was used to informally guide the discussion. Guides are used to be suggestive, not prescriptive (Smith and Osborn, 2003). The discussion guide contained open-ended questions which were used to detect Instagram usage, opinions, beliefs and perceptions. However, it must be noted that some additional questions were asked during the focus group, coherent with its semi-structured nature to gather richer data where applicable. Lastly, the discussion guide was created to address the research aim. 3.3.3 Ethical Considerations The research design adhered to Lancaster’s Universities ethics committee which is in line with the British Psychological Society’s Code of Ethics and Conduct (BPS, 2009). Each participant gave informed consent, they were informed of the confidentiality agreement, which was to anonymise their identity when using the data by given each of the individuals a pseudonym (Forrester, 2010). Participants were ascribed a pseudonym from the letters A-L to protect their identities. They were informed of their right to withdraw and were given a debrief sheet at the end of the focus groups. Data recorded was discussed only between the researcher and the supervisor. 3.3.4 Data Analysis Procedure Data analysis from the research findings are used in a way which helps to manifest the respondent’s discussion, to examine possible beliefs or constructs as portrayed by the participants (Smith and Osborn, 2003). This aims to understand the complexity of the content, rather than depicting general frequency. The transcript is used to interpret meanings beyond the literal meaning, including context and deducing themes from the data. Thematic analysis was used to analyse the transcribed data. This method was utilised due to its flexible nature, which helps to produce rich descriptions and accounts of the topic being studied (Braun & Clarke, 2006). The research followed the 6-stage account as outlined by Braun and Clarke (2006). Stage one of their model involves familiarity of content, which is done by re-reading the transcripts. Stage two involves identifying key features and giving them a relating initial code. Thirdly, themes are deduced from the features by combining relevant codes, some create sub-themes and others are able to be subordinate themes. Fourthly, the themes are broken down and refined into separate themes, in the fifth stage these themes are used to create a thematic map. Lastly, each theme is written up and analysed to the fullest extent.
Interacting in a Virtual Environment, the role of visual perception, the human hand and the recognition of rescaling.
Visual Perception Rescaling effects Virtual Reality Hand-size Constancy Body size effects.
A common assumption from perception research is that we can estimate the size of the environment by using our own hand as a perceptual metric by comparing the size of our hand to the environment. Further research aimed to explore this effect by manipulating the size of the hand to see if it could accurately estimate the size of objects and found that even when the hand was magnified or minimized people perceived their hand to stay around the same size. The effect that the hand is perceived as a constant size is called the hand-size constancy effect and the current research has aimed to expand on previous research by examining if hand-size constancy still occurs even when hand size increases whilst in the presence of the participant. This research was done using a new method which eliminates more demand characteristics than previous hand-size constancy research. Participants took part in a virtual scenario using virtual reality in which each time a participant attempted the task, their hand or non-corporeal hand gradually increased in size, until a total of 38% size increase. Results from this research found that participants did recognise their hand size increase in the non-corporeal condition and did not notice hand size change in the real hand condition. These results support previous research by finding that hand size constancy can still occur even when eliminating demand characteristics that may have occurred in previous research using a more discrete method.
Participants. The participants were 30 typically developing adults between the ages of 19 and 50 (N = 30, 12 male and 18 female, M = 24.39 years old, SD = 7.76 years). Participants were mainly recruited from a major university in the North West of England using posters on the university campus and online advertisements. Participants received £5 in return for their participation. Materials The current research used the Oculus Rift with leap motion to detect hand movement. The experiment was created using the Unity game engine software to create a programme called the virtual bowling alley. The virtual bowling alley was created to mimic a real table top bowling alley in which all the items in the game were created for this experiment including the bowling ball, the pins and the virtual hand used in the experiment. Two questionnaires were essential to this study, “The Embodiment Questionnaire” and “The Virtual Presence Questionnaire”. The Embodiment questionnaire was an adaptation from Sanchez-Vives’ research which explored visual hand illusions (Sanchez-Vives, Spanlang, Frisoli, Bergamasco, & Slater, 2010). The embodiment questionnaire was used to test the extent of different variables the participant may exhibit whilst within virtual reality. Variables related to ownership of limbs in virtual reality e.g. “I sometimes felt as if my hand was located where my virtual hand was to be” the illusion of movement which looked at how much your virtual arm impacted on the movement of your real arm, validity which looked at how your movements impacted on your virtual arm and control regarding how much control you had of your virtual arm. The Embodiment Questionnaire uses a 7-point Likert scale in which you rate how much you agree with the statement (Appendix 1). The other questionnaire required for this study was “The Virtual Presence Questionnaire” which was an adapted version from Usoh’s paper looking at presence questionnaires (Usho, Catena, Arman, & Slater, 2000). The virtual presence questionnaire was used to examine how much the participant rated their immersion within the virtual scenario. Rating of virtual immersion was done through questions which examined whether their sense of immersion whilst being within the virtual scenario was stronger than their sense of place in their actual location within the virtual reality lab. For example, questions like “To what extent were there times the virtual bowling scenario was reality for you” was used to examine immersion and presence within virtual reality. The virtual presence questionnaire also used a 7-point Likert scale (1 = disagree, 7 = agree) (Appendix 2). Other materials required were a calculator to count the amount of bowling pins knocked down each attempt and to total the amount of bowling pins knocked down per participant. All the appropriate ethical documentation was also required (Information sheet, Virtual Reality health and safety sheet, consent document and debriefing sheet). Procedure After the 30 participants required for the study were obtained, the participants were asked to sign a digital calendar in which they selected which day they were free to take part in the study with the promise of a 30-minute experiment and £5 reward for taking part. Participants were advised to arrive to the lab 10 minutes prior to the study and when they did arrive they were greeted by the researcher at the door of the lab. After a short introduction, the participant was then sat down at a table with some documents and writing equipment. The participant was asked to look at the study information sheet first, this sheet contained contextual knowledge about the study regarding the task that they would get involved in. After the participant stated that they understood all the information on the information sheet then they were given the ethics consent form to sign. The ethics consent form contained all the participants ethical rights (right to withdraw, anonymisation of the data etc…), the participants were advised to carefully read through the sheet to make sure they understood their ethic rights and asked to sign their name, age and date on the ethic sheet. Also, on a separate piece of paper, the researcher noted the participants participant number which was used to code the data anonymously. When the participant completed the ethics consent form, they were told that the experiment would now begin. The participant was escorted to a different desk with a computer set up on the desk. Noticeably, the computer was set up in a way in which the chair was at a set distance from the oculus rift sensor to allow for full immersion. The participant was sat down on the chair that was at the set distance away from the computer, in which the computer was set to the home screen and the researcher assisted the participant in putting on the oculus rift head mounted display (HMD), the HMD had a hand sensor attached to the front of it to detect hand movement. When the participant was sat down, they were asked to confirm that they were comfortable with the HMD on and that they could see clearly. When the participant gave consent, they were told that they were going to enter the virtual bowling alley now, the virtual bowling alley was an in-house created virtual scene used for this experiment. The virtual bowling alley was created in the unity engine using C++ to create virtual objects such as the pins and ensuring they had an interaction engine script attached to them to give them physics. The virtual bowling alley was a table top bowling simulation, created with the intention that there would be a lot of hand exposure during the experiment as the participants would have to use their hands to push the ball and knock over the pins Participants were assigned to 1 of 2 groups; the hand group or the non-corporeal hand group. The group the participant was assigned to impacted on what type of hands they would have during the virtual bowling scenario, for example, when entering the virtual bowling alley in the hand group your hands would be regular virtual hands that are created to mimic real hands. (Figure 2). Participants who were assigned to group 2 (the non-corporeal hand group) when entering the virtual bowling alley, they would see blocks in place of their hands, these block hands were created to replace their hands in virtual reality with objects that could complete the same tasks that a hand could, but did not represent the hand in any way, a non-corporeal hand. When participants entered the virtual bowling scenario and confirmed that they were calibrated to the bowling scenario (their visual view point was correct, and they could move their hands around accurately) then they were told they had 20 attempts to knock down as many pins as they could, with 10 pins an attempt this means there was a total of 200 pins. Each time an attempt was completed by the participant, the experiment would press a key on the keyboard which reset the pins and the bowling ball for the participant. Each time the virtual bowling alley attempt was reset the participants hand (group 1) or cubes (group 2) increased in size by approximately 2% per bowling task attempt until they completed their 20 attempts in which their hand/ non-corporeal hand would have increased in size by 38%. Also, it is worth mentioning that each time the bowling ball attempt was completed, and the alley was reset the bowling ball would randomly change from bigger to smaller sizes (10 different sizes per experiment between 50% increase in size and 50% decrease in size, twice per size). The changes in the ball size were required so that participants did not use the bowling ball as a reference of scale to compare to their change of size in hands or cube hands (non-corporeal hands). When the participant completed the 20 attempts of the bowling task, the virtual bowling programme would automatically exit, and the participant was asked to take off the HMD and escorted back to their first seat which was the table they completed their consent form. The experimenter also made note on a separate sheet of the participants total bowling pins knocked down out of 200. When the participant was sat down at the table the experimenter would then hand the participant a sheet with 2 questions on it. Question 1: “Did you detect any changes whilst in the virtual environment?” this is a yes or no response. After the participant answered question 1 they were then asked question 2 “If hand size was manipulated would you estimate your hand changed in size or not?”. The response for question 2 would also be a yes or no response, it is worth noting that if the participant did respond with “yes” to question 2, then the researcher asked them if they estimated if hand size increased or decreased in which the experimenter would ask the participant to note this response underneath question 2. After they answered the 2 questions regarding the virtual bowling alley the participant would then be handed 2 more documents both being questionnaires. The participant would be asked to firstly fill out the virtual presence questionnaire and then the virtual embodiment questionnaires, they were also told if they had any questions regarding the questionnaires they could ask at any time. After the participant confirmed that they were happy with their responses to the questions and completed all the questions then the experimenter passed the participant a debrief sheet which gave more context to the experiment and was very explicit about the participants hand changing in size over time. The participant was asked if they had any questions regarding the experiment, if they did the researcher happily answered them, if not, then the researcher would thank the participant for their time. When all the results were collected from the 30 participants, the data was stored on a locked private computer in which only the experimenters had access to. All documents regarding the experiment were also locked in a storage cabinet which was under lock and key. The independent variable in this study was hand type (hands vs non-corporal hands) and the dependent variable in this study was the response to the questions regarding the virtual bowling scenario (question 1 and 2). Due to the nature of the dependent variables data a Chi-Square was used as nominal data was collected on 2 independent groups. Other data regarding age, gender, handedness, virtual presence scores and virtual embodiment scores were also analysed using independent t-tests.